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Neuronal representation of time and probability

The accurate estimation of time intervals is an essential aspect of motor performance. Most often temporal judgments are tightly linked to the dynamics of spatial features in the environment, e.g. the time for a ball to arrive within reach (``time to contact''). Thus, the prediction of forthcoming events is crucial for organizing most efficiently motor performance. Removing temporal uncertainty by providing prior information about when to move significantly shortens reaction time (see for a review [1]). In a condition, in which the delay between two signals is manipulated such that a finite number of durations is randomly presented, reaction time decreases due to the increase of probability for the second (GO) signal to occur as time elapses from the first (instruction) signal [2]. In order to assess this probability, the elapsed time has to be correctly estimated. In other words, time estimation is an integral part of movement preparation and correct time estimation improves movement performance-expressed by reaction time. We have shown that timing processes are indeed represented in motor cortical single neuron activity, albeit in a manner that is strongly dependent on context [3]. Motor cortical neurons significantly synchronize their activity at moments when a GO signal is expected at the end of a correctly estimated delay [2,4,5,6]. This timing which is inherent to the motor task is represented in the temporal dynamics of significant precise spike synchrony not only in single pairs of neurons, but also at the population level [6]. The temporal population dynamics of synchrony becomes more structured with practice and learning. In particular, significant synchrony becomes more localized in time during late experimental sessions compared to early ones. In parallel, the average population firing rate mainly decreases with practice along with an improvement of the behavioral performance [6]. Furthermore, local field potentials (LFPs) recorded simultaneously with spiking single-neuron activity modulate during the delay period as a function of time. The estimation of a fixed delay period is associated with a single cycle modulation of the LFP. Its amplitude depends on the probability of movement execution and its timing on the duration of the delay to be estimated [7]. Additionally, the LFP signal is highly oscillatory during the delay period with a mean frequency in the ß-range (15-30Hz), an oscillation which abruptly stopps with movement onset. The correlation strength of the center peak varies and is strongly modulated both in time and with the behavioral condition. Both the frequency of the correlated oscillation as well as the correlation strength increases toward the end of the delay period, i.e. in relation to the expectancy of the GO signal.

[1] Riehle A (2005) In: Riehle A, Vaadia E (eds) Motor cortex in voluntary movements: a distributed system for distributed functions. CRC-Press, Boca Raton, FL, pp 213-240.

[2] Riehle A, Grün S, Diesmann M, Aertsen A (1997) Science 278: 1950-1953.

[3] Roux S, Coulmance M, Riehle A (2003) Europ J Neurosci 18: 1011-1016.

[4] Riehle A, Grammont F, Diesmann M, Grün S (2000) J Physiol (Paris) 94: 569-582.

[5] Grammont F, Riehle A (2003) Biol Cybern 88: 360-373.

[6] Kilavik BE, Roux S, Ponce-Alvarez A, Confais J, Grün S, Riehle A (2009) J Neurosci 29: 12653-12663.

[7] Roux S, MacKay WA, Riehle A (2006) BehavBrain Res 169: 335-351.
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