Shaul Druckmann
(http://www.janelia.org/people/scientist/shaul-druckmann)
Wednesday 11th July 2012
16.00
B10 Seminar Room, Basement,
Alexandra House, 17 Queen Square, London, WC1N 3AR
"Stability out of volatility: persistent stimulus encoding despite time varying activity in overcomplete representations"
Our brains are capable of remarkably stable stimulus representations, for instance during working memory tasks. While stimuli are kept in working memory, i.e., during delay periods in working memory tasks, neurons in prefrontal cortex display elevated firing rates and are thus thought to support the memory representation. Surprisingly, the activity of individual neurons during the delay period is constantly changing. Since neuronal activity encodes the stimulus, its time-varying dynamics appears paradoxical and incompatible with stable network representations. Indeed, this finding raises a fundamental question: can stable representations only be encoded with stable neural activity, or its corollary – is every change in activity a sign of change in network representation?
Here we explain how different time varying representations offered by individual neurons can be woven together to form a coherent, time invariant, representation. Motivated by two ubiquitous features of Neocortex: redundancy of neural representation and sparse intra-cortical connections, we derive a network architecture that resolves the apparent contradiction between representation stability and changing neural activity. Our theory predicts relations between neuronal functional properties and network architecture. Such networks can be seen as generalizations of line attractor models.
We show that our intuition regarding network representation, typically derived from considering single processes in isolation, may be misleading, and that the complex, time-varying activity of distributed processing in many neural and biological circuits does not necessarily imply that the network explicitly encodes time-varying properties.
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