1. Semantic Memory Psychology 3717

2. Introduction This is our memory for facts about the world This is our memory for facts about the world How do we know that the capital of Viet Nam is Hanoi How do we know that the capital of Viet Nam is Hanoi How is this type of information stored? How is this type of information stored? Is there any difference between ‘natural’ and ‘logical’ concepts? Is there any difference between ‘natural’ and ‘logical’ concepts? How the heck could we figure this out? How the heck could we figure this out?

3. TLC No, not that lame TV channel ful of trading spaces and makeovers…. No, not that lame TV channel ful of trading spaces and makeovers…. The Teachable Language Comprehender The Teachable Language Comprehender Hierarchical associative network of concepts that began as a computer simulation Hierarchical associative network of concepts that began as a computer simulation

4. bacground Quinlan and his colleagues tried to make a computer program that would simulate how a person learns language Quinlan and his colleagues tried to make a computer program that would simulate how a person learns language Realized that concepts, not words, were the building blocks of knowledge Realized that concepts, not words, were the building blocks of knowledge Example ‘the policeman held up his hand and the cars stopped (Collins & Quinlan, 1973) Example ‘the policeman held up his hand and the cars stopped (Collins & Quinlan, 1973)

5. You know exactly what that phrase entails You know exactly what that phrase entails Cop is directing traffic Cop is directing traffic People push pedals etc People push pedals etc Tacit knowledge if you will Tacit knowledge if you will Three types of elements of semantic memory Three types of elements of semantic memory

6. The three elements Units, properties and pointers Units, properties and pointers Unit is a thing (the cop, his hand, the car etc) Unit is a thing (the cop, his hand, the car etc) Properties are conceptual (raising the hand that sort of thing) Properties are conceptual (raising the hand that sort of thing) Pointers denote specific associations Pointers denote specific associations

7. So where does this get us? Semantic memory then is a HUGE hierarchical network of relationships between elements Semantic memory then is a HUGE hierarchical network of relationships between elements Is statements then are relationships between a superordinate element and a subordinate Is statements then are relationships between a superordinate element and a subordinate A bird is a fish will not produce a yes A bird is a fish will not produce a yes A fish is an animal and a bird is an animal will A fish is an animal and a bird is an animal will

8. Collins and Quinlan (1969) A _____ is a ______ statements A _____ is a ______ statements Sentence verification Sentence verification RT longer when number of associative links was greater RT longer when number of associative links was greater Less relevant property relationships, longer RT Less relevant property relationships, longer RT (a canary is yellow is longer than a canary can breather) (a canary is yellow is longer than a canary can breather)

9. However… Ok, by this theory, the satement ‘a bear is a mammal’ should be quicker than ‘a bear is an animal’ Ok, by this theory, the satement ‘a bear is a mammal’ should be quicker than ‘a bear is an animal’ Ummm, no…. Ummm, no…. So the ‘semantic distance effect’ does not show up here So the ‘semantic distance effect’ does not show up here

10. More buts Does not deal with the typicality effect at all Does not deal with the typicality effect at all Does not explain why ‘a robin is a shark’ is more quickly rejected than ‘a robin is a salmon’ Does not explain why ‘a robin is a shark’ is more quickly rejected than ‘a robin is a salmon’ Conrad (1972) said that it is the typicality of the statement itself that is the issue Conrad (1972) said that it is the typicality of the statement itself that is the issue

11. Feature set theory Smith, Shoben and Rips (1974) Smith, Shoben and Rips (1974) Concepts stored as sets of attributes Concepts stored as sets of attributes RT then depends on comparing features of exemplar with stored concept RT then depends on comparing features of exemplar with stored concept Predicts the symbolic distance effect (very similar items take long RTs Predicts the symbolic distance effect (very similar items take long RTs Predicts the category size effect (concept to superordinate) Predicts the category size effect (concept to superordinate)

12. But…. You knew there would be a but You knew there would be a but What are the defining features of a concept What are the defining features of a concept What is a dog for example What is a dog for example Your idea is different than mine Your idea is different than mine But we gt the same effects with subjects But we gt the same effects with subjects

13. Spreading activation Collins and Loftus (1975) Collins and Loftus (1975) Network like TLC Network like TLC NOT as rigidly hierarchical NOT as rigidly hierarchical Still have units and properties, but not so hierarchical Still have units and properties, but not so hierarchical Distance is important Distance is important

14. But.. This one sounds better but there is a but This one sounds better but there is a but Distantly related concepts should give longer RTs Distantly related concepts should give longer RTs But ‘a canary is a shark’ takes like no time But ‘a canary is a shark’ takes like no time

15. Propositional network theory Anderson (1983) Anderson (1983) ACT and ACT* ACT and ACT* For example ‘Kurt’s mother sent him a package last week’ For example ‘Kurt’s mother sent him a package last week’ Three propositions Three propositions More propositions, sentences take longer, even with fewer words More propositions, sentences take longer, even with fewer words

16. Neural network models Units or nodes that are like neurons, on and off Units or nodes that are like neurons, on and off But, units have a threshold and once acticavted past this threshold you get ‘firing’ But, units have a threshold and once acticavted past this threshold you get ‘firing’ Units are connected either excitatorily or inhibtorily Units are connected either excitatorily or inhibtorily There are activation rules There are activation rules Output rules, how a unit sends info to next unit Output rules, how a unit sends info to next unit Learning rules Learning rules Groups of units or modules, are devoted to specific cognitive functions Groups of units or modules, are devoted to specific cognitive functions

17. properties Content addressable memory Content addressable memory Network makes guesses Network makes guesses Network makes spontaneous generalizations Network makes spontaneous generalizations

18. conclusions I don’t want to get too bogged down in this but, I think that we can make a few statements I don’t want to get too bogged down in this but, I think that we can make a few statements All the theories are about connections All the theories are about connections Probably NOT hierarchical, completely Probably NOT hierarchical, completely Activation probably spreads Activation probably spreads This stuff can get way hard…. This stuff can get way hard….