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Richer N, Bradford JC, Ferris DP. Mobile neuroimaging: What we have learned about the neural control of human walking, with an emphasis on EEG-based research. Neurosci Biobehav Rev 2024; 162:105718. [PMID: 38744350 DOI: 10.1016/j.neubiorev.2024.105718] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2023] [Revised: 04/18/2024] [Accepted: 05/08/2024] [Indexed: 05/16/2024]
Abstract
Our understanding of the neural control of human walking has changed significantly over the last twenty years and mobile brain imaging methods have contributed substantially to current knowledge. High-density electroencephalography (EEG) has the advantages of being lightweight and mobile while providing temporal resolution of brain changes within a gait cycle. Advances in EEG hardware and processing methods have led to a proliferation of research on the neural control of locomotion in neurologically intact adults. We provide a narrative review of the advantages and disadvantages of different mobile brain imaging methods, then summarize findings from mobile EEG studies quantifying electrocortical activity during human walking. Contrary to historical views on the neural control of locomotion, recent studies highlight the widespread involvement of many areas, such as the anterior cingulate, posterior parietal, prefrontal, premotor, sensorimotor, supplementary motor, and occipital cortices, that show active fluctuations in electrical power during walking. The electrocortical activity changes with speed, stability, perturbations, and gait adaptation. We end with a discussion on the next steps in mobile EEG research.
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Affiliation(s)
- Natalie Richer
- Department of Kinesiology and Applied Health, University of Winnipeg, Winnipeg, Manitoba, Canada.
| | - J Cortney Bradford
- US Army Combat Capabilities Development Command US Army Research Laboratory, Adelphi, MD, USA
| | - Daniel P Ferris
- J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, FL, USA
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2
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Gibson E, Douglas G, Jeffries K, Delaurier J, Chestnut T, Charlton JM. Foot orientation and trajectory variability in locomotion: Effects of real-world terrain. PLoS One 2024; 19:e0293691. [PMID: 38753603 PMCID: PMC11098422 DOI: 10.1371/journal.pone.0293691] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Accepted: 03/20/2024] [Indexed: 05/18/2024] Open
Abstract
Capturing human locomotion in nearly any environment or context is becoming increasingly feasible with wearable sensors, giving access to commonly encountered walking conditions. While important in expanding our understanding of locomotor biomechanics, these more variable environments present challenges to identify changes in data due to person-level factors among the varying environment-level factors. Our study examined foot-specific biomechanics while walking on terrain commonly encountered with the goal of understanding the extent to which these variables change due to terrain. We recruited healthy adults to walk at self-selected speeds on stairs, flat ground, and both shallow and steep sloped terrain. A pair of inertial measurement units were embedded in both shoes to capture foot biomechanics while walking. Foot orientation was calculated using a strapdown procedure and foot trajectory was determined by double integrating the linear acceleration. Stance time, swing time, cadence, sagittal and frontal orientations, stride length and width were extracted as discrete variables. These data were compared within-participant and across terrain conditions. The physical constraints of the stairs resulted in shorter stride lengths, less time spent in swing, toe-first foot contact, and higher variability during stair ascent specifically (p<0.05). Stride lengths increased when ascending compared to descending slopes, and the sagittal foot angle at initial contact was greatest in the steep slope descent condition (p<0.05). No differences were found between conditions for horizontal foot angle in midstance (p≥0.067). Our results show that walking on slopes creates differential changes in foot biomechanics depending on whether one is descending or ascending, and stairs require different biomechanics and gait timing than slopes or flat ground. This may be an important factor to consider when making comparisons of real-world walking bouts, as greater proportions of one terrain feature in a data set could create bias in the outcomes. Classifying terrain in unsupervised walking datasets would be helpful to avoid comparing metrics from different walking terrain scenarios.
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Affiliation(s)
- Emma Gibson
- Department of Physical Therapy, University of British Columbia, Vancouver, BC, Canada
| | - Greg Douglas
- Department of Physical Therapy, University of British Columbia, Vancouver, BC, Canada
| | - Katelyn Jeffries
- Department of Physical Therapy, University of British Columbia, Vancouver, BC, Canada
| | - Julianne Delaurier
- Department of Physical Therapy, University of British Columbia, Vancouver, BC, Canada
| | - Taylor Chestnut
- Department of Physical Therapy, University of British Columbia, Vancouver, BC, Canada
| | - Jesse M. Charlton
- School of Kinesiology, University of British Columbia, Vancouver, BC, Canada
- School of Biomedical Engineering, University of British Columbia, Vancouver, BC, Canada
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3
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Guo X, Zhao S, Yu L, Wang H, Acquah MEE, Chen W, Gu D. Neural Correlates of Abnormal Cortical Gait Control in Parkinson's Disease: A Whole-Gait-Cycle EEG Study. IEEE Trans Biomed Eng 2024; 71:400-409. [PMID: 37535480 DOI: 10.1109/tbme.2023.3301528] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/05/2023]
Abstract
OBJECTIVE Electroencephalography (EEG) with high time-resolution allows for recording dynamic cortical activity during walking and provides new insight into the underlying pathophysiology of gait impairments in PD. However, traditional gait-phase-specific EEG analysis only measures the brain activities in the isolated gait phase, but neglects the between-gait-phase interactions as well as the whole-gait-cycle characteristics, and therefore is unable to effectively reflect the abnormal cortical gait control. METHODS In this study, we introduced three whole-gait-cycle measures of intra-stride EEG activity (i.e., mean desynchronization, amplitude of fluctuations, and coupling to the gait phase), and investigated their abnormalities in PD and relationships with gait impairments, which were further compared with the traditional gait-phase-specific measures. RESULTS Compared with healthy controls, PD patients showed overwhelming stronger desynchronizations (ERD) across the whole gait cycle in θ, α and low-β bands, implying a cortical compensatory strategy in response to the low efficiency of the motor network. Patients also exhibited weaker intra-stride ERD fluctuations in the central area in α and low-β bands, with reduced amplitude and less coupling to the gait phase, which were correlated with gait impairments in walking speed, gait rhythm and walking stability. However, gait-phase-specific EEG measures did not show any significant correlation with gait impairments in PD. CONCLUSION Our results demonstrated the efficiency of whole-gait-cycle EEG measures in characterizing the abnormal cortical gait control, and for the first time, associated gait impairments with weak intra-stride electrocortical fluctuations. SIGNIFICANCE The findings may shed light on the development of cortical-targeted interventions for PD.
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Reakkamnuan C, Kumarnsit E, Cheaha D. Local field potential (LFP) power and phase-amplitude coupling (PAC) changes in the striatum and motor cortex reflect neural mechanisms associated with bradykinesia and rigidity during D2R suppression in an animal model. Prog Neuropsychopharmacol Biol Psychiatry 2023; 127:110838. [PMID: 37557945 DOI: 10.1016/j.pnpbp.2023.110838] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Revised: 07/30/2023] [Accepted: 08/04/2023] [Indexed: 08/11/2023]
Abstract
Impairments in motor control are the primary feature of Parkinson's disease, which is caused by dopaminergic imbalance in the basal ganglia. Identification of neural biomarkers of dopamine D2 receptor (D2R) suppression would be useful for monitoring the progress of neuropathologies and effects of treatment. Male Swiss albino ICR mice were deeply anesthetized, and electrodes were implanted in the striatum and motor cortex to record local field potential (LFP). Haloperidol (HAL), a D2R antagonist, was administered to induce decreased D2R activity. Following HAL treatment, the mice showed significantly decreased movement velocity in open field test, increased latency to descend in a bar test, and decreased latency to fall in a rotarod test. LFP signals during HAL-induced immobility (open field test) and catalepsy (bar test) were analyzed. Striatal low-gamma (30.3-44.9 Hz) power decreased during immobility periods, but during catalepsy, delta power (1-4 Hz) increased, beta1(13.6-18 Hz) and low-gamma powers decreased, and high-gamma (60.5-95.7 Hz) power increased. Striatal delta-high-gamma phase-amplitude coupling (PAC) was significantly increased during catalepsy but not immobility. In the motor cortex, during HAL-induced immobility, beta1 power significantly increased and low-gamma power decreased, but during HAL-induced catalepsy, low-gamma and beta1 powers decreased and high-gamma power increased. Delta-high-gamma PAC in the motor cortex significantly increased during catalepsy but not during immobility. Altogether, the present study demonstrated changes in delta, beta1 and gamma powers and delta-high-gamma PAC in the striatum and motor cortex in association with D2R suppression. In particular, delta power in the striatum and delta-high-gamma PAC in the striatum and motor cortex appear to represent biomarkers of neural mechanisms associated with bradykinesia and rigidity.
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Affiliation(s)
- Chayaporn Reakkamnuan
- Physiology program, Division of Health and Applied Sciences, Faculty of Science, Prince of Songkla University (PSU), Hat Yai, Songkhla 90110, Thailand; Biosignal Research Center for Health, Faculty of Science, Prince of Songkla University, Hatyai, Songkhla 90110, Thailand
| | - Ekkasit Kumarnsit
- Physiology program, Division of Health and Applied Sciences, Faculty of Science, Prince of Songkla University (PSU), Hat Yai, Songkhla 90110, Thailand; Biosignal Research Center for Health, Faculty of Science, Prince of Songkla University, Hatyai, Songkhla 90110, Thailand
| | - Dania Cheaha
- Biology program, Division of Biological Sciences, Faculty of Science, Prince of Songkla University (PSU), Hat Yai, Songkhla 90110, Thailand; Biosignal Research Center for Health, Faculty of Science, Prince of Songkla University, Hatyai, Songkhla 90110, Thailand.
