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Lin HP, Xu Y, Zhang X, Woolley D, Zhao L, Liang W, Huang M, Cheng HJ, Zhang L, Wenderoth N. A usability study on mobile EMG-guided wrist extension training in subacute stroke patients-MyoGuide. J Neuroeng Rehabil 2024; 21:39. [PMID: 38515192 PMCID: PMC10956308 DOI: 10.1186/s12984-024-01334-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2023] [Accepted: 03/07/2024] [Indexed: 03/23/2024] Open
Abstract
BACKGROUND Effective stroke rehabilitation requires high-dose, repetitive-task training, especially during the early recovery phase. However, the usability of upper-limb rehabilitation technology in acute and subacute stroke survivors remains relatively unexplored. In this study, we introduce subacute stroke survivors to MyoGuide, a mobile training platform that employs surface electromyography (sEMG)-guided neurofeedback training that specifically targets wrist extension. Notably, the study emphasizes evaluating the platform's usability within clinical contexts. METHODS Seven subacute post-stroke patients (1 female, mean age 53.7 years, mean time post-stroke 58.9 days, mean duration per training session 48.9 min) and three therapists (one for eligibility screening, two for conducting training) participated in the study. Participants underwent ten days of supervised one-on-one wrist extension training with MyoGuide, which encompassed calibration, stability assessment, and dynamic tasks. All training records including the Level of Difficulty (LoD) and Stability Assessment Scores were recorded within the application. Usability was assessed through the System Usability Scale (SUS) and participants' willingness to continue home-based training was gauged through a self-developed survey post-training. Therapists also documented the daily performance of participants and the extent of support required. RESULTS The usability analysis yielded positive results, with a median SUS score of 82.5. Compared to the first session, participants significantly improved their performance at the final session as indicated by both the Stability Assessment Scores (p = 0.010, mean = 229.43, CI = [25.74-433.11]) and the LoD (p < 0.001; mean: 45.43, CI: [25.56-65.29]). The rate of progression differed based on the initial impairment levels of the patient. After training, participants expressed a keen interest in continuing home-based training. However, they also acknowledged challenges related to independently using the Myo armband and software. CONCLUSIONS This study introduces the MyoGuide training platform and demonstrates its usability in a clinical setting for stroke rehabilitation, with the assistance of a therapist. The findings support the potential of MyoGuide for wrist extension training in patients across a wide range of impairment levels. However, certain usability challenges, such as donning/doffing the armband and navigating the application, need to be addressed to enable independent MyoGuide training requiring only minimal supervision by a therapist.
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Affiliation(s)
- Hao-Ping Lin
- Singapore-ETH Centre, Future Health Technologies Programme, CREATE campus, 1 Create Way, CREATE Tower, #06-01, Singapore, 138602, Singapore
| | - Yang Xu
- Department of Rehabilitation, Shengjing Hospital of China Medical University, 16 Puhe Road, Shenyang, Liaoning, 110134, China
| | - Xue Zhang
- Department of Health Sciences and Technology, Neural Control of Movement Lab, ETH Zurich, Gloriastrasse 37/39 GLC G17.2, Zurich, 8092, Switzerland
| | - Daniel Woolley
- Department of Health Sciences and Technology, Neural Control of Movement Lab, ETH Zurich, Gloriastrasse 37/39 GLC G17.2, Zurich, 8092, Switzerland
| | - Lina Zhao
- Department of Rehabilitation, Shengjing Hospital of China Medical University, 16 Puhe Road, Shenyang, Liaoning, 110134, China
| | - Weidi Liang
- Department of Rehabilitation, Shengjing Hospital of China Medical University, 16 Puhe Road, Shenyang, Liaoning, 110134, China
| | - Mengdi Huang
- Department of Rehabilitation, Shengjing Hospital of China Medical University, 16 Puhe Road, Shenyang, Liaoning, 110134, China
| | - Hsiao-Ju Cheng
- Singapore-ETH Centre, Future Health Technologies Programme, CREATE campus, 1 Create Way, CREATE Tower, #06-01, Singapore, 138602, Singapore
| | - Lixin Zhang
- Department of Rehabilitation, Shengjing Hospital of China Medical University, 16 Puhe Road, Shenyang, Liaoning, 110134, China
| | - Nicole Wenderoth
- Singapore-ETH Centre, Future Health Technologies Programme, CREATE campus, 1 Create Way, CREATE Tower, #06-01, Singapore, 138602, Singapore.
- Department of Health Sciences and Technology, Neural Control of Movement Lab, ETH Zurich, Gloriastrasse 37/39 GLC G17.2, Zurich, 8092, Switzerland.
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Meissner SN, Bächinger M, Kikkert S, Imhof J, Missura S, Carro Dominguez M, Wenderoth N. Self-regulating arousal via pupil-based biofeedback. Nat Hum Behav 2024; 8:43-62. [PMID: 37904022 PMCID: PMC10810759 DOI: 10.1038/s41562-023-01729-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Accepted: 09/20/2023] [Indexed: 11/01/2023]
Abstract
The brain's arousal state is controlled by several neuromodulatory nuclei known to substantially influence cognition and mental well-being. Here we investigate whether human participants can gain volitional control of their arousal state using a pupil-based biofeedback approach. Our approach inverts a mechanism suggested by previous literature that links activity of the locus coeruleus, one of the key regulators of central arousal and pupil dynamics. We show that pupil-based biofeedback enables participants to acquire volitional control of pupil size. Applying pupil self-regulation systematically modulates activity of the locus coeruleus and other brainstem structures involved in arousal control. Furthermore, it modulates cardiovascular measures such as heart rate, and behavioural and psychophysiological responses during an oddball task. We provide evidence that pupil-based biofeedback makes the brain's arousal system accessible to volitional control, a finding that has tremendous potential for translation to behavioural and clinical applications across various domains, including stress-related and anxiety disorders.
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Affiliation(s)
- Sarah Nadine Meissner
- Neural Control of Movement Laboratory, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland.
| | - Marc Bächinger
- Neural Control of Movement Laboratory, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
| | - Sanne Kikkert
- Neural Control of Movement Laboratory, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
- Neuroscience Center Zurich, University and ETH Zurich, Zurich, Switzerland
- Spinal Cord Injury Center, Balgrist University Hospital, University of Zurich, Zurich, Switzerland
| | - Jenny Imhof
- Neural Control of Movement Laboratory, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
- Neuroscience Center Zurich, University and ETH Zurich, Zurich, Switzerland
| | - Silvia Missura
- Neural Control of Movement Laboratory, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
| | - Manuel Carro Dominguez
- Neural Control of Movement Laboratory, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
- Neuroscience Center Zurich, University and ETH Zurich, Zurich, Switzerland
| | - Nicole Wenderoth
- Neural Control of Movement Laboratory, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland.
- Neuroscience Center Zurich, University and ETH Zurich, Zurich, Switzerland.
- Future Health Technologies, Singapore-ETH Centre, Campus for Research Excellence and Technological Enterprise (CREATE), Singapore, Singapore.
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Cheng HJ, Chin LF, Kanzler CM, Lehner R, Kuah CWK, Kager S, Josse E, Samkharadze T, Sidarta A, Gonzalez PC, Lie E, Zbytniewska-Mégret M, Wee SK, Liang P, Gassert R, Chua K, Lambercy O, Wenderoth N. Upper limb sensorimotor recovery in Asian stroke survivors: a study protocol for the development and implementation of a Technology-Assisted dIgitaL biOmaRker (TAILOR) platform. Front Neurol 2023; 14:1246888. [PMID: 38107648 PMCID: PMC10722087 DOI: 10.3389/fneur.2023.1246888] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2023] [Accepted: 11/06/2023] [Indexed: 12/19/2023] Open
Abstract
Background Stroke is a leading cause of lifelong disability worldwide, partially driven by a reduced ability to use the upper limb in daily life causing increased dependence on caregivers. However, post-stroke functional impairments have only been investigated using limited clinical scores, during short-term longitudinal studies in relatively small patient cohorts. With the addition of technology-based assessments, we propose to complement clinical assessments with more sensitive and objective measures that could more holistically inform on upper limb impairment recovery after stroke, its impact on upper limb use in daily life, and on overall quality of life. This paper describes a pragmatic, longitudinal, observational study protocol aiming to gather a uniquely rich multimodal database to comprehensively describe the time course of upper limb recovery in a representative cohort of 400 Asian adults after stroke. Particularly, we will characterize the longitudinal relationship between upper limb recovery, common post-stroke impairments, functional independence and quality of life. Methods Participants with stroke will be tested at up to eight time points, from within a month to 3 years post-stroke, to capture the influence of transitioning from hospital to community settings. We will perform a battery of established clinical assessments to describe the factors most likely to influence upper limb recovery. Further, we will gather digital health biomarkers from robotic or wearable sensing technology-assisted assessments to sensitively characterize motor and somatosensory impairments and upper limb use in daily life. We will also use both quantitative and qualitative measures to understand health-related quality of life. Lastly, we will describe neurophysiological motor status using transcranial magnetic stimulation. Statistics Descriptive analyses will be first performed to understand post-stroke upper limb impairments and recovery at various time points. The relationships between digital biomarkers and various domains will be explored to inform key aspects of upper limb recovery and its dynamics using correlation matrices. Multiple statistical models will be constructed to characterize the time course of upper limb recovery post-stroke. Subgroups of stroke survivors exhibiting distinct recovery profiles will be identified. Conclusion This is the first study complementing clinical assessments with technology-assisted digital biomarkers to investigate upper limb sensorimotor recovery in Asian stroke survivors. Overall, this study will yield a multimodal data set that longitudinally characterizes post-stroke upper limb recovery in functional impairments, daily-life upper limb use, and health-related quality of life in a large cohort of Asian stroke survivors. This data set generates valuable information on post-stroke upper limb recovery and potentially allows researchers to identify different recovery profiles of subgroups of Asian stroke survivors. This enables the comparisons between the characteristics and recovery profiles of stroke survivors in different regions. Thus, this study lays out the basis to identify early predictors for upper limb recovery, inform clinical decision-making in Asian stroke survivors and establish tailored therapy programs. Clinical trial registration ClinicalTrials.gov, identifier: NCT05322837.
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Affiliation(s)
- Hsiao-Ju Cheng
- Singapore-ETH Centre, Future Health Technologies Programme, CREATE Campus, Singapore, Singapore
| | - Lay Fong Chin
- Singapore-ETH Centre, Future Health Technologies Programme, CREATE Campus, Singapore, Singapore
- Institute of Rehabilitation Excellence (IREx), Tan Tock Seng Hospital Rehabilitation Centre, Singapore, Singapore
| | - Christoph M Kanzler
- Singapore-ETH Centre, Future Health Technologies Programme, CREATE Campus, Singapore, Singapore
- Rehabilitation Engineering Laboratory, Department of Health Sciences and Technology, ETH Zürich, Zürich, Switzerland
| | - Rea Lehner
- Singapore-ETH Centre, Future Health Technologies Programme, CREATE Campus, Singapore, Singapore
| | - Christopher W K Kuah
- Singapore-ETH Centre, Future Health Technologies Programme, CREATE Campus, Singapore, Singapore
- Institute of Rehabilitation Excellence (IREx), Tan Tock Seng Hospital Rehabilitation Centre, Singapore, Singapore
- Rehabilitation Research Institute of Singapore, Nanyang Technological University, Singapore, Singapore
| | - Simone Kager
- Singapore-ETH Centre, Future Health Technologies Programme, CREATE Campus, Singapore, Singapore
- Rehabilitation Engineering Laboratory, Department of Health Sciences and Technology, ETH Zürich, Zürich, Switzerland
| | - Eva Josse
- Singapore-ETH Centre, Future Health Technologies Programme, CREATE Campus, Singapore, Singapore
- Rehabilitation Engineering Laboratory, Department of Health Sciences and Technology, ETH Zürich, Zürich, Switzerland
| | - Tengiz Samkharadze
- Singapore-ETH Centre, Future Health Technologies Programme, CREATE Campus, Singapore, Singapore
| | - Ananda Sidarta
- Rehabilitation Research Institute of Singapore, Nanyang Technological University, Singapore, Singapore
| | - Pablo Cruz Gonzalez
- Rehabilitation Research Institute of Singapore, Nanyang Technological University, Singapore, Singapore
| | - Eloise Lie
- Rehabilitation Research Institute of Singapore, Nanyang Technological University, Singapore, Singapore
| | - Monika Zbytniewska-Mégret
- Rehabilitation Engineering Laboratory, Department of Health Sciences and Technology, ETH Zürich, Zürich, Switzerland
| | - Seng Kwee Wee
- Singapore-ETH Centre, Future Health Technologies Programme, CREATE Campus, Singapore, Singapore
- Institute of Rehabilitation Excellence (IREx), Tan Tock Seng Hospital Rehabilitation Centre, Singapore, Singapore
- Rehabilitation Research Institute of Singapore, Nanyang Technological University, Singapore, Singapore
- Singapore Institute of Technology (SIT), Singapore, Singapore
| | - Phyllis Liang
- Singapore-ETH Centre, Future Health Technologies Programme, CREATE Campus, Singapore, Singapore
- Rehabilitation Research Institute of Singapore, Nanyang Technological University, Singapore, Singapore
| | - Roger Gassert
- Singapore-ETH Centre, Future Health Technologies Programme, CREATE Campus, Singapore, Singapore
- Rehabilitation Engineering Laboratory, Department of Health Sciences and Technology, ETH Zürich, Zürich, Switzerland
| | - Karen Chua
- Singapore-ETH Centre, Future Health Technologies Programme, CREATE Campus, Singapore, Singapore
- Institute of Rehabilitation Excellence (IREx), Tan Tock Seng Hospital Rehabilitation Centre, Singapore, Singapore
- Rehabilitation Research Institute of Singapore, Nanyang Technological University, Singapore, Singapore
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
| | - Olivier Lambercy
- Singapore-ETH Centre, Future Health Technologies Programme, CREATE Campus, Singapore, Singapore
- Rehabilitation Engineering Laboratory, Department of Health Sciences and Technology, ETH Zürich, Zürich, Switzerland
| | - Nicole Wenderoth
- Singapore-ETH Centre, Future Health Technologies Programme, CREATE Campus, Singapore, Singapore
- Neural Control of Movement Laboratory, Department of Health Sciences and Technology, ETH Zürich, Zürich, Switzerland
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Altermatt M, Thomas FA, Wenderoth N. Movement predictability modulates sensorimotor processing. Front Hum Neurosci 2023; 17:1237407. [PMID: 38053650 PMCID: PMC10694232 DOI: 10.3389/fnhum.2023.1237407] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Accepted: 10/30/2023] [Indexed: 12/07/2023] Open
Abstract
Introduction An important factor for optimal sensorimotor control is how well we are able to predict sensory feedback from internal and external sources during movement. If predictability decreases due to external disturbances, the brain is able to adjust muscle activation and the filtering of incoming sensory inputs. However, little is known about sensorimotor adjustments when predictability is increased by availability of additional internal feedback. In the present study we investigated how modifications of internal and external sensory feedback influence the control of muscle activation and gating of sensory input. Methods Co-activation of forearm muscles, somatosensory evoked potentials (SEP) and short afferent inhibition (SAI) were assessed during three object manipulation tasks designed to differ in the predictability of sensory feedback. These included manipulation of a shared object with both hands (predictable coupling), manipulation of two independent objects without (uncoupled) and with external interference on one of the objects (unpredictable coupling). Results We found a task-specific reduction in co-activation during the predictable coupling compared to the other tasks. Less sensory gating, reflected in larger subcortical SEP amplitudes, was observed in the unpredictable coupling task. SAI behavior was closely linked to the subcortical SEP component indicating an important function of subcortical sites in predictability related SEP gating and their direct influence on M1 inhibition. Discussion Together, these findings suggest that the unpredictable coupling task cannot only rely on predictive forward control and is compensated by enhancing co-activation and increasing the saliency for external stimuli by reducing sensory gating at subcortical level. This behavior might serve as a preparatory step to compensate for external disturbances and to enhance processing and integration of all incoming external stimuli to update the current sensorimotor state. In contrast, predictive forward control is accurate in the predictable coupling task due to the integrated sensory feedback from both hands where sensorimotor resources are economized by reducing muscular co-activation and increasing sensory gating.
