Psych 240 Exam 3 princy

conceptual knowledge

knowledge that enables us to recognize objects and events and to make inferences about their properties

concept

mental representation of a class or individual

categorization

the process by which objects are placed in categorical groups; include all possible examples of a particular concept

what do categories allow us to do?

enable us to understand individual cases not previously encountered; without them we'd be constantly mystified/helpless

what are categories

pointers to knowledge that provide lots of general information from which we can focus on unique characteristics

definitional approach to categorization

determine category membership based on whether the object meets the definition of the category

major problem with definitional approach

not all (commonly agreed) category members actually meet the definition—e.g., "chairs"

Wittgenstein's Family Resemblance

Category members resemble one another in various (but not all) ways; led to prototype idea where you "reference" a category member

prototype approach to categorization

membership in a category is determined by comparing the object to a prototype that represents the category

prototypes are usually

highly typical members (ex. robin for "bird" instead of penguin)

strong relationship between prototypicality and family resemblance

rosch and mervis: list common features of various objects to find that highly typical category members shared many features w/other members and vice versa

typicality effects

exemplars that are more average or normal for a given category are likely to be listed first when people are asked to name exemplars of that category, and are more rapidly verified as category members

exemplar approach to categorization

the approach to categorization in which members of a category are judged against exemplars, examples of members of the category that the person has encountered in the past

Advantages of exemplar approach

Easily takes into account atypical cases

By remembering unique cases instead of always using "average"

For example: some birds don't fly

Easily deals with variable categories

Don't have average for "games"

Lots of different examples (video games, football, chess)

can be used along with prototypes

categories are hierarchically organized

Categories are hierarchically organized from more specific to more general

Evidence that Basic-Level Is Special

-Going above basic level results in a large loss of information

-Going below basic level results in little gain of information

semantic networks

Maybe concepts are arranged in (semantic) networks that represent how they are organized in the mind

Hierarchical semantic network model

a model of semantic memory organized in terms of nodes and links that stores properties at the highest relevant node to conserve cognitive economy

cognitive economy

shared properties are only stored at higher-level nodes

Hierarchical semantic network model prediction

verifying properties should take longer the more "nodes" must be traversed (longer "distance")

spreading activation

when concept presented, relevant node activated; when node activated, activity spreads among all connected links (semantically related concepts, properties, etc.)

"lexical decision" priming task

present pairs of words or nonwords, when both are words some are related and some aren't, result shows faster RT for related words which shows spreading activation (today show a single word then between related or not)

criticisms of Hierarchical semantic network model prediction (C and Q)

Cannot explain some typicality effects (some things are verified faster even when node time is the same);

little evidence for cognitive economy/inheritance (ex. wings also stored at canary node);

some sentence-verification results are problematic (pig is animal is verified faster than pig is mammal)

connectionist approach to categorization

connectionism is the approach to creating computer models for representing cognitive processes (aka parallel distributed processing)

linked units

Input units: activated by stimulation from environment

Hidden units: receive input from input units

Output units: receive input from hidden units

connection weights

determine how much activation one unit can pass on to another unit

How do connectionist networks learn?

- don't have knowledge "programmed in"

- so...typically begin with equal or random response parameters

- then, "train" network over many trials

- stimulus is given to begin and illicit network response;

correct response is given and error signal is generated

Back-propagation

process wherein error signal transmitted back through the circuit; process repeats until error signal is zero

promise to connectionist approach

Much success in simulating many cognitive processes and seems analogous to real brains/neurons (can explain generalization of learning and exhibits graceful degradation: disruption of performance occurs gradually as parts of the system are damaged)

how are concepts represented in the brain?

maybe various brain areas specialized to process information about different categories

sensory-functional hypothesis

derived from finding that some brain-damaged individuals have trouble categorizing animals, but not artifacts (or reverse); maybe we categorize animals w/sensory info, artifacts by function but inconsistent evidence

semantic category approach

proposes that there are specific neural circuits in the brain for some specific categories; not on sensory vs functional basis

multiple factors approach (property cluster)

examines how concepts are differentiated from each other as function of various kinds of properties, not identifying specific brain areas/networks for existing concepts; discover how properties cluster within various categories; "crowding" may differentiate some concepts

Embodied approach to categorization

our knowledge of concepts is based on reactivation of sensory and motor processes that occur when we interact with the object

Mirror neurons (example of perception/action connections)

fire when we do a task or when we observe another doing that same task

Semantic somatotopy

correspondence between words related to specific parts of the body and the location of brain activity associated with that part of the body; not always observant of impairment

Hub & Spoke model

proposal that different areas of the brain are connected to the anterior temporal lobe; some patients with anterior temporal lobe damage have semantic dementia

trouble with identifying all objects, not just particular categories

the ATL integrates info from more specialized category areas

Porbric et al. (2010)

- Used TMS to stimulate ATL or parietal (spoke)

- When TMS impaired ATL, trouble naming both artifacts and living things

- When TMS impaired certain parietal area, only trouble naming artifacts

Mental imagery

experiencing a sensory impression without sensory input; have imagery in various sense modalities (hearing, taste, etc.)

