A simple white noise analysis of neuronal light responses

Chichilnisky, E. J.

doi:10.1080/net.12.2.199.213

Cited by 527 publications

(429 citation statements)

References 22 publications

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“…To conclude, equation (13) simply describes a synaptic rectification, which is a very common feature in neural modeling and in retinal models [4,5,12]. A smooth rectification is needed here to account for the observed 'low-input' range of ganglion cells, where ganglion cells clearly act underlinearly, but are not totally silent either (see cell simulations in Section 3.3).…”

Section: Synaptic Current Upon Ganglion Cellsmentioning

confidence: 99%

“…The easiest way to implement a sub-linearity of retinal responses with respect to contrast, is that of standard models [4], also known as LNP (Linear, Nonlinear, Poisson) models. These models allow to choose, or experimentally determine (Chichilnisky [5]) a static non-linear function through which the filtered signal is passed before spike generation. Contrast gain control will then be represented by a compression part in the non-linear function, making the output under-linear with the input contrast.…”

Section: Other Models Of Gain Controlmentioning

confidence: 99%

“…Contrast gain control will then be represented by a compression part in the non-linear function, making the output under-linear with the input contrast. Advantage of this approach is its tractability from experimental data [5]. Inconveniences are its being non-dynamical (it cannot explain the temporal changes in filtering with contrast), its lack of spatial extent (the nonlinearity applies only cell by cell, so perceptual enhancements such as that presented in Section 3.4.1 are greatly reduced) and the fact that it does not explain at all where the non-linearity occurs in the retina.…”

Section: Other Models Of Gain Controlmentioning

confidence: 99%

“…Furthermore, most standard models have an empirical architecture, designed to fit some experimental ganglion cells recordings [5,17,12]. Instead, we propose here a model where each part can be mapped to physiology, including the interpretation of most parameters.…”

Section: Introductionmentioning

confidence: 99%

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Virtual Retina: A biological retina model and simulator, with contrast gain control

2008

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Section: Synaptic Current Upon Ganglion Cellsmentioning

confidence: 99%

Section: Other Models Of Gain Controlmentioning

confidence: 99%

Section: Other Models Of Gain Controlmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Virtual Retina: A biological retina model and simulator, with contrast gain control

2008

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“…However, in some cases it may be necessary to fit a model with an unconstrained nonlinearity. In these cases, the filtered stimulus is usually plotted against the actual responses ( Figure 3D) and the relationship between the two is estimated either by binning and averaging or by fitting a suitable parametric function (Chichilnisky 2001).…”

Section: The Approachmentioning

confidence: 99%

The use of computational modeling to link sensory processing with behavior in Drosophila

Clemens

Murthy

2017

Preprint

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A major goal of systems neuroscience is to understand how the brain represents information, and how those representations are used to drive behavior. Even though genetic model organisms like Drosophila grant unprecedented experimental access to the nervous system for manipulating and recording neural activity, the complexity of natural stimuli and natural behaviors still poses a challenge for solving the connections between neural activity and behavior. Here, we advocate for the use of computational modeling to complement (and enhance) the Drosophila toolkit. We first lay out a modelling framework for making sense of the relation between natural sensory stimuli, neuronal responses, and natural behavior. We then highlight how this framework can be used to reveal how neural circuits drive behavior, using selected case studies.PeerJ Preprints | https://doi.org/10.7287/peerj.preprints.2720v1 | CC BY 4.0 Open Access |

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Expression of Channelrhodopsin‐2 in Rod Bipolar Cells Restores ON and OFF Responses at High Spatial Resolution in Blind Mouse Retina

Reh

Lee

Zeck

2022

Advanced Therapeutics

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Rod bipolar cells (rBCs) represent a promising target for vision restoration as they relay information to the major image processing pathways in the retina. However, the diversity of the retinal output and the resolution obtained by optogenetic actuation of rBCs is unclear. Herein, the photostimulation of rBCs expressing channelrhodopsin‐2 is studied in a transgenic, photoreceptor‐degeneration mouse (rd10) while simultaneously recording the retinal output using a high‐density microelectrode array. After analyzing several hundred retinal output neurons, both optogenetic ON and OFF type responses are identified at similar ratio at stimulation thresholds well below photodamage intensity. The temporal latency of both response types is in the same range (≈$\approx$ 50 ms) as reported for healthy mouse retinal ganglion cells. The spatial resolution ranges between 0.1 and 0.2 cycles deg‐1, which is close to that found in healthy mice. Photostimulation over an extended area (29 deg) but not localized stimuli induces strong bursting activity, which may originate from large‐scale activation of a coupled network of retinal cells. The distinct ON and OFF optogenetically induced activity patterns in retinal ganglion cells and the high temporal and spatial resolution demonstrate that near‐physiological vision restoration may be achieved under optimal conditions in late stage retinal degeneration.

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A simple white noise analysis of neuronal light responses

Cited by 527 publications

References 22 publications

Virtual Retina: A biological retina model and simulator, with contrast gain control

Virtual Retina: A biological retina model and simulator, with contrast gain control

The use of computational modeling to link sensory processing with behavior in Drosophila

Expression of Channelrhodopsin‐2 in Rod Bipolar Cells Restores ON and OFF Responses at High Spatial Resolution in Blind Mouse Retina

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