Psyc236 Letures:
Lecture 1 – Intro
Sensation:
Sensation refers to how our senses (i.e. sight) transform physical properties of the environment (i.e.
patterns of light) into electric nerve signals, which are then relayed to the brain.
Sensation is the stimulation of our sensory organs (eyes, ears, skin, nose, tongue)
Perception:
Perception is the process of turning these neuronal signals into a meaningful experience. Like a
colour, or a face.
Perception is the “selection, organization and interpretation of sensory input.
Perception is conscious.
So when you are sleeping there may be sensation, but typically no perception.
Cognition:
Cognition refers to “all the processes by which sensory input is transformed, reduced, elaborated,
stored, recovered and used” (Neisser, 1967).
So this includes for example things like attention, memory, thought.
Perception and cognition:
There is obviously some overlap between what is considered perception and what cognition.
For example face perception cannot be perfectly separated from face recognition, the latter requires
memory.
We have 5 senses – Smell, taste, touch hearing and sight
Typical focus on visual perception
27 % vision = 250 cm2
8% auditory = 75 cm2
7% somatosensory
6% motor
0.5% olfactory
Visual perception:
Light (i.e. from the sun) shines on an object in the environment, where part of the light is reflected
and falls into our eyes.
There photoreceptors detect/measure the light and transform it into electric neuronal signals,
which are send to our brain. (sensation).
Then the visual cortex transforms, interprets this signals in very specific ways resulting in perception
of the world surrounding us. Perception, “I perceive; I see …”
We intuitively tend to understand perception as an objective, somewhat passive process, where we
neutrally observe our surrounding. q Nothing could be further from the truth, there is little passive
about perception (and less objectiveness than we like to believe).
Interestingly we say “ I perceive … “ semantically acknowledging the active role of the ‘I’. q Indeed
we even have a vivid perception of ’self’.
We take our perception as ground truth
Unified experience/parallel processing:
Probably because our brain is slow, and we are under time pressure visual perception consists of
several parallel processes.
Determining colour, texture, motion, position even faces or object categories occurs in parallel and
often independently and even at different speeds.
Yet we have a uniform percept: The binding problem.
When a tree is falling you can’t wait until you identified the tree before you take evasive action.
Visual perception is understood as very accurate, solving complex problems.
And if it’s inaccurate we typically ignore that because we don’t know any better.
Some difficulties
2 eyes, but see 1 world
Retina 2-D, but see world as 3-D
Move head, but world seems stable
Only get partial views of objects, but see complete objects
Blink, but see continuous vision.
Psychophysics:
Making physical measurements of Behaviour
Can be combined with eye movement recordings
Sebastien Millet, Harrold Hill, Me,
Simone Favelle, Steven Palmisano actually many more in some form
EEG:
Sort of similar setup + add in an EEG recording system
Instead of measuring behaviour, it measured brain activity
Bob Barry, Adam Clarke, Nadia Solowij, though often not so much measuring Perception and
Cognition per se.
fMRI:
Measuring brain activity, in that sense like EEG, but obviously very different kind of measurements.
Lecture 2:
Cones:
Three types for color
Up to two bipolar cells per receptor (divergence)
Low sensitivity (need proper light)
6-7 millions
Photopic vision
Barely 20 degress
Rods:
One type only
Many receptor cells per bipolar cell (convergence)
High sensitivity (good for night vision)
120 million
Scotopic vision
None in the fovea centralis (0.5 degree)
Anatomy of retina:
0.4mm thick layered structure:
3 dark layers of cell bodies
3 light layers of axons and synapses
Fovea:
High spatial resolution • Two bipolar cells per receptor (Divergence) • Low sensitivity (needs much
light) • 25% of ganglion cells (=axons to the brain) • Another 25% for parafovea • 1% of receptor
cells • Very high receptor density • Small receptors • Only cones
\
Periphery:
• Low spatial resolution • Many receptor cells per bipolar cell (convergence) • High sensitivity (good
for night vision) • 50% of ganglion cells • 99% of all receptors • Lower receptor density • Larger
receptors (sensitive) • Mostly rods
• While there is more cones than rods in the periphery and almost no rods (or even none in the very
foveola) in the centre that does not mean peripheral vision relies on rods only.
• Instead during day light even perception relies on cones – even in the periphery.
• Defining a clear boundary between fovea and periphery is difficult as there are a number of steps
/ boundaries at different eccentricities.
• Accuity decreases gradual without noticeable steps.
