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Could a neuroscientist understand a microprocessor?

Eric Jonas, View ORCID ProfileKonrad Kording
doi: https://doi.org/10.1101/055624
Eric Jonas
University of California, Berkeley
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  • For correspondence: jonas@eecs.berkeley.edu
Konrad Kording
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Abstract

There is a popular belief in neuroscience that we are primarily data limited, that producing large, multimodal, and complex datasets will, enabled by data analysis algorithms, lead to fundamental insights into theway the brain processes information.Microprocessors are among those artificial information processing systems that are both complex and that we understand at all levels, from the overall logical flow, via logical gates, to the dynamics of transistors. Here we take a simulated classical microprocessor as a model organism, and use our ability to perform arbitrary experiments on it to see if popular data analysis methods from neuroscience can elucidate the way it processes information. We show that the approaches reveal interesting structure in the data but do not meaningfully describe the hierarchy of information processing in the processor. This suggests that current approaches in neuroscience may fall short of producing meaningful models of the brain.

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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. All rights reserved. No reuse allowed without permission.
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Posted May 26, 2016.
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Could a neuroscientist understand a microprocessor?
Eric Jonas, Konrad Kording
bioRxiv 055624; doi: https://doi.org/10.1101/055624
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Could a neuroscientist understand a microprocessor?
Eric Jonas, Konrad Kording
bioRxiv 055624; doi: https://doi.org/10.1101/055624

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