Introduction to Cognitive Science — Ch2: Language, Reasoning, Problem Solving, Consciousness

Language Processing

Language and cognition:
→ The Sapir-Whorf hypothesis (linguistic relativity):
  Strong version: language determines thought
  Weak version: language influences thought (the version supported today)
  Evidence from colour perception and spatial language experiments
→ Universal grammar:
  Chomsky: the capacity to acquire language is biologically built in
  The language acquisition device (LAD): grammar rules extracted automatically
  The poverty of the stimulus argument: input is too sparse, so innate structure is required

Generative grammar and syntactic processing:
→ Deep structure vs surface structure:
  Transformational rules generate the surface structure
  "John is easy to please" vs "John is eager to please"
  The same surface form over different deep structures
→ Garden-path sentences:
  "The horse raced past the barn fell."
  An initial misparse, then reanalysis
→ Models of syntactic processing:
  Serial models: syntax first, then semantic integration
  Parallel models: syntax and semantics processed together

Lexical access:
→ Two stages in recognising a word:
  Visual analysis → lexical search → semantic activation
→ The word superiority effect:
  A letter is recognised better inside a word than on its own
→ Priming: a related word speeds up processing
  Semantic priming: DOCTOR → NURSE (faster)
  Repetition priming: repeated exposure shortens processing time
→ Context effects: sentence context shapes word recognition

Discourse processing:
→ The situation model:
  Building a mental representation of the situation, beyond the literal text
  Integrating time, space, causality and goals
→ Inference generation: supplying what the text leaves out, automatically
  Bridging inferences: connecting to earlier information
  Elaborative inferences: generating additional detail
→ Discourse cohesion: held together by pronouns, deixis and connectives

Reasoning and Decision Making

Types of reasoning:
→ Deductive reasoning:
  If the premises are true, the conclusion must be true
  The syllogism: "All humans are mortal; Socrates is human..."
  Errors: applying an invalid form

→ Inductive reasoning:
  Deriving a general principle from observations
  Conclusions are probable, never certain
  Strength depends on sample size and representativeness

→ Abductive reasoning:
  Inference to the best explanation
  A doctor's diagnosis, a detective's deduction

Formal logic and psychology:
→ The Wason selection task:
  Which cards must you turn over to test a rule of the form "if P then Q"?
  The error: confirmation bias
  P and not-Q must be turned; people choose P and Q instead
→ Performance improves with permission schemas:
  Recast the abstract rule in a social context and accuracy rises
  Cosmides: the cheater-detection module hypothesis

Confirmation bias:
→ Seeking and interpreting only information that supports your belief
→ In tension with scientific thinking
→ The ability to look for falsifying evidence has to be trained

Dual process theory:
→ Kahneman, Thinking, Fast and Slow
  System 1 (fast thinking):
    Automatic, intuitive, fast, emotional, low effort
    Runs on heuristics
  System 2 (slow thinking):
    Controlled, analytic, slow, logical, high effort
    Rule-based processing
→ System 1 errors: availability, representativeness and anchoring heuristics
→ Interaction: System 1 answers first, System 2 reviews

Probability judgement:
→ Representativeness heuristic:
  Base rate neglect
  The "Linda problem": feminist bank teller judged more likely than bank teller
  (the conjunction fallacy)
→ Availability heuristic:
  Judging what comes to mind easily as more frequent
  Overrating air-crash risk against the far greater risk of car crashes
→ Anchoring and adjustment:
  Over-reliance on the first number encountered

Problem Solving

The Gestalt approach:
→ Insight: a solution that arrives suddenly, the "aha!" moment
  Wolfgang Köhler: insight experiments with chimpanzees
→ Restructuring: re-representing the problem in a new way
→ Functional fixedness:
  Fixating on an object's usual function blocks creative use
  Duncker's candle problem: seeing the matchbox as a shelf

