A quantitative analysis of information about past and present stimuli
encoded by spikes of A1 neurons.
S. Klampfl, S. V. David, P. Yin, S. A. Shamma, and W. Maass
In order to process the rich temporal structure of their acoustic environment,
organisms have to integrate information over time into an appropriate neural
response. Previous studies have addressed the modulation of responses of
auditory neurons to a current sound in dependence of the immediate
stimulation history, but a quantitative analysis of this important
computational process has been missing. In this study, we analyzed temporal
integration of information in the spike output of 122 single neurons in
primary auditory cortex (A1) of four awake ferrets in response to random tone
sequences. We quantified the information contained in the responses about
both current and preceding sounds in two ways: by estimating directly the
mutual information between stimulus and response, and by training linear
classifiers to decode information about the stimulus from the neural
response. We found that (i) many neurons conveyed a significant amount of
information not only about the current tone, but also simultaneously about
the previous tone, (ii) that the neural response to tone sequences was a
non-linear combination of responses to the tones in isolation, and (iii)
that, nevertheless, much of the information about current and previous tones
could be extracted by linear decoders. Furthermore our analysis of these
experimental data shows that methods from information theory and the
application of standard machine learning methods for extracting specific
information yield quite similar results.
Reference: S. Klampfl, S. V. David, P. Yin, S. A. Shamma, and W. Maass.
A quantitative analysis of information about past and present stimuli encoded
by spikes of A1 neurons.
Journal of Neurophysiology, 108:1366-1380, 2012.