Pitfalls in the Assessment of Brain-Machine Interfaces Using Information Transfer Rate

Lebedev, M. A.; Tseng, P.-H.; Ifft, P. J.; Ochei, D.; Nicolelis, M. A.

doi:10.1101/205013

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bioRxiv · 10.1101/205013

Pitfalls in the Assessment of Brain-Machine Interfaces Using Information Transfer Rate

Lebedev, M. A.·Tseng, P.-H.·Ifft, P. J.·Ochei, D.·Nicolelis, M. A.

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Abstract

Information transfer rate (ITR), measured in bits/s, can be applied to evaluate motor performance, including the capacity of brain-machine interfaces (BMIs) to control external actuators. In a 2013 article entitled \"Transfer of information by BMI\" and published in Neuroscience, Tehovnik and his colleagues utilized ITR to assess the performance of several BMIs reported in the literature. We examined these analyses closely and found several fundamental flaws in their evaluation of ITR. Here we discuss the pitfalls in Tehovniks measurements of ITR, as well as several other issues raised in \"Transfer of information by BMI\", including the claim that BMIs cannot be a reasonable option for paralyzed patients.\n\nHighlightsO_LIInformation transfer rate is discussed for BMI experiments, where subjects reach to targets.\nC_LIO_LITask settings, not just the number of possible targets, are important to calculate information correctly.\nC_LIO_LIActive tactile exploration can be quantified as information transfer, but the number of targets is insufficient for such quantification.\nC_LIO_LIInformation transfer rate increases with the number of neural recording channels.\nC_LIO_LIFor practical applications, improvement in quality of life is essential, not information transfer rate per se.\nC_LI

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Lebedev, M. A., Tseng, P.-H., Ifft, P. J., Ochei, D., Nicolelis, M. A.. 2017-10-18. Pitfalls in the Assessment of Brain-Machine Interfaces Using Information Transfer Rate. https://doi.org/10.1101/205013

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