• Approximately: 0-2 degrees: Fovea 2-5 degrees: Parafovea 5-16 degrees: near periphery 60 to 90
degrees: far periphery
Types of ganglion cells/paths:
P-path: : Fairly small cells (midget ganglion cells and parvocellular cells in LGN). About 80%, small
receptive fields. High spatial resolution.
M-path: Large cells (parasol ganglion cells and magnocellular cells in LGN). About 10%, large
receptive fields. Fast. Respond to low contrast.
K-path: Small cells (bistratified ganglion cells and konicellular cells in LGN). 8-10%, large receptive
fields. blue on, red green off receptive fields
Visual span – approximately 180 degrees
3 types of ganglion cells in retina are part of 3 pathways
- Parvo system houses the midget ganglions
- Magno system houses the Parasol ganglions
-Konio system houses bistratified ganglions
Parvo path:
-
Fairly small cells, 80%, small receptive fields and high spatial resolution
-
Magno path:
Large cells (parasol and magnocellular cells) 10%, large, large receptive fields, they are blind
to colour, low spatial resolution but fast
Konio path:
Small cells (bistratified and koniocellular cells in LGN) 8-10%, large receptive fields, Blue on
(S-cones are rare), red green off receptive fields
Week 2 – Color perception:
-
White light:
Mixture of different lights frequencies.
Week 4 – Lecture 1:
Size perception:
Delboeuf Illusion:
Alice in Wonderland Syndrome which involves the distortion of perceived size as well as
of distance and self body size. Imagine how disturbing misperceiving size might be and,
conversely, how being able to explain that this occurs might help reduce anxiety.
Keywords:
Size: visual angle spatial frequency perceived size
Size constancy: Size distance scaling emments law
Illusions: Ponzo, Titchner, Ames room
Theories: Constructivist, Direct
The problem:
-
-
“The problem” is that the size of the image arriving at the retina is a function of
both the size and of the distance from us of the object that we are looking at in
the world.
a small image could be of a small object relatively close or a much large object
further away.
-
Geometrical optics allows us to determine the size of the image if we know the
size of the object and its distance, what the brain has to do is the opposite:
determined the size and distance of the object knowing only the size of the
image. This is like having one known but two unknowns.
-
The size of the object is the distal stimulus but the visual system only has retinal image size
the proximal stimulus.
-
The geometry of image formation, geometrical optics, means that the image of
an object that has a constant size in the world will vary as a function of viewing
distance as shown below
-
Size is inversely proportional to viewing distance hence double the distance and you halve
the image size.
The two trees are the same size (above) but the size of their images is very
different. The image of the one twice as far away is half the size. Some, despite
this, we experience size constancy, that is objects do not appear to change in
size as a function of viewing distance. A tree does not appear to grow as we
approach it even if we are aware that it takes over more and more of our field of
view, what we can see.
Geometry: Visual angle:
-
-
Visual angle is used as “A measure of image size on the retina, corresponding to the
number of degrees the image subtends from its extremes to the focal point of the
eye” Palmer (1999) “Vision Science: Photons to Phenomenology” (Italics in original).
This is illustrated where the visual angle subtended by an object (the bar)
increases as its distance from the eye decreases although the size of the bar itself
does not change. The angle referred to is the angle between the lines where they
cross.
Use visual angle to describe the size of the proximal stimulus on the retina. 1º of visual
angle corresponds to 0.288mm on the retina in humans. The width of your thumb at
arm’s length subtends 2º and can be used to measure the approximate visual angle of
objects.
Visual angle equation:
H = Height of object
A = visual angle
D = distance between object and eye
Arctan = the inverse of the trigonometric tan function. Estimated for small angles being <10 degrees)
Physiology:
The receptive fields of receptor cells are (retinal image) size specific - they only respond
to light from a limited area on the retina. This is also true of ganglion cells including
ones with centre surround organisation - the centre and the surround have clearly
defined sizes.
-
receptive fields are thus well suited to encoding retinal image size - their
response to a stimulus will vary as a function of the size of the stimulus (a circle
of light above). However, this does not solve "the problem" as the same cells are
agnostic with respect to (do not know about) distance and, as we have
seen, retinal image size is a function of viewing distance as well as object size.
-
V1 receptive fields come in a range of sizes (as illustrated above) and thus well
suited to encoding a range of retinal image sizes (but still do not encode viewing
distance. They respond best to an image of a certain size regardless of how far
away the object projecting that image is).
