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Guo Z, Lin JP, Simeone O, Mills KR, Cvetkovic Z, McClelland VM. Cross-frequency cortex-muscle interactions are abnormal in young people with dystonia. Brain Commun 2024; 6:fcae061. [PMID: 38487552 PMCID: PMC10939448 DOI: 10.1093/braincomms/fcae061] [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: 07/18/2023] [Revised: 01/10/2024] [Accepted: 02/23/2024] [Indexed: 03/17/2024] Open
Abstract
Sensory processing and sensorimotor integration are abnormal in dystonia, including impaired modulation of beta-corticomuscular coherence. However, cortex-muscle interactions in either direction are rarely described, with reports limited predominantly to investigation of linear coupling, using corticomuscular coherence or Granger causality. Information-theoretic tools such as transfer entropy detect both linear and non-linear interactions between processes. This observational case-control study applies transfer entropy to determine intra- and cross-frequency cortex-muscle coupling in young people with dystonia/dystonic cerebral palsy. Fifteen children with dystonia/dystonic cerebral palsy and 13 controls, aged 12-18 years, performed a grasp task with their dominant hand. Mechanical perturbations were provided by an electromechanical tapper. Bipolar scalp EEG over contralateral sensorimotor cortex and surface EMG over first dorsal interosseous were recorded. Multi-scale wavelet transfer entropy was applied to decompose signals into functional frequency bands of oscillatory activity and to quantify intra- and cross-frequency coupling between brain and muscle. Statistical significance against the null hypothesis of zero transfer entropy was established, setting individual 95% confidence thresholds. The proportion of individuals in each group showing significant transfer entropy for each frequency combination/direction was compared using Fisher's exact test, correcting for multiple comparisons. Intra-frequency transfer entropy was detected in all participants bidirectionally in the beta (16-32 Hz) range and in most participants from EEG to EMG in the alpha (8-16 Hz) range. Cross-frequency transfer entropy across multiple frequency bands was largely similar between groups, but a specific coupling from low-frequency EMG to beta EEG was significantly reduced in dystonia [P = 0.0061 (corrected)]. The demonstration of bidirectional cortex-muscle communication in dystonia emphasizes the value of transfer entropy for exploring neural communications in neurological disorders. The novel finding of diminished coupling from low-frequency EMG to beta EEG in dystonia suggests impaired cortical feedback of proprioceptive information with a specific frequency signature that could be relevant to the origin of the excessive low-frequency drive to muscle.
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Affiliation(s)
- Zhenghao Guo
- Department of Engineering, King's College London, London WC2R 2LS, UK
- School of Biomedical Engineering, Dalian University of Technology, Dalian 116024, China
| | - Jean-Pierre Lin
- Children's Neuroscience, Evelina London Children's Hospital, Guy's & St Thomas' NHS Foundation Trust (GSTT), London SE1 7EH, UK
| | - Osvaldo Simeone
- Department of Engineering, King's College London, London WC2R 2LS, UK
| | - Kerry R Mills
- Department of Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London, London SE5 9RX, UK
| | - Zoran Cvetkovic
- Department of Engineering, King's College London, London WC2R 2LS, UK
| | - Verity M McClelland
- Children's Neuroscience, Evelina London Children's Hospital, Guy's & St Thomas' NHS Foundation Trust (GSTT), London SE1 7EH, UK
- Department of Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London, London SE5 9RX, UK
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Beauchamp JA, Hassan AS, McPherson LM, Negro F, Pearcey GEP, Cummings M, Heckman CJ, Dewald JPA. Motor unit firing rate modulation is more impaired during flexion synergy-driven contractions of the biceps brachii in chronic stroke. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.11.22.23298905. [PMID: 38045404 PMCID: PMC10690344 DOI: 10.1101/2023.11.22.23298905] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/05/2023]
Abstract
Following a hemiparetic stroke, individuals exhibit altered motor unit firing patterns during voluntary muscle contractions, including impairments in firing rate modulation and recruitment. These individuals also exhibit abnormal muscle coactivation through multi-joint synergies (e.g., flexion synergy). Here, we investigate whether motor unit firing activity during flexion synergy-driven contractions of the paretic biceps brachii differs from that of voluntary contractions and use these differences to predict changes in descending motor commands. To accomplish this, we characterized motor unit firing patterns of the biceps brachii in individuals with chronic hemiparetic stroke during voluntary isometric elbow flexion contractions in the paretic and non-paretic limbs, as well as during contractions driven by voluntary effort and by flexion synergy expression in the paretic limb. We observed significant reductions in motor unit firing rate modulation from the non-paretic to paretic limb (non-paretic - paretic: 0.14 pps/%MVT, 95% CI: [0.09 0.19]) that were further reduced during synergy-driven contractions (voluntary paretic - synergy driven: 0.19 pps/%MVT, 95% CI: [0.14 0.25]). Moreover, using recently developed metrics, we evaluated how a stroke-induced reliance on indirect motor pathways alters the inputs that motor units receive and revealed progressive increases in neuromodulatory and inhibitory drive to the motor pool in the paretic limb, with the changes greatest during synergy-driven contractions. These findings suggest that an interplay between heightened neuromodulatory drive and alterations in inhibitory command structure may account for the observed motor unit impairments, further illuminating underlying neural mechanisms involved in the flexion synergy and its impact on motor unit firing patterns post-stroke.
