Neural Computation via Neural Geometry: A Place Code for Inter-whisker Timing in the Barrel Cortex?

Abstract

The place theory proposed by Jeffress (1948) is still the dominant model of how the brain represents the movement of sensory stimuli between sensory receptors. According to the place theory, delays in signalling between neurons, dependent on the distances between them, compensate for time differences in the stimulation of sensory receptors. Hence the location of neurons, activated by the coincident arrival of multiple signals, reports the stimulus movement velocity. Despite its generality, most evidence for the place theory has been provided by studies of the auditory system of auditory specialists like the barn owl, but in the study of mammalian auditory systems the evidence is inconclusive. We ask to what extent the somatosensory systems of tactile specialists like rats and mice use distance dependent delays between neurons to compute the motion of tactile stimuli between the facial whiskers (or ‘vibrissae’). We present a model in which synaptic inputs evoked by whisker deflections arrive at neurons in layer 2/3 (L2/3) somatosensory ‘barrel’ cortex at different times. The timing of synaptic inputs to each neuron depends on its location relative to sources of input in layer 4 (L4) that represent stimulation of each whisker. Constrained by the geometry and timing of projections from L4 to L2/3, the model can account for a range of experimentally measured responses to two-whisker stimuli. Consistent with that data, responses of model neurons located between the barrels to paired stimulation of two whiskers are greater than the sum of the responses to either whisker input alone. The model predicts that for neurons located closer to either barrel these supralinear responses are tuned for longer inter-whisker stimulation intervals, yielding a topographic map for the inter-whisker deflection interval across the surface of L2/3. This map constitutes a neural place code for the relative timing of sensory stimuli.

The Robot Vibrissal System: Understanding Mammalian Sensorimotor Co-ordination Through Biomimetics

“…(Shimegi, Akasaki et al, 2000) with permission from Society for Neuroscience. The right panel shows the behaviour of our model (Wilson, Bednar et al, 2011). In both panels, the response facilitation index Ð computed as the ratio between the response to a paired stimulation of adjacent whiskers A and B and the linear sum of the responses to either A or B separately Ð is shown as a function of the time interval that separated the two whisker deflections.…”

“…In both panels, the response facilitation index Ð computed as the ratio between the response to a paired stimulation of adjacent whiskers A and B and the linear sum of the responses to either A or B separately Ð is shown as a function of the time interval that separated the two whisker deflections. Figure reproduced from (Wilson, Bednar et al, 2011). (Widrow and Stearns, 1985).…”

“…In order to provide a further test of the generality of the place theory, we sought to apply it to a model of tactile stimulus processing in rodent barrel cortex (Wilson, Bednar et al, 2011). We asked whether model cortical neurons receiving synaptic inputs via delays governed by realistic connection geometry and plausible axonal propagation speeds would match the range of real responses to paired stimulation of adjacent whiskers.…”

“…Inputs to the model were patterns of activity in simulated layer 4, encoding the spatial location and direction of whisker deflections caused by tactile stimuli that varied in shape, direction and speed. Layer 4 activity patterns were then remapped as layer 2/3 activity patterns using distance-dependent signalling delays in the layer 4 to layer 2/3 projection, to additionally encode the relative timing of whisker deflections (Wilson, Bednar et al, 2011). This model represents a biologically grounded method by which to map the full spatial-temporal pattern of multi-whisker inputs to an essentially spatial representation of the stimulus across layer 2/3.…”

Effects of Adaptation on Discrimination of Whisker Deflection Velocity and Angular Direction in a Model of the Barrel Cortex

“…Prior modeling work carried out within the barrel system has been aimed at elucidating response properties of barrel neurons in the context of thalamic and cortical input, delineating the interplay of synaptic and intrinsic neuronal properties, describing the transformation of receptive fields from barreloid to barrel cells, and the computation of temporal intervals between the deflections of distinct whiskers (Kyriazi and Simons, 1993 ; Pinto et al, 1996 , 2003 ; Pesavento et al, 2010 ; Wilson et al, 2011 ; Ly et al, 2012 ; Middleton et al, 2012 ; Pesavento and Pinto, 2012 ; Liu et al, 2014 ). The modeling work in this manuscript follows a similar modeling philosophy to that of Kyriazi and Simons ( 1993 ) and Liu et al ( 2014 ), in that I do not attempt to incorporate the detailed intrinsic neuronal properties of TC, FS, and RS cells; rather, I construct a biologically-oriented model that captures network structure and dynamics, with model parameters sharply constrained by physiological measurements.…”