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Identification of a Retinal Circuit for Recurrent Suppression Using Indirect Electrical Imaging.

ABSTRACT: Understanding the function of modulatory interneuron networks is a major challenge, because such networks typically operate over long spatial scales and involve many neurons of different types. Here, we use an indirect electrical imaging method to reveal the function of a spatially extended, recurrent retinal circuit composed of two cell types. This recurrent circuit produces peripheral response suppression of early visual signals in the primate magnocellular visual pathway. We identify a type of polyaxonal amacrine cell physiologically via its distinctive electrical signature, revealed by electrical coupling with ON parasol retinal ganglion cells recorded using a large-scale multi-electrode array. Coupling causes the amacrine cells to fire spikes that propagate radially over long distances, producing GABA-ergic inhibition of other ON parasol cells recorded near the amacrine cell axonal projections. We propose and test a model for the function of this amacrine cell type, in which the extra-classical receptive field of ON parasol cells is formed by reciprocal inhibition from other ON parasol cells in the periphery, via the electrically coupled amacrine cell network.

SUBMITTER: Greschner M

PROVIDER: S-EPMC5182067 | biostudies-literature | 2016 Aug

REPOSITORIES: biostudies-literature

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Identification of a Retinal Circuit for Recurrent Suppression Using Indirect Electrical Imaging.

Greschner Martin M Heitman Alexander K AK Field Greg D GD Li Peter H PH Ahn Daniel D Sher Alexander A Litke Alan M AM Chichilnisky E J EJ

Current biology : CB 20160707 15

Understanding the function of modulatory interneuron networks is a major challenge, because such networks typically operate over long spatial scales and involve many neurons of different types. Here, we use an indirect electrical imaging method to reveal the function of a spatially extended, recurrent retinal circuit composed of two cell types. This recurrent circuit produces peripheral response suppression of early visual signals in the primate magnocellular visual pathway. We identify a type o ...[more]

PMID: 27397894

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Project description:Electrical source imaging is used in presurgical epilepsy evaluation and in cognitive neurosciences to localize neuronal sources of brain potentials recorded on EEG. This study evaluates the spatial accuracy of electrical source imaging for known sources, using electrical stimulation potentials recorded on simultaneous stereo-EEG and 37-electrode scalp EEG, and identifies factors determining the localization error. In 11 patients undergoing simultaneous stereo-EEG and 37-electrode scalp EEG recordings, sequential series of 99-110 biphasic pulses (2 ms pulse width) were applied by bipolar electrical stimulation on adjacent contacts of implanted stereo-EEG electrodes. The scalp EEG correlates of stimulation potentials were recorded with a sampling rate of 30 kHz. Electrical source imaging of averaged stimulation potentials was calculated utilizing a dipole source model of peak stimulation potentials based on individual four-compartment finite element method head models with various skull conductivities (range from 0.0413 to 0.001 S/m). Fitted dipoles with a goodness of fit of ≥80% were included in the analysis. The localization error was calculated using the Euclidean distance between the estimated dipoles and the centre point of adjacent stimulating contacts. A total of 3619 stimulation locations, respectively, dipole localizations, were included in the evaluation. Mean localization errors ranged from 10.3 to 26 mm, depending on source depth and selected skull conductivity. The mean localization error increased with an increase in source depth (r(3617) = [0.19], P = 0.000) and decreased with an increase in skull conductivity (r(3617) = [-0.26], P = 0.000). High skull conductivities (0.0413-0.0118 S/m) yielded significantly lower localization errors for all source depths. For superficial sources (<20 mm from the inner skull), all skull conductivities yielded insignificantly different localization errors. However, for deeper sources, in particular >40 mm, high skull conductivities of 0.0413 and 0.0206 S/m yielded significantly lower localization errors. In relation to stimulation locations, the majority of estimated dipoles moved outward-forward-downward to inward-forward-downward with a decrease in source depth and an increase in skull conductivity. Multivariate analysis revealed that an increase in source depth, number of skull holes and white matter volume, while a decrease in skull conductivity independently led to higher localization error. This evaluation of electrical source imaging accuracy using artificial patterns with a high signal-to-noise ratio supports its application in presurgical epilepsy evaluation and cognitive neurosciences. In our artificial potential model, optimizing the selected skull conductivity minimized the localization error. Future studies should examine if this accounts for true neural signals.

Dataset Information

Identification of a Retinal Circuit for Recurrent Suppression Using Indirect Electrical Imaging.

Publications

Identification of a Retinal Circuit for Recurrent Suppression Using Indirect Electrical Imaging.

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