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Cortical Reorganization of Early Somatosensory Processing in Hemiparetic Stroke. J Clin Med 2022; 11:jcm11216449. [PMID: 36362680 PMCID: PMC9654771 DOI: 10.3390/jcm11216449] [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: 09/23/2022] [Revised: 10/27/2022] [Accepted: 10/29/2022] [Indexed: 11/06/2022] Open
Abstract
The cortical motor system can be reorganized following a stroke, with increased recruitment of the contralesional hemisphere. However, it is unknown whether a similar hemispheric shift occurs in the somatosensory system to adapt to this motor change, and whether this is related to movement impairments. This proof-of-concept study assessed somatosensory evoked potentials (SEPs), P50 and N100, in hemiparetic stroke participants and age-matched controls using high-density electroencephalograph (EEG) recordings during tactile finger stimulation. The laterality index was calculated to determine the hemispheric dominance of the SEP and re-confirmed with source localization. The study found that latencies of P50 and N100 were significantly delayed in stroke brains when stimulating the paretic hand. The amplitude of P50 in the contralateral (to stimulated hand) hemisphere was negatively correlated with the Fügl-Meyer upper extremity motor score in stroke. Bilateral cortical responses were detected in stroke, while only contralateral cortical responses were shown in controls, resulting in a significant difference in the laterality index. These results suggested that somatosensory reorganization after stroke involves increased recruitment of ipsilateral cortical regions, especially for the N100 SEP component. This reorganization delays the latency of somatosensory processing after a stroke. This research provided new insights related to the somatosensory reorganization after stroke, which could enrich future hypothesis-driven therapeutic rehabilitation strategies from a sensory or sensory-motor perspective.
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Tian R, Dewald JPA, Yang Y. Assessing the Usage of Indirect Motor Pathways Following a Hemiparetic Stroke. IEEE Trans Neural Syst Rehabil Eng 2021; 29:1568-1572. [PMID: 34343095 PMCID: PMC8372540 DOI: 10.1109/tnsre.2021.3102493] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
A hallmark impairment in a hemiparetic stroke is a loss of independent joint control resulting in abnormal co-activation of shoulder abductor and elbow flexor muscles in their paretic arm, clinically known as the flexion synergy. The flexion synergy appears while generating shoulder abduction (SABD) torques as lifting the paretic arm. This likely be caused by an increased reliance on contralesional indirect motor pathways following damage to direct corticospinal projections. The assessment of functional connectivity between brain and muscle signals, i.e., brain-muscle connectivity (BMC), may provide insight into such changes to the usage of motor pathways. Our previous model simulation shows that multi-synaptic connections along the indirect motor pathway can generate nonlinear connectivity. We hypothesize that increased usage of indirect motor pathways (as increasing SABD load) will lead to an increase of nonlinear BMC. To test this hypothesis, we measured brain activity, muscle activity from shoulder abductors when stroke participants generate 20% and 40% of maximum SABD torque with their paretic arm. We computed both linear and nonlinear BMC between EEG and EMG. We found dominant nonlinear BMC at contralesional/ipsilateral hemisphere for stroke, whose magnitude increased with the SABD load. These results supported our hypothesis and indicated that nonlinear BMC could provide a quantitative indicator for determining the usage of indirect motor pathways following a hemiparetic stroke.
