Neural simulations of adaptive reafference suppression in the elasmobranch electrosensory system

Abstract

The electrosensory system of elasmobranchs is extremely sensitive to weak electric fields, with behavioral thresholds having been reported at voltage gradients as low as 5 nV/cm. To achieve this amazing sensitivity, the electrosensory system must extract weak extrinsic signals from a relatively large reafferent background signal associated with the animal's own movements. Ventilatory movements, in particular, strongly modulate the firing rates of primary electrosensory afferent nerve fibers, but this modulation is greatly suppressed in the medullary electrosensory processing nucleus, the dorsal octavolateral nucleus. Experimental evidence suggests that the neural basis of reafference suppression involves a common-mode rejection mechanism supplemented by an adaptive filter that fine tunes the cancellation. We present a neural model and computer simulation results that support the hypothesis that the adaptive component may involve an anti-Hebbian form of synaptic plasticity at molecular layer synapses onto ascending efferent neurons, the principal output neurons of the nucleus. Parallel fibers in the molecular layer carry a wealth of proprioceptive, efference copy, and sensory signals related to the animal's own movements. The proposed adaptive mechanism acts by canceling out components of the electrosensory input signal that are consistently correlated with these internal reference signals.