PSYC 212 - Midterm #2

Qualia

the subjective, first-person experiences of sensations, like the redness of red or the pain of a headache

The principle of univariance

A single photoreceptor can be activated by different wavelength + intensity combinations, making these combos indistinguishable

- one type of photoreceptor cannot perceive color alone

- color vision requires multiple photoreceptor types working together

Trichromacy

Our eyes perceive color based on the combined activity of three types of cone cells.

- Each wavelength of light triggers a unique pattern of responses across the three cones, regardless of intensity

- discovered by using a color-matching method (Young and VonHelmholtz, Maxwell)

- Three colors are needed to match any other color — two are not always enough

Color anomalous

a term for what is usually called "color blindness"

- Most "color blind" individuals can still make discriminations based on wavelength (discriminations are different from norm)

Deuteranope vs. Protanope vs. Tritanopia

Deuteranope: due to absence of M-cones

- difficulty distinguishing green from red

Protanope: due to absence of L-cones

- difficulty distinguishing red hues from greens

Tritanopia: due to the absence of S-cones (rare)

- difficulty distinguishing green-blue, yellow-pink and purple-red

Cone monochromat

has only one cone type

- Truly color blind

Metamers

different mixtures of wavelengths that look identical

- More generally, any pair of stimuli that are perceived as identical in spire of physical differences

Additive color mixing

the process of creating colors by combining different wavelengths of light

- The primary colors are red, green, and blue (RGB)

- When all three are combined at full intensity, they produce white light

- Basis for color displays like TV screams and computer monitors

Subtractive Color Mixing

the process of creating colors by removing (absorbing) certain wavelengths of light

-The primary colors are cyan, magenta, and yellow (CMY)

- When combined, they absorb more light and produce darker colors, with all three mixing to form black

- Used in printing, painting, and pigments

Non Spectral hues

hues that can arise only from mixtures of wavelengths

- There is no "purple" in the spectrum, it has to come from a particular combination of activity across S, M, and L cones

Opponent Color Theory (Ewald Hering)

some color combinations are perceived as "legal" while others are "illegal"

Legal colors: bluish-green (cyan), reddish-yellow (orange), bluish-red (purple)

Illegal colors: reddish-green, bluish-yellow

- Supports the opponent process theory (colors are processed in opposing pairs: red vs. green, blue vs. yellow)

Hue cancellation experiments

method used to determine opponent color processing

- Participants adjust the amount of an "opponent" color (ex: adding green to cancel out red) until no trace of the original hue remains

- Helps map sensitivity of the visual system to different color opponent dies (red-green, blue-yellow)

In Opponent Color Theory, to compute red-green component...

the system compares the activity of M cones to the activity of L cones

In Opponent Color Theory, to compute blue-yellow component...

the system combines the activity of L cones and M cones, stating that the combined activity is yellow, and then compares pooled L&M cone activity to S cones

L Cones (Long-Wavelength Sensitive) (red)

M Cones (Medium-Wavelength Sensitive) (green)

S Cones (Short-Wavelength Sensitive) (blue)

Discounting the illuminant

estimates the light source and adjusts perception to maintain stable colors

- Even when lighting conditions change (sun vs indoors), we perceive objects as having the same color

Color constancy

allows us to discount the influence of the illuminant and focus on the true colors of objects

Template theory

the visual system recognizes objects by matching the neural representation of the image with an internal representation of the same shape in the brain

- limited flexibility (sensitive to variations)

- requires many templates for many different views

- ex: matches imput to a stored dog template

Exemplar theory

the brain recognizes objects by comparing them to multiple stored examples rather than a single template

- Recognition process: comparison with multiple previously seen instances

- high flexibility (handles variability well)

- stores many exemplars but generalizes well

- ex: compares input to multiple stored dog examples (various breeds, angles, and contexts)

Prototypes theory

We create mental "averages" of categories based on our experiences

- stores only one prototype per category

- allows for some variation but relies on a central example

- new objects are recognized by comparing them to the most representative prototype in our mind

- Example: When seeing a new dog, we compare it to our "idealized average dog" in our memory

GCM (Generalized Context Model) (Nosofsky)

you store many specific faces you've seen before

- When you see a new face, you compare it to your stored faces and assign it to a category based on how similar it is to the ones you've seen

General Recognition Theory (GRT) – Ashby

- brain analyzes perceptual dimensions (ex: face shape, jaw width, eye size) to classify objects

- Categories are probabilistic → No strict rules; instead, the brain works with overlapping distributions of features.

