Everything

Lecture

What is Psychology

• Commonly defined as the scientific study of mind, brain, and behaviour

• Cognitive, neuro, biological, developmental, social, organisation, evolutionary

What Defines a Science?

Features of a Science

• Science is grounded in observations

  • data is needed to confirm

• Science is cumulative

• Science is self-correcting

• Science achieves explanation and understanding

Falsification and the Logic of Scientific Discovery

• The scientific method implies incremental refinement

  • our knowledge progressively becomes a closer approximation to truth/reality

  • observation/data → explanation/theory → prediction/hypothesis

Critical Thinking

• Real scientific inference requires exercising judgement

  • How trustworthy are the data upon which influences are based? (Judgements about the quality of the data)

  • Is the theoretical explanation a general one, or is it limited to this specific instance? (Judgements about the adequacy of theory)

  • Does the experiment show the effect that the researcher thinks it does or if the effect arises for the reasons the experimenter thinks it does? (Judgements about the alternative explanations)

Judgments About Data

• Is the evidence reliable?

  • Is the measures a valid indicator of the construct?

  • Does repeating the experiment achieve the same results

Reliability and Validity

• Ideally, measures should be both reliable and valid

  • both are required for making legitimate inferences

• Reliability refers to how “repeatable” or consistent a measure is

  • if you were to asses the same construct in the same way, using the same method of measurement, do you tend to get the same results?

• Validity refers to the degree to which a measure assesses the thing it is purposed to assess

  • Is the construct you seek to measure actually related to the measurement?

Cranial Capacity and Intelligence?

• Racial Hierarchy = general consensus was that whites were on top and blacks on the bottom—but this had no supporting data

• Morton came up with measuring cranical capacity to find out the intelligence

• Bigger skull→bigger brain=more intelligent

Reliable but Not Valid

• Problem = cranial capacity does not really relate to intelligence, but it does relate to overall body size

  • Morton’s measure conflated with body size

• If the measure is not a valid reflection of the construct of interest, neither are the inferences based on the measure

Judgements about Theory

• Is the theory general?

  • A scientific explanation should apply to more than just one specific case

• Can the theory be tested?

  • Does the theory predict novel observations?

  • Are there results that would falsify the theory?

• Is the theory parsimonious?

  • A parsimonious theory provides the simplest possible explanation that suffices to explain all relevant observations

  • Principle of Ockham’s Razor

• Can we rule out alternative explanations?

  • If multiple explanations can explain the data is there a way to distinguish them?

Judgments About Alternative Explanations

• Correlation vs Causation

  • Because two variables are related to each other does not mean that one causes the other

Measurement & Uncertainty

Uncertainty and Quantitative Measurement

• Allows us to put a numerical value on a measurement

  • Quantifies our uncertainty

  • Permits objective measurement by others

• Most importantly, Quantitative Measurement allows for comparisons

  • Of groups of individuals

  • Of the same individual through time

Samples and Populations

• In most cases, we measure something about a sample of people and seek to form generalised conclusions in the population at large

  • What is true of the sample/population need not be true of the individual

  • What is true of the sample need not be trust of another sample (even if both are drawn from the same population)

  • For example, a study using the big five personality test with 2000 women and 2000 men found that women scored much higher than men in their agreeableness. From these samples it was inferred that women are generally more agreeable than men. This does not mean that all 2000 women were more agreeable than all 2000 men, or that a repeated study of 4000 different people from the same city would demonstrate the same results. However, there were clearly individual women that were more agreeable (according to the test) than individual men in order to get this result. Furthermore, what is true of the sample (women are more agreeable than men), is not true of all women in the area where the sample was taken. However there are obviously individual women who are more agreeable than individual men in the general population area.

Uncertainty and Replication

• Testing the efficacy of a treatment for depression

  • Can compare a control group (standard treatment) with a new treatment group.

  • Then, assess post-treatment depression score—is the new treatment effective? (Lower post-depression in new treatment to standard treatment)

Implications: Inference is Uncertain

• Sometimes a study will produce evidence for an effect when there is no true effect to be found

  • false positive rate (5%)

• Sometimes a study will fail to produce evidence for an effect even though there is a true effect to find

Online Content — uq-extend

The Scientific Method

• Science is defined as any discipline that makes use of the so-called scientific method.

• This is an approach to understanding the world through cycles of developing and testing theories.

• Psychology is a scientific discipline through its reliance on the scientific method for refining our understanding of mind, brain, and behaviour.

• The scientific method is the iterative means by which scientific knowledge is amassed tested and refined.

• It describes the relationship between three components:

  • Observations/data

    • data are facts about the world; they are phenomena that a scientific discipline seeks to explain

  • Explanations or theories

    • theories are statements that seek to organise data coherently

    • the structure of theories tends to be shaped by data

    • a theory explains how different observations relate to one another and, more importantly, explains why the facts are the way that they are

  • Predictions or hypotheses

    • logical implications that follow from a theory

    • predictive statements that can be shown to be consistent or inconsistent with future observations

• Theories must have two properties to be considered scientific:

  • Testable predictions — does the theory generate hypotheses that can be evaluated against data?

  • Falsifiability — the predictions must allow for the theory to be shown to be false. That is, the theory must be able to make a prediction that can, in principle, be shown to be incorrect.

• Refining scientific knowledge

  • If a theoretical prediction is confirmed by the observation, then the theory is provisionally accepted, and another hypotheses is tested

  • A theory successfully predicting something does not confirm the theory. Rather, a theory that successfully predicts data is simply one that can be kept and tested again

  • If a theory generates predictions that are shown to be inconsistent with subsequent observations, then the theory can be considered to be falsified.

    • If it is falsified, the theory can then be adjusted by refining its assumptions and seeing if revisions of the theory can bring it in accord with the data, or, the theory can be rejected outright and abandoned in favour for some other alternative thory

Lecture

The Behavioural Paradigm

• Root metaphor of the blank slate

  • out behaviours are wholly determined by our environment

• Key concepts of History of Reinforcement and Learning

  • law of effect—behaviours that are rewarded tend to be repeated

  • rejection of unobservable processes as unscientific

• Questions about how contingencies pairing stimuli with reward/punishment affect subsequent behaviour

The Cognitive Paradigm

• Root metaphor of computer

  • inputs are processes and transformed into outputs

• Key concepts of mental representations and mental states

  • focus on unobservable mental processes and their (observable) effets

  • attention, memory and decision-making

• Questions about the mental processes that give rise to behaviour

  • studied experimentally, often with human participants

The Biological Paradigm

• Root metaphor of the biological machine

  • What are the physical bases of thought and behaviour?

• Key concepts of evolution, genetics, and physiological functions

  • Focus on identifying physiological correlates of specific behaviours/cognition

  • Measurements of brain activity and identification of genetic contributions to behaviours or psychological disorders

• Questions about how mental processes are physically realised in the brain and how such functionality evolved

  • studied experimentally (humans and animals) as well as via case studies

Research Methodologies in Psychology

Research and Confirmation Bias

• People often seek out information that confirms their beliefs

  • Occurrence of expected or favoured events are highlighted

  • Occurrence of unexpected or unfavourable events are minimised

Benefits of Research Methodologies

• Impose control or structure over the observations we make

• The more structure there is, the more confident we can be about the causal status between events

• A variety of methods are often used to provide converging evidence for a theory

Experimental Designs

• Specifically set up to support causal inference

• Manipulate an independent variable while measuring the effect on another dependent variable

  • the different ‘levels’ of the IV create different experimental conditions

  • All other factors are held constant across conditions by either being allowed to vary randomly or by being deliberately equated

  • If the DV changes significantly across conditions, we may infer that the change was caused by manipulation of the IV

  • Example = the dependent variable is response time and independent variable is the level of rest

Sources of Bias in Research

What is Bias and Where Does it Come From?

• Bias refers to factors that affect the data that are obtained in a study

  • Can have follow-on effects on conclusions and theoretical inferences

  • If bias is not detected, conclusions/inferences can be compromised

Sampling Bias

• When the study sample is not representative of the population to which you wish to generalise the study conclusions to

Expectations Effects

• single-blind research can restrict participant knowledge of study aims

• double-blind research can restrict experimenter knowledge of participant groups

• Bias from participant expectations

  • placebo effects

  • hawthorne effect

  • stereotype threat

  • demand effects

• Bias from experimenter expectations

  • rosenthal effects (pygmalion/golem)

Operational Definitions

• Defining variables in terms of the ‘operations’ (methods) used to observe/measure/manipulate them

  • differences in response time are identified with the amount of conflict information that is being processed

• Operational definitions are not all equally valid

  • some measures are more clearly linked to theoretical concepts than others

UQ Extend

Paradigms in Psychology

• Paradigm = a typical example or pattern of something; distinct set of concepts or thought patterns, including theories, research methods, postulates, and standards for what constitute legitimate contributions to a field; a framework for understanding and investigation phenomena within a discipline

• They determine what standard standard operation—or normal scientific activities—within a discipline looks like

• Paradigms define

  • concepts that are used in theories

  • research questions that are addressed by a discipline

  • methodologies used to investigate these questions

• Paradigms offer perspective on how phenomena are understood and the means by which once can achieve an understanding of phenomena

  • Similar concepts include ideologies (liberalism, etc) and world views (atheistic or theistic world view) as they will affect and change your opinions on matters

• There are five major paradigms in the history of psychology

  • clinical practice

    • psychodynamic

    • humanist

  • experimental psychology (adheres to scientific method)

    • behaviourist

    • cognitive

    • biological

Behaviourist Paradigms

• Arose partly due to the rejection of Freud’s psychodynamic theories

• Behaviourist psychologists encouraged people to consider how the external environment shapes our thoughts and behaviours

• Humans, and other animals, can be viewed as blank states whose psychology is determined wholly by the external environment

  • “product of one’s environment”

Methodological Behaviourism

• John B. Watson, early 1900s

• According to Watson, a proper scientific psychology must focus on publicly observable phenomena, such as overt behaviours

• Shifted study to relationships between publicly and observable stimuli and their behavioural consequences

Radical Behaviourism

• BF Skinner

• Skinner suggests that internal events, such as thoughts and feelings, could be understood according to the same learning principles that can explain publicly observable behaviours

• Although, the external environment was still viewed as the determinant of both observable and unobservable behaviours

• Rejects the idea that mind and mental events play any causal roles in human psychology—they are ultimately caused by external factors

Cognitive Paradigm

• Moved away from Behaviourism in the 1950s

• Places mental events at the centre of psychological research

• Regarded as the current dominant paradigm in psychology

• The key assertions that mental events can be studied scientifically and that they play a causal role in determining behaviour

• Seeks to understand the processes that “transform” stimuli into behaviours

• Most of the research conducted in this paradigm concern itself with identifying cognitive processes that are required to relate changes in stimuli with changes in behaviour

• Determining how unobservable processes interact is inherently a difficult task, and so a lot of contemporary work makes use of sophisticated mathematical models that attempt to quantitatively describe how different cognitive processes interact

Biological Paradigm

• Does not focus exclusively on abstract functional relationships between cognitive processes

• Seeks to explain cognition and behaviour in terms of biological processes

• Synergistic with work within cognitive and behaviourist paradigms

• fMRI and EEGs allow research to identify neural correlates of cognition and behaviour

• Research in the biological paradigm is often more interested in the biological mechanisms that implement or enable cognition, and identifying patterns of neural activity that are associated with specific cognitive activities

• Can appear more descriptive than explanatory

The Brain

• ~2% of body weight

• receives ~20% of blood pumped from the heart

• consumes ~20% of body’s energy

• 100 billion neurons

• 1,000,000 billion synapses

• 10^1,000,000 possible circuits

Major Parts of the Brain

• Cerebrum

  • cerebral hemispheres forebrain

  • two hemispheres, divided by longitudinal fissures or inter-hemispheric fissure

  • Cerebral cortex is the outermost surface layer of the cerebrum

• Cortext = grey matter

  • surface of the brain 2-4mm thick

  • contains the cells bodies of the brain’s neurons

  • highly folded to maximise surface area (amount of cortex that can fit inside skulls)

  • white matter underneath the grey matter is all the wiring (axons of the neurons, connecting to the spinal cord and to other areas of the cortex

• Cerebellum = hind brain

• Brain stem

Frontal Lobe

• Executive functions

  • reasoning, planning, problem solving

  • inhibitory control

  • working memory

• Motor functions

  • premotor cortex — motor planning

  • primary motor cortex — execution

• speech production (broca’s area)

Parietal Lobe

• Primary somatosensory cortex

  • perception of touch

• Sense of space and locations

  • gives sense of stable world around us relative to our position

• Spatial Attention

  • directing attention and eye-movements to explore visual world

• Linking vision to action

  • represents spatial location of objects around us for guiding actions

Occipital Lobe

• Posterior part of the brain, inferior to parietal lobe

• Primary visual cortex

  • all visual perceptions

• Higher visual areas

  • different regions process shapes, colours, orientation, motion

Temporal Lobe

• Primary auditory cortex

  • perception of sound

• Language comprehension (wernicke’s area)

Limbic System, Medial Temporal Lobe

• Amygdala

  • fear and arousal, responds to threat/danger

  • fear & learning phobias

• Hippocampus

  • learning and memory, forming new episodic memories

  • damage causes anterograde amnesia (can’t form new memories)

Corpus Callosum

• Neuron Connections between the left and right hemispheres

• Allows brain communication between hemispheres

• Split-brain patients—left & right hemispheres disconnected. The two hemispheres cannot communicate with each other

Phineas Gage

• Railway worker

• A iron rod, 1m in length, went through his head in 1848, yet he remained conscious during and after accident

• Damaged frontal lobes

• Died 12 years later

• Suffered a profound change in personality — fitful, irreverent, indulging in profanity, no restraint

Broca’s Area — Speech Production

• In 1861, Paul Broca described a patient who was unable to speak after damage to the left frontal lobe (Broca’s area)

Broca’s Aphasia

• Speech is slow and non-fluent

• Difficulty finding appropriate words (anomia)

