Title
Modeling population responses of rapidly-adapting mechanoreceptive fibers.
Abstract
The population response of rapidly-adapting (RA) fibers is one component of the physiological substrate of the sense of touch. Herein, we describe a computational scheme based on the population-response model by K.O. Johnson (J. Neurophysiol. 37: 48-72, 1974) which we extended by permitting the capability to include the spatial distributions of receptors in the glabrous skin linked to RA fibers. The hypothetical cases simulated were rectangular, uniformly random and proximo-distally Gaussian distributions. Each spatial organization produced qualitatively distinct population-response profiles that also varied due to stimulus parameters. The effects of stimulus amplitude, average innervation density and contactor-probe location were studied by considering various response measures: number of active fibers, summated firing rate and the average firing rate of a subset of the modeled population. The outcome of the measures were statistically compared among simulated anatomical distributions. The response is the same for rectangular and uniformly random distributions, both of which have a homogeneous innervation density. However, the Gaussian distribution produced statistically different responses when the measure was not averaged over the subset population which represented the receptive field of a higher-order neuron. These results indicate that, as well as stimulus parameters, the anatomical organization is a significant determinant of the population response. Therefore, reconstructing population activity for testing psychophysical hypotheses must presently be done with care until the organization of the receptors within the skin has been clarified.
Year
DOI
Venue
2002
10.1023/A:1016535413000
Journal of Computational Neuroscience
Keywords
Field
DocType
population response,rapidly-adapting fiber,mechanoreceptor,computational model
Receptive field,Population,Biological system,Control theory,Mechanoreceptor,Gaussian,Spatial organization,Somatosensory system,Stimulus (physiology),Statistics,Amplitude,Mathematics
Journal
Volume
Issue
ISSN
12
3
0929-5313
Citations 
PageRank 
References 
7
1.79
0
Authors
2
Name
Order
Citations
PageRank
Burak Güçlü1307.65
Stanley J Bolanowski2113.16