Weekend bioRxiv Preprint Review: Could a neuroscientist understand a microprocessor?

The paper below, which may raise further concerns about potential direction of the Human Brain Project, is brief, and should be read to be properly appreciated. The concerns the paper supports have been raised before, by this writer and many others, but the paper supports those concerns by showing how little we might learn about a highly complex information system using even the latest neuronal probes if we have no detailed theoretical understanding of what functions are intended by the tissue under investigation. A well written and clever bit of work.



Could a neuroscientist understand a microprocessor?

Eric Jonas and Konrad Kording

May 26, 2016


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 the way 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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