Volume 16 Supplement 1

## 24th Annual Computational Neuroscience Meeting: CNS*2015

- Poster presentation
- Open Access

# Could the prior development of the retinotopic map account for the radial bias in the orientation map in V1?

- Ryan Thomas Philips
^{1}Email author and - V Srinivasa Chakravarthy
^{1}

**16 (Suppl 1)**:P28

https://doi.org/10.1186/1471-2202-16-S1-P28

© Philips and Chakravarthy 2015

**Published:**18 December 2015

## Keywords

- Neural Activity
- Initial Configuration
- Initial Training
- Retinal Layer
- Previous Time Step

*ζ*

_{ r1,r2 }) along with its lateral excitations and inhibitions (

*η*

_{ kl }) from the previous time step.

*μ*

_{ ij,r1r2 }), lateral excitatory (

*E*

_{ ij,kl }) and lateral inhibitory (

*I*

_{ ij,kl }) weights adapt based on a normalized Hebbian mechanism. In order to develop the retinotopic map, the inputs to the retinal layer consists of centered (assumed to be the point of fixation) rectangular bars of varying dilations and rotations as modelled in [3]. The retinotopic map developed, biases the initial configuration of the orientation map (see Figure 1B) since all the bars given during the initial training are centered. For the subsequent refinement of the orientation map, Gaussians of differing orientation and positions (non-centered) are given as inputs to the retinal layer. After training for 4000 iterations (see Figure 1C,D), it is observed that the developed orientation map prefers those orientations which the retinotopy biases it towards, quantified by their corresponding histograms (See Figure 1E,F). As seen from the histogram the area occupied by the region mapping 1250-1500 is larger in the map developed assuming retinotopic bias, compared to that of the map developed assuming isotropy.

## Conclusions

A neural activity based model for the development of radially biased orientation maps in V1 is demonstrated.

## Authors’ Affiliations

## References

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- Bednar JA: Topographica: building and analyzing map-level simulations from Python, C/C++, MATLAB, NEST, or NEURON components. Frontiers in Neuroinformatics. 2009, 3: 8-PubMedPubMed CentralView ArticleGoogle Scholar
- Philips R, Chakravarthy S: The mapping of eccentricity and meridional angle onto orthogonal axes in the primary visual cortex: An activity-dependent developmental model. Frontiers in Computational Neuroscience. 2015, 9: 3-PubMedPubMed CentralView ArticleGoogle Scholar

## Copyright

This article is published under license to 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.