• speech still carries meaning

• comprehension is (mostly) unaffected

Wernicke’s Area — Language Comprehension

• In 1874, Carl Wernickle suggested that lessions to the left posterior temporal lobe led to deficits in language comprehension

Wernicke’s Aphasia

• Unable to understand language — deficit in comprehension

• Speech is fluent with normal prosody (rhythm, intonation)

• Speech has no meaning, nonsense speech

Wilder Penfield

• Stimulated the brain with electrical probes while the patients were conscious, during surgery for epilepsy

• Published maps of motor and sensory cortices of the human brain

Homunculus

• Primary sensory cortex and primary motor cortex

• Brain function mapped by electrical stimulation

• Brain stimulation leads to sensation or movement (muscle twitch)

• Size of area on cortex determines sensitivity or fine motor control

Autonomic Nervous System

• Central Nervous System = brain and spinal cord

• Peripheral Nervous System

  • Somatic nervous system = voluntary, motor, and sensory

• Autonomic Nervous System

  • Involuntary

  • Heart-rate, respiration, sweating

  • Stress, arousal, fight-or-flight

• 2 divisions

  • Sympathetic Nervous System

    • emotional arousal, stress, fear

    • fight or flight response

    • increases heart-rate, respiration, perspiration, pupils dilate

  • Parasympathetic Nervous System

    • Rest and digest

    • lowers heart rate, respiration

    • Increases stomach, intestine activity (digestion)

    • opposes the sympathetic nervous system

Brainstem

Medulla

• Autonomic nervous system functions

• Controls heart rate, respiration, regulation of blood pressure, body temperature

• Reflex centres for coughing, sneezing, swallowing, vomiting

Disorders of Consciousness

Persistent Vegetative State

• Severe damage to upper brain (hemispheres and cortex)

• If brainstem is not damaged, autonomic nervous system functions can remain

• Sometimes normal respiration, control of heart rate, some face and eye movements remain

• Patients have NO conscious awareness

“Locked-in” Syndrome

• Amyotrophic Lateral Sclerosis (ALS) or Motor Neuron Disease

  • loss of motor neurons to spinal cord

• or brain injury (following accident)

• Intact cerebrum and brainstem, but ‘disconnected’ from spinal cord

• Normal cognitive function, vision, and hearing, but patients cannot move

• May be fully conscious and aware, but totally unresponsive

Cerebellum

• Hind brain

• Sense of balance and co-ordination of complex movement

• Motor learning — fine adjustment of movement based on feedbacl

Primary Motor and Sensory Areas

• Primary motor cortex activity leads to movement (muscle contraction)

• Primary sensory cortex activity leads to sensation

• Different parts of motor and sensory cortex map to different parts of the body (homunculus)

“Motor Programs” for movement

• Movements planned and ‘programmed’ in the brain before initiation, like a computer program (theory from 1960s)

• Brain creates program just before movement OR retrieves program for learnt skilled actions

Sense of Agency

• Brain automatically links sensory events and own actions to infer causality

• Sense that my action caused that event

The Neuron

Cell Body

• Common to all cells

• Contains nucleus and all structures necessary for cell functioning (DNA)

Dendrites

• Unique to neurons

• Receives signals — input zone

• Many per neuron, receives input from many other neurons

Axon

• Unique to neurons

• Sends signals — output from axon hillock at cell body to axon terminals

• One per neuron — only one axon for output

• Wrapped in myelin for efficient transmission of signals along the axon

Axon Terminals

• Terminal boutons/buttons

• Form synapses with other neurons

• Secret neurotransmitters to send signals across synapses to other neurons

Glial Cells

• Brain contains neurons and Glial Cells

• Supporting cells for neurons

Oligodendrocytes

• Produces the myelin sheath that wraps around axons

Astrocytes

• Supplies nutrients from blood to the neurons

• Maintains blood-brain barrier

Microglia

• Brains immune system

• Cleans up foreign or toxic substances

The myelin of axons

• Oligodendrocytes form myelin sheath by wrapping around the axon

• Essential for efficient communication, for propagation of signals along axon

• Multiple Sclerosis involves loss of myelin, disruption of efficient neural communication throughout the body

Synapses

• Join axon terminals of one neuron to dendrites of another neuron for transmission of signals between neurons

• Neural signals go one-way

  • pre-synaptic = from cell body to axon terminal

  • post-synaptic = from dendrite to cell body

Neurotransmitter

• Chemical ‘messenger’

• released from pre-synaptic terminal

• acts of post-synaptic receptors

Neurotransmitter Release

• Depolarisation of axon terminal (action potential) triggers release of neurotransmitter

• Neurotransmitter acts on receptor on post-synaptic neuron to open ion channels and pass signals

  • chemical signal neuron-to-neuron

Synaptic Vesicles

• Stores neurotransmitter in synaptic terminal

• Joins cell membrane wall to release neurotransmitter into synaptic cleft

• recycled: neurotransmitter taken back into pre-synaptic terminal is re-packaged into vesicles

Neurotransmitter Receptors

• Gates on post-synaptic side (neuron dendrite)

• Neurotransmitter in syanptic cleft joins with receptor

• Activates receptor to open ion channels on post-synaptic neuron

  • Transmits signal by opening ion channels and changing membrane potential on synaptic neuron

• Lock and key — each receptor only binds to a specific type of neurotransmitter

  • only activate their specific type of receptor

  • important for drug effects—drugs can act on specific receptors to cause specific effects

Re-uptake Pump

• Clears neurotransmitter from synaptic cleft back into pre-synaptic terminal

Enzymes

• Break down neurotransmitter in synaptic cleft

Both stop neurotransmitter signalling to post-synaptic neuron — closes ion channels (when neurotransmitter is gone) and turns off the signal

Dopamine — Parkinson’s Disease

• loss of dopamine in the basal ganglia deep in the brain

• primarily affects movement

• treatment with l-dope replaces dopamine in the brain

Anti-Depressant Drugs — Serotonin

• Act to keep serotonin in the synaptic cleft for longer which increases serotonin signalling

SSRIs

• Selective serotonin re-uptake inhibitors (prozac, zoloft, lexapro, lovan, cipramil)

MAOIs

• Monoamine oxidase inhibitors (Nardil, parnate)

Neurons — Electrical Signals

• Action potential

• Electrical signal pulse travels along the axon

• Fixed size — either on or off, signal or no signal

Cell Membrane Wall

• 70% of the brain is water

• Water surrounds the cells — extra-cellular fluid

• Water fills the cells — intra-cellular fluid

• Cell membrane forms barrier between extra-cellular and intra-cellular fluid

Ions and Electrical Potential across Cell Membrane

• Sodium (Na+) and Potassium (K+) positively charged ions

• Different concentrations outside and inside cell, across cell membrane

• Gives difference in electrical charge (potential) across cell membrane

Membrane Potential — Resting Potential

• Membrane Potential Definition = difference in the eletrical charge (voltage) between inside and outside cell, across cell membrane wall

• Resting Potential Definition = at rest (not during action potential) more positive ions outside than inside the cell gives overall negative potential (voltage) inside compared with outside the cell

Ion channels in Cell Membrane

• Ion channels in cell membrane wall open and close to pass or block movement of ions across cell membrane

  • Ions move between intra- and extra-cellular fluid

  • movement of ions changes electrical potential

• Important types

Ion channel 1: Sodium Potassium Pump

• Actively pumps Na+ and K+ across cell membrane

• Overall pumps positive charge out of cell (3 Na+ out for every 2 K+ in)

  • Positive change will naturally move towards negative area (opposites attract)

• Maintains negative resting membrane potential (approximately -70mV)

• Uses energy — about 25% of body total energy (70% of brain energy)

Action Potential

• Transmissions of electrical signal along axon

• Input from other neurons (via synapses on dendrites) increase membrane potential

• If voltage exceeds threshold, triggers action potential

• Depolarisation of cell: membrane potential goes back to zero

  • occurs in less than 0.002 seconds

• Repolarisation: membrane potential back to -70mV resting potential

  • refractory period — more difficult for another action potential to occur

  • further to threshold to trigger another action potential

• Fixed Size and All-or-None principle:

  • If threshold level is reached, action potential of a fixed sized will occur. The size of the action potential is always the same for that neuron.

  • All-or-None: Either a full action potential is “fired” (if membrane potential reaches threshold) or there is no action potential. There are no “large” or “small” action potentials.

  • The strength of the neuron signal is determined by the rate of repeated action potentials

• Conduction along axon

  • Starts at axon hillock: membrane at axon hillock has lowest threshold to trigger action potential

  • Depolarisation spreads from site of action potential to neighbouring region of cell membrane: causes neighbouring region to pass threshold to trigger action potential

  • Repolarisation and undershoot (refractory period) prevents action potential going backwards

Ion Channel 2: Voltage-dependent ion channels

• Voltage dependent ion channel, closed at resting potential

• Open when membrane potential reaches threshold voltage

• Allows flow of ions across cell membrane

  • positive ions can flow from outside into the cel (because positive charge will naturally move towards negative area)

• Causes depolarisation of cell (voltage less negative = closer to zero)

Voltage-dependent ion channels: Na+ and K+

• Different channels open and close at different membrane potentials (voltage dependent)

• Depolarisation: Na+ channels open when voltage exceeds threshold

  • Na+ flows into cell

  • Less negative potential

• Repolarisation: Na+ channels close and K+ channels open after depolarisation

  • K+ flows out of cell

  • plus Na/K pump

  • more negative potential

Ligand-Gated Ion Channels

• Neurotransmitter receptors open ion channels when neurotransmitter binds

• Different neurotransmitters bind to and open different ion channels (Na+, K+, Cl-) to change membrane potential in different ways

• Receptor binding

  • Can cause depolarisation (less negative)

  • Can cause hyperpolarisation (more negative)

EPSPs and IPSPs

• Receptor Channels — activated by neurotransmitters

Excitatory

• Receptor open channels that cause depolarisation

• ESPS = excitatory post synaptic potential

Inhibitory

• Receptor opens channels that cause hyperpolarisation

• IPSP = inhibitory post-synaptic potential

• further from threshold for action potential

Graded Potentials

• Excitatory and Inhibitory inputs (via dendrites) combine together

  • changes membrane potential on postsynaptic cell

• Graded Potential on postsynaptic cell depends on strength of synapse connection (on dendrite)

  • strong connection causes large change in membrane potential

  • weak connection causes small change

When do Inputs trigger an Action Potential?

• Membrane potential at axon hillock depends on sum and timing of inputs through dendrites

• If enough excitatory inputs occur together close enough in time, membrane potential will exceed threshold level for action potential

• if membrane potential exceeds threshold level (at axon hillock)

  • triggers action potential, neuron sends signals along its axon

Integration of Signals

• Neuron receives many, many inputs — has only one output

  • what combination of inputs will cause this neuron to fire and pass on it’s signal

• Brain is enormous integrator of information — adapts with learning (billions of neurons with millions of billions of connections)

Integration of Information in the Brain

• Imagine this neuron represents memory of your grandmother.

• When this neuron fires, you consciously recall your grandmother

Brain Measurement

• Single neuronrecording done almost entirely in animals.

• Our main techniques nowadays in humans measuring brain activities with techniques of EEG and MRI.

Early Studies

• Led to basically all of our knowledge of function in different parts of the brain up until around the 1950s.

• All came from studies of patients with brain lesions, in particular damage lesions to parts of the brain.

Brain lesions

• Explain normal brain function = by examining what changes in behaviour or cognition when part of the brain is damaged.

• Often examined patients following stroke = strikes caused by blockage of blood supply to part of the brain. That part of the brain doesn't receive oxygen can leave a permanent lesion or damage to that part of the brain or in people following brain injury.

• the assumption here is that whatever it is that changes in behaviour or cognition must rely on that part of the brain that's damaged.

• When that part of the brain's damaged, a particular behaviour function is lost.

Single Neuron Recording

• Most accurate for localisation and timing of brain activity, measuring brain activity of the brain, is with single neuron recording.

• Using an electrode implant or positioned directly into the brain to measure action potentials firing from individual neurons.

• This is done almost exclusively in animals, often in rats or cats.

  • Although there are more and more studies appearing nowadays using this technique in human volunteers during brain surgery.

• determines what it is that that individual neuron is encoding or detecting when it sends its signal off down its axon, communicating to the rest of the brain.

• The only signal a neuron can send out is an "all or nothing" fixed size action potential.

• what is it that causes that neuron to fire? what kind of stimulus or action or thought or memory does firing of that neurons represent? What's its signalling out to the rest of the brain?

• it's highly invasive.

Visual Cortex

• been studied extensively in vision (visual cortex).

• vision works by saying what it is that individual neurons encode as they pass their information from very early areas to later areas in the brain, encoding more complex features.

• Across those neurons is encoded the whole representation of our visual space.

• Hubel and Wiesel. their work through the 1950s and '60s.

Motor System

• Reading out from firing of the motor cortex on this homunculus to try to decode plans, intentions for movement, feed into a computer that can then control a robot. And this is maybe a way of developing neuro prosthetics, prosthetic arms, that patients can control directly from their brain activity.

Brain Measurement: EEG and MRI

EEG

• electroencephalography,

• Measures the summed activity from action potentials from the many, many thousands of neurons in the cortex. Basically underneath the locations of electrode sensors that are placed on the scope.

• Fit a cap to the person's head with maybe 64 electrodes senses and we're measuring the summed electrical activity coming from action potentials around the area underneath each electrode sensor.

• This oscillatory activity of the brain that we measure (the brain waves) is actually the best technique that we have for assessing a person's level of, say, sleep, alertness, and arousal.

• The waveforms, the frequency of the oscillations, we see an EEG vary characteristic ways depending on a person's level of alertness or sleep.

• Alpha activity.

  • There's oscillations in activity, these waves of about eight to 12 hertz. So 8-12 peaks, wave, waves per second we call alpha activity.

  • And it's really considered that kind of idling activity of the brain.