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Starkweather CK, Morrison MA, Yaroshinsky M, Louie K, Balakid J, Presbrey K, Starr PA, Wang DD. Human upper extremity motor cortex activity shows distinct oscillatory signatures for stereotyped arm and leg movements. Front Hum Neurosci 2023; 17:1212963. [PMID: 37635808 PMCID: PMC10449648 DOI: 10.3389/fnhum.2023.1212963] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Accepted: 07/25/2023] [Indexed: 08/29/2023] Open
Abstract
Introduction Stepping and arm swing are stereotyped movements that require coordination across multiple muscle groups. It is not known whether the encoding of these stereotyped movements in the human primary motor cortex is confined to the limbs' respective somatotopy. Methods We recorded subdural electrocorticography activities from the hand/arm area in the primary motor cortex of 6 subjects undergoing deep brain stimulation surgery for essential tremor and Parkinson's disease who performed stepping (all patients) and arm swing (n = 3 patients) tasks. Results We show stepping-related low frequency oscillations over the arm area. Furthermore, we show that this oscillatory activity is separable, both in frequency and spatial domains, from gamma band activity changes that occur during arm swing. Discussion Our study contributes to the growing body of evidence that lower extremity movement may be more broadly represented in the motor cortex, and suggest that it may represent a way to coordinate stereotyped movements across the upper and lower extremities.
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Affiliation(s)
- Clara Kwon Starkweather
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, United States
| | - Melanie A. Morrison
- Department of Radiology, University of California, San Francisco, San Francisco, CA, United States
| | - Maria Yaroshinsky
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, United States
| | - Kenneth Louie
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, United States
| | - Jannine Balakid
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, United States
| | - Kara Presbrey
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, United States
| | - Philip A. Starr
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, United States
| | - Doris D. Wang
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, United States
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Liu C, Downey RJ, Salminen JS, Rojas SA, Richer N, Pliner EM, Hwang J, Cruz-Almeida Y, Manini TM, Hass CJ, Seidler RD, Clark DJ, Ferris DP. Electrical Brain Activity during Human Walking with Parametric Variations in Terrain Unevenness and Walking Speed. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.31.551289. [PMID: 37577540 PMCID: PMC10418077 DOI: 10.1101/2023.07.31.551289] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/15/2023]
Abstract
Mobile brain imaging with high-density electroencephalography (EEG) can provide insight into the cortical processes involved in complex human walking tasks. While uneven terrain is common in the natural environment and poses challenges to human balance control, there is limited understanding of the supraspinal processes involved with traversing uneven terrain. The primary objective of this study was to quantify electrocortical activity related to parametric variations in terrain unevenness for neurotypical young adults. We used high-density EEG to measure brain activity when thirty-two young adults walked on a novel custom-made uneven terrain treadmill surface with four levels of difficulty at a walking speed tailored to each participant. We identified multiple brain regions associated with uneven terrain walking. Alpha (8 - 13 Hz) and beta (13 - 30 Hz) spectral power decreased in the sensorimotor and posterior parietal areas with increasing terrain unevenness while theta (4 - 8 Hz) power increased in the mid/posterior cingulate area with terrain unevenness. We also found that within stride spectral power fluctuations increased with terrain unevenness. Our secondary goal was to investigate the effect of parametric changes in walking speed (0.25 m/s, 0.5m/s, 0.75 m/s, 1.0 m/s) to differentiate the effects of walking speed from uneven terrain. Our results revealed that electrocortical activities only changed substantially with speed within the sensorimotor area but not in other brain areas. Together, these results indicate there are distinct cortical processes contributing to the control of walking over uneven terrain versus modulation of walking speed on smooth, flat terrain. Our findings increase our understanding of cortical involvement in an ecologically valid walking task and could serve as a benchmark for identifying deficits in cortical dynamics that occur in people with mobility deficits.
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Affiliation(s)
- Chang Liu
- Department of Biomedical Engineering, University of Florida, Gainesville, FL, USA
- McKnight Brain Institute, University of Florida, Gainesville, FL
| | - Ryan J. Downey
- Department of Biomedical Engineering, University of Florida, Gainesville, FL, USA
| | - Jacob S. Salminen
- Department of Biomedical Engineering, University of Florida, Gainesville, FL, USA
| | - Sofia Arvelo Rojas
- Department of Biomedical Engineering, University of Florida, Gainesville, FL, USA
| | - Natalie Richer
- Department of Biomedical Engineering, University of Florida, Gainesville, FL, USA
| | - Erika M. Pliner
- Department of Biomedical Engineering, University of Florida, Gainesville, FL, USA
| | - Jungyun Hwang
- Department of Neurology, University of Florida, Gainesville, FL, USA
| | - Yenisel Cruz-Almeida
- Department of Community Dentistry and Behavioral Science, University of Florida, Gainesville, FL, USA
- Pain Research and Intervention Center of Excellence (PRICE), University of Florida, Gainesville, FL, USA
- Department of Epidemiology, University of Florida, Gainesville, FL, USA
| | - Todd M. Manini
- Department of Health Outcomes and Biomedical Informatics, University of Florida, Gainesville, FL, USA
| | - Chris J. Hass
- Department of Applied Physiology and Kinesiology, University of Florida, Gainesville, FL, USA
| | - Rachael D. Seidler
- Department of Applied Physiology and Kinesiology, University of Florida, Gainesville, FL, USA
- Norman Fixel Institute for Neurological Diseases, University of Florida, Gainesville, FL, USA
- McKnight Brain Institute, University of Florida, Gainesville, FL
| | - David J. Clark
- Department of Neurology, University of Florida, Gainesville, FL, USA
- Brain Rehabilitation Research Center, Malcom Randall VA Medical Center, Gainesville, FL, USA
| | - Daniel P. Ferris
- Department of Biomedical Engineering, University of Florida, Gainesville, FL, USA
- McKnight Brain Institute, University of Florida, Gainesville, FL
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7
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Stangl M, Maoz SL, Suthana N. Mobile cognition: imaging the human brain in the 'real world'. Nat Rev Neurosci 2023; 24:347-362. [PMID: 37046077 PMCID: PMC10642288 DOI: 10.1038/s41583-023-00692-y] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/03/2023] [Indexed: 04/14/2023]
Abstract
Cognitive neuroscience studies in humans have enabled decades of impactful discoveries but have primarily been limited to recording the brain activity of immobile participants in a laboratory setting. In recent years, advances in neuroimaging technologies have enabled recordings of human brain activity to be obtained during freely moving behaviours in the real world. Here, we propose that these mobile neuroimaging methods can provide unique insights into the neural mechanisms of human cognition and contribute to the development of novel treatments for neurological and psychiatric disorders. We further discuss the challenges associated with studying naturalistic human behaviours in complex real-world settings as well as strategies for overcoming them. We conclude that mobile neuroimaging methods have the potential to bring about a new era of cognitive neuroscience in which neural mechanisms can be studied with increased ecological validity and with the ability to address questions about natural behaviour and cognitive processes in humans engaged in dynamic real-world experiences.
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Affiliation(s)
- Matthias Stangl
- Department of Psychiatry and Biobehavioral Sciences, Jane and Terry Semel Institute for Neuroscience and Human Behaviour, University of California, Los Angeles, Los Angeles, CA, USA.
| | - Sabrina L Maoz
- Department of Bioengineering, University of California, Los Angeles, Los Angeles, CA, USA
| | - Nanthia Suthana
- Department of Psychiatry and Biobehavioral Sciences, Jane and Terry Semel Institute for Neuroscience and Human Behaviour, University of California, Los Angeles, Los Angeles, CA, USA.
- Department of Bioengineering, University of California, Los Angeles, Los Angeles, CA, USA.
- Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
- Department of Psychology, University of California, Los Angeles, Los Angeles, CA, USA.
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Lorach H, Galvez A, Spagnolo V, Martel F, Karakas S, Intering N, Vat M, Faivre O, Harte C, Komi S, Ravier J, Collin T, Coquoz L, Sakr I, Baaklini E, Hernandez-Charpak SD, Dumont G, Buschman R, Buse N, Denison T, van Nes I, Asboth L, Watrin A, Struber L, Sauter-Starace F, Langar L, Auboiroux V, Carda S, Chabardes S, Aksenova T, Demesmaeker R, Charvet G, Bloch J, Courtine G. Walking naturally after spinal cord injury using a brain-spine interface. Nature 2023:10.1038/s41586-023-06094-5. [PMID: 37225984 DOI: 10.1038/s41586-023-06094-5] [Citation(s) in RCA: 70] [Impact Index Per Article: 70.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Accepted: 04/17/2023] [Indexed: 05/26/2023]
Abstract
A spinal cord injury interrupts the communication between the brain and the region of the spinal cord that produces walking, leading to paralysis1,2. Here, we restored this communication with a digital bridge between the brain and spinal cord that enabled an individual with chronic tetraplegia to stand and walk naturally in community settings. This brain-spine interface (BSI) consists of fully implanted recording and stimulation systems that establish a direct link between cortical signals3 and the analogue modulation of epidural electrical stimulation targeting the spinal cord regions involved in the production of walking4-6. A highly reliable BSI is calibrated within a few minutes. This reliability has remained stable over one year, including during independent use at home. The participant reports that the BSI enables natural control over the movements of his legs to stand, walk, climb stairs and even traverse complex terrains. Moreover, neurorehabilitation supported by the BSI improved neurological recovery. The participant regained the ability to walk with crutches overground even when the BSI was switched off. This digital bridge establishes a framework to restore natural control of movement after paralysis.
