Intelligence: the cognitive science

• A. Crystallized intelligence
• B. The g factor ✓
• C. Fluid reasoning
• D. Emotional quotient

Why: Charles Spearman noticed that test scores across different cognitive tasks tend to correlate positively, and he proposed a single general factor, labeled g, that accounts for this shared variance. Crystallized intelligence and fluid reasoning are later subdivisions proposed by Cattell and Horn, and emotional quotient is a separate construct not tied to Spearman's work.

• A. The highest score a person can achieve
• B. The average score for the age group the test was normed on ✓
• C. The score that indicates a person is of normal health
• D. The minimum score needed to attend university

Why: Modern IQ tests are standardized so that the mean score for the reference (norming) population is 100, with a standard deviation typically set at 15. A score of 100 therefore marks average performance relative to that age group, not a maximum or any health or academic threshold.

• A. To rank adults for military officer selection
• B. To identify French schoolchildren who needed special educational support ✓
• C. To measure the genetic potential of different populations
• D. To diagnose adult dementia

Why: The Binet-Simon scale was commissioned by the French government to identify children who would struggle in regular schooling so they could receive additional help. Binet emphasized that the test measured current performance and was not a fixed measure of innate ability, a point often overlooked in later uses.

• A. Reliability is about consistency of results; validity is about whether the test measures what it claims to measure ✓
• B. Reliability is about test length; validity is about test difficulty
• C. Reliability and validity are two names for the same property
• D. Reliability refers to cost; validity refers to speed of administration

Why: A reliable test yields consistent scores across occasions, items, or raters, while a valid test measures the intended construct. A test can be reliable without being valid, for example a consistently produced measure that captures the wrong thing, but a valid test must generally be reliable as well.

• A. Bodily-kinesthetic intelligence ✓
• B. Spatial reasoning quotient
• C. Working memory capacity
• D. Processing speed index

Why: Gardner's original framework included linguistic, logical-mathematical, spatial, musical, bodily-kinesthetic, interpersonal, and intrapersonal intelligences, later expanded with others such as naturalist. The other options are cognitive abilities or index scores found in factor-analytic models like the Wechsler scales, not in Gardner's list.

• A. Cerebellum
• B. Prefrontal cortex ✓
• C. Medulla oblongata
• D. Hippocampus

Why: The prefrontal cortex, located at the front of the frontal lobes, supports executive functions such as planning, decision-making, working memory, and abstract reasoning, which are central to many measures of intelligence.

• A. Astrocyte
• B. Neuron ✓
• C. Synapse
• D. Myelin sheath

Why: Neurons are specialized cells that receive, process, and transmit information through electrical impulses and chemical neurotransmitters. Glia, synapses, and myelin all support or enable neuronal communication but are not the primary signaling units.

• A. Amygdala
• B. Thalamus
• C. Hippocampus ✓
• D. Basal ganglia

Why: The hippocampus, located in the medial temporal lobe, is essential for consolidating new declarative and episodic memories. Damage to it, as in famous case studies of patient H.M., produces severe anterograde amnesia.

• A. A region that regulates heartbeat and breathing
• B. A bundle of nerve fibers connecting the two cerebral hemispheres ✓
• C. The outer layer of gray matter covering the cortex
• D. A chemical messenger released at synapses

Why: The corpus callosum is a large band of white matter fibers that allows communication between the left and right cerebral hemispheres, integrating information processed in each side.

• A. Frontal lobe
• B. Temporal lobe
• C. Parietal lobe
• D. Occipital lobe ✓

Why: The occipital lobe, at the back of the brain, contains the primary visual cortex and processes visual input such as shape, color, and motion. The other lobes handle different functions, such as motor control, auditory processing, and spatial awareness.

• A. Long-term memory
• B. Sensory memory ✓
• C. Working memory
• D. Procedural memory

Why: Sensory memory briefly holds raw sensory input (such as iconic visual or echoic auditory traces) for well under a second before information either decays or is passed on for further processing.

