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Spike times make sense

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Many behavioral responses are completed too quickly for the underlying sensory processes to rely on estimation of neural firing rates over extended time windows. Theoretically, first-spike times could underlie such rapid responses, but direct evidence has been lacking. Such evidence has now been uncovered in the human somatosensory system. We discuss these findings and their potential generalization to other sensory modalities, and we consider some future challenges for the neuroscientific community.

Section snippets

First-spike times code fingertip events

To investigate neuronal coding in the human somatosensory system, Johansson and Birznieks [4] recorded from different afferents (FA-I, SA-I and SA-II) in the median nerve within the upper arm while they varied the direction of force and the shape of a stimulus applied to the fingertip. But instead of using the mean firing rate as a dependent variable, they focused on spike timing relative to stimulus onset. They found that the stimulus direction systematically influenced first-spike latency for

Rank-order coding at the population level

Because recordings were not obtained simultaneously across the various afferents, it is difficult to understand how this first-spike time information is used at the population level. One possibility would be to rely on the specific order of firing among the afferents (a ‘rank order’ or ‘recruitment order’ code). Because first-spike latency jitter from trial to trial was <1 ms (median value) in all cases (i.e. much smaller than the variance in latency between afferents of one type), this code is

Origins of spike asynchrony and the need for reference signals

First-spike time differences across neurons (‘spike asynchrony’) arise in neuronal systems in two non-exclusive situations (not counting stochastic effects in spike generation processes): either because of stimulus dynamics (different receptors activated at different times), as in visual motion processing 6, 7, or because of differences in stimulus features (because the time to threshold directly reflects feature strength and optimality 2, 8, 9, 10 (Figure 1). At the next level, however,

Reading out spike asynchrony: internal and external reference signals

In laboratory situations, stimulus onset is generally clearly defined and can serve as an obvious reference signal (as in the study by Johansson and Birznieks [4]), but it requires further assumptions to be used explicitly: whereas the experimenter knows precisely when a stimulus is turned on, the subject still has to acquire this information from the sensory input itself. For example, periods of neuronal silence preceding stimulus onset, together with synaptic adaptation properties, might

How general is spike-time coding?

Over recent years, there has been a host of experimental discoveries in various systems – some of them mentioned here – that hint to the sophistication of neural codes employed in the brain (Table 1). Spike timing comes up almost systematically as a highly reliable coding dimension, at least insofar as the relevant reference signals are available to the experimenter. In our opinion, exploring these reference signals might turn out to be one important key to solving several outstanding problems

Acknowledgements

This work was supported in part by the ACI ‘Integrated and Computational Neuroscience’ of the CNRS. We are thankful to Vivek Jayaraman, Christof Koch, Gilles Laurent and Daniel Pressnitzer for helpful comments.

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