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Towards a state-space geometry of neural responses to natural scenes: A steady-state approach

Bruce C. Hansen, David J. Field, Michelle R. Greene, Cassady Olson, Vladimir Miskovic
doi: https://doi.org/10.1101/705376
Bruce C. Hansen
1Colgate University, Department of Psychological & Brain Sciences, Neuroscience Program, Hamilton NY
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  • For correspondence: bchansen@colgate.edu
David J. Field
2Cornell University, Department of Psychology, Ithaca NY
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Michelle R. Greene
3Bates College, Neuroscience Program, Lewiston ME
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Cassady Olson
1Colgate University, Department of Psychological & Brain Sciences, Neuroscience Program, Hamilton NY
4University of Chicago, Committee on Computational Neuroscience, Chicago IL
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Vladimir Miskovic
5State University of New York at Binghamton, Department of Psychology, Binghamton NY
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Abstract

Our understanding of information processing by the mammalian visual system has come through a variety of techniques ranging from psychophysics and fMRI to single unit recording and EEG. Each technique provides unique insights into the processing framework of the early visual system. Here, we focus on the nature of the information that is carried by steady state visual evoked potentials (SSVEPs). To study the information provided by SSVEPs, we presented human participants with a population of natural scenes and measured the relative SSVEP response. Rather than focus on particular features of this signal, we focused on the full state-space of possible responses and investigated how the evoked responses are mapped onto this space. Our results show that it is possible to map the relatively high-dimensional signal carried by SSVEPs onto a 2-dimensional space with little loss. We also show that a simple biologically plausible model can account for a high proportion of the explainable variance (∼73%) in that space. Finally, we describe a technique for measuring the mutual information that is available about images from SSVEPs. The techniques introduced here represent a new approach to understanding the nature of the information carried by SSVEPs. Crucially, this approach is general and can provide a means of comparing results across different neural recording methods. Altogether, our study sheds light on the encoding principles of early vision and provides a much needed reference point for understanding subsequent transformations of the early visual response space to deeper knowledge structures that link different visual environments.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted July 16, 2019.
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Towards a state-space geometry of neural responses to natural scenes: A steady-state approach
Bruce C. Hansen, David J. Field, Michelle R. Greene, Cassady Olson, Vladimir Miskovic
bioRxiv 705376; doi: https://doi.org/10.1101/705376
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Towards a state-space geometry of neural responses to natural scenes: A steady-state approach
Bruce C. Hansen, David J. Field, Michelle R. Greene, Cassady Olson, Vladimir Miskovic
bioRxiv 705376; doi: https://doi.org/10.1101/705376

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