  • And these alpha ways become extremely large when people are relaxed and sleepy, particularly when they close their eyes.

  • And the alpha waves gets suppressed when a person's eyes open, alert, particularly engaged in sort of highly demanding cognitive tasks.

  • So it gives us a measure overall of the person's alertness and cognitive load.

• Because EEG is also used clinically for monitoring patients with epilepsy, suspected epileptic seizures, will wear the electrode cap over a long period and doctors will be looking for signs of abnormal spiking electrical activity representing seizure activity in the brain.

• In our research EEG, we're typically interested in something else called event related potentials. We do that by presenting a particular stimulus. And then taking short windows or epochs of the EEG activity following that stimulus. And usually will average together many, many trials in response to that stimulus. And what we'll see is different peaks of activity that always occur at the same time point following presentation of that stimulus. So they really represent different stages of information processing in the brain as neurons fire their signal and passing from one level to another level in the brain, there's a whole series of information processing steps.

EEG and Event-Related Potentials

• Activity of neurons in the brain actually generates small electrical currents that we can detect and measure on the surface of the head by electroencephalography, or EEG.

• This is a common technique used for measuring brain activity as it changes over time in tasks associated with our perception, cognition, decision-making, and planning actions.

• The participant is seated comfortably in front of a computer monitor and keyboard so that they can perform computerized tasks while we measure their brain activity during the task.

• The EEG brain activity is measured from electrode sensors that are fitted in an elastic cap on the participant’s head. In this case, the cap contains sixty-four EEG sensors that fit across the person’s entire scalp.

• The electrode sensors need to connect with the skin to detect the very small electrical currents that come from brain activity, and so a conductive electrolyte gel is used for each electrode sensor. The electrode sensors are then fitted into the cap and connect with the scalp via the electrolyte gel.

• The small electrical signal changes, representing brain activity, that are picked up by the EEG sensors, are monitored in real time. Each line or trace on the screen represents the activity recorded by a single electrode sensor.

• Each individual trace shows the sum of the electrical activity of hundreds of thousands of neurons within the region underneath the location of each sensor.

• What we see as these rhythmic oscillations of brain activity, or brain-waves, are quite difficult to interpret here and represent the fluctuating activity of the brain going on over time. We do see some changes in the frequency or rate of these oscillation waves with different levels of alertness or arousal, or with increasing cognitive load, but generally in our experiments we are more interested in changes in brain activity that underlie a particular behavioural or cognitive task.

• So, once the EEG has started recording, the participant will complete an experiment task and we will record brain activity associated with that task.

• In this experiment, the participant is watching a field of moving dots while listening tosimple auditory tones being played. After a delay, the dots begin gradually moving in the same direction, and the participant has to indicate which direction as soon as they can perceive it. What we are actually measuring, though, is the brain activity in response to the auditory tones that the participant is not attending to. We actually see from the EEG activity, that the brain is still tracking and anticipating presentation of the tones automatically, even when the participants are not aware of them and their entire focus is on the moving dots. We can see this in EEG by looking specifically at the brain activity around the time that each auditory tone is presented. The time of each tone is tagged in the EEG recording for later offline analysis.

• To get a clear measure of the changing brain activity in response to the auditory tone, we need to record many instances of activity around the time of the tone – usually with over one hundred trials that we then average together.

• Once we have collected all of the EEG data in the lab, we then analyse offline by computer. We cut out the segments of the EEG data, called epochs, around every instance when a tone was presented. These epochs are all precisely aligned in time to the exact moment when a tone occurred and, by averaging the epochs together, we can see the precise changes in brain activity over time associated with the brain’s processing of the auditory tone.

• These are called “Event Related Potentials” – showing the brain activity related to a particular event.

• The event related potentials show us different stages of information processing in the brain, from the earliest stages of sensory perception to later and higher-order stages of cognitive and decision-making processes.

• In this case, we can see a series of peaks that represent these different stages of information processing in the brain.

• The line at time zero here shows the onset of the auditory tone, and the first peaks here occur around 100 ms following the tone onset and represent early stages of sensory processing in the auditory cortex. Later components, such as the large positive wave around 300 ms after the tone reflect higher-order cognitive processing, such evaluating the tone for relevance or comparing or storing in working memory.

• We can see the level of activity over the entire head at each time point, known as a topography map. This map gives us an idea of which areas of the brain were most active over different stages of processing of the auditory tone. This is the limitation of EEG and event-related potentials – while we can see broadly where activity was greatest in the brain over different stages of information processing, it is very difficult to localise precisely where in the brain those processes are occurring.

• So Event-Related Potentials, recorded from EEG, give us a very powerful technique to examine the timing of stimulus or information processing in the brain. We can then track the different brain processes that occur through stages of sensory perception, stimulus evaluation, decision-making, and selecting appropriate responses.

Face Procession - N170

• studies will often look at particular stages or processes that we think occur in the brain for particular kinds of stimuli.

• One well-known peak and component of information processing is for faces.

• That in part of the visual system, there seems to be an area that's quite specialised for our ability to process, to recognise people's identity from their faces, the face processing.

• And in EEG, we see a large negative peak at about 170 milliseconds after faces presented. And it's something quite specific to faces and represents this activity in this area that's for face recognition.

Event-related potentials

• very good for showing us the precise time of information processing in the brain.

• They do provide us a direct measure of electrical activity does come from neuronal firing. Not individual neurons but summed activity from many, many neurons.

• And the main problem with event-related potentials though, is it's difficult to accurately localise exactly where in the brain that activity is coming from.

• So we say that have relatively poor spatial resolution. That is, we measure activity across the whole surface of the scalp. And we get these maps that can show broadly where on the head the activity's coming from.

• But it's hard to map that exactly to a precise location in the brain. So for localisation of brain activity, we turn to functional brain imaging methods.

Function Brain Imaging

• Techniques started in the 1980s with a technical PET, Positron Emission Tomography, that involved injecting radioactive labeled water, often water or glucose, into the bloodstream and map the location of the blood flow through the brain via this radioactive label.

• Nowadays, these techniques are still used and particular chemicals are made to attach sort of radioactive labels to particular neurotransmitters and so we can actually plot out density concentration of neurotransmitters of receptors in the brain.

• For just straight brain activations, in what parts of the brain are active with particular tasks, now we use exclusively functional MRI measuring, still measuring changes in blood flow, but related to changes in blood oxygen level.

• Anyone who's gone to an MRI scanner clinically will often have done that, to have these beautiful pictures of body's anatomy.

• The little 'f' in front for fMRI, functional MRI uses the same machine, but quite a different technique. And all it gives us is a statistical map of where there's a change in blood oxygen level in the brain with a particular task.

• As a statistical map we make into colours and we just put it on top of the beautiful anatomical picture of the brain. But the fMRI is just these coloured activation spots, show statistically where there's a change in activation with a particular task.

• Functional MRI is actually detecting changes in blood oxygen level. And it's important we know neurons, when they become more active, they consume a lot of energy and they need oxygen, oxygen for energy. And so active neurons are using oxygen.

• When we see an increase in brain activity, we actually see an increase in blood flow and more oxygen delivered to that area. And that gives us our increase in fMRI signal.

• There's much research on fMRI localising function to particular parts of the brain. But that's basically how the technique works.

• Really excellent for our ability to localise where and where in the brain activity changes with a particular task. The problems are, well, it's a relatively indirect = a bit slow and delayed relative to the electrical activity of the neurons themselves.

• It is also a very expensive technique.

Brain Imaging with MRI

• Functional MRI allows us to localise activity associated with different functions, such as different aspects of attention, cognition, decision-making, or emotion, to specific parts of the brain.

• The MRI scanner uses a very strong super-conducting magnet that is always on. It’s extremely important that people do not have any metal on them or inside their body when they go into the scanner. All participants go through a short interview screening procedure first to make sure it is safe for them to go into the scanner.

• For the MRI scan, the participant lies on the scanner bed that then goes inside the large outer magnet. The MRI scanner makes a lot of noise during scans and so the participant wears headphones, which allow us to communicate with the participant while they are in the scanner.

• The participant lies down with their head in a head coil, which is what captures the images of their brain. They also use a button-response pad which they hold inside the scanner, and so they can respond to tasks in the scanner by pressing buttons on the response pad.

• Then rest of the head coil is fitted. There is a mirror on the top of the head coil, in front of the participants’ eyes, and they can watch a computer display screen that is outside the tunnel of the magnet through this mirror on the head coil.

• So, for the scan, the person is lying on their back inside the coil of the magnet, they are viewing stimuli on screen via the mirror on the head coil, wearing headphones for the noise, and responding to tasks by pressing buttons on the response-pad by their side.

• For functional MRI, now we add a task for the participant to perform inside the scanner, so that we can measure their brain activity to investigate brain function associated with the task.

• With functional MRI, we actually measure changes in the oxygen level in blood that happen as brain activity increases. As neurons in the brain increase in activity, firing more rapidly, they consume more energy. Energy in the brain is from glucose and oxygen, which are carried in the blood, so areas of the brain with increased activity actually receive an increased supply of oxygenated blood.

• It is this increase in blood oxygen level to active areas of the brain that we measure with fMRI.

• Once we have collected all this image data, we analyse later by examining and quantifying the level of MRI signal change, representing increased blood oxygen level, or brain activity, in different regions of the brain.

• Nowadays, we can do functional MRI scans with far higher resolution and have very precise localisation of activity within specific regions of the brain, even down to the level of specific layers within the cortex.

• We also have far more sophisticated computational techniques, including machine learning methods, that allow us to start to make inferences about the type of information that is encoded in activity that we see in the brain.

Brain plasticity and connections

• Brain plasticity really is how the brain changes with experience and learning.

• Brain plasticity or neuroplasticity, is the capability of the brain to alter its functional organisation as a result of experience.

• And the brain is constantly changing and adapting, altering through its connections, mostly, with all experience and learning throughout all of life. And this is neuroplasticity.

Connections

• the importance of these connections, we have to go back to what it is that's causing a neuron to fire and pass on its signal through integration of the many, many inputs that that neuron is receiving from many other parts of the brain through its dendrites.

• Each individual neuron having many, many inputs, many, many synapse connections from other neurons in the brain coming in through its dendrites; some excitatory, some inhibitory - all signaling different things.

• And that neuron is integrating all that information to determine will it fire its signal, whatever it's representing, and pass that signal on in the brain or not.

• So it's going to be things from sensory areas, vision, sounds, smells that all match characteristics of your grandma will all feed into this neuron with excitatory signals and push the membrane potential and this neuron higher, closer to threshold until there's enough inputs all at once that match and this neuron fires. And you think, "oh grandma!"

Neuroplasticity and Synapses

• Anything we learn or encode in memory involves physical changes in the brain. That's what we mean by neuroplasticity. That's the capacity of the brain to change its organization with experience and learning. And this happens constantly throughout all of life.

• Ramon Y Cajal, who studied the structure and growth of neurons throughout brain development, and he won the Nobel Prize for his neuron theory of the brain.

• He noted that neurons do not regenerate and was absolutely correct.

• When neurons in the brain are damaged or die, they never regrow or repair.

• The brain actually continues to change physically with learning and experience throughout all of life. In particular, we now know that neurons are born throughout all of life through stem cells that occur naturally within the brain.

• Stem cells are cells that are undifferentiated and they can become any kind of cell in the body. n the brain, stem cells differentiate into neurons in two areas:

Hippocampus

• One critical for learning and memory is the hippocampus.

• We know that the hippocampus is essential for memory because removal of the hippocampus leads to severe memory impairment.

• However, we still don't fully understand the significance of neurogenesis in the hippocampus for learning.

• This is still a very current and active area of research.

Synaptogenesis

• More important, though, the main way that we know in which the brain changes with learning is by forming and strengthening new synapse connections through processes of synaptogenesis, new synapse connections are created in the brain or existing connections are strengthened or weakened.

• One important figure in the history of neuroscience of learning is Donald Hebb. A simple observation that he made was that pet rats of exactly the same breed and genetics as laboratory rats still tended to be smarter if raised in a household environment as pets than in laboratory housing.

• There's actually a whole range of cognitive tasks that we have to test learning and memory abilities in rats, and rats raised in home environments as pets do better in those tasks than do laboratory rats. This actually spurred on a whole field and a well-used paradigm in learning in animal research known as environmental enrichment, where rats raised in enriched conditions actually show much more extensive growth of dendrites and synaptic connections throughout the brain. If the rats are raised in an enriched condition, having lots of opportunity for sensory and motor exploration and stimulation, rather than the standard laboratory housing, this actually leads to more extensive growth of the dendritic tree of cortical neurons and more extensive synapse connections through the brain.

• A really important process, is known as long term potentiation LTP and refers to a strengthening of synapse connections through a whole range of chemical and molecular processes.

• Synaptic strength changes with learning.

• Now, if we look back, considering when a neuron will fire its action potential, depending on the relative weighting or balance of incoming signals, to dendrite through synapse connections, remember, a neuron will be receiving many thousands of inputs through synapse connections, some excitatory, some inhibitory, some strong, some weak, and in the end, for this neuron, what's important is will its membrane potential exceed the threshold level required for it to fire an action potential and pass on its signal or not?

• Now, that said, some of the synapse connections coming into dendrites of this neuron, they may release neurotransmitters that are excitatory and cause a slight increase in membrane potential, an excitatory post-synaptic potential. Some of those synapse connections will release a neurotransmitter that's inhibitory and cause a slight decrease in membrane potential, an inhibitory post-synaptic potential, and those potentials will be strong or weak depending on the strength of synapse connection.

• That is neurons that share connections together in a chain and fire their action potentials from one neuron on to the next and cause the next neuron to fire, the synapse connection between those neurons will strengthen every time those neurons fire together.

• So Hebbian learning really is a process whereby the repeated firing at both pre-synaptic and post-synaptic neurons firing together strengthens that synapse connection between them, so that, in future, activation of the pre-synaptic neuron becomes more likely to cause the post-synaptic neuron to also fire, through the strengthened connection.

