Perception Midterm

Introspection

“thinking” about your own perceptual experience

Introspection Problems (2)

1. your own experience is subjective and thus not verifiable

2. introspection may not reveal underlying processes

Some important insights from introspection

a. Color opponency (eg red and green are opposing sensations) b. Lateral inhibition (eg Mach bands)

Thresholds

weakest stimuli we can detect or tell apart

a high threshold means

a low sensitivity and vice versa

problems in measuring thresholds (3)

a. thresholds are limited by noise and thus not all or none

b. detection thus depends on both sensitivity and criterion

c. signal detection theory provides a method for understanding threshold judgments in the presence of noise (undertainty)

Can you use thresholds to characterize sensory channels

Yes

channel

a “filter” that is selective for certain information

Example of channel

an orientation channel will respond only to a narrow range of tilts

while measuring two interacting stimuli they are able to be measured by channels, why ?

if the stimuli influence each other they are encoded by the same channel

An example of channels being measured by measuring how two stimuli interact

adapting to one size affects the threshold only for similar sizes

Reaction times

a measure of the speed of a response

How is reaction times inferred

Can be used to infer the type of processing involved in a perception

Classic examples of reaction time studies

a. Stroop effect

b. Mental rotation

c. Visual search

Neuropsychology

studying perceptual deficits in patients with brain damage

Neuoimaging examples

fMRI and PET

Electrical potentials

Single unit recording

fMRI and PET

examining which parts of the brain are active during a perceptual task by monitoring blood flow

Electrical potentials

examining brain responses to stimuli by measuring the electrical responses on scalp (e.g. visual evoked potential) or surface of the eye (e.g. electroretinogram)

Single unit recording

measuring the responses of individual cells by recording their electrical signals

Neuron

many varieties but 4 basic parts

4 basic parts of neuron

1. Cell body

2. Dendrites

3. Axon

4. Synapse

Cell body

contains most of the machinery to keep cell functioning

Dendrites

fibers for receiving information from other neurons

Axon

fiber for sending information to other neurons

Synapse

where neuron makes contact with other neurons

Neurons signal information through electrical activity controlled by the flow of charged ions across the cell membrane leads to what

leads to charge differences across the membrane

3 important electrical potentials for understanding how a neuron works:

1. Resting potential

2. Graded potentials

3. Action potential

Resting potential

baseline charge difference when cell is at rest (not stimulated)

Graded Potential

passive charge difference in response to stimulation

a. synaptic potential

b. receptor potential

synaptic potential

due to influence of other neuron

receptor potential

due to “transduction” of physical stimulus

ex: the absorption of light

Action Potential

brief charge (nerve impulse or “spike”) generated by a neuron to carry information along the axon

Differences between action potentials and graded potentials

Differences between action potentials (red) and graded potentials (blue) : Size of potential

Acton potential : large-fixed

Graded potential : small-variable

Differences between action potentials (red) and graded potentials (blue) : Duration

Action : brief (e.g. 1 msec)

Graded : long

Differences between action potentials (red) and graded potentials (blue) : Signal

Action : depolarize only

Graded : depolarization or hyperpolarization

Differences between action potentials (red) and graded potentials (blue) : location

Action : axon

Graded : throughout cell

Differences between action potentials (red) and graded potentials (blue) : purpose

Action : to carry fixed signal over long distances

Graded : to sum together the inputs from other cells

Synapse

connection between neurons mediated by chemical neurotransmitters

Synapses can have excitatory vs. inhibitory effects on what type of cell

the post-synaptic cell

Receptive fields depend on the pattern of what

synaptic connections to the cell

Neurons can carry information by (3)

1. Size of response (graded, or number of action potentials)

2. Pattern of responses (e.g. temporal coding of sound frequencies)

3. Pattern of connections (labelled lines)

The problem of perception (3)

1. Stimuli are inherently ambiguous

• eg: many different objects could give rise to the same retinal image

2. The brain must therefore make guesses or “unconscious inferences” in order to interpret the image

3. Perception is therefore “indirect” because it requires “information processing”

Levels of understanding perception (3)

1. ecological or computational

2. psychological

3. physiological

ecological or computational level

what is the goal of the perception, and whatproperties of the stimulus or the situation allow the problem to be solved?

Example: optic flow: as we move through the environment the retinal image changes in characteristic ways that provide cues about our motion

psychological Level

what are the processes underlying our perception and what sort of mental representations do they lead to?

physiological level

how are these processes and representations realized by the nervous system?