• A. 1 to 2 items
• B. 7 plus or minus 2 items ✓
• C. 15 to 20 items
• D. Unlimited items

Why: Miller's 1956 paper 'The Magical Number Seven, Plus or Minus Two' proposed that short-term memory holds about 7 (plus or minus 2) chunks of information. Later research suggests the true capacity may be closer to 4 chunks.

• A. Selective attention ✓
• B. Divided attention
• C. Sustained vigilance
• D. Retrieval cueing

Why: Selective attention is the process of concentrating on relevant information while suppressing irrelevant stimuli. The crowded-party scenario is the classic illustration, often called the cocktail party effect.

• A. Storing long-term autobiographical events
• B. Coordinating attention and directing the flow of information between subsystems ✓
• C. Producing motor movements
• D. Encoding visual images only

Why: The central executive is the attentional control system in Baddeley and Hitch's model. It allocates resources, coordinates the phonological loop and visuospatial sketchpad, and manages task switching.

• A. The testing effect
• B. The serial position effect ✓
• C. The spacing effect
• D. Interference theory

Why: The serial position effect describes better recall for early items (primacy effect) and late items (recency effect) in a list. Primacy reflects transfer into long-term memory, while recency reflects items still held in working memory.

• A. Inductive reasoning
• B. Deductive reasoning ✓
• C. Abductive reasoning
• D. Analogical reasoning

Why: Deductive reasoning guarantees its conclusion if the premises are true and the argument is valid. Inductive reasoning yields probable conclusions based on observed patterns, while abductive reasoning infers the best explanation for observations.

• A. A guaranteed step-by-step procedure that always produces the correct answer
• B. A mental shortcut that is efficient but does not guarantee a correct solution ✓
• C. A formal logical proof used to verify conclusions
• D. A measure of how quickly a person can solve problems

Why: Heuristics are rule-of-thumb strategies that reduce cognitive effort and often work well, but they can lead to errors. Algorithms, by contrast, are guaranteed procedures.

• A. Hindsight bias
• B. Confirmation bias ✓
• C. Availability bias
• D. Anchoring effect

Why: Confirmation bias leads people to favor evidence that supports what they already believe while discounting contradictory evidence, which can distort reasoning and decision making.

• A. Choosing the option that maximizes expected utility after evaluating all alternatives
• B. Choosing the first option that meets an acceptable threshold ✓
• C. Randomly selecting among available options to avoid overthinking
• D. Delaying a decision until more information becomes available

Why: Satisficing, a blend of 'satisfy' and 'suffice,' describes selecting an option that is good enough rather than optimal. Simon argued that limited time and information make this a realistic strategy for human decision makers.

• A. A tendency to use an object only in its typical, familiar way, which can block creative problem solving ✓
• B. A permanent loss of problem-solving ability after brain injury
• C. An inability to focus attention on a task for extended periods
• D. A preference for solving problems in the same order every time

Why: Functional fixedness, studied by Karl Duncker and others, is the difficulty of seeing an object as useful for a purpose other than its usual one. It is a classic obstacle to insight in problem solving.

• A. The permanent loss of neurons after early childhood
• B. The brain's ability to reorganize itself by forming new connections and strengthening or weakening existing ones ✓
• C. The fixed wiring of neural circuits determined entirely by genetics
• D. The electrical insulation that surrounds axons

Why: Neural plasticity refers to the brain's capacity to change its structure and function in response to experience, learning, and injury by modifying synaptic connections throughout life.

• A. Hebbian learning ✓
• B. Synaptic pruning
• C. Myelination
• D. Neurogenesis

Why: Hebbian learning, proposed by Donald Hebb, states that when one neuron repeatedly helps activate another, the connection between them is strengthened, forming the basis for associative learning.

• A. A lasting decrease in synaptic strength after repeated low-frequency stimulation
• B. The death of neurons caused by prolonged stimulation
• C. A lasting increase in synaptic strength following high-frequency stimulation of a synapse ✓
• D. The temporary fatigue of neurotransmitter release

Why: LTP is a persistent strengthening of synapses after brief, high-frequency stimulation. It is considered a major cellular mechanism underlying learning and memory.

• A. The cerebellum
• B. The brainstem
• C. The hippocampus ✓
• D. The occipital lobe

Why: The hippocampus plays a critical role in consolidating short-term experiences into long-term declarative memories, as shown by patients with hippocampal damage who cannot form new lasting memories.

