stmltm

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STM LTM STM LTM STM LTM Retrieval Storage; Consolidatio Case of H. M. Hippocampus Not loss of LTM, Not loss of STM, but loss of consolidation

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STMLTM. STMLTM. STMLTM. Retrieval. Storage; Consolidation. Case of H. M. Hippocampus. Not loss of LTM, Not loss of STM, but loss of consolidation. Tolman: Cognitive Maps. G. St. Olton: Radial Arm Maze. How?. Intramaze (e.g., smell food, scratch on floor) - PowerPoint PPT Presentation

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Page 1: STMLTM

STM LTM

STM LTM

STM LTM

Retrieval

Storage; Consolidation

Case of H. M.

Hippocampus

Not loss of LTM,Not loss of STM,

but loss of consolidation

Page 2: STMLTM

St

G

Tolman: Cognitive Maps

Page 3: STMLTM

Olton: Radial Arm Maze

How?

Intramaze (e.g., smell food, scratch on floor)Extramaze (stimuli around the maze)

Page 4: STMLTM

Then rotate maze*

*

*

*

Choose 4

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*

*

*

*

Which will they visit? Go to “space”, not armUse extramaze cues

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Morris: Water Maze

Hence:“Spatial”, and not any single cue.

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Morris: Water Maze Further tests:Probe trial

Page 8: STMLTM

Role of Hippocampus in Spatial LearningHippocampal Damage:Still get a little faster at finding platform

Probe Trial:Shows no “spatial strategy

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Role of Hippocampus in Spatial Learning

If visible platform, do as well as normal

Suggests role of hippocampus specifically in the “spatial” aspects of the water maze task

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Configural Learning Hypothesis

Spatial Learning is type of configural learning:response is based on > 1 cue

Hippocampus and Configural learning:

A—USB—USAB—

A—USB—

If Hippocampal damage, can do:

but not configualdiscrimination,

Page 11: STMLTM

Integrating across experiences

Rule learning (learning set)Strategies

Win-stay Win-shift

Strategy is then applied to new situations:More rapid learning of new (same strategy) task.

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Hypothesis Testing

New task: Try different hypotheses (strategies)If wrong, throw it outIf correct, stick with it

Leads to “step function” learning curveslooks like “insight”

PercentCorrect

Trials

100

Page 13: STMLTM

Concept Formation

Concept: Category- a set of objects/events having common features/relationships

Abstraction: How a concept is formed. Abstract (summarize) common features.

Form prototype (composite average) based on experiences with specific exemplars (examples)

Page 14: STMLTM

Common assumptions:1. Universal connectivity2. Contiguity

(note: preparedness: perhaps not “universal”)

3. Spread of activation

“Neural networks” and prototype formation

Page 15: STMLTM

“Neural networks” and prototype formation

Common assumptions:1. Universal connectivity2. Contiguity

tail

fur

ears

4 legs3. Spread of activation

Page 16: STMLTM

tail

fur

ears

4 legs

Learning rule: Delta Rule

External input

Internal input

Page 17: STMLTM

Learning rule: Delta Rule

ET

Sensory neuronSensory neuronExternal input

Internal input

∆ Int = c (Ext - Int)

REM: ∆V = c (Vmax - V)

∆ synaptic efficacy

Page 18: STMLTM

External Internal

Similar Ideas

Vmax V

Get Expect

Sensory detection and activation Retrieval of a node

Difference = Surprise