Visual imagery

"seeing" in absence of visual stimulus; another important form of cognition--nonverbal

Wundt and Imagery

proposed 3 basic elements of consciousness: sensations, feelings, and images

Imageless thought debate

discussion about whether contemplation is possible without pictures

Imageless thought debate - Aristotle

claimed thought impossible w/out images

Imageless thought debate - Galton

noted some w/lousy visual imagery think just fine

Imageless thought debate - Smallwood

good evidence for imageless thought, uses random prompts for participants to note ongoing mental processes; sometimes imageless thought reported

Paivio (1963, 1965)—early cognitive paradigm used paired-associate learning

study pairs of words; first word used as recall cue at test; varied whether words were concrete or abstract

imagery easier w/concrete (vs. abstract) words;

result is that memory was better for concrete words

"Conceptual-peg" hypothesis

concrete words allow forming visual images that other words, items, etc. can "hang onto"

Mental rotation

vary angle of comparison shape, measure response RT

Result: RT increased linearly w/angle (to max--180°)

Do imagery and perception share the same mechanisms?

If so, perhaps we "scan" visual images in similar fashion to how we "scan" (actually) seen objects

Kosslyn (1973)—classic study

Memorize picture (boat), create an image of it

Participants first focused on one part of the boat, then asked to "look" for another part—measured RT for verifying

Result: Longer RT to check "longer distances" in image

Early support for similar imagery/perception mechanisms

Lea (1975)

More distractions when scanning longer distances may have increased reaction time

Kosslyn et al. (1978)

Island with 7 locations, 21 trips

It took longer to scan between greater distances

Visual imagery is spatial (like perception)

"imagery debate"

Is imagery spatial or propositional?

Pylyshyn (1973)

Spatial representation is an epiphenomenon

Accompanies real mechanism but is not actually a part of it

Proposed that imagery is propositional

Can be represented by abstract symbols

Pylyshyn (2003)

Kosslyn's results can be explained by using real-word knowledge unconsciously

Tacit- knowledge explanation

Finke and Pinker (1982)

First, briefly presented display w/four dots

Then, second display w/arrow appears

Participants judge whether arrow points to dots previously seen

Not instructed to use visual imagery

No time to memorize, no (prior) tacit knowledge

Key result: Longer RT when greater distance between arrow and (previous) dot

supports mental spatial/"traveling" imagery idea

Relationship between viewing distance and ability to perceive details

Imagine small object next to large object

Quicker to detect details on the larger object

Kosslyn (1978): tried this with imagery

Imagine two animals (e.g., rabbit/elephant or rabbit/fly)

"Zoom in" or "out" until larger animal fills visual field

Then...(critical task):

Ask questions about rabbit features (e.g., have whiskers?)

Result: faster RTs when rabbit "large" vs. "small"

Also... "mental-walk" task w/single imagined animals

"Zoom in" in imagination until animal fills visual field, estimate distance

Result: Move closer to small animals than to large animals

Again, support idea that images are spatial, like perception

Do perception and imagery interact?

perhaps share same/similar mechanisms

Perky (1910)

projected faint images, participants imagined same object

- reported images closely resembled projected ones

- participants didn't realize projected images were present

- so...images and actual visual stimuli seem confusable/similar

Farah (1985)

- participants initially imagined "H" or "T", then either H or T actually presented (briefly), accuracy calculated

- Result: better performance when prior image matched actual stimulus

- again suggests that imagery and actual perception closely related

"imagery debate" resolution

Not quite: still possible to alternatively explain many results as using tacit knowledge, etc.

For example: "Zoom-in/zoom-out" studies

BUT: perhaps neuroimaging approaches will aid progress

Kreiman et al. (2000)

Record individual neuron responses to perceiving vs. imagining object—same neurons respond

Le Bihan et al. (1993)—fMRI study

Both real & imagined (visual) stimuli activate similar areas in visual cortex

what do some studies suggest?

perception vs. imagery differences (i.e., only partial overlap)

Ganis and coworkers (2004)--fMRI

again, compare real vs. imagined visual stimuli

very similar activation for both in front & middle brain

BUT: much stronger activation for real stimuli in visual cortex (back of brain)

Amedi et al. (2005)—fMRI

as usual, various similar activations for real vs. imagined

BUT: w/imagined, less activity for other sensory areas

consistent w/imagery being more fragile, need to minimize interference

But...fMRI correlations w/imagery don't definitively show causal relationship (even though very suggestive)

So...would be helpful to manipulate relevant brain areas

Kosslyn et al (1999):

