Untitled - Laboratory of Neurophysics and Physiology

Milenkovic, O., Alterovitz, G., Battail, G., Coleman, T. P., et al., Eds., Special Issue on Molecular
Biology and Neuroscience, IEEE Transactions on Information Theory, Volume 56, Number 2, February,
2010.
Dimitrov, A.G., Lazar, A.A. and Victor, J.D., Information Theory in Neuroscience, Journal of Computational
Neuroscience, Vol. 30, No. 1, February 2011, pp. 1-5, Special Issue on Methods of Information
Theory.
W5
Neural mechanisms of working memory limits
Space Grignard, Wed & Thu, 9:00-17:30
Albert Compte, IDIBAPS, Barcelona, Spain
Zachary Kilpatrick, University of Houston, Houston, TX, USA
Working memory can store multiple pieces of transitory information during a delay period. Each item
of information can then be used in later neural computations. Electrode recording and fMRI studies
have identified several brain areas that encode working memory with persistent activity or based on
transient neural dynamics. Importantly, the process appears to have some fundamental limits. First,
memory of a single cue degrades in accuracy as a function of the delay time. Second, memory accuracy
of multiple objects is limited by the number of objects present. Several conceptual frameworks have
been proposed to explain the nature of these limitations (slots vs. resource models). Only recently
have the neural mechanisms responsible for working memory limits been explored computationally and
neurophysiologically. This session will bring together experimentalists and theorists to discuss how the
neural activity that serves working memory affects its accuracy and capacity.
Talks:
Ronald van den Berg, University of Cambridge; Variability in visual working memory
Jaejin Lee, University of Pittsburgh
Christian Machens, Champalimaud
Jonathan Wallis, University of California - Berkeley; Prefrontal mechanisms contributing to working
memory
Paul Bays, University College London; Working memory capacity and allocation reflect noise in neural
populations
Vladimir Itskov, Univerisity of Nebraska Associative memory encoding in bump attractor networks:
switching between dual functions on the same network
Sophie Deneve, École Normale Supérieure; What are the real limits of working memory in balanced
spiking networks
Yuri Dabaghian, Baylor College of Medicine; A topological model of the hippocampal spatial map and
spatial learning capacity
Gianluigi Mongillo, Universite Paris Descartes
Tim Buschman, Princeton University; Neural Dynamics of Working Memory Capacity Limits in Prefrontal
and Parietal Cortex
Masud Husain, University of Oxford; Forgetting over seconds: attention and the role of the hippocampus
Yoram Burak, Hebrew University of Jerusalem; Fundamental limits on persistent activity in stochastic
attractor networks
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