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Huwiler S, Carro-Domínguez M, Stich FM, Sala R, Aziri F, Trippel A, Ryf T, Markendorf S, Niederseer D, Bohm P, Stoll G, Laubscher L, Thevan J, Spengler CM, Gawinecka J, Osto E, Huber R, Wenderoth N, Schmied C, Lustenberger C. Auditory stimulation of sleep slow waves enhances left ventricular function in humans. Eur Heart J 2023; 44:4288-4291. [PMID: 37794725 PMCID: PMC10590124 DOI: 10.1093/eurheartj/ehad630] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/06/2023] Open
Affiliation(s)
- Stephanie Huwiler
- Neural Control of Movement Lab, Institute of Human Movement Sciences and Sport, Department of Health Sciences and Technology, ETH Zurich, Zurich 8092, Switzerland
| | - Manuel Carro-Domínguez
- Neural Control of Movement Lab, Institute of Human Movement Sciences and Sport, Department of Health Sciences and Technology, ETH Zurich, Zurich 8092, Switzerland
| | - Fabia M Stich
- Neural Control of Movement Lab, Institute of Human Movement Sciences and Sport, Department of Health Sciences and Technology, ETH Zurich, Zurich 8092, Switzerland
| | - Rossella Sala
- Neural Control of Movement Lab, Institute of Human Movement Sciences and Sport, Department of Health Sciences and Technology, ETH Zurich, Zurich 8092, Switzerland
| | - Florent Aziri
- Neural Control of Movement Lab, Institute of Human Movement Sciences and Sport, Department of Health Sciences and Technology, ETH Zurich, Zurich 8092, Switzerland
| | - Anna Trippel
- Neural Control of Movement Lab, Institute of Human Movement Sciences and Sport, Department of Health Sciences and Technology, ETH Zurich, Zurich 8092, Switzerland
| | - Tabea Ryf
- Department of Cardiology, University Heart Center Zurich, University of Zurich, Zurich 8091, Switzerland
| | - Susanne Markendorf
- Department of Cardiology, University Heart Center Zurich, University of Zurich, Zurich 8091, Switzerland
| | - David Niederseer
- Department of Cardiology, University Heart Center Zurich, University of Zurich, Zurich 8091, Switzerland
| | - Philipp Bohm
- Department of Cardiology, University Heart Center Zurich, University of Zurich, Zurich 8091, Switzerland
| | - Gloria Stoll
- Neural Control of Movement Lab, Institute of Human Movement Sciences and Sport, Department of Health Sciences and Technology, ETH Zurich, Zurich 8092, Switzerland
| | - Lily Laubscher
- Neural Control of Movement Lab, Institute of Human Movement Sciences and Sport, Department of Health Sciences and Technology, ETH Zurich, Zurich 8092, Switzerland
| | - Jeivicaa Thevan
- Institute of Clinical Chemistry, University Hospital Zurich, University of Zurich, Zurich 8091, Switzerland
| | - Christina M Spengler
- Exercise Physiology Lab, Institute of Human Movement Sciences and Sport, Department of Health Sciences and Technology, ETH Zurich, Zurich 8092, Switzerland
- Zurich Center for Integrative Human Physiology (ZIHP), University of Zurich, Zurich 8057, Switzerland
| | - Joanna Gawinecka
- Institute of Clinical Chemistry, University Hospital Zurich, University of Zurich, Zurich 8091, Switzerland
| | - Elena Osto
- Institute of Clinical Chemistry, University Hospital Zurich, University of Zurich, Zurich 8091, Switzerland
| | - Reto Huber
- Center of Competence Sleep & Health Zurich, University of Zurich, Zurich 8006, Switzerland
- Neuroscience Center Zurich (ZNZ), University of Zurich, ETH Zurich, Zurich 8057, Switzerland
- Child Development Centre, University Children’s Hospital, University of Zurich, Zurich 8032, Switzerland
- Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric Hospital Zurich, University of Zurich, Zurich 8032, Switzerland
| | - Nicole Wenderoth
- Neural Control of Movement Lab, Institute of Human Movement Sciences and Sport, Department of Health Sciences and Technology, ETH Zurich, Zurich 8092, Switzerland
- Neuroscience Center Zurich (ZNZ), University of Zurich, ETH Zurich, Zurich 8057, Switzerland
- Future Health Technologies, Singapore-ETH Center, Campus for Research Excellence and Technological Enterprise (CREATE), Singapore 138602, Singapore
| | - Christian Schmied
- Department of Cardiology, University Heart Center Zurich, University of Zurich, Zurich 8091, Switzerland
| | - Caroline Lustenberger
- Neural Control of Movement Lab, Institute of Human Movement Sciences and Sport, Department of Health Sciences and Technology, ETH Zurich, Zurich 8092, Switzerland
- Center of Competence Sleep & Health Zurich, University of Zurich, Zurich 8006, Switzerland
- Neuroscience Center Zurich (ZNZ), University of Zurich, ETH Zurich, Zurich 8057, Switzerland
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Markicevic M, Sturman O, Bohacek J, Rudin M, Zerbi V, Fulcher BD, Wenderoth N. Neuromodulation of striatal D1 cells shapes BOLD fluctuations in anatomically connected thalamic and cortical regions. eLife 2023; 12:e78620. [PMID: 37824184 PMCID: PMC10569790 DOI: 10.7554/elife.78620] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Accepted: 09/21/2023] [Indexed: 10/13/2023] Open
Abstract
Understanding how the brain's macroscale dynamics are shaped by underlying microscale mechanisms is a key problem in neuroscience. In animal models, we can now investigate this relationship in unprecedented detail by directly manipulating cellular-level properties while measuring the whole-brain response using resting-state fMRI. Here, we focused on understanding how blood-oxygen-level-dependent (BOLD) dynamics, measured within a structurally well-defined striato-thalamo-cortical circuit in mice, are shaped by chemogenetically exciting or inhibiting D1 medium spiny neurons (MSNs) of the right dorsomedial caudate putamen (CPdm). We characterize changes in both the BOLD dynamics of individual cortical and subcortical brain areas, and patterns of inter-regional coupling (functional connectivity) between pairs of areas. Using a classification approach based on a large and diverse set of time-series properties, we found that CPdm neuromodulation alters BOLD dynamics within thalamic subregions that project back to dorsomedial striatum. In the cortex, changes in local dynamics were strongest in unimodal regions (which process information from a single sensory modality) and weakened along a hierarchical gradient towards transmodal regions. In contrast, a decrease in functional connectivity was observed only for cortico-striatal connections after D1 excitation. Our results show that targeted cellular-level manipulations affect local BOLD dynamics at the macroscale, such as by making BOLD dynamics more predictable over time by increasing its self-correlation structure. This contributes to ongoing attempts to understand the influence of structure-function relationships in shaping inter-regional communication at subcortical and cortical levels.
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Affiliation(s)
- Marija Markicevic
- Neural Control of Movement Lab, HEST, ETH ZürichZurichSwitzerland
- Neuroscience Center Zurich, University and ETH ZurichZurichSwitzerland
- Department of Radiology and Biomedical Imaging, School of Medicine, Yale UniversityNew HavenUnited States
| | - Oliver Sturman
- Neuroscience Center Zurich, University and ETH ZurichZurichSwitzerland
- Laboratory of Molecular and Behavioral Neuroscience, Institute for Neuroscience, HEST, ETH ZurichZurichSwitzerland
| | - Johannes Bohacek
- Neuroscience Center Zurich, University and ETH ZurichZurichSwitzerland
- Laboratory of Molecular and Behavioral Neuroscience, Institute for Neuroscience, HEST, ETH ZurichZurichSwitzerland
| | - Markus Rudin
- Institute of Pharmacology and Toxicology, University of ZurichZurichSwitzerland
- Institute for Biomedical Engineering, University and ETH ZurichZurichSwitzerland
| | - Valerio Zerbi
- Neuro-X Institute, School of Engineering (STI), EPFLLausanneSwitzerland
- CIBM Centre for Biomedical ImagingLausanneSwitzerland
| | - Ben D Fulcher
- School of Physics, The University of SydneyCamperdownAustralia
| | - Nicole Wenderoth
- Neural Control of Movement Lab, HEST, ETH ZürichZurichSwitzerland
- Neuroscience Center Zurich, University and ETH ZurichZurichSwitzerland
- Future Health Technologies, Singapore-ETH Centre, Campus for Research Excellence and Technological Enterprise (CREATE)SingaporeSingapore
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Rabe F, Kikkert S, Wenderoth N. Performing a vibrotactile discrimination task modulates finger representations in primary somatosensory cortex. J Neurophysiol 2023; 130:1015-1027. [PMID: 37671429 PMCID: PMC10649835 DOI: 10.1152/jn.00428.2022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Revised: 08/29/2023] [Accepted: 08/31/2023] [Indexed: 09/07/2023] Open
Abstract
It is well established that vibrotactile stimuli are represented in somatotopic maps. However, less is known about whether these somatotopic representations are modulated by task demands and maybe even in the absence of tactile input. Here, we used a vibrotactile discrimination task as a tool to investigate these questions in further detail. Participants were required to actively perceive and process tactile stimuli in comparison to a no-task control condition where identical stimuli were passively perceived (no-memory condition). Importantly, both vibrotactile stimuli were either applied to the right index or little finger, allowing us to investigate whether cognitive task demands shape finger representations in primary somatosensory cortex (S1). Using multivoxel pattern analysis and representational similarity analysis, we found that S1 finger representations were more distinct during the memory than the no-memory condition. Interestingly, this effect was not only observed while tactile stimuli were presented but also during the delay period (i.e., in the absence of tactile stimulation). Our findings imply that when individuals are required to focus on tactile stimuli, retain them in their memory, and engage in active processing of distinctive stimulus features, this exerts a modulatory effect on the finger representations present in S1.NEW & NOTEWORTHY Using multivoxel pattern analysis, we found that discrimination task demands shape finger representations in the contralateral primary somatosensory cortex (S1), and that somatotopic representations are modulated by task demands not only during tactile stimulation but also to a certain extent in the absence of tactile input.
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Affiliation(s)
- Finn Rabe
- Neural Control of Movement Laboratory, Department of Health Sciences and Technology, ETH Zürich, Zurich, Switzerland
| | - Sanne Kikkert
- Neural Control of Movement Laboratory, Department of Health Sciences and Technology, ETH Zürich, Zurich, Switzerland
- Neuroscience Center Zurich (ZNZ), ETH Zurich and University of Zurich, Zurich, Switzerland
| | - Nicole Wenderoth
- Neural Control of Movement Laboratory, Department of Health Sciences and Technology, ETH Zürich, Zurich, Switzerland
- Spinal Cord Injury Center, Balgrist University Hospital, University of Zürich, Zurich, Switzerland
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Lin HP, Zhao L, Woolley D, Zhang X, Cheng HJ, Liang W, Kuah C, Plunkett T, Chua K, Zhang L, Wenderoth N. Exploring the Feasibility of Computer Vision for Detecting Post-Stroke Compensatory Movements. IEEE Int Conf Rehabil Robot 2023; 2023:1-6. [PMID: 37941212 DOI: 10.1109/icorr58425.2023.10304697] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2023]
Abstract
Compensatory movements are commonly observed post-stroke and can negatively affect long-term motor recovery. In this context, a system that monitors movement quality and provides feedback would be beneficial. In this study, we aimed to detect compensatory movements during seated reaching using a conventional tablet camera and an open-source markerless body pose tracking algorithm called MediaPipe [1]. We annotated compensatory movements of stroke patients per frame based on the comparison between the paretic and non-paretic arms. We trained a binary classification model using the XGBoost algorithm to detect compensatory movements, which showed an average accuracy of 0.92 (SD 0.07) in leave-one-trial-out cross-validation across four participants. Although we observed good model performance, we also encountered challenges such as missing landmarks and misalignment, when using MediaPipe Pose. This study highlights the feasibility of using near real-time compensatory movement detection with a simple camera system in stroke rehabilitation. More work is necessary to assess the generalizability of our approach across diverse groups of stroke survivors and fully implement near real-time compensatory movement detection on a mobile device.
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Potok W, van der Groen O, Sivachelvam S, Bächinger M, Fröhlich F, Kish LB, Wenderoth N. Contrast detection is enhanced by deterministic, high-frequency transcranial alternating current stimulation with triangle and sine waveform. J Neurophysiol 2023; 130:458-473. [PMID: 37465880 PMCID: PMC10625838 DOI: 10.1152/jn.00465.2022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Revised: 07/05/2023] [Accepted: 07/14/2023] [Indexed: 07/20/2023] Open
Abstract
Stochastic resonance (SR) describes a phenomenon where an additive noise (stochastic carrier-wave) enhances the signal transmission in a nonlinear system. In the nervous system, nonlinear properties are present from the level of single ion channels all the way to perception and appear to support the emergence of SR. For example, SR has been repeatedly demonstrated for visual detection tasks, also by adding noise directly to cortical areas via transcranial random noise stimulation (tRNS). When dealing with nonlinear physical systems, it has been suggested that resonance can be induced not only by adding stochastic signals (i.e., noise) but also by adding a large class of signals that are not stochastic in nature that cause "deterministic amplitude resonance" (DAR). Here, we mathematically show that high-frequency, deterministic, periodic signals can yield resonance-like effects with linear transfer and infinite signal-to-noise ratio at the output. We tested this prediction empirically and investigated whether nonrandom, high-frequency, transcranial alternating current stimulation (tACS) applied to the visual cortex could induce resonance-like effects and enhance the performance of a visual detection task. We demonstrated in 28 participants that applying 80-Hz triangular-waves or sine-waves with tACS reduced the visual contrast detection threshold for optimal brain stimulation intensities. The influence of tACS on contrast sensitivity was equally effective to tRNS-induced modulation, demonstrating that both tACS and tRNS can reduce contrast detection thresholds. Our findings suggest that a resonance-like mechanism can also emerge when deterministic electrical waveforms are applied via tACS.NEW & NOTEWORTHY Our findings extend our understanding of neuromodulation induced by noninvasive electrical stimulation. We provide the first evidence showing acute online benefits of transcranial alternating current stimulation (tACS)triangle and tACSsine targeting the primary visual cortex (V1) on visual contrast detection in accordance with the resonance-like phenomenon. The "deterministic" tACS and "stochastic" high-frequency-transcranial random noise stimulation (tRNS) are equally effective in enhancing visual contrast detection.
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Affiliation(s)
- Weronika Potok
- Neural Control of Movement Lab, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
- Neuroscience Center Zurich (ZNZ), Federal Institute of Technology Zurich, University and Balgrist Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Onno van der Groen
- Neurorehabilitation and Robotics Laboratory, School of Medical and Health Sciences, Edith Cowan University, Joondalup, Western Australia, Australia
| | - Sahana Sivachelvam
- Neural Control of Movement Lab, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
| | - Marc Bächinger
- Neural Control of Movement Lab, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
- Neuroscience Center Zurich (ZNZ), Federal Institute of Technology Zurich, University and Balgrist Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Flavio Fröhlich
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States
- Carolina Center for Neurostimulation, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States
- Department of Neurology, University of North Carolina at Chapel Hill, North Carolina, United States
- Department of Cell Biology and Physiology, University of North Carolina at Chapel Hill, North Carolina, United States
- Department of Biomedical Engineering, University of North Carolina at Chapel Hill, North Carolina, United States
- Neuroscience Center, University of North Carolina at Chapel Hill, North Carolina, United States
| | - Laszlo B Kish
- Department of Electrical & Computer Engineering, Texas A&M University, College Station, Texas, United States
| | - Nicole Wenderoth
- Neural Control of Movement Lab, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
- Neuroscience Center Zurich (ZNZ), Federal Institute of Technology Zurich, University and Balgrist Hospital Zurich, University of Zurich, Zurich, Switzerland
- Future Health Technologies, Singapore-ETH Centre, Campus for Research Excellence and Technological Enterprise (CREATE), Singapore
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Zbären GA, Meissner SN, Kapur M, Wenderoth N. Physical inference of falling objects involves simulation of occluded trajectories in early visual areas. Hum Brain Mapp 2023. [PMID: 37195021 DOI: 10.1002/hbm.26338] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Revised: 04/05/2023] [Accepted: 04/26/2023] [Indexed: 05/18/2023] Open
Abstract
Humans possess an intuitive understanding of the environment's physical properties and dynamics, which allows them to predict the outcomes of physical scenarios and successfully interact with the physical world. This predictive ability is thought to rely on mental simulations and has been shown to involve frontoparietal areas. Here, we investigate whether such mental simulations may be accompanied by visual imagery of the predicted physical scene. We designed an intuitive physical inference task requiring participants to infer the parabolic trajectory of an occluded ball falling in accordance with Newtonian physics. Participants underwent fMRI while (i) performing the physical inference task alternately with a visually matched control task, and (ii) passively observing falling balls depicting the trajectories that had to be inferred during the physical inference task. We found that performing the physical inference task activates early visual areas together with a frontoparietal network when compared with the control task. Using multivariate pattern analysis, we show that these regions contain information specific to the trajectory of the occluded ball (i.e., fall direction), despite the absence of visual inputs. Using a cross-classification approach, we further show that in early visual areas, trajectory-specific activity patterns evoked by the physical inference task resemble those evoked by the passive observation of falling balls. Together, our findings suggest that participants simulated the ball trajectory when solving the task, and that the outcome of these simulations may be represented in form of the perceivable sensory consequences in early visual areas.