- Decision Boundaries → The brain draws statistical lines to separate categories (ex: distinguishing two similar faces)

- Multivariate Signal Detection → Uses patterns & probabilities, not just simple yes/no recognition

GReaT, patterns and probabilities without any strict rules

Recognition by components theory

we recognize objects using an alphabet of shapes, called geons (geometric ions) that together can form any geometric object

Grandmother cells

a single neuron responsible for recognizing your grandmother (Jerry Lettvin)

Deep neural network (DNN)

multilayer neural networks capable of being trained to recognize objects

- Numerous instances of an object are shown to the network, with feedback provided

- Over time, the network learns to recognize new instances of the object that it has never explicitly been trained on

Object recognition pathway

Retinal Ganglion Cells and the LGN (Lateral Geniculate Nucleus) detect localized contrast, spots of light and dark.

The LGN sends this visual information to the Primary Visual Cortex (V1).

V1 begins shape processing by detecting edges, bars, and orientations.

Intermediate and high-level vision

Intermediate-level vision (V2, V3, V4, etc.) is related to grouping features into colors, textures, and surfaces

High-level vision (IT cortex) is related to recognizing complex shapes, objects, and categories

Boundary ownership

For a given edge/contour, neurons determine which side belongs to the object and which side belongs to the background (a fundamental process in figure-ground segregation)

Intermediate (mid) level vision

The step between basic feature detection (edges, contrast) and recognizing full objects and scenes

- Groups visual info into meaningful objects by perceiving edges, surfaces, and boundaries

- Acts as a bridge between detecting simple features and understanding what we see

- Example: Helps decide which lines and shapes belong to a dog vs. its shadow

Computerized edge detectors vs human vision

Computerized edge detectors sometimes miss edges that humans easily perceive because they rely purely on contrast and intensity differences

Illusory contour

contour that is perceived even though no physical edge exists between one side and the other

The Gestalt theory

"The whole is greater than the sum of its parts"

- opposes Structuralism, which breaks perception into basic elements

- suggests we naturally organize elements into meaningful wholes, not just process each part separately

- ex: We see a complete shape (like a triangle) instead of just individual lines

Gestalt grouping principles

proximity, similarity, common region, connectedness, good continuation, closure, figure-ground, parallelism, symmetry, common fate

Rules that describe how elements in an image are visually grouped to form unified wholes:

Proximity: Objects close together are seen as a group.

Similarity: Elements that share color, shape, size, or texture are grouped.

Common Region: Elements within the same bounded area are grouped.

Connectedness: Physically connected elements are perceived as one group.

Good Continuation: Lines and edges follow the smoothest path.

Closure: The brain fills in gaps to perceive complete shapes.

Figure-Ground: The mind separates objects (figure) from the background (ground).

Parallelism: Objects with parallel contours are grouped.

Symmetry: Symmetrical elements are more likely to be grouped.

Common Fate: Elements moving in the same direction are grouped together.

Five principles of intermediate vision

(1) Group what should be grouped together

(2) Separate what should be separated

(3) Use prior knowledge

(4) Avoid accidents

(5) Seek consensus and minimize ambiguity

Loudness

the psychological perception of sound intensity

- Measured in decibels (dB) relative to the smallest perceivable pressure

- 0 dB represents the minimum audible level (not no sound)

Logarithmic scaling for decibels (dB)

+10 dB = 10x increase in intensity

- Ex: the difference between 10dB (10^1) and 20db (10^2) dB is 100-10=90

Frequency and Pitch

Pitch: How we perceive sound, mainly based on the fundamental frequency

Frequency (Hz): The number of cycles per second (e.g., 2 cycles = 2Hz)

Pure tones: Sounds with one frequency

- Higher frequency = higher pitch, and lower frequency = lower pitch

Equal loudness curve

a graph plotting sound pressure level (dB SPL) against the frequency for which a listener perceives constant loudness

- Unit used is called a "phon," which corresponds to the dB value of the curve at 1k Hz

Harmonic spectrum

Complex sounds contain energy at integer (whole number) multiples of the fundamental frequency—the lowest frequency produced by a vibrating source.

These higher multiples are called harmonics.

