Dynamics in networks of spiking neurons
Session Chair:
W. Gerstner
Networks of spiking neurons have several interesting dynamic properties,
for example very rapid and characteristic transients,
synchronous firing and asynchronous states.
A better understanding of typical
phenomena has important implications
for problems associated with neuronal coding (spikes or rates).
For example, the population activity is a ratetype quantity, but does not
need temporal averaging  which suggests
fast rate coding as a potential strategy.
The idea of the workshop is to start from
mathematical models of network dynamics,
see what is known in terms of results,
and then try to find out what the implications
for 'coding' in the most general sense could be.
A few points that could be raised in the workshop:

The populatation activity can respond
rapidly to changes of the stimulus
(rapid switching, e.g. Treves, 1992; Tsodyks and Sejnowski, 1995;
Van Vreeswijk and Somolinsky, 1996).
This suggests the capability of fast
signal transmission, consistent with
reaction time experiments (Thorpe et al. 1996).
What are the implications for 'rapid computation'?

Networks of spiking neurons
with balanced excitation/inhibition are noisy
(e.g., Van Vreeswijk and Sompolinsky, 1996) and so are cortical neurons
(e.g., Softky and Koch, 1993).
Is it `useful' for the net to have a certain noise level?
What is the signaltonoise ratio?

How do correlations in the firing times
of different neurons affect the signal transmission
capacity of the population (Spiridon et al., 1998; Panzeri et al., 1998)?

In simulations simplified models of population activity
must be used, e.g., Population Density Methods or
WilsonCowantype equations.
What is a good description of the dynamics of population activity?

What are the differences in the dynamics between homogeneous and
heterogeneous networks? Which coding strategies work
better in homogeneous, which better in inhomogeneous networks?

What would be desirable structures/connectivity patterns
to exploit the dynamical properties of spiking neurons?

What is the use of spontaneous acitivity in networks
of spiking neurons?

In view of all the above, what are coding strategies
in large networks of spiking neurons?
Potential audience: Researchers interested in
questions of coding and dynamics.
Program:
The workshop is planned for 2 sessions on Friday, Dec. 4.
Each session will be started off
by a couple of talks with enough time for lots of discussions.
(4 x 25 min talks + 40 minutes discussion in the morning,
3x 25 minutes talks + 90 minutes discussion in the evening).
 7.307.50 Introduction (W.Gerstner, Lausanne)
 7.508.20 C. van Vreeswijk (London/Jerusalem),
Asynchronous chaoslike firing in
heterogeneous networks
 8.208.50 D. Hansel (Paris),
Robust synchrony in large heterogeneous neuronal networks:
the role of inhibition
 8.509.15 Discussion
 9.159.45 D. Nykamp (NYU),
A Population Density Method that Facilitates
LargeScale Modeling of Neural Networks
 9.4510.15 J. Eggert (TU Munich),
Dynamics of assemblies of spiking neurons:
Integral and differential equation approaches
 10.1510.30 Discussion
  BREAK 
 4:004:30 S. Panzeri (Oxford),
The role of correlations in fast information transmission
 4:305:00 W. Maass (Graz),
Neural Systems as nonlinear Filters
 5:005:30 3 short contributions from additional participants
 5:307:00 PANEL DISCUSSION
including B.J. Richmond (NIH) and the speakers:
What do we learn from all of this for coding?
 role of noise
 sources of noise
 role of heterogeneity
 fast information processing schemes
Location:
The
NIPS'98 Workshops
will be held on December 4 and 5
in Breckenridghe (Colorado). The workshops follow
the main conference
Neural Information Processing Systems, NIPS'98
which will be held in Denver on December 13.