After effects. Psychologist micro- electrode:
After-effects can be used to investigate how physical properties are encoded by the
visual system.
Spatial frequency:
Counting the number of bars" in a given area is more formally referred to as spatial
frequency and defined as the number of cycles in a degree of visual
angle (c/deg.). See STT Figure 4.2 below.
Formal experiments (e.g. Blakemore and Campbell, 1969) have used adaptation to
characterise the spatial frequency response of the human visual system. For example the
data blow show the effect of adapting to a 7.1 cycle/degree grating
T he results show that sensitivity (left) reduces most for the adapting frequency and
effects close frequencies to a lesser extent.
Perceived size:
What do we perceive?
STT Figure 4.25 below shows "objects" A and B that are the same size and object C that
is half the size.
Viewed from the same distance object C would have twice the spatial frequency as
objects A and B. However when object B is presented twice as far away its spatial
frequency (and retinal image size) will now match that of object C.
The responses of cells tuned to spatial frequency would now be the same to B and C but
different to A although "in the world" B is the same size as A not C. Is that what we see?
The size of images on the retina is not important, the size of objects in the world is.
When asked to judge spatial frequency (size) of objects presented at the same
distance people can easily judge either object or image size (because size is all that is
changing).
However when the objects are presented at different distances people find it easier
to judge whether or not object size matches than image size. Put another way we
see that A and B above as the same size (which they are!) even though the retinal images
of B and C are more similar.
This demonstrates that humans show size constancy, the "ability to perceive the
real size of objects regardless of their distance from us” STT p.122
Size contancy:
Size constancy, the “ability to perceive the real size of objects regardless of their distance
from us” (STT p.122) can usefully be considered the goal of size perception. To successfully
interact with the world we need to know about the size of objects, not the size of images.
Holway & Boring (1941)
✎ EditSign
conducted a classic psychology experiment to test size constancy.
The Observer's task was to adjust the size of a comparison stimulus (Sc) presented at a
constant distance (Dc) of 10 feet (~3 m) until it matched the size of a standard stimulus
(Ss)which was presented at variety of distances (Ds). The Observer (O) was seated at the
corner of a corridor and so could choose to look at either the comparison or the
standard (not both) at any one time.
The comparison stimuli were designed so that they always projected the same visual
angle (1°). i.e. the ones further away were bigger than the closer ones (10' indicates 10
feet)
Holway and Boring predicted two possible patterns of results depending on whether
people responded on the basis of visual angle or objects size. Responding on the basis
of visual angle should mean that the comparison circle was always adjusted to the same
size (as the visual angle of the standard stimulus did not change). If the observers
responded on the basis of object size they should adjust the comparison to be
bigger for the more distant stimuli (as these were bigger!). They refer to these
competing predictions as the law of visual angle and the law of size constancy
respectively.
As well as varying distance and size of the standard stimuli, Holway and Boring also
varied the visual information about depth available on the basis that accurate
perception of depth may be necessary for size constancy. Most depth was
available with both eyes open and least with one eye looking through an artificial
pupil (1.8 mm pinhole) and a reduction tunnel (poster tube?!) the blocks out
environmental cues to depth. The results are shown below.
The take home message is that when multiple sources of information about depth were
available binocularly (both eyes open)Observers were pretty good at matching the
comparison stimulus to the actual (distal) size of the standard i.e. they showed size
constancy. However when little information about depth was available and all they could
see was the circle itself their adjustments were more in line with matching visual angle.
The results suggest that size constancy can be achieved but that it depends on
information about depth being available.
Size distance scaling:
The Holway and Boring (1941) results suggest that the perception of distance is critical
to being able to perceive object size and achieve size constancy. One possibility is that
the brain in effect does inverse optics/geometry. As we saw the size of an object and its
distance determine visual angle. If distance is known (a big if!) then this relationship can
be reversed and visual can be used to determine size.
Emmerts law = for a given retinal image size, perceived size is proportional to
perceived distance. Equation:
S = perceived size
K = a constant
R = retinal image size
D = perceived distance
This effectively reverses the geometrical rule of image formation that, for a
given object size, image size is inversely proportional to distance.
The Ponzo illusion:
The Ponzo illusion is a classical geometric illusion first published by Ponzo in 1911. As
you probably know the two horizontal lines are the same length but people normally
report experiencing the upper one as longer.
Although they are actually the same distance from you on the screen the top
line appears to be further away thanks to the converging parallels. Size distance
scaling would explain this as the size of the upper line would be scaled by its greater
perceived distance.
