Memory: Its Nature and Organization in the Brain

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Memory Its Nature and Organization in the Brain

• James L. McClelland
• Stanford University

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Pinter on Memory

• What interests me a great deal is the mistiness
  of the past Harold Pinter, Conversation with
  Mel Gussow prior to the opening of Old Times,
  1971

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The Vagaries of Memory

• Misty, cloud-like, and subject to distortion
• Ah yes, I remember it well!
• Memory and the Paleontologist metaphor
• Fragments stitched together with the aid of
  plaster, glue prior knowledge, beliefs, and
  desires.
• Fragments may come from one or many dinosaurs
  not necessarily of the same species!
• From metaphor to mechanism
• What do we know about memory in the brain that
  can help explain why memory is this way?

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What is a Memory?

• The trace left in the memory system by an
  experience?
• A representation brought back to mind of a prior
  event or experience?
• Note that in some theories, these things are
  assumed to be one and the same (although there
  may be some decay or corruption).
• Not so in a connectionist approach to memory!

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In a connectionist approach

• The trace left by an event is a pattern of
  adjustments to connections among units
  participating in the processing of the event or
  experience.
• The representation brought back to mind is a
  pattern of activation which may be similar to
  that produced by the experience, constructed with
  the participation of the affected connections.
• Such connections are generally assumed also to be
  affected by many other events, so the process of
  reinstatement is always subject to influence
  from traces of other experiences.

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Contrasting Approaches to the Neural Basis of
Memory

• Multiple memory systems approach
• Seeks dissociations of different forms of
  learning and memory.
• Explicit vs. implicit memory
• Declarative vs. procedural memory
• Semantic vs. episodic memory
• Familiarity vs. recollection
• Seeks tasks or task components that can be used
  to isolate the contributions of each system.
• Although it is assumed that more than one system
  can contribute to performance in a given task,
  the contributions are simply alternative paths to
  correct performance.
• For example in a recognition memory task
• One can decide one has seen an item before either
  because it seems familiar or because things that
  are associated with it are recalled.

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An Alternative Approach

• Complementary and Cooperating Brain Systems
• Memory task performance depends on multiple
  contributing brain systems.
• Contributions of components to overall task
  performance depend on their neuro-mechanistic
  properties.
• Components work together so that overall
  performance may be better than the sum of the
  independent contributions of the parts.

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The Complementary Learning Systems
Theory(McClelland, McNaughton OReilly, 1995)

• Neuropsychological motivation
• The basic theory
• Neurophysiology consistent with the account
• Why there should be complementary systems

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Bi-lateral destruction of hippocampus and related
areas produces
- Profound deficit in forming new arbitrary
associations and new episodic memories. -
Preserved general intelligence, knowledge and
acquired skills. - Preserved learning of new
skills and item-specific priming. - Loss of
recently learned material w/ preservation of
prior knowledge, acquired skills, and remote
memory.
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The Theory Processing and Learning in Neocortex

• An input and a response to it result in
  activation distributed across many areas in the
  neocortex.
• Small connection weight changes occur as a
  result, producing
• Item-specific effects
• Gradual skill acquisition
• These small changes are not sufficient to support
  rapid acquisition of arbitrary new associations.

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Complementary Learning System in the Hippocampus

• Bi-directional connections produce a reduced
  description of the cortical pattern in the
  hippocampus.
• Large connection weight changes bind bits of
  reduced description together
• Cued recall depends on pattern completion within
  the hippocampal network
• Consolidation occurs through repeated
  reactivation, leading to cumulation of small
  changes in cortex.

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Supporting Neurophysiological Evidence

• The necessary pathways exist.
• Anatomy and physiology of the hippocampus support
  its role in fast learning.
• Reactivation of hippocampal representations
  during sleep.

