Origins of Cognitive Psychology Flashcards
wundt 1879
- structuralist approach
- structure of the mind
- components of consciosness
- Introspection
William James 1800
- functionalist approach
- functions of conscious activity NOT components of consciousness
- Function of thought = behaviour
- study of mental operations not structures
- emphasis on overt, observable behaviours
John B Watson 1919
- introspection - seen as subjective
* behaviour - objective
what was cognitive psychology developed in response too
the perceived limitations of the behaviourist approach
key events on cognitive psychology
- Chomsky (1956) – theory of language
- Miller (1956) – theory of capacity of short term memory
- Newell & Simon (1958) – theory of human problem solving
cognitive psychology
understanding human cognition through behavioural evidence - experiments
cognitive neuroscience
using behaviour and the brain to understand human cognition - recording brain activity
cognitive neuropsychology
studying brain-damaged patients to understand normal human cognition
computational cognitive science
using computational models to understand cognition
information processing approach sees human information processing as
akin to that of a computer
data - inputted, stored and retrieved
what is human information processing influenced by
bottom up and top down processing
what are bottom-up processes influenced by
environmental stimuli
what are top-down processes influenced by
internal subjective factors
what was the early assumption about information processing
that it is serial
serial processing
one process completed before moving onto the next
parallel processing
two or more cognitive processes that occur at the same time
*will increase with practice
strengths of cognitive psychology (approach)
first systematic approach to understanding human cognition
strengths of cognitive psychology (theories)
led to numerous theories and tasks which have been adopted by other approaches
weaknesses of cognitive psychology (validity)
lacks ecological validity
weaknesses of cognitive psychology (evidence)
indirect evidence of the underlying processes (speed/accuracy)
weaknesses of cognitive psychology (test)
theories often hard to test
weaknesses of cognitive psychology (paradigms)
findings often paradigm-specific (aging and PM)
weaknesses of cognitive psychology (theoretical framework)
lack overarching theoretical framework of cognition
egs of cognitive neuropsychology
- localisation of brain cognition - Brocas area
- modal model of memory - info transferred from one store to the next
- shallice and warrington - brain damaged patient -no short term memory but LTM was still intact
cognitive neuropsychology assumptions (functional modulartity)
independent processing units in the brain
cognitive neuropsychology assumptions (domain specificity)
respond to only one class of stimul
cognitive neuropsychology assumptions (anatomical modularity)
each module is located in a specific brain region
cognitive neuropsychology assumptions (uniformity of functional architecture across people)
allow us to generalise findings to normal human cognition
single dissociation
- not necessarily indicative of modularity
* one task might be more difficult than other
double dissociation
*provides reasonable evidence of at least partial independence/modularity
strengths of cognitive neuropsychology (dissociations)
double dissociations provide strong evidence for modularity
strengths of cognitive neuropsychology (causal links)
causal links shown between brain damage and cognitive performance
strengths of cognitive neuropsychology (study)
especially important in the study if language/memory
strengths of cognitive neuropsychology (links)
link between cognitive psychology and cognitive neuroscience
weaknesses of cognitive neuropsychology (modularity)
assumption of modularity is too strong
weaknesses of cognitive neuropsychology (compensation)
patients develop compensatory strategies
weaknesses of cognitive neuropsychology (brain damage)
brain damage often affects several modules
weaknesses of cognitive neuropsychology (interconnections)
de-emphasises interconnections between cognitive processes
weaknesses of cognitive neuropsychology (plasticity)
ignores plasticity
weaknesses of neuropsychology (generalisability)
individual differences make it difficult to generalise
Brodmann
- cognitive neuroscience
- identified 52 different areas
eg. primary visual cortex
single-unit recordings (cognitive neuroscience)
micro-electrode records activity of single neurons
event-related potentials (ERPs) (cognitive neuroscience)
same/similar stimulus presented and pattern of brain activity
what are ERPs good for
working out timings
what are ERPs less good for
spatial resolution
positron emission tomography (PET) (cognitive neuroscience)
detects positrons (emitted from radioactive substance)
what are PESs good for
spatial resolution
what are PETs poor for
temporal resolution
functional magnetic resonance imaging (fMRI) (cognitive neuroscience)
measures bloody oxygenation using MRI machine
what are fMRIs good for
spatial and temporal resolution
Haxby et al (cognitive neuroscience)
- used fMRI
- allowed researchers to identify category viewed on 96% of trials when ps looked at pictures of different categories eg cats, faces…)
Falk et al (cognitive neuroscience)
- quit smoking programme
* increased activity in medial prefrontal region predicted success of programme
strengths of cognitive neuropsychology (combined techniques)
combination of techniques offer excellent spatial and/or temporal resolution
strengths of cognitive neuroscience (specialisation and integration)
can study functional specialisation and brain integration
weaknesses of cognitive neuroscience (relationships)
difficulty relating brain activation to cognitive theories
weaknesses of cognitive neuroscience (underpowered)
provides only correlational evidence from a few patients
weaknesses of cognitive neuroscience (validity)
lacks ecological validity
weaknesses of cognitive neuroscience (paradigms)
problem of paradigm specificity
computational modelling (computational cognitive science)
programming computers to model/mimic some aspects of human cognitive functioning
artificial intelligence (computational cognitive science)
constructing computer systems that produce intelligent outcomes
cognitive architectures (computational cognitive science)
domain general cognitive models - overall architecture of cognition
Computational modelling - the issue of knowledge representation
1) what form does knowledge representation take?
2) where do these representations of knowledge reside within the human brain (or computer model)?
3) different assumptions by different types of computer models eg symbol systems vs connectionist models
symbol systems
*cognitive processes involve explicit manipulation of symbols - mental representations
how are objects represented (symbol systems)
objects are represented as symbols and are semantically interpretable
how are connectionist networks inspired by the neuronal structure of the brain
- brain consists of simple, richly connected cells
- each receives many inputs - excitory and inhibitory
- inputs summed and if threshold exceeded, output sent to other cells
what do connectionist networks consist of
a set of simple, richly connected processing units
what do connectionist networks receive
receive a number of inputs which it sums
what does connectionist networks do with the produced sums
a single output is derived from the sum and broadcasted to other units
how are the concepts represented in connectionist networks
through a distribution of activation
strengths of computational modelling (theoretical assumptions)
theoretical assumptions spelt out in precise detail in order to model cognition
strengths of computational modelling (distributed knowledge)
notion of distributed knowledge empirically supported
strengths of computational modelling (parallel processing)
emphasis on parallel processing fits with current evidence
strengths of computational modelling (brain damage)
often lesion models to examine effects of brain damage
weaknesses of computational modelling (neurological plausibility)
models arent neurologically plausible
weaknesses of computational modelling (factors)
de-emphasises motivational and emotional factos