two new papers on transient responses of pacemakers at Neuroprose

[Stiber]

The following 2 papers are now available for copying from the
Neuroprose repository: stiber.transcomp.ps.Z, stiber.transhyst.ps.Z.

stiber.transcomp.ps.Z (194085 bytes, 10 pages)

M. Stiber, R. Ieong, J.P. Segundo
Responses to Transients in Living and Simulated Neurons
(submitted to NIPS'95; also technical report HKUST-CS95-26)

This paper is concerned with synaptic coding when inputs to a neuron
change over time.  Experiments were performed on a living and
simulated embodiment of a prototypical inhibitory synapse.  Results
indicate that the neuron's reponse lags its input by a fixed delay.
Based on this, we present a qualitative model for phenomena previously
observed in the living preparation, including hysteresis and
dependence of discharge regularity on rate of change of presynaptic
spike rate.  As change is the rule rather than the exception in life,
understanding neurons' responses to nonstationarity is essential for
understanding their function.


stiber.transhyst.ps.Z (244297 bytes, 13 pages)

M. Stiber and R. Ieong

Hysteresis and Asymmetric Sensitivity to Change in Pacemaker Responses
to Inhibitory Input Transients
(in press, Proc. Int. Conf. on Brain Processes, Theories, and Models. 
W.S.  McCulloch: 25 Years in Memoriam; also technical report
HKUST-CS95-29)

The coding of presynaptic spike trains to postsynaptic ones is the
unit of computation in nervous systems. While such coding has been
examined in detail under stationary input conditions, the effects of
changing inputs have until recently been understood only
superficially.  When a neuron receives transient inputs with
monotonically changing instantaneous rate, its response along time
depends not only on the rate at that time, but also on the sign and
magnitude of its rate of change.  This has been shown previously for
the living embodiment of a prototypical inhibitory synapse.  We
present simulations of a physiological model of this living
preparation which reproduce its behaviors.  Based on these results, we
propose a simple model for the neuron's response involving a constant
delay between its input and internal state.  This is then generalized
to a nonlinear dynamical model of any similar system with an internal
state which lags its input.

** If you absolutely, positively can't produce your own hardcopy (or
induce a friend to do so for you), hardcopies can be requested in
writing to: Technical Reports, Department of Computer Science, The
Hong Kong University of Science and Technology, Clear Water Bay,
Kowloon, Hong Kong; don't forget to include the TR number. **

---
Dr. Michael Stiber                              stiber at bpe.es.osaka-u.ac.jp
c/o Prof. S. Sato
Department of Biophysical Engineering
Osaka University
Toyonaka 560 Osaka, Japan

On leave from:
Department of Computer Science				stiber at cs.ust.hk
The Hong Kong University of Science & Technology	tel: +852-2358-6981
Clear Water Bay, Kowloon, Hong Kong			fax: +852-2358-1477