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. |