Timbre is the quality that makes sounds with the same pitch and loudness (like a violin vs. flute) still sound different—it's shaped by the sound’s harmonic profile

Inverted spectrum

A thought experiment in the philosophy of color:

Two people use the same color words and make the same color distinctions…BUT their actual color experiences (qualia) could be completely different (ex: one sees red where the other sees blue)

Pitch

the psychological aspect of sound related mainly to fundamental frequency

Auditory canal

a tube-like structure that directs sound waves from the outer ear to the tympanic ossicles

Tympanic membrane (eardrum)

a thin, vibrating membrane that separates the outer ear from the middle ear and transmits sound vibrations to the ossicles

Ossicles

three small bones in the middle ear (malleus, incus, and stapes) that amplify and transmit sound vibrations to the inner ear

Cochlea

a spiral-shaped fluid-filled structure in the inner ear that converts sound vibrations into neural signals for hearing

Oval window

a membrane-covered opening that connects the middle ear to the cochlea, transmitting vibrations from the ossicles

Round window

a flexible membrane in the cochlea that helps relieve pressure from sound waves traveling through the cochlear fluid

Cochlear (Auditory) nerves

the nerve that carries auditory information from the cochlea to the brain for sound processing

Organ of Corti

a structure on basilar membrane of the cochlea that is composed of hair cells and dendrites of auditory nerve fibers

Basilar membrane

a structure within the cochlea that vibrates in response to sound

- assists in frequency discrimination by supporting hair cells

tectorial membrane

a gelatinous membrane in the cochlea that interacts with hair cells

- Aids in the conversion of mechanical sound vibrations into electrical signal

Hair cells

sensory receptor cells in the cochlea that erect sound vibrations and convert them into neural signals transmitted to the brain via the auditory nerve

Temporal coding

Auditory nerve (AN) firing is phase-locked → Neurons fire at specific points in a sound wave cycle

- Works best for low frequencies (below 4000–5000 Hz)

- At higher frequencies, neurons can’t fire fast enough due to their refractory period (reset time)

Volley principle

Individual auditory nerve fibers can’t fire fast enough to keep up with high-frequency sounds, so neurons work together in a team and take turns firing at different phases of the sound wave, creating a combined pattern that accurately represents the frequency

the two pathways object information is divided into after processing in the extrastriate cortex

the "where" pathway (dorsal stream) and the "what" pathway (ventral stream)

- Division supports spatial awareness (dorsal) and object recognition (ventral) in visual perception

Area V4

represents intermediate-level shape information

- extracts curves, textures, and complex contours

- sensitive to local features

PIT

it represents object parts, specializing in intermediate processing

Lateral Occipital Complex (LOC)

Encodes whole objects, not just fragments

- Recognizes shape-based objects → Even without color or texture

- Works from any angle → Object identity stays the same

- Bridges mid-level (V4, PIT) → high-level (IT cortex, FFA, PPA) recognition

- Helps separate objects from backgrounds (figure-ground segregation)

Fusiform face area (FFA)

Located in the fusiform gyrus of the ventral temporal lobe (right hemisphere, sometimes both)

- specialized in recognizing faces

- Most tuned to faces but also helps with expert-level recognition (ex: identifying cars or birds)

Invariant Recognition: Helps recognize faces across angles, lighting, and expressions (view-invariant representation).

- Linked to prosopagnosia (inability to recognize faces)

Parahippocampal place area (PPA)

Recognizes scenes and places (not just objects)

- Selective for spatial layout

- Helps distinguish scene perception from memory-based navigation

- Bridges vision & place cognition → Connects visual input to spatial understanding

- Not just about objects → Focuses on how spaces are arranged

- Works separately from hippocampus → Doesn't handle memory-based navigation

Rank detection locations in the brain by least to most complex

1) V1 (Primary Visual Cortex) → Detects basic edges & orientations (early vision)

2) V2 (Secondary Visual Cortex) → Detects simple shapes & contours, starts grouping features

3) V4 (Visual Area 4) → Processes color, curvature, and complex shapes

4) PIT (Posterior Inferotemporal Cortex) → Recognizes more detailed object shapes

5) LOC (Lateral Occipital Complex) → Detects entire objects rather than just features

6) FFA (Fusiform Face Area) → Specializes in face recognition

7) PPA (Parahippocampal Place Area) → Recognizes scenes & places instead of objects

8) AIT (Anterior Inferotemporal Cortex) → Processes highly complex objects like specific faces, animals, or tools

