Literature DB >> 32006952

Utility and lower limits of frequency detection in surface electrode stimulation for somatosensory brain-computer interface in humans.

Daniel R Kramer1,2, Krista Lamorie-Foote3, Michael Barbaro3, Morgan B Lee3, Terrance Peng3, Angad Gogia3, George Nune4, Charles Y Liu1,2, Spencer S Kellis2,5,6, Brian Lee1,2.   

Abstract

OBJECTIVE: Stimulation of the primary somatosensory cortex (S1) has been successful in evoking artificial somatosensation in both humans and animals, but much is unknown about the optimal stimulation parameters needed to generate robust percepts of somatosensation. In this study, the authors investigated frequency as an adjustable stimulation parameter for artificial somatosensation in a closed-loop brain-computer interface (BCI) system.
METHODS: Three epilepsy patients with subdural mini-electrocorticography grids over the hand area of S1 were asked to compare the percepts elicited with different stimulation frequencies. Amplitude, pulse width, and duration were held constant across all trials. In each trial, subjects experienced 2 stimuli and reported which they thought was given at a higher stimulation frequency. Two paradigms were used: first, 50 versus 100 Hz to establish the utility of comparing frequencies, and then 2, 5, 10, 20, 50, or 100 Hz were pseudorandomly compared.
RESULTS: As the magnitude of the stimulation frequency was increased, subjects described percepts that were "more intense" or "faster." Cumulatively, the participants achieved 98.0% accuracy when comparing stimulation at 50 and 100 Hz. In the second paradigm, the corresponding overall accuracy was 73.3%. If both tested frequencies were less than or equal to 10 Hz, accuracy was 41.7% and increased to 79.4% when one frequency was greater than 10 Hz (p = 0.01). When both stimulation frequencies were 20 Hz or less, accuracy was 40.7% compared with 91.7% when one frequency was greater than 20 Hz (p < 0.001). Accuracy was 85% in trials in which 50 Hz was the higher stimulation frequency. Therefore, the lower limit of detection occurred at 20 Hz, and accuracy decreased significantly when lower frequencies were tested. In trials testing 10 Hz versus 20 Hz, accuracy was 16.7% compared with 85.7% in trials testing 20 Hz versus 50 Hz (p < 0.05). Accuracy was greater than chance at frequency differences greater than or equal to 30 Hz.
CONCLUSIONS: Frequencies greater than 20 Hz may be used as an adjustable parameter to elicit distinguishable percepts. These findings may be useful in informing the settings and the degrees of freedom achievable in future BCI systems.

Entities:  

Keywords:  BCI; BCI = brain-computer interface; ECoG; ECoG = electrocorticography; EMU = epilepsy monitoring unit; NHP = nonhuman primate; S1 = primary somatosensory cortex; brain-computer interface; cortical stimulation; electrocorticography; frequency; sensory feedback control; somatosensation

Year:  2020        PMID: 32006952      PMCID: PMC7242113          DOI: 10.3171/2019.11.FOCUS19696

Source DB:  PubMed          Journal:  Neurosurg Focus        ISSN: 1092-0684            Impact factor:   4.047


  29 in total

1.  Restoring the sense of touch with a prosthetic hand through a brain interface.

Authors:  Gregg A Tabot; John F Dammann; Joshua A Berg; Francesco V Tenore; Jessica L Boback; R Jacob Vogelstein; Sliman J Bensmaia
Journal:  Proc Natl Acad Sci U S A       Date:  2013-10-14       Impact factor: 11.205

2.  Control of limb dynamics in normal subjects and patients without proprioception.

Authors:  R L Sainburg; M F Ghilardi; H Poizner; C Ghez
Journal:  J Neurophysiol       Date:  1995-02       Impact factor: 2.714

3.  Electrocorticographic changes in field potentials following natural somatosensory percepts in humans.

Authors:  Daniel R Kramer; Michael F Barbaro; Morgan Lee; Terrance Peng; George Nune; Charles Y Liu; Spencer Kellis; Brian Lee
Journal:  Exp Brain Res       Date:  2019-02-22       Impact factor: 1.972

4.  Intraoperative electrical stimulation mapping as an aid for surgery of intracranial lesions involving motor areas in children.

Authors:  Francesco Signorelli; J Guyotat; C Mottolese; F Schneider; G D'Acunzi; J Isnard
Journal:  Childs Nerv Syst       Date:  2004-05-07       Impact factor: 1.475

5.  A cognitive neuroprosthetic that uses cortical stimulation for somatosensory feedback.

Authors:  Christian Klaes; Ying Shi; Spencer Kellis; Juri Minxha; Boris Revechkis; Richard A Andersen
Journal:  J Neural Eng       Date:  2014-09-22       Impact factor: 5.379

6.  Direct electrical stimulation of the somatosensory cortex in humans using electrocorticography electrodes: a qualitative and quantitative report.

Authors:  L A Johnson; J D Wander; D Sarma; D K Su; E E Fetz; J G Ojemann
Journal:  J Neural Eng       Date:  2013-05-13       Impact factor: 5.379

7.  A learning-based approach to artificial sensory feedback leads to optimal integration.

Authors:  Maria C Dadarlat; Joseph E O'Doherty; Philip N Sabes
Journal:  Nat Neurosci       Date:  2014-11-24       Impact factor: 24.884

8.  Engineering Artificial Somatosensation Through Cortical Stimulation in Humans.

Authors:  Brian Lee; Daniel Kramer; Michelle Armenta Salas; Spencer Kellis; David Brown; Tatyana Dobreva; Christian Klaes; Christi Heck; Charles Liu; Richard A Andersen
Journal:  Front Syst Neurosci       Date:  2018-06-04

9.  Semi-automated Anatomical Labeling and Inter-subject Warping of High-Density Intracranial Recording Electrodes in Electrocorticography.

Authors:  Liberty S Hamilton; David L Chang; Morgan B Lee; Edward F Chang
Journal:  Front Neuroinform       Date:  2017-10-31       Impact factor: 4.081

Review 10.  Restoring sensorimotor function through intracortical interfaces: progress and looming challenges.

Authors:  Sliman J Bensmaia; Lee E Miller
Journal:  Nat Rev Neurosci       Date:  2014-05       Impact factor: 34.870

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