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PSY 368 Human Memory. Semantic Memory cont. Reconstructive Memory. Announcements. Data from Experiment 3 due April 9 (Mon) Experiment 3 Report due April 16 If you missed the details of the Experiment, I included them again at the end of this lecture
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PSY 368 Human Memory Semantic Memory cont. Reconstructive Memory
Announcements • Data from Experiment 3 due April 9 (Mon) • Experiment 3 Report due April 16 • If you missed the details of the Experiment, I included them again at the end of this lecture • Optional reading for Monday is posted on Blackboard site (Media Library: Optional Readings): • Einstein, et al (2005) Prospective Memory article • Dr. Dawn McBride will be our speaker
Exam 2 • … was hard! • The mean % was 67.7%. • The range of scores was from 41% to 92% • So when interpreting your score, think “good job” if in the 80s and 90s and ‘okay’ if in the mid 60s to 70s. • It was harder than I expected, so I am thinking about offering an additional, one-time-only extra credit option. I’ll get the details hammered out this weekend (probably another article and focus questions kind of thing)
Summary of Semantic Memory • Semantic memory = knowledge • Some evidence for a separate system • Early models suggested hierarchical network - cognitive economy • Results suggest no strict hierarchy or cognitive economy • But current network models suggest loosened hierarchy (spreading activation) • Other ideas: compound cues, prototypes, exemplars, schemas • What kind of impact is there of this organization on retrieval of memories?
Compound Cue Models • Alternatives to Spreading activation models • Examine mechanisms of priming and extent to explain of priming effects • Make predictions about performance in memory retrieval tasks • Generally they are mathematical models that predict sets of results based on strength of cue associations • There are a lot of models to choose from (see “optional chapter” for details) • In SAM (Search of Associative Memory), a matrix of association among cues and memory traces, which are called images • Cues are assembled in a short-term store, or probe set, which is the match against all item in memory • In TODAM (Theory Of Distributed Associative Memory), to-be-remembered items are represented as vectors of features • Sum of vectors, convolution • The resulting scalar can be mapped into familiarity and, in turn, into response time and accuracy
Semantics as Exemplars • Instance theory: each concept is represented as examples of previous experience (e.g., Medin & Schaffer, 1978; Hintzman, 1986) • Make comparisons to stored instances • Typically have a probabilistic component • Which instance gets retrieved for comparison dog
Semantics as Prototypes • Prototype theory: store feature information with most “prototypical” instance (Eleanor Rosch, 1975) 1) chair 1) sofa 2) couch 3) table : : 12) desk 13) bed : : 42) TV 54) refrigerator Rate on a scale of 1 to 7 if these are good examples of category: Furniture TV couch table bed chair desk refrigerator
Semantics as Prototypes • Prototype theory: store feature information with most “prototypical” instance (Eleanor Rosch, 1975) • Prototypes: • Some members of a category are better instances of the category than others • Fruit: apple vs. pomegranate • What makes a prototype? • Possibly an abstraction of exemplars • More central semantic features • What type of dog is a prototypical dog? • What are the features of it? • We are faster at retrieving prototypes of a category than other members of the category
Semantics as Prototypes • The main criticisms of the theory • The model fails to provide a rich enough representation of conceptual knowledge • Vague: How can we think logically if our concepts are so vague? • Flexibility: How do our concepts manage to be flexible and adaptive, if they are fixed to the similarity structure of the world? • features have different importance in different contexts • what determines the feature weights • Individual differences: If each of us represents the prototype differently, how can we identify when we have the same concept, as opposed to two different concepts with the same label? • Does membership = similarity?: Why do we have concepts which incorporate objects which are clearly dissimilar, and exclude others which are apparently similar?
Demo • Before we start talking about constructive (integrative) and reconstructive memory, let’s do a demonstration. • I will present you with a long list of words, which I’ll later test your memory for.