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Affiliation(s)
- Henri Lorach
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neuroscience, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
| | - Andrea Galvez
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neuroscience, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
| | - Valeria Spagnolo
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neuroscience, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
| | - Felix Martel
- Univ. Grenoble Alpes, CEA, LETI, Clinatec, Grenoble, France
| | - Serpil Karakas
- Univ. Grenoble Alpes, CEA, LETI, Clinatec, Grenoble, France
| | - Nadine Intering
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neuroscience, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
| | - Molywan Vat
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neuroscience, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
| | - Olivier Faivre
- Univ. Grenoble Alpes, CEA, LETI, Clinatec, Grenoble, France
| | - Cathal Harte
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neuroscience, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
| | - Salif Komi
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neuroscience, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
| | - Jimmy Ravier
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neuroscience, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
| | - Thibault Collin
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neuroscience, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
| | - Laure Coquoz
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neuroscience, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
| | - Icare Sakr
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neuroscience, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
| | - Edeny Baaklini
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neuroscience, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
| | - Sergio Daniel Hernandez-Charpak
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neuroscience, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
| | - Gregory Dumont
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neuroscience, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
| | | | | | - Tim Denison
- Medtronic, Minneapolis, MN, USA
- Department of Engineering Science, University of Oxford, Oxford, UK
| | - Ilse van Nes
- Department of Rehabilitation, Sint Maartenskliniek, Nijmegen, the Netherlands
| | - Leonie Asboth
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neuroscience, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
| | | | - Lucas Struber
- Univ. Grenoble Alpes, CEA, LETI, Clinatec, Grenoble, France
| | | | - Lilia Langar
- Univ. Grenoble Alpes, CHU Grenoble Alpes, Clinatec, Grenoble, France
| | | | - Stefano Carda
- Department of Clinical Neuroscience, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Stephan Chabardes
- Univ. Grenoble Alpes, CEA, LETI, Clinatec, Grenoble, France
- Univ. Grenoble Alpes, CHU Grenoble Alpes, Clinatec, Grenoble, France
| | | | - Robin Demesmaeker
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Department of Clinical Neuroscience, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland
| | | | - Jocelyne Bloch
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland.
- Department of Clinical Neuroscience, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland.
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland.
| | - Grégoire Courtine
- NeuroX Institute, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland.
- Department of Clinical Neuroscience, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland.
- NeuroRestore, Defitech Center for Interventional Neurotherapies, EPFL/CHUV/UNIL, Lausanne, Switzerland.
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9
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Laurence-Chasen JD, Ross CF, Arce-McShane FI, Hatsopoulos NG. Robust cortical encoding of 3D tongue shape during feeding in macaques. Nat Commun 2023; 14:2991. [PMID: 37225708 PMCID: PMC10209084 DOI: 10.1038/s41467-023-38586-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2022] [Accepted: 05/08/2023] [Indexed: 05/26/2023] Open
Abstract
Dexterous tongue deformation underlies eating, drinking, and speaking. The orofacial sensorimotor cortex has been implicated in the control of coordinated tongue kinematics, but little is known about how the brain encodes-and ultimately drives-the tongue's 3D, soft-body deformation. Here we combine a biplanar x-ray video technology, multi-electrode cortical recordings, and machine-learning-based decoding to explore the cortical representation of lingual deformation. We trained long short-term memory (LSTM) neural networks to decode various aspects of intraoral tongue deformation from cortical activity during feeding in male Rhesus monkeys. We show that both lingual movements and complex lingual shapes across a range of feeding behaviors could be decoded with high accuracy, and that the distribution of deformation-related information across cortical regions was consistent with previous studies of the arm and hand.
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Affiliation(s)
- Jeffrey D Laurence-Chasen
- Department of Organismal Biology and Anatomy, The University of Chicago, 1027 E 57th Street, Chicago, IL, 60637, USA.
| | - Callum F Ross
- Department of Organismal Biology and Anatomy, The University of Chicago, 1027 E 57th Street, Chicago, IL, 60637, USA
| | - Fritzie I Arce-McShane
- Department of Oral Health Sciences, School of Dentistry, University of Washington, 1959 NE Pacific Street, Box #357475, Seattle, WA, 98195-7475, USA
- Graduate Program in Neuroscience, University of Washington, 1959 NE Pacific St., Seattle, WA, 98195-7475, USA
| | - Nicholas G Hatsopoulos
- Department of Organismal Biology and Anatomy, The University of Chicago, 1027 E 57th Street, Chicago, IL, 60637, USA
- Program in Computational Neuroscience, The University of Chicago, 5812 South Ellis Avenue, Chicago, IL, 60637, USA
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10
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Ye X, Peng L, Sun N, He L, Yang X, Zhou Y, Xiong J, Shen Y, Sun R, Liang F. Hotspots and trends in fNIRS disease research: A bibliometric analysis. Front Neurosci 2023; 17:1097002. [PMID: 36937686 PMCID: PMC10017540 DOI: 10.3389/fnins.2023.1097002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2022] [Accepted: 02/17/2023] [Indexed: 03/06/2023] Open
Abstract
Objective To summarize the general information and hotspots of functional near-infrared spectroscopy (fNIRS)-based clinical disease research over the past 10 years and provide some references for future research. Methods The related literature published between 1 January 2011 and 31 January 2022 was retrieved from the Web of Science core database (WoS). Bibliometric visualization analysis of countries/regions, institutions, authors, journals, keywords and references were conducted by using CiteSpace 6.1.R3. Results A total of 467 articles were included, and the annual number of articles published over nearly a decade showed an upward trend year-by-year. These articles mainly come from 39 countries/regions and 280 institutions. The representative country and institution were the USA and the University of Tubingen. We identified 266 authors, among which Andreas J Fallgatter and Ann-Christine Ehlis were the influential authors. Neuroimage was the most co-cited journal. The major topics in fNIRS disease research included activation, prefrontal cortex, working memory, cortex, and functional magnetic resonance imaging (fMRI). In recent years, the Frontier topics were executive function, functional connectivity, performance, diagnosis, Alzheimer's disease, children, and adolescents. Based on the burst of co-cited references, gait research has received much attention. Conclusion This study conducted a comprehensive, objective, and visual analysis of publications, and revealed the status of relevant studies, hot topics, and trends concerning fNIRS disease research from 2011 to 2022. It is hoped that this work would help researchers to identify new perspectives on potential collaborators, important topics, and research Frontiers.
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Affiliation(s)
- Xiangyin Ye
- Acupuncture and Tuina School, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Li Peng
- Department of Ultrasound, The First People’s Hospital of Longquanyi District, Chengdu, China
| | - Ning Sun
- Rehabilitation Medicine Center and Institute of Rehabilitation Medicine, West China Hospital, Sichuan University, Chengdu, China
| | - Lian He
- Department of Ultrasound, The First People’s Hospital of Longquanyi District, Chengdu, China
| | - Xiuqiong Yang
- Department of Ultrasound, The First People’s Hospital of Longquanyi District, Chengdu, China
| | - Yuanfang Zhou
- Acupuncture and Tuina School, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Jian Xiong
- Acupuncture and Tuina School, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Yuquan Shen
- Department of Rehabilitation Medicine, The First People’s Hospital of Longquanyi District, Chengdu, China
| | - Ruirui Sun
- Acupuncture and Tuina School, Chengdu University of Traditional Chinese Medicine, Chengdu, China
- Ruirui Sun,
| | - Fanrong Liang
- Acupuncture and Tuina School, Chengdu University of Traditional Chinese Medicine, Chengdu, China
- *Correspondence: Fanrong Liang,
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11
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Silva AB, Liu JR, Zhao L, Levy DF, Scott TL, Chang EF. A Neurosurgical Functional Dissection of the Middle Precentral Gyrus during Speech Production. J Neurosci 2022; 42:8416-8426. [PMID: 36351829 PMCID: PMC9665919 DOI: 10.1523/jneurosci.1614-22.2022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2022] [Accepted: 08/30/2022] [Indexed: 11/17/2022] Open
Abstract
Classical models have traditionally focused on the left posterior inferior frontal gyrus (Broca's area) as a key region for motor planning of speech production. However, converging evidence suggests that it is not critical for either speech motor planning or execution. Alternative cortical areas supporting high-level speech motor planning have yet to be defined. In this review, we focus on the precentral gyrus, whose role in speech production is often thought to be limited to lower-level articulatory muscle control. In particular, we highlight neurosurgical investigations that have shed light on a cortical region anatomically located near the midpoint of the precentral gyrus, hence called the middle precentral gyrus (midPrCG). The midPrCG is functionally located between dorsal hand and ventral orofacial cortical representations and exhibits unique sensorimotor and multisensory functions relevant for speech processing. This includes motor control of the larynx, auditory processing, as well as a role in reading and writing. Furthermore, direct electrical stimulation of midPrCG can evoke complex movements, such as vocalization, and selective injury can cause deficits in verbal fluency, such as pure apraxia of speech. Based on these findings, we propose that midPrCG is essential to phonological-motoric aspects of speech production, especially syllabic-level speech sequencing, a role traditionally ascribed to Broca's area. The midPrCG is a cortical brain area that should be included in contemporary models of speech production with a unique role in speech motor planning and execution.