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He F, Yang Y. Nonlinear System Identification of Neural Systems from Neurophysiological Signals. Neuroscience 2021; 458:213-228. [PMID: 33309967 PMCID: PMC7925423 DOI: 10.1016/j.neuroscience.2020.12.001] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2020] [Revised: 11/30/2020] [Accepted: 12/01/2020] [Indexed: 12/20/2022]
Abstract
The human nervous system is one of the most complicated systems in nature. Complex nonlinear behaviours have been shown from the single neuron level to the system level. For decades, linear connectivity analysis methods, such as correlation, coherence and Granger causality, have been extensively used to assess the neural connectivities and input-output interconnections in neural systems. Recent studies indicate that these linear methods can only capture a certain amount of neural activities and functional relationships, and therefore cannot describe neural behaviours in a precise or complete way. In this review, we highlight recent advances in nonlinear system identification of neural systems, corresponding time and frequency domain analysis, and novel neural connectivity measures based on nonlinear system identification techniques. We argue that nonlinear modelling and analysis are necessary to study neuronal processing and signal transfer in neural systems quantitatively. These approaches can hopefully provide new insights to advance our understanding of neurophysiological mechanisms underlying neural functions. These nonlinear approaches also have the potential to produce sensitive biomarkers to facilitate the development of precision diagnostic tools for evaluating neurological disorders and the effects of targeted intervention.
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Affiliation(s)
- Fei He
- Centre for Data Science, Coventry University, Coventry CV1 2JH, UK
| | - Yuan Yang
- Stephenson School of Biomedical Engineering, The University of Oklahoma, Tulsa, OK 74135, USA; Department of Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA; Laureate Institute for Brain Research, Tulsa, OK 74136, USA
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Tian R, Dewald JPA, Sinha N, Yang Y. Assessing Neural Connectivity and Associated Time Delays of Muscle Responses to Continuous Position Perturbations. Ann Biomed Eng 2020; 49:432-440. [PMID: 32705425 DOI: 10.1007/s10439-020-02573-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2020] [Accepted: 07/14/2020] [Indexed: 12/25/2022]
Abstract
Both linear and nonlinear electromyographic (EMG) connectivity has been reported during the expression of stretch reflexes, though it is not clear whether they are generated by the same neural pathways. To answer this question, we aim to distinguish linear and nonlinear connectivity, as well as their delays in muscle responses, resulting from continuous elbow joint perturbations. We recorded EMG from Biceps Brachii muscle when eight able-bodied participants were performing a steady elbow flexion torque while simultaneously receiving a continuous position perturbation. Using a recently developed phase coupling metric, we estimated linear and nonlinear connectivity as well as their associated delays between Biceps EMG responses and perturbations. We found that the time delay for linear connectivity (24.5 ± 5.4 ms) is in the range of short-latency stretch reflex period (< 35 ms), while that for nonlinear connectivity (53.8 ± 3.2 ms) is in the range of long-latency stretch reflex period (40-70 ms). These results suggest that the estimated linear connectivity between EMG and perturbations is very likely generated by the mono-synaptic spinal stretch reflex loop, while the nonlinear connectivity may be associated with multi-synaptic supraspinal stretch reflex loops. As such, this study provides new evidence of the nature of neural connectivity related to the stretch reflex.
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Affiliation(s)
- Runfeng Tian
- Department of Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, 645 N Michigan Avenue, Suite 1100, Chicago, IL, 60611, USA.,Stephenson School of Biomedical Engineering, The University of Oklahoma, Tulsa, OK, USA
| | - Julius P A Dewald
- Department of Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, 645 N Michigan Avenue, Suite 1100, Chicago, IL, 60611, USA.,Department of Biomedical Engineering, McCormick School of Engineering, Northwestern University, Evanston, IL, USA
| | - Nirvik Sinha
- Department of Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, 645 N Michigan Avenue, Suite 1100, Chicago, IL, 60611, USA
| | - Yuan Yang
- Department of Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, 645 N Michigan Avenue, Suite 1100, Chicago, IL, 60611, USA. .,Stephenson School of Biomedical Engineering, The University of Oklahoma, Tulsa, OK, USA.
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