The information-processing approach:
→ Newell and Simon: problem space theory
  Initial state → goal state, moving via operators
  Searching the problem space
→ Means-end analysis:
  Reducing the difference between the current state and the goal
  Setting subgoals, then solving recursively
  Applied to the Tower of Hanoi
→ Analogy:
  Applying a solution to a problem with the same underlying structure
  The radiation problem and the military problem

Experts vs novices:
→ Chess research (Chase and Simon):
  Experts remember in chunks
  Novices remember individual piece positions
  Experts recognise larger patterns
→ Domain specificity: expertise does not carry across domains
→ Deliberate practice:
  Ericsson: focused practice with feedback, not mere repetition
  The basis of the "10,000 hour" claim

Creative problem solving:
→ Wallas's four stages:
  Preparation → incubation → illumination → verification
→ Divergent thinking vs convergent thinking
→ The Remote Associates Test (RAT): finding the word that links the set
→ Conditions: psychological safety, a playful attitude, broad knowledge

Theories of Consciousness

The hard problem of consciousness:
→ David Chalmers: why do physical processes give rise to subjective experience?
→ The easy problems: explaining cognitive function (sensing, attending, reporting)
→ The hard problem: explaining subjective experience (qualia) itself
→ The zombie argument: could a being be functionally identical yet have no experience?

Global workspace theory:
→ Bernard Baars: consciousness as a global broadcast
→ A central space where many modular brain regions share information
→ Conscious content: whatever is broadcast to the global workspace
→ Neural implementation: widespread activation of a frontoparietal network
→ Stanislas Dehaene: neuroscientific support
  Attention and consciousness: related, but dissociable

Higher-order theories:
→ David Rosenthal: higher-order thought theory
  A conscious experience is a representation of one's own mental state
  It requires the higher-order thought "I am experiencing X"
→ Self-representation: the recursive structure of consciousness

Integrated information theory (IIT):
→ Giulio Tononi: consciousness is integrated information
→ Phi (Φ): the quantity of integrated information
  High Φ = high consciousness
  The cortex has high Φ, the cerebellum low Φ (a structural difference)
→ A panpsychist implication: consciousness anywhere a system is complex enough?

Neural correlates of consciousness (NCC):
→ The minimal neural mechanisms that correlate with conscious experience
→ Binocular rivalry:
  A different image to each eye; only one is conscious at a time
  Neural activity is measured as awareness flips
→ Masking studies: brain activation from stimuli that never reach awareness
→ fMRI, EEG and MEG: imaging states of consciousness

Frequently Asked Questions

Q. In dual process theory, which brain regions are System 1 and System 2? A. Dual process theory draws a functional distinction, not an anatomical one. System 1 is not a single region but a family of automatic processes spread across the amygdala (emotional processing), basal ganglia (habitual action), cerebellum (automated movement) and temporal lobe (face recognition), among others. System 2 corresponds to controlled processing involving the prefrontal cortex (goal direction, working memory) and anterior frontal regions. Recent neuroscience treats the “two systems” less as a dichotomy than as a continuum from automatic to controlled, with many intermediate levels. A skilled chess player reading a position instantly looks like System 1, but it is really System 2 processing that long training has automated. Kahneman himself stressed that the two systems are a metaphor, not names for separate brain structures.

Q. Is the “hard problem” of consciousness beyond the reach of science? A. It is true that Chalmers’s hard problem remains unsolved, but the debate is about method rather than about hopelessness, and it falls into three broad positions. First, eliminativism: Churchland and others argue that qualia is a mistaken concept in the first place, and that the notion of consciousness will be reconstructed as neuroscience matures. Second, emergentism: consciousness emerges from sufficiently complex physical systems and can be explained scientifically — the stance of global workspace theory and IIT. Third, dualism: Chalmers’s own position, which grants consciousness an aspect that does not reduce to physical explanation. In practice, neuroscience keeps mapping the neural correlates of consciousness in finer detail, and measurement of conscious level in anaesthesia, sleep and vegetative states continues to improve. Even if the hard problem stays open in theory, the practical applications — diagnosing coma, monitoring anaesthesia, assessing consciousness in AI — will keep advancing.