Synapses with short-term plasticity are optimal estimators of presynaptic membrane potentials.

The trajectory of the somatic membrane potential of a cortical neuron exactly reflects the computations performed on its afferent inputs. However, the spikes of such a neuron are a very low-dimensional and discrete projection of this continually evolving signal. We explored the possibility that the neuron's efferent synapses perform the critical computational step of estimating the membrane potential trajectory from the spikes. We found that short-term changes in synaptic efficacy can be interpreted as implementing an optimal estimator of this trajectory. Short-term depression arose when presynaptic spiking was sufficiently intense as to reduce the uncertainty associated with the estimate; short-term facilitation reflected structural features of the statistics of the presynaptic neuron such as up and down states. Our analysis provides a unifying account of a powerful, but puzzling, form of plasticity.

How is somatosensory information used to adapt to changes in the mechanical environment?

Recent studies examining adaptation to unexpected changes in the mechanical environment highlight the use of position error in the adaptation process. However, force information is also available. In this chapter, we examine adaptation processes in three separate studies where the mechanical environment was changed intermittently. We compare the expected consequences of using position error and force information in the changes to motor commands following a change in the mechanical environment. In general, our results support the use of position error over force information and are consistent with current computational models of motor learning. However, in situations where the change in the mechanical environment eliminates position error the central nervous system does not necessarily respond as would be predicted by these models. We suggest that it is necessary to take into account the statistics of prior experience to account for our observations. Another deficiency in these models is the absence of a mechanism for modulating limb mechanical impedance during adaptation. We propose a relatively simple computational model based on reflex responses to perturbations which is capable of accounting for iterative changes in temporal patterns of muscle co-activation.

Modulation of somatosensory processing by action.

Psychophysical evidence suggests that sensations arising from our own movements are diminished when predicted by motor forward models and that these models may also encode the timing and intensity of movement. Here we report a functional magnetic resonance imaging study in which the effects on sensation of varying the occurrence, timing and force of movements were measured. We observed that tactile-related activity in a region of secondary somatosensory cortex is reduced when sensation is associated with movement and further that this reduction is maximal when movement and sensation occur synchronously. Motor force is not represented in the degree of attenuation but rather in the magnitude of this region's response. These findings provide neurophysiological correlates of previously-observed behavioural forward-model phenomena, and advocate the adopted approach for the study of clinical conditions in which forward-model deficits have been posited to play a crucial role.