COGSCI 200 Final Exam Review (IM COOKED)
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303 Terms
Q: Perception
It is the brain's interpretation of sensory input, using priors and likelihoods to construct a model of the world.
Q: Inverse optics problem
It is the problem that many different 3D scenes can produce the same 2D retinal image, making perception ambiguous.
Q: Priors in perception
They are assumptions the brain makes about the typical structure of the world to resolve ambiguous sensory input.
Q: Likelihoods in perception
They evaluate how probable the sensory data is given a particular interpretation of the world.
Q: Bayesian brain hypothesis
It is the idea that the brain performs probabilistic inference by integrating priors and sensory evidence.
Q: Hollow-mask illusion
It demonstrates that strong face priors override bottom-up sensory signals, making a concave mask look convex.
Q: Light-from-above prior
It is the brain's assumption that lighting typically comes from above, influencing depth interpretation.
Q: Occlusion assumption
It is the expectation that objects continue behind occluders rather than disappearing or teleporting.
Q: Shadows in perception
They are interpreted as changes in lighting rather than pigment, helping the brain infer scene structure.
Q: Encapsulation in perception
It is the idea that cognitive beliefs cannot override perceptual processing, as seen in visual illusions.
Q: Ponzo illusion
It shows that perceived depth affects perceived size because of size-distance scaling.
Q: Size-distance invariance
It is the principle that perceived size equals retinal size multiplied by perceived distance.
Q: Predictive coding
It is the theory that the brain predicts sensory input and updates its model via prediction errors.
Q: Inattentional blindness
It is failing to notice unexpected stimuli when attention is elsewhere.
Q: Change blindness
It is the failure to detect large changes in a scene because visual representation is limited.
Q: Blindsight
It is the ability to respond to visual stimuli without conscious awareness due to V1 damage.
Q: Hard problem of consciousness
It is the challenge of explaining how physical processes give rise to subjective experience.
Q: Global workspace theory
It states that consciousness arises when information becomes globally available across cognitive systems.
Q: Integrated Information Theory
It claims consciousness depends on the amount and structure of integrated information in a system.
Q: Subliminal priming
It is when unconscious stimuli influence thoughts or behavior.
Q: Backward masking
It is a technique where a brief stimulus is overwritten by a later one, preventing conscious awareness.
Q: Place cells
They are hippocampal neurons that fire at specific spatial locations.
Q: Grid cells
They are entorhinal neurons with hexagonal firing patterns that create a spatial metric.
Q: Path integration
It is estimating one's position by tracking self-motion cues.
Q: Marr's computational level
It defines what problem the system solves and why.
Q: Marr's algorithmic level
It specifies the rules and representations used to solve the problem.
Q: Marr's implementation level
It describes the physical mechanisms that carry out the computation.
Q: Frame problem
It is the challenge of determining which facts are relevant when reasoning about actions.
Q: Symbol grounding problem
It is the question of how abstract symbols acquire meaning.
Q: Functionalism
It is the view that mental states are defined by their functional roles rather than their physical substrate.
Q: Multiple realizability
It is the idea that mental processes can occur in different physical systems.
Q: Computational Theory of Mind
It states that thinking is the manipulation of symbolic representations using rules.
Q: Mental representation
It is an internal state that encodes information about the world.
Q: Systematicity
It refers to structured thought, such as being able to think "A loves B" and "B loves A."
Q: Compositionality
It is the principle that meanings are built from parts and rules.
Q: Productivity
It is the ability to generate infinitely many thoughts or sentences from finite resources.
Q: Turing machine
It is an abstract computational device that manipulates symbols according to rules.
Q: Church-Turing thesis
It holds that anything computable can be computed by a Turing machine.
Q: Algorithmic information processing
It is computation that transforms representations step by step according to rules.
Q: Chinese Room Argument
It argues that syntax alone cannot produce semantic understanding.
Q: Searle's claim in Chinese Room
It states that running a program is insufficient for genuine understanding.
Q: Systems Reply
It suggests that the entire system, not the individual, could understand Chinese.
Q: Robot Reply
It argues that grounding symbols in a robot's sensory experience could create understanding.
Q: Connectionism
It is the theory that mental processes arise from distributed neural networks rather than symbolic rules.
Q: Distributed representation
It is encoding information across many units rather than in a single symbolic location.
Q: Symbolic representation
It uses discrete, structured symbols similar to language.
Q: Double dissociation
It occurs when two abilities can be independently impaired, suggesting separate systems.
Q: Modularity (Fodor)
It proposes that the mind contains domain-specific, fast, encapsulated systems with fixed neural architecture.