• So, in this way, the brain learns a lot through associations, through these repeated firings of neurons, firing together and wiring together. And that's actually the basis of much neuroplasticity and learning, that the brain pathways or connections that are used often get strengthened through this process of Hebbian learning.

Brain Reorganisation

• The primary sensory and primary motor cortices have this homunculus organisation.

• Homunculus, where the size of the area on the cortex represents the sensitivity we have in that part of the body, on the sensory side. Or the level of fine motor control we have with that part of the body on the motor side, and these are also things that are learnt and changed with experience.

Study 1

• So this is a study of people who played string instruments using their left hand, very frequently on the strings, right hand really just with a bow.

• And so through practice with an instrument they're receiving a lot of sensory input and sensory sensation through the fingers of their left hand.

• And in this study, the researchers have used a technique measuring brain activity in response to sensation on the index finger and sensation on the fifth finger, the little pinky finger. And measuring the distance representation or those fingers on the surface of the brain, on the cortex.

• And the distance between them represents basically the size of the hand area in sensory cortex for the string players left hand. And they find that that hand area is much larger in string players than non string players for the left hand and also larger for the left-hand then for their right hand, which is not having the same sensory input through the strings.

• So just that experience over a long period with sensation through the fingertips is causing a expanding of the hand area on the sensory cortex.

Study 2

• We look at what happens with brain reorganisation following damage of, following injury to the brain, a lot of recovery of function after brain damage or injury, for example, following a stroke, occurs by reorganisation of the brain.

• That is, some areas that are not damaged, taking over function from damaged areas, which again involves a reconnection, a remapping of undamaged areas now to new functions.

• So this is a study actually performed in monkeys where they've deliberately caused lesion in part of the monkeys primary motor cortex.

• So as a model of what would happen in stroke if someone has a stroke that affects their motor cortex. They'll actually develop the muscle weakness or even loss of movement on one side of their body.

• So in this study, the researchers used electrical stimulation to map out all the areas on the motor cortex that connected with the monkey's hand. They stimulate that part of the brain causes muscle contraction in the hand, the hand area on primary motor cortex for the monkeys. And then they made a small area of lesion within that hand area.

• As a result, the monkeys had some impaired movement with their hand. They had a deficit caused by damage to that hand area. And as you can see in the top, the top image, is a model where the monkeys had no rehabilitation and that is no movement.

• Basically with damage to the hand, they stopped using their hand. And with lack of use, the area of the brain representing the hand actually shrinks and gets smaller. And that's we call maladaptive plasticity.

• The lower picture shows what happened with rehabilitation. In this case, the monkeys good hand was restrained and so it was basically forced to use its impaired hand. And with use of that hand, actually the area, the cortex representing the hand started to expand, expand even beyond areas that previously were connected to control of the hand. So other areas taking over function in compensation for damaged areas. And that growth of the handy on the motor cortex associated with improved function for the monkey in its hand movement. So with use particularly rehabilitation motor training was in expanding and other areas taking I have a function from damaged areas.

Study 3

• A really dramatic case which shows you how incredible this plasticity can be with brain reorganisation is this really interesting study of blind people reading braille with FMRI.

• They actually took blind people who read Braille and sighted people and taught them how to read braille. And they found in the blind people their visual cortex actually takes over function, shows activity, with reading braille.

• Braille, of course, has little spots on the dots on the page that are read through the fingertips through sensation.

• So should involve sensory cortex, somatosensory cortex but in blind people that primary visual cortex otherwise is lacking input and there's still functional neurons there. And it appears that the brain reorganises and those areas take I have a function for reading, although through fingertips and somatosensation. And this only happened in the blind people.

Neuropsychology — Brain Lesions

• Explains normal brain function by examining what changes when part of the brain is damaged

  • Stroke or brain injury in humans

  • Induced lesions in animals (electrical/chemical)

• Assumption: Whatever changes in behaviour/cognition must rely on that part of the brain that is damaged

Single Neuron Recording

• Place a thin electrode into an animal’s brain (rat, cat, monkey)

• record action potentials “firing” from a single neuron

• Measure what that neuron encodes or detects

  • What causes it to fire?

  • What stimulus / action / thought (?) does it represent?

• Best Localisation and Timing of brain function

  • Directly measuring action potentials from individual neurons

• Problems

  • Highly invasive

    • electrodes directly into brain

  • Animals only

    • (although some studies now measure single neuron firing in humans during brain surgery)

Visual Cortex

• Hubel and Wiesel, 1959

  • First recordings from visual cortex neurons in cats

  • Nobel Prize in 1981

EEG—Electroencephalography

• Summed activity from action potentials of neurons in the cortex cause electrical activity change on the scalp (skin of the head)

• Measure voltage changes from electrodes placed on the scalp

• Waveforms vary with brain states:

  • Sleep and Alertness

• Brain activity in EEG shows constant oscillations (waves)

• Frequencies of oscillations change with alertness and sleep

• Clinical Uses:

  • Detecting stages of sleep

  • Monitoring for Epileptic seizures

ERPs—Event-related potentials

• Brain activity related to a specific event or stimulus

• Average together >100 trials of EEG in response to the stimulus

• Peaks represents different stages of processing of the stimulus

• Example:

  • Auditory Event-Related Potentials

    • Activity over time in different parts of the brain auditory pathway for processing sounds

  • Clinical Use:

    • Detecting deafness in babies

• ERPs can show precise time of information processing in the brain

  • Direct measure of electrical activity (neuron firing) in the brain

• Problems

• Difficult to accurately localise activity to specific brain areas

  • Poor spatial resolution

  • Measures electrical potential conducted across the scalp

  • Hard to determine exactly where in the brain this activity comes from

Example—Face Processing

• ERPs can show precise time of information processing in the brain

  • 100ms Viewing any stimuli

    • peak of brain activity 100ms after seeing visual stimulus

    • Early brain processing of general visual features (brightness, colours, edges)

  • 170ms Viewing faces

    • peak of brain activity 170ms after seeing face

    • brain processing for face recognition in visual cortex

Functional Brain Imaging

• PET: Positron Emission Tomography

  • 1980 to late 90’s

  • Uses radioactive substances injected into bloodstream

  • Used now to map neurotransmitters or receptors (radioactively labelled “tracers”) in the brain

• fMRI: Functional Magnetic Resonance Imaging

  • 1992 to current

  • Measures change in blood oxygen level

MRI versus fMRI

• MRI studies brain anatomy.

• Functional MRI (fMRI) studies brain function.

fMRI

• fMRI measures changes in blood oxygen level that accompany changes in brain activity

• Good localisation of brain activity

• Problems

  • Indirect measure of brain activity

    • BOLD signal from change in blood oxygen level

    • Not precise timing of neural activity

  • very expensive !!

fMRI — Change in Blood Oxygen

• Functional MRI detects change in Blood Oxygen Level (BOLD signal)

• Active neurons use Oxygen

• Oxygen is carried in blood – delivered to active neurons

• Change in Blood Oxygen Level = Change in Brain Activity

• Increased Brain Activity → increased Blood Flow (more oxygen delivered) → Increased fMRI signal

First Ever (1992)

• Participants viewed checkerboard

  • Off for 60s

  • Flashing for 60s

  • Off for 60s

  • Flashing for 60s

  • Increased BOLD signal (increased blood flow = increased brain activity) in visual cortex when flashing

Brain Measurement is NOT mind-reading

• Cannot infer what people are thinking or doing or feeling based on measurement of their brain activity !!!

  • Reverse Inference = bad!

• Good Experimental Design:

  • Manipulate one factor – independent variable (eg. task or behaviour) and Measure the effect on the dependent variable (eg. brain activity).

  • Cannot do reverse: Cannot look at brain activity (dependent variable) to determine what the independent variable was (i.e. task people were doing)

Brain Plasticity

• How the brain changes with learning

• Definition: The capability of the brain to alter its functional organisation as a result of experience.

• Neurogenesis and Synaptogenesis

  • Generation of new neurons and synapses (connections)

Integration of Signals — whole brain

• Neuron receives many, many inputs – has only one output

  • What combination of inputs will cause this neuron to “fire” and pass on it’s signal?

• Brain is enormous “integrator” of information – adapts with learning (billions of neurons with millions of billions of connections)

• When sum of all inputs is high enough, triggers output (cell “fires”)

Integration of Information in the Brain

• Imagine this neuron represents memory of your grandmother

• When this neuron “fires” you consciously recall your grandmother

• What information does this neuron need to receive to “fire” and give conscious recall of your grandmother?

Grandmother Cells

• “Grandmother Cells” – all theoretical

  • Neurons could “represent” (encode or “fire” to) a specific concept, such as your grandmother (Jerry Lettvin, 1969)

  • Billions of neurons can encode billions of concepts

  • Memory may be represented by groups of neurons each encoding specific concepts or objects

• “Jennifer Aniston cells” found in Hippocampus

  • Recording from neurons in hippocampus in epilepsy patients

  • Fire specifically to pictures of Jennifer Aniston

Connections

• Spreading Activation Model - Theory

  • Neurons represent a specific concept (eg. Grandmother cells)

  • Share connections with neurons that represent related concepts

  • Eg. Fire-engine èRed, Truck, Fire, Siren

  • Activation (firing) of one neuron leads to spreading activation to related or connected neurons (concepts)

• Learning and Memory

  • Making and strengthening connections between neurons that represent associated concepts

Ramon y Cajal

• Studied growth of neurons and axons during brain development

• Neurons do not regenerate

  • “In the adult centers the nerve paths are something fixed, ended and immutable. Everything must die, nothing may be regenerated. It is for the science of the future to change, if possible, this harsh decree.”

• Cajal was mostly right, but not entirely …

Neurogenesis — growing new brain cells

• Neurons never regenerate or repair: damaged brain areas never “re-grow” BUT

• New neurons constantly “born” throughout life from Neural stem cells

• Only two areas in adult brain:

  • Hippocampus (learning and memory)

  • Subventricular zone for olfactory bulb

Synapses

• Synaptogenesis

  • Definition: Generation of new synapses: brain connections

• New synapses are constantly formed and strengthened with experience and learning

Environmental Enrichment

• “Enriched” conditions lead to growth of dendrites and more extensive synaptic connections

Learning and Memory

Strengthening Synapse Connections

• Long-Term Potentiation (LTP)

  • Change in the structure of synapses to give stronger signal from pre-synaptic to post-synaptic neuron

  • Many mechanisms

    • Eg. More post-synaptic receptors

  • focus of cellular/molecular neuroscience research on memory and learning

Graded Potentials

• Excitatory and Inhibitory inputs (via dendrites) sum together

  • Change membrane potential at axon hillock

  • Graded Potentials

• Graded Potential at axon hillock depends on strength of synapse connection (on dendrite)

  • Strong stimulus causes large change in membrane potential

  • Weak stimulus causes small change

Hebb’s Law — Hebbian learning

• “Neurons that fire together wire together”

• “When an axon of cell A is near enough to excite cell B and repeatedly or persistently takes part in firing it, some growth process or metabolic change takes place in one or both cells such that A's efficiency, as one of the cells firing B, is increased.” Donald Hebb, 1949.

• Repeated firing of pre-synaptic and post-synaptic neuron “firing together” strengthens synaptic connection

• Brain “learns” associations through repeated pairings

• Strengthens connections between paired stimuli or events

• Basis of Neuroplasticity Learning:

• Brain pathways (connections) that are used often are strengthened

Homunculus

• Primary Sensory cortex and Primary Motor cortex

• Size of area on cortex determines sensitivity or fine motor control

Neuroplasticity

Brain re-organisation with experience

• Studied sensory cortex in musicians who play stringed instruments

• Measured activity for index and little finger sensation for left and right hand

• String players had larger area on primary sensory cortex for left hand fingers than non string players

• Sensory cortex finger areas expand with use and experience

Brain re-organisation after damage

• Lesioned motor cortex in monkeys and used electrical stimulation to map hand area

• With no rehabilitation: (no movement) motor cortex area for hand got smaller: maladaptive plasticity

• With rehabilitation: (movement training) motor cortex area for hand expanded and movement improved.

• After damage, motor cortex can re-organise with use to recover function.

Brain re-organisation in blind people damage

• Studied brain activity in blind people while reading Braille

• Brain activity in visual cortex while reading Braille

• Visual cortex changed only in blind participants. Sighted participants did not show visual cortex activity when reading Braille

• Brain areas lacking their normal input can take new functions with use

Left vs Right Hemisphere: Myths and Facts

• Popular myth: left hemisphere = analytical, right hemisphere = creative – no basis in reality.

• True lateralization: few functions localized to one hemisphere.

• Most brain functions require coordination of both hemispheres.

Strongly Lateralized Functions

• Language and speech: in most people, left hemisphere (Broca’s area).

• Tone of voice & prosody: more right hemisphere.

• Face perception: stronger in right hemisphere.

• Perceptual grouping: right hemisphere tends to see overall patterns.

Contralateral Functions

• Motor, sensory, and visual areas:

  • Left hemisphere → controls/feels right side of body.

  • Right hemisphere → controls/feels left side.

  • Visual fields: left side of vision → right hemisphere; right side → left hemisphere.

Hand Dominance & Language

• Most people: left hemisphere for both speech and movement.

• Right-handers: ~95% have language in left hemisphere.

• Left-handers: ~70% have language in left hemisphere, 30% in right.

• Hand dominance ≠ language dominance.

Corpus Callosum and Inter-Hemispheric Communication

• Corpus callosum: main structure allowing info transfer between hemispheres.

• Crucial for tasks that need info from both sides (e.g., naming objects seen in left visual field).

Experiments on Visual Input & Language

• Flash images to left or right visual field to control which hemisphere processes them.

• Example:

  • Sun flashed right → left hemisphere sees it, can say “sun”.

  • Sun flashed left → right hemisphere sees it, info crosses corpus callosum to left hemisphere to name it.

Split-Brain Patients

• Corpus callosum cut (to treat epilepsy) → no inter-hemispheric communication.

• Everyday life: patients function normally.

