Semantic Memory Psychology 3717

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

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

background 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 Example ‘ the policeman held up his hand and the cars stopped (Collins & Quinlan, 1973)

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

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

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

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

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

More buts 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 ’ Conrad (1972) said that it is the typicality of the statement itself that is the issue

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

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

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

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

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

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

properties Content addressable memory Network makes guesses Network makes spontaneous generalizations

conclusions 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 Probably NOT hierarchical, completely Activation probably spreads This stuff can get way hard….