Reproducibility and Variability in Neural Spike Trains

Abstract

To provide information about dynamic sensory stimuli, the pattern of action potentials in spiking neurons must be variable. To ensure reliability these variations must be related, reproducibly, to the stimulus. For H1, a motion-sensitive neuron in the fly's visual system, constant-velocity motion produces irregular spike firing patterns, and spike counts typically have a variance comparable to the mean, for cells in the mammalian cortex. But more natural, time-dependent input signals yield patterns of spikes that are much more reproducible, both in terms of timing and of counting precision. Variability and reproducibility are quantified with ideas from information theory, and measured spike sequences in H1 carry more than twice the amount of information they would if they followed the variance-mean relation seen with constant inputs. Thus, models that may accurately account for the neural response to static stimuli can significantly underestimate the reliability of signal transfer under more natural conditions.

Encoding of motion in real time by the fly visual system

“…Across most of the cells' activity range, response variability (as given by the across-trial variance of the responses of spiking TCs to repetitive presentation of identical motion stimuli) is considerably smaller than the mean response amplitude. This is also true for constant stimuli [39 • ], despite an earlier claim to the contrary [40]. Although many questions remain regarding the biophysical and neuronal determinants of response variability, fly TCs appear to differ considerably with respect to variability from mammalian cortical neurons, such as in the motion pathway of monkeys [2].…”

Coding properties of spiking neurons: reverse and cross-correlations

“…The problem of neural coding can be phrased as two questions (Berry & Meister, 1998;Bialek, Rieke, de Ruyter van Steveninck & Warland, 1991;de Ruyter van Steveninck, Lowen, Strong, Koberle & Bialek, 1997;Kjaer, Hertz & Richmond, 1994;Ko Ènig, Engel & Singer, 1996;Optican & Richmond, 1987;Rieke, Warland, de Ruyter van Steveninck & Bialek, 1996;Roddey, Girish & Miller, 2000;Softky, 1995;Tovee, Rolls, Treves & Belles, 1993). …”

“…Systematic experiments along those lines have, for example, been performed by Poliakov, Powers and Binder (1997) in continuation of earlier models and experiments (Fetz & Gustafsson, 1983;Kirkwood & Sears, 1978;Knox, 1974;Moore, Segundo, Perkel & Levitan, 1970). The second question can be addressed by information theoretic measurements (Bialek et al, 1991;de Ruyter van Steveninck et al, 1997;Optican & Richmond, 1987;Tovee et al, 1993) or, in its simplest form by reverse-correlation measurements (de Boer & Kuyper, 1968). In the reverse-correlation approach, a neuron is stimulated by a time-dependent stimulus I t I 0 1 DI t .…”

Elementary Motion Detection

“…To study how H1 changes its response characteristics during flight is especially interesting, since H1 is one of the most studied cells in insect physiology (Brenner et al, 2000;Haag and Borst, 1997;Maddess and Laughlin, 1985;vanSteveninck et al, 1997). I investigated how the response properties of the lobula plate tangential cell H1 changes during flight using extracellular recording.…”