The simple geometrical illusion on the left can be thought of a reductionist stimuli
where only thee key elements remain (if you got rid of the converging lines the
illusion should no longer work). A more complicated scene like the on the right can
work as well or better.
With regards physiology there is evidence that the V1 response reflects perceived size
not just image size, at least when the illusions is attended to suggesting top-down
influences (Fang, Boyaci, Kersten et al 2008). V1 involvement is also suggested by
findings where the inducing components (the converging lines) are presented in one eye
and the test components (the bars) are presented in the other eye (Song et al 2011).
The responses of single cells in macaque V1 are also claimed to reflected perceived size (Ni,
Murray, and Horwitz, 2014). Macaques, and all the other species that have bene
tested (including rats, pigeons and horses), appear susceptible to the Ponzo
illusion. This is also the case for human infants from around 7 months old (Yonas,
Granrod, Arterberry & Hanson, 1986). Children who have sight restored having been
blind from birth are reported to be immediately susceptible to the Ponzo illusion
(Gandhi, Kali, Ganesh and Sinha, 2015).
Ponzo, Theoretical explanations:
There are a number of explanations of the Ponzo illusions which suggests none of them
are right. While misapplied constancy scaling would appear to explain the classical
version of the illusion and relate nicely to accounts of size constancy that involve scaling
retinal image size by perceived distance, misapplied size distance scaling does not
appear to explain many variants of the Ponzo illusion.
Constructivist theories like Gregory's start from an assumption that the retinal image is
inadequate and ambiguous. As retinal image size is a function of both distance and objet
size the image alone is not sufficient to support or explain perception. Gregory viewed
perception as very much like science with the brain testing hypotheses against the available
data (the image). Sideways rules, such as scaling perceived size by perceived distance, and
"top-down" knowledge based on experience are both also required to interpret the image.
Alternative explanations emphasise "bottom-up" effects of local properties of the image
over a global scene based interpretation. For example if the upper bar gets assimilated
(joined to) the oblique lines due to its proximity that would simply explain why it appears
bigger. Other explanations invoke size scaling by local background information, not
unlike the Titchner or Ebbinghaus illusion (STT figure 4.14)
It is not immediately clear how this can be applied to the simplest variation of the Ponzo
illusion unless the gap to the oblique lines provide the context more like the concentric
circles of the Delboeuf illusion. A role of the background in scaling apparent size would
certainly be possible when the bars are shown.
The Ames Room:
1. A reduced change in apparent size has been claimed for people, particularly
females, viewing their significant other (Dion & Dion, 1976). Labelled the Honi effect
(Honey effect?!) this may not be entirely reliable (Ong, Luck & Olson 1980) limiting its
possible application as a lovemeter.
Direct perception of size:
As explained briefly during the lecture drop-in a direct perceptionist in the tradition of JJ
Gibson would argue that there are in variants in the structure of the optic array, the
pattern of light reaching a point that directly specify size. This avoids any need to take
distance in to account when inferring size.
Two touch invariants are the number of texture elements occluded and the horizon
ratio. These are outlined and illustrated next.
Do all the red disks ("checkers") below look the same size? Hopefully the two lower in
each image but how about the two higher ones? Does theone in the first or the second
image look bigger? According to the Gibsonians the checker that covers (occludes)
most checks (texture elements) should look biggest. i.e the one higher up in the second
image. In terms of retinal image size (or size on the screen) the one higher up on the left
is smaller than the other three.
Clearly we do not live on a checkerboard but statistical properties of ground coverings
like grass (e.g. density of blades) would perform the same function IRL (in real life)
The constructivists might argue that it looks bigger because it looks further away and
size distance scaling has been applied by the brain. More on Gibsonians and
constructivists in the final lecture but, basically, these are two theories visual
perception. Misapplied constancy scaling is a constructivist approach while the number
of occluded texture elements occluded is a Gibsonian invariant directly available from
the light reaching the eye..
Horizon Ratio:
Horizon ratio (Sedgwick 1973)is another Gibsonian invariant that might allow us to
perceive size directly. It is illustrated below.
Hopefully the two cylinders look about the same size in the world though one is clearly
smaller in the image. The Gibsonians would argue that is because the horizon ratio is
the same in both cases. The horizon ratio is the amount the cylinder sticks up above the
horizon cpompared to the amount that is below the horizon (the ratio of those
two heights). This is labelled below.