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Affiliation(s)
- Gabrielle Aude Zbären
- Neural Control of Movement Lab, Swiss Federal Institute of Technology (ETH), Zurich, Switzerland
| | - Sarah Nadine Meissner
- Neural Control of Movement Lab, Swiss Federal Institute of Technology (ETH), Zurich, Switzerland
| | - Manu Kapur
- Learning Sciences and Higher Education, Swiss Federal Institute of Technology (ETH), Zurich, Switzerland
| | - Nicole Wenderoth
- Neural Control of Movement Lab, Swiss Federal Institute of Technology (ETH), Zurich, Switzerland
- Future Health Technologies, Singapore-ETH Centre, Campus for Research Excellence and Technological Enterprise (CREATE), Singapore
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Potok W, Post A, Beliaeva V, Bächinger M, Cassara' AM, Neufeld E, Polania R, Kiper D, Wenderoth N. Modulation of visual contrast sensitivity with tRNS across the visual system, evidence from stimulation and simulation. eNeuro 2023:ENEURO.0177-22.2023. [PMID: 37263793 DOI: 10.1523/eneuro.0177-22.2023] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2022] [Revised: 05/17/2023] [Accepted: 05/23/2023] [Indexed: 06/03/2023] Open
Abstract
Transcranial random noise stimulation (tRNS) has been shown to significantly improve visual perception. Previous studies demonstrated that tRNS delivered over cortical areas acutely enhances visual contrast detection of weak stimuli. However, it is currently unknown whether tRNS-induced signal enhancement could be achieved within different neural substrates along the retino-cortical pathway.In 3 experimental sessions, we tested whether tRNS applied to the primary visual cortex(V1) and/or to the retina improves visual contrast detection. We first measured visual contrast detection threshold (VCT; N=24, 16females) during tRNS delivery separately over V1 and over the retina, determined the optimal tRNS intensities for each individual(ind-tRNS), and retested the effects of ind-tRNS within the sessions. We further investigated whether we could reproduce the ind-tRNS-induced modulation on a different session (N=19, 14females). Finally, we tested whether the simultaneous application of ind-tRNS to the retina and V1 causes additive effects. Moreover, we present detailed simulations of the induced electric field across the visual system.We found that at the group level tRNS decreases VCT compared to baseline when delivered to the V1. Beneficial effects of ind-tRNS could be replicated when retested within the same experimental session but not when retested in a separate session. Applying tRNS to the retina did not cause a systematic reduction of VCT, irrespective of whether the individually optimized intensity was considered or not. We also did not observe consistent additive effects of V1 and retina stimulation.Our findings demonstrate significant tRNS-induced modulation of visual contrast processing in V1, but not in the retina.Significance statementOur findings confirm previous evidence showing acute online benefits of tRNS of V1 on visual contrast detection in accordance with the stochastic resonance phenomenon. We further extend it, demonstrating that the optimal tRNS intensity varies among participants, but when individually tailored it can improve visual processing when re-tested within the experimental session. The tRNS-induced enhancement in visual sensitivity was observed for cortical contrast processing, but stimulation of the retina did not lead to systematic effects.
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Affiliation(s)
- Weronika Potok
- Neural Control of Movement Lab, Department of Health Sciences and Technology, ETH Zürich, 8093, Zurich, Switzerland
- Neuroscience Center Zurich (ZNZ), University of Zurich, Federal Institute of Technology Zurich, University and Balgrist Hospital Zurich, 8057, Zurich, Switzerland
| | - Alain Post
- Neural Control of Movement Lab, Department of Health Sciences and Technology, ETH Zürich, 8093, Zurich, Switzerland
| | - Valeriia Beliaeva
- Decision Neuroscience Lab, Department of Health Sciences and Technology, ETH Zürich, 8057, Zurich, Switzerland
| | - Marc Bächinger
- Neural Control of Movement Lab, Department of Health Sciences and Technology, ETH Zürich, 8093, Zurich, Switzerland
- Neuroscience Center Zurich (ZNZ), University of Zurich, Federal Institute of Technology Zurich, University and Balgrist Hospital Zurich, 8057, Zurich, Switzerland
| | - Antonino Mario Cassara'
- Foundation for Research on Information Technologies in Society (IT'IS), 8004, Zurich, Switzerland
| | - Esra Neufeld
- Foundation for Research on Information Technologies in Society (IT'IS), 8004, Zurich, Switzerland
| | - Rafael Polania
- Neuroscience Center Zurich (ZNZ), University of Zurich, Federal Institute of Technology Zurich, University and Balgrist Hospital Zurich, 8057, Zurich, Switzerland
- Decision Neuroscience Lab, Department of Health Sciences and Technology, ETH Zürich, 8057, Zurich, Switzerland
| | - Daniel Kiper
- Life Science Zurich Learning Center, 8057, Zurich, Switzerland
| | - Nicole Wenderoth
- Neural Control of Movement Lab, Department of Health Sciences and Technology, ETH Zürich, 8093, Zurich, Switzerland
- Neuroscience Center Zurich (ZNZ), University of Zurich, Federal Institute of Technology Zurich, University and Balgrist Hospital Zurich, 8057, Zurich, Switzerland
- Future Health Technologies, Singapore-ETH Centre, Campus for Research Excellence And Technological Enterprise (CREATE), 138602, Singapore
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Kikkert S, Sonar HA, Freund P, Paik J, Wenderoth N. Hand and face somatotopy shown using MRI-safe vibrotactile stimulation with a novel soft pneumatic actuator (SPA)-skin interface. Neuroimage 2023; 269:119932. [PMID: 36750151 DOI: 10.1016/j.neuroimage.2023.119932] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2022] [Revised: 01/23/2023] [Accepted: 02/02/2023] [Indexed: 02/07/2023] Open
Abstract
The exact somatotopy of the human facial representation in the primary somatosensory cortex (S1) remains debated. One reason that progress has been hampered is due to the methodological challenge of how to apply automated vibrotactile stimuli to face areas in a manner that is: (1) reliable despite differences in the curvatures of face locations; and (2) MR-compatible and free of MR-interference artefacts when applied in the MR head-coil. Here we overcome this challenge by using soft pneumatic actuator (SPA) technology. SPAs are made of a soft silicon material and can be in- or deflated by means of airflow, have a small diameter, and are flexible in structure, enabling good skin contact even on curved body surfaces (as on the face). To validate our approach, we first mapped the well-characterised S1 finger layout using this novel device and confirmed that tactile stimulation of the fingers elicited characteristic somatotopic finger activations in S1. We then used the device to automatically and systematically deliver somatosensory stimulation to different face locations. We found that the forehead representation was least distant from the representation of the hand. Within the face representation, we found that the lip representation is most distant from the forehead representation, with the chin represented in between. Together, our results demonstrate that this novel MR compatible device produces robust and clear somatotopic representational patterns using vibrotactile stimulation through SPA-technology.
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Affiliation(s)
- Sanne Kikkert
- Neural Control of Movement Laboratory, Department of Health Sciences and Technology, ETH Zürich, Zürich, Switzerland; Spinal Cord Injury Center Balgrist, University Hospital Zürich, University of Zürich, Zürich, Switzerland.
| | | | - Patrick Freund
- Spinal Cord Injury Center Balgrist, University Hospital Zürich, University of Zürich, Zürich, Switzerland
| | - Jamie Paik
- Reconfigurable Robotics Lab, EPFL, Lausanne, Switzerland
| | - Nicole Wenderoth
- Neural Control of Movement Laboratory, Department of Health Sciences and Technology, ETH Zürich, Zürich, Switzerland
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Andrews SC, Kämpf L, Curtin D, Hinder M, Wenderoth N, Stout JC, Coxon JP. A single bout of moderate-intensity aerobic exercise improves motor learning in premanifest and early Huntington's disease. Front Psychol 2023; 14:1089333. [PMID: 36968757 PMCID: PMC10032374 DOI: 10.3389/fpsyg.2023.1089333] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2022] [Accepted: 02/20/2023] [Indexed: 03/10/2023] Open
Abstract
Introduction Cardiorespiratory exercise has emerged as a promising candidate to modify disease progression in Huntington's disease (HD). In animal models, exercise has been found to alter biomarkers of neuroplasticity and delay evidence of disease, and some interventions-including exercise-have shown benefits in human HD patients. In healthy human populations, increasing evidence suggests that even a single bout of exercise can improve motor learning. In this pilot study, we investigated the effect of a single bout of moderate intensity aerobic exercise on motor skill learning in presymptomatic and early manifest HD patients. Methods Participants were allocated to either an exercise (n = 10) or control (n = 10) group. They performed either 20 min of moderate intensity cycling or rest before practicing a novel motor task, the sequential visual isometric pinch force task (SVIPT). After 1 week, the retention of the SVIPT was measured in both groups. Results We found that the exercise group performed significantly better during initial task acquisition. There were no significant differences in offline memory consolidation between groups, but total skill gain across both acquisition and retention sessions was greater in the group who exercised. The better performance of the exercise group was driven by improvements in accuracy, rather than speed. Discussion We have shown that a single bout of moderate intensity aerobic exercise can facilitate motor skill learning in people with HD gene-expansion. More research is needed to investigate the underlying neural mechanisms and to further explore the potential for neurocognitive and functional benefits of exercise for people with HD.
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Affiliation(s)
- Sophie C. Andrews
- School of Psychological Sciences, Turner Institute for Brain and Mental Health, Monash University, Clayton, VIC, Australia
- Healthy Brain Ageing Research Group, Thompson Institute, University of the Sunshine Coast, Birtinya, QLD, Australia
| | - Lydia Kämpf
- School of Psychological Sciences, Turner Institute for Brain and Mental Health, Monash University, Clayton, VIC, Australia
- Neural Control of Movement Lab, Department of Health Sciences and Technology, ETH Zürich, Zurich, Switzerland
| | - Dylan Curtin
- School of Psychological Sciences, Turner Institute for Brain and Mental Health, Monash University, Clayton, VIC, Australia
| | - Mark Hinder
- Sensorimotor Neuroscience and Ageing Research Group, School of Psychological Sciences, College of Health and Medicine, University of Tasmania, Hobart, TAS, Australia
| | - Nicole Wenderoth
- Neural Control of Movement Lab, Department of Health Sciences and Technology, ETH Zürich, Zurich, Switzerland
- Neuroscience Center Zurich (ZNZ), Federal Institute of Technology Zurich, University and Balgrist Hospital Zurich, University of Zurich, Zurich, Switzerland
- Future Health Technologies, Singapore-ETH Centre, Campus for Research Excellence and Technological Enterprise (CREATE), Singapore, Singapore
| | - Julie C. Stout
- School of Psychological Sciences, Turner Institute for Brain and Mental Health, Monash University, Clayton, VIC, Australia
| | - James P. Coxon
- School of Psychological Sciences, Turner Institute for Brain and Mental Health, Monash University, Clayton, VIC, Australia
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Lin HP, Zhang X, Xu Y, Woolley D, Zhao L, Liang W, Cheng HJ, Zhang L, Wenderoth N. A Usability Study on Mobile EMG-Guided Neurofeedback Training for Individuals With Stroke – MyoPanda. Arch Phys Med Rehabil 2023. [DOI: 10.1016/j.apmr.2022.12.024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/05/2023]
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15
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Cheng HJ, Chin LF, Kanzler CM, Lehner R, Kuah CWK, Wee SK, Liang P, Chua KS, Lambercy O, Wenderoth N. Deep Phenotyping of Upper Limb Sensorimotor Recovery in Asian Stroke Survivors: A Study Protocol. Arch Phys Med Rehabil 2023. [DOI: 10.1016/j.apmr.2022.12.059] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/05/2023]
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16
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Huwiler S, Huwyler S, Kiener L, Sala R, Schmied C, Huber R, Wenderoth N, Lustenberger C. Effects of auditory sleep modulation approaches on slow waves and autonomic recovery functions. Sleep Med 2022. [DOI: 10.1016/j.sleep.2022.05.055] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/17/2022]
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17
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Alaerts K, Bernaerts S, Wenderoth N. Effects of single- and multiple-dose oxytocin treatment on amygdala low-frequency BOLD fluctuations and BOLD spectral dynamics in autism. Transl Psychiatry 2022; 12:393. [PMID: 36127337 PMCID: PMC9489696 DOI: 10.1038/s41398-022-02158-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/24/2022] [Revised: 09/02/2022] [Accepted: 09/07/2022] [Indexed: 11/17/2022] Open
Abstract
Prior neuroimaging clinical trials investigating the neural effects of intranasal administration of the neuropeptide oxytocin demonstrated a key role of the amygdala in oxytocin's neuromodulatory effects. These studies mostly demonstrated the acute effects of single-dose administrations, examining task-dependent effects of oxytocin on brain activity elicited during explicit experimental tasks or stimuli presentations. The increased consideration of oxytocin as a potential ameliorating treatment in autism spectrum disorder (ASD) requires a better understanding of how multiple-dose oxytocin administration affects intrinsic, task-free, amygdala function. In this double-blind, randomized, placebo-controlled trial with between-subject design, 38 adult men with ASD underwent resting-state fMRI scanning before and after oxytocin or placebo treatment. Effects were assessed either after a single-dose administration, consisting of 24 international units, or after multiple-dose treatment, consisting of 4 weeks of once-daily nasal spray administrations. Compared to placebo, oxytocin induced a decrease in intrinsic resting-state BOLD signal amplitudes of the bilateral amygdala (fractional amplitudes of low-frequency fluctuations) and modulated cross-frequency interactions between adjacent BOLD frequency components. The right amygdala showed a pattern of reduced cross-frequency harmonicity, while the left amygdala showed a relative increase in harmonic cross-frequency interactions after oxytocin treatment. Notably, the direction and magnitude of BOLD spectral changes induced after a single-dose were qualitatively similar to treatment effects induced after multiple-dose treatment. Furthermore, the identified spectral changes in amygdalar BOLD amplitude and cross-frequency harmonicity were associated with improved feelings of tension, reflecting oxytocin's anxiolytic, stress-reducing neuromodulatory role. The observed effects of oxytocin on amygdalar BOLD spectral characteristics and associated behaviors contribute to a deeper mechanistic understanding of the intrinsic, task-free neuromodulatory dynamics that underlie single- and multiple-dose oxytocin treatment in ASD. European Clinical Trial Registry (Eudract 2014-000586-45).
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Affiliation(s)
- Kaat Alaerts
- Department of Rehabilitation Sciences, Group Biomedical Sciences, Neuromodulation Laboratory, Neurorehabilitation Research Group, University of Leuven, KU Leuven, Leuven, Belgium.
| | - Sylvie Bernaerts
- grid.5596.f0000 0001 0668 7884Department of Rehabilitation Sciences, Group Biomedical Sciences, Neuromodulation Laboratory, Neurorehabilitation Research Group, University of Leuven, KU Leuven, Leuven, Belgium
| | - Nicole Wenderoth
- grid.5801.c0000 0001 2156 2780Department of Health Sciences and Technology, Neural Control of Movement Lab, ETH Zurich, Zurich, Switzerland
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Huwiler S, Carro Dominguez M, Huwyler S, Kiener L, Stich FM, Sala R, Aziri F, Trippel A, Schmied C, Huber R, Wenderoth N, Lustenberger C. Effects of auditory sleep modulation approaches on brain oscillatory and cardiovascular dynamics. Sleep 2022; 45:6632997. [PMID: 35793672 PMCID: PMC9453626 DOI: 10.1093/sleep/zsac155] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Revised: 06/01/2022] [Indexed: 11/14/2022] Open
Abstract
Abstract
Slow waves, the hallmark feature of deep nonrapid eye movement sleep, do potentially drive restorative effects of sleep on brain and body functions. Sleep modulation techniques to elucidate the functional role of slow waves thus have gained large interest. Auditory slow wave stimulation is a promising tool; however, directly comparing auditory stimulation approaches within a night and analyzing induced dynamic brain and cardiovascular effects are yet missing. Here, we tested various auditory stimulation approaches in a windowed, 10 s ON (stimulations) followed by 10 s OFF (no stimulations), within-night stimulation design and compared them to a SHAM control condition. We report the results of three studies and a total of 51 included nights and found a large and global increase in slow-wave activity (SWA) in the stimulation window compared to SHAM. Furthermore, slow-wave dynamics were most pronouncedly increased at the start of the stimulation and declined across the stimulation window. Beyond the changes in brain oscillations, we observed, for some conditions, a significant increase in the mean interval between two heartbeats within a stimulation window, indicating a slowing of the heart rate, and increased heart rate variability derived parasympathetic activity. Those cardiovascular changes were positively correlated with the change in SWA, and thus, our findings provide insight into the potential of auditory slow wave enhancement to modulate cardiovascular restorative conditions during sleep. However, future studies need to investigate whether the potentially increased restorative capacity through slow-wave enhancements translates into a more rested cardiovascular system on a subsequent day.
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Affiliation(s)
- Stephanie Huwiler
- Department of Health Sciences and Technology, Neural Control of Movement Lab, Institute of Human Movement Sciences and Sport, ETH Zurich, Zurich, Switzerland
| | - Manuel Carro Dominguez
- Department of Health Sciences and Technology, Neural Control of Movement Lab, Institute of Human Movement Sciences and Sport, ETH Zurich, Zurich, Switzerland
| | - Silja Huwyler
- Department of Health Sciences and Technology, Neural Control of Movement Lab, Institute of Human Movement Sciences and Sport, ETH Zurich, Zurich, Switzerland
| | - Luca Kiener
- Department of Health Sciences and Technology, Neural Control of Movement Lab, Institute of Human Movement Sciences and Sport, ETH Zurich, Zurich, Switzerland
| | - Fabia M Stich
- Department of Health Sciences and Technology, Neural Control of Movement Lab, Institute of Human Movement Sciences and Sport, ETH Zurich, Zurich, Switzerland
| | - Rossella Sala
- Department of Health Sciences and Technology, Neural Control of Movement Lab, Institute of Human Movement Sciences and Sport, ETH Zurich, Zurich, Switzerland
| | - Florent Aziri
- Department of Health Sciences and Technology, Neural Control of Movement Lab, Institute of Human Movement Sciences and Sport, ETH Zurich, Zurich, Switzerland
| | - Anna Trippel
- Department of Health Sciences and Technology, Neural Control of Movement Lab, Institute of Human Movement Sciences and Sport, ETH Zurich, Zurich, Switzerland
| | - Christian Schmied
- Department of Cardiology, University Heart Center Zurich, University of Zurich, Zurich, Switzerland
| | - Reto Huber
- Center of Competence Sleep and Health Zurich, University of Zurich, Zurich, Switzerland
- Neuroscience Center Zurich (ZNZ), University of Zurich, ETH Zurich, Zurich, Switzerland
- Child Development Centre, University Children’s Hospital, University of Zurich, Zurich, Switzerland
- Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Nicole Wenderoth
- Department of Health Sciences and Technology, Neural Control of Movement Lab, Institute of Human Movement Sciences and Sport, ETH Zurich, Zurich, Switzerland
- Neuroscience Center Zurich (ZNZ), University of Zurich, ETH Zurich, Zurich, Switzerland
- Future Health Technologies, Singapore-ETH Center, Campus for Research Excellence and Technological Enterprise (CREATE), Singapore, Singapore
| | - Caroline Lustenberger
- Corresponding author. Caroline Lustenberger, Department of Health Sciences and Technology, Neural Control of Movement Lab, ETH Zurich, Zurich, 8092, Switzerland.