Used transcranial magnetic stimulation (TMS)

- TMS applied to visual brain area during both perception and imagery task

Results:

- RT slower for both tasks when TMS applied to visual area, no effect for either task when applied to control brain area

- Suggests visual area brain activity plays causal role for both perception and imagery

Farah (2000): M.G.S.--patient w/removed right occipital lobe

visual brain area damage decreased both perceptual visual field and size of image visual field

so...in "mental walk", horse filled up imagined visual field from further away

again, strong perception/imagery relationship

Bisiach & Luzzatti (1978): patient w/unilateral neglect

Depending on whether patient imagined familiar location from one end or the other, "left" side was neglected

again, strong perception/imagery link

Guariglia et al (1993)

patient with unilateral neglect, but only with images (!)—perception OK

Farah et al. (1998)

patient "R.M."—damage to occipital and parietal lobes

could recognize and draw objects presented to him

but—couldn't draw from memory (which requires imagery)

Behrmann et al. (1994)

C.K.—patient w/visual agnosia

couldn't visually recognize real objects, but could image/draw

what to make of neuropsychological results

much evidence suggesting same/shared mechanisms for perception and imagery

but—also good evidence that perception and imagery are dissociable, suggesting separate mechanisms

Behrmann et al. (1994)—suggested solution

Perception and imagery mechanisms partially overlap

Visual perception involves bottom-up processing; located at lower and higher visual centers

Imagery is a top-down process; located at higher visual centers (only)

Behrmann application to

C.K., R.M., and M.G.S.'s dissociation patterns:

CK: lower visual damage left (higher-level) imagery OK

RM's higher-level damage impaired imagery but not visual processes

More trouble explaining M.G.S., who still had imagery problem despite having only lower visual center damage

Chalmers and Reisberg (1985)

Had participants create mental images of ambiguous figures

Difficult to flip from one perception to another while holding a mental image of it

practical uses of imagery

tool to improve memory

method of loci - placing images at locations

Visualizing items to be remembered in different locations in a mental image of a (familiar) spatial layout

Pegword technique--Associating to-be-remembered words w/images

similar to method of loci, but use standard words rather than locations (e.g., one-bun; two-shoe, three-tree, etc.)

form visual image of each to-be-remembered word along with "pegword" from your standard list

Harvey et al. (2005)—several results

- Groups either imagined favorite food or favorite vacation.

- Result: Food craving increased for food imagining group

- Later, food-imaging participants imagined either nonfood visual images or nonfood auditory images

- Food craving decreased in both groups, more for nonfood visual group

- Consistent w/ Baddely's WM model (i.e., more interference w/visual nonfood imagery)

Kemps & Tiggermann (2013)

Participants looked at phone app w/random visual dots whenever felt food craving

Food cravings, actual consumption went down

Note: error in text—the random dots interfere w/visuospatial sketchpad, not phonological loop

problem

an obstacle between a present state and a goal; not immediately obvious how to get around the obstacle, so the problem is (obviously) difficult

Key Gestalt problem-solving framework

-First, ascertain how problem is represented in mind

-To solve, generally need to restructure problem (i.e., change problem representation)

-Classic example: Kohler's "circle problem"

importance of insight in solving problems

Insight: sudden realization of problem solution

Often requires restructuring the problem

if insight occurs

shouldn't experience much "warning" prior to insight/solution; also...noninsight problems should yield "warning"

Metcalfe and Wiebe (1987)

- Insight: triangle problem, chain problem

- Noninsight: algebra

- Warmth judgments every 15 seconds

- Insight problems solved suddenly

- Noninsight problems solved gradually

Candle problem

Mount candle on wall so it can burn but not drip on floor

Two-string problem

Given chair and pliers, how connect two strings?

Duncker's (1945) candle problem

Only c. 50% solved; much better (c. 90%) when box empty (matches separate) rather than matches in box

Maier's (1931) two-strings problem

Less than 50% solved; much better (c. 80%) when "hint" given ("accidentally" hit strings)

Central problem

Fixation—focus on aspect of problem that prevents arriving at (different) solution

common form of central problem

Functional fixedness--restricting use of an object to familiar functions

functional fixedness in candle problem

seeing boxes as containers inhibited using them as supports

functional fixedness in two-string problem

usual function inhibits seeing them as possible weights

functional fixedness

A preconceived notion about how to approach a problem

Based on past experiences with similar problems

another (unhelpful) mental set

Applying past solution approaches to (even very similar) additional problems may inhibit use of better solutions

Water-jug problem (Luchins, 1942)

three jugs, hold different quantities of water

task: obtain desired amount by pouring water back and forth

Result: (successful) method for earlier problems carried over to final problems, even though latter had simpler solutions

Information-Processing Approach

Influential modern information-processing approach:

Newell and Simon (1972)

Models problem solving as a search (for solution)