9) PRC (Perirhinal Cortex) → Combines visual & memory info for object recognition in different contexts

10) PFC (Prefrontal Cortex) → Highest-level processing, involving decision-making, categorization, and conscious recognition

Decoding method

collect fMRI scans of a participant while they view images from multiple known categories

- Train a computer model to recognize the brain activity patterns associated with each category

- Test the model to see if it can correctly identify an unseen image based on learned brain activity patterns

Decoding based on similarity using fMRI

Brain activity patterns are positively correlated when viewing similar stimuli but negatively correlated when categories change

- Strong positive correlation (high R score) when viewing only faces or only houses

- Moderate negative correlation (negative R score) when switching between categories (ex: face → house)

- This shows how fMRI can decode brain activity based on similarity in response patterns

Encoding method

A technique using fMRI scans to study how the brain processes images

Step 1: Define a feature space (ex: Gabor wavelet pyramid for visual stimuli)

Step 2: Train the model by mapping how different features affect brain activity in each voxel

Step 3: Predict neural responses to new, unseen stimuli

Step 4: Compare predicted vs. actual fMRI data to assess model accuracy and understand brain region representations

Desktops Take Precise Commands

Second-order isomorphism

similar objects in the physical world must have similar representations in the mind

V1

detects basic visual features such as orientation, contrast, spatial frequency, and edges

V2

extracts more complex edge and texture information

- specializes in illusory contours, border ownership, texture segmentation

AIT (anterior inferotemporal cortex)

encodes whole object identities, integrating across transformations

- specializes in view-invariant object recognition, category-general processing

PRC (perihinal cortex)

represents object-specific information

- differentiates between highly similar objects, fine-grained semantic encoding

PFC (prefrontal cortex)

integrates visual information with memory and decision-making

- specializes in goal-directed behavior, flexible object categorization, conceptual knowledge

Early visual processing (Basic feature extraction)

V1 (Primary Visual Cortex) → Detects edges, orientation, contrast, spatial frequency

V2 → detects border ownership, illusory contours, and texture segmentation

V4 → Integrates local features into curves, textures, and color processing.

Mid-Level Shape Processing

PIT (Posterior Inferotemporal Cortex): Processes object parts and shape configurations

LOC (Lateral Occipital Complex): Integrates shape components into whole-object representations

High-Level Object Representation

Category preferential hubs (ex: OFA, FFA, PPA). Preferential response to categories of objects (object detection?)

AIT (Anterior Inferotemporal Cortex): Encodes view-invariant object identity and general category structure

PRC (Perirhinal Cortex): Differentiates highly similar objects, encoding fine-grained semantic distinctions

Integration with Memory and Cognition

PFC (Prefrontal Cortex) → Links object perception with memory, attention, and decision-making

Hippocampus (if memory is involved) → Associates objects with episodic memory and spatial context

Apex of the cochlea

where low frequencies are coded

Base (entrance) of the ear

where high frequencies are coded

Hearing aids

sound amplifiers that have a processor and a microphone that pick up the sound from the environment and make it louder inside the ear

- The traditional design is the microphone and chip sitting behind the ear and the loudspeaker inside the ear (Behind the ear (BTE) hearing aid)

- Have directional microphones that focus on speech and have noise canceling algorithms for background noise

Cochlear implant (CI)

electric rod is inserted along the basilar membrane of the cochlea (starting at base of cochlea goes to apex)

- its electric firing is guided by receiver connected to external piece, which is attached to head by magnet

- external piece has microphone that picks up sounds from environment and converts them into electric firing patterns

Candidacy for cochlear implant

people who begin hearing starting at 60 dB (have less than 60% of speech recognition) qualify best for a cochlear implant

- For people with mild to moderate hearing loss (starts hearing as of 40-50 dB) who pick up on more than 60% of speech recognition, a hearing aid may be better

Electro-acoustic stimulation (EAS)

hearing aids are combined with cochlear implants depending on the frequencies we want to fix

- Low-pitched sounds are fed through a natural pathway of sound by just amplifying with a loudspeaker (hearing aid) inside the ear to fix the mild hearing loss for those low frequencies

- High-pitched sounds: the electrode is surgically inserted inside the ear, and electricity is sent right to the nerve

Maximal cochlear duct coverage improves sound quality study

Study: Compared patients with shorter vs. longer electrodes (longer electrodes cover more of the cochlea).