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Affiliation(s)
- Alexander B Silva
- Department of Neurological Surgery, University of California, San Francisco, California, 94158
- Weill Institute for Neurosciences, University of California, San Francisco, California, 94158
- Medical Scientist Training Program, University of California, San Francisco, California, 94158
- Graduate Program in Bioengineering, University of California, Berkeley, California 94720, & University of California, San Francisco, California, 94158
| | - Jessie R Liu
- Department of Neurological Surgery, University of California, San Francisco, California, 94158
- Weill Institute for Neurosciences, University of California, San Francisco, California, 94158
- Graduate Program in Bioengineering, University of California, Berkeley, California 94720, & University of California, San Francisco, California, 94158
| | - Lingyun Zhao
- Department of Neurological Surgery, University of California, San Francisco, California, 94158
- Weill Institute for Neurosciences, University of California, San Francisco, California, 94158
| | - Deborah F Levy
- Department of Neurological Surgery, University of California, San Francisco, California, 94158
- Weill Institute for Neurosciences, University of California, San Francisco, California, 94158
| | - Terri L Scott
- Department of Neurological Surgery, University of California, San Francisco, California, 94158
- Weill Institute for Neurosciences, University of California, San Francisco, California, 94158
| | - Edward F Chang
- Department of Neurological Surgery, University of California, San Francisco, California, 94158
- Weill Institute for Neurosciences, University of California, San Francisco, California, 94158
- Graduate Program in Bioengineering, University of California, Berkeley, California 94720, & University of California, San Francisco, California, 94158
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12
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Lim J, Wang PT, Shaw SJ, Gong H, Armacost M, Liu CY, Do AH, Heydari P, Nenadic Z. Artifact propagation in subdural cortical electrostimulation: Characterization and modeling. Front Neurosci 2022; 16:1021097. [PMID: 36312030 PMCID: PMC9596776 DOI: 10.3389/fnins.2022.1021097] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Accepted: 09/21/2022] [Indexed: 11/13/2022] Open
Abstract
Cortical stimulation via electrocorticography (ECoG) may be an effective method for inducing artificial sensation in bi-directional brain-computer interfaces (BD-BCIs). However, strong electrical artifacts caused by electrostimulation may significantly degrade or obscure neural information. A detailed understanding of stimulation artifact propagation through relevant tissues may improve existing artifact suppression techniques or inspire the development of novel artifact mitigation strategies. Our work thus seeks to comprehensively characterize and model the propagation of artifacts in subdural ECoG stimulation. To this end, we collected and analyzed data from eloquent cortex mapping procedures of four subjects with epilepsy who were implanted with subdural ECoG electrodes. From this data, we observed that artifacts exhibited phase-locking and ratcheting characteristics in the time domain across all subjects. In the frequency domain, stimulation caused broadband power increases, as well as power bursts at the fundamental stimulation frequency and its super-harmonics. The spatial distribution of artifacts followed the potential distribution of an electric dipole with a median goodness-of-fit of R2 = 0.80 across all subjects and stimulation channels. Artifacts as large as ±1,100 μV appeared anywhere from 4.43 to 38.34 mm from the stimulation channel. These temporal, spectral and spatial characteristics can be utilized to improve existing artifact suppression techniques, inspire new strategies for artifact mitigation, and aid in the development of novel cortical stimulation protocols. Taken together, these findings deepen our understanding of cortical electrostimulation and provide critical design specifications for future BD-BCI systems.
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Affiliation(s)
- Jeffrey Lim
- Department of Biomedical Engineering, University of California, Irvine, Irvine, CA, United States
- *Correspondence: Jeffrey Lim
| | - Po T. Wang
- Department of Biomedical Engineering, University of California, Irvine, Irvine, CA, United States
| | - Susan J. Shaw
- Rancho Los Amigos National Rehabilitation Center, Downey, CA, United States
| | - Hui Gong
- Rancho Los Amigos National Rehabilitation Center, Downey, CA, United States
| | - Michelle Armacost
- Rancho Los Amigos National Rehabilitation Center, Downey, CA, United States
| | - Charles Y. Liu
- Rancho Los Amigos National Rehabilitation Center, Downey, CA, United States
| | - An H. Do
- Department of Neurology, University of California, Irvine, Irvine, CA, United States
| | - Payam Heydari
- Department of Biomedical Engineering, University of California, Irvine, Irvine, CA, United States
- Department of Electrical Engineering and Computer Science, University of California, Irvine, Irvine, CA, United States
| | - Zoran Nenadic
- Department of Biomedical Engineering, University of California, Irvine, Irvine, CA, United States
- Department of Electrical Engineering and Computer Science, University of California, Irvine, Irvine, CA, United States
- Zoran Nenadic
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13
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Cometa A, Falasconi A, Biasizzo M, Carpaneto J, Horn A, Mazzoni A, Micera S. Clinical neuroscience and neurotechnology: An amazing symbiosis. iScience 2022; 25:105124. [PMID: 36193050 PMCID: PMC9526189 DOI: 10.1016/j.isci.2022.105124] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
In the last decades, clinical neuroscience found a novel ally in neurotechnologies, devices able to record and stimulate electrical activity in the nervous system. These technologies improved the ability to diagnose and treat neural disorders. Neurotechnologies are concurrently enabling a deeper understanding of healthy and pathological dynamics of the nervous system through stimulation and recordings during brain implants. On the other hand, clinical neurosciences are not only driving neuroengineering toward the most relevant clinical issues, but are also shaping the neurotechnologies thanks to clinical advancements. For instance, understanding the etiology of a disease informs the location of a therapeutic stimulation, but also the way stimulation patterns should be designed to be more effective/naturalistic. Here, we describe cases of fruitful integration such as Deep Brain Stimulation and cortical interfaces to highlight how this symbiosis between clinical neuroscience and neurotechnology is closer to a novel integrated framework than to a simple interdisciplinary interaction.
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14
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Yin Z, Zhu G, Liu Y, Zhao B, Liu D, Bai Y, Zhang Q, Shi L, Feng T, Yang A, Liu H, Meng F, Neumann WJ, Kühn AA, Jiang Y, Zhang J. OUP accepted manuscript. Brain 2022; 145:2407-2421. [PMID: 35441231 PMCID: PMC9337810 DOI: 10.1093/brain/awac121] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2022] [Revised: 03/11/2022] [Accepted: 03/24/2022] [Indexed: 11/30/2022] Open
Abstract
Freezing of gait is a debilitating symptom in advanced Parkinson’s disease and responds heterogeneously to treatments such as deep brain stimulation. Recent studies indicated that cortical dysfunction is involved in the development of freezing, while evidence depicting the specific role of the primary motor cortex in the multi-circuit pathology of freezing is lacking. Since abnormal beta-gamma phase-amplitude coupling recorded from the primary motor cortex in patients with Parkinson’s disease indicates parkinsonian state and responses to therapeutic deep brain stimulation, we hypothesized this metric might reveal unique information on understanding and improving therapy for freezing of gait. Here, we directly recorded potentials in the primary motor cortex using subdural electrocorticography and synchronously captured gait freezing using optoelectronic motion-tracking systems in 16 freely-walking patients with Parkinson’s disease who received subthalamic nucleus deep brain stimulation surgery. Overall, we recorded 451 timed up-and-go walking trials and quantified 7073 s of stable walking and 3384 s of gait freezing in conditions of on/off-stimulation and with/without dual-tasking. We found that (i) high beta-gamma phase-amplitude coupling in the primary motor cortex was detected in freezing trials (i.e. walking trials that contained freezing), but not non-freezing trials, and the high coupling in freezing trials was not caused by dual-tasking or the lack of movement; (ii) non-freezing episodes within freezing trials also demonstrated abnormally high couplings, which predicted freezing severity; (iii) deep brain stimulation of subthalamic nucleus reduced these abnormal couplings and simultaneously improved freezing; and (iv) in trials that were at similar coupling levels, stimulation trials still demonstrated lower freezing severity than no-stimulation trials. These findings suggest that elevated phase-amplitude coupling in the primary motor cortex indicates higher probabilities of freezing. Therapeutic deep brain stimulation alleviates freezing by both decoupling cortical oscillations and enhancing cortical resistance to abnormal coupling. We formalized these findings to a novel ‘bandwidth model,’ which specifies the role of cortical dysfunction, cognitive burden and therapeutic stimulation on the emergence of freezing. By targeting key elements in the model, we may develop next-generation deep brain stimulation approaches for freezing of gait.
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Affiliation(s)
| | | | | | - Baotian Zhao
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Defeng Liu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Yutong Bai
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Quan Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Lin Shi
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Tao Feng
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Anchao Yang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Huanguang Liu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Fangang Meng
- Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
- Beijing Key Laboratory of Neurostimulation, Beijing, China
| | - Wolf Julian Neumann
- Movement Disorder and Neuromodulation Unit, Department of Neurology, Charité—Campus Mitte, Charite—Universitatsmedizin Berlin, Chariteplatz 1, 10117 Berlin, Germany
| | - Andrea A Kühn
- Movement Disorder and Neuromodulation Unit, Department of Neurology, Charité—Campus Mitte, Charite—Universitatsmedizin Berlin, Chariteplatz 1, 10117 Berlin, Germany
- Berlin School of Mind and Brain, Charite—Universitatsmedizin Berlin, Unter den Linden 6, 10099 Berlin, Germany
- NeuroCure, Charite—Universitatsmedizin Berlin, Chariteplatz 1, 10117 Berlin, Germany
| | - Yin Jiang
- Correspondence may also be addressed to: Dr Yin Jiang Capital Medical University Department of Functional Neurosurgery, Beijing Neurosurgical Institute No. 119 South 4208 Ring West Road Fengtai District, 100070 Beijing, China E-mail:
| | - Jianguo Zhang
- Correspondence to: Prof. Dr Jianguo Zhang Capital Medical University Department of Neurosurgery, Beijing Tiantan Hospital No. 119 South 4th Ring West Road Fengtai District, 100070 Beijing, China E-mail:
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15
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Abdul Nabi Ali A, Alam M, Klein SC, Behmann N, Krauss JK, Doll T, Blume H, Schwabe K. Predictive accuracy of CNN for cortical oscillatory activity in an acute rat model of parkinsonism. Neural Netw 2021; 146:334-340. [PMID: 34923220 DOI: 10.1016/j.neunet.2021.11.025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2021] [Revised: 10/08/2021] [Accepted: 11/24/2021] [Indexed: 10/19/2022]
Abstract
In neurological and neuropsychiatric disorders neuronal oscillatory activity between basal ganglia and cortical circuits are altered, which may be useful as biomarker for adaptive deep brain stimulation. We investigated whether changes in the spectral power of oscillatory activity in the motor cortex (MCtx) and the sensorimotor cortex (SMCtx) of rats after injection of the dopamine (DA) receptor antagonist haloperidol (HALO) would be similar to those observed in Parkinson disease. Thereafter, we tested whether a convolutional neural network (CNN) model would identify brain signal alterations in this acute model of parkinsonism. A sixteen channel surface micro-electrocorticogram (ECoG) recording array was placed under the dura above the MCtx and SMCtx areas of one hemisphere under general anaesthesia in rats. Seven days after surgery, micro ECoG was recorded in individual free moving rats in three conditions: (1) basal activity, (2) after injection of HALO (0.5 mg/kg), and (3) with additional injection of apomorphine (APO) (1 mg/kg). Furthermore, a CNN-based classification consisting of 23,530 parameters was applied on the raw data. HALO injection decreased oscillatory theta band activity (4-8 Hz) and enhanced beta (12-30 Hz) and gamma (30-100 Hz) in MCtx and SMCtx, which was compensated after APO injection (P ¡ 0.001). Evaluation of classification performance of the CNN model provided accuracy of 92%, sensitivity of 90% and specificity of 93% on one-dimensional signals. The CNN proposed model requires a minimum of sensory hardware and may be integrated into future research on therapeutic devices for Parkinson disease, such as adaptive closed loop stimulation, thus contributing to more efficient way of treatment.