• Lab tasks reveal split functions:

  • Picture flashed to left field: right hemisphere sees it, but no speech → patient says “nothing”.

  • But can point or draw with left hand (right hemisphere control) to show what was seen.

  • Picture flashed to right field: left hemisphere sees it, patient names it easily.

Classic Findings (Sperry & Gazzaniga)

• Left hemisphere has verbal language and can describe what it sees.

• Right hemisphere can understand language (to some extent) and control left hand to draw/point to what it saw.

• No direct speech in right hemisphere.

Deep Implications

• Right hemisphere can control left hand actions but can’t verbally describe them.

• Raises questions about independent “consciousness” in each hemisphere.

Patient HM and the Role of the Hippocampus

HM’s Case (1953)

• HM had hippocampus removed bilaterally to treat epilepsy.

• Surgery stopped seizures but caused inability to form new memories (anterograde amnesia).

• HM remembered childhood and past events → hippocampus not storage site for old memories.

Key Findings from HM

• Hippocampus is essential for encoding new episodic (event-based) memories.

• Short-term memory (e.g., holding a phone number) and procedural memory (e.g., mirror drawing) were intact.

• HM could learn new motor skills (procedural learning) but not recall learning them.

Types of Memory

• Short-term memory: brief mental rehearsal.

• Long-term memory:

  • Declarative (explicit):

    • Episodic: personal experiences, events.

    • Semantic: facts, knowledge (e.g., Paris is the capital of France).

  • Procedural (implicit): motor skills (e.g., riding a bike).

• HM’s deficit: declarative long-term memory encoding.

Hippocampus & Spatial Navigation

• Contains place cells → mental maps for navigating familiar environments.

Epilepsy and Memory Impairment

Medial Temporal Lobe Epilepsy

• Seizures often originate in medial temporal lobes (near hippocampus).

• Epilepsy may damage hippocampus over time due to repeated abnormal firing (excitotoxicity).

• Shrinking (atrophy) of hippocampus linked to declining memory performance.

Surgical Treatment & Memory Risks

• When medication fails, surgical removal of seizure focus (temporal lobe) can control epilepsy.

• Surgery can risk memory loss if hippocampus is removed/damaged.

Neuropsychological Assessment Before Surgery

• Test verbal memory (left hemisphere, left hippocampus) and visual memory (right hemisphere, right hippocampus).

• If both verbal & visual memory are impaired pre-surgery, removing hippocampus risks permanent amnesia.

Wada Test (Water Test)

• Temporarily anesthetizes one hemisphere to see if the other can compensate for memory.

• If memory disappears during the test, surgery is too risky (risk of amnesia).

Post-Surgery Role of Neuropsychologists

• Assess memory function pre- and post-surgery.

• Follow-up at 3, 6, 12, 24 months.

• Offer rehabilitation and strategies to cope with memory deficits.

• Important to ensure seizure control to prevent further cognitive decline.

Key Message

• Hippocampus critical for encoding new declarative memories.

• Repeated seizures → hippocampal damage → progressive memory loss.

• Timely epilepsy treatment is essential to protect memory

Lateralisation of Brain Function

• Lateralised functions

  • Some brain functions rely more on one-side of the brain than the other

• Left hemisphere

  • language and speech

• Right hemisphere

  • tone of voice/prosody

  • face perception

  • perceptual grouping

• Crossing (contralateral) functions

  • movement, sensation, and visions

  • Left hemisphere

    • right body movement and sensation

    • right side vision

  • Right Hemisphere

    • left body movement, sensation, vision

Language — Left Hemisphere (usually)

• Language is lateralised to the left hemisphere in most people

  • Language comprehension, speech, reading

  • Speech production

• Language and Hand Dominance

  • No overall “dominant hemisphere”

  • Right-handed people

    • 95% have language in Left Hemisphere

    • (5% in right hemisphere)

  • Left-handed people (10% of population)

    • 70% have language in Left Hemisphere

    • (30% in right hemisphere)

Contralateral Function

Motor and Sensory Cortex

• Contralateral = opposite side

• Ipsilateral = same side

• Primary motor and sensory cortex

  • connect to contralateral (opposite) side of body

    • right hemisphere to left side of body

    • left hemisphere to right side of body

Vision

• Each side of visual space mapped to contralateral visual cortex (opposite side of body)

  • left side of vision to right hemisphere

  • right side of vision to left hemisphere

• Note: not left eye/right eye

  • input to each half of retina of each eye is split so that left vision from both eyes foes to the right hemisphere and the right vision from both eyes to left hemisphere

  • important for 3D depth perception

Corpus Callosum

• Connects the left and right hemispheres

• Axons of neurons (nerve fibres) crossing to the opposite (contralateral) hemisphere

  • Neurons send their axons via the corpus callosum to connect with neurons in the opposite hemisphere

  • Allows transfer of information between the two hemispheres

Inter-Hemispheric Communication

• Vision goes to contralateral hemisphere

• In laboratory, can present stimuli very briefly to left or right of screen (on and off before people have time to move their eyes; < 200 ms)

• Stimuli go selectively to right or left hemisphere

• Language in left hemisphere – can report what is on right side of screen

• Stimuli on left of screen è Right Hemisphere

• Must cross to Left Hemisphere for language to report what object was

• Inter-hemispheric communication across corpus callosum

• What about action? How can the person point to the sun? Left and Right hands?

• Vision goes to contralateral hemisphere

  • Left of screen → Right Hemisphere

• Movement controlled by contralateral hemisphere

  • Left hemisphere → Right arm movement

• Left Hemisphere for language to report what object was

• Left Hemisphere for right hand to point to object

• Inter-hemispheric communication across corpus callosum

Split Brain — severed corpus callosum

• “Last resort” surgical treatment for very severe epilepsy

  • Corpus callosum severed to stop seizure activity from spreading to the other hemisphere

• Sperry and Gazzaniga studied “split-brain” patients (1960’s)

• Led to much knowledge about lateralisation of brain function

Experiments

• Images flashed to left or right of screen - “seen” by only right or left hemisphere

• People can reach under screen to touch and feel objects – find them by feel

• Right hemisphere can “read” and understand words, but no speech (so no verbal report)

Hemispheres can function independently

• Left hemisphere can tell what it has seen

• Right hemisphere can only show it (via the left hand)

• Patient cannot say what their left hand is doing !!

• Separate “consciousness” in each hemisphere?

Limbic System

Hippocampus

• Medial temporal lobe

• Memory

  • Forming new episodic memories

  • Damage causes memory loss (can’t form new memories)

• Spatial Navigation

  • Mental map of familiar environment (Nobel Prize 2014)

Memory and H.M.

• “H.M.” had his hippocampus removed to treat epilepsy (in 1953 at age 27)

• Cured epilepsy but …caused severe memory loss

  • Could not form new memories and recall anything from after the time of the surgery.

  • Would immediately “forget” everything that just happened

  • Could remember and recall things from before his surgery

  • Could “mentally rehearse” to remember things for a few seconds

  • Could learn new skills (but could not remember learning them)

• Led to new understanding of memory:

  • Memory” not one thing, but different components mediated by different parts of the brain

• Short-term memory

  • Lasts several seconds. Eg. remembering phone number long enough to type in to phone

  • H.M. could “mentally rehearse” to remember things

• Long-term memory

  • Declarative – Conscious recollection (things you can “declare”)

    • Episodic – Memory of past events or “episodes”, things you’ve seen and done,

      • eg. what you had for lunch yesterday, what you did on your birthday last year

    • Semantic – Facts and basic knowledge you can recall and declare

      • eg. Paris is the capital city of France

  • Procedural – Not for conscious recall

    • Skills you have learnt. Eg. how to ride a bike, how to sign your name

    • H.M. could learn new skills (but not remember having learnt them)

  • Encoding

    • Laying down new memories for long-term storage

    • H.M. could not form new memories

  • Retrieval

    • Retrieving memories for conscious recall

    • H.M. could recall memories from before surgery

Attention and Cognitive Control

• Frontal and parietal lobes mediate attention and control behavior.

• These lobes are highly evolved in humans.

Top-Down vs Bottom-Up Attention

• Top-down: conscious, voluntary control based on goals and experience.

• Bottom-up: involuntary attention capture by salient stimuli or unconscious drives.

Example:

• Top-down: Finding red keys on a cluttered desk.

• Bottom-up: Sudden movement or bright color involuntarily captures attention.

Parietal Lobe and Spatial Attention

• Parietal lobe: crucial for directing spatial attention (often linked with eye movements).

• Damage can cause spatial neglect: ignoring one side of space (e.g., left-side neglect after right parietal damage).

What is Attention?

• William James: attention = selecting one of many possible objects/thoughts.

• Acts as a filter to manage limited brain processing capacity.

• Selective attention:

  • Spatial: moving “spotlight” of attention to different locations.

  • Feature-based: focusing on specific features (e.g., color, shape, sound).

Example:

• Where’s Wally: moving attention to find red-and-white stripes.

Multitasking & Capacity Limits

• True multitasking is impossible: we switch attention between tasks.

• Example: Not aware of your seat pressure until someone mentions it.

Brain Networks for Attention

• Top-down attention (goal-driven): dorsal network (frontal & parietal regions).

• Bottom-up attention (stimulus-driven): ventral network (frontal & parietal).

Key Model:

• Corbetta & Schulman model (supported by fMRI & lesion studies).

Spatial Neglect

• Damage to parietal cortex (often from stroke) → neglect of contralateral space.

• Patients unaware of everything on the affected side.

Frontal Lobes: Role in Behavior and Regulation

• Frontal lobes: largest lobes, highly evolved in humans.

• Crucial for executive functions:

  • Reasoning, planning, problem-solving.

  • Inhibitory control (suppressing inappropriate actions/urges).

Inhibitory Control and Bottom-Up vs Top-Down

• Everyday control depends on top-down control (conscious goals) over bottom-up urges (unconscious drives).

• Example: resisting cake on a diet (top-down inhibits bottom-up desire).

Disorders of Inhibitory Control

• ADHD: impulsivity, distractibility.

• OCD: compulsions driven by intrusive obsessions.

• Addiction: compulsive behavior, impaired self-control.

Phineas Gage and Personality Change

• Severe frontal lobe damage → loss of behavioral control: impulsive, inappropriate, profane behavior.

Top-Down and Bottom-Up

• Perception (or conscious awareness) and behaviour is a combination of:

  • bottom-up processes—driven by external stimuli or unconscious states

  • top-down processes—cognitive control or volitional choice; modulation by prior knowledge and experience

Frontal Lobe

• Anterior to the central sulcus

• cognitive control of behaviour

• executive functions

  • reasoning, planning, problem-solving

  • inhibitory control

  • working memory

• motor functions

  • premotor cortex—motor planning

  • primary motor cortex—execution

• speech (broca’s area)

Attention

Selectivity

• ‘Select’ and prioritise stimuli based on location or features (whatever is relevant for goal)

  • Moving ‘spotlight’ (location)

  • Relevant features (colour, shape, etc)

Capacity Limited

• ‘Resources’ for attention are limited

• We can’t ‘attend’ to all incoming sensory information

• We use attention to filter and prioritise sensory information

“Conscious” controlled – Top-down

• Selecting and prioritising according to task or goal

• Voluntarily shifting visual attention (spotlight) to search

• Choosing features for selection, or “focus of attention

“Automatic” attention – Bottom-up

• Attention “captured” involuntarily by highly salient stimuli

• Things that “stand out” or Pop-out,

  • eg. sudden movement, colours or shapes that stand out from the background capture our attention

• Advertisers know how to capture your attention involuntarily, draw your eyes to particular things.

Parietal and Prefrontal network for Attention

Corbetta and Schulman (2002)

• Nature Reviews Neuroscience

• Network of Prefrontal and Parietal Cortex mediate attention

• Different areas for Goal-Directed and Stimulus-Driven attention (top-down and bottom-up)

• Based on brain imaging (MRI) studies and patients with brain lesions (spatial neglect)

Spatial Neglect

• Lesion (damage) to one hemisphere, frontal or parietal cortex

• Most commonly caused by stroke (blockage of blood supply)

• Deficit in directing attention to one side of space (side contralateral to brain lesion)

• “Ignore” things on one side; Unable to perceive stimuli on side contralateral to brain lesion

• Not due to any sensory deficit (i.e. normal vision)

• Simultagnosia: Can’t perceive multiple objects simultaneously

  • Will ignore objects on the neglected side

• Frontal-Parietal network necessary for attention to objects and space on the contralateral side

Executive and Inhibitory Control

• Crucial for control of behaviour

  • Selection of appropriate actions

  • Inhibition or suppression of inappropriate actions or usual responses (task-switching)

• Many disorders associated with impaired inhibitory control:

  • Attention Deficit Hyperactivity Disorder (ADHD): impulsive behaviours, difficulty preventing distraction to maintain attention on task

  • Obsessive Compulsive Disorder (OCD): Repetitive compulsive behaviour (washing, cleaning, checking)

  • Reward Addictions (e.g. gambling, internet: gaming, shopping, pornography): Compulsive behaviours

Maintaining Attention and Inhibitory Control

Continuous Performance Task

• Commonly used neuropsychological test

• Particularly sensitive to attention deficits in children

  • ADHD: Attention Deficit Hyperactivity Disorder

  • Relies on frontal cortex executive control: Ability to focus and maintain attention and inhibit “pre-potent” response (i.e. inhibit the usual rule)

• Simple example (lots of other variations)

  • Letters presented on screen one after the other

  • Read each letter aloud EXCEPT letter X

  • Say letters as quickly as possible

Frontal Leucotomy — Lobotomy

• Egas Moniz (1874-1955), a Portuguese physician, introduced prefrontal leucotomy for the relief of psychiatric disorders

• Based on observations of temperament change (“calming” effect) in chimapanzees following frontal lobe lesions

• First performed in 1935

• For severe psychosis (eg, schizophrenia, bipolar disorder) for which there was no other treatment

• Stopped following the introduction of antipsychotic medications in 1950’s

• Moniz’s lobotomy was down in a surgical theatre, with the needle going down through the top of the head and into three areas, where it was twisted

• Walter Freeman, USA, transorbital lobotomy from 1946 psych-surgery ‘by the bedside’ was done through going past the eyelid into the brain and moving the needle side to side. >18,000 patients in USA by 1951

Frontal Lobe — Clinical Conditions

Fronto-temporal Dementia (FTD)

• Degeneration (loss of neurons) in the Frontal and Temporal lobes

• 2nd most common dementia (after Alzheimer’s disease)

• Early symptoms difficult to distinguish from Alzheimer’s disease

• Symptoms: (all important functions of the Frontal Lobes)

  • Disinhibition: Increasingly inappropriate actions. eg. impulsive behaviour, overeating, overly-sexual behaviour, lack of social “tact”, lack of care for appearance and personal hygeine

  • Apathy: Lack of motivation, emotionally distant, withdrawn (may appear like depression)

  • Loss of Empathy: Unaware of the emotions of others, lacking social skills, may become socially withdrawn

  • Deficits in Executive Functions (Neuropsychological Testing) Planning, reasoning, organisation of complex tasks or sequences

  • (Speech and Language, Motor deficits)

Frontal Lobes: Role in Behavior and Regulation

• Frontal lobes: largest lobes, highly evolved in humans.

