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Model-based analysis of pattern motion processing in mouse primary visual cortex

Muir, Dylan R. and Roth, Morgane M. and Helmchen, Fritjof and Kampa, Björn M.. (2015) Model-based analysis of pattern motion processing in mouse primary visual cortex. Frontiers in neural circuits, 9. p. 38.

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Abstract

Neurons in sensory areas of neocortex exhibit responses tuned to specific features of the environment. In visual cortex, information about features such as edges or textures with particular orientations must be integrated to recognize a visual scene or object. Connectivity studies in rodent cortex have revealed that neurons make specific connections within sub-networks sharing common input tuning. In principle, this sub-network architecture enables local cortical circuits to integrate sensory information. However, whether feature integration indeed occurs locally in rodent primary sensory areas has not been examined directly. We studied local integration of sensory features in primary visual cortex (V1) of the mouse by presenting drifting grating and plaid stimuli, while recording the activity of neuronal populations with two-photon calcium imaging. Using a Bayesian model-based analysis framework, we classified single-cell responses as being selective for either individual grating components or for moving plaid patterns. Rather than relying on trial-averaged responses, our model-based framework takes into account single-trial responses and can easily be extended to consider any number of arbitrary predictive models. Our analysis method was able to successfully classify significantly more responses than traditional partial correlation (PC) analysis, and provides a rigorous statistical framework to rank any number of models and reject poorly performing models. We also found a large proportion of cells that respond strongly to only one stimulus class. In addition, a quarter of selectively responding neurons had more complex responses that could not be explained by any simple integration model. Our results show that a broad range of pattern integration processes already take place at the level of V1. This diversity of integration is consistent with processing of visual inputs by local sub-networks within V1 that are tuned to combinations of sensory features.
Faculties and Departments:05 Faculty of Science > Departement Biozentrum > Former Organization Units Biozentrum > Neural Networks (Mrsic-Flogel)
UniBasel Contributors:Roth, Morgane and Muir, Dylan R
Item Type:Article, refereed
Article Subtype:Research Article
Publisher:Frontiers Media
e-ISSN:1662-5110
Note:Publication type according to Uni Basel Research Database: Journal article -- This Document is Protected by copyright and was first published by Frontiers. All rights reserved. It is reproduced with permission.
Language:English
Identification Number:
Last Modified:16 Aug 2016 14:07
Deposited On:16 Aug 2016 13:51

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