Relating information, encoding and adaptation: decoding the population firing rate in visual areas 17/18 in response to a stimulus transition.

ABSTRACT: Neurons in the primary visual cortex typically reach their highest firing rate after an abrupt image transition. Since the mutual information between the firing rate and the currently presented image is largest during this early firing period it is tempting to conclude this early firing encodes the current image. This view is, however, made more complicated by the fact that the response to the current image is dependent on the preceding image. Therefore we hypothesize that neurons encode a combination of current and previous images, and that the strength of the current image relative to the previous image changes over time. The temporal encoding is interesting, first, because neurons are, at different time points, sensitive to different features such as luminance, edges and textures; second, because the temporal evolution provides temporal constraints for deciphering the instantaneous population activity. To study the temporal evolution of the encoding we presented a sequence of 250 ms stimulus patterns during multiunit recordings in areas 17 and 18 of the anaesthetized ferret. Using a novel method we decoded the pattern given the instantaneous population-firing rate. Following a stimulus transition from stimulus A to B the decoded stimulus during the first 90ms was more correlated with the difference between A and B (B-A) than with B alone. After 90ms the decoded stimulus was more correlated with stimulus B than with B-A. Finally we related our results to information measures of previous (B) and current stimulus (A). Despite that the initial transient conveys the majority of the stimulus-related information; we show that it actually encodes a difference image which can be independent of the stimulus. Only later on, spikes gradually encode the stimulus more exclusively.

SUBMITTER: Eriksson D 

PROVIDER: S-EPMC2860500 | biostudies-literature | 2010 Apr

REPOSITORIES: biostudies-literature