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Affiliation(s)
- Ali Abdul Nabi Ali
- Institute of Microelectronic Systems, Architectures and Systems, Leibniz University Hannover, Hannover, D-30167, Lower Saxony, Germany
| | - Mesbah Alam
- Department of Neurosurgery, Hannover Medical School, Hannover, D-30625, Lower Saxony, Germany.
| | - Simon C Klein
- Institute of Microelectronic Systems, Architectures and Systems, Leibniz University Hannover, Hannover, D-30167, Lower Saxony, Germany
| | - Nicolai Behmann
- Institute of Microelectronic Systems, Architectures and Systems, Leibniz University Hannover, Hannover, D-30167, Lower Saxony, Germany
| | - Joachim K Krauss
- Department of Neurosurgery, Hannover Medical School, Hannover, D-30625, Lower Saxony, Germany
| | - Theodor Doll
- Biomaterial Engineering, Hannover Medical School and Translational Medical Engineering Fraunhofer ITEM, Hannover, D-30625, Lower Saxony, Germany
| | - Holger Blume
- Institute of Microelectronic Systems, Architectures and Systems, Leibniz University Hannover, Hannover, D-30167, Lower Saxony, Germany
| | - Kerstin Schwabe
- Department of Neurosurgery, Hannover Medical School, Hannover, D-30625, Lower Saxony, Germany
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16
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Jeanvoine H, Labriffe M, Tannou T, Navasiolava N, Ter Minassian A, Girot JB, Leiber LM, Custaud MA, Annweiler C, Dinomais M. Specific age-correlated activation of top hierarchical motor control areas during gait-like plantar stimulation: An fMRI study. Hum Brain Mapp 2021; 43:833-843. [PMID: 34738281 PMCID: PMC8720193 DOI: 10.1002/hbm.25691] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2021] [Revised: 10/09/2021] [Accepted: 10/11/2021] [Indexed: 12/26/2022] Open
Abstract
A better understanding of gait disorders that are associated with aging is crucial to prevent adverse outcomes. The functional study of gait remains a thorny issue due to technical constraints inherent to neuroimaging procedures, as most of them require to stay supine and motionless. Using an MRI‐compatible system of boots reproducing gait‐like plantar stimulation, we investigated the correlation between age and brain fMRI activation during simulated gait in healthy adults. Sixty‐seven right‐handed healthy volunteers aged between 20 and 77 years old (49.2 ± 18.0 years; 35 women) were recruited. Two paradigms were assessed consecutively: (a) gait‐like plantar stimulation and (b) chaotic and not gait‐related plantar stimulation. Resulting statistical parametric maps were analyzed with a multiple‐factor regression that included age and a threshold determined by Monte‐Carlo simulation to fulfill a family‐wise error rate correction of p < .05. In the first paradigm, there was an age‐correlated activation of the right pallidum, thalamus and putamen. The second paradigm showed an age‐correlated deactivation of both primary visual areas (V1). The subtraction between results of the first and second paradigms showed age‐correlated activation of the right presupplementary motor area (Brodmann Area [BA] 6) and right mid‐dorsolateral prefrontal cortex (BA9‐10). Our results show age‐correlated activity in areas that have been associated with the control of gait, highlighting the relevance of this simulation model for functional gait study. The specific progressive activation of top hierarchical control areas in simulated gait and advancing age corroborate a progressive loss of automation in healthy older adults.
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Affiliation(s)
- Henry Jeanvoine
- Department of Radiology, Angers University Hospital, University of Angers, Angers, France
| | - Matthieu Labriffe
- Department of Radiology, Angers University Hospital, University of Angers, Angers, France.,Laboratoire Angevin de Recherche en Ingénierie des Systèmes, EA7315, University of Angers, Angers, France
| | - Thomas Tannou
- Department of Geriatrics, Besançon University Hospital, University of Franche-Comté, Besançon, France.,Integrative and Clinical Neurosciences, EA 481, University of Franche-Comté, Besançon, France.,Centre de Recherche, Institut Universitaire de Gériatrie de Montréal, Montréal, Canada
| | - Nastassia Navasiolava
- Clinical Research Center, Angers University Hospital, University of Angers, Angers, France
| | - Aram Ter Minassian
- Laboratoire Angevin de Recherche en Ingénierie des Systèmes, EA7315, University of Angers, Angers, France.,Department of Anesthesia and Critical Care, Angers University Hospital, Angers, France
| | - Jean-Baptiste Girot
- Department of Radiology, Angers University Hospital, University of Angers, Angers, France.,Laboratoire Angevin de Recherche en Ingénierie des Systèmes, EA7315, University of Angers, Angers, France
| | - Louis-Marie Leiber
- Department of Radiology, Angers University Hospital, University of Angers, Angers, France.,Laboratoire Angevin de Recherche en Ingénierie des Systèmes, EA7315, University of Angers, Angers, France
| | - Marc-Antoine Custaud
- Clinical Research Center, Angers University Hospital, University of Angers, Angers, France.,Laboratoire de Biologie Neuro-Vasculaire et Mitochondriale Intégrée, UMR CNRS 6214 INSERM U1083, University of Angers, Angers, France
| | - Cédric Annweiler
- Department of Neuroscience, Division of Geriatric Medicine and Memory Clinic-Angers University Hospital, UPRES EA 4638-University of Angers, Angers, France.,Department of Medical Biophysics, Robarts Research Institute, Schulich School of Medicine and Dentistry, University of Western Ontario, London, Ontario, Canada
| | - Mickaël Dinomais
- Laboratoire Angevin de Recherche en Ingénierie des Systèmes, EA7315, University of Angers, Angers, France.,Department of Physical and Rehabilitation Medicine, Angers University Hospital, University of Angers, Angers, France
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17
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Tia B, Pifferi F. Oscillatory Activity in Mouse Lemur Primary Motor Cortex During Natural Locomotor Behavior. Front Syst Neurosci 2021; 15:655980. [PMID: 34220457 PMCID: PMC8249816 DOI: 10.3389/fnsys.2021.655980] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2021] [Accepted: 05/17/2021] [Indexed: 11/29/2022] Open
Abstract
In arboreal environments, substrate orientation determines the biomechanical strategy for postural maintenance and locomotion. In this study, we investigated possible neuronal correlates of these mechanisms in an ancestral primate model, the gray mouse lemur. We conducted telemetric recordings of electrocorticographic activity in left primary motor cortex of two mouse lemurs moving on a branch-like small-diameter pole, fixed horizontally, or vertically. Analysis of cortical oscillations in high β (25–35 Hz) and low γ (35–50 Hz) bands showed stronger resting power on horizontal than vertical substrate, potentially illustrating sensorimotor processes for postural maintenance. Locomotion on horizontal substrate was associated with stronger event-related desynchronization than vertical substrate, which could relate to locomotor adjustments and/or derive from differences in baseline activity. Spectrograms of cortical activity showed modulation throughout individual locomotor cycles, with higher values in the first than second half cycle. However, substrate orientation did not significantly influence these variations. Overall, these results confirm that specific cortical mechanisms are solicited during arboreal locomotion, whereby mouse lemurs adjust cortical activity to substrate orientation during static posture and locomotion, and modulate this activity throughout locomotor cycles.
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18
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Camarrone F, Branco MP, Ramsey NF, Van Hulle MM. Accurate Offline Asynchronous Detection of Individual Finger Movement From Intracranial Brain Signals Using a Novel Multiway Approach. IEEE Trans Biomed Eng 2021; 68:2176-2187. [PMID: 33186097 DOI: 10.1109/tbme.2020.3037934] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
Asynchronous motor Brain Computer Interfacing (BCI) is characterized by the continuous decoding of intended muscular activity from brain signals. Such applications have gained widespread interest for enabling users to issue commands volitionally. In conventional motor BCIs features extracted from brain signals are concatenated into vector- or matrix-based (or one-/two-way) representations. Nevertheless, when accounting for the original multimodal or multiway signal structure, decoding performance has been shown to improve jointly with result interpretability. However, as multiway decoders are notorious for the extensive computational cost to train them, conventional ones are still preferred. To curb this limitation, we introduce a novel multiway classifier, called Block-Term Tensor Classifier that inherits the improved accuracy of multiway methods while providing fast training. We show that it can outperform state-of-the-art multiway and two-way Linear Discriminant Analysis classifiers in asynchronous detection of individual finger movements from intracranial recordings, an essential feature to achieve a sense of dexterity with hand prosthetics and exoskeletons.
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19
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Brazhnik E, Novikov N, McCoy AJ, Ilieva NM, Ghraib MW, Walters JR. Early decreases in cortical mid-gamma peaks coincide with the onset of motor deficits and precede exaggerated beta build-up in rat models for Parkinson's disease. Neurobiol Dis 2021; 155:105393. [PMID: 34000417 DOI: 10.1016/j.nbd.2021.105393] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2020] [Revised: 04/27/2021] [Accepted: 05/12/2021] [Indexed: 11/30/2022] Open
Abstract
Evidence suggests that exaggerated beta range local field potentials (LFP) in basal ganglia-thalamocortical circuits constitute an important biomarker for feedback for deep brain stimulation in Parkinson's disease patients, although the role of this phenomenon in triggering parkinsonian motor symptoms remains unclear. A useful model for probing the causal role of motor circuit LFP synchronization in motor dysfunction is the unilateral dopamine cell-lesioned rat, which shows dramatic motor deficits walking contralaterally to the lesion but can walk steadily ipsilaterally on a circular treadmill. Within hours after 6-OHDA injection, rats show marked deficits in ipsilateral walking with early loss of significant motor cortex (MCx) LFP peaks in the mid-gamma 41-45 Hz range in the lesioned hemisphere; both effects were reversed by dopamine agonist administration. Increases in MCx and substantia nigra pars reticulata (SNpr) coherence and LFP power in the 29-40 Hz range emerged more gradually over 7 days, although without further progression of walking deficits. Twice-daily chronic dopamine antagonist treatment induced rapid onset of catalepsy and also reduced MCx 41-45 Hz LFP activity at 1 h, with increases in MCx and SNpr 29-40 Hz power/coherence emerging over 7 days, as assessed during periods of walking before the morning treatments. Thus, increases in high beta power in these parkinsonian models emerge gradually and are not linearly correlated with motor deficits. Earlier changes in cortical circuits, reflected in the rapid decreases in MCx LFP mid-gamma LFP activity, may contribute to evolving plasticity supporting increased beta range synchronized activity in basal ganglia-thalamocortical circuits after loss of dopamine receptor stimulation.
