Memory: Its Nature and Organization in the Brain

1. Memory: Its Nature and Organization in the Brain James L. McClelland Stanford University

2. 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

3. 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?

4. 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!

5. 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.

6. 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.

7. 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.

8. 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

9. 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.

10. 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.

11. hippocampus 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.

12. 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.

14. 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

15. 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.

16. 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.

17. Keil, 1979

18. The Model of Rumelhart (1990)

19. Differentiation in Development, Catastrophic Interference, and Interleaved Learning Initially Still Young Somewhat Older

20. 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.

21. Effect of Prior Association on Paired-Associate Learning in Control and Amnesic Populations Base rates

22. 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

23. 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

24. Hippocampus Relation Cue Context Target Neo-Cortex 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.

25. Simulation Results From KM Model

26. 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.