Abstract
Adaptation is at the heart of sensation and nowhere is it more salient than in early visual processing. Light adaptation in photoreceptors is doubly dynamical: it depends upon the temporal structure of the input and it affects the temporal structure of the response. We introduce a non-linear dynamical adaptation model of photoreceptors. It is simple enough that it can be solved exactly and simulated with ease; analytical and numerical approaches combined provide both intuition on the behavior of dynamical adaptation and quantitative results to be compared with data. Yet the model is rich enough to capture intricate phenomenology. First, we show that it reproduces the known phenomenology of light response and short-term adaptation. Second, we present new recordings and demonstrate that the model reproduces cone response with great precision. Third, we derive a number of predictions on the response of photoreceptors to sophisticated stimuli such as periodic inputs, various forms of flickering inputs, and natural inputs. In particular, we demonstrate that photoreceptors undergo rapid adaptation of response gain and time scale, over ∼ 300 ms—i. e., over the time scale of the response itself—and we confirm this prediction with data. For natural inputs, this fast adaptation can modulate the response gain more than tenfold and is hence physiologically relevant.
Highlights
The ability of neurons to modulate their response as a function of the environment or the task is at once a staple of neural information processing and an achievement of neural biophysics
Photoreceptors constitute the interface between the visual world and the cerebral world, as they convert light inputs into neural signals. This conversion is subject to continuous adaptation: response gain and time scale vary as a function of input history
This adaptation is ‘dynamical’ both because it depends upon the temporal structure of the stimulus and because it affects the kinetics of the response
Summary
The ability of neurons to modulate their response as a function of the environment or the task is at once a staple of neural information processing and an achievement of neural biophysics. One expects significant adaptation as these cells convert wide-ranging natural inputs into neural activity confined to a comparatively restricted range This is true, in particular, of peripheral visual cells [1,2,3,4,5,6,7,8,9,10,11] and especially of photoreceptors [11,12,13,14,15,16,17,18,19,20,21,22,23,24,25].
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