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Affiliation(s)
- Elena Brazhnik
- Neurophysiological Pharmacology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892-3702, United States of America
| | - Nikolay Novikov
- Neurophysiological Pharmacology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892-3702, United States of America
| | - Alex J McCoy
- Neurophysiological Pharmacology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892-3702, United States of America
| | - Neda M Ilieva
- Neurophysiological Pharmacology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892-3702, United States of America
| | - Marian W Ghraib
- Neurophysiological Pharmacology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892-3702, United States of America
| | - Judith R Walters
- Neurophysiological Pharmacology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892-3702, United States of America.
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20
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Li Y, Wang PT, Vaidya MP, Flint RD, Liu CY, Slutzky MW, Do AH. Refinement of High-Gamma EEG Features From TBI Patients With Hemicraniectomy Using an ICA Informed by Simulated Myoelectric Artifacts. Front Neurosci 2020; 14:599010. [PMID: 33328870 PMCID: PMC7732541 DOI: 10.3389/fnins.2020.599010] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2020] [Accepted: 10/30/2020] [Indexed: 11/20/2022] Open
Abstract
Recent studies have shown the ability to record high-γ signals (80-160 Hz) in electroencephalogram (EEG) from traumatic brain injury (TBI) patients who have had hemicraniectomies. However, extraction of the movement-related high-γ remains challenging due to a confounding bandwidth overlap with surface electromyogram (EMG) artifacts related to facial and head movements. In our previous work, we described an augmented independent component analysis (ICA) approach for removal of EMG artifacts from EEG, and referred to as EMG Reduction by Adding Sources of EMG (ERASE). Here, we tested this algorithm on EEG recorded from six TBI patients with hemicraniectomies while they performed a thumb flexion task. ERASE removed a mean of 52 ± 12% (mean ± S.E.M) (maximum 73%) of EMG artifacts. In contrast, conventional ICA removed a mean of 27 ± 19% (mean ± S.E.M) of EMG artifacts from EEG. In particular, high-γ synchronization was significantly improved in the contralateral hand motor cortex area within the hemicraniectomy site after ERASE was applied. A more sophisticated measure of high-γ complexity is the fractal dimension (FD). Here, we computed the FD of EEG high-γ on each channel. Relative FD of high-γ was defined as that the FD in move state was subtracted by FD in idle state. We found relative FD of high-γ over hemicraniectomy after applying ERASE were strongly correlated to the amplitude of finger flexion force. Results showed that significant correlation coefficients across the electrodes related to thumb flexion averaged ~0.76, while the coefficients across the homologous electrodes in non-hemicraniectomy areas were nearly 0. After conventional ICA, a correlation between relative FD of high-γ and force remained high in both hemicraniectomy areas (up to 0.86) and non-hemicraniectomy areas (up to 0.81). Across all subjects, an average of 83% of electrodes significantly correlated with force was located in the hemicraniectomy areas after applying ERASE. After conventional ICA, only 19% of electrodes with significant correlations were located in the hemicraniectomy. These results indicated that the new approach isolated electrophysiological features during finger motor activation while selectively removing confounding EMG artifacts. This approach removed EMG artifacts that can contaminate high-gamma activity recorded over the hemicraniectomy.
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Affiliation(s)
- Yongcheng Li
- Department of Neurology, University of California, Irvine, Irvine, CA, United States
| | - Po T. Wang
- Department of Biomedical Engineering, University of California, Irvine, Irvine, CA, United States
| | - Mukta P. Vaidya
- Department of Neurology, Northwestern University, Chicago, IL, United States
- Department of Physiology, Northwestern University, Chicago, IL, United States
- Department of Physical Medicine and Rehabilitation, Northwestern University, Chicago, IL, United States
| | - Robert D. Flint
- Department of Neurology, Northwestern University, Chicago, IL, United States
- Department of Physiology, Northwestern University, Chicago, IL, United States
- Department of Physical Medicine and Rehabilitation, Northwestern University, Chicago, IL, United States
| | - Charles Y. Liu
- Department of Neurosurgery, University of Southern California, Los Angeles, CA, United States
- Rancho Los Amigos National Rehabilitation Center, Downey, CA, United States
- Neurorestoration Center, University of Southern California, Los Angeles, CA, United States
| | - Marc W. Slutzky
- Department of Neurology, Northwestern University, Chicago, IL, United States
- Department of Physiology, Northwestern University, Chicago, IL, United States
- Department of Physical Medicine and Rehabilitation, Northwestern University, Chicago, IL, United States
| | - An H. Do
- Department of Neurology, University of California, Irvine, Irvine, CA, United States
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21
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Wang DD, Choi JT. Brain Network Oscillations During Gait in Parkinson's Disease. Front Hum Neurosci 2020; 14:568703. [PMID: 33192399 PMCID: PMC7645204 DOI: 10.3389/fnhum.2020.568703] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2020] [Accepted: 09/29/2020] [Indexed: 11/15/2022] Open
Abstract
Human bipedal walking is a complex motor task that requires supraspinal control for balance and flexible coordination of timing and scaling of many muscles in different environment. Gait impairments are a hallmark of Parkinson’s disease (PD), reflecting dysfunction of cortico-basal ganglia-brainstem circuits. Recent studies using implanted electrodes and surface electroencephalography have demonstrated gait-related brain oscillations in the basal ganglia and cerebral cortex. Here, we review the physiological and pathophysiological roles of (1) basal ganglia oscillations, (2) cortical oscillations, and (3) basal ganglia-cortical interactions during walking. These studies extend a novel framework for movement of disorders where specific patterns of abnormal oscillatory synchronization in the basal ganglia thalamocortical network are associated with specific signs and symptoms. Therefore, we propose that many gait dysfunctions in PD arise from derangements in brain network, and discuss potential therapies aimed at restoring gait impairments through modulation of brain network in PD.
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Affiliation(s)
- Doris D Wang
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, United States
| | - Julia T Choi
- Department of Applied Physiology and Kinesiology, University of Florida, Gainesville, FL, United States
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22
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Tia B, Takemi M, Kosugi A, Castagnola E, Ricci D, Ushiba J, Fadiga L, Iriki A. Spectral Power in Marmoset Frontal Motor Cortex during Natural Locomotor Behavior. Cereb Cortex 2020; 31:1077-1089. [PMID: 33068002 PMCID: PMC7786367 DOI: 10.1093/cercor/bhaa275] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2020] [Revised: 08/25/2020] [Accepted: 08/25/2020] [Indexed: 12/15/2022] Open
Abstract
During primate arboreal locomotion, substrate orientation modifies body axis orientation and biomechanical contribution of fore- and hindlimbs. To characterize the role of cortical oscillations in integrating these locomotor demands, we recorded electrocorticographic activity from left dorsal premotor, primary motor, and supplementary motor cortices of three common marmosets moving across a branch-like small-diameter pole, fixed horizontally or vertically. Animals displayed behavioral adjustments to the task, namely, the horizontal condition mainly induced quadrupedal walk with pronated/neutral forelimb postures, whereas the vertical condition induced walk and bound gaits with supinated/neutral postures. Examination of cortical activity suggests that β (16–35 Hz) and γ (75–100 Hz) oscillations could reflect different processes in locomotor adjustments. During task, modulation of γ ERS by substrate orientation (horizontal/vertical) and epoch (preparation/execution) suggests close tuning to movement dynamics and biomechanical demands. β ERD was essentially modulated by gait (walk/bound), which could illustrate contribution to movement sequence and coordination. At rest, modulation of β power by substrate orientation underlines its role in sensorimotor processes for postural maintenance.
