Human muscle spindles act as forward sensory models.

Modern theories of motor control incorporate forward models that combine sensory information and motor commands to predict future sensory states. Such models circumvent unavoidable neural delays associated with on-line feedback control. Here we show that signals in human muscle spindle afferents during unconstrained wrist and finger movements predict future kinematic states of their parent muscle. Specifically, we show that the discharges of type Ia afferents are best correlated with the velocity of length changes in their parent muscles approximately 100-160 ms in the future and that their discharges vary depending on motor sequences in a way that cannot be explained by the state of their parent muscle alone. We therefore conclude that muscle spindles can act as "forward sensory models": they are affected both by the current state of their parent muscle and by efferent (fusimotor) control, and their discharges represent future kinematic states. If this conjecture is correct, then sensorimotor learning implies learning how to control not only the skeletal muscles but also the fusimotor system.

An in computo investigation of the Landau-Kleffner syndrome

We describe a computational model of the thalamus and the cortex able to reproduce some essential epileptiform features commonly observed in the Landau-Kleffner syndrome. Investigation with this realistic model leads us to the formulation of a cellular mechanism that could be responsible for the epileptic discharges occuring with this severe syndrome. Understanding this mechanism is of prime importance for developing new therapeutical strategies. © 2007 IEEE.