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Grinberg A, Strong A, Strandberg J, Selling J, Liebermann DG, Björklund M, Häger CK. Electrocortical activity associated with movement-related fear: a methodological exploration of a threat-conditioning paradigm involving destabilising perturbations during quiet standing. Exp Brain Res 2024; 242:1903-1915. [PMID: 38896295 PMCID: PMC11252179 DOI: 10.1007/s00221-024-06873-0] [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: 03/08/2024] [Accepted: 06/12/2024] [Indexed: 06/21/2024]
Abstract
Musculoskeletal trauma often leads to lasting psychological impacts stemming from concerns of future injuries. Often referred to as kinesiophobia or re-injury anxiety, such concerns have been shown to hinder return to physical activity and are believed to increase the risk for secondary injuries. Screening for re-injury anxiety is currently restricted to subjective questionnaires, which are prone to self-report bias. We introduce a novel approach to objectively identify electrocortical activity associated with the threat of destabilising perturbations. We aimed to explore its feasibility among non-injured persons, with potential future implementation for screening of re-injury anxiety. Twenty-three participants stood blindfolded on a translational balance perturbation platform. Consecutive auditory stimuli were provided as low (neutral stimulus [CS-]) or high (conditioned stimulus [CS+]) tones. For the main experimental protocol (Protocol I), half of the high tones were followed by a perturbation in one of eight unpredictable directions. A separate validation protocol (Protocol II) requiring voluntary squatting without perturbations was performed with 12 participants. Event-related potentials (ERP) were computed from electroencephalography recordings and significant time-domain components were detected using an interval-wise testing procedure. High-amplitude early contingent negative variation (CNV) waves were significantly greater for CS+ compared with CS- trials in all channels for Protocol I (> 521-800ms), most prominently over frontal and central midline locations (P ≤ 0.001). For Protocol II, shorter frontal ERP components were observed (541-609ms). Our test paradigm revealed electrocortical activation possibly associated with movement-related fear. Exploring the discriminative validity of the paradigm among individuals with and without self-reported re-injury anxiety is warranted.
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Affiliation(s)
- Adam Grinberg
- Department of Community Medicine and Rehabilitation, Umeå University, Umeå, Sweden.
| | - Andrew Strong
- Department of Community Medicine and Rehabilitation, Umeå University, Umeå, Sweden
| | | | - Jonas Selling
- Department of Community Medicine and Rehabilitation, Umeå University, Umeå, Sweden
| | - Dario G Liebermann
- Department of Physical Therapy, Stanley Steyer School of Health Professions, Faculty of Medical & Health Sciences, Tel-Aviv University, Tel Aviv, Israel
| | - Martin Björklund
- Department of Community Medicine and Rehabilitation, Umeå University, Umeå, Sweden
- Centre for Musculoskeletal Research, Department of Occupational Health Sciences and Psychology, University of Gävle, Gävle, Sweden
| | - Charlotte K Häger
- Department of Community Medicine and Rehabilitation, Umeå University, Umeå, Sweden
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Wallace DM, Benyamini M, Nason-Tomaszewski SR, Costello JT, Cubillos LH, Mender MJ, Temmar H, Willsey MS, Patil PG, Chestek CA, Zacksenhouse M. Error detection and correction in intracortical brain-machine interfaces controlling two finger groups. J Neural Eng 2023; 20:046037. [PMID: 37567222 PMCID: PMC10594236 DOI: 10.1088/1741-2552/acef95] [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: 05/23/2023] [Revised: 08/01/2023] [Accepted: 08/11/2023] [Indexed: 08/13/2023]
Abstract
Objective.While brain-machine interfaces (BMIs) are promising technologies that could provide direct pathways for controlling the external world and thus regaining motor capabilities, their effectiveness is hampered by decoding errors. Previous research has demonstrated the detection and correction of BMI outcome errors, which occur at the end of trials. Here we focus on continuous detection and correction of BMI execution errors, which occur during real-time movements.Approach.Two adult male rhesus macaques were implanted with Utah arrays in the motor cortex. The monkeys performed single or two-finger group BMI tasks where a Kalman filter decoded binned spiking-band power into intended finger kinematics. Neural activity was analyzed to determine how it depends not only on the kinematics of the fingers, but also on the distance of each finger-group to its target. We developed a method to detect erroneous movements, i.e. consistent movements away from the target, from the same neural activity used by the Kalman filter. Detected errors were corrected by a simple stopping strategy, and the effect on performance was evaluated.Mainresults.First we show that including distance to target explains significantly more variance of the recorded neural activity. Then, for the first time, we demonstrate that neural activity in motor cortex can be used to detect execution errors during BMI controlled movements. Keeping false positive rate below5%, it was possible to achieve mean true positive rate of28.1%online. Despite requiring 200 ms to detect and react to suspected errors, we were able to achieve a significant improvement in task performance via reduced orbiting time of one finger group.Significance.Neural activity recorded in motor cortex for BMI control can be used to detect and correct BMI errors and thus to improve performance. Further improvements may be obtained by enhancing classification and correction strategies.
