Postdoc and PhD position available in computational neuroscience

[Walter Senn]

A postdoc and a PhD position is available by October 1, 2004, in the
computational neuroscience group at the Institute of Physiology,
University of Bern, Switzerland.

We are studying biophysical models of neurons and synapses in the
context of cortical information processing and learning. The aim of our
reaearch is to relate dynamic properties of isolated neurons and
synapses (studied in in vitro experiments by the groups of H.-R.
Luescher and M.E. Larkum in our Institute) to higher cognitive
functions. In our recent work we described slow adaptation of cortical
neurons as measured in vitro in our lab [1], and related it to the
cortical representation of time [2]. Other experimental and theoretical
research in our lab shows that top-down input onto dendrites of layer 5
pyramidal cells can modulate the gain of these neurons [3], as observed
in attentional experiments in vivo. In a current project we are studying
spike-timing dependent plasticity (STDP) in the context of pattern
classification and reinforcement learning [4]. These algorithms will be
tested against data from in vitro experiments on long-term plasticity
performed in our lab.

Ideal candidates have a strong background in neural networks and/or
computational neuroscience, and are interested to work at the interface
between computational theories and electrophysiology. Please send CV,
addresses of three references, and a half page description of your work
and interests to wsenn at cns.unibe.ch (but no doc-files, if possible).

Walter Senn and Stefano Fusi
http://www.cns.unibe.ch/


[1] Neocortical pyramidal cells respond as integrate-and-fire neurons to
in vivo-like input currents.
    A. Rauch, G. La Camera, H-R Lüscher, W. Senn and S. Fusi. Journal of
Neurophysiology, 90:1598-1612 (2003)
    http://www.cns.unibe.ch/publications/ftp/paper_transferfunction.pdf

[2] Climbing neuronal activity as an event-based cortical representation
of time.
    J. Reutimann, V. Yakovlev, S. Fusi and W. Senn. The Journal of
Neuroscience, 24:3295-3303 (2004)
    http://www.cns.unibe.ch/publications/ftp/paper_climbing_activity.pdf

[3] Top-down dendritic input increases the gain of layer 5 pyramidal
neurons.
    M. Larkum, W. Senn and H.-R. Lüscher, Cerebral Cortex, in press (2004)
    http://www.cns.unibe.ch/publications/ftp/paper_gain_modulation04.pdf

[4] Learning with bounded synapses generates synaptic democracy and
balanced neurons.
    With a proof of the perceptron convergence theorem for bounded synapses.
    W. Senn and S. Fusi, submitted (2004)
    http://www.cns.unibe.ch/publications/ftp/paper_bounded_synapses04.pdf

--
Walter Senn                   Phone office: +41 31 631 87 21
Physiological Institute       Phone home:   +41 31 332 38 31
University of Bern            Fax: +41 31 631 46 11
Buehlplatz 5                  Email: wsenn at cns.unibe.ch
CH-3012 Bern                  http://www.cns.unibe.ch/~wsenn/