Flexible Neural Hardware Supports Dynamic Computations in Retina

灵活的神经硬件支持视网膜动态计算

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Abstract

The ability of the retina to adapt to changes in mean light intensity and contrast is well known. Classically, however, adaptation is thought to affect gain but not to change the visual modality encoded by a given type of retinal neuron. Recent findings reveal unexpected dynamic properties in mouse retinal neurons that challenge this view. Specifically, certain cell types change the visual modality they encode with variations in ambient illumination or following repetitive visual stimulation. These discoveries demonstrate that computations performed by retinal circuits with defined architecture can change with visual input. Moreover, they pose a major challenge for central circuits that must decode properties of the dynamic visual signal from retinal outputs.

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