title: Computational role of large receptive fields in the primary somatosensory cortex.
abstract: Computational studies are challenging the intuitive view that neurons with broad tuning curves are necessarily less discriminative than neurons with sharp tuning curves. In the context of somatosensory processing, broad tuning curves are equivalent to large receptive fields. To clarify the computational role of large receptive fields for cortical processing of somatosensory information, we recorded ensembles of single neurons from the infragranular forelimb/forepaw region of the rat primary somatosensory cortex while tactile stimuli were separately delivered to different locations on the forelimbs/forepaws under light anesthesia. We specifically adopted the perspective of individual columns/segregates receiving inputs from multiple body location. Using single-trial analyses of many single-neuron responses, we obtained two main results. 1) The responses of even small populations of neurons recorded from within the same estimated column/segregate can be used to discriminate between stimuli delivered to different surround locations in the excitatory receptive fields. 2) The temporal precision of surround responses is sufficiently high for spike timing to add information over spike count in the discrimination between surround locations. This surround spike-timing code (i) is particularly informative when spike count is ambiguous, e.g., in the discrimination between close locations or when receptive fields are large, (ii) becomes progressively more informative as the number of neurons increases, (iii) is a first-spike code, and (iv) is not limited by the assumption that the time of stimulus onset is known. These results suggest that even though large receptive fields result in a loss of spatial selectivity of single neurons, they can provide as a counterpart a sophisticated temporal code based on latency differences in large populations of neurons without necessarily sacrificing basic information about stimulus location.
authors.affiliation: School of Biomedical Engineering, Science and Health Systems, Drexel University, Philadelphia, Pennsylvania 19104, USA.
authors.forename: Guglielmo
authors.initials: G
authors.lastname: Foffani
authors.forename: John K
authors.initials: JK
authors.lastname: Chapin
authors.forename: Karen A
authors.initials: KA
authors.lastname: Moxon
mesh_terms: D000200:Action Potentials / Q000502:physiology; D000818:Animals; D001931:Brain Mapping; D003198:Computer Simulation; D004192:Discrimination, Psychological / Q000502:physiology; D005552:Forelimb / Q000294:innervation; D008959:Models, Neurological; D009474:Neurons / Q000502:physiology*; D010812:Physical Stimulation / Q000379:methods; D051381:Rats; D011930:Reaction Time / Q000502:physiology; D013003:Somatosensory Cortex / Q000166:cytology* / Q000502:physiology; D014110:Touch / Q000502:physiology; D014738:Vibrissae / Q000294:innervation