Spike-frequency adaptation separates transient communication signals from background oscillations
Jan Benda, André Longtin & Len Maler
Journal of Neuroscience 25(9), 2312-2321 (2005)
Abstract
Spike-frequency adaptation is a prominent feature of many neurons.
However, little is known about its computational role in processing
behaviorally relevant natural stimuli beyond filtering out slow
changes in stimulus intensity.
Here we present a more complex example where we demonstrate how
spike-frequency adaptation plays a key role in separating transient
signals from slower oscillatory signals.
We recorded in vivo from very rapidly adapting
electroreceptor afferents of the weakly electric fish
Apteronotus leptorhynchus.
The firing-frequency response of electroreceptors
to fast communication stimuli ("small chirps") is
strongly enhanced compared to the response to slower oscillations ("beats")
arising from interactions of same-sex conspecifics.
We are able to accurately predict the
electroreceptor afferent response to chirps and beats,
using a recently proposed general model for spike-frequency adaptation.
The model's parameters are determined for each neuron individually
from the responses to step stimuli.
We conclude that
the dynamics of the rapid spike-frequency adaptation is sufficient
to explain the data.
Analysis of additional data from step-responses demonstrates that spike
frequency adaptation acts subtractively rather than divisively
as expected from depressing synapses.
Therefore, the adaptation dynamics is linear
and creates a high-pass filter with a
cutoff frequency of 23 Hz that separates
fast signals from slower changes in input.
A similar critical frequency is seen in
behavioral data on the probability
of a fish emitting chirps as a function of beat frequency.
These results demonstrate how spike-frequency adaptation in general
can facilitate extraction of signals of different time scales,
specifically high-frequency signals embedded in slower oscillations.
Last modified: Fri Nov 28 11:23:03 CET 2008