Identifying the nonlinear structure of receptive fields in the mammalian retina
Dimokratis Karamanlis,Tim Gollisch · COSYNE 2022
Sensory neurons can integrate their inputs nonlinearly, and this nonlinear pooling allows the extraction of complex features from the natural environment. Such nonlinear computations are ubiquitous in the visual system, and can be captured with encoding models that partition receptive fields into subunits whose outputs are nonlinearly combined. In the retina, the nonlinearities that transform subunit signals before integration by retinal ganglion cells affect the cells’ sensitivity to the spatial structure of natural scenes. Fitting subunit models to neural responses remains a challenge, as av
Thu, Mar 17, 2022