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Affiliation(s)
- Dylan M Wallace
- Department of Robotics, University of Michigan, Ann Arbor, MI, United States of America
| | - Miri Benyamini
- BCI for Rehabilitation Lab., Faculty of Mechanical Engineering, Technion - Israel Institute of Technology, Haifa, Israel
| | - Samuel R Nason-Tomaszewski
- Cortical Neural Prosthetics Lab., Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, United States of America
| | - Joseph T Costello
- Department of Electrical and Computer Engineering, University of Michigan, Ann Arbor, MI, United States of America
| | - Luis H Cubillos
- Department of Robotics, University of Michigan, Ann Arbor, MI, United States of America
| | - Matthew J Mender
- Cortical Neural Prosthetics Lab., Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, United States of America
| | - Hisham Temmar
- Cortical Neural Prosthetics Lab., Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, United States of America
| | - Matthew S Willsey
- Cortical Neural Prosthetics Lab., Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, United States of America
- Department of Neurosurgery, University of Michigan, Ann Arbor, MI, United States of America
| | - Parag G Patil
- Cortical Neural Prosthetics Lab., Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, United States of America
- Department of Neurosurgery, University of Michigan, Ann Arbor, MI, United States of America
| | - Cynthia A Chestek
- Department of Robotics, University of Michigan, Ann Arbor, MI, United States of America
- Cortical Neural Prosthetics Lab., Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, United States of America
- Department of Electrical and Computer Engineering, University of Michigan, Ann Arbor, MI, United States of America
| | - Miriam Zacksenhouse
- BCI for Rehabilitation Lab., Faculty of Mechanical Engineering, Technion - Israel Institute of Technology, Haifa, Israel
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Benyamini M, Demchenko I, Zacksenhouse M. Error related EEG potentials evoked by visuo-motor rotations. Brain Res 2021; 1769:147606. [PMID: 34364850 DOI: 10.1016/j.brainres.2021.147606] [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: 10/05/2020] [Revised: 07/04/2021] [Accepted: 07/27/2021] [Indexed: 11/30/2022]
Abstract
Electroencephalographic (EEG) correlates of errors, known as error-related potentials (ErrPs), provide promising tools to investigate error processing in the brain and to detect and correct errors induced by brain-computer interfaces (BCIs). Visuo-motor rotation (VMR) is a well-known experimental paradigm to introduce visuo-motor errors that closely mimics directional errors induced by BCIs. However, investigations of ErrPs during VMR experiments are limited and reveals different ErrPs depending on task and synchronization. We conducted VMR experiments with 5 randomly selected conditions (no-rotation, small, ±22.5°, or large, ±45° rotations) to hamper adaptation and facilitate investigation of the effect of error size. We tracked eye movements so EEG was synchronized not only to onset of movement correction (OMC) but also to saccadic movement onset (SMO). Kinematic analysis indicated that maximum deviations from a straight line to the target were larger in trials with large rotations compared to small or no rotations, but there was a large overlap. Thus, we also compared ErrPs generated by trials with different maximum deviations. Our results reveal that trials with large rotations and especially trials with large maximum deviations evoke a significant positive ErrP component. The positive peak appeared 380 msec after SMO and 240 msec after OMC. Furthermore, the positive peak was associated with activity in Brodmann areas 5 and 7, in agreement with other studies and with the role of posterior parietal cortex in reaching movements. The observed ErrP may facilitate further investigation of error processing in the brain and error detection and correction in BCIs.
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Affiliation(s)
- Miri Benyamini
- Brain-Computer Interfaces for Rehabilitation Lab., Faculty of Mechanical Engineering, Technion, Israel.
| | - Igor Demchenko
- Brain-Computer Interfaces for Rehabilitation Lab., Faculty of Mechanical Engineering, Technion, Israel.
| | - Miriam Zacksenhouse
- Brain-Computer Interfaces for Rehabilitation Lab., Faculty of Mechanical Engineering, Technion, Israel; Technion Autonomous Systems Program, Technion, Israel.
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