Literature DB >> 23724837

Stereoelectroencephalography for continuous two-dimensional cursor control in a brain-machine interface.

Sumeet Vadera1, Amar R Marathe, Jorge Gonzalez-Martinez, Dawn M Taylor.   

Abstract

Stereoelectroencephalography (SEEG) is becoming more prevalent as a planning tool for surgical treatment of intractable epilepsy. Stereoelectroencephalography uses long, thin, cylindrical "depth" electrodes containing multiple recording contacts along each electrode's length. Each lead is inserted into the brain percutaneously. The advantage of SEEG is that the electrodes can easily target deeper brain structures that are inaccessible with subdural grid electrodes, and SEEG does not require a craniotomy. Brain-machine interface (BMI) research is also becoming more common in the Epilepsy Monitoring Unit. A brain-machine interface decodes a person's desired movement or action from the recorded brain activity and then uses the decoded brain activity to control an assistive device in real time. Although BMIs are primarily being developed for use by severely paralyzed individuals, epilepsy patients undergoing invasive brain monitoring provide an opportunity to test the effectiveness of different invasive recording electrodes for use in BMI systems. This study investigated the ability to use SEEG electrodes for control of 2D cursor velocity in a BMI. Two patients who were undergoing SEEG for intractable epilepsy participated in this study. Participants were instructed to wiggle or rest the hand contralateral to their SEEG electrodes to control the horizontal velocity of a cursor on a screen. Simultaneously they were instructed to wiggle or rest their feet to control the vertical component of cursor velocity. The BMI system was designed to detect power spectral changes associated with hand and foot activity and translate those spectral changes into horizontal and vertical cursor movements in real time. During testing, participants used their decoded SEEG signals to move the brain-controlled cursor to radial targets that appeared on the screen. Although power spectral information from 28 to 32 electrode contacts were used for cursor control during the experiment, post hoc analysis indicated that better control may have been possible using only a single SEEG depth electrode containing multiple recording contacts in both hand and foot cortical areas. These results suggest that the advantages of using SEEG for epilepsy monitoring may also apply to using SEEG electrodes in BMI systems. Specifically, SEEG electrodes can target deeper brain structures, such as foot motor cortex, and both hand and foot areas can be targeted with a single SEEG electrode implanted percutaneously. Therefore, SEEG electrodes may be an attractive option for simple BMI systems that use power spectral modulation in hand and foot cortex for independent control of 2 degrees of freedom.

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Year:  2013        PMID: 23724837     DOI: 10.3171/2013.3.FOCUS1373

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


  4 in total

1.  Demonstration of a semi-autonomous hybrid brain-machine interface using human intracranial EEG, eye tracking, and computer vision to control a robotic upper limb prosthetic.

Authors:  David P McMullen; Guy Hotson; Kapil D Katyal; Brock A Wester; Matthew S Fifer; Timothy G McGee; Andrew Harris; Matthew S Johannes; R Jacob Vogelstein; Alan D Ravitz; William S Anderson; Nitish V Thakor; Nathan E Crone
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2013-12-12       Impact factor: 3.802

Review 2.  The science and engineering behind sensitized brain-controlled bionic hands.

Authors:  Chethan Pandarinath; Sliman J Bensmaia
Journal:  Physiol Rev       Date:  2021-09-20       Impact factor: 37.312

3.  Defining Surgical Terminology and Risk for Brain Computer Interface Technologies.

Authors:  Eric C Leuthardt; Daniel W Moran; Tim R Mullen
Journal:  Front Neurosci       Date:  2021-03-26       Impact factor: 4.677

4.  Spontaneous State Detection Using Time-Frequency and Time-Domain Features Extracted From Stereo-Electroencephalography Traces.

Authors:  Huanpeng Ye; Zhen Fan; Guangye Li; Zehan Wu; Jie Hu; Xinjun Sheng; Liang Chen; Xiangyang Zhu
Journal:  Front Neurosci       Date:  2022-03-17       Impact factor: 4.677

  4 in total

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