• A. Neural connections that are frequently activated are strengthened, while unused connections tend to weaken or be pruned ✓
• B. Brain cells must be consumed by the body to produce new neurons
• C. Learning new skills permanently damages older memories
• D. Neurons stop functioning once they are no longer needed for daily tasks

Why: The 'use it or lose it' principle reflects that active, repeated neural pathways become stronger and more efficient, while inactive synapses are gradually eliminated through pruning.

• A. The Universal Grammar hypothesis
• B. The Sapir-Whorf hypothesis ✓
• C. The Critical Period hypothesis
• D. The Dual-Coding hypothesis

Why: The Sapir-Whorf hypothesis, also called linguistic relativity, holds that language structure shapes or constrains thought. Universal Grammar argues for innate linguistic structures shared by all humans, and the other options address different topics in language acquisition and memory.

• A. Phonology
• B. Displacement ✓
• C. Morphology
• D. Prosody

Why: Displacement is a design feature of human language identified by Charles Hockett that allows speakers to talk about things distant in time or space, or that do not exist at all. Phonology, morphology, and prosody describe sound systems, word structure, and intonation respectively.

• A. Abstraction via categorization ✓
• B. Working memory rehearsal
• C. Perceptual constancy
• D. Procedural learning

Why: Abstraction via categorization involves extracting common features across diverse instances to form general concepts. Working memory rehearsal maintains information briefly, perceptual constancy keeps objects looking stable despite changing sensory input, and procedural learning concerns skills acquired through practice.

• A. Visual object recognition
• B. Long-term episodic memory
• C. Language production and comprehension ✓
• D. Motor coordination of the hands

Why: Broca's area is linked to speech production and syntax, while Wernicke's area is linked to language comprehension. Damage to either area produces characteristic language impairments, making them central to the neural basis of language.

• A. That children learn language entirely through reinforcement from adults
• B. That some linguistic knowledge must be innate because the input children receive is too limited to explain it ✓
• C. That language has no connection to general intelligence
• D. That bilingual children cannot master grammar

Why: The poverty of the stimulus argument, associated with Noam Chomsky, holds that children acquire complex grammatical rules despite limited, imperfect input, suggesting innate linguistic constraints. The other options misstate either the argument or unrelated claims.

• A. Cognitive neuroscience
• B. Artificial intelligence ✓
• C. Behavioral economics
• D. Psychometrics

Why: Artificial intelligence (AI) is the field focused on creating systems that can perform tasks such as reasoning, learning, perception, and language use, which normally require human intelligence.

• A. Whether a machine can perform arithmetic faster than a human
• B. Whether a machine's responses are indistinguishable from a human's in conversation ✓
• C. Whether a machine can physically move like a human
• D. Whether a machine has consciousness

Why: Proposed by Alan Turing in 1950, the Turing Test asks whether a human judge, conversing via text with a machine and a human, can reliably tell which is which. Passing it indicates behavior indistinguishable from human conversation, not necessarily understanding or consciousness.

• A. Connectionism
• B. Symbolic AI ✓
• C. Reinforcement learning
• D. Evolutionary computation

Why: Symbolic AI (also called good old-fashioned AI) represents knowledge with symbols and manipulates them using explicit logical rules. Connectionist and learning-based approaches instead learn patterns from data.

• A. The structure of computer circuits
• B. The architecture of biological brains, with interconnected units that pass signals ✓
• C. The organization of human societies
• D. The layout of genetic code

Why: Artificial neural networks are loosely modeled on biological neurons: simple units connected by weighted links that transmit activation. The analogy is rough, but it inspired connectionist approaches to machine cognition.

• A. It performs well on new data because it generalizes effectively
• B. It has learned the training data too closely, including noise, and performs poorly on new data ✓
• C. It requires too little computational power
• D. It has been trained on too many different types of tasks

Why: Overfitting occurs when a model memorizes idiosyncrasies and noise in its training data rather than the underlying pattern, so its accuracy drops on unseen examples. This is a central concern when comparing AI learning to human generalization.