Browsing by Subject "Adaptation, Ocular"

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    Dopaminergic modulation of retinal processing from starlight to sunlight.
    (Journal of pharmacological sciences, 2019-05-04) Roy, Suva; Field, Greg D
    Neuromodulators such as dopamine, enable context-dependent plasticity of neural circuit function throughout the central nervous system. For example, in the retina, dopamine tunes visual processing for daylight and nightlight conditions. Specifically, high levels of dopamine release in the retina tune vision for daylight (photopic) conditions, while low levels tune it for nightlight (scotopic) conditions. This review covers the cellular and circuit-level mechanisms within the retina that are altered by dopamine. These mechanisms include changes in gap junction coupling and ionic conductances, both of which are altered by the activation of diverse types of dopamine receptors across diverse types of retinal neurons. We contextualize the modulatory actions of dopamine in terms of alterations and optimizations to visual processing under photopic and scotopic conditions, with particular attention to how they differentially impact distinct cell types. Finally, we discuss how transgenic mice and disease models have shaped our understanding of dopaminergic signaling and its role in visual processing. Cumulatively, this review illustrates some of the diverse and potent mechanisms through which neuromodulation can shape brain function.
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    Ignoring correlated activity causes a failure of retinal population codes.
    (Nature communications, 2020-09-14) Ruda, Kiersten; Zylberberg, Joel; Field, Greg D
    From starlight to sunlight, adaptation alters retinal output, changing both the signal and noise among populations of retinal ganglion cells (RGCs). Here we determine how these light level-dependent changes impact decoding of retinal output, testing the importance of accounting for RGC noise correlations to optimally read out retinal activity. We find that at moonlight conditions, correlated noise is greater and assuming independent noise severely diminishes decoding performance. In fact, assuming independence among a local population of RGCs produces worse decoding than using a single RGC, demonstrating a failure of population codes when correlated noise is substantial and ignored. We generalize these results with a simple model to determine what conditions dictate this failure of population processing. This work elucidates the circumstances in which accounting for noise correlations is necessary to take advantage of population-level codes and shows that sensory adaptation can strongly impact decoding requirements on downstream brain areas.