Findings:

Shorter electrodes → patients heard higher-pitched sounds.

Cochlear implants capture all sounds and feed them at the entrance of the cochlea, where high-pitched sounds are coded.

Longer electrodes → fewer patients reported high-pitched sounds.

Long-Term: Over time, most patients reported getting used to the sound, and fewer found it high-pitched.

Anatomy-based fitting (ABF)

Improves speech recognition in both quiet and noisy environments for experienced bilateral cochlear implant (CI) users

Tradeoff: Adjusts frequencies to match between both ears, improving performance when there’s no frequency mismatch

Improves music perception: Enhances music quality, melodic contour, and song appreciation

Single-sided deafness (SSD)

patients with only one functioning ear show deficits in…

- Speech in noise Recognition deficit (ipsilesional (same-side) auditory hemifield)

- listening Effort (have to put more effort into listening)

- sound Localization deficit

SIR/EL

Pupillometric measure of listening effort

the more a human requires cognitive effort, the more their pupil dilates

Time coding

The brain and ears synchronize neuronal firing to the wavelengths of sound

- Best for low frequencies, helping with precise sound perception

Fine structure processing

Encodes the timing details of sound → Matches the brain’s natural way of hearing

- Uses modern coding to follow the wave pattern inside the sound signal

- Enhances musical perception → Especially for experienced cochlear implant users

- Improves low-frequency detection (<1000 Hz) → Key for richer sound quality

- Works for both unilateral & bilateral cochlear implants → More natural hearing experience

When fixing hearing loss, is tinnitus fixed?

Yes

Color constancy relating to the dress example

some people interpret the dress as blue and black because they interpret the illuminant as having a lot of yellow, while some people perceive the dress as white and gold because they interpret the illuminant as having more blue in it

Akinetopsia

a rare neuropsychological disorder in which the affected individual has no perception of motion

- Can be caused by lesions of areas MT/MST

- Patients report seeing streams of multiple, frozen images trailing in the wake of moving objects

Apparent motion

the illusory impression of smooth motion resulting from the rapid alteration of objects that appear in different locations in rapid succession

Motion detection circuit ("Reichardt detectors")

(1) M neuron registers a change in position between A and B but...

- would also respond to 2 still cars

- would also respond to a car moving backwards

(2) Solution: add neuron D, which incorporates delay

Aperture problem

When viewing motion through a small aperture (window or receptive field), the actual direction of movement can be ambiguous

- small viewing area only captures part of the motion, making it hard to determine the true direction

Correspondence problem

The challenge of matching features from one frame to the next in motion detection

- Essential for tracking movement and perceiving motion correctly

Motion information from several local apertures (or receptive fields)

Can be combined to determine the global motion of the object

- There are several directions of motion within each aperture that are compatible with the stimulation the receptor is receiving

- whichever possible motion direction is the same in all apertures is the true global motion direction of the object

Smooth pursuit vs. Saccade vs. Vergence vs. Reflexive eye movements

Smooth pursuit: voluntary eye movement in which the eyes move smoothly to follow a moving object

Saccade: voluntarily and involuntarily eye movement in which the eyes rapidly change fixation from one object/location to another (3-4 times every second)
Vergence: voluntary and involuntary eye movement in which the two eyes move in opposite directions

Reflexive eye movements: automatic and involuntary eye movements

• ex: when the eyes move to compensate for head and body movement while maintaining fixation on a particular target

Microsaccade

Tiny, involuntary eye movements that happen automatically

- Sharpens details for clearer vision

- Prevents visual fading (keep vision stable)

- Helps see past blood vessels in the eye

- Compensates for vision loss outside the fovea

whats in the MICRO-SAC? Some Pricy tHC

Saccadic suppression

is the temporary reduction of visual sensitivity that occurs during rapid eye movements (saccades) to prevent motion blur and maintain visual stability

Cochlear Nucleus

The first brainstem region that receives auditory signals from the cochlea, where initial sound processing occurs.

Superior Olive

A brainstem structure involved in sound localization by comparing timing and intensity differences between ears

Inferior Colliculus

integrates auditory information from brainstem nuclei and assists in reflexive responses to sound

- midbrain structure

Medial Geniculate Nucleus (MGN)

A relay station in the thalamus that processes and transmits auditory information to the primary auditory cortex