• Crucial for executive functions:

  • Reasoning, planning, problem-solving.

  • Inhibitory control (suppressing inappropriate actions/urges).

Inhibitory Control and Bottom-Up vs Top-Down

• Everyday control depends on top-down control (conscious goals) over bottom-up urges (unconscious drives).

• Example: resisting cake on a diet (top-down inhibits bottom-up desire).

Disorders of Inhibitory Control

• ADHD: impulsivity, distractibility.

• OCD: compulsions driven by intrusive obsessions.

• Addiction: compulsive behavior, impaired self-control.

Phineas Gage and Personality Change

• Severe frontal lobe damage → loss of behavioral control: impulsive, inappropriate, profane behavior.

Frontal Lobotomies

• Early “treatment” for psychosis, especially schizophrenia (before antipsychotics).

• Pioneered by Egas Moniz (Nobel Prize 1949).

• Walter Freeman (USA): 18,000 patients by 1951.

• Result: loss of frontal lobe-mediated behavioral control.

Frontotemporal Dementia (FTD)

• 2nd most common dementia (after Alzheimer’s).

• Progressive neuron loss in frontal and temporal lobes.

Symptoms of FTD

• Behavioral variant:

  • Inappropriate, impulsive actions (overeating, inappropriate sexual behavior).

  • Loss of social tact and self-care.

  • Disinhibition in everyday life.

• Neuropsychological testing: deficits in planning, reasoning, executive function.

Language Variants of FTD

• Non-fluent/agrammatic variant (like Broca’s aphasia): effortful, halting speech.

• Logopenic variant: word-finding pauses, effortful but good understanding.

• Semantic dementia: fluent speech but empty content, loss of word knowledge.

Example:

• Non-fluent: knows what a glass is but struggles to say “glass.”

• Semantic dementia: can say “glass” but doesn’t understand its function.

Neuropsychology in FTD

• Assess changes: behavior, language, cognition.

• Executive functions: starting/stopping behavior, regulation, goal-setting.

Example Test:

• Hayling Sentence Completion Test:

  • Fill in missing word → measures initiation.

  • Fill in with nonsense word → measures inhibition.

• Patients with behavioral FTD: can’t inhibit automatic responses (e.g., keep saying “ship” instead of nonsense word).

Real-World Implications

• Damage to frontal regions → impulsive decisions (e.g., impulse buying).

• Examples:

  • Patient bought 200 pounds of fish.

  • Another patient impulsively bought 3 kitchens.

Key Insight:

• Frontal lobes regulate behavior by balancing starting and stopping of actions → damage or disease disrupts this balance.

Learning: Habituation and Sensitization

• Learning = modification of behavior through experience.

• No new behaviors emerge; existing behaviors change in strength.

Aplysia californica (Sea Slug)

• Simple nervous system (~20,000 neurons).

• Studied by Eric Kandel → foundational for neurobiology of learning.

• Key anatomy:

  • Gill: breathing.

  • Siphon: expelling waste.

• Gill withdrawal reflex: automatic retraction when disturbed.

Habituation

• Repeated stimulus exposure → decrease in response strength.

• Procedure:

  • Firm water jet to siphon → measure gill withdrawal.

  • Repeat every ~90 seconds.

  • Gill withdrawal reflex weakens over time.

• Adaptive: ignoring non-threatening, persistent stimuli conserves energy.

Sensitization

• Exposure to strong aversive stimulus → increase in response strength.

• Procedure:

  • Baseline: water jet to siphon → measure response.

  • Apply weak electric shock to tail.

  • Apply water jet again → stronger gill withdrawal than initially.

• Adaptive: heightens vigilance after exposure to potential threat (“better safe than sorry”).

Classical Conditioning

• Associative learning: forming links between neutral stimuli and natural responses.

• Pavlov’s dogs:

  • US (food) → UR (salivation).

  • CS (metronome) + US → eventually, CS alone elicits CR (salivation).

• Key elements:

  • Unconditioned Stimulus (US)

  • Unconditioned Response (UR)

  • Conditioned Stimulus (CS)

  • Conditioned Response (CR)

• Higher-order conditioning: CS1 (metronome) can condition CS2 (tennis ball) → weaker CR as removed further from US.

Operant Conditioning

• Learning via consequences of behavior (Law of Effect).

• Thorndike’s puzzle boxes: cats learn which actions release latch faster.

• BF Skinner’s operant chamber (Skinner box): allows controlled study of behavior → reinforcement/punishment.

Reinforcement vs. Punishment

• Reinforcement: increases behavior frequency.

• Punishment: decreases behavior frequency.

Positive vs. Negative

• Positive: adding a stimulus.

• Negative: removing a stimulus.

Examples:

Schedules of Reinforcement

Continuous Reinforcement

• 1:1 ratio: every behavior is reinforced.

• Fast learning, but not robust to extinction.

Partial Reinforcement

• More robust learning, slower extinction.

Types:

Behavior Patterns

• Variable ratio: highest, constant rate of responding.

• Fixed ratio: stop-start responding after reinforcement.

• Variable interval: steady, moderate responding.

• Fixed interval: scalloped pattern – ramp up as interval ends.

Key Takeaways

• Classical conditioning: links neutral cues with automatic responses.

• Operant conditioning: links behavior with consequences → reinforcement/punishment.

• Schedules of reinforcement: determine how consistently behavior is rewarded → affects response patterns and learning robustness.

Classical Conditioning Overview

• Classical Conditioning Overview

  • Principles of Conditioning

  • Acquisition and Time-Sensitivity

  • Extinction (not forgetting!)

  • Spontaneous Recovery

  • Generalization & Discrimination

  Classical Conditioning: Applications

  • Advertising

  • Fears, Phobias, and Little Albert

  • Behavioral Treatments for Phobias

  • Disgust and Taste Aversion

Principles of Conditioning: Acquisition

• A conditioned response (CR) does not appear instantly.

• Rather, it is gradually acquired by repeatedly pairing the UCS and CS.

• Early learning is characterized by more rapid trial-by-trial changes in the CR.

• Later on in learning, there is progressively less change in the CR, as it approaches an asymptote.

Time-sensitive

• Both the rate and the asymptotic strength of the conditioned response depend on the relative timing of the CS and the UCS.

• Learning is most efficient when the CS is presented shortly before the UCS.

• Backward conditioning, presenting the UCS before the CS, is often ineffective.

• Potential evolutionary significance: a Cause must occur before an Effect

Extinction

• A conditioned response will reduce in strength and eventually disappear if the CS is repeatedly presented without the UCS.

• Extinction is a common way of eliminating a CR. Another way is to try and pair the CS with a new CR.

• Important to note that extinction is not the same as forgetting a CS-CR pairing

Spontaneous Recovery

• If extinction produces forgetting—it should not be possible for a CR to reappear unless the CS-CR association has been retrained.

• The previously trained CS-CR association remained intact

  • Potentially being suppressed by other more active associations

• Presentation of the original learning context can trigger spontaneous reappearance of the CR

Generalisation and Discrimination

• Stimuli that are similar to the CS will tend to elicit the same CR as the CS itself. When this happens, the CR has generalized to the novel stimulus.

• If the stimulus is dissimilar from the CS, it will not elicit the CR. The organism is able to discriminate the CS from the new stimulus.

Applications

Fears and Phobias

• The Little Albert experiment, conducted by John B.

• Watson and Rosalie Rayner in 1920, involved conditioning a young child named Albert to fear a white rat by pairing it with a loud, frightening noise. This demonstrated how emotional responses like fear can be classically conditioned in humans

Disgust and Taste Aversion

• Disgust towards certain stimuli can be viewed as a form of Classical Conditioning

• Strong “one-trial” learning after food poisoning experiences

• Biological rationale for these kinds of rapid learning

Operant Conditioning Overview

Learning via Reward and Punishment

• Relative effectiveness of reward and punishment

• Unintended consequences of punishment

Principles of Operant Conditioning

• Relation to Classical Conditioning

• Continuous vs. Partial Reinforcement: Humphrey’s Paradox

Applications of Operant Conditioning

• Shaping and Complex Behavior

• Revisiting Fears and Phobias

• Superstition and Irrational Behavior

Reinforcement and Punishment

• Reinforcement —outcome that increases the strength/frequency/probability of a behavior

• Punishment — outcome that decreases the strength/frequency/probability of a behavior

• What makes an outcome Reinforcing or Punishing depends on what has been added or removed from the environment

• Reinforcement tends to train a target behavior more effectively than Punishment

• The target behavior (sitting) elicits a good outcome (dog treat)

• A non-target behavior (not sitting) elicits a bad outcome (shock)

Punishment is Uninformative & Open-ended

• Reinforcement is more focused and informative

• Punishment can lead to unexpected outcomes

• If a Punishment outcome can be anticipated by the learner, they may learn ways to avoid it

• Potentially undesirable behaviours may be

• Negatively Reinforced by removing a bad (future) outcome

Principles of Operant Conditioning

Extinction

• Eliminating a previously reinforced behavior by no longer delivering reinforcement

Spontaneous Recovery

• Re-emergence of a previously reinforced behavior despite suspension of reinforcement

Generalisation/Discrimination

• Whether a reinforced behaviour is emitted in response to similar, but not identical stimuli

Acquisition and Consistency of Reinforcement

• Acquisition – Incrementally associating a behavior with an outcome

• Timing rules for Classical Conditioning still apply – the closer in time a Behavior is followed by Reinforcement, the more rapidly learning will proceed

• With Operant Conditioning, we need to consider how consistently reinforcement is being delivered to the learner

  • Continuous Reinforcement – every instance of the behavior is reinforced

  • Partial Reinforcement – only some instances of the behavior are reinforced

Humphrey’s Paradox

• Humphrey's Paradox, proposed by Nicholas Humphrey in 1976, questions why self-regarding emotions like fear and pain exist if they do not directly aid survival.

• It suggests that such feelings seem maladaptive since an organism could theoretically respond to danger without experiencing these emotions.

• However, the paradox underscores how subjective experiences like fear might actually promote learning and caution in potentially dangerous situations, highlighting their adaptive value.

Applications

Shaping and Animal Training

• To train a target behavior, begin by reinforcing behaviors that vaguely approximate the target behavior. Then, restrict reinforcement to behaviors that are increasingly similar to the target behavior.

• Simple behaviors can be chained together by reinforcement to form more complex behaviors

Fears and Phobias

• Fears that are acquired through Classical Conditioning may not passively resist extinction or forgetting…

• Anxiety caused by the Conditioned Stimulus can be relieved by actively avoiding the stimulus.

• Reduction in anxiety provoked by avoidance behavior Negatively Reinforces the fear.

Superstition and Irrational Behaviour

• Pigeon develops a “superstition” about the behaviors that seemingly provoked a food reward

• Operant Conditioning can maintain superstitious behaviors (or rituals) via Positive and Negative Reinforcement

Memory: Multi-Store Model and Processes

Memory, or the retention of information over time, is often described using a multi-store model consisting of sensory memory, short-term memory (STM), and long-term memory (LTM). Encoding, storage, and retrieval are central to these processes.

• Sensory Memory is fleeting and modality-specific. Iconic memory (visual) lasts less than a second and has a high capacity, while echoic memory (auditory) lasts 5–10 seconds but has lower capacity.

• Short-Term Memory is not modality-specific. It holds about 7 ± 2 items (Miller’s “magical number”), lasting 20–30 seconds without rehearsal. Rehearsal refreshes STM contents and aids in transferring information to LTM.

• Long-Term Memory is not capacity-limited and can last indefinitely. Forgetting here is more due to retrieval failures than storage losses.

Forgetting from STM has been explained by two major theories:

1. Decay: Information fades with time.

2. Interference: New information disrupts retrieval of older items. Research (e.g., Peterson & Peterson) found that both longer delays and competing tasks (e.g., backward counting) worsen recall, supporting interference as a major factor.

Free Recall and Serial Position Effects

Free recall experiments, where participants recall lists of words in any order, reveal a serial position curve:

• Primacy effect: Early items are remembered better due to more rehearsal and transfer to LTM.

• Recency effect: Last items are remembered well because they remain in STM.

• Middle items: Recall is lowest because of minimal rehearsal and interference.

Classical Conditioning

Pioneered by Pavlov, this form of learning involves associating a neutral stimulus (e.g., a metronome) with an unconditioned stimulus (e.g., food) until the neutral stimulus alone elicits the conditioned response (e.g., salivation). This can extend to higher-order conditioning, where new neutral stimuli (e.g., a tennis ball) become conditioned by association with already conditioned stimuli.

Operant Conditioning

Building on Thorndike’s law of effect, B.F. Skinner formalized operant conditioning: learning driven by consequences.

