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Failure to learn during roving, analysing the unsupervised bias hypothesis

David Higgins, Michael Herzog
doi: https://doi.org/10.1101/383398
David Higgins
1Modeling of Cognitive Processes, TU Berlin
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  • For correspondence: dave@uiginn.com michael.herzog@epfl.ch
Michael Herzog
2École Polytechnique de Lausanne
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Abstract

We examine the unsupervised bias hypothesis [11] as an explanation for failure to learn two bisection tasks, when task sequencing is randomly alternating (roving). This hypothesis is based on the idea that a covariance based synaptic plasticity rule, which is modulated by a reward signal, can be biased when reward is averaged across multiple tasks of differing difficulties. We find that, in our hands, the hypothesis in its original form can never explain roving. This drives us to develop an extended mathematical analysis, which demonstrates not one but two forms of unsupervised bias. One form interacts with overlapping task representations and the other does not. We find that overlapping task representations are much more susceptible to unsupervised biases than non-overlapping representations. Biases from non-overlapping representations are more likely to stabilise learning. But this in turn is incompatible with the experimental understanding of perceptual learning and task representation, in bisection tasks. Finally, we turn to alternative network encodings and find that they also are unlikely to explain failure to learn during task roving as a result of unsupervised biases. As a solution, we present a single critic hypothesis, which is consistent with recent literature and could explain roving by a, much simpler, certainty normalised reward signalling mechanism.

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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 August 02, 2018.
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Failure to learn during roving, analysing the unsupervised bias hypothesis
David Higgins, Michael Herzog
bioRxiv 383398; doi: https://doi.org/10.1101/383398
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Failure to learn during roving, analysing the unsupervised bias hypothesis
David Higgins, Michael Herzog
bioRxiv 383398; doi: https://doi.org/10.1101/383398

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