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Zerbi V, Pagani M, Markicevic M, Matteoli M, Pozzi D, Fagiolini M, Bozzi Y, Galbusera A, Scattoni ML, Provenzano G, Banerjee A, Helmchen F, Basson MA, Ellegood J, Lerch JP, Rudin M, Gozzi A, Wenderoth N. Correction: Brain mapping across 16 autism mouse models reveals a spectrum of functional connectivity subtypes. Mol Psychiatry 2022; 27:3920-3921. [PMID: 35322201 PMCID: PMC9708546 DOI: 10.1038/s41380-022-01510-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Affiliation(s)
- V Zerbi
- Neural Control of Movement Lab, ETH Zurich, Zurich, Switzerland
| | - M Pagani
- Functional Neuroimaging Lab, Istituto Italiano di Tecnologia, Center for Neuroscience and Cognitive Systems, Rovereto, Italy
| | - M Markicevic
- Neural Control of Movement Lab, ETH Zurich, Zurich, Switzerland
| | - M Matteoli
- Laboratory of Pharmacology and Brain Pathology, Neurocenter, Humanitas Clinical and Research Center - IRCCS, Rozzano, Mi, Italy
- CNR Institute of Neuroscience, Milano, Italy
| | - D Pozzi
- Laboratory of Pharmacology and Brain Pathology, Neurocenter, Humanitas Clinical and Research Center - IRCCS, Rozzano, Mi, Italy
- Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, Milan, Italy
| | - M Fagiolini
- F.M. Kirby Neurobiology Department, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Y Bozzi
- Center for Mind/Brain Sciences (CIMeC), University of Trento, Rovereto, Italy
| | - A Galbusera
- Functional Neuroimaging Lab, Istituto Italiano di Tecnologia, Center for Neuroscience and Cognitive Systems, Rovereto, Italy
| | - M L Scattoni
- Research Coordination and Support Service, Istituto Superiore di Sanità, Rome, Italy
| | - G Provenzano
- Department of Cellular, Computational and Integrative Biology. (CIBIO), University of Trento, Trento, Italy
| | - A Banerjee
- Brain Research Institute, University of Zurich, Zurich, Switzerland
- Biosciences Institute, Newcastle University, Newcastle upon Tyne, UK
| | - F Helmchen
- Brain Research Institute, University of Zurich, Zurich, Switzerland
| | - M A Basson
- Centre for Craniofacial and Regenerative Biology, King's College London, London, UK
- MRC Centre for Neurodevelopmental Disorders, King's College, London, London, UK
| | - J Ellegood
- Mouse Imaging Ctr., Hosp. For Sick Children, Toronto, ON, Canada
| | - J P Lerch
- Mouse Imaging Ctr., Hosp. For Sick Children, Toronto, ON, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - M Rudin
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
| | - A Gozzi
- Functional Neuroimaging Lab, Istituto Italiano di Tecnologia, Center for Neuroscience and Cognitive Systems, Rovereto, Italy.
| | - N Wenderoth
- Neural Control of Movement Lab, ETH Zurich, Zurich, Switzerland
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Antal A, Luber B, Brem AK, Bikson M, Brunoni AR, Cohen Kadosh R, Dubljević V, Fecteau S, Ferreri F, Flöel A, Hallett M, Hamilton RH, Herrmann CS, Lavidor M, Loo C, Lustenberger C, Machado S, Miniussi C, Moliadze V, Nitsche MA, Rossi S, Rossini PM, Santarnecchi E, Seeck M, Thut G, Turi Z, Ugawa Y, Venkatasubramanian G, Wenderoth N, Wexler A, Ziemann U, Paulus W. Non-invasive brain stimulation and neuroenhancement. Clin Neurophysiol Pract 2022; 7:146-165. [PMID: 35734582 PMCID: PMC9207555 DOI: 10.1016/j.cnp.2022.05.002] [Citation(s) in RCA: 43] [Impact Index Per Article: 21.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Revised: 04/19/2022] [Accepted: 05/18/2022] [Indexed: 12/15/2022] Open
Abstract
The available data frame with a wide parameter space of tES does not allow an overarching protocol recommendation. Established engineering risk-management procedures with regard to manufacturing should be followed. Consensus among experts is that tES for neuroenhancement is safe as long as tested protocols are followed.
Attempts to enhance human memory and learning ability have a long tradition in science. This topic has recently gained substantial attention because of the increasing percentage of older individuals worldwide and the predicted rise of age-associated cognitive decline in brain functions. Transcranial brain stimulation methods, such as transcranial magnetic (TMS) and transcranial electric (tES) stimulation, have been extensively used in an effort to improve cognitive functions in humans. Here we summarize the available data on low-intensity tES for this purpose, in comparison to repetitive TMS and some pharmacological agents, such as caffeine and nicotine. There is no single area in the brain stimulation field in which only positive outcomes have been reported. For self-directed tES devices, how to restrict variability with regard to efficacy is an essential aspect of device design and function. As with any technique, reproducible outcomes depend on the equipment and how well this is matched to the experience and skill of the operator. For self-administered non-invasive brain stimulation, this requires device designs that rigorously incorporate human operator factors. The wide parameter space of non-invasive brain stimulation, including dose (e.g., duration, intensity (current density), number of repetitions), inclusion/exclusion (e.g., subject’s age), and homeostatic effects, administration of tasks before and during stimulation, and, most importantly, placebo or nocebo effects, have to be taken into account. The outcomes of stimulation are expected to depend on these parameters and should be strictly controlled. The consensus among experts is that low-intensity tES is safe as long as tested and accepted protocols (including, for example, dose, inclusion/exclusion) are followed and devices are used which follow established engineering risk-management procedures. Devices and protocols that allow stimulation outside these parameters cannot claim to be “safe” where they are applying stimulation beyond that examined in published studies that also investigated potential side effects. Brain stimulation devices marketed for consumer use are distinct from medical devices because they do not make medical claims and are therefore not necessarily subject to the same level of regulation as medical devices (i.e., by government agencies tasked with regulating medical devices). Manufacturers must follow ethical and best practices in marketing tES stimulators, including not misleading users by referencing effects from human trials using devices and protocols not similar to theirs.
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Affiliation(s)
- Andrea Antal
- Department of Neurology, University Medical Center, Göttingen, Germany
- Corresponding author at: Department of Neurology, University Medical Center, Göttingen, Robert Koch Str. 40, 37075 Göttingen, Germany.
| | - Bruce Luber
- Noninvasive Neuromodulation Unit, Experimental Therapeutics and Pathophysiology Branch, National Institute of Mental Health, Bethesda, MD, USA
| | - Anna-Katharine Brem
- University Hospital of Old Age Psychiatry, University of Bern, Bern, Switzerland
- Department of Old Age Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Marom Bikson
- Biomedical Engineering at the City College of New York (CCNY) of the City University of New York (CUNY), NY, USA
| | - Andre R. Brunoni
- Departamento de Clínica Médica e de Psiquiatria, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
- Service of Interdisciplinary Neuromodulation (SIN), Laboratory of Neurosciences (LIM-27), Institute of Psychiatry, Hospital das Clínicas da Faculdade de Medicina da USP, São Paulo, Brazil
| | - Roi Cohen Kadosh
- School of Psychology, Faculty of Health and Medical Sciences, University of Surrey, Guildford GU2 7XH, UK
| | - Veljko Dubljević
- Science, Technology and Society Program, College of Humanities and Social Sciences, North Carolina State University, Raleigh, NC, USA
| | - Shirley Fecteau
- Department of Psychiatry and Neurosciences, Faculty of Medicine, Université Laval, CERVO Brain Research Centre, Centre intégré universitaire en santé et services sociaux de la Capitale-Nationale, Quebec City, Quebec, Canada
| | - Florinda Ferreri
- Unit of Neurology, Unit of Clinical Neurophysiology, Study Center of Neurodegeneration (CESNE), Department of Neuroscience, University of Padua, Padua, Italy
- Department of Clinical Neurophysiology, Kuopio University Hospital, University of Eastern Finland, Kuopio, Finland
| | - Agnes Flöel
- Department of Neurology, Universitätsmedizin Greifswald, 17475 Greifswald, Germany
- German Centre for Neurodegenerative Diseases (DZNE) Standort Greifswald, 17475 Greifswald, Germany
| | - Mark Hallett
- Human Motor Control Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Roy H. Hamilton
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
| | - Christoph S. Herrmann
- Experimental Psychology Lab, Department of Psychology, Carl von Ossietzky Universität, Oldenburg, Germany
| | - Michal Lavidor
- Department of Psychology and the Gonda Brain Research Center, Bar Ilan University, Israel
| | - Collen Loo
- School of Psychiatry and Black Dog Institute, University of New South Wales; The George Institute; Sydney, Australia
| | - Caroline Lustenberger
- Neural Control of Movement Lab, Institute of Human Movement Sciences and Sport, Department of Health Sciences and Technology, ETH Zurich, 8092 Zurich, Switzerland
| | - Sergio Machado
- Department of Sports Methods and Techniques, Federal University of Santa Maria, Santa Maria, Brazil
- Laboratory of Physical Activity Neuroscience, Neurodiversity Institute, Queimados-RJ, Brazil
| | - Carlo Miniussi
- Center for Mind/Brain Sciences – CIMeC and Centre for Medical Sciences - CISMed, University of Trento, Rovereto, Italy
| | - Vera Moliadze
- Institute of Medical Psychology and Medical Sociology, University Medical Center Schleswig Holstein, Kiel University, Kiel, Germany
| | - Michael A Nitsche
- Department Psychology and Neurosciences, Leibniz Research Centre for Working Environment and Human Factors at TU, Dortmund, Germany
- Dept. Neurology, University Medical Hospital Bergmannsheil, Bochum, Germany
| | - Simone Rossi
- Siena Brain Investigation and Neuromodulation Lab (Si-BIN Lab), Unit of Neurology and Clinical Neurophysiology, Department of Medicine, Surgery and Neuroscience, University of Siena, Italy
| | - Paolo M. Rossini
- Department of Neuroscience and Neurorehabilitation, Brain Connectivity Lab, IRCCS-San Raffaele-Pisana, Rome, Italy
| | - Emiliano Santarnecchi
- Precision Neuroscience and Neuromodulation Program, Gordon Center for Medical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Margitta Seeck
- Department of Clinical Neurosciences, Hôpitaux Universitaires de Genève, Switzerland
| | - Gregor Thut
- Centre for Cognitive Neuroimaging, School of Psychology and Neuroscience, EEG & Epolepsy Unit, University of Glasgow, United Kingdom
| | - Zsolt Turi
- Department of Neuroanatomy, Institute of Anatomy and Cell Biology, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Yoshikazu Ugawa
- Department of Human Neurophysiology, Fukushima Medical University, Fukushima, Japan
| | | | - Nicole Wenderoth
- Neural Control of Movement Lab, Institute of Human Movement Sciences and Sport, Department of Health Sciences and Technology, ETH Zurich, 8092 Zurich, Switzerland
- Future Health Technologies, Singapore-ETH Centre, Campus for Research Excellence And Technological Enterprise (CREATE), Singapore
| | - Anna Wexler
- Department of Medical Ethics and Health Policy, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Ulf Ziemann
- Department of Neurology and Stroke, University of Tübingen, Germany
- Hertie Institute for Clinical Brain Research, University of Tübingen, Germany
| | - Walter Paulus
- Department of of Neurology, Ludwig Maximilians University Munich, Germany
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21
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Grimm C, Frässle S, Steger C, von Ziegler L, Sturman O, Shemesh N, Peleg-Raibstein D, Burdakov D, Bohacek J, Stephan KE, Razansky D, Wenderoth N, Zerbi V. Optogenetic activation of striatal D1R and D2R cells differentially engages downstream connected areas beyond the basal ganglia. Cell Rep 2021; 37:110161. [PMID: 34965430 DOI: 10.1016/j.celrep.2021.110161] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2021] [Revised: 10/20/2021] [Accepted: 12/01/2021] [Indexed: 11/16/2022] Open
Abstract
The basal ganglia (BG) are a group of subcortical nuclei responsible for motor and executive function. Central to BG function are striatal cells expressing D1 (D1R) and D2 (D2R) dopamine receptors. D1R and D2R cells are considered functional antagonists that facilitate voluntary movements and inhibit competing motor patterns, respectively. However, whether they maintain a uniform function across the striatum and what influence they exert outside the BG is unclear. Here, we address these questions by combining optogenetic activation of D1R and D2R cells in the mouse ventrolateral caudoputamen with fMRI. Striatal D1R/D2R stimulation evokes distinct activity within the BG-thalamocortical network and differentially engages cerebellar and prefrontal regions. Computational modeling of effective connectivity confirms that changes in D1R/D2R output drive functional relationships between these regions. Our results suggest a complex functional organization of striatal D1R/D2R cells and hint toward an interconnected fronto-BG-cerebellar network modulated by striatal D1R and D2R cells.
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Affiliation(s)
- Christina Grimm
- Neural Control of Movement Lab, Department of Health Sciences and Technology, ETH Zürich, Zürich, Switzerland; Neuroscience Center Zurich, ETH Zürich and University of Zurich, Zürich, Switzerland
| | - Stefan Frässle
- Translational Neuromodeling Unit (TNU), Institute for Biomedical Engineering, University of Zürich and ETH Zürich, Zürich, Switzerland
| | - Céline Steger
- Neuroscience Center Zurich, ETH Zürich and University of Zurich, Zürich, Switzerland; Center for MR Research, University Children's Hospital Zurich, Zürich, Switzerland
| | - Lukas von Ziegler
- Laboratory of Molecular and Behavioral Neuroscience, Institute for Neuroscience, Department of Health Sciences and Technology, ETH Zürich, Zürich, Switzerland; Neuroscience Center Zurich, ETH Zürich and University of Zurich, Zürich, Switzerland
| | - Oliver Sturman
- Laboratory of Molecular and Behavioral Neuroscience, Institute for Neuroscience, Department of Health Sciences and Technology, ETH Zürich, Zürich, Switzerland; Neuroscience Center Zurich, ETH Zürich and University of Zurich, Zürich, Switzerland
| | - Noam Shemesh
- Champalimaud Research, Champalimaud Centre for the Unknown, Lisbon, Portugal
| | - Daria Peleg-Raibstein
- Laboratory of Neurobehavioral Dynamics, Department of Health Sciences and Technology, Institute for Neuroscience, ETH Zürich, Zürich, Switzerland; Institute for Biomedical Engineering and Institute of Pharmacology and Toxicology, Faculty of Medicine, University of Zurich, Zürich, Switzerland
| | - Denis Burdakov
- Laboratory of Neurobehavioral Dynamics, Department of Health Sciences and Technology, Institute for Neuroscience, ETH Zürich, Zürich, Switzerland; Institute for Biomedical Engineering and Institute of Pharmacology and Toxicology, Faculty of Medicine, University of Zurich, Zürich, Switzerland; Neuroscience Center Zurich, ETH Zürich and University of Zurich, Zürich, Switzerland
| | - Johannes Bohacek
- Laboratory of Molecular and Behavioral Neuroscience, Institute for Neuroscience, Department of Health Sciences and Technology, ETH Zürich, Zürich, Switzerland; Neuroscience Center Zurich, ETH Zürich and University of Zurich, Zürich, Switzerland
| | - Klaas Enno Stephan
- Translational Neuromodeling Unit (TNU), Institute for Biomedical Engineering, University of Zürich and ETH Zürich, Zürich, Switzerland
| | - Daniel Razansky
- Institute for Biomedical Engineering, Department of Information Technology and Electrical Engineering, ETH Zürich, Zürich, Switzerland; Institute of Biological and Medical Imaging (IBMI), Technical University of Munich and Helmholtz Center Munich, Munich, Germany; Neuroscience Center Zurich, ETH Zürich and University of Zurich, Zürich, Switzerland
| | - Nicole Wenderoth
- Neural Control of Movement Lab, Department of Health Sciences and Technology, ETH Zürich, Zürich, Switzerland; Neuroscience Center Zurich, ETH Zürich and University of Zurich, Zürich, Switzerland
| | - Valerio Zerbi
- Neural Control of Movement Lab, Department of Health Sciences and Technology, ETH Zürich, Zürich, Switzerland; Neuroscience Center Zurich, ETH Zürich and University of Zurich, Zürich, Switzerland.
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22
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Zerbi V, Pagani M, Markicevic M, Matteoli M, Pozzi D, Fagiolini M, Bozzi Y, Galbusera A, Scattoni ML, Provenzano G, Banerjee A, Helmchen F, Basson MA, Ellegood J, Lerch JP, Rudin M, Gozzi A, Wenderoth N. Brain mapping across 16 autism mouse models reveals a spectrum of functional connectivity subtypes. Mol Psychiatry 2021; 26:7610-7620. [PMID: 34381171 PMCID: PMC8873017 DOI: 10.1038/s41380-021-01245-4] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/02/2020] [Revised: 06/30/2021] [Accepted: 07/20/2021] [Indexed: 02/07/2023]
Abstract
Autism Spectrum Disorder (ASD) is characterized by substantial, yet highly heterogeneous abnormalities in functional brain connectivity. However, the origin and significance of this phenomenon remain unclear. To unravel ASD connectopathy and relate it to underlying etiological heterogeneity, we carried out a bi-center cross-etiological investigation of fMRI-based connectivity in the mouse, in which specific ASD-relevant mutations can be isolated and modeled minimizing environmental contributions. By performing brain-wide connectivity mapping across 16 mouse mutants, we show that different ASD-associated etiologies cause a broad spectrum of connectional abnormalities in which diverse, often diverging, connectivity signatures are recognizable. Despite this heterogeneity, the identified connectivity alterations could be classified into four subtypes characterized by discrete signatures of network dysfunction. Our findings show that etiological variability is a key determinant of connectivity heterogeneity in ASD, hence reconciling conflicting findings in clinical populations. The identification of etiologically-relevant connectivity subtypes could improve diagnostic label accuracy in the non-syndromic ASD population and paves the way for personalized treatment approaches.
