Transcript MemoryContinEd10-09-28

Memory: Its Nature and Organization in
the Brain
James L. McClelland
Stanford University
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
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?
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!
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.
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.
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.
The Complementary Learning Systems Theory
(McClelland, McNaughton & O’Reilly, 1995)
• Neuropsychological motivation
• The basic theory
• Neurophysiology consistent with the account
• Why there should be complementary systems
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.
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.
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.
hippocampus
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.
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
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.
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 (R&M’04).
• Rapid learning of new
information in such systems
leads to catastrophic
interference.
– Structured knowledge gradually
built up is rapidly destroyed.
Keil, 1979
The Model of Rumelhart (1990)
Differentiation in Development,
Catastrophic Interference,
and Interleaved Learning
Initially
Still Young
Somewhat Older
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 O’Reilly, 1995
 How the complementary learning systems work together to
create ‘episodic’ and ‘semantic’ memory.
Effect of Prior Association on Paired-Associate
Learning in Control and Amnesic Populations
Cutting (1978), Expt. 1
100
Control (Expt)
Percent Correct
80
Amnesic (Expt)
60
40
20
0
Base rates
-20
Very Easy
Easy
Fairly Easy
Hard
Category (Ease of Association)
Very Hard
Kwok & McClelland Model of
Semantic 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
Context
Neo-Cortex
Relation
Cue
Target
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
Context
Neo-Cortex
Relation
Cue
Target
Kwok & McClelland Simulation: Experiment
• Experiment involves
presentation of a set of cuetarget pairs in a fixed context;
cortex fills in relation as
mediator.
Hippocampus
• 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.
Context
Neo-Cortex
Relation
Cue
Target
Simulation Results From KM Model
Cutting (1978), Expt. 1
100
80
Percent Correct
Control (Model)
84
Amnesic (Model)
70
68
Control (Expt)
60
Amnesic (Expt)
40
20
9
0
0
0
-20
Very Easy
Easy
Fairly Easy
Hard
Category (Ease of Association)
Very Hard
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.