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Computational Neuroscience Journal Club

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Summary In a slight departure from our usual structure, this edition of the journal club will pay tribute to the late Krishna Shenoy, who sadly passed away in January. Krishna’s contributions to the field were significant and wide-ranging, particularly in areas of motor cortex dynamics and brain-computer interface (BCI). After a brief retrospective we’ll delve deeper into these contributions, examining some of his papers which had the greatest impact in the field.

We first review some of his key contributions to understanding the neural control of movement. 15 years ago, basic motor cortex responses were still poorly understood and subject of multiple controversies over competing representational views (such as whether cortical activity encodes muscle action or reach velocity). Krishna proposed the alternative “dynamical systems perspective”, spanning across many works over more than a decade.

We’ll then examine some of his work on BCI , starting with “A high-performance brain–computer interface” (Santhanam et al. 2006). This paper demonstrated an invasive BCI in two rhesus monkeys that achieved unprecedented information rates via a ‘direct end-point control’ strategy. We’ll then discuss “A high-performance neural prosthesis enabled by control algorithm design” (Gilja et al. 2012), where we consider a control algorithm based on a modified Kalman filter (ReFIT-KF) which enables high performance across cursor movement tasks.

References [1] “Cortical Preparatory Activity: Representation of Movement or First Cog in a Dynamical Machine?” (Churchland et al. 2010) [2] “Neural population dynamics during reaching” (Churchland et al. 2013) [3] “Cortical activity in the null space: permitting preparation without movement” (Churchland et al. 2014) [4] “A high-performance brain–computer interface” (Santhanam et al. 2006) [5] “A high-performance neural prosthesis enabled by control algorithm design” (Gilja et al. 2012)

This talk is part of the Computational Neuroscience series.

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