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NSF Science of Learning

NSF Science of Learning. Lila Davachi Dept Psychology and Neural Science New York University. Introduction. We ’ ve known the hippocampus and MTL are critical for new memories to become consolidated Decades of work to understand how the hippocampus (in particular) supports memory

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NSF Science of Learning

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  1. NSF Science of Learning Lila Davachi Dept Psychology and Neural Science New York University

  2. Introduction • We’ve known the hippocampus and MTL are critical for new memories to become consolidated • Decades of work to understand how the hippocampus (in particular) supports memory • Divergence in the field • - Rodent physiologists mostly studying spatial learning • - Psychologists studying word-list learning • - They could not be more different • Recent convergence (worth exploring further!) • - Reactivation mechanism for memory consolidation • - Sequences critical! • Related accomplishments • - Reactivation facilitates building complex knowledge structures through ‘integrative learning’

  3. Objectives • 1. Reactivation • Mechanism for consolidation during awake rest • More general mechanism for integrative learning 2. Active Learning

  4. Objectives • 1. Reactivation • Mechanism for consolidation during awake rest • More general mechanism for integrative learning 2. Active Learning

  5. Systems consolidation of memory • Systems consolidation is a process of trace reorganization proposed to shift the memory representation from a hippocampal-dependent to a hippocampal-independent representation. • Hypothesized to be achieved through both online and offline hippocampal-cortical interactions that occur after the initial learning. • Specifically, ‘replay’ of the pattern of activity linked with the initial experience has been hypothesized to be at least one mechanism supporting memory consolidation

  6. Background Hippocampal neural ‘replay’ has been shown in the rodent both during sleep (Pavlides & Winson, 1989; Wilson & McNaughton, 1994) and during awake rest (Foster & Wilson, 2006; Diba & Buzsaki, 2007). Critically, recent work has shown that selective suppression of hippocampal replay during offline periods can impair spatial memory (Girardeau et al, 2009; Ego-Stengel & Wilson, 2010)

  7. Hippocampal Replay

  8. time Experience Retrieval Off-line When does reactivation occur? Consciousness

  9. time Experience Retrieval Off-line When does reactivation occur? Consciousness Off-line? Sleep Awake rest? Brain region resting?

  10. Awake rest and memory consolidation Object-Face Task Baseline Rest Post-Task Rest 21 mins 8.4 mins 8.4 mins r = .37 (Tambini, Ketz and Davachi ,2010, Neuron)

  11. Awake rest and memory consolidation Object-Face Task Baseline Rest Post-Task Rest 21 mins 8.4 mins 8.4 mins r = .60 r = .37 r = .37 (Tambini, Ketz and Davachi ,2010, Neuron)

  12. Resting Hippocampal-LO correlations Assoc hits > misses (Tambini, Ketz and Davachi ,2010, Neuron)

  13. Change in correlations predict later memory for the preceding representations (Tambini, Ketz and Davachi, 2010, Neuron)

  14. Patterns of replay? Sleep before task Sleep after task Sutherland and McNaughton, CONB 2000 • Reactivation of patterns of activity across cells is specific

  15. Encoding Task Baseline Rest Post-Task Rest task-Post-rest similarity = .56 task- Base-rest similarity = .26

  16. Summary • Reactivation is seen during immediate post-encoding rest periods • Initial evidence that this can be seen at the level of single voxels in their patterns of activation with other voxels • The magnitude of reactivation is related to later memory • How long a rest period needed? • What counts as rest?

  17. Objectives • 1. Reactivation • Mechanism for consolidation during awake rest • More general mechanism for integrative learning 2. Active Learning

  18. Integration during learning: mediated by reactivation (Zeithamova et al, 2012, Neuron)

  19. Integration during learning: mediated by reactivation (Zeithamova et al, 2012, Neuron)

  20. Summary • Reactivation during new encoding can enhance memory updating/integration • Using multivariate methods, can measure the reactivation of categorical representations. This methodological innovation opens many doors to understanding how and when reactivation occurs and when is it beneficial/detrimental? • How could this be leveraged to enhance conceptual learning? • How much can be reactivated at once? • How effect reactivation? Single cue? Context?

  21. Reactivation different functions? • Reactivation during sleep/awake rest/online tasks? • Possibilities: • Reactivation during sleep: integrating into existing knowledge? • Awake rest: good for strenghthening? • On line tasks: good for updating?

  22. Objectives • 1. Reactivation • Mechanism for consolidation during awake rest • More general mechanism for integrative learning 2. Active Learning

  23. Active Learning • Hypothesis testing? Using what we know we don’t know to select information? • Recent work suggests that just the act of selecting, itself, may enhance encoding • Action systems in the brain rely on dopamine, for e.g. to reinforce appropriate behaviors • Is it possible then when learning in an active manner, the brain brings on another system that may not be technically ‘needed’ but that has the consequence of enhancing learning?

  24. Active Learning Active Learner ‘Yolked’ Learner Voss et al, 2011, Nature Neuroscience

  25. Active Learning Memory is enhanced!

  26. Active Learning • Different levels of ‘active’ • Possibility that simply pressing a button can leverage another system (dopamine) and enhance long-term retention of representations • Think iPAD!

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