Tell me something interesting: Context dependent adaptation in somatosensory cortex

• Published in: Journal of neuroscience methods Vol. 210; no. 1; pp. 35 - 48
• Main Authors: Davies, Lucy A., Garcia-Lazaro, Jose A., Schnupp, Jan W.H., Wennekers, Thomas, Denham, Susan L.
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier B.V 15.09.2012
• Subjects: Action Potentials - physiology; Adaptation; Adaptation, Physiological - physiology; Animals; Local context; Models, Neurological; Rats; Rats, Long-Evans; Sensory Receptor Cells - physiology; Somatosensory cortex; Somatosensory Cortex - cytology; Somatosensory Cortex - physiology; Spike-rate adaptation; Stimulus statistics; Synapses - physiology; Synaptic depression; Somatosensory cortex; Synaptic depression; Spike-rate adaptation; Stimulus statistics; Local context; Adaptation
• ISSN: 0165-0270; 1872-678X; 1872-678X
• DOI: 10.1016/j.jneumeth.2011.12.003

It is widely accepted that through a process of adaptation cells adjust their sensitivity in accordance with prevailing stimulus conditions. However, in two recent studies exploring adaptation in the rodent inferior colliculus and somatosensory cortex, neurons did not adapt towards global mean, but rather became most sensitive to inputs that were located towards the edge of the stimulus distribution with greater intensity than the mean. We re-examined electrophysiological data from the somatosensory study with the purpose of exploring the underlying encoding strategies. We found that neural gain tended to decrease as stimulus variance increased. Following adaptation to changes in global mean, neuronal output was scaled such that the relationship between firing rate and local, rather than global, differences in stimulus intensity was maintained. The majority of cells responded to large, positive deviations in stimulus amplitude; with a small number responding to both positive and negative changes in stimulus intensity. Adaptation to global mean was replicated in a model neuron by incorporating both spike-rate adaptation and tonic-inhibition, which increased in proportion to stimulus mean. Adaptation to stimulus variance was replicated by approximating the output of a population of neurons adapted to global mean and using it to drive a layer of recurrently connected depressing synapses. Within the barrel cortex, adaptation ensures that neurons are able to encode both overall levels of variance and large deviations in the input. This is achieved through a combination of gain modulation and a shift in sensitivity to intensity levels that are greater than the mean.