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Rapid neural coding in the mouse retina with the first wave of spikes

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HAL Id: hal-01026507

https://hal.inria.fr/hal-01026507

Submitted on 21 Jul 2014

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Rapid neural coding in the mouse retina with the first

wave of spikes

Geoffrey Portelli, John Barrett, Evelyne Sernagor, Timothée Masquelier,

Pierre Kornprobst

To cite this version:

Geoffrey Portelli, John Barrett, Evelyne Sernagor, Timothée Masquelier, Pierre Kornprobst. Rapid

neural coding in the mouse retina with the first wave of spikes. Twenty Third Annual Computational

Neuroscience Meeting: CNS2014, Jul 2014, Québec City, Canada. 15 (Suppl 1), pp.P120, 2014, BMC

Neuroscience. �hal-01026507�

(2)

P O S T E R P R E S E N T A T I O N

Open Access

Rapid neural coding in the mouse retina with the

first wave of spikes

Geoffrey Portelli

1*

, John Barrett

2

, Evelyne Sernagor

2

, Timothée Masquelier

3,4

, Pierre Kornprobst

1

From

The Twenty Third Annual Computational Neuroscience Meeting: CNS*2014

Québec City, Canada. 26-31 July 2014

For flashed stimuli presentations, it is known that the latency of the first spike of retinal ganglion cells (RGC) encodes information about the stimulus. This was shown at the level of individual neurons but also at the popula-tion level by considering the relative latency between cer-tain pairs of RGC [1]. In this work, we further investigated this population code on mouse retinas using a 60-channel MEA (469 RGC pooled from 5 retinas) in response to gratings of varying phase, spatial frequency.

Interestingly, due to the presence of a high spontaneous activity, we did not find any RGC pair showing a clear relation between the relative latencies and stimuli as in [1]. So we extended this analysis to the whole population instead of looking at individual pairs, by considering the relative order of all spike latencies, i.e. the shape of the first wave of spikes (FWS) after stimulus onset.

We first showed that the FWS is specific to each sti-muli. To do so, we defined a distance between the FWS of a reference grating and the gratings with similar spa-tial frequency and varying phases. This distance was correlated to the phase difference between gratings.

Then, to estimate quantitatively the coding efficiency of the FWS, we performed a discrimination task where the aim was to identify the phase among gratings of identical spatial frequency. We compared the performance (fraction of correct predictions, FCP) of the FWS under classical Bayesian decoders to independent response latency of each recorded RGC. Results showed the FWS decoder which is based on the relative rank of latencies only, was as efficient as the pure latency decoder based on absolute latency values (~73% of FCP for both).

Finally, as the spikes from the output of the retina are conveyed and processed by higher neural structure such as the Lateral Geniculate Nucleus (LGN), we investigated

the possible effects of an a posteriori processing stage on the neural code. We fed a simulated LGN-like layer [2] with the spikes obtained from our recordings. We then analyzed the output spikes from the simulated LGN using the same discrimination task. As the number of RGC increased, the FWS decoder rapidly outperforms the latency decoder. Considering all RGC, we compared the performance obtained before and after the LGN. Results showed the latency decoder discrimination per-formance decreased (from 73% to 40% of FCP) although the FWS decoder discrimination performance remained more stable (from 73% to 70% of FCP).

Acknowledgements

The research received financial support from the 7th Framework Programme for Research of the European Commission, under Grant agreement no 600847: RENVISION project of the Future and Emerging Technologies (FET) programme (Neuro-bio-inspired systems (NBIS) FET-Proactive Initiative). Authors’ details

1

Neuromathcomp, INRIA, Sophia Antipolis, 06902, France.2Institute of Neuroscience, Medical School, Newcastle University, Newcastle UK.3Institut

de la Vision, UPMC Université Paris 06, Paris, 75012, France.4CNRS, UMR 7210, Paris, 75012, France.

Published: 21 July 2014 References

1. Gollisch T, Meister M: Rapid neural coding in the retina with relative spike latencies. Science 2008, 319:1108-1111, DOI: 10.1126/science.1149639. 2. Masquelier T: Relative spike time coding and STDP-based orientation

selectivity in the early visual system in natural continuous and saccadic vision : a computational model. J Comput Neurosci 2012, 32:425-441.

doi:10.1186/1471-2202-15-S1-P120

Cite this article as: Portelli et al.: Rapid neural coding in the mouse retina with the first wave of spikes. BMC Neuroscience 2014 15(Suppl 1): P120.

* Correspondence: geoffrey.portelli@inria.fr

1Neuromathcomp, INRIA, Sophia Antipolis, 06902, France

Full list of author information is available at the end of the article Portelli et al. BMC Neuroscience 2014, 15(Suppl 1):P120 http://www.biomedcentral.com/1471-2202/15/S1/P120

© 2014 Portelli et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http:// creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

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