Seven years of recording from monkey cortex with a chronically implanted multiple microelectrode

Krüger, Jürgen; Caruana, Fausto; Volta, Riccardo Dalla; Rizzolatti, Giacomo

doi:10.3389/fneng.2010.00006

Cited by 55 publications

(58 citation statements)

References 22 publications

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“…Chronic intracortical electrode signals degrade with time, which decreases BMI performance and success rates [92–95]. To date, efforts to rescue performance have focused on designing new kinematic decoders [56–59,63,65,96,97].…”

Section: Discussionmentioning

confidence: 99%

Augmenting intracortical brain-machine interface with neurally driven error detectors

et al. 2017

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Objective Making mistakes is inevitable, but identifying them allows us to correct or adapt our behavior to improve future performance. Current brain-machine interfaces (BMIs) make errors that need to be explicitly corrected by the user, thereby consuming time and thus hindering performance. We hypothesized that neural correlates of the user perceiving the mistake could be used by the BMI to automatically correct errors. However, it was unknown whether intracortical outcome error signals were present in the premotor and primary motor cortices, brain regions successfully used for intracortical BMIs. Approach We report here for the first time a putative outcome error signal in spiking activity within these cortices when rhesus macaques performed an intracortical BMI computer cursor task. Main results We decoded BMI trial outcomes shortly after and even before a trial ended with 96% and 84% accuracy, respectively. This led us to develop and implement in real-time a first-of-its-kind intracortical BMI error “detect-and-act” system that attempts to automatically “undo” or “prevent” mistakes. The detect-and-act system works independently and in parallel to a kinematic BMI decoder. In a challenging task that resulted in substantial errors, this approach improved the performance of a BMI employing two variants of the ubiquitous Kalman velocity filter, including a state-of-the-art decoder (ReFIT-KF). Significance Detecting errors in real-time from the same brain regions that are commonly used to control BMIs should improve the clinical viability of BMIs aimed at restoring motor function to people with paralysis.

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Section: Discussionmentioning

confidence: 99%

Augmenting intracortical brain-machine interface with neurally driven error detectors

et al. 2017

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“…2A). The strategy of the current study was specifically to exploit the stability of the microwire recordings (25,26) to ask whether the functional properties of face-selective cells are consistent over long time scales. Accordingly, after briefly verifying that the basic visual properties of the targeted neurons conformed to expectations regarding face selectivity in recordings collected on a single day ( Fig.…”

Section: Resultsmentioning

confidence: 99%

Face-selective neurons maintain consistent visual responses across months

McMahon

Jones

Bondar

et al. 2014

Proc. Natl. Acad. Sci. U.S.A.

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Face perception in both humans and monkeys is thought to depend on neurons clustered in discrete, specialized brain regions. Because primates are frequently called upon to recognize and remember new individuals, the neuronal representation of faces in the brain might be expected to change over time. The functional properties of neurons in behaving animals are typically assessed over time periods ranging from minutes to hours, which amounts to a snapshot compared to a lifespan of a neuron. It therefore remains unclear how neuronal properties observed on a given day predict that same neuron's activity months or years later. Here we show that the macaque inferotemporal cortex contains face-selective cells that show virtually no change in their patterns of visual responses over time periods as long as one year. Using chronically implanted microwire electrodes guided by functional MRI targeting, we obtained distinct profiles of selectivity for face and nonface stimuli that served as fingerprints for individual neurons in the anterior fundus (AF) face patch within the superior temporal sulcus. Longitudinal tracking over a series of daily recording sessions revealed that face-selective neurons maintain consistent visual response profiles across months-long time spans despite the influence of ongoing daily experience. We propose that neurons in the AF face patch are specialized for aspects of face perception that demand stability as opposed to plasticity.vision | fMRI | physiology M any biological systems perform in a stable manner over time. The consistent behavior that is evident at the global level of the organism can persist despite continuous change in the system's component parts. A cup of coffee, for instance, tastes the same today as it did one year ago, despite the fact that the receptors in our taste buds are replaced every two weeks (1). In addition to the continuous replacement of individual cells, the protein constituents of cells likewise undergo nearly continuous turnover (2). What happens in the central nervous system? Because the lifespan of most neurons in the brain approaches that of the organism (3), it is conceivable that the population of faceselective cells that fire today when you see your mother, for instance, is identical to the population that fired under the same circumstances 10 years ago. However, in the absence of direct evidence, there is no reason to assume that this is the case, or more generally that stable network performance implies stable units. And indeed, both theoretical (4) and experimental results from motor cortex (5, 6) demonstrate that a network composed of unstable units may nonetheless exhibit stable performance. Recent recordings from the mouse hippocampus showed that reliable location signaling is driven largely by neurons that gradually enter and leave the population of functionally active place cells over the course of several days (7). In that study, only 15% of longitudinally monitored neurons were found to retain the same place fields in two sessions that were separ...

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“…Recent attempts include microwire arrays (Krüger et al 2010;Nicolelis et al 2003;Palmer 1978;Williams et al 1999) and the "Utah" array (Maynard et al 1999;Nordhausen et al 1996;Suner et al 2005) and the "Michigan" probe (Hoogerwerf and Wise 1994;Vetter et al 2004) that both use narrowly spaced silicon microelectrodes. All these techniques allow gathering data from many individual neurons simultaneously and have been reported to provide single-unit responses still several months following implantation, occasionally even after 1 or several years (Krüger et al 2010;Nicolelis et al 2003;Suner et al 2005). Because all these techniques use stationary electrodes, a main advantage is that they allow for recording essentially the same cluster of neurons or even the same individual units (Dickey et al 2009) on a day-by-day basis.…”

mentioning

confidence: 99%

A new type of recording chamber with an easy-to-exchange microdrive array for chronic recordings in macaque monkeys

Galashan

Rempel

Meyer

et al. 2011

Journal of Neurophysiology

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Seven years of recording from monkey cortex with a chronically implanted multiple microelectrode

Cited by 55 publications

References 22 publications

Augmenting intracortical brain-machine interface with neurally driven error detectors

Augmenting intracortical brain-machine interface with neurally driven error detectors

Face-selective neurons maintain consistent visual responses across months

A new type of recording chamber with an easy-to-exchange microdrive array for chronic recordings in macaque monkeys

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