Informtation processing in sensory systems (3)

1. encoding, representation, and decoding

2. Serial vs parallel processing in sensory systems

3. Multiple-channel models and population codes

Serial processing in sensory systems

different stages along the visual pathway represent increasingly more abstract properties of the stimulus

parallel processing in sensory systems

different visual subsystems encode different properties

(e.g. obects vs. motion)

Coding efficiency and information theory (2)

1. Limited channel capacity

2. Creating more efficient representations by removing redundant signals

Examples of Limited channel capacity

neurons have a small range of response levels

Examples of Creating more efficient representations by removing redundant signals

redundancy

• nearby locations typically have the same light level

Predictive coding

representing how stimuli deviate from expectations

Predictive coding Examples

coding a color by how it differs from gray or a face by how it differs from an average face

Plasticity in sensory representations example

developmental changes and perceptual learning

Bayesian inference in perception

decode the the sensory signals to estimate the stimulus by combining evidence from the senses with prior expectations

example of a prior: assume lighting is from above to interpret shading cues

Cornea and lens function

for focusing light to form image on the retina

Retina

thin layer of neurons along back of eye that absorb (receptors), process and transmit information about the light image

Fovea

small region of retina specialized for finest vision, corresponding to the center of gaze

Optic disk or blind spot

receptor-free “hole” in retina where ganglion cell axons leave the eye

Photopigments and transduction

conversion of physical energy to neural signal

Rods vs. cones

2 branches of dark adaptation curve reveal two mechanisms

Rods (purple) v Cones (yellow) : sensitivity to light

Rods : High

Cones : low

Rods (purple) v Cones (yellow) : Operating Range

Cones : moderate- bright

Rods : dim light

Rods (purple) v Cones (yellow) : Spatial Acuity (detail )

Rods: low

Cones: high

Rods (purple) v Cones (yellow) : Retinal Distribution

Rods : peak around 20 deg

Cones: peak in fovea

Rods (purple) v Cones (yellow) : # of receptor types

Rods : 1

Cones : 3

Rods (purple) v Cones (yellow) : Color Vision

Rods : no

Cones : yes

Receptive field (RF)

area on the retina to which a cell responds

Bipolar cell receptive fields

Center - surrounded

Different Bipolar cell receptive fields

1. Direct receptor input vs. indirect input through horizontal cells

2. on-center vs. off-center

3. Lateral inhibition: inhibition between spatially adjacent cells

Direct receptor input vs. indirect input through horizontal cells

1. forward – Receptors to bipolar cells to ganglion cells

2. Lateral – Horizontal cells and amacrine cells

on-center vs. off-center

on-center : responds to a bright spot of light that just covers the center

off-center : responds to a dark spot of light that just covers the center

Lateral inhibition

inhibition between spatially adjacent cells

Ganglion cell receptive fields similar to which cells

Bipolar cells

Information flow in the retina:

1. Straight through: receptor to bipolar to ganglion cell

2. Sideways: via horizontal cells and amacrine cells

Center-surround RF's emphasize contrast, de-emphasize absolute light level - why?

on-center cell responds best to a bright spot of light that just covers the center

off-center cell responds best to a dark spot that just covers the center

Examples of contrast effects

Simultaneous Contrast

Hermann Grid

Mach bands

Most ganglion cells send their axons to

Lateral geniculate nucleus (LGN)

Why do Nasal fibers cross over

so each LGN represents contralateral visual field

(ie opposite side of the world)

layers Of the LGN

magnocellular and parvocellular

These come from both eyes to line up signals

Cells have similar RF's to Which cells

Ganglion cells

Examples : center-surround and monocular

Monocular

Responds to signals only from one eye

Primary visual cortex also is known as

striate cortex or V1

What happens in the primary visual cortex

where most LGN cells send their axons

some RF properties first seen in cortex:

1. Orientation selectivity

2. Binocular

3. Increased selectivity for size

4. Sensitivity to direction of movement

5. simple cells v complex cells

Binocular

cells receive inputs from both eyes

Simple cells

spatially separated on and off subregions in receptive field, like center-surround cells

Complex cells

same stimulus selectivity as simple cells but no clear subregions within receptive field

Organization of different cell types in striate cortex

1. Retinotopic organization

2. Columnar organization

3. The hypercolumn

Retinotopic organization

spatial layout of retina is preserved by layout of cortex, but

Cortical magnification factor: much more of cortex is devoted to the fovea, much less to peripheral retina

Cortical magnification factor

much more of cortex is devoted to the fovea, much less to peripheral retina

Columnar organization

at each location cells in different layers have similar properties (e.g. preferred stimulus orientation), while RF’s change systematically as move from one point on the cortex to the next (e.g. preferred orientation changes smoothly from one column of cells to the next)

The hypercolumn

a functional module (~1mm square of cortex) that processes all orientations, eye combinations, colors, sizes, motion direction for a given location in space

Parallel pathways

Different areas are specialized for processing different visual tasks at the same time

Output of striate

about 30 distinct visual areas have been identified in primate cortex, suggesting a great deal of visual perception happens after the striate

Example of Different areas are specialized for processing different visual tasks at the same time (in parallel)

where pathway (parietal cortex) vs. what pathway (temporal)

Where do Parallel pathways begin with different cell types

In the retina

Two major pathways named for the LGN layers through which they pass:

magnocellular

parvocellular