The ratio of the two red arrows should be the same in each case indicating that the
cylinder is the same height.
The fact cylinder cuts the horizon also tell you that the cylinder is bigger than you (so
don't mess with it!). This is because the horizon is at your eye height all illustrated
below. The line of sight that goes to the horizon is approximately horizontal i.e. at you
eye height
Ponzo variant:
Do the men all look the same size? Can you explain this variant of the Ponzo illusion in
terms of misapplied constancy scaling? Can you explain it in terms of texture element
occlusion and/or horizon ratio? Remember the vanish point, where parallels lines
converge to, would be on the horizon.
Week 5:
Lecture 1 – Depth Perception:
Types of distance and depth cues:
1.
2.
3.
4.
Oculomotor cues
Pictorial Cues:
Stereoscopic cue
Motion cue
Texture gradients:
Equally spaced texture elements of equal size (blades of grass) will appear to be packed closer
together as distance increases
These texture elements might be used as a scale to judge both distance and size
Properties of texture gradients:
An object of equal size will cover an equal number of texture elements
•
An object that is twice as far away will have twice as many texture elements between it and
the observer
•
e.g. The further cylinder is twice as far away as the near cylinder (and both are the same
size).
Does foreshortening tell you about depth?
•
Orientation is the first derivative of depth
–
•
The rate of change of depth
Curvature is the second derivative of depth
–
The rate of change of orientation….
–
General point: Depth perception is closely related to the perception of 3D shape
Pictorial Cue:
Familiar size:
•
Under certain conditions, knowledge of an object’s true size can influence our perception of
its distance from us
•
Epstein (1965) Experiment - observers were presented with equal sized photo’s of a dime, a
quarter and a 50 cent coin in a darkened room.
•
These photos were physically positioned at the same distance from observers and
illuminated with a spot of light
•
When viewed with one eye, the dime was perceived to be nearer than the quarter, which
was perceived to be nearer than the 50 cent coin.
•
•
Can potentially provide absolute depth
–
•
Whether it does or not is an “empirical question”
Familiar size has been used historically as a range finder for artillery (Morgan, 2003)
–
At what distance from the observer does a model soldier of known size exactly
match the real soldier?
Relative and familiar size and opacity:
•
Nearer objects will o_ _ _u_e further ones
•
Perspective is a combination of relative size and _o_e_ _o_ _e_i_ _
•
Familiar size is a potential cue to a_ _o_u_e distance but the Ames room demonstrates that
it can be overridden
Position relative to horizon:
•
Height in the visual field is a cue to depth order and relative depth:
–
objects below the horizon appear to be further away when they are higher
–
objects above the horizon appear to be further away when they are lower
•
The horizon can be used as a reference point to determine distance
•
There are three types of horizon:
•
Geometrical horizon: where horizontal lines converge
•
True horizon takes into account the curvature of the earth
•
Visible horizon is the most distant visible boundary in the scene
Atmospheric Perspective:
•
Not all pictorial cues are based on geometric effects of distance between viewer and
object/environment
•
For example, distant objects often less clear, due to particles in the air
•
May also be partially caused by differences in clarity of detail (spatial frequency)
Shading and lighting:
•
The variation in light coming from a surface as a function of its angle with respect the light
source
•
For a Lambertian/matte surface this in independent of the viewing angle.
Shading is ambiguous:
•
Equivalent convex and concave (hollow) surfaces lit from opposite directions give rise to
identical images
Assumprtions:
•
Light comes from above + objects are convex
Stereoscopic cues:
Stereoscopic cues are used in 3-D movies etc to make objects appear in front or behind the screen.
We have 2 horizontally separated eyes with overlapping visual fields.
As a result, the left eye has a slightly different view of the same scene to the right eye.
Motion CUES:
•
Perception is almost never static
•
Either the observer or the object (or both) are moving
•
This motion provides information about the 3-D layout of the environment and the shape of
objects in it
Kinetic occlusion Cue Acceleration/ Deletion
Motion Parallax:
•
As your head moves relative to objects, nearer objects appear to move faster than further
away objects
•
The relative speed of the objects movement provides powerful cue to their relative distance
•
Also the direction of their perceived movement changes with fixation
•
Objects further than the fixation point move in the direction of the observer’s head
•
Objects closer than fixation point move in opposite direction to the observer’s head
•
Points closer than the point of fixation will move in the same/opposite direction as/to the
observer’s direction of movement
•
As distance from the point of fixation increases, image movement speed will
increase/decrease
Cue Combination:
•
No one cue dominates
•
Compliment and compensate for each other
–
•
Provide different types of information based on different evidence
The more cues the better the impression of depth
Palmer, S. (1999) Vision Science
No occlusion
Absolute + quantitative = absolute egocentric depth
Relative + quantitative = relative
Relative + qualitative = Ordinal or 3D shape/slant and curvature
Lecture 2 – Object recognition:
Detection of target picture:
Humans are able to recognize objects through recognition of what is meant to be observed
Eg. Captcha quizzes
Whats the problem?