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Affiliation(s)
- V Zerbi
- Neural Control of Movement Lab, ETH Zurich, Zurich, Switzerland
| | - M Pagani
- Functional Neuroimaging Lab, Istituto Italiano di Tecnologia, Center for Neuroscience and Cognitive Systems, Rovereto, Italy
| | - M Markicevic
- Neural Control of Movement Lab, ETH Zurich, Zurich, Switzerland
| | - M Matteoli
- Laboratory of Pharmacology and Brain Pathology, Neurocenter, Humanitas Clinical and Research Center - IRCCS, Rozzano, Mi, Italy
- CNR Institute of Neuroscience, Milano, Italy
| | - D Pozzi
- Laboratory of Pharmacology and Brain Pathology, Neurocenter, Humanitas Clinical and Research Center - IRCCS, Rozzano, Mi, Italy
- Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, Milan, Italy
| | - M Fagiolini
- F.M. Kirby Neurobiology Department, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Y Bozzi
- Center for Mind/Brain Sciences (CIMeC), University of Trento, Rovereto, Italy
| | - A Galbusera
- Functional Neuroimaging Lab, Istituto Italiano di Tecnologia, Center for Neuroscience and Cognitive Systems, Rovereto, Italy
| | - M L Scattoni
- Research Coordination and Support Service, Istituto Superiore di Sanità, Rome, Italy
| | - G Provenzano
- Department of Cellular, Computational and Integrative Biology. (CIBIO), University of Trento, Trento, Italy
| | - A Banerjee
- Brain Research Institute, University of Zurich, Zurich, Switzerland
- Biosciences Institute, Newcastle University, Newcastle upon Tyne, UK
| | - F Helmchen
- Brain Research Institute, University of Zurich, Zurich, Switzerland
| | - M A Basson
- Centre for Craniofacial and Regenerative Biology, King's College London, London, UK
- MRC Centre for Neurodevelopmental Disorders, King's College, London, London, UK
| | - J Ellegood
- Mouse Imaging Ctr., Hosp. For Sick Children, Toronto, ON, Canada
| | - J P Lerch
- Mouse Imaging Ctr., Hosp. For Sick Children, Toronto, ON, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - M Rudin
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
| | - A Gozzi
- Functional Neuroimaging Lab, Istituto Italiano di Tecnologia, Center for Neuroscience and Cognitive Systems, Rovereto, Italy.
| | - N Wenderoth
- Neural Control of Movement Lab, ETH Zurich, Zurich, Switzerland
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23
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Kikkert S, Pfyffer D, Verling M, Freund P, Wenderoth N. Finger somatotopy is preserved after tetraplegia but deteriorates over time. eLife 2021; 10:e67713. [PMID: 34665133 PMCID: PMC8575460 DOI: 10.7554/elife.67713] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2021] [Accepted: 10/18/2021] [Indexed: 12/12/2022] Open
Abstract
Previous studies showed reorganised and/or altered activity in the primary sensorimotor cortex after a spinal cord injury (SCI), suggested to reflect abnormal processing. However, little is known about whether somatotopically specific representations can be activated despite reduced or absent afferent hand inputs. In this observational study, we used functional MRI and a (attempted) finger movement task in tetraplegic patients to characterise the somatotopic hand layout in primary somatosensory cortex. We further used structural MRI to assess spared spinal tissue bridges. We found that somatotopic hand representations can be activated through attempted finger movements in the absence of sensory and motor hand functioning, and no spared spinal tissue bridges. Such preserved hand somatotopy could be exploited by rehabilitation approaches that aim to establish new hand-brain functional connections after SCI (e.g. neuroprosthetics). However, over years since SCI the hand representation somatotopy deteriorated, suggesting that somatotopic hand representations are more easily targeted within the first years after SCI.
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Affiliation(s)
- Sanne Kikkert
- Neural Control of Movement Laboratory, Department of Health Sciences and Technology, ETH ZürichZürichSwitzerland
- Spinal Cord Injury Center, Balgrist University Hospital, University of ZürichZürichSwitzerland
| | - Dario Pfyffer
- Spinal Cord Injury Center, Balgrist University Hospital, University of ZürichZürichSwitzerland
| | - Michaela Verling
- Neural Control of Movement Laboratory, Department of Health Sciences and Technology, ETH ZürichZürichSwitzerland
| | - Patrick Freund
- Spinal Cord Injury Center, Balgrist University Hospital, University of ZürichZürichSwitzerland
- Department of Brain Repair and Rehabilitation, UCL Institute of Neurology, University College LondonLondonUnited Kingdom
- Wellcome Trust Centre for Neuroimaging, UCL Institute of Neurology, University College LondonLondonUnited Kingdom
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
| | - Nicole Wenderoth
- Neural Control of Movement Laboratory, Department of Health Sciences and Technology, ETH ZürichZürichSwitzerland
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24
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Mihelj E, Bächinger M, Kikkert S, Ruddy K, Wenderoth N. Mental individuation of imagined finger movements can be achieved using TMS-based neurofeedback. Neuroimage 2021; 242:118463. [PMID: 34384910 DOI: 10.1016/j.neuroimage.2021.118463] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2021] [Revised: 07/09/2021] [Accepted: 08/04/2021] [Indexed: 11/27/2022] Open
Abstract
Neurofeedback (NF) in combination with motor imagery (MI) can be used for training individuals to volitionally modulate sensorimotor activity without producing overt movements. However, until now, NF methods were of limited utility for mentally training specific hand and finger actions. Here we employed a novel transcranial magnetic stimulation (TMS) based protocol to probe and detect MI-induced motor activity patterns in the primary motor cortex (M1) with the aim to reinforce selective facilitation of single finger representations. We showed that TMS-NF training but not MI training with uninformative feedback enabled participants to selectively upregulate corticomotor excitability of one finger, while simultaneously downregulating excitability of other finger representations within the same hand. Successful finger individuation during MI was accompanied by strong desynchronization of sensorimotor brain rhythms, particularly in the beta band, as measured by electroencephalography. Additionally, informative TMS-NF promoted more dissociable EEG activation patterns underlying single finger MI, when compared to MI of the control group where no such feedback was provided. Our findings suggest that selective TMS-NF is a new approach for acquiring the ability of finger individuation even if no overt movements are performed. This might offer new treatment modality for rehabilitation after stroke or spinal cord injury.
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Affiliation(s)
- Ernest Mihelj
- Department of Health Sciences and Technology, Neural Control of Movement Laboratory, ETH Zurich, Auguste-Piccard-Hof 1 Building HPT, Floor EETH, Zurich, Switzerland
| | - Marc Bächinger
- Department of Health Sciences and Technology, Neural Control of Movement Laboratory, ETH Zurich, Auguste-Piccard-Hof 1 Building HPT, Floor EETH, Zurich, Switzerland
| | - Sanne Kikkert
- Department of Health Sciences and Technology, Neural Control of Movement Laboratory, ETH Zurich, Auguste-Piccard-Hof 1 Building HPT, Floor EETH, Zurich, Switzerland
| | - Kathy Ruddy
- Trinity College Institute of Neuroscience and School of Psychology, Trinity College Dublin, Ireland
| | - Nicole Wenderoth
- Department of Health Sciences and Technology, Neural Control of Movement Laboratory, ETH Zurich, Auguste-Piccard-Hof 1 Building HPT, Floor EETH, Zurich, Switzerland; Neuroscience Center Zurich (ZNZ), University of Zurich, Federal Institute of Technology, Zurich, Switzerland; Future Health Technologies, Singapore-ETH Center, Campus for Research Excellence And Technological Enterprise (CREATE), Singapore.
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25
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Robinson N, Chouhan T, Mihelj E, Kratka P, Debraine F, Wenderoth N, Guan C, Lehner R. Design Considerations for Long Term Non-invasive Brain Computer Interface Training With Tetraplegic CYBATHLON Pilot. Front Hum Neurosci 2021; 15:648275. [PMID: 34211380 PMCID: PMC8239283 DOI: 10.3389/fnhum.2021.648275] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2020] [Accepted: 05/17/2021] [Indexed: 11/13/2022] Open
Abstract
Several studies in the recent past have demonstrated how Brain Computer Interface (BCI) technology can uncover the neural mechanisms underlying various tasks and translate them into control commands. While a multitude of studies have demonstrated the theoretic potential of BCI, a point of concern is that the studies are still confined to lab settings and mostly limited to healthy, able-bodied subjects. The CYBATHLON 2020 BCI race represents an opportunity to further develop BCI design strategies for use in real-time applications with a tetraplegic end user. In this study, as part of the preparation to participate in CYBATHLON 2020 BCI race, we investigate the design aspects of BCI in relation to the choice of its components, in particular, the type of calibration paradigm and its relevance for long-term use. The end goal was to develop a user-friendly and engaging interface suited for long-term use, especially for a spinal-cord injured (SCI) patient. We compared the efficacy of conventional open-loop calibration paradigms with real-time closed-loop paradigms, using pre-trained BCI decoders. Various indicators of performance were analyzed for this study, including the resulting classification performance, game completion time, brain activation maps, and also subjective feedback from the pilot. Our results show that the closed-loop calibration paradigms with real-time feedback is more engaging for the pilot. They also show an indication of achieving better online median classification performance as compared to conventional calibration paradigms (p = 0.0008). We also observe that stronger and more localized brain activation patterns are elicited in the closed-loop paradigm in which the experiment interface closely resembled the end application. Thus, based on this longitudinal evaluation of single-subject data, we demonstrate that BCI-based calibration paradigms with active user-engagement, such as with real-time feedback, could help in achieving better user acceptability and performance.
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Affiliation(s)
- Neethu Robinson
- School of Computer Science and Engineering, Nanyang Technological University, Singapore, Singapore
| | - Tushar Chouhan
- School of Computer Science and Engineering, Nanyang Technological University, Singapore, Singapore.,Future Health Technologies, Singapore-ETH Centre, Singapore, Singapore
| | - Ernest Mihelj
- Neural Control of Movement Lab, Department of Health Science and Technology, Swiss Federal Institute of Technology Zurich, Zurich, Switzerland
| | - Paulina Kratka
- Neural Control of Movement Lab, Department of Health Science and Technology, Swiss Federal Institute of Technology Zurich, Zurich, Switzerland
| | - Frédéric Debraine
- Neural Control of Movement Lab, Department of Health Science and Technology, Swiss Federal Institute of Technology Zurich, Zurich, Switzerland
| | - Nicole Wenderoth
- Future Health Technologies, Singapore-ETH Centre, Singapore, Singapore.,Neural Control of Movement Lab, Department of Health Science and Technology, Swiss Federal Institute of Technology Zurich, Zurich, Switzerland
| | - Cuntai Guan
- School of Computer Science and Engineering, Nanyang Technological University, Singapore, Singapore.,Future Health Technologies, Singapore-ETH Centre, Singapore, Singapore
| | - Rea Lehner
- Future Health Technologies, Singapore-ETH Centre, Singapore, Singapore.,Neural Control of Movement Lab, Department of Health Science and Technology, Swiss Federal Institute of Technology Zurich, Zurich, Switzerland
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26
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Lambercy O, Lehner R, Chua K, Wee SK, Rajeswaran DK, Kuah CWK, Ang WT, Liang P, Campolo D, Hussain A, Aguirre-Ollinger G, Guan C, Kanzler CM, Wenderoth N, Gassert R. Neurorehabilitation From a Distance: Can Intelligent Technology Support Decentralized Access to Quality Therapy? Front Robot AI 2021; 8:612415. [PMID: 34026855 PMCID: PMC8132098 DOI: 10.3389/frobt.2021.612415] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2020] [Accepted: 04/20/2021] [Indexed: 12/18/2022] Open
Abstract
Current neurorehabilitation models primarily rely on extended hospital stays and regular therapy sessions requiring close physical interactions between rehabilitation professionals and patients. The current COVID-19 pandemic has challenged this model, as strict physical distancing rules and a shift in the allocation of hospital resources resulted in many neurological patients not receiving essential therapy. Accordingly, a recent survey revealed that the majority of European healthcare professionals involved in stroke care are concerned that this lack of care will have a noticeable negative impact on functional outcomes. COVID-19 highlights an urgent need to rethink conventional neurorehabilitation and develop alternative approaches to provide high-quality therapy while minimizing hospital stays and visits. Technology-based solutions, such as, robotics bear high potential to enable such a paradigm shift. While robot-assisted therapy is already established in clinics, the future challenge is to enable physically assisted therapy and assessments in a minimally supervized and decentralized manner, ideally at the patient’s home. Key enablers are new rehabilitation devices that are portable, scalable and equipped with clinical intelligence, remote monitoring and coaching capabilities. In this perspective article, we discuss clinical and technological requirements for the development and deployment of minimally supervized, robot-assisted neurorehabilitation technologies in patient’s homes. We elaborate on key principles to ensure feasibility and acceptance, and on how artificial intelligence can be leveraged for embedding clinical knowledge for safe use and personalized therapy adaptation. Such new models are likely to impact neurorehabilitation beyond COVID-19, by providing broad access to sustained, high-quality and high-dose therapy maximizing long-term functional outcomes.
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Affiliation(s)
- Olivier Lambercy
- Rehabilitation Engineering Laboratory, Department of Health Sciences and Technology, ETH Zurich, Switzerland.,Future Health Technologies, Singapore-ETH Centre, Campus for Research Excellence and Technological Enterprise (CREATE), Singapore, Singapore
| | - Rea Lehner
- Future Health Technologies, Singapore-ETH Centre, Campus for Research Excellence and Technological Enterprise (CREATE), Singapore, Singapore.,Neural Control of Movement Laboratory, Department of Health Sciences and Technology, ETH Zurich, Switzerland
| | - Karen Chua
- Future Health Technologies, Singapore-ETH Centre, Campus for Research Excellence and Technological Enterprise (CREATE), Singapore, Singapore.,Centre for Advanced Rehabilitation Therapeutics, Tan Tock Seng Hospital Rehabilitation Centre, Singapore, Singapore.,Rehabilitation Research Institute Singapore, Nanyang Technological University, Singapore, Singapore
| | - Seng Kwee Wee
- Future Health Technologies, Singapore-ETH Centre, Campus for Research Excellence and Technological Enterprise (CREATE), Singapore, Singapore.,Centre for Advanced Rehabilitation Therapeutics, Tan Tock Seng Hospital Rehabilitation Centre, Singapore, Singapore.,Singapore Institute of Technology (SIT), Singapore, Singapore
| | - Deshan Kumar Rajeswaran
- Future Health Technologies, Singapore-ETH Centre, Campus for Research Excellence and Technological Enterprise (CREATE), Singapore, Singapore.,Centre for Advanced Rehabilitation Therapeutics, Tan Tock Seng Hospital Rehabilitation Centre, Singapore, Singapore
| | - Christopher Wee Keong Kuah
- Future Health Technologies, Singapore-ETH Centre, Campus for Research Excellence and Technological Enterprise (CREATE), Singapore, Singapore.,Centre for Advanced Rehabilitation Therapeutics, Tan Tock Seng Hospital Rehabilitation Centre, Singapore, Singapore
| | - Wei Tech Ang
- Future Health Technologies, Singapore-ETH Centre, Campus for Research Excellence and Technological Enterprise (CREATE), Singapore, Singapore.,Rehabilitation Research Institute Singapore, Nanyang Technological University, Singapore, Singapore.,School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore, Singapore
| | - Phyllis Liang
- Future Health Technologies, Singapore-ETH Centre, Campus for Research Excellence and Technological Enterprise (CREATE), Singapore, Singapore.,Rehabilitation Research Institute Singapore, Nanyang Technological University, Singapore, Singapore
| | - Domenico Campolo
- Future Health Technologies, Singapore-ETH Centre, Campus for Research Excellence and Technological Enterprise (CREATE), Singapore, Singapore.,School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore, Singapore
| | - Asif Hussain
- Future Health Technologies, Singapore-ETH Centre, Campus for Research Excellence and Technological Enterprise (CREATE), Singapore, Singapore.,School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore, Singapore.,Articares Pte Ltd, Singapore, Singapore
| | | | - Cuntai Guan
- Future Health Technologies, Singapore-ETH Centre, Campus for Research Excellence and Technological Enterprise (CREATE), Singapore, Singapore.,School of Computer Science and Engineering, Nanyang Technological University, Singapore, Singapore
| | - Christoph M Kanzler
- Rehabilitation Engineering Laboratory, Department of Health Sciences and Technology, ETH Zurich, Switzerland.,Future Health Technologies, Singapore-ETH Centre, Campus for Research Excellence and Technological Enterprise (CREATE), Singapore, Singapore
| | - Nicole Wenderoth
- Future Health Technologies, Singapore-ETH Centre, Campus for Research Excellence and Technological Enterprise (CREATE), Singapore, Singapore.,Neural Control of Movement Laboratory, Department of Health Sciences and Technology, ETH Zurich, Switzerland
| | - Roger Gassert
- Rehabilitation Engineering Laboratory, Department of Health Sciences and Technology, ETH Zurich, Switzerland.,Future Health Technologies, Singapore-ETH Centre, Campus for Research Excellence and Technological Enterprise (CREATE), Singapore, Singapore
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27
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Alaerts K, Steyaert J, Vanaudenaerde B, Wenderoth N, Bernaerts S. Changes in endogenous oxytocin levels after intranasal oxytocin treatment in adult men with autism: An exploratory study with long-term follow-up. Eur Neuropsychopharmacol 2021; 43:147-152. [PMID: 33309460 DOI: 10.1016/j.euroneuro.2020.11.014] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Revised: 11/27/2020] [Accepted: 11/30/2020] [Indexed: 02/03/2023]
Abstract
Intranasal administration of the neuropeptide oxytocin (OT) is increasingly explored as a potential treatment for targeting the core symptoms of autism spectrum disorder (ASD). Previously, interactions of exogenously administered OT with its endogenous production have been demonstrated following single-dose administrations. However, the impact of repeated, long-term OT use on endogenous salivary OT levels is unknown. In this double-blind, randomized, placebo-controlled study with between-subject design, 34 adult men with ASD were either assigned to a four-week treatment of once-daily intranasal OT administrations (24 IU) or placebo. Salivary OT samples were obtained before and after the treatment period as well as at two follow-up sessions, four weeks and one year after cessation of the treatment. Receiving OT intranasally but not placebo reliably increased endogenous salivary levels of OT immediately post-treatment and at the follow-up session four weeks post treatment, indicating an interaction between exogenously administered OT and its endogenous production. Notably, increases in salivary OT at the four-week follow-up session were most pronounced in individuals with larger behavioral improvements in ASD social symptoms. These results suggest that OT's positive effects on social behaviors may lead to a self-perpetuating elevation of OT levels through a feed-forward triggering of its own release. Together, the current investigation provides initial evidence that repeated intranasal administration of OT can induce long-lasting changes in endogenous salivary OT levels, presumably through a positive spiral of OT release.