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Different Learning and Coding Characteristics of
Hippocampus and Neocortex

• Hippocampus learns quickly to allow one-trial
  learning of particulars of individual items and
  events.
• Cortex learns slowly to allow sensitivity to
  overall statistical structure of experience.
• Hippocampus uses sparse conjunctive
  representations to maintain the distinctness of
  specific items and events.
• Cortex uses representations that start out highly
  overlapping and differentiate gradually to allow
• Generalization where warranted
• Differentiation where necessary

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Examples of neurons found in entorhinal cortex
and hippocampal area CA3, consistent with the
idea that the hippocampus but not cortex uses
sparse conjunctive coding
Recording was made while animal traversed an
eight-arm radial maze.
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Why Are There Complementary Learning Systems?

• Discovery of structure requires gradual
  interleaved learning with dense (overlapping)
  patterns of activation.
• Models based on this idea have led to successful
  accounts of many aspects of conceptual
  development and disintegration of conceptual
  knowledge in semantic dementia (RM04).
• Rapid learning of new information in such systems
  leads to catastrophic interference.
• Structured knowledge gradually built up is
  rapidly destroyed.

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Keil, 1979
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The Model of Rumelhart (1990)
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Differentiation in Development, Catastrophic
Interference, and Interleaved Learning
Initially
Still Young
Somewhat Older
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Overview

• What is a memory?
• The essence of the connectionist/PDP perspective
• Contrasting systems-level approaches to the
  neural basis of memory
• The complementary learning systems approach
• McClelland, McNaughton, and OReilly, 1995
• How the complementary learning systems work
  together to create episodic and semantic
  memory.

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Effect of Prior Association on Paired-Associate
Learning in Control and Amnesic Populations
Base rates
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Kwok McClelland Model ofSemantic and Episodic
Memory

• Model includes slow learning cortical system and
  a fast-learning hippocampal system.
• Cortex contains units representing both content
  and context of an experience.
• Semantic memory is gradually built up through
  repeated presentations of the same content in
  different contexts.
• Formation of new episodic memory depends on
  hippocampus and the relevant cortical areas,
  including context.
• Loss of hippocampus would prevent initial rapid
  binding of content and context.
• Loss of context representation would prevent
  retrieval of context with content, or use of
  context in retrieval.
• Some patients lifelong amnesia for episodes may
  reflect loss of cortical representation of
  context.
• Episodic memories benefit from prior cortical
  learning when they involve meaningful materials.

Hippocampus
Relation
Cue
Context
Target
Neo-Cortex
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Kwok McClelland Simulation Pretraining

• Cortical network is pre-trained with 4
  cue-relation-target triples for each of 20
  different cues.
• Dog chews bone
• Dog chases cat
• Words are patterns of activation over units in
  the appropriate pool.
• Context varies randomly throughout cortical
  pretraining.
• Training frequency was varied to create strong
  and weak associates for each cue.

Hippocampus
Relation
Cue
Context
Target
Neo-Cortex
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Kwok McClelland Simulation Experiment

• Experiment involves presentation of a set of
  cue-target pairs in a fixed context cortex fills
  in relation as mediator.
• Hippocampal network assigns sparse conjunctive
  representation to the combined cue and context.
• Hebbian learning is used to associate this
  representation with the corresponding target
  pattern.
• Simulation addresses very easy (strong), easy
  (weak) and very hard (unassociated) conditions of
  Cutting (1978) experiment.

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Simulation Results From KM Model
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Summary

• Memory traces are in your connections memories
  are constructed using these traces (and those of
  other experiences) to constrain the construction
  process.
• Memory task performance involves cooperation
  among brain regions
• Cortical regions that gradually learn to
  represent content and context
• Medial temporal regions that can learn
  conjunctive associations of cortical patterns
  rapidly
• There are no separate systems dedicated to
  different kinds of memory. These functions
  depend on cooperating brain systems.
• A body of findings on spared and impaired
  learning of meaningful materials in amnesia can
  be explained by a model based on these principles.