Semantic memory Flashcards
(45 cards)
What is semantic memory?
General knowledge (no specific event).
Anatomy of semantic dementia
Anterior parts of the temporal lobe.
2 reasons for categorisation of objects and events (unit of semantic categories)
- Economy (encoding of general structure).
- Generalisation (apply old knowledge to new situations).
Economy in categorisation
Pick up general pattern from individual instances. Common info is stored once, making it more efficient. Then use specific info (outstanding details).
Generalisation in categorisation
Applying prior knowledge in new contexts and predict properties about a new object.
Why are concepts so important?
They are like ‘ the glue that holds our mental world together’. Ties past experiences to present interactions with the world.
What type of hierarchical structure does semantic knowledge have?
Taxonomic (superordinate/basic level/subordinate).
Collins and Quillian (1969) ‘a canary…?’ true or false
Evidence of hierarchical storage. RTs are faster for descriptions that are specific to the concept (eg. ‘can sing’) and increase as the descriptions move further up the hierarchy. Different properties are stored at different hierarchical levels so ‘can sing’ immediately activates concept of canary while ‘has feathers’ searching until the ‘bird’ node is reached.
Mandler and McDonough (1993) semantic development in infants habituation
Children learn general categories first, before making finer distinctions.
Infants habituate to toys that are different animals. 9 month-olds showed no dishabituation to the rabbit but there was a significant increase in playing time with the bus. There was no significant difference in playing time for the 11 month=olds. 9 month olds did not distinguish between different types of animals. (Same with 4x dog habituation and then probed with a dog or a fish. Significant difference only for 0;11).
Keil (1979) predicability trees
Investigating which predicates could go with which concepts according to 5, 7 and 11 year-olds.
As age increases, there is a finer differentiation as age increases (a rabbit can no longer be sorry). A progressive differentiation about the features of concepts (not simply concepts themselves).
Development of loss of concepts in semantic dementia
Loss of specific concepts first. More general concepts are kept.
Acquisition and loss of knowledge progression
Development: acquire superordinate-level concepts first.
Semantic dementia: lose superordinate-level concepts last.
Is there a single hierarchy of knowledge?
No, concepts can be flexible (dogs are both canines and pets). Concepts are context-dependent (a disease that affects dogs is more likely to affect wolves; a shop that sells dogs is more likely to sell cats).
Rosche (1973) on within-category differences
Concepts cluster around prototypes. An apple is a fruitier fruit than an olive.
What are the 4 effects of prototypes?
- Faster categorisation and verification.
- More frequently listed in a category.
- Learnt first and spared in SD.
- Recognised well even if never seen.
Lupyan (2013) on how ‘all-or-none’ concepts are structured
Fuzzy concepts. Even for triangles, which has a strict rule on group membership, some triangles are more triangular than others.
Rosch et al. (1976) on how basic level is different
Basic level has an advantage in naming (picture verification, language learning, SD). Psychologically privileged as they strike a good balance of being inclusive but informative.
Empirical challenges in semantic knowledge
- Complex knowledge structure - why are some levels/concepts more important? Hierarchical structure, typicality, basic level.
- Developmental challenges - how is structure learnt and how is flexibility preserved?
- Conceptual challenges - how is structure coded neurally?
What is a connectionist model?
A network of simple interacting units with modifiable connections (based on experience). Input units -> hidden units -> output units.
Function of units
Integration and activation.
What is learning in a connectionist network?
The changes in the strengths of connections.
5 principles of connectionist models.
- Neurons integrate information (input from many other neurons).
- Neural activity reflects level of input (more input = more activity).
- Layered brain structure.
- Influence via connections.
- Learning alters connection strengths.
What does the processing unit do? 3 steps.
- Integrate input from the previous layer (input from multiple other units).
- Transform the net input to an activity level (ai).
- Transmits activity level to units in next layer.
How is input in unit(i) calculated?
Input(i) = activity level of previous unit(j) * the strength of connection between the units(ij).
Netinput(i) = the sum of inputs.