Article,
Noise and coupling affect signal detection and bursting in a simulated physiological neural network
Journal of Neurophysiology, (2002)
Abstract
Signal detection in the CNS relies on a complex interaction between
the numerous synaptic inputs to the detecting cells. Two effects,
stochastic resonance (SR) and coherence resonance (CR) have been
shown to affect signal detection in arrays of basic neuronal models.
Here, an array of simulated hippocampal CA1 neurons was used to test
the hypothesis that physiological noise and electrical coupling can
interact to modulate signal detection in the CA1 region of the hippocampus.
The array was tested using varying levels of coupling and noise with
different input signals. Detection of a subthreshold signal in the
network improved as the number of detecting cells increased and as
coupling was increased as predicted by previous studies in SR; however,
the response depended greatly on the noise characteristics present
and varied from SR predictions at times. Careful evaluation of noise
characteristics may be necessary to form conclusions about the role
of SR in complex systems such as physiological neurons. The coupled
array fired synchronous, periodic bursts when presented with noise
alone. The synchrony of this firing changed as a function of noise
and coupling as predicted by CR. The firing was very similar to certain
models of epileptiform activity, leading to a discussion of CR as
a possible simple model of epilepsy. A single neuron was unable to
recruit its neighbors to a periodic signal unless the signal was
very close to the synchronous bursting frequency. These findings,
when viewed in comparison with physiological parameters in the hippocampus,
suggest that both SR and CR can have significant effects on signal
processing in vivo.
