4.6 Article Proceedings Paper

General features of inhibition in the inner retina

期刊

JOURNAL OF PHYSIOLOGY-LONDON
卷 595, 期 16, 页码 5507-5515

出版社

WILEY
DOI: 10.1113/JP273648

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资金

  1. European Commission [ERC StG 677687 NeuroVisEco]
  2. National Institutes of Neurological Disorders and Stroke
  3. National Eye Institute of the National Institutes of Health [U01NS090562, 1R01EY023766]
  4. German Federal Ministry of Education and Research
  5. Max Planck Society (BMBF) [FKZ: 01GQ1002, MPG M.FE.LambdaKYBE0004]

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Visual processing starts in the retina. Within only two synaptic layers, a large number of parallel information channels emerge, each encoding a highly processed feature like edges or the direction of motion. Much of this functional diversity arises in the inner plexiform layer, where inhibitory amacrine cells modulate the excitatory signal of bipolar and ganglion cells. Studies investigating individual amacrine cell circuits like the starburst or A17 circuit have demonstrated that single types can possess specific morphological and functional adaptations to convey a particular function in one or a small number of inner retinal circuits. However, the interconnected and often stereotypical network formed by different types of amacrine cells across the inner plexiform layer prompts that they should be also involved in more general computations. In line with this notion, different recent studies systematically analysing inner retinal signalling at a population level provide evidence that general functions of the ensemble of amacrine cells across types are critical for establishing universal principles of retinal computation like parallel processing or motion anticipation. Combining recent advances in the development of indicators for imaging inhibition with large-scale morphological and genetic classifications will help to further our understanding of how single amacrine cell circuits act together to help decompose the visual scene into parallel information channels. In this review, we aim to summarise the current state-of-the-art in our understanding of how general features of amacrine cell inhibition lead to general features of computation.

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