Quadratic Mutual Information estimation of mouse dLGN receptive fields reveals asymmetry between ON and OFF visual pathways

Mu, Zhiguang, Nikolic, Konstantin ORCID: https://orcid.org/0000-0002-6551-2977 and Schultz, Simon (2021) Quadratic Mutual Information estimation of mouse dLGN receptive fields reveals asymmetry between ON and OFF visual pathways. In: 2021 10th International IEEE/EMBS Conference on Neural Engineering (NER), 4-6 May 2021, Virtual conference.

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The longstanding theory of “parallel processing” predicts that, except for a sign reversal, ON and OFF cells are driven by a similar pre-synaptic circuit and have similar visual field coverage, direction/orientation selectivity, visual acuity and other functional properties. However, recent experimental data challenges this view. Here we present an information theory based receptive field (RF) estimation method - quadratic mutual information (QMI) - applied to multi-electrode array electrophysiological recordings from the mouse dorsal lateral geniculate nucleus (dLGN). This estimation method provides more accurate RF estimates than the commonly used Spike-Triggered Average (STA) method, particularly in the presence of spatially correlated inputs. This improved efficiency allowed a larger number of RFs (285 vs 189 cells) to be extracted from a previously published dataset. Fitting a spatial-temporal Difference-of-Gaussians (ST-DoG) model to the RFs revealed that while the structural RF properties of ON and OFF cells are largely symmetric, there were some asymmetries apparent in the functional properties of ON and OFF visual processing streams - with OFF cells preferring higher spatial and temporal frequencies on average, and showing a greater degree of orientation selectivity.

Item Type: Conference or Workshop Item (Paper)
ISSN: 1948-3554
ISBN: 9781728143378
Identifier: 10.1109/ner49283.2021.9441357
Identifier: 10.1109/ner49283.2021.9441357
Additional Information: © 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Keywords: Radio frequency, Visualization, Fitting, Estimation, Neural engineering, Parallel processing, Mice
Subjects: Construction and engineering > Biomedical engineering
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Depositing User: Konstantin Nikolic
Date Deposited: 15 Jun 2021 11:19
Last Modified: 28 Aug 2021 07:15
URI: https://repository.uwl.ac.uk/id/eprint/7959


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