• Reinforcement (increases behavior) and punishment (decreases behavior) can be positive (adding a stimulus) or negative (removing a stimulus).

• Reinforcement schedules:

  • Continuous reinforcement: Every response is reinforced.

  • Partial reinforcement: Only some responses are reinforced.

    • Fixed ratio: e.g., every 5th behavior.

    • Variable ratio: reinforcement after an unpredictable number of behaviors (e.g., gambling).

    • Fixed interval: reinforcement after a predictable time interval.

    • Variable interval: reinforcement after an unpredictable time interval (e.g., pop quizzes).

      Variable schedules tend to produce steadier responding than fixed schedules.

Effective Retrieval and Memory Cues

• Retrieval cues are any features of the environment that help trigger memories. They work by forming associations with the target information, increasing the chance of recall if direct retrieval fails.

• The stronger the cue–target association, the better the retrieval performance.

Contextual Cues and Encoding Specificity

• The principle of encoding specificity (Tulving) states that memory is improved when the retrieval context matches the encoding context.

• Godden & Baddeley (1975) demonstrated this with divers recalling word lists better when tested in the same environment (land or underwater) as where they learned them.

Depth of Processing and Retrieval

• The depth of processing framework (Craik & Lockhart) states that deeper, more meaningful encoding improves memory.

  • Shallow processing (e.g., noticing capital letters) yields poor recall.

  • Intermediate processing (e.g., considering rhymes) yields better recall.

  • Deep processing (e.g., thinking about uses of an object) produces the best recall.

• Deeper processing creates more conceptual associations, which provide more retrieval cues.

Everyday Cues and Retrieval

• Examples include driving: cues in the environment (e.g., a fork in the road) automatically trigger retrieval of appropriate behaviors (e.g., turning on the indicator).

Interference: When Cues Misfire

Sometimes, strong associations cause errors rather than aiding retrieval:

• Proactive interference: Old memories disrupt new learning (e.g., using the indicator as in your old car when you get a new car with switched controls).

• Retroactive interference: New learning disrupts old memories (e.g., struggling to recall a word in your native language after intense immersion in a second language).

Summary

• Retrieval cues are essential for memory: they create multiple pathways to access stored information.

• Deeper encoding and matched contexts strengthen cues.

• However, strong but mismatched cues can interfere with retrieval, causing proactive or retroactive interference.

Multi-Store Model of Memory

• Theoretical Implications of the Multi-Store Model

  • Distinguishing Different Memory Stores

  • Measuring Sensory Memory

  • Measuring Short-Term Memory

  • Measuring Long-Term Memory

Implications

• Information is successively transferred to different memory stores

  • Increasingly durable forms of memory

• Several points where information can be lost

  • Transfer from sensory memory to short-term memory

  • Transfer from short-term memory to long-term memory

Sensory Memory

• Fleeting awareness of the presence of lots of information…

• …but it is difficult to report or describe all the details

• Perhaps we have access to a very large amount of sensory information, but a very short window of opportunity to encode it into a more durable form

The Capacity of Sensory Memory

• Sperling (1960) contrasted performance on Full Report and Partial Report versions of the memory task you just completed

• Full Report performance was around 5 letters (50% of array)

• Partial Report performance was virtually perfect (100% of cued array)

• A large amount of information is stored in visual sensory memory (12+ items), but only for a short amount of time—otherwise Full Report would be as good as Partial Report!

Measuring Short-Term Memory

The Capacity of Short-Term Memory

• Commonly measured using a span task

  • Study a list of letters/digits/words, presented at a rate of around 1 per second

  • Recall as many digits as you can in the order they were presented

  • List length when recall errors occur reflects storage capacity

• Approximately 7 ± 2 items (Miller, 1956)

• Duration of around 20-30 seconds or so

• The effective shelf-life of information in Short-Term Memory can be increased through rehearsal

Rehearsal and Forgetting

• Memory span appears shorter when rehearsal is prevented

• Perhaps the Magical Number 7 ± 2 is overly optimistic!

• Cowan (2001) has argued that the capacity limit is actually closer to 4 ± 1

• How does forgetting from short-term memory occur?

  • Temporal Decay – memories fade with the passage of time

  • Interference – memories become harder to distinguish from one another as they become more numerous

Measuring Long Term Memory

Capacity of Long-Term Memory

• Capacity of Long-Term Memory is massive (perhaps unlimited?)

• How many words do you know?

• How many people do you know by name?

• How many songs can you remember the lyrics to

• How many movies, TV shows, etc. can you remember details of?

• What about personal life events?

• How many skills, actions, and movements can you perform?

Memory Tests in the Yearbook Study

• Tested people’s memory for their High School graduation cohort using their own yearbooks as stimuli

• Interval between graduation and testing ranged from 2 weeks to 57 years

• Free Recall – Recall as many full names as you can in 8 minutes

• Recognition of Names – Do you recognize this name? (yes/no)

• Recognition of Portraits – Do you recognize this person? (yes/no)

• Matching Names to Portraits (two versions)

• Cued Recall – Who is this?

• Variation in difficulty across tests. Some require more specific information than others (e.g., Matching requires memory of names-to-faces, whereas Recognition of Names/Portraits do not)

• Matching performance and recognition of partial information is very good!

• Free Recall and Cued Recall fare worse, but are still remarkably good!

• Only major drop-off occurs after a retention interval of nearly 50 years

Retrieval & Reconstruction

• Cue-based retrieval

  • Mnemonic strategies: From Simple Cues to Complex Chunking

  • Can memory be trained?

• Beyond Pure Retrieval: Memory as a Reconstructive Process

  • Schemas

  • Misinformation

  • False Memory

Common Mnemonic Strategies

• Method of Loci

  • Associate memoranda with locations/landmarks along a familiar route

• Pegword Technique

  • “One is a bun, two is a shoe, three is a tree, etc.”

  • Pairing vivid imagery with memoranda

• Keyword Method

  • Pair a word that sounds similar to the to-be-remembered target

Chunked

• Elements within a group become associated with each other

  • They can form cohesive (if not meaningful) units

  • Retrieval of one part triggers retrieval of the whole unit

Chase and Ericsson (1982)

• Daily training: 1-Up, 2-Down

  • Start with a 5-item list

  • Tested one participant, SF, for 260+ hours over 2 years

  • List length can only increase with consistent recall

  • End of Day 1

    • Best recall: 7 items

    • Pure Rehearsal

  • End of Day 4

    • Best recall: 9 items

    • Group by 3s

  • End of Day 264

    • Best recall: 82 items

    • Complex Chunking

• SF was an avid longdistance runner—with deep knowledge of times

• Sequences of numbers remembered in terms of running times in different races (e.g., half-mile, marathon, etc.)

• SF was not an exception to the rule. Another runner, DD, was recruited and trained to use SF’s method. DD’s span was 68 items after 268 hours

Cues and Associations

Beyond Pure Retrieval

• We mostly think of memory as a “reactive” process – we selectively retrieve information that’s been held in storage.

• But there is good reason to believe that memory is also an “active” process that involves an element of reconstruction.

• Sometimes what comes out never actually went in!

• Schemas

  • Templates or “scripts” for familiar situations

  • If the details of something are forgotten (or not encoded), the “default” offered by the script can be inserted into one’s memory for what happened

Implanting False Memories

• Relatives of participants provided experimenter with information on 3 events that happened when the participant was around 5 years old

• A fourth story, introduced by the experimenter, was about the participant getting lost at the shops for a long time

• Around 25% of participants reported “remembering” being lost—some even provided additional details about the event

Implications for Eyewitness Memory

• Multiple factors erode confidence in eyewitness memory.

  • Suggestibility

  • Schemas

• Reconstructive nature of memory demands caution on the part of law enforcement agencies and jurors.

Other Distinctions About Memory

• Memory for specific facts—information you are aware of recalling

• Procedural or Implicit Memory

  • Memory for doing things—may not be tied to conscious awareness

• Episodic Memory

  • Memory for specific events or scenes from one’s life

• Semantic Memory

  • Information about general knowledge that is housed in Long-Term Memory

Problem Solving: Key Approaches

Overview:

Problem solving involves moving from an initial state to a goal state, often through multiple interacting steps and potential pathways. Solutions can be reached either incrementally or suddenly (insight).

Two Main Approaches:

1. Incremental Problem Solving:

   • Involves a gradual, step-by-step progression.

   • Example: Thorndike’s Cats – They learned to escape puzzle boxes through repeated, incremental improvements, without sudden insight.

2. Insight Problem Solving:

   • Involves sudden, seemingly effortless leaps to the solution (“aha!” moments).

   • Example: Archimedes’ Bath – Eureka moment realizing volume can be measured by water displacement.

   • Kohler’s Chimps – Sudden stacking of crates to reach bananas.

Computational Perspective:

Popularized by Newell & Simon (1970s), focusing on incremental approaches.

• Problem Solving Algorithms:

  • Fixed, step-by-step procedures guaranteeing a solution.

  • Often slow and computationally demanding.

  • Example: Following step-by-step Lego instructions.

• Problem Solving Heuristics:

  • Flexible, “rules of thumb” that are faster but may not always work.

  • Example: Building Lego walls and roof based on experience.

Problem Space and Navigation:

• Problem solving as navigating from an initial state (pile of Lego bricks) to a goal state (completed house).

• Actions (algorithmic or heuristic) incrementally change the problem state.

Two Noteworthy Heuristics (Newell & Simon):

1. Means-Ends Analysis:

   • Breaks down the problem into smaller, manageable sub-goals.

   • Example: Build four walls, then a roof.

2. Hill-Climbing:

   • No explicit solution known in advance.

   • Progress by always choosing the next step that most improves the current state.

   • Limitation: Can get stuck at a “local maximum” that is not the true solution (like stopping at a high point on a foggy hill that isn’t the summit).

Conclusion:

• Insight and incremental approaches are both central to problem solving.

• Incremental approaches include reliable algorithms and faster, flexible heuristics.

• Heuristics are versatile but can lead to suboptimal or incorrect solutions.

• Effective problem solving involves weighing these approaches based on the problem’s demands and available resources.

Concept Representation Overview

• Classical view of concepts

• Necessary & sufficient features

• Challenges to the classical view

• Conceptual structure: typicality & prototype theory, ad hoc categories, exceptions & exemplar theory

• Key topics: similarity, hierarchical structure, and concept use

What is a Concept?

• Mental representations organizing knowledge about specific things (real or imaginary)

• Help identify what things are and their properties

The Classical View of Concepts

• Concepts defined by necessary and sufficient features

• Something either is an example of the concept or not

• Positive examples possess necessary features

• Examples: all birds have feathers, hatch, and fly

Challenges to the Classical View

• No features shared by all examples (Wittgenstein, 1953)

  • Example: “games” lack a single defining feature

• People may not recognize category members despite knowing defining features (Hampton, 1979)

  • E.g., inconsistent categorization of vegetables

• Typicality ratings (Rosch, 1975) show categories are graded, not all-or-none

Conceptual Structure

Family Resemblance

• Examples share many (but not all) features; overlapping features differ across examples

Typicality & Family Resemblance

• Typical category members share more features with other category members

• Less typical members share fewer features with others

• High family resemblance stimuli learned faster and rated as more typical (Rosch & Mervis, 1975)

Typicality in Goal-Derived Categories

• Concepts can be constructed on-the-fly for goals (ad hoc categories; Barsalou, 1983)

• Ad hoc categories show typicality and family resemblance

Prototype Theory of Concepts

• Prototypes viewed as an ideal, average, list of common features, or single most typical example

• Typicality depends on proximity to the prototype and shared features

• Posner & Keele (1968): more prototypical stimuli classified faster and remembered better

Challenges for Prototype Theory

• Similarity to multiple exemplars more influential than prototype similarity (Shepard’s exponential generalization law)

• Handling category exceptions is difficult (e.g., bats resemble bird prototype more than mammal prototype)

Exemplar Theory

• Concepts as collections of memorized instances (category exemplars)

• Membership determined by overall similarity to category exemplars

• Typical stimuli highly similar to many other category exemplars

Core Topics for Concepts

Similarity

• Central to both prototype and exemplar theories

• Conceptualized as distance in psychological space

• Triangle inequality (Tversky, 1977): may not hold if different contexts affect similarity judgments

Hierarchical Structure

• Superordinate and subordinate categories (e.g., animals → dogs → beagles)

• Features at higher levels are present at lower levels (supports inference)

• Typicality influences whether features generalize from typical to atypical exemplars

The Basic Level

• Intermediate category level preferred (e.g., “tree” over “pine” or “plant”)

• Informs and differentiates objects

• Influenced by culture and expertise (Medin et al., 1997)

Category Use & Conceptual Structure

• Experts (e.g., tree taxonomists) structure knowledge differently than laypeople

Summary—Concept Representation

• Concepts organize knowledge, enabling identification and inference

• Classical definitional views replaced by prototypes and exemplars

• Typicality and family resemblance essential

• Key themes: similarity, hierarchical structure, interactions between structure and use

Decision-Making

Decision-Making Overview

• Heuristics and cognitive biases

• Heuristics reveal how cognition operates

Quick Recap – Rational Choice

• Subjective expected utility framework (Von Neumann & Morgenstern, 1944) is effortful

• Example: cost-benefit trade-offs in housing decisions

Young Charles Darwin Decides

• Weighs pros and cons of marriage

• Example of decision-making complexities

Heuristics for Decision-Making

• Simple rules of thumb (heuristics) simplify decision-making

• May not produce optimal decisions but are fast and effective

A Cook’s Tour of Heuristics

• Exploring what heuristics reveal about cognition

Recognition Heuristic (Goldstein & Gigerenzer, 2002)

• When little information is available, choose the recognized option

• Effective when recognition correlates with the target attribute

Representativeness Heuristic

• Judgments based on similarity to a cognitive prototype

• E.g., Linda as feminist bank teller; random sequence illusions

• Leads to conjunction fallacy (bank teller vs. feminist bank teller)

Base Rate Neglect

• Ignoring statistical base rates in favor of descriptive information (e.g., Jack at party)

Availability Heuristic

• Decisions based on how easily instances come to mind (e.g., homicide vs. suicide rates)

Heuristics Influence Information Processing

• Order effects in math problems (anchoring and adjustment)

• Labels (e.g., “friendly” or “rude”) bias impression formation

Framing Effects

• Decisions depend on how problems are framed (e.g., “200 saved” vs. “400 die”)

What Heuristics and Biases Reveal

• Departures from rational choice

• Influence of memory and information priority

• Heuristics offer timely, usually effective decisions

Perception: More Than Our Senses

We do not see with our eyes, hear with our ears, or smell with our noses. Our sense organs only transduce environmental energy into signals that our brain then processes. What we experience—sight, sound, smell, taste, and touch—are products of brain activity, not direct impressions of the world.