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Affiliation(s)
- Banty Tia
- Laboratory for Symbolic Cognitive Development, RIKEN Center for Biosystems Dynamics Research, Kobe, 650-0047, Japan.,Center for Translational Neurophysiology of Speech and Communication, Istituto Italiano di Tecnologia, Ferrara, 44121, Italy
| | - Mitsuaki Takemi
- Laboratory for Symbolic Cognitive Development, RIKEN Center for Biosystems Dynamics Research, Kobe, 650-0047, Japan.,Graduate School of Science and Technology, Keio University, Yokohama, 223-8522, Japan.,Graduate School of Education, The University of Tokyo, Tokyo, 113-8654, Japan.,Japan Science and Technology Agency, PRESTO, Saitama, 332-0012, Japan
| | - Akito Kosugi
- Laboratory for Symbolic Cognitive Development, RIKEN Center for Biosystems Dynamics Research, Kobe, 650-0047, Japan.,Graduate School of Science and Technology, Keio University, Yokohama, 223-8522, Japan
| | - Elisa Castagnola
- Center for Translational Neurophysiology of Speech and Communication, Istituto Italiano di Tecnologia, Ferrara, 44121, Italy
| | - Davide Ricci
- Center for Translational Neurophysiology of Speech and Communication, Istituto Italiano di Tecnologia, Ferrara, 44121, Italy
| | - Junichi Ushiba
- Department of Biosciences and Informatics, Faculty of Science and Technology, Keio University, Yokohama, 223-8522, Japan
| | - Luciano Fadiga
- Center for Translational Neurophysiology of Speech and Communication, Istituto Italiano di Tecnologia, Ferrara, 44121, Italy.,Section of Physiology, University of Ferrara, Ferrara, 44121, Italy
| | - Atsushi Iriki
- Laboratory for Symbolic Cognitive Development, RIKEN Center for Biosystems Dynamics Research, Kobe, 650-0047, Japan
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23
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Jacobsen NSJ, Blum S, Witt K, Debener S. A walk in the park? Characterizing gait-related artifacts in mobile EEG recordings. Eur J Neurosci 2020; 54:8421-8440. [PMID: 32909315 DOI: 10.1111/ejn.14965] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2020] [Revised: 08/31/2020] [Accepted: 09/01/2020] [Indexed: 01/22/2023]
Abstract
Brain activity during natural walking outdoors can be captured using mobile electroencephalography (EEG). However, EEG recorded during gait is confounded with artifacts from various sources, possibly obstructing the interpretation of brain activity patterns. Currently, there is no consensus on how the amount of artifact present in these recordings should be quantified, or is there a systematic description of gait artifact properties. In the current study, we expand several features into a seven-dimensional footprint of gait-related artifacts, combining features of time, time-frequency, spatial, and source domains. EEG of N = 26 participants was recorded while standing and walking outdoors. Footprints of gait-related artifacts before and after two different artifact attenuation strategies (after artifact subspace reconstruction (ASR) and after subsequent independent component analysis [ICA]) were systematically different. We also evaluated topographies, morphologies, and signal-to-noise ratios (SNR) of button-press event-related potentials (ERP) before and after artifact handling, to confirm gait-artifact reduction specificity. Morphologies and SNR remained unchanged after artifact attenuation, whereas topographies improved in quality. Our results show that the footprint can provide a detailed assessment of gait-related artifacts and can be used to estimate the sensitivity of different artifact reduction strategies. Moreover, the analysis of button-press ERPs demonstrated its specificity, as processing did not only reduce gait-related artifacts but ERPs of interest remained largely unchanged. We conclude that the proposed footprint is well suited to characterize individual differences in gait-related artifact extent. In the future, it could be used to compare and optimize recording setups and processing pipelines comprehensively.
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Affiliation(s)
- Nadine Svenja Josée Jacobsen
- School of Medicine and Health Sciences, Department of Psychology, Neuropsychology Lab, University of Oldenburg, Oldenburg, Germany
| | - Sarah Blum
- School of Medicine and Health Sciences, Department of Psychology, Neuropsychology Lab, University of Oldenburg, Oldenburg, Germany
| | - Karsten Witt
- School of Medicine and Health Sciences, Department of Neurology and Research Center Neurosensory Science, University of Oldenburg, Oldenburg, Germany
| | - Stefan Debener
- School of Medicine and Health Sciences, Department of Psychology, Neuropsychology Lab, University of Oldenburg, Oldenburg, Germany
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24
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Multi-session anodal transcranial direct current stimulation enhances lower extremity functional performance in healthy older adults. Exp Brain Res 2020; 238:1925-1936. [DOI: 10.1007/s00221-020-05827-6] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2019] [Accepted: 05/02/2020] [Indexed: 12/22/2022]
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25
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Malekzadeh-Arasteh O, Pu H, Lim J, Liu CY, Do AH, Nenadic Z, Heydari P. An Energy-Efficient CMOS Dual-Mode Array Architecture for High-Density ECoG-Based Brain-Machine Interfaces. IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS 2020; 14:332-342. [PMID: 31902769 DOI: 10.1109/tbcas.2019.2963302] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
This article presents an energy-efficient electrocorticography (ECoG) array architecture for fully-implantable brain machine interface systems. A novel dual-mode analog signal processing method is introduced that extracts neural features from high- γ band (80-160 Hz) at the early stages of signal acquisition. Initially, brain activity across the full-spectrum is momentarily observed to compute the feature weights in the digital back-end during full-band mode operation. Subsequently, these weights are fed back to the front-end and the system reverts to base-band mode to perform feature extraction. This approach utilizes a distinct optimized signal pathway based on power envelope extraction, resulting in 1.72× power reduction in the analog blocks and up to 50× potential power savings for digitization and processing (implemented off-chip in this article). A prototype incorporating a 32-channel ultra-low power signal acquisition front-end is fabricated in 180 nm CMOS process with 0.8 V supply. This chip consumes 1.05 μW (0.205 μW for feature extraction only) power and occupies 0.245 [Formula: see text] die area per channel. The chip measurement shows better than 76.5-dB common-mode rejection ratio (CMRR), 4.09 noise efficiency factor (NEF), and 10.04 power efficiency factor (PEF). In-vivo human tests have been carried out with electroencephalography and ECoG signals to validate the performance and dual-mode operation in comparison to commercial acquisition systems.
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26
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Nordin AD, Hairston WD, Ferris DP. Faster Gait Speeds Reduce Alpha and Beta EEG Spectral Power From Human Sensorimotor Cortex. IEEE Trans Biomed Eng 2020; 67:842-853. [PMID: 31199248 PMCID: PMC7134343 DOI: 10.1109/tbme.2019.2921766] [Citation(s) in RCA: 45] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023]
Abstract
OBJECTIVE Our aim was to determine if walking speed affected human sensorimotor electrocortical dynamics using mobile high-density electroencephalography (EEG). METHODS To overcome limitations associated with motion and muscle artifact contamination in EEG recordings, we compared solutions for artifact removal using novel dual-layer EEG electrodes and alternative signal processing methods. Dual-layer EEG simultaneously recorded human electrocortical signals and isolated motion artifacts using pairs of mechanically coupled and electrically independent electrodes. For electrical muscle activity removal, we incorporated electromyographic (EMG) recordings from the neck into our mobile EEG data processing pipeline. We compared artifact removal methods during treadmill walking at four speeds (0.5, 1.0, 1.5, and 2.0 m/s). RESULTS Left and right sensorimotor alpha and beta spectral power increased in contralateral limb single support and push off, and decreased during contralateral limb swing at each speed. At faster walking speeds, sensorimotor spectral power fluctuations were less pronounced across the gait cycle with reduced alpha and beta power (p < 0.05) compared to slower speeds. Isolated noise recordings and neck EMG spectral power fluctuations matched gait events and showed broadband spectral power increases at faster speeds. CONCLUSION AND SIGNIFICANCE Dual-layer EEG enabled us to isolate changes in human sensorimotor electrocortical dynamics across walking speeds. A comparison of signal processing approaches revealed similar intrastride cortical fluctuations when applying common (e.g., artifact subspace reconstruction) and novel artifact rejection methods. Dual-layer EEG, however, allowed us to document and rule out residual artifacts, which exposed sensorimotor spectral power changes across gait speeds.
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27
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Delval A, Bayot M, Defebvre L, Dujardin K. Cortical Oscillations during Gait: Wouldn't Walking be so Automatic? Brain Sci 2020; 10:E90. [PMID: 32050471 PMCID: PMC7071606 DOI: 10.3390/brainsci10020090] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2020] [Revised: 02/03/2020] [Accepted: 02/07/2020] [Indexed: 01/12/2023] Open
Abstract
Gait is often considered as an automatic movement but cortical control seems necessary to adapt gait pattern with environmental constraints. In order to study cortical activity during real locomotion, electroencephalography (EEG) appears to be particularly appropriate. It is now possible to record changes in cortical neural synchronization/desynchronization during gait. Studying gait initiation is also of particular interest because it implies motor and cognitive cortical control to adequately perform a step. Time-frequency analysis enables to study induced changes in EEG activity in different frequency bands. Such analysis reflects cortical activity implied in stabilized gait control but also in more challenging tasks (obstacle crossing, changes in speed, dual tasks…). These spectral patterns are directly influenced by the walking context but, when analyzing gait with a more demanding attentional task, cortical areas other than the sensorimotor cortex (prefrontal, posterior parietal cortex, etc.) seem specifically implied. While the muscular activity of legs and cortical activity are coupled, the precise role of the motor cortex to control the level of muscular contraction according to the gait task remains debated. The decoding of this brain activity is a necessary step to build valid brain-computer interfaces able to generate gait artificially.
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Affiliation(s)
- Arnaud Delval
- UMR-S1172, Lille Neuroscience & Cognition, Inserm, University Lille, 59000 Lille, France; (M.B.); (L.D.); (K.D.)
- Clinical Neurophysiology Department, CHU Lille, 59000 Lille, France
| | - Madli Bayot
- UMR-S1172, Lille Neuroscience & Cognition, Inserm, University Lille, 59000 Lille, France; (M.B.); (L.D.); (K.D.)
- Clinical Neurophysiology Department, CHU Lille, 59000 Lille, France
| | - Luc Defebvre
- UMR-S1172, Lille Neuroscience & Cognition, Inserm, University Lille, 59000 Lille, France; (M.B.); (L.D.); (K.D.)
- Movement Disorders Department, CHU Lille, 59000 Lille, France
| | - Kathy Dujardin
- UMR-S1172, Lille Neuroscience & Cognition, Inserm, University Lille, 59000 Lille, France; (M.B.); (L.D.); (K.D.)
- Movement Disorders Department, CHU Lille, 59000 Lille, France
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28
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Volkova K, Lebedev MA, Kaplan A, Ossadtchi A. Decoding Movement From Electrocorticographic Activity: A Review. Front Neuroinform 2019; 13:74. [PMID: 31849632 PMCID: PMC6901702 DOI: 10.3389/fninf.2019.00074] [Citation(s) in RCA: 32] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2019] [Accepted: 11/14/2019] [Indexed: 01/08/2023] Open
Abstract
Electrocorticography (ECoG) holds promise to provide efficient neuroprosthetic solutions for people suffering from neurological disabilities. This recording technique combines adequate temporal and spatial resolution with the lower risks of medical complications compared to the other invasive methods. ECoG is routinely used in clinical practice for preoperative cortical mapping in epileptic patients. During the last two decades, research utilizing ECoG has considerably grown, including the paradigms where behaviorally relevant information is extracted from ECoG activity with decoding algorithms of different complexity. Several research groups have advanced toward the development of assistive devices driven by brain-computer interfaces (BCIs) that decode motor commands from multichannel ECoG recordings. Here we review the evolution of this field and its recent tendencies, and discuss the potential areas for future development.