•
Scene segmentation
•
•
•
What is object and what is background?
Viewing conditions
•
Viewpoint
•
Lighting
Partial occlusion
Obscuring vison in a isolated spot preventing visual expectations of an image. Eg Wearing sunglasses
causes a partial occlusion when visualizing a face
Visual Agnosias:
•
Simultagnosia:
-
Simultanagnosia (or simultagnosia) is a rare neurological disorder characterized by
the inability of an individual to perceive more than a single object at a time.
•
Apperceptive/Associative –
-
is a failure in recognition due to deficits in the early stages of perceptual
processing. Associative agnosia is a failure in recognition despite no deficit in
perception. Associative agnosia patients can typically draw, match or copy objects
while apperceptive agnosia patients cannot
-
Associative: can copy and describe* and match but not name shapes.
-
Apperceptive: cannot copy or describe or match shapes. Can draw from memory. Can also
recognize object by touch
•
Prosopagnosia (face blindness) - means you cannot recognise people's faces. Face
blindness often affects people from birth and is usually a problem a person has for
most or all of their life. It can have a severe impact on everyday life.
•
Object agnosia
•
•
Animate/inanimate
Alexia (reading)
inability to recognize or read written words or letters, typically as a result of brain damage.
What is the Aim?
•
To know what is where by looking” Marr (1982)
•
•
What (ventral) and where (dorsal) pathways
Shape constancy
•
Ability to perceiving an object as having the same shape despite changes in the
retinal image of that object
Wolfe 2021 – path of perception:
2D image based:
Naïve template making:
Invariant features:
Bruce, Green & Georgeson (2003) Visual perception: physiology, psychology and ecology. Chapter 9
Soviet tanks all have T in the name and have the invariant feature of a rounded rear turret
O’Kane, Biederman, Cooper & Nystrom (1997)
Pandemonium model:
A method for combining simple visual features?
Classic model
Can predict likely mistakes (shared features)
Problems with this account
Does not code relations between features or number of features
Recognition by components:
Parts based recognition scheme.
Non-Accidental Properties:
Non accidental image properties (NAP)
Image properties that are invariant over orientation and depth.
Lowe (1985)
Co-linearity
Curvilinearity
Symmetry
Parallelism
Co-termination
Lowe (1984)
Edges associated with depth and orientation discontinuities
Same in the image and the world
For all non-accidental viewpoints
Relations between Parts:
•
Geon structural description
•
Non accidental relations
•
Relative size (G1>G2, G1=G2, G1<G2)
•
Verticality (G1 above/below/side G2)
•
Centering (End-to-end, end-side centered/not centered)
•
Relative size of joined surface (longer/shorter)
Evidence against: Viewpoint dependence:
Week 6
Week 7
Week 8:
Lecture 1 – Cognition:
How do we know the outside world?