Sensory Adaptation & Aftereffects

• Sensory systems adapt to prolonged exposure, reducing responsiveness to constant inputs.

• Example: The rotating spiral illusion, or the “motion aftereffect.”

• Visual adaptation enhances salience of new inputs.

• Troxler fading: Inputs fade when fixated upon, causing aftereffects and illusions (like the “crimson chaser” illusion).

• Adaptation occurs in all sensory modalities and ensures that new, novel stimuli stand out.

Multimodal Integration & the McGurk Effect

• The McGurk Effect shows how audio and visual inputs combine to create a perceptual experience that differs from either alone.

• Perception is not simply veridical—it is constructed by the brain from multimodal evidence.

Perception as Construction, Not Reflection

• Perceptual filling-in: We “complete” missing parts of our vision (e.g., the physiological blind spot) using contextual cues.

• Neon colour spreading demonstrates how our brain constructs percepts from available evidence.

• This reveals the naïve realism fallacy—believing that we perceive the world exactly as it is.

Transduction in Hearing & Vision

• Hearing: Soundwaves cause air molecules to compress and rarefy.

  • Frequency = pitch.

  • Amplitude = loudness.

  • Hair cells in the cochlea detect these vibrations and convert them into electrochemical signals.

• Vision: Light is transduced by photoreceptors in the retina.

  • Photoreceptors (rods and cones) absorb photons and trigger electrical signals that travel to the brain via the optic nerve.

  • However, the human eye is limited by cellular layers that blur images and create a blind spot.

Colour Vision: Individual Differences & Species Variability

• Humans: Three types of cones (trichromatic vision).

  • Short cones (blue), medium cones (green), long cones (red).

• Some people lack one cone type (red-green colour blindness), others have a fourth cone (potentially superhuman colour vision).

• Birds and goldfish see beyond human limits—ultraviolet and infrared.

• Idiosyncratic variation: Even people with “normal” trichromatic vision differ in their cone ratios, possibly causing unique perceptions.

Colour Constancy: Accounting for Lighting

• The brain adjusts colour perception to discount the effect of illumination—colour constancy.

• Example: The viral dress photo (white and gold or blue and black) demonstrates how perception of colour can depend on assumptions about lighting.

Key Takeaway:

Perception is not a perfect record of reality.

• Our brains construct perceptions based on sensory input, past experiences, and contextual information.

• This is why your experience of “red” might not be exactly the same as mine, even though we share the same physical environment.

Sensation & Perception

• The world’s first Experimental Psychology lab was established by Wilhelm Wundt in Leipzig, Germany, in 1879.

• Initially a physiologist, Wundt wanted to understand human perception…

• He developed a method he called introspection

• Wundt & Helmholtz knew that we see with our brains, and that we don’t see all that meets our eyes, because they were well aware of a host of visual phenomena

• By applying the scientific method to study sensation/perception, Wundt created a setting where other Phenomena could be studied

• This includes all the diverse phenomena studied in contemporary psychological science

Human Visual Perception: A sub-conscious inference

• “objects in space around us appear to possess the qualities of our sensations. They appear to have an odor or a taste, and so on. Yet these qualities of sensations belong only to our nervous system… Even when we know this, however, the illusion does not cease” Helmholtz 1878: The facts of perception

Overthrowing Dualism

• By applying the scientific method to study sensation/perception, Wundt and Helmholtz were contributing to the over throw of centuries of misconception…

• The human mind had been thought to be separate from the human brain…

• The human brain was thought to be material, and therefore measurable. The human mind, however, had been thought to be immaterial

• The philosopher Rene Descartes had supported this concept, called dualism. He thought the brain communicated with the mind by transmitting signals out into the ether via the pineal gland

• As sensation and perception had been thought to be products of the mind, they were considered irrevocably mysterious, and beyond measure!

• The suggestion that we could measure perception was controversial

• It was suggested that setting up an experimental psychology lab…

• “would insult religion by putting the human soul in a pair of scales.” University of Cambridge Senate, 1877

What is the different between Sensation & Perception?

• Sensation: An ability to detect sensory input. As you will see next week, your central nervous system can detect many signals that you may never become aware of…

• Perception: Your subjective experiences of sensory input.

• e.g. the feeling of red, or the experience of roughness on your skin as your brush a rough surface, or the experience of a particular musical note

How did Wundt & von Helmhotz know that we perceive with our brains/minds

• As you have begun to see in our online content, Wundt & von Helmholtz were aware of a number of situations where our brains/minds generate experiences that are additional to the retinal images that reach our eyes…

• In a very real sense, your brain makes things up

Visual Perception

• Our brains have no direct access to information concerning the external visual environment!

• To ‘see’ the visual system must detect electromagnetic radiation, and convert it into neural events

• Ultimately, our brains infer what these neural events are signalling regarding our surrounds

Transduction

• The conversion of electromagnetic radiation into neural events. Involves light sensitive chemicals - visual pigments

• Visual pigments are contained in outer segments of photoreceptors that form the retina

• Pigments absorb photons of light, beginning a process that changes photoreceptor membrane conductance, causing depolarisation and action potentials

• The conversion of electromagnetic radiation into neural events. Involves light sensitive chemicals - visual pigments

• Visual pigments are contained in outer segments of photoreceptors that form the retina

• Pigments absorb photons of light, beginning a process that changes photoreceptor membrane conductance, causing depolarisation and action potentials

• Action potentials propagate to retinal Ganglion cells, via Horizontal, Bipolar & Amacrine cells, forward through retina

• Output from retinal ganglion cells combine to form the optic nerve – that carries signals out of your retinae to your brain

• To reach your brain, the optic nerve must pass through your retinae

The visible spectrum

• Each photoreceptor maximally absorbs a specific wavelength of light, with absorbance tapering off as wavelengths increasingly change from optimal

• The range of wavelengths that can be absorbed form the visible spectrum – the ‘light’ that you can see

The Physiological Blindspot

• The point at which the optic nerve leaves your eye is called the optic disc.

• At the topic disc there can be no photoreceptors – so you are blind to images that project to that position on your retinae

• As you are BLIND to images that project to your optic disc, it is often called the blindspot!

• There are several reasons people don’t typically notice their blindspots, but the most interesting is that the human visual system seems to assume that the same things that surround the blindspot are also within the blindspot – a process called perceptual filling in

Coloured Aftereffects

• Another situation where your brain causes you to see things that are not present on the retinae are Coloured Aftereffects (which were well known to Helmholtz and Wundt)

• The fact that you can see colours, when none are physically present, shows that you are seeing activity in your brain, rather than retinal images, or a veridical impression of the external world!

• Coloured Aftereffects helped reveal what wavelengths of light cones are maximally responsive to many decades before we had the requisite technology to study photoreceptors

Opponent Process Theory

• Opponent Process theory – After protracted viewing of certain colours, you can see oppositely coloured afterimages. This allowed colour vision scientists to infer that the human visual system contains competitive mechanisms tuned to opposite colours…

Face After-effects

Gender face after-effects

• Sensory adaptation does not just impact low-level processes in your retinae. It can impact perception of complex visual features – like the gender of human faces

• The gender face aftereffect shows that even our experiences of well known complex forms are subject to change – shaped by visual adaptation.

• Perception is a dynamic construction of your brain / mind

What Causes Aftereffects

• Aftereffects occur, in part, because the firing rates of neurons that are responsive to an input ‘adapt’ over time, which means they become less responsive

• In an opponent code, neurons are maximally responsive to opposite features – such as to red and to green

• Note that cells are maximally responsive to one type of input, and are less responsive to a wide range of other inputs

• Prior to adaptation, cells that are maximally responsive to opposite colours would be equally responsive to an intermediate colour ‘grey’

• 2-channel opponent code If the visual system is adapted to green, cells that are maximally responsive to green become less responsive…

• Then if you are exposed to grey, neurons that are maximally responsive to the opposite colour red will become relatively more responsive

• Unbalanced responses to inputs due to adaptation is what causes perceptual aftereffects…

• Your experiences of physical inputs depends on the responses of millions of neurons, and these change depending on what they have been adapted to

Attention, awareness and responses to inputs

• Visual adaptation is one way to modulate the responses of cells to inputs. Attention is another.

• The basketball demo works because feature based attention causes your visual system to be less responsive to unattended colours (in this case, to black)

• You can also have spatial and time based attention

Colour Constancy

• Perception is not simply determined by the physical lights that are refracted from a given surface!

• Colour Constancy: In different conditions the colour of the same wavelength of light can look very different

• The human brain facilitates a sense of colour constancy, by estimating what the prevailing light source is, and subtracting its influence from your impression of object colours

• To understand this, you have to appreciate that a range of wavelengths are reflected from any given surface, and this range is shifted by the light source

• You can use the brains’ tendency to estimate the prevailing light source to reverse apparent colour

• You can use the brains’ tendency to estimate the prevailing light source to reverse apparent colour and contrast polarity (brightness)

• Some people’s visual systems infer that ‘the dress’ is lit by a warm light source (the sun). Their brains subtract a ‘yellow’ illuminant, creating a veridical impression of the dress

• Others visual systems infer a cool illuminant (an indoor light source), creating an impression of a tan/gold and white dress

Colour blindness

• To understand why, you need to know a little bit about normal human daytime vision

• Usually, humans use 3 types of ‘photoreceptor’ which catch photons carried by different wavelengths of light, and turns these into signals that are sent to your brain

• A very small number of people (girls) have an extra class of day time photoreceptor

  • These girls may have ‘super’ human colour vision – able to distinguish many more colours than others!

• We all have different concentrations of daytime photoreceptors…

• Some people may experience green colours as brighter than red, and others the reverse. But we all learn colours by association, so normally we could never tell if this were true

Visual Pathways and Brain Processing

Primary Visual Pathway

• Signals travel from the eye via the optic nerve to the optic chiasm.

• At the chiasm, signals cross: right visual field signals go to left brain hemisphere; left visual field signals go to right hemisphere.

• This crossing is independent of which eye the signals come from.

• Damage before optic chiasm affects one eye; damage after affects one visual field side, indicating brain damage.

• Signals continue to lateral geniculate nuclei (LGNs) and then to primary visual cortex (V1) in occipital lobe.

Primary Visual Cortex (V1)

• V1 located in occipital cortex, one in each hemisphere.

• Each V1 maps the opposite side of visual field retinotopically (adjacent neurons correspond to adjacent retina regions).

• Foveal (central) vision mapped at posterior V1; peripheral vision maps more anteriorly.

• Vertical retinotopic mapping: lower visual field maps to upper V1 and vice versa.

• Damage to V1 causes cortical scotomas—blind spots corresponding to damaged visual field areas.

Visual Perception and V1 Activity

• Not all V1 activity leads to conscious visual perception.

• Flicker fusion threshold (~30Hz for color) limits conscious detection of rapidly changing stimuli, but V1 cells respond above this threshold.

• Some V1 responses are subliminal; brain processes visual information not consciously perceived.

Blindsight and Visual Sensitivity without Awareness

Blindsight Phenomenon

• Occurs after V1 damage causing cortical blindness.

• Patients report blindness in affected visual field regions but retain unconscious visual sensitivity.

• Demonstrated with forced-choice tasks where patients guess stimulus features above chance despite denying seeing them.

• Examples include Helen (monkey with bilateral V1 removal) and human patient PN navigating obstacles without conscious sight.

Implications of Blindsight

• V1 necessary for conscious vision but not all visual processing.

• Visual sensitivity can persist without conscious awareness.

• Shows subjective reports of vision can be unreliable.

Measuring Visual Sensitivity: Signal Detection Theory

Basics of Signal Detection

• Experiments include signal-present and signal-absent (catch) trials.

• Participant responses categorized as hits, misses, false alarms, and correct rejections.

• Sensitivity measured by d-prime: ratio of hit rate to false alarm rate; d-prime = 0 means no sensitivity.

• Sensitivity >0 means hit rate > false alarm rate.

Applications

• Used to objectively measure sensitivity despite subjective uncertainty or blindness (e.g., blindsight).

• Practical applications include fingerprint matching and airport security screening.

• Experts show bias: prefer misses (false negatives) over false alarms (false positives) to avoid wrongful decisions.

• Training in security introduces fake signals to reduce complacency and maintain detection sensitivity.

Functional Architecture of Visual Brain and Selective Deficits

Receptive Fields and Response Selectivity

• Visual neurons have receptive fields (retinal regions eliciting response).

• Response selectivity: neurons respond to specific stimulus features (e.g., orientation, motion).

• Example: a V1 cell responds strongly to vertical bars regardless of color, motion, or length, but not to slanted/horizontal bars.

Historical Discovery of Visual Cortex Properties

• Early research found retinal and LGN neurons respond to spots of light, but cortical neurons do not.

• Accidental discovery by Hubel and Wiesel: cortical neurons respond to oriented edges/bars, not spots.

• Nobel Prize awarded for discovering orientation selectivity in V1 neurons.

Hierarchical Processing in Visual System

• Simple features (bars, orientation) encoded in V1.

• More complex features (motion patterns, object categories, faces) processed in higher visual cortical areas downstream of V1.

• Processing hierarchy builds complexity from basic retinal inputs to advanced object recognition.