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Affiliation(s)
- Ksenia Volkova
- Center for Bioelectric Interfaces, Higher School of Economics, National Research University, Moscow, Russia
| | - Mikhail A. Lebedev
- Center for Bioelectric Interfaces, Higher School of Economics, National Research University, Moscow, Russia
| | - Alexander Kaplan
- Center for Bioelectric Interfaces, Higher School of Economics, National Research University, Moscow, Russia
- Center for Biotechnology Development, National Research Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russia
- Laboratory for Neurophysiology and Neuro-Computer Interfaces, Faculty of Biology, Lomonosov Moscow State University, Moscow, Russia
| | - Alexei Ossadtchi
- Center for Bioelectric Interfaces, Higher School of Economics, National Research University, Moscow, Russia
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29
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Wang PT, Camacho E, Wang M, Li Y, Shaw SJ, Armacost M, Gong H, Kramer D, Lee B, Andersen RA, Liu CY, Heydari P, Nenadic Z, Do AH. A benchtop system to assess the feasibility of a fully independent and implantable brain-machine interface. J Neural Eng 2019; 16:066043. [PMID: 31585451 DOI: 10.1088/1741-2552/ab4b0c] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
OBJECTIVE State-of-the-art invasive brain-machine interfaces (BMIs) have shown significant promise, but rely on external electronics and wired connections between the brain and these external components. This configuration presents health risks and limits practical use. These limitations can be addressed by designing a fully implantable BMI similar to existing FDA-approved implantable devices. Here, a prototype BMI system whose size and power consumption are comparable to those of fully implantable medical devices was designed and implemented, and its performance was tested at the benchtop and bedside. APPROACH A prototype of a fully implantable BMI system was designed and implemented as a miniaturized embedded system. This benchtop analogue was tested in its ability to acquire signals, train a decoder, perform online decoding, wirelessly control external devices, and operate independently on battery. Furthermore, performance metrics such as power consumption were benchmarked. MAIN RESULTS An analogue of a fully implantable BMI was fabricated with a miniaturized form factor. A patient undergoing epilepsy surgery evaluation with an electrocorticogram (ECoG) grid implanted over the primary motor cortex was recruited to operate the system. Seven online runs were performed with an average binary state decoding accuracy of 87.0% (lag optimized, or 85.0% at fixed latency). The system was powered by a wirelessly rechargeable battery, consumed ∼150 mW, and operated for >60 h on a single battery cycle. SIGNIFICANCE The BMI analogue achieved immediate and accurate decoding of ECoG signals underlying hand movements. A wirelessly rechargeable battery and other supporting functions allowed the system to function independently. In addition to the small footprint and acceptable power and heat dissipation, these results suggest that fully implantable BMI systems are feasible.
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Affiliation(s)
- Po T Wang
- Department of Biomedical Engineering, University of California, Irvine, CA 92697, United States of America
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30
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Configuration of electrical spinal cord stimulation through real-time processing of gait kinematics. Nat Protoc 2019; 13:2031-2061. [PMID: 30190556 DOI: 10.1038/s41596-018-0030-9] [Citation(s) in RCA: 64] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
Epidural electrical stimulation (EES) of the spinal cord and real-time processing of gait kinematics are powerful methods for the study of locomotion and the improvement of motor control after injury or in neurological disorders. Here, we describe equipment and surgical procedures that can be used to acquire chronic electromyographic (EMG) recordings from leg muscles and to implant targeted spinal cord stimulation systems that remain stable up to several months after implantation in rats and nonhuman primates. We also detail how to exploit these implants to configure electrical spinal cord stimulation policies that allow control over the degree of extension and flexion of each leg during locomotion. This protocol uses real-time processing of gait kinematics and locomotor performance, and can be configured within a few days. Once configured, stimulation bursts are delivered over specific spinal cord locations with precise timing that reproduces the natural spatiotemporal activation of motoneurons during locomotion. These protocols can also be easily adapted for the safe implantation of systems in the vicinity of the spinal cord and to conduct experiments involving real-time movement feedback and closed-loop controllers.
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31
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Slutzky MW. Brain-Machine Interfaces: Powerful Tools for Clinical Treatment and Neuroscientific Investigations. Neuroscientist 2019; 25:139-154. [PMID: 29772957 PMCID: PMC6611552 DOI: 10.1177/1073858418775355] [Citation(s) in RCA: 33] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023]
Abstract
Brain-machine interfaces (BMIs) have exploded in popularity in the past decade. BMIs, also called brain-computer interfaces, provide a direct link between the brain and a computer, usually to control an external device. BMIs have a wide array of potential clinical applications, ranging from restoring communication to people unable to speak due to amyotrophic lateral sclerosis or a stroke, to restoring movement to people with paralysis from spinal cord injury or motor neuron disease, to restoring memory to people with cognitive impairment. Because BMIs are controlled directly by the activity of prespecified neurons or cortical areas, they also provide a powerful paradigm with which to investigate fundamental questions about brain physiology, including neuronal behavior, learning, and the role of oscillations. This article reviews the clinical and neuroscientific applications of BMIs, with a primary focus on motor BMIs.
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Affiliation(s)
- Marc W Slutzky
- 1 Departments of Neurology, Physiology, and Physical Medicine & Rehabilitation, Northwestern University, Chicago, IL, USA
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32
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Nordin AD, Hairston WD, Ferris DP. Human electrocortical dynamics while stepping over obstacles. Sci Rep 2019; 9:4693. [PMID: 30886202 PMCID: PMC6423113 DOI: 10.1038/s41598-019-41131-2] [Citation(s) in RCA: 71] [Impact Index Per Article: 14.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2018] [Accepted: 02/28/2019] [Indexed: 12/21/2022] Open
Abstract
To better understand human brain dynamics during visually guided locomotion, we developed a method of removing motion artifacts from mobile electroencephalography (EEG) and studied human subjects walking and running over obstacles on a treadmill. We constructed a novel dual-layer EEG electrode system to isolate electrocortical signals, and then validated the system using an electrical head phantom and robotic motion platform. We collected data from young healthy subjects walking and running on a treadmill while they encountered unexpected obstacles to step over. Supplementary motor area and premotor cortex had spectral power increases within ~200 ms after object appearance in delta, theta, and alpha frequency bands (3–13 Hz). That activity was followed by similar posterior parietal cortex spectral power increase that decreased in lag time with increasing locomotion speed. The sequence of activation suggests that supplementary motor area and premotor cortex interrupted the gait cycle, while posterior parietal cortex tracked obstacle location for planning foot placement nearly two steps ahead of reaching the obstacle. Together, these results highlight advantages of adopting dual-layer mobile EEG, which should greatly facilitate the study of human brain dynamics in physically active real-world settings and tasks.
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Affiliation(s)
- Andrew D Nordin
- J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, USA.
| | - W David Hairston
- Human Research and Engineering Directorate, U.S. Army Research Laboratory, Aberdeen Proving Ground, USA
| | - Daniel P Ferris
- J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, USA
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33
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Habets JGV, Heijmans M, Kuijf ML, Janssen MLF, Temel Y, Kubben PL. An update on adaptive deep brain stimulation in Parkinson's disease. Mov Disord 2018; 33:1834-1843. [PMID: 30357911 PMCID: PMC6587997 DOI: 10.1002/mds.115] [Citation(s) in RCA: 75] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2018] [Revised: 06/26/2018] [Accepted: 07/08/2018] [Indexed: 12/24/2022] Open
Abstract
Advancing conventional open‐loop DBS as a therapy for PD is crucial for overcoming important issues such as the delicate balance between beneficial and adverse effects and limited battery longevity that are currently associated with treatment. Closed‐loop or adaptive DBS aims to overcome these limitations by real‐time adjustment of stimulation parameters based on continuous feedback input signals that are representative of the patient's clinical state. The focus of this update is to discuss the most recent developments regarding potential input signals and possible stimulation parameter modulation for adaptive DBS in PD. Potential input signals for adaptive DBS include basal ganglia local field potentials, cortical recordings (electrocorticography), wearable sensors, and eHealth and mHealth devices. Furthermore, adaptive DBS can be applied with different approaches of stimulation parameter modulation, the feasibility of which can be adapted depending on specific PD phenotypes. Implementation of technological developments like machine learning show potential in the design of such approaches; however, energy consumption deserves further attention. Furthermore, we discuss future considerations regarding the clinical implementation of adaptive DBS in PD. © 2018 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Jeroen G V Habets
- Departments of Neurosurgery, Maastricht University Medical Center, Maastricht, The Netherlands.,School of Mental Health and Neuroscience, Maastricht University Medical Center, Maastricht, The Netherlands
| | - Margot Heijmans
- Departments of Neurosurgery, Maastricht University Medical Center, Maastricht, The Netherlands.,School of Mental Health and Neuroscience, Maastricht University Medical Center, Maastricht, The Netherlands
| | - Mark L Kuijf
- Department of Neurology, Maastricht University Medical Center, Maastricht, The Netherlands
| | - Marcus L F Janssen
- Department of Neurology, Maastricht University Medical Center, Maastricht, The Netherlands.,Department of Clinical Neurophysiology, Maastricht University Medical Center, Maastricht, The Netherlands.,School of Mental Health and Neuroscience, Maastricht University Medical Center, Maastricht, The Netherlands
| | - Yasin Temel
- Departments of Neurosurgery, Maastricht University Medical Center, Maastricht, The Netherlands.,School of Mental Health and Neuroscience, Maastricht University Medical Center, Maastricht, The Netherlands
| | - Pieter L Kubben
- Departments of Neurosurgery, Maastricht University Medical Center, Maastricht, The Netherlands.,School of Mental Health and Neuroscience, Maastricht University Medical Center, Maastricht, The Netherlands
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