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Affiliation(s)
- Kaat Alaerts
- University of Leuven, KU Leuven, Belgium, Department of Rehabilitation Sciences, Group Biomedical Sciences, Neurorehabilitation Research Group, Belgium; Leuven Autism Research Consortium, KU Leuven, Belgium.
| | - Jean Steyaert
- University of Leuven, KU Leuven, Belgium, Department of Neurosciences, Group Biomedical Sciences, Psychiatry Research Group, Belgium; Leuven Autism Research Consortium, KU Leuven, Belgium
| | - Bart Vanaudenaerde
- University of Leuven, KU Leuven, Belgium, Department of Chronic Diseases, Metabolism and Ageing, Group Biomedical Sciences, Pneumology Research Group, Belgium
| | - Nicole Wenderoth
- ETH Zurich, Switzerland, Department of Health Sciences and Technology, Neural Control of Movement Lab, Switzerland
| | - Sylvie Bernaerts
- University of Leuven, KU Leuven, Belgium, Department of Rehabilitation Sciences, Group Biomedical Sciences, Neurorehabilitation Research Group, Belgium; Leuven Autism Research Consortium, KU Leuven, Belgium
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28
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Lambelet C, Temiraliuly D, Siegenthaler M, Wirth M, Woolley DG, Lambercy O, Gassert R, Wenderoth N. Characterization and wearability evaluation of a fully portable wrist exoskeleton for unsupervised training after stroke. J Neuroeng Rehabil 2020; 17:132. [PMID: 33028354 PMCID: PMC7541267 DOI: 10.1186/s12984-020-00749-4] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2019] [Accepted: 08/24/2020] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND Chronic hand and wrist impairment are frequently present following stroke and severely limit independence in everyday life. The wrist orientates and stabilizes the hand before and during grasping, and is therefore of critical importance in activities of daily living (ADL). To improve rehabilitation outcomes, classical therapy could be supplemented by novel therapies that can be applied in unsupervised settings. This would enable more distributed practice and could potentially increase overall training dose. Robotic technology offers new possibilities to address this challenge, but it is critical that devices for independent training are easy and appealing to use. Here, we present the development, characterization and wearability evaluation of a fully portable exoskeleton for active wrist extension/flexion support in stroke rehabilitation. METHODS First we defined the requirements, and based on these, constructed the exoskeleton. We then characterized the device with standardized haptic and human-robot interaction metrics. The exoskeleton is composed of two modules placed on the forearm/hand and the upper arm. These modules weigh 238 g and 224 g, respectively. The forearm module actively supports wrist extension and flexion with a torque up to 3.7 Nm and an angular velocity up to 530 deg/s over a range of 154∘. The upper arm module includes the control electronics and battery, which can power the device for about 125 min in normal use. Special emphasis was put on independent donning and doffing of the device, which was tested via a wearability evaluation in 15 healthy participants and 2 stroke survivors using both qualitative and quantitative methods. RESULTS All participants were able to independently don and doff the device after only 4 practice trials. For healthy participants the donning and doffing process took 61 ±15 s and 24 ±6 s, respectively. The two stroke survivors donned and doffed the exoskeleton in 54 s/22 s and 113 s/32 s, respectively. Usability questionnaires revealed that despite minor difficulties, all participants were positive regarding the device. CONCLUSIONS This study describes an actuated wrist exoskeleton which weighs less than 500 g, and which is easy and fast to don and doff with one hand. Our design has put special emphasis on the donning aspect of robotic devices which constitutes the first barrier a user will face in unsupervised settings. The proposed device is a first and intermediate step towards wearable rehabilitation technologies that can be used independently by the patient and in unsupervised settings.
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Affiliation(s)
- Charles Lambelet
- Neural Control of Movement Lab, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
| | - Damir Temiraliuly
- Neural Control of Movement Lab, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
| | - Marc Siegenthaler
- Neural Control of Movement Lab, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
| | - Marc Wirth
- Neural Control of Movement Lab, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
| | - Daniel G. Woolley
- Neural Control of Movement Lab, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
| | - Olivier Lambercy
- Rehabilitation Engineering Laboratory, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
| | - Roger Gassert
- Rehabilitation Engineering Laboratory, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
| | - Nicole Wenderoth
- Neural Control of Movement Lab, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
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29
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Samogin J, Marino M, Porcaro C, Wenderoth N, Dupont P, Swinnen SP, Mantini D. Frequency-dependent functional connectivity in resting state networks. Hum Brain Mapp 2020; 41:5187-5198. [PMID: 32840936 PMCID: PMC7670639 DOI: 10.1002/hbm.25184] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2020] [Accepted: 08/07/2020] [Indexed: 12/27/2022] Open
Abstract
Functional magnetic resonance imaging studies have documented the resting human brain to be functionally organized in multiple large‐scale networks, called resting‐state networks (RSNs). Other brain imaging techniques, such as electroencephalography (EEG) and magnetoencephalography (MEG), have been used for investigating the electrophysiological basis of RSNs. To date, it is largely unclear how neural oscillations measured with EEG and MEG are related to functional connectivity in the resting state. In addition, it remains to be elucidated whether and how the observed neural oscillations are related to the spatial distribution of the network nodes over the cortex. To address these questions, we examined frequency‐dependent functional connectivity between the main nodes of several RSNs, spanning large part of the cortex. We estimated connectivity using band‐limited power correlations from high‐density EEG data collected in healthy participants. We observed that functional interactions within RSNs are characterized by a specific combination of neuronal oscillations in the alpha (8–13 Hz), beta (13–30 Hz), and gamma (30–80 Hz) bands, which highly depend on the position of the network nodes. This finding may contribute to a better understanding of the mechanisms through which neural oscillations support functional connectivity in the brain.
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Affiliation(s)
- Jessica Samogin
- Research Center for Motor Control and Neuroplasticity, KU Leuven, Leuven, Belgium
| | - Marco Marino
- Research Center for Motor Control and Neuroplasticity, KU Leuven, Leuven, Belgium.,Brain Imaging and Neural Dynamics Research Group, IRCCS San Camillo Hospital, Venice, Italy
| | - Camillo Porcaro
- Research Center for Motor Control and Neuroplasticity, KU Leuven, Leuven, Belgium.,Institute of Cognitive Sciences and Technologies (ISTC), National Research Council (CNR), Rome, Italy.,Centre for Human Brain Health and School of Psychology, University of Birmingham, Birmingham, UK.,Department of Information Engineering, Università Politecnica delle Marche, Ancona, Italy.,Research in Advanced Neurorehabilitation, S. Anna Istitute, Crotone, Italy
| | - Nicole Wenderoth
- Neural Control of Movement Lab, Department of Health Sciences, ETH Zurich, Zurich, Switzerland
| | - Patrick Dupont
- KU Leuven Brain Institute, KU Leuven, Leuven, Belgium.,Laboratory for Cognitive Neurology, KU Leuven, Leuven, Belgium
| | - Stephan P Swinnen
- Research Center for Motor Control and Neuroplasticity, KU Leuven, Leuven, Belgium.,KU Leuven Brain Institute, KU Leuven, Leuven, Belgium
| | - Dante Mantini
- Research Center for Motor Control and Neuroplasticity, KU Leuven, Leuven, Belgium.,Brain Imaging and Neural Dynamics Research Group, IRCCS San Camillo Hospital, Venice, Italy
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30
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Wälti MJ, Woolley DG, Wenderoth N. Assessing Rhythmic Visual Entrainment and Reinstatement of Brain Oscillations to Modulate Memory Performance. Front Behav Neurosci 2020; 14:118. [PMID: 32765231 PMCID: PMC7378394 DOI: 10.3389/fnbeh.2020.00118] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2019] [Accepted: 06/15/2020] [Indexed: 11/13/2022] Open
Abstract
The human brain’s ability to store information and remember past events is thought to be orchestrated by the synchronization of neuronal oscillations in various frequency bands. A vast amount of research has found that neural oscillations in the theta (∼4–7 Hz) and alpha (∼8–12 Hz) bands play an important role in memory formation. More specifically, it has been suggested that memory performance benefits if the same oscillatory pattern is present during encoding and retrieval. However, the causal relevance of these oscillations is not well understood. Rhythmic sensory stimulation is thought to entrain ongoing brain oscillations and modulate associated functions (e.g., memory formation). In the present study, we used rhythmic visual stimulation at 6 and 10 Hz to experimentally modulate the memory encoding process in a recognition memory task. In addition, we reinstated oscillatory activity from the encoding episode during retrieval, which has been hypothesized to result in memory performance improvements compared to non-reinstated conditions and incongruent reinstatement. Contrary to our hypothesis, we find no effect of neural entrainment during encoding on subsequent memory performance. Likewise, memory retrieval does not benefit from neural reinstatement. The results are discussed with respect to methodological challenges of rhythmic sensory stimulation as a means to alter cognitive processes and induce context-dependent memory effects.
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Affiliation(s)
- Michel J Wälti
- Neural Control of Movement Lab, Department of Health Sciences and Technology, ETH Zürich, Zurich, Switzerland.,Cognition, Perception and Behaviour in Urban Environments, Future Cities Laboratory, Singapore-ETH Centre, Singapore, Singapore.,Neuroscience Center Zurich (ZNZ), University and ETH Zürich, Zurich, Switzerland
| | - Daniel G Woolley
- Neural Control of Movement Lab, Department of Health Sciences and Technology, ETH Zürich, Zurich, Switzerland
| | - Nicole Wenderoth
- Neural Control of Movement Lab, Department of Health Sciences and Technology, ETH Zürich, Zurich, Switzerland.,Neuroscience Center Zurich (ZNZ), University and ETH Zürich, Zurich, Switzerland
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31
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Bikson M, Hanlon CA, Woods AJ, Gillick BT, Charvet L, Lamm C, Madeo G, Holczer A, Almeida J, Antal A, Ay MR, Baeken C, Blumberger DM, Campanella S, Camprodon JA, Christiansen L, Loo C, Crinion JT, Fitzgerald P, Gallimberti L, Ghobadi-Azbari P, Ghodratitoostani I, Grabner RH, Hartwigsen G, Hirata A, Kirton A, Knotkova H, Krupitsky E, Marangolo P, Nakamura-Palacios EM, Potok W, Praharaj SK, Ruff CC, Schlaug G, Siebner HR, Stagg CJ, Thielscher A, Wenderoth N, Yuan TF, Zhang X, Ekhtiari H. Guidelines for TMS/tES clinical services and research through the COVID-19 pandemic. Brain Stimul 2020; 13:1124-1149. [PMID: 32413554 PMCID: PMC7217075 DOI: 10.1016/j.brs.2020.05.010] [Citation(s) in RCA: 64] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2020] [Accepted: 05/10/2020] [Indexed: 01/10/2023] Open
Abstract
BACKGROUND The COVID-19 pandemic has broadly disrupted biomedical treatment and research including non-invasive brain stimulation (NIBS). Moreover, the rapid onset of societal disruption and evolving regulatory restrictions may not have allowed for systematic planning of how clinical and research work may continue throughout the pandemic or be restarted as restrictions are abated. The urgency to provide and develop NIBS as an intervention for diverse neurological and mental health indications, and as a catalyst of fundamental brain research, is not dampened by the parallel efforts to address the most life-threatening aspects of COVID-19; rather in many cases the need for NIBS is heightened including the potential to mitigate mental health consequences related to COVID-19. OBJECTIVE To facilitate the re-establishment of access to NIBS clinical services and research operations during the current COVID-19 pandemic and possible future outbreaks, we develop and discuss a framework for balancing the importance of NIBS operations with safety considerations, while addressing the needs of all stakeholders. We focus on Transcranial Magnetic Stimulation (TMS) and low intensity transcranial Electrical Stimulation (tES) - including transcranial Direct Current Stimulation (tDCS) and transcranial Alternating Current Stimulation (tACS). METHODS The present consensus paper provides guidelines and good practices for managing and reopening NIBS clinics and laboratories through the immediate and ongoing stages of COVID-19. The document reflects the analysis of experts with domain-relevant expertise spanning NIBS technology, clinical services, and basic and clinical research - with an international perspective. We outline regulatory aspects, human resources, NIBS optimization, as well as accommodations for specific demographics. RESULTS A model based on three phases (early COVID-19 impact, current practices, and future preparation) with an 11-step checklist (spanning removing or streamlining in-person protocols, incorporating telemedicine, and addressing COVID-19-associated adverse events) is proposed. Recommendations on implementing social distancing and sterilization of NIBS related equipment, specific considerations of COVID-19 positive populations including mental health comorbidities, as well as considerations regarding regulatory and human resource in the era of COVID-19 are outlined. We discuss COVID-19 considerations specifically for clinical (sub-)populations including pediatric, stroke, addiction, and the elderly. Numerous case-examples across the world are described. CONCLUSION There is an evident, and in cases urgent, need to maintain NIBS operations through the COVID-19 pandemic, including anticipating future pandemic waves and addressing effects of COVID-19 on brain and mind. The proposed robust and structured strategy aims to address the current and anticipated future challenges while maintaining scientific rigor and managing risk.
