Subject-specific modulation of local field potential spectral power during brain–machine interface control in primates

So, Kelvin; Dangi, Siddharth; Orsborn, Amy L.; Gastpar, Michael; Carmena, Jose M.

doi:10.1088/1741-2560/11/2/026002

Cited by 68 publications

(78 citation statements)

References 36 publications

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“…We based our variant of the So and colleagues study's task on an earlier report [45] and therefore used a 300 ms hold time and 8 second time limit. We note that in [34] the hold time was actually 400 ms and the time limit was 10 seconds.…”

Section: Methodsmentioning

confidence: 99%

A high performing brain–machine interface driven by low-frequency local field potentials alone and together with spikes

et al. 2015

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Objective Brain-machine interfaces (BMIs) seek to enable people with movement disabilities to directly control prosthetic systems with their neural activity. Current high performance BMIs are driven by action potentials (spikes), but access to this signal often diminishes as sensors degrade over time. Decoding local field potentials (LFPs) as an alternative or complementary BMI control signal may improve performance when there is a paucity of spike signals. To date only a small handful of LFP decoding methods have been tested online; there remains a need to test different LFP decoding approaches and improve LFP-driven performance. There has also not been a reported demonstration of a hybrid BMI that decodes kinematics from both LFP and spikes. Here we first evaluate a BMI driven by the local motor potential (LMP), a low-pass filtered time-domain LFP amplitude feature. We then combine decoding of both LMP and spikes to implement a hybrid BMI. Approach Spikes and LFP were recorded from two macaques implanted with multielectrode arrays in primary and premotor cortex while they performed a reaching task. We then evaluated closed-loop BMI control using biomimetic decoders driven by LMP, spikes, or both signals together. Main Results LMP decoding enabled quick and accurate cursor control which surpassed previously reported LFP BMI performance. Hybrid decoding of both spikes and LMP improved performance when spikes signal quality was mediocre to poor. Significance These findings show that LMP is an effective BMI control signal which requires minimal power to extract and can substitute for or augment impoverished spikes signals. Use of this signal may lengthen the useful lifespan of BMIs and is therefore an important step towards clinically viable BMIs.

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Section: Methodsmentioning

confidence: 99%

A high performing brain–machine interface driven by low-frequency local field potentials alone and together with spikes

et al. 2015

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“…Of the 11 neural measures compared, magnitude of the LFP in the relatively broad 80–500 Hz band (which we refer to as high-frequency LFP ) provided the richest information of saccade direction intention across a range of decoders. The high-frequency LFP used herein differs from those found to be the most informative in other LFP-based decoding studies, which have reported a wide variety of frequency ranges including sub-ranges of 0–150 Hz [24], combinations of sub-ranges below 190 Hz [22], 25–90 Hz [27], 50–300 Hz [18], 70–200 Hz [44], 76–150 Hz [45], and 200–400 Hz [31]. Together with the current results, these findings suggest that the optimal neural activity measure for BCI purposes depends on the exact recording configuration used and brain areas implanted.…”

Section: Discussionmentioning

confidence: 99%

“…Previous studies have used a number of different neural activity measures for BCI purposes, including multiunit/single-unit firing rates, local field potentials (LFPs) in different frequency bands, or hybrid signals [2,18,20–24], with differing conclusions about which is the most effective for decoding. Here we systematically test a variety of neural activity measures to assess their suitability for decoding intended saccadic eye movement directions.…”

Section: Introductionmentioning

confidence: 99%

Decoding of intended saccade direction in an oculomotor brain–computer interface

et al. 2017

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To date, invasive brain-computer interface (BCI) research has largely focused on replacing lost limb functions using signals from of hand/arm areas of motor cortex. However, the oculomotor system may be better suited to BCI applications involving rapid serial selection from spatial targets, such as choosing from a set of possible words displayed on a computer screen in an augmentative and alternative communication (AAC) application. Here we describe a chronic intracortical BCI in monkeys to decode intended saccadic eye movement direction. Using activity from multiple frontal cortical areas, we could decode intended saccade direction in real time with high accuracy, particularly at contralateral locations. Accurate decoding was evident even at the beginning of the BCI session; no extensive BCI experience was necessary. High-frequency (80–500 Hz) local field potential magnitude provided the best performance, even over spiking activity, thus simplifying future BCI applications. Most of the information came from the frontal and supplementary eye fields, with relatively little contribution from dorsolateral prefrontal cortex. Our results support the feasibility of high-accuracy intracortical oculomotor BCIs that require little or no practice to operate and may be ideally suited for “point and click” computer operation as used in most current AAC systems.

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“…For patient 1, the multi-taper method was used to estimate the baseline spectrum as well as beta power online [6], [7]. In patient 2, however, stimulation was on and due to the low sampling rate, the contaminated signal from the stimulation artifact, and the processor clock artifact (at multiple frequencies, see [35]), the smoothing from the multi-taper method spread artifacts to other frequency band estimates, yielding a noisy estimate of the spectrum.…”

Section: Methodsmentioning

confidence: 99%

Neurofeedback Control in Parkinsonian Patients Using Electrocorticography Signals Accessed Wirelessly With a Chronic, Fully Implanted Device

Khanna

Swann

Hemptinne

et al. 2017

IEEE Trans. Neural Syst. Rehabil. Eng.

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Parkinson’s disease (PD) is characterized by motor symptoms such as rigidity and bradykinesia that prevent normal movement. Beta band oscillations (13–30 Hz) in neural local field potentials (LFPs) have been associated with these motor symptoms. Here, three PD patients implanted with a therapeutic deep brain neural stimulator that can also record and wirelessly stream neural data played a neurofeedback game where they modulated their beta band power from sensorimotor cortical areas. Patients’ beta band power was streamed in real-time to update the position of a cursor that they tried to drive into a cued target. After playing the game for 1–2 hours each, all three patients exhibited above chance-level performance regardless of subcortical stimulation levels. This study, for the first time, demonstrates using an invasive neural recording system for at-home neurofeedback training. Future work will investigate chronic neurofeedback training as a potentially therapeutic tool for patients with neurological disorders.

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Subject-specific modulation of local field potential spectral power during brain–machine interface control in primates

Abstract: Overall, our results demonstrate proficient, continuous BMI control using LFPs and provide insight into the subject-specific spectral patterns of LFP activity modulated during control.

Cited by 68 publications

References 36 publications

A high performing brain–machine interface driven by low-frequency local field potentials alone and together with spikes

A high performing brain–machine interface driven by low-frequency local field potentials alone and together with spikes

Decoding of intended saccade direction in an oculomotor brain–computer interface

Neurofeedback Control in Parkinsonian Patients Using Electrocorticography Signals Accessed Wirelessly With a Chronic, Fully Implanted Device

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