Cognition:
-
The acquisition, storage, retrieval and use of knowledge
Includes perception, attention, memory, language, problem solving, imaging and reasoning
Cognitive psychology = study of mental proesses we use to make sense of our environments
Brief history of cognitive psych:
-
Looking inward – considering the inner workings of the mind
Rejecting inner processes as acceptable objects of study
Rejecting the rejection – taking up the challenge to scientifically explore mental processes
Scientific
Data are observable (and quantifiable)
Brain is the seat of cognitive processes
Functional
Not tabula rasa
Structuralism:
 Understanding the elements of
consciousness & structure of mind
 Wilhelm Wundt - First Psychology lab (late 1870s)
 Application of the scientific method to psychology
 Method of introspection - systematically vary a stimulus and observe the effects
 Describe experience in basic terms
 Thoughts, images, feelings
Functionalism:
•
Psychologists should examine the processes of the mind rather than the contents
•
William James (1890)
•
Function and pragmatism
•
Study of consciousness, “Stream of thought”
•
Learning through association
•
Psychology as a natural science
Behaviourilsm:
•
Emerges 1913, dominant from 1920s - 1950s
•
James Watson and B.F. Skinner
•
Only observable behaviour can be studied
•
No role for mental representations
•
All behaviour learned through conditioning and explainable as chains of stimulus-response
connections
•
Investigating behaviour requires environmental control and directly observing
organism response
•
Behaviour shaped by the presence/absence of rewards/punishments
•
Contiguity, frequency and reinforcement
Counters to behaviourism:
-
Reinforcement not needed for learning to occur
The specific example of human language
Information processing post WWII
Unshaped behaviour:
Learning is not always constrained by environment or S-R relationship
Chomsky’s challenge
 Chomsky (1959) - “scathing review of Skinner’s ideas”
 Behaviourist principles cannot explain human language abilities
○ Language is creative
○ Language is not constrained by reinforcement contingencies
The information age:
 Post WWII
 Information transmission (e.g.,
 Development of computer technology
 Information theory
Information processing:
 Miller (1956): 7 ± 2 the capacity of short-term memory

Mental processes demonstrated information processing qualities
○
○
○
Broadbent (1958) - described a human information processing system
Neisser *1967) cognitive psychology
 Behaviourism is inadequate because it does not yield any insight into how people think
 Cognitive psychology is


“…all the processes by which the sensory input is transformed, reduced, elaborated,
stored, recovered and used."
Neuroimaging:
•
Cognitive neuroscience approach to human cognition
•
PET
•
EEG/ERP
•
Magnetic Resonance Imaging and fMRI
•
TMS
Magnetic resonance Imaging (MRI)
Maps brain anatomy/structure
Powerful magnetic field aligns protons, disrupted with RF pulse
Records energy signal of protons returning to alignment
Functional MRI (fMRI)
•
fMRI detects changes in blood flow over time (i.e., during task performance)
•
•
BOLD (blood-oxygen-level dependent) effect
Good spatial and temporal resolution
Transcranial Magnetic Stimulation:
•
Large magnetic pulse creating virtual lesions -> causal inferences
•
Map cortical activity
•
Limited spatial resolution
Advantages of functional neuroimaging:
•
Can help localise function in healthy controls
•
Has revealed activity in areas previously thought to be uninvolved in cognition (e.g.
cerebellum)
•
Can be combined to provide converging evidence
So why not rely?
•
Imaging provides descriptive information.
•
•
How does neural activity result in mental phenomena?
•
Imaging reveals associations, not causality
•
fMRI has been called “phrenology with magnets”
•
•
Ecological validity of tasks
•
Measurement issues
Cognitive Neuropsychology:
•
Aims to relate theories of cognitive function to knowledge of brain structure and function
•
Use of clinical and normal or “typically developed” populations
•
Localize where and when cognitive processes occur within brain structures
•
Implications for model confirmation/development
•
Constraints for theory, e.g.,
Assumptions of Cognitive Neuropsychology:
Modularity - Large number of fairly independent processing modules
•
Functional specialisation
•
E.g. AV entertainment system
•
Neurological specificity (isomorphism) - there is a correspondence between the
organisation of the mind and the organisation of the brain
•
> both modularity & specificity lead to the locality assumption
•
Transparency - observable behaviour will indicate which module is dysfunctional
•
Subtractivity - Performance reflects total cognitive system minus the impaired module(s)
•
Universality - There are no individual differences in the organisation of cognitive modules
Associations:
•
Implies a link or connection between two phenomena
•
Between two cognitive deficits
•
•
Between a cognitive deficit and a lesion site
•
•
e.g.
e.g.
Problems:
•
Determining causality, nearly always exceptions
•
May have damage to more than one process
Dissociations:
Patient A: Performance on task X impaired, but performance on task Y intact
•
E.g. task X =
task Y =
•
Implication is that tasks are handled by different sets of cognitive processes.
•
But…
•
It could be argued that tasks X and Y involve one process (e.g. recognition of "something")
but that one is a very hard task and the other is a much easier task.
Double dissociations:
Patient B: Performance on task X intact, but performance on task Y impaired
•
E.g.
