Abstract
Neurons in sensory systems are commonly characterized by their receptive fields. These are experimentally often obtained by reverse-correlation analyses, for example, by calculating the spike-triggered average. The reverse-correlation approach, however, generally assumes a fixed temporal relation between spike-generating stimulus features and measured spikes. Temporal jitter of spikes will therefore distort the estimated receptive fields. Here, a novel extension of widely used reverse-correlation techniques (spike-triggered average as well as spike-triggered covariance) is presented that allows accurate measurements of receptive fields even in the presence of considerable spike-time jitter. It is shown that the method correctly recovers the receptive fields from simulated spike trains. When applied to recordings from auditory receptor cells of locusts, a considerable sharpening of receptive fields as compared to standard spike-triggered averages is observed. In addition, the multiple filters that are obtained from a conventional spike-triggered covariance analysis of these data can be collapsed into a single component if spike jitter is accounted for. Finally, it is shown how further effects on spike timing, such as systematic shifts in spike latency, can be included in the approach.
Notes
1Note, however, that even if the jitter distribution for deconvolution were known, one would face the notorious problem of noise amplification for frequencies that are poorly represented in the jitter distribution.