Q: Prosopagnosia
It is face-blindness caused by damage to the fusiform face area.
Q: Inversion effect
It is the disproportionate impairment in recognizing inverted faces, showing specialized processing.
Q: Composite face illusion
It is the difficulty in perceiving separated face parts due to holistic processing.
Q: Sugita (2008)
It found that monkeys deprived of faces still prefer face-like patterns, meaning innate bias plus tuning.
Q: Newborn face preference
It shows that infants have an early sensitivity to face-like configurations.
Q: Infant-directed speech
It is exaggerated, melodic speech that supports infant attention and word segmentation.
Q: Word segmentation problem
It is the challenge of identifying word boundaries in continuous speech.
Q: Transitional probabilities
They help infants detect word boundaries based on how likely syllables follow one another.
Q: Saffran et al. (1996)
It demonstrated that infants can rapidly learn statistical regularities in speech.
Q: Perceptual narrowing
It is the loss of sensitivity to non-native phonemes as infants specialize.
Q: Fast mapping
It is learning a word's meaning from a single minimal exposure.
Q: Mutual exclusivity
It is the assumption that each object has one label.
Q: Whole-object assumption
It is the expectation that labels refer to whole objects rather than their parts.
Q: Syntactic bootstrapping
It is using sentence structure to infer verb meaning.
Q: Semantic bootstrapping
It uses semantic categories to infer syntactic structure.
Q: Pragmatic inference
It is using context and speaker intent to determine meaning.
Q: Gricean maxims
They are conversational principles guiding cooperative communication.
Q: Universal Grammar
It is the idea that humans are born with innate constraints on language learning.
Q: Poverty of the stimulus
It argues that input is insufficient to explain children's rapid grammar learning.
Q: Nicaraguan Sign Language
It shows children spontaneously generate grammatical structure when exposed to limited input.
Q: Critical period for phonology
It states that early childhood is the optimal time for sound-category learning.
Q: Critical period for syntax
It extends into adolescence, after which grammar learning becomes difficult.
Q: Broca's aphasia
It produces nonfluent speech with relatively spared comprehension.
Q: Wernicke's aphasia
It produces fluent but meaningless speech with impaired comprehension.
Q: Conduction aphasia
It impairs repetition due to damage to the arcuate fasciculus.
Q: McGurk effect
It shows that visual information can shape auditory perception of speech.
Q: Intuitive physics
It is basic knowledge about object behavior present early in development.
Q: Solidity principle
It is the expectation that objects cannot pass through each other.
Q: Spatiotemporal continuity
It is the expectation that objects move on continuous paths.
Q: Cohesion principle
It is the expectation that objects behave as unified wholes.
Q: Support principle
It is the expectation that objects require physical support.
Q: Baillargeon's findings
They show infants understand object permanence earlier than Piaget proposed.
Q: Habituation-dishabituation
It is a method where infants' looking times reveal expectations.
Q: Wynn (1992)
It found infants detect incorrect arithmetic outcomes using looking time.
Q: Approximate Number System
It is a nonverbal system for estimating quantity based on ratios.
Q: Weber's Law in number
It states that discriminability between quantities depends on their ratio.
Q: Xu and Spelke findings
They showed infants differentiate numbers when ratios are large enough.
Q: PLATO model
It is a deep-learning model showing intuitive physics can arise from general-purpose learning.
Q: Core knowledge domains
They include objects, agents, number, space, and biology.
Q: Intuitive psychology
It is infants' early reasoning about beliefs, desires, and intentions.
Q: False-belief understanding
It is recognizing that others can hold incorrect beliefs.
Q: Woodward's goal attribution
It shows infants interpret human movements as goal-directed.
Q: Teleological stance
It is interpreting behavior as purposeful and efficient.
Q: Rational action principle
It is the expectation that agents act efficiently to achieve their goals.
Q: Shape bias in word learning
It is the tendency for children to categorize objects by shape rather than color or material.
Q: Overregularization
It is when children apply grammatical rules too broadly, such as saying "goed" or "mouses," showing rule-learning.
Q: Lexical ambiguity
It refers to words that have multiple possible meanings.
Q: Syntactic ambiguity
It refers to sentences that can be parsed in more than one structural way.
Q: Garden-path sentence
It is a sentence that misleads the parser into an incorrect initial structure.
Q: Minimal attachment
It is the parsing strategy that prefers the simplest syntactic structure.
Q: Late closure
It is the parsing strategy that attaches new information to the current phrase.
Q: Modular sentence processing
It is the view that syntax is computed before meaning is considered.