semantic memory
as the store of knowledge about the world - contains concepts
concept
mental representations and fundamental units of thought/knowledge e.g. concept of an animal
how are concepts organised in the memory system
first idea of Hierarchical network model
Hierarchical network model
- Collins & Quallian 1969
- semantic memory organised into a series of hierarchical networks
- major concepts as nodes
- properties/features are associated with each concept
- cognitive economy
what is cognitive economy in the hierarchical network
properties are stored higher up, and not repeated lower down, to minimize redundancy
support for Hierarchical model
- Collins & Quallian
- sentence verification task (say whether sentence is true of false)
- allow us to quantify reaction time
- properties (e.g. sing) stored as the same level as the target concept (e.g. canary) are accessed more quickly (short reaction time)
- those stored higher up need more time to be processed (e.g. canary can fly has longer verification time)
reaction time in sentence verification tasks
- unless information is directly linked to a concept in semantic memory, we infer the answer from properties of high nodes
- verification time increases for broader concepts e.g. a bird flying
- more inferences slows (increases) verification time
problems with hierarchical model
- problem of familiarity in sentence verification task:
how often do you hear the sentence ‘a canary has skin’? when controlled reduced hierarchical distance effect - how typical is the verification concept: verification is faster for more representative member categories, independent of hierarchical distance e.g. penguin vs canary as a bird (canary more typical of category)
model that developed from Hierarchical model
spreading activation model
spreading activation model
Collins & Loftus 1975
- semantic memory is organized by semantic relatedness/distance
- lengths of links indicates the degree of semantic relatedness
- activity at one node causes activation of other nodes via links
- spreading activation decreases as it gets further away from the original point of activation
e.g. penguin is a bird has slow activation whereas canary is a bird is strong activation
- due to previous experiences
supporting evidence for spreading activation model - study
semantic priming tasks
McNamara 1992
- when presenting one stimulus that is more semantically related makes subsequent processing more efficient/faster (short-link)
e.g. red + rose vs red + flower
- semantic links and distance determine the strength and speed of activation spread from one concept to the other
supporting evidence for spreading activation model - paradigm
- Deese-Roediger-McDermoot (DRM) Paradigm
- p’s selected words they did not study as they were related to the subject
- suggest activation spreads from all words presented/studied to words related
spreading activation model evaluation
- more flexible than hierarchical model (links of different strength and distance)
- can account for more empirical findings
- but reduces specificity of model’s predictions
- and more difficult to test
limitations of spreading activation model
- the notion that each concept is represented by a single node is oversimplified what about abstract concepts e.g. justice
- each concept has a fixed mental representation whereas the context in which we encounter them changes the way we process them, so do different people have different representations?
the role of context in semantic memory - theory
situated simulation theory
situated simulation theory
- concepts are processed in different settings
- their processing is influenced by the current context/setting
- concepts have perceptual/motor/action related properties
e.g. activated aspects of ‘bicycle’ concept reflect current goals … e.g. for a child would have training wheels as a part of the perceptual properties that are activated
Barsalou 2009
evidence for situated stimulation theory - does access to concepts involve motor systems?
Hauk et al 2004
- Brain areas activated by action words overlap with activation produced by corresponding movement e.g. leg words (AW) and foot movements
- action words activate motor areas related to the concept - shows action related elements are presented with a concept- therefore facilitate accessing the meaning of the concept
evidence for situated stimulation theory - does involvement of motor system facilitate access to concepts
Miler et al. 2018
- presented words either relating to hands or feet (e.g. sprint) and asked p’s to respond with hands or feet
- when consistency between meaning and response then reaction time faster (sprint + feet)
- when inconsistent reaction time slower (sprint with hands)
- understanding of action verbs requires activation of the motor areas used to carry out the names action
situated simulation theory evaluation
processing of concepts depends on the situation and perceptual + motor processes in a given task
limitations of SST model
- are the concepts variable across situations e.g. concept has a core but there are context dependent elements
- are these action related -
properties secondary i.e. after the concept meaning has been accessed, then action-related are activated
Concepts in the brain - semantic memory approaches
- grandmother cell hypothesis
- feature-based approach
grandmother cell hypothesis
- semantic memories are represented in the brain as whole objects
- each concept with its own node or neuron
e.g. special neuron for your grandmother - types of nodes are grouped together e.g. all living things
- not a lot of evidence to support this
feature-based approach
- different kinds of information about a given object are stored in separate brain regions
e.g. visual information is stored in one part of the brain, while auditory linked to the same object is stored in another (but networks between areas) - more likely
neurocognitive model
Hub-and-spoke model
(Patterson et al 2007)
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lecture 1 - Learning32
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Lecture 2 - Episodic memory30
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Lecture 3 - Semantic Memory35
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LECTURE 4 - Memory Retrieval57
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Lecture 5 - Forgetting46
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Lecture 6 - Reasoning & Decision-making42
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Lecture 7 - Reasoning46
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Lecture 8 - Risky Choice34
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Lecture 9 - Emotion in decision-making31
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Group Decision-Making26