•
The performance of patients A & B together provide a double dissociation
•
Strong evidence that there are cognitive processes involved in Task X that are not involved
in Task Y and vice versa > modularity
Lecture 2 – Models of cognition: Information processing and neural networks:
-
Learning outcomes:
Describe and compare the information processing (IP) and neural network (also known as
connectionist) models of cognition
Provide an example of an IP and a neural network model of cognition
-
Discuss the advantages and limitations of IP and neural network models
Information Processing approach:
Computational approach: Marr, 1982
-
-
Mental processes could be understood as information processing events ( obiding by a set of
laws)
Components cannot be understood in isolation ( being part of a system)
Fundamental components of an IP system:
A representation is a internal model of the external world
Processes are the active parts which transform or operate on information changing one
representation to the next.
Information processing model of object recognition:
•
Stage (hierarchical) model of object recognition (Riddoch & Humphreys, 2001)
•
Structure (representations and processes)
•
Evidence
•
Neurophysiological evidence:
Feature analysis – analysing certain characteristics of an object in order to identify it
•
Hubel & Wiesel (1962) single cell recording in the visual cortex of cats
Clinical evidence:
-
Visual agnosia – charaterised by having an inability to visually recognize objects despite
having intact knowledge of the objects characteristics
Impairment is perceptual and cognitive however not sensory
No loss in intelligence – don’t have to be “dumb for this to happen”
Different types of agnosia:
•
Agnosics may have difficulty recognizing the geometric features of an object (apperceptive
agnosia)
Or they may be able to perceive the geometric features but not know what the object is used for
(associative agnosia)
Apperceptive agnosia:
CAN: name colours, navigate, distinguish areas of brightness, detect edges of shape
CAN NOT:
•
recognise objects
•
copy simple shapes
•
match shapes
•
When patients are able to identify objects, they do so based on inferences using colour,
size, texture and/or reflective cues to piece it together.
•
E.g., fail to discriminate despite clear differences in shape and surface features
Herpes simplex Encephalitis Patients
•
Problems with recognising or describing objects, typically natural/living objects.
•
Case study Giulietta (Sartori et al, 1993)
•
Can distinguish and match overlapping figures
•
Unable to draw from memory or match parts to whole objects
•
Difficulty with verbal descriptions of visual form
•
Can make semantic decisions
Associative agnosia:
Perception is intact
Can match and copy objects
Impairment is to the association of the percept to its meaning – perception without meaning
Eg: Patient JB:
•
Poor at associative matching task with objects (but not with words), thus intact associative
knowledge
Anomia:
•
Intact visual and semantic knowledge
•
Can match and copy objects, do object decision tasks, describe objects, etc
•
Inability to name things, people, and places
•
Anomic patients cannot reliably find and use nouns in conversation.
•
Frequent use of thing and stuff.
The connectionist Model:
•
•
Neurally inspired
•
Based on assumption that cognition depends on the millions of interconnected
neurons in the brain – “Neural Networks”
•
Biologically plausible
Timing issue
•
Processing would take too long if done in sequential steps
Connectionist models and brain structure:
•
Units = neurons
•
Activation = firing rate
•
Connections = synapses
•
Connection weight = synaptic strength (excitatory or inhibitory)
Parallel distributed processing – PDP
•
Large number of small, independent, yet highly interconnected units processing simple
functions in parallel
•
All processing is assumed to be parallel
•
Parts are processed simultaneously with the whole (interactive)
Localized vs Distributed Representation:
Concepts represented by single units or distributed patterns of action
Localized coding: 000000001000 – Can represent 12 different concepts
Distributed coding: 010001100101 – can represent 212 or 4096 different concepts
Localized representation:
•
Each unit or node represents a property or proposition
•
•
Word nodes, sound nodes, feature nodes
Jets and Sharks example (Westside Story) McClelland (1981)
Distributed representation
•
Representations are stored as a pattern of activation across a set of units
•
Two classes of distributed representation:
•
Units may represent conceptual primitives or
•
Units may have no meaning as individual elements
Distributed representation
•
Representation are stored as a pattern of activation across a set of units
•
Two classes of distributed representation:
•
Units may represent conceptual primitives or
•
Units may have no meaning as individual elements
Advantages of distributed representations
•
Economy – provides high information capacity over few units
•
Generalisation – capitalises on similarity when dealing with new stimuli (general and specific
information)
•
Learning - can explain how the “adult” system came about
•
Graceful degradation - if the system is damaged it does not collapse completely but shows
impairment in function directly related to the magnitude of the damage
Disadvantages of distributed representations
•
Can be difficult to decipher exactly what is going on in the network
•
Resemblance to the brain is fairly superficial
•
•
Fails to capture the full scope of cognitive phenomena
•
Week 9
Different types of neurons
E.g., emotion, social dimensions