288 pp. per issue
6 x 9, illustrated
2014 Impact factor:

Neural Computation

May 2014, Vol. 26, No. 5, Pages 920-952
(doi: 10.1162/NECO_a_00581)
© 2014 Massachusetts Institute of Technology
Signal-Tuned Gabor Functions as Models for Stimulus-Dependent Cortical Receptive Fields
Article PDF (512.31 KB)

We propose and analyze a model, based on signal-tuned Gabor functions, for the receptive fields and responses of V1 cells. Signal-tuned Gabor functions are gaussian-modulated sinusoids whose parameters are obtained from a given, spatial, or spectral “tuning” signal. These functions can be proven to yield exact representations of their tuning signals and have recently been proposed as the kernels of a variant Gabor transform—the signal-tuned Gabor transform (STGT)—which allows the accurate detection of spatial and spectral events. Here we show that by modeling the receptive fields of simple and complex cells as signal-tuned Gabor functions and expressing their responses as STGTs, we are able to replicate the properties of these cells when tested with standard grating and slit inputs, at the same time emulating their stimulus-dependent character as revealed by recent neurophysiological studies.