Prior Knowledge and Memory Consolidation Expanding Competitive Trace Theory

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Prior Knowledge and Memory Consolidation Expanding Competitive Trace Theory Anna Smith

Outline 1. 2. 3. 4. 5. Background in Memory Models Models of Consolidation The Hippocampus Competitive Trace Theory My Project

1 Memory is fundamental inextricable, descriptive, predictive, hopefully cohesive

Search of Associative Memory Associative network model Memory images are either active or inactive Can activate others based on weight of connections

April 6, 2017 2 Substrate doesn t matter?

3 The Hippocampus Bilateral limbic structures in the medial temporal lobe Patient HM: damage to MTL lost consolidation and working memory, but retained some LTM Hippocampal Formation (HF): Dentate Gyrus (DG), CA1-CA2-CA3 complex, and subiculum Parahippocampal Gyrus: presubiculum, entorhinal cortex (EC), perirhinal cortex, and postrhinal cortex

Connectivity EC: cortical input/output structure Perirhinal Ctx EC HF : codes for spatial information (place cells) Postrhinal Ctx EC HF: codes for nonspatial DG: receives input from the cortex and projects to CA3 sparse connectivity (granule cells) CA3: Full of recurrent connections, forming its own network CA1: Fewer neurons relative to CA3 Relays information from CA3 back to afferent regions in the cortex via the EC

Pattern Separation and Pattern Completion How? Trade-off between gist (pattern-completed) and detail (pattern-separated) memory DG: Pattern Separation CA3: Pattern Completion CA1: strong enough CA3 packages input and retains segregation takes orthogonal input and compares it to stored patterns representations elicit response in corresponding CA1 network Sensory input arrives from EC, dispersed onto granule cells Redundancy reduced Output becomes orthogonalized (non-overlapping) Partial activation of a strong CA3 network can activate the rest of the network Impoverished stimuli gravitate towards stable states (attractors) More neurons relative to CA3 creates redundancy and robustness (less sensitive to noise) Relays memory traces back to afferent regions

Models of Consolidation Role of hippocampus in resulting cortical memory traces? SMSC MTT Standard Model of Systems Consolidation Multiple Trace Theory Hippocampus only necessary in initial transfer of information MTL no longer needed after migration to the cortex Argues for continued interaction between cortex and MTL in encoding and retrieval Each instance of recalling or experiencing a stimulus creates a new memory trace

April 6, 2017 2 Substrate doesn t matter?

Competitive Trace Theory Hippocampus is an index Unifies input, not the site of memory storage 2 processes after binding a memory trace: Consolidation Decontextualization Orthogonal traces cause anti-hebbian competition more exposures more gist-based Reagh and Yassa (2014) Hypothesis: repeated exposures to a stimulus will be detrimental to detail memory 4 Findings: Confirmed hypothesis; subjects more likely to confuse similar lures and targets when stimuli are repeated three times vs once

Finally my comps: The Effect of Cortical Schemas on Memory Trace Competition A follow-up of Reagh and Yassa (2014) that seeks to expand CTT to account memory traces of novel stimuli. Schemas: related cortical representations in an associative network Allows for systematic search during retrieval Assists in consolidation; allows for alteration of synaptic weights 5 Hypothesis: encoding nonschematic stimuli is more cognitively laborious, and recognition will take more exposures but I expect to see a competitive effect after a threshold number of repetitions

Study Phase 60 distinct items Press a, s, or d for density rating Test Phase The Task 79 test items: 30 targets, 30 lures, 19 foils. Counterbalanced. Target Bin 1 Lure (most difficult) Bin 2 Lure (less difficult) Novel Foil Repeated 1x, 3x, or 6x

The Task

schemas used in this task are weakly bound Cortical inputs enter through EC pattern separation in DG pattern completion in CA3 mental representation Celtic knots don t gravitate towards any strong attractor, so perhaps more detail is preserved compared to Reagh and Yassa (2014) but orthogonalization still causes trace competition Predictions Discrimination (correct lure rejections) strongest for 3-repetition, weak in 1 and 6 Recognition (correct target acceptances) strongest for 6-repetition Both facilitated in Bin 2 lures

Acknowledgements Thank you! to Michael Yassa, Zachariah Reagh, and the members of Yassa Lab Larry Wichlinski, my comps adviser My friends, for edits and speech practice Anyone who participated in my pilot study of stimulus similarity