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Affiliation(s)
- Marom Bikson
- Department of Biomedical Engineering, The City College of New York of CUNY, New York, NY, USA
| | - Colleen A Hanlon
- Department of Cancer Biology, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Adam J Woods
- Center for Cognitive Aging and Memory, McKnight Brain Institute, Department of Clinical and Health Psychology, University of Florida, Gainesville, FL, USA
| | - Bernadette T Gillick
- Department of Rehabilitation Medicine, School of Medicine, University of Minnesota, MN, Minneapolis, USA
| | - Leigh Charvet
- Department of Neurology, NYU Grossman School of Medicine, New York, NY, USA
| | - Claus Lamm
- Social, Cognitive and Affective Neuroscience Unit, Department of Cognition, Emotion, and Methods in Psychology, Faculty of Psychology, University of Vienna, Vienna, Austria
| | | | - Adrienn Holczer
- Department of Neurology, Albert Szent-Györgyi Health Center, Faculty of Medicine, University of Szeged, Hungary
| | - Jorge Almeida
- Proaction Lab, Faculty of Psychology and Educational Sciences, University of Coimbra, Portugal; CINEICC, Faculty of Psychology and Educational Sciences, University of Coimbra, Portugal
| | - Andrea Antal
- Department of Clinical Neurophysiology, University Medical Center Göttingen, Göttingen, Germany; Institute of Medical Psychology, Otto-von-Guericke University Magdeburg, Magdeburg, Germany
| | - Mohammad Reza Ay
- Department of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences, Tehran, Iran
| | - Chris Baeken
- Faculty of Medicine and Health Sciences, Ghent Experimental Psychiatry (GHEP) Lab, Ghent University, Ghent, Belgium; Department of Psychiatry, University Hospital (UZBrussel), Brussels, Belgium; Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, the Netherlands
| | - Daniel M Blumberger
- Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, Canada; Department of Psychiatry, Faculty of Medicine, University of Toronto, Toronto, Canada
| | - Salvatore Campanella
- Laboratoire de Psychologie Médicale et D'Addiction, ULB Neuroscience Institute (UNI), Université Libre de Bruxelles (ULB), Place Vangehuchten, B-1020, Brussels, Belgium
| | - Joan A Camprodon
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Lasse Christiansen
- Danish Research Centre for Magnetic Resonance (DRCMR), Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark
| | - Colleen Loo
- School of Psychiatry & Black Dog Institute, University of New South Wales, Sydney, Australia
| | - Jennifer T Crinion
- Institute of Cognitive Neuroscience, University College London, London, UK
| | - Paul Fitzgerald
- Epworth Centre for Innovation in Mental Health, Epworth HealthCare and Department of Psychiatry, Monash University, Camberwell, Victoria, Australia
| | | | - Peyman Ghobadi-Azbari
- Department of Biomedical Engineering, Shahed University, Tehran, Iran; Iranian National Center for Addiction Studies (INCAS), Tehran, Iran
| | - Iman Ghodratitoostani
- Neurocognitive Engineering Laboratory (NEL), Center for Mathematical Sciences Applied to Industry, Institute of Mathematical and Computer Sciences, University of Sao Paulo, Brazil
| | - Roland H Grabner
- Educational Neuroscience, Institute of Psychology, University of Graz, Austria
| | - Gesa Hartwigsen
- Lise Meitner Research Group Cognition and Plasticity, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Akimasa Hirata
- Department of Electrical and Mechanical Engineering, Nagoya Institute of Technology, Nagoya, Japan
| | - Adam Kirton
- Departments of Pediatrics and Clinical Neuroscience, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Helena Knotkova
- MJHS Institute for Innovation in Palliative Care, New York, NY, USA; Department of Family and Social Medicine, Albert Einstein College of Medicine, The Bronx, NY, USA
| | - Evgeny Krupitsky
- First Pavlov State Medical University, V. M. Bekhterev National Research Medical Center for Psychiatry and Neurology, St. Petersburg, Russia
| | - Paola Marangolo
- Department of Humanities Studies, University Federico II, Naples, Italy; Aphasia Research Lab, IRCCS Santa Lucia Foundation, Rome, Italy
| | | | - Weronika Potok
- Neural Control of Movement Lab, Department of Health Science and Technology, ETH Zurich, Switzerland
| | - Samir K Praharaj
- Department of Psychiatry, Kasturba Medical College, Manipal, Manipal Academy of Higher Education, Manipal, India
| | - Christian C Ruff
- Zurich Center for Neuroeconomics (ZNE), Department of Economics, University of Zurich, Zurich, Switzerland
| | - Gottfried Schlaug
- Neuroimaging-Neuromodulation and Stroke Recovery Laboratory, Department of Neurology, Beth Israel Deaconess Medical Center and Baystate Medical Center, UMass Medical School, MA, USA
| | - Hartwig R Siebner
- Danish Research Centre for Magnetic Resonance (DRCMR), Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark; Institute of Clinical Medicine, Faculty of Health Sciences and Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Charlotte J Stagg
- Wellcome Centre for Integrative Neuroimaging and MRC Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Axel Thielscher
- Danish Research Centre for Magnetic Resonance (DRCMR), Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark; Department of Health Technology, Technical University of Denmark, Kgs. Lyngby, Denmark
| | - Nicole Wenderoth
- Neural Control of Movement Lab, Department of Health Science and Technology, ETH Zurich, Switzerland
| | - Ti-Fei Yuan
- Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Xiaochu Zhang
- CAS Key Laboratory of Brain Function and Disease and School of Life Sciences, Division of Life Science and Medicine, University of Science & Technology of China, Hefei, China
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32
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Mailleux L, Simon-Martinez C, Radwan A, Blommaert J, Gooijers J, Wenderoth N, Klingels K, Ortibus E, Sunaert S, Feys H. White matter characteristics of motor, sensory and interhemispheric tracts underlying impaired upper limb function in children with unilateral cerebral palsy. Brain Struct Funct 2020; 225:1495-1509. [PMID: 32318818 DOI: 10.1007/s00429-020-02070-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2018] [Accepted: 04/11/2020] [Indexed: 12/19/2022]
Abstract
This study explored the role of lesion timing (periventricular white matter versus cortical and deep grey matter lesions) and type of corticospinal tract (CST) wiring pattern (contralateral, bilateral, ipsilateral) on white matter characteristics of the CST, medial lemniscus, superior thalamic radiations and sensorimotor transcallosal fibers in children with unilateral cerebral palsy (CP), and examined the association with upper limb function. Thirty-four children (mean age 10 years 7 months ± 2 years 3 months) with unilateral CP underwent a comprehensive upper limb evaluation and diffusion weighted imaging (75 directions, b value 2800). Streamline count, fractional anisotropy and mean diffusivity were extracted from the targeted tracts and asymmetry indices were additionally calculated. Transcranial magnetic stimulation was applied to assess the CST wiring pattern. Results showed a more damaged CST in children with cortical and deep grey matter lesions (N = 10) and ipsilateral CST projections (N = 11) compared to children with periventricular white matter lesions (N = 24; p < 0.02) and contralateral CST projections (N = 9; p < 0.025), respectively. Moderate to high correlations were found between diffusion metrics of the targeted tracts and upper limb function (r = 0.45-0.72; p < 0.01). Asymmetry indices of the CST and sensory tracts could best explain bimanual performance (74%, p < 0.0001) and unimanual capacity (50%, p = 0.004). Adding lesion timing and CST wiring pattern did not further improve the model of bimanual performance, while for unimanual capacity lesion timing was additionally retained (58%, p = 0.0002). These results contribute to a better understanding of the underlying neuropathology of upper limb function in children with unilateral CP and point towards a clinical potential of tractography.
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Affiliation(s)
- Lisa Mailleux
- Department of Rehabilitation Sciences, KU Leuven, Leuven, Belgium.
| | | | - Ahmed Radwan
- Department of Imaging and Pathology, KU Leuven, Leuven, Belgium
| | | | | | - Nicole Wenderoth
- Department of Movement Sciences, KU Leuven, Leuven, Belgium.,Neural Control of Movement Lab, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
| | - Katrijn Klingels
- Department of Rehabilitation Sciences, KU Leuven, Leuven, Belgium.,BIOMED, Rehabilitation Research Center (REVAL), UHasselt, Diepenbeek, Belgium
| | - Els Ortibus
- Department of Development and Regeneration, KU Leuven, Leuven, Belgium
| | - Stefan Sunaert
- Department of Imaging and Pathology, KU Leuven, Leuven, Belgium
| | - Hilde Feys
- Department of Rehabilitation Sciences, KU Leuven, Leuven, Belgium
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33
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Markicevic M, Fulcher BD, Lewis C, Helmchen F, Rudin M, Zerbi V, Wenderoth N. Cortical Excitation:Inhibition Imbalance Causes Abnormal Brain Network Dynamics as Observed in Neurodevelopmental Disorders. Cereb Cortex 2020; 30:4922-4937. [PMID: 32313923 PMCID: PMC7391279 DOI: 10.1093/cercor/bhaa084] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
Abnormal brain development manifests itself at different spatial scales. However, whether abnormalities at the cellular level can be diagnosed from network activity measured with functional magnetic resonance imaging (fMRI) is largely unknown, yet of high clinical relevance. Here a putative mechanism reported in neurodevelopmental disorders, that is, excitation-to-inhibition ratio (E:I), was chemogenetically increased within cortical microcircuits of the mouse brain and measured via fMRI. Increased E:I caused a significant "reduction" of long-range connectivity, irrespective of whether excitatory neurons were facilitated or inhibitory Parvalbumin (PV) interneurons were suppressed. Training a classifier on fMRI signals, we were able to accurately classify cortical areas exhibiting increased E:I. This classifier was validated in an independent cohort of Fmr1y/- knockout mice, a model for autism with well-documented loss of parvalbumin neurons and chronic alterations of E:I. Our findings demonstrate a promising novel approach towards inferring microcircuit abnormalities from macroscopic fMRI measurements.
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Affiliation(s)
- Marija Markicevic
- Neural Control of Movement Lab, HEST, ETH Zürich, 8093 Zurich, Switzerland.,Neuroscience Center Zurich, University and ETH Zurich, 8057 Zurich, Switzerland
| | - Ben D Fulcher
- School of Physics, The University of Sydney, NSW 2006, Australia
| | - Christopher Lewis
- Brain Research Institute, University of Zurich, 8057 Zurich, Switzerland
| | - Fritjof Helmchen
- Neuroscience Center Zurich, University and ETH Zurich, 8057 Zurich, Switzerland.,Brain Research Institute, University of Zurich, 8057 Zurich, Switzerland
| | - Markus Rudin
- Neuroscience Center Zurich, University and ETH Zurich, 8057 Zurich, Switzerland.,Institute of Pharmacology and Toxicology, University of Zurich, 8057 Zurich, Switzerland.,Institute for Biomedical Engineering, University and ETH Zurich, 8093 Zurich, Switzerland
| | - Valerio Zerbi
- Neural Control of Movement Lab, HEST, ETH Zürich, 8093 Zurich, Switzerland.,Neuroscience Center Zurich, University and ETH Zurich, 8057 Zurich, Switzerland
| | - Nicole Wenderoth
- Neural Control of Movement Lab, HEST, ETH Zürich, 8093 Zurich, Switzerland.,Neuroscience Center Zurich, University and ETH Zurich, 8057 Zurich, Switzerland
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Abstract
With the increasing necessity of animal models in biomedical research, there is a vital need to harmonise findings across species by establishing similarities and differences in rodent and primate neuroanatomy. Using connectivity fingerprint matching, we compared cortico-striatal circuits across humans, non-human primates, and mice using resting-state fMRI data in all species. Our results suggest that the connectivity patterns for the nucleus accumbens and cortico-striatal motor circuits (posterior/lateral putamen) were conserved across species, making them reliable targets for cross-species comparisons. However, a large number of human and macaque striatal voxels were not matched to any mouse cortico-striatal circuit (mouse->human: 85% unassigned; mouse->macaque 69% unassigned; macaque->human; 31% unassigned). These unassigned voxels were localised to the caudate nucleus and anterior putamen, overlapping with executive function and social/language regions of the striatum and connected to prefrontal-projecting cerebellar lobules and anterior prefrontal cortex, forming circuits that seem to be unique for non-human primates and humans.
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Affiliation(s)
- Joshua Henk Balsters
- Department of Psychology, Royal Holloway University of LondonEghamUnited Kingdom
- Neural Control of Movement Laboratory, Department of Health Sciences and TechnologyETH ZurichSwitzerland
| | - Valerio Zerbi
- Neural Control of Movement Laboratory, Department of Health Sciences and TechnologyETH ZurichSwitzerland
| | - Jerome Sallet
- Wellcome Centre for Integrative Neuroimaging, Department of Experimental Psychology, University of OxfordOxfordUnited Kingdom
| | - Nicole Wenderoth
- Neural Control of Movement Laboratory, Department of Health Sciences and TechnologyETH ZurichSwitzerland
| | - Rogier B Mars
- Wellcome Centre for Integrative Neuroimaging, Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of OxfordOxfordUnited Kingdom
- Donders Institute for Brain, Cognition and Behaviour, Radboud University NijmegenNijmegenNetherlands
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Cretu AL, Ruddy KL, Post A, Wenderoth N. Muscle-specific modulation of indirect inputs to primary motor cortex during action observation. Exp Brain Res 2020; 238:1735-1744. [PMID: 32266444 DOI: 10.1007/s00221-020-05801-2] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2019] [Accepted: 03/25/2020] [Indexed: 01/22/2023]
Abstract
Single-pulse transcranial magnetic stimulation (spTMS) studies report that movement observation facilitates corticospinal excitability in primary motor cortex (M1) in a muscle-specific manner. However, motor evoked potentials (MEPs) elicited by spTMS are known to reflect the summation of several descending volleys in corticospinal neurons which are evoked via mono- and polysynaptic inputs (so-called indirect waves or I-waves). It is unclear which of these components contribute to the muscle-specific modulation of M1 during action observation. The interactions between different I-waves are reflected in the facilitatory peaks elicited with a short-intracortical facilitation (SICF) protocol when two pulses are sent to M1 at precise intervals (i.e., 1.3, 2.5 or 4.1 ms). Here, we explored the modulation of early and late SICF peaks during action observation by measuring highly specific MEP amplitude changes measured in two muscles (index, FDI and little finger, ADM) while participants observed two different actions (precision and whole-hand grip). Our results demonstrate that both early (1.3 ms) and late (2.5 and 4.1 ms) SICF peaks are modulated in the context of movement observation. However, only the second peak (ISI 2.5 ms) was significantly associated with the muscle-specific modulation of corticospinal excitability as measured with spTMS. This late SICF peak is believed to reflect the activity cortico-cortical pathways involved in the facilitation of muscle-specific representations in M1. Thus, our findings suggest that movement observation leads to widespread activation of different neural circuits within M1, including those mediating cortico-cortical communication.
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Affiliation(s)
- Andreea Loredana Cretu
- Neural Control of Movement Lab, Department of Health Science and Technology, Swiss Federal Institute of Technology Zurich, Zurich, Switzerland.
| | - Kathy L Ruddy
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin 2, Ireland
| | - Alain Post
- Neural Control of Movement Lab, Department of Health Science and Technology, Swiss Federal Institute of Technology Zurich, Zurich, Switzerland
| | - Nicole Wenderoth
- Neural Control of Movement Lab, Department of Health Science and Technology, Swiss Federal Institute of Technology Zurich, Zurich, Switzerland
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36
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Simon-Martinez C, Mailleux L, Hoskens J, Ortibus E, Jaspers E, Wenderoth N, Sgandurra G, Cioni G, Molenaers G, Klingels K, Feys H. Randomized controlled trial combining constraint-induced movement therapy and action-observation training in unilateral cerebral palsy: clinical effects and influencing factors of treatment response. Ther Adv Neurol Disord 2020; 13:1756286419898065. [PMID: 32031542 PMCID: PMC6977217 DOI: 10.1177/1756286419898065] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2019] [Accepted: 12/09/2019] [Indexed: 01/21/2023] Open
Abstract
Introduction: Constraint-induced movement therapy (CIMT) improves upper limb (UL) motor
execution in unilateral cerebral palsy (uCP). As these children also show
motor planning deficits, action-observation training (AOT) might be of
additional value. Here, we investigated the combined effect of AOT to CIMT
and identified factors influencing treatment response. Methods: A total of 44 children with uCP (mean 9 years 6 months, SD 1 year 10 months)
participated in a 9-day camp wearing a splint for 6 h/day and were allocated
to the CIMT + AOT (n = 22) and the CIMT + placebo group
(n = 22). The CIMT + AOT group received 15 h of AOT
(i.e. video-observation) and executed the observed tasks, whilst the
CIMT + AOT group watched videos free of biological motion and executed the
same tasks. The primary outcome measure was bimanual performance. Secondary
outcomes included measures of body function and activity level assessed
before (T1), after the intervention (T2), and at 6 months follow-up (T3).
Influencing factors included behavioural and neurological
characteristics. Results: Although no between-groups differences were found
(p > 0.05; η2 = 0–16), the addition of AOT
led to higher gains in children with initially poorer bimanual performance
(p = 0.02; η2 = 0.14). Both groups improved
in all outcome measures after the intervention and retained the gains at
follow up (p < 0.01; η2 = 0.02–0.71). Poor
sensory function resulted in larger improvements in the total group
(p = 0.03; η2 = 0.25) and high amounts of
mirror movements tended to result in a better response to the additional AOT
training (p = 0.06; η2 = 0.18). Improvements
were similar irrespective of the type of brain lesion or corticospinal tract
wiring pattern. Conclusions: Adding AOT to CIMT, resulted in a better outcome for children with poor motor
function and high amounts of mirror movements. CIMT with or without AOT
seems to be more beneficial for children with poor sensory function. Trial registration: Registered at ClinicalTrials.gov on 22nd August 2017 (ClinicalTrials.gov
identifier: NCT03256357).
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Affiliation(s)
- Cristina Simon-Martinez
- KU Leuven, Department of Rehabilitation Sciences, Herestraat 49, bus 1510, Leuven, 3000, Belgium
| | - Lisa Mailleux
- KU Leuven, Department of Rehabilitation Sciences, Leuven, Belgium
| | - Jasmine Hoskens
- KU Leuven, Department of Rehabilitation Sciences, Leuven, Belgium
| | - Els Ortibus
- KU Leuven, Department of Development and Regeneration, Leuven, Belgium
| | - Ellen Jaspers
- Neural Control of Movement Lab, Department of Health Sciences and Technology, ETH Zurich, Switzerland
| | - Nicole Wenderoth
- Neural Control of Movement Lab, Department of Health Sciences and Technology, ETH Zurich, Switzerland
| | - Giuseppina Sgandurra
- Department of Developmental Neuroscience, IRCCS Fondazione Stella Maris, Calambrone, Italy
| | - Giovanni Cioni
- Department of Developmental Neuroscience, IRCCS Fondazione Stella Maris, Calambrone, Italy
| | - Guy Molenaers
- KU Leuven, Department of Development and Regeneration, Leuven, Belgium
| | - Katrijn Klingels
- KU Leuven, Department of Rehabilitation Sciences, Leuven, Belgium
| | - Hilde Feys
- KU Leuven, Department of Rehabilitation Sciences, Leuven, Belgium
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37
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Grandjean J, Canella C, Anckaerts C, Ayrancı G, Bougacha S, Bienert T, Buehlmann D, Coletta L, Gallino D, Gass N, Garin CM, Nadkarni NA, Hübner NS, Karatas M, Komaki Y, Kreitz S, Mandino F, Mechling AE, Sato C, Sauer K, Shah D, Strobelt S, Takata N, Wank I, Wu T, Yahata N, Yeow LY, Yee Y, Aoki I, Chakravarty MM, Chang WT, Dhenain M, von Elverfeldt D, Harsan LA, Hess A, Jiang T, Keliris GA, Lerch JP, Meyer-Lindenberg A, Okano H, Rudin M, Sartorius A, Van der Linden A, Verhoye M, Weber-Fahr W, Wenderoth N, Zerbi V, Gozzi A. Common functional networks in the mouse brain revealed by multi-centre resting-state fMRI analysis. Neuroimage 2019; 205:116278. [PMID: 31614221 DOI: 10.1016/j.neuroimage.2019.116278] [Citation(s) in RCA: 111] [Impact Index Per Article: 22.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2019] [Revised: 10/04/2019] [Accepted: 10/11/2019] [Indexed: 01/07/2023] Open
Abstract
Preclinical applications of resting-state functional magnetic resonance imaging (rsfMRI) offer the possibility to non-invasively probe whole-brain network dynamics and to investigate the determinants of altered network signatures observed in human studies. Mouse rsfMRI has been increasingly adopted by numerous laboratories worldwide. Here we describe a multi-centre comparison of 17 mouse rsfMRI datasets via a common image processing and analysis pipeline. Despite prominent cross-laboratory differences in equipment and imaging procedures, we report the reproducible identification of several large-scale resting-state networks (RSN), including a mouse default-mode network, in the majority of datasets. A combination of factors was associated with enhanced reproducibility in functional connectivity parameter estimation, including animal handling procedures and equipment performance. RSN spatial specificity was enhanced in datasets acquired at higher field strength, with cryoprobes, in ventilated animals, and under medetomidine-isoflurane combination sedation. Our work describes a set of representative RSNs in the mouse brain and highlights key experimental parameters that can critically guide the design and analysis of future rodent rsfMRI investigations.
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Affiliation(s)
- Joanes Grandjean
- Singapore Bioimaging Consortium, Agency for Science, Technology and Research, 11 Biopolis Way, 138667, Singapore.
| | - Carola Canella
- Functional Neuroimaging Laboratory, Istituto Italiano di Tecnologia, Centre for Neuroscience and Cognitive Systems @ UNITN, 38068, Rovereto, Italy; CIMeC, Centre for Mind/Brain Sciences, University of Trento, 38068, Rovereto, Italy
| | - Cynthia Anckaerts
- Bio-Imaging Lab, University of Antwerp, CDE, Universiteitsplein 1, 2610, Antwerp, Belgium
| | - Gülebru Ayrancı
- Douglas Mental Health University Institute, McGill University, Montreal, Quebec, Canada
| | - Salma Bougacha
- Commissariat à l'Énergie Atomique et Aux Énergies Alternatives (CEA), Direction de la Recherche Fondamentale (DRF), Institut François Jacob, MIRCen, Fontenay-aux-roses, France; Centre National de la Recherche Scientifique (CNRS), Université Paris-Sud, Université Paris-Saclay UMR 9199, Neurodegenerative Diseases Laboratory, Fontenay-aux-Roses, France
| | - Thomas Bienert
- Department of Radiology, Medical Physics, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Killianstr. 5a, 79106, Freiburg, Germany; BrainLinks-BrainTools Cluster of Excellence, University of Freiburg, Georges-Köhler-Allee 80, 79110, Freiburg, Germany
| | - David Buehlmann
- Institute for Biomedical Engineering, University and ETH Zürich, Wolfgang-Pauli-Str. 27, 8093, Zürich, Switzerland
| | - Ludovico Coletta
- Functional Neuroimaging Laboratory, Istituto Italiano di Tecnologia, Centre for Neuroscience and Cognitive Systems @ UNITN, 38068, Rovereto, Italy; CIMeC, Centre for Mind/Brain Sciences, University of Trento, 38068, Rovereto, Italy
| | - Daniel Gallino
- Douglas Mental Health University Institute, McGill University, Montreal, Quebec, Canada
| | - Natalia Gass
- Department of Neuroimaging, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Clément M Garin
- Commissariat à l'Énergie Atomique et Aux Énergies Alternatives (CEA), Direction de la Recherche Fondamentale (DRF), Institut François Jacob, MIRCen, Fontenay-aux-roses, France; Centre National de la Recherche Scientifique (CNRS), Université Paris-Sud, Université Paris-Saclay UMR 9199, Neurodegenerative Diseases Laboratory, Fontenay-aux-Roses, France
| | - Nachiket Abhay Nadkarni
- Commissariat à l'Énergie Atomique et Aux Énergies Alternatives (CEA), Direction de la Recherche Fondamentale (DRF), Institut François Jacob, MIRCen, Fontenay-aux-roses, France; Centre National de la Recherche Scientifique (CNRS), Université Paris-Sud, Université Paris-Saclay UMR 9199, Neurodegenerative Diseases Laboratory, Fontenay-aux-Roses, France
| | - Neele S Hübner
- Department of Radiology, Medical Physics, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Killianstr. 5a, 79106, Freiburg, Germany; BrainLinks-BrainTools Cluster of Excellence, University of Freiburg, Georges-Köhler-Allee 80, 79110, Freiburg, Germany
| | - Meltem Karatas
- Department of Radiology, Medical Physics, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Killianstr. 5a, 79106, Freiburg, Germany; The Engineering Science, Computer Science and Imaging Laboratory (ICube), Department of Biophysics and Nuclear Medicine, University of Strasbourg and University Hospital of Strasbourg, 67000, Strasbourg, France
| | - Yuji Komaki
- Central Institute for Experimental Animals (CIEA), 3-25-12, Tonomachi, Kawasaki, Kanagawa, 210-0821, Japan; Department of Physiology, Keio University School of Medicine, 35 Shinanomachi, Shinjuku, Tokyo, 160-8582, Japan
| | - Silke Kreitz
- Institute of Experimental and Clinical Pharmacology and Toxicology, Friedrich-Alexander University Erlangen-Nürnberg (FAU), Fahrstraße 17, 91054, Erlangen, Germany
| | - Francesca Mandino
- Singapore Bioimaging Consortium, Agency for Science, Technology and Research, 11 Biopolis Way, 138667, Singapore; Faculty of Life Sciences, University of Manchester, Manchester, United Kingdom
| | - Anna E Mechling
- Department of Radiology, Medical Physics, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Killianstr. 5a, 79106, Freiburg, Germany; BrainLinks-BrainTools Cluster of Excellence, University of Freiburg, Georges-Köhler-Allee 80, 79110, Freiburg, Germany
| | - Chika Sato
- Functional and Molecular Imaging Team, Department of Molecular Imaging and Theranostics, National Institute of Radiological Sciences, National Institutes for Quantum and Radiological Science and Technology, Anagawa 4-9-1, Inage, Chiba-city, Chiba, 263-8555, Japan
| | - Katja Sauer
- Institute of Experimental and Clinical Pharmacology and Toxicology, Friedrich-Alexander University Erlangen-Nürnberg (FAU), Fahrstraße 17, 91054, Erlangen, Germany
| | - Disha Shah
- Bio-Imaging Lab, University of Antwerp, CDE, Universiteitsplein 1, 2610, Antwerp, Belgium; Laboratory for the Research of Neurodegenerative Diseases, VIB Center for Brain and Disease Research, KU Leuven, O&N4 Herestraat 49 Box 602, 3000, Leuven, Belgium
| | - Sandra Strobelt
- Institute of Experimental and Clinical Pharmacology and Toxicology, Friedrich-Alexander University Erlangen-Nürnberg (FAU), Fahrstraße 17, 91054, Erlangen, Germany
| | - Norio Takata
- Central Institute for Experimental Animals (CIEA), 3-25-12, Tonomachi, Kawasaki, Kanagawa, 210-0821, Japan; Department of Neuropsychiatry, Keio University School of Medicine, 35 Shinanomachi, Shinjuku, Tokyo, 160-8582, Japan
| | - Isabel Wank
- Institute of Experimental and Clinical Pharmacology and Toxicology, Friedrich-Alexander University Erlangen-Nürnberg (FAU), Fahrstraße 17, 91054, Erlangen, Germany
| | - Tong Wu
- Queensland Brain Institute, The University of Queensland, Brisbane, Queensland, Australia; Centre for Medical Image Computing, Department of Computer Science, & Max Planck University College London Centre for Computational Psychiatry and Ageing Research, University College London, London, UK; Computational, Cognitive and Clinical Imaging Lab, Division of Brain Sciences, Department of Medicine, Imperial College London, W12 0NN, UK; UK DRI Centre for Care Research and Technology, Imperial College London, W12 0NN, UK
| | - Noriaki Yahata
- Functional and Molecular Imaging Team, Department of Molecular Imaging and Theranostics, National Institute of Radiological Sciences, National Institutes for Quantum and Radiological Science and Technology, Anagawa 4-9-1, Inage, Chiba-city, Chiba, 263-8555, Japan
| | - Ling Yun Yeow
- Singapore Bioimaging Consortium, Agency for Science, Technology and Research, 11 Biopolis Way, 138667, Singapore
| | - Yohan Yee
- Hospital for Sick Children and Department of Medical Biophysics, The University of Toronto, Toronto, Ontario, Canada
| | - Ichio Aoki
- Functional and Molecular Imaging Team, Department of Molecular Imaging and Theranostics, National Institute of Radiological Sciences, National Institutes for Quantum and Radiological Science and Technology, Anagawa 4-9-1, Inage, Chiba-city, Chiba, 263-8555, Japan
| | - M Mallar Chakravarty
- Douglas Mental Health University Institute, McGill University, Montreal, Quebec, Canada; Department of Psychiatry, McGill University, Montreal, Quebec, Canada; Department of Biological and Biomedical Engineering, McGill University, Montreal, Quebec, Canada
| | - Wei-Tang Chang
- Singapore Bioimaging Consortium, Agency for Science, Technology and Research, 11 Biopolis Way, 138667, Singapore
| | - Marc Dhenain
- Commissariat à l'Énergie Atomique et Aux Énergies Alternatives (CEA), Direction de la Recherche Fondamentale (DRF), Institut François Jacob, MIRCen, Fontenay-aux-roses, France; Centre National de la Recherche Scientifique (CNRS), Université Paris-Sud, Université Paris-Saclay UMR 9199, Neurodegenerative Diseases Laboratory, Fontenay-aux-Roses, France
| | - Dominik von Elverfeldt
- Department of Radiology, Medical Physics, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Killianstr. 5a, 79106, Freiburg, Germany; BrainLinks-BrainTools Cluster of Excellence, University of Freiburg, Georges-Köhler-Allee 80, 79110, Freiburg, Germany
| | - Laura-Adela Harsan
- The Engineering Science, Computer Science and Imaging Laboratory (ICube), Department of Biophysics and Nuclear Medicine, University of Strasbourg and University Hospital of Strasbourg, 67000, Strasbourg, France
| | - Andreas Hess
- Institute of Experimental and Clinical Pharmacology and Toxicology, Friedrich-Alexander University Erlangen-Nürnberg (FAU), Fahrstraße 17, 91054, Erlangen, Germany
| | - Tianzi Jiang
- Queensland Brain Institute, The University of Queensland, Brisbane, Queensland, Australia; Brainnetome Center & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China
| | - Georgios A Keliris
- Bio-Imaging Lab, University of Antwerp, CDE, Universiteitsplein 1, 2610, Antwerp, Belgium
| | - Jason P Lerch
- Hospital for Sick Children and Department of Medical Biophysics, The University of Toronto, Toronto, Ontario, Canada; Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, OX3 9DU, UK
| | - Andreas Meyer-Lindenberg
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Germany
| | - Hideyuki Okano
- Department of Physiology, Keio University School of Medicine, 35 Shinanomachi, Shinjuku, Tokyo, 160-8582, Japan; Laboratory for Marmoset Neural Architecture, RIKEN Brain Science Institute, Wako, Saitama, 351-0198, Japan
| | - Markus Rudin
- Institute for Biomedical Engineering, University and ETH Zürich, Wolfgang-Pauli-Str. 27, 8093, Zürich, Switzerland; Institute of Pharmacology and Toxicology, University of Zürich, Winterthurerstrasse 190, 8057, Zürich, Switzerland; Neuroscience Center Zürich, ETH Zürich and University of Zürich, Zürich, Switzerland
| | - Alexander Sartorius
- Department of Neuroimaging, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Annemie Van der Linden
- Bio-Imaging Lab, University of Antwerp, CDE, Universiteitsplein 1, 2610, Antwerp, Belgium
| | - Marleen Verhoye
- Bio-Imaging Lab, University of Antwerp, CDE, Universiteitsplein 1, 2610, Antwerp, Belgium
| | - Wolfgang Weber-Fahr
- Department of Neuroimaging, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Nicole Wenderoth
- Neural Control of Movement Lab, Department of Health Sciences and Technology, ETH Zürich, Winterthurerstrasse 190, 8057, Zurich, Switzerland; Neuroscience Center Zürich, ETH Zürich and University of Zürich, Zürich, Switzerland
| | - Valerio Zerbi
- Neural Control of Movement Lab, Department of Health Sciences and Technology, ETH Zürich, Winterthurerstrasse 190, 8057, Zurich, Switzerland; Neuroscience Center Zürich, ETH Zürich and University of Zürich, Zürich, Switzerland
| | - Alessandro Gozzi
- Functional Neuroimaging Laboratory, Istituto Italiano di Tecnologia, Centre for Neuroscience and Cognitive Systems @ UNITN, 38068, Rovereto, Italy
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Samogin J, Liu Q, Marino M, Wenderoth N, Mantini D. Shared and connection-specific intrinsic interactions in the default mode network. Neuroimage 2019; 200:474-481. [DOI: 10.1016/j.neuroimage.2019.07.007] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2018] [Revised: 04/24/2019] [Accepted: 07/04/2019] [Indexed: 10/26/2022] Open
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39
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Bächinger M, Lehner R, Thomas F, Hanimann S, Balsters J, Wenderoth N. Human motor fatigability as evoked by repetitive movements results from a gradual breakdown of surround inhibition. eLife 2019; 8:46750. [PMID: 31524600 PMCID: PMC6746551 DOI: 10.7554/elife.46750] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2019] [Accepted: 08/22/2019] [Indexed: 01/08/2023] Open
Abstract
Motor fatigability emerges when demanding tasks are executed over an extended period of time. Here, we used repetitive low-force movements that cause a gradual reduction in movement speed (or 'motor slowing') to study the central component of fatigability in healthy adults. We show that motor slowing is associated with a gradual increase of net excitability in the motor network and, specifically, in primary motor cortex (M1), which results from overall disinhibition. Importantly, we link performance decrements to a breakdown of surround inhibition in M1, which is associated with high coactivation of antagonistic muscle groups. This is consistent with the model that a loss of inhibitory control might broaden the tuning of population vectors such that movement patterns become more variable, ill-timed and effortful. We propose that the release of inhibition in M1 is an important mechanism underpinning motor fatigability and, potentially, also pathological fatigue as frequently observed in patients with brain disorders.
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Affiliation(s)
- Marc Bächinger
- Department of Health Sciences and Technology, Neural Control of Movement Lab, Zurich, Switzerland.,Neuroscience Center Zurich (ZNZ), University of Zurich, Federal Institute of Technology Zurich, University and Balgrist Hospital Zurich, Zurich, Switzerland
| | - Rea Lehner
- Department of Health Sciences and Technology, Neural Control of Movement Lab, Zurich, Switzerland.,Neuroscience Center Zurich (ZNZ), University of Zurich, Federal Institute of Technology Zurich, University and Balgrist Hospital Zurich, Zurich, Switzerland
| | - Felix Thomas
- Department of Health Sciences and Technology, Neural Control of Movement Lab, Zurich, Switzerland.,Neuroscience Center Zurich (ZNZ), University of Zurich, Federal Institute of Technology Zurich, University and Balgrist Hospital Zurich, Zurich, Switzerland
| | - Samira Hanimann
- Department of Health Sciences and Technology, Neural Control of Movement Lab, Zurich, Switzerland
| | - Joshua Balsters
- Department of Health Sciences and Technology, Neural Control of Movement Lab, Zurich, Switzerland.,Department of Psychology, Royal Holloway University of London, Egham, United Kingdom
| | - Nicole Wenderoth
- Department of Health Sciences and Technology, Neural Control of Movement Lab, Zurich, Switzerland.,Neuroscience Center Zurich (ZNZ), University of Zurich, Federal Institute of Technology Zurich, University and Balgrist Hospital Zurich, Zurich, Switzerland
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40
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Simon-Martinez C, Jaspers E, Alaerts K, Ortibus E, Balsters J, Mailleux L, Blommaert J, Sleurs C, Klingels K, Amant F, Uyttebroeck A, Wenderoth N, Feys H. Influence of the corticospinal tract wiring pattern on sensorimotor functional connectivity and clinical correlates of upper limb function in unilateral cerebral palsy. Sci Rep 2019; 9:8230. [PMID: 31160679 PMCID: PMC6547689 DOI: 10.1038/s41598-019-44728-9] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2019] [Accepted: 05/21/2019] [Indexed: 12/02/2022] Open
Abstract
In children with unilateral cerebral palsy (uCP), the corticospinal tract (CST)-wiring patterns may differ (contralateral, ipsilateral or bilateral), partially determining motor deficits. However, the impact of such CST-wiring on functional connectivity remains unknown. Here, we explored resting-state sensorimotor functional connectivity in 26 uCP with periventricular white matter lesions (mean age (standard deviation): 12.87 m (±4.5), CST wiring: 9 contralateral, 9 ipsilateral, 6 bilateral) compared to 60 healthy controls (mean age (standard deviation): 14.54 (±4.8)), and between CST-wiring patterns. Functional connectivity from each M1 to three bilateral sensorimotor regions of interest (primary sensory cortex, dorsal and ventral premotor cortex) and the supplementary motor area