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Spiking allows neurons to estimate their causal effect

Benjamin James Lansdell, Konrad Paul Kording
doi: https://doi.org/10.1101/253351
Benjamin James Lansdell
1Department of Bioengineering, University of Pennsylvania, PA, USA
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Konrad Paul Kording
1Department of Bioengineering, University of Pennsylvania, PA, USA
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Abstract

Learning aims at causing better performance and the typical gradient descent learning is an approximate causal estimator. However real neurons spike, making their gradients undefined. Interestingly, a popular technique in economics, regression discontinuity design, estimates causal effects using such discontinuities. Here we show how the spiking threshold can reveal the influence of a neuron’s activity on the performance, indicating a deep link between simple learning rules and economics-style causal inference.

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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 4.0 International license.
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Posted January 25, 2018.
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Spiking allows neurons to estimate their causal effect
Benjamin James Lansdell, Konrad Paul Kording
bioRxiv 253351; doi: https://doi.org/10.1101/253351
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Spiking allows neurons to estimate their causal effect
Benjamin James Lansdell, Konrad Paul Kording
bioRxiv 253351; doi: https://doi.org/10.1101/253351

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