Cognition

1. Cognitive Psychology Studies the Mind via the Brain

Our path forward, therefore, is to study mental processes indirectly, relying on the fact that these processes, themselves invisible, have visible consequences...

Inferring the invisible. Cognitive psychology scientifically studies the mind, focusing on knowledge acquisition, retention, and use. Unlike early introspectionists who relied on subjective reports, modern cognitive psychologists study the mind indirectly. They observe measurable behaviors like response time, accuracy, and errors to infer the underlying mental processes, much like a detective infers a crime from clues.

Brain specialization. The brain is the biological basis of cognition, with different regions specialized for different functions. The hindbrain controls basic life support, the midbrain coordinates movement and relays sensory info, and the forebrain (especially the cerebral cortex) handles higher-level cognition. Subcortical structures like the hippocampus (memory) and amygdala (emotion) are also crucial.

Linking mind and brain. Cognitive neuroscience uses methods like fMRI, EEG, and studies of brain damage (neuropsychology) to link mental processes to specific brain activity or structures. For example, Capgras syndrome, where familiar faces feel unfamiliar, is linked to damage in areas connecting face recognition (temporal lobe) and emotional evaluation (amygdala), illustrating how complex functions require coordinated brain activity.

2. Perception is Active and Interpretive

Your perception goes beyond the information given in the drawing, by specifying an arrangement in depth.

Beyond sensory input. Perception begins with sensory data (light hitting the retina, activating rods and cones), but it's not just passive reception. Early processing in the eye (lateral inhibition) enhances edges. The brain then actively organizes and interprets this input, going "beyond the information given."

Organizing the world. Gestalt principles (proximity, similarity) guide how we group elements into objects. We impose figure/ground organization and interpret ambiguous stimuli (Necker cube, vase/profiles). This interpretation happens early, influencing even feature detection.

Achieving constancy. We perceive objects as having constant properties (size, shape, brightness) despite changing sensory input. This relies on unconscious inference, where the brain accounts for viewing conditions (distance, angle, illumination). These same mechanisms can lead to visual illusions when cues are misleading.

3. Object Recognition is Hierarchical and Context-Dependent

It seems, then, that our science of salt passing won’t get very far if we insist on talking only about the physical stimulus.

Features and context. Object recognition starts with detecting simple features (lines, curves), but context and prior knowledge heavily influence the process (top-down processing). We recognize words faster in context (word superiority effect) and are biased by spelling patterns.

Network models. Feature nets propose layers of detectors (features, letters, words) that fire based on input and prior activation (frequency, recency). This explains priming effects and why we misread irregular inputs as regular. More complex models include inhibition and feedback.

Objects and faces. Recognition-by-components (RBC) uses geons (basic 3D shapes) for object recognition. Brain areas like the IT cortex respond to complex objects. However, face recognition seems special, relying on holistic processing (configurations) rather than parts, supported by areas like the FFA, and is vulnerable to inversion.

4. Attention Selects and Limits Processing

It implies withdrawal from some things in order to deal effectively with others...

Focusing the mind. Selective attention is the ability to focus on one input while ignoring others. Dichotic listening and shadowing show we process little semantic content from unattended channels, though some salient info (like your name) can break through.

Limits of awareness. Attention is crucial for conscious perception. Without attending, we can experience inattentional blindness (missing obvious stimuli) and change blindness (missing large changes). This suggests perception requires effort and resources.

Priming and control. Attention works by priming relevant detectors (expectation-based priming), making them more responsive. This draws on a limited capacity. Spatial attention acts like a spotlight. Executive control directs attention, but unconscious processes (habits, reflexes) can operate automatically, sometimes leading to action slips.

5. Memory is a Network of Connections

Learning also needs to establish some appropriate indexing; it must pave a path to the new information, so that this information can be retrieved at some future point.

Multiple memory systems. Memory involves working memory (active, limited capacity, fragile) and long-term memory (vast, durable storage). The modal model proposed information flows from sensory to short-term (working) to long-term memory, but working memory is now seen as active processing, not just a passive store.

Acquisition and retrieval. Getting information into LTM requires effortful, deep processing (attention to meaning, relational rehearsal), not just repetition. Learning establishes connections that serve as retrieval paths. Retrieval is context-dependent; matching learning and retrieval conditions (physical or mental) improves recall.

Implicit and explicit. Memory can be explicit (conscious recall/recognition) or implicit (unconscious influence on behavior, like priming). Amnesia (retrograde/anterograde) often disrupts explicit but spares implicit memory, showing these are distinct. Memory is reconstructive, influenced by schemas and misinformation, leading to errors (DRM, false fame, source confusion), but generally reliable.

6. Concepts Organize Knowledge

Concepts (like “dog”) allow you to apply your general knowledge to new cases you encounter (like Milo).

Beyond definitions. Concepts are the building blocks of knowledge, enabling us to categorize and make inferences. Definitions often fail for common concepts (e.g., "dog") due to exceptions. Instead, concepts are often represented by prototypes (ideal examples) or exemplars (specific instances).

Typicality and resemblance. Categorization often relies on resemblance to prototypes or exemplars, leading to graded membership (some members are "better" than others). Typicality influences judgment speed and frequency of mention.

Beliefs and structure. Categorization also depends on background beliefs about a category's essential properties and causal relationships, overriding resemblance in some cases (e.g., a mutilated lemon is still a lemon). These beliefs are organized in a network, guiding inference and reasoning about new cases. Different types of concepts (natural kinds, artifacts) are processed differently and linked to distinct brain areas.

7. Language is a Rule-Governed, Generative System

Once again, therefore, note the generativity of language—that is, the capacity to create an endless series of new combinations, all built from a small set of fundamental units.

Hierarchical structure. Language is organized hierarchically: phonemes (sounds) combine into morphemes (meaning units), which form words, phrases, and sentences. Rules govern combinations at each level.

Production and perception. Speech production involves coordinating airflow (voicing, manner/place of articulation). Perception is complex (segmentation, coarticulation) but aided by context (phonemic restoration) and categorical perception (hearing sounds as distinct categories).

Syntax and pragmatics. Syntax rules govern sentence structure (phrase structure, descriptive rules), guiding parsing (figuring out word roles). Parsing is fast but can lead to garden-path errors. Prosody (intonation) and extralinguistic context aid understanding. Pragmatic rules and common ground guide conversation, allowing unspoken inferences. Language is biologically rooted (aphasia, SLI) and influences thought via attention.

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Last updated: May 23, 2025