Neurons of the cerebral cortex exhibit precise interspike timing in correspondence to behavior

Abstract

We show that times of spikes can be very precise. In the cerebral cortex, where each nerve cell is affected by thousands of others, it is the common belief that the exact time of a spike is random up to an averaged firing rate over tens of milliseconds. In a brain slice, precise time relations of several neurons have been observed. It remained unclear whether this phenomenon can also be observed in brains of behaving animals. Here we show, in behaving monkeys, that time intervals between spikes, measured in correspondence to a specific behavior, may be controlled to within the milliseconds range. data mining ͉ motor cortex ͉ neural codes ͉ precise timing ͉ single units A s known, most nerve cells in the brain communicate with each other by standard pulses called action potentials (or spikes). In the cerebral cortex, where each nerve cell is affected by thousands of others (1, 2), the common belief, so far, is that each neuron represents one aspect of the mental processes not by precise firing time, but by elevating its firing rate (3). However, if time relations among different neurons could be precisely controlled and read out, complex representations could be built from simpler ones efficiently and very fast (4-6). In a brain slice, precise time relations among several neurons have been observed (7). Could this phenomenon be also observed in brains of behaving animals? Here, we use data-mining techniques and rigorous statistic testing to test the precision of time intervals between spikes of different neurons. We show, in behaving monkeys, that when time intervals between spikes of different neurons are measured in correspondence to a specific behavior, timing may be controlled to the milliseconds range with the best case reaching 0.5 ms. Experiments Description and Drawings AnalysisIn our experiments, single unit activity was recorded from eight microelectrodes inserted into the motor and premotor cortices of a monkey while it was freely scribbling. Spike data analysis was carried for two sets of measurements. In the first set (consisting of 3 experimental days), time resolution of recording was 1 ms, whereas in the second set (consisting of 5 other days), it was 0.1 ms.Repeated scribbling paths were extracted by data-mining algorithms (8, 9). These paths are called drawing components. In a typical day there are 12-25 such drawing components. Fig. 1 illustrates the monkey's drawings and two simple drawing components. The Main IdeaTo determine whether there are any precise timing relations between the spikes of two neurons and the drawing, we selected a time slice before the start of each drawing component. For a given pair of neurons, we counted how many times a spike in the first neuron was followed by a spike in the second neuron within each of 50 particular time intervals. For the first set of measurements, these intervals were 0-1 ms, 2-3 ms, . . . , 98-99 ms, and for the second set they were 0-0.9 ms, 1-1.9 ms, 2-2.9 ms, . . . , 49-49.9 ms. The interval that repeated the largest number of times was hypot...

Cortical free-association dynamics: Distinct phases of a latching network

“…Experimental paradigms have been used to explore such activity, even in non-human primates, e.g. in the free drawing task developed by Moshe Abeles and coworkers [51]. The behavioural model and the mathematical model can be brought to bear onto each other.…”

Conditional modeling and the jitter method of spike resampling

“…Imagine making a 1-s recording from each of two neurons for each of 100 trials. Possibly, the two neurons have identical inhomogeneous (i.e., 1 Some authors prefer alternative terms for jittering, such as "dithering" (Gerstein 2004;Grün 2009;Pazienti et al 2007, Pazienti et al 2008, "teetering" (Shmiel et al 2005), or "artificial jitter" (Rokem et al 2006), etc., presumably to distinguish from another use of the word "jitter" as the intrinsic temporal variability in individual spikes. For example, in some situations involving highly reliable (Billimoria et al 2006) or simulated or modeled spike trains (Pazienti et al 2007), individual spikes can unambiguously be placed in correspondence with one another across trials.…”

“…In various guises, jitter and related spike resampling methods are in common use (Abeles and Gat 2001;Amarasingham 2004;Baker and Lemon 2000;Butts et al 2007;Date et al 1999;Dragoi and Buzsáki 2006;Fujisawa et al 2008;Furukawa and Middlebrooks 2002;Gerstein 2004;Grün 2009;Grün et al 2009;Gütig et al 2002;Harrison 2005;Harrison and Geman 2009;Hatsopoulos et al 2003;Ikegaya et al 2004;Jones et al 2004;Lu and Wang 2003;Maldonado et al 2009;Nádasdy et al 1999;Oram et al 1999;Pazienti et al 2007Pazienti et al , 2008Pipa et al 2007;Renart et al 2010;Rieke et al 1997;Rokem et al 2006;Shmiel et al 2005Shmiel et al , 2006Smith and Kohn 2008;Stark and Abeles 2009; see also Amarasingham et al 2011).…”

- Spike Trains as Event Sequences: Fundamental Implications

“…Various applications to neurophysiological questions can be found in [58,16,22,24,25,41,47,52,60,64,65,66,59,48,33]. It is one of the simplest and most effective models for isolating and visualizing synchrony-like correlations.…”