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ANC/DTC Seminar: Misha Tsodyks, Weizmann Institute (Host: Mark van Rossum)

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Information storage in retrieval in neural network models of long-term memory

What
  • ANC/DTC Seminar
When Nov 20, 2012
from 11:00 AM to 12:00 PM
Where IF 4.31/4.33
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The dominant theoretical framework for long-term memory is attractor neural networks (ANN) in which information is encoded by neuronal ensembles and stored by Hebbian synaptic modifications. I will present two projects addressing the issues of storage and retrieval in this framework. In the first project, I will show how memory representations exhibit slow dynamics when similar input patterns are repeatedly presented to the network. Under certain conditions, memory representations collapse into single attractor encode groups of memories. This collapse can be observed in psychophysical experiments with sequences of morphed faces. In the second project, I will  address the issue of memory recall in the absence memory-specific retrieval cues, such as in free recall experiments. I will develop a an associative model of recall where each retrieved memory item is triggering the recall of the next item. This model can be cast in the language of random graph theory and some universal laws of recall can be derived that broadly account for classical free recall experiments.