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Nonlinear Encoding of Tactile Patterns in the Barrel Cortex

¹ Harvard–Massachusetts Institute of Technology Division of Health Sciences and Technology, Harvard University, Cambridge, Massachusetts 02138; ² Division of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts 02138

Submitted 16 September 2003; accepted in final form 16 December 2003

Cells in the rodent barrel cortex respond to vibrissa deflection with a brief excitatory component and a longer suppressive component. The response to a given deflection is thus scaled because of suppression induced by a preceding deflection, causing the neuronal response to be linked to the temporal properties of the peripheral stimulus. A paired-deflection stimulus was used to characterize the postexcitatory suppression and a 3-deflection stimulus was used to investigate the nonlinear response to patterns of whisker deflections in barbiturate-anesthetized Sprague–Dawley rats. The postexcitatory suppression was not dependent on a sensory-evoked action potential to the first deflection, implying that it is likely a subthreshold property of the network. The suppression induced by a deflection served to suppress both the excitatory and suppressive components of a subsequent neuronal response, thus effectively disinhibiting it. Two different response properties were observed in the recorded cells. Approximately 65% responded to a vibrissa deflection with an excitatory component followed by a suppressive component and 35% responded with excitation, suppression, and a subsequent rebound in excitation. Based on these observations of postexcitatory dynamics, a prediction method was used to estimate neuronal responses to more complex stimulus trains. Using the 2nd-order representation obtained from the paired-deflection stimulus, responses to general periodic deflection patterns were well predicted. A higher cutoff frequency was predicted for rebound cells compared with cells not exhibiting rebound excitation, consistent with experimental observations. The method also predicted the response of neurons to a random aperiodic deflection pattern. Therefore the temporal structure of cortical dynamics after a single deflection dictates the response to complex temporal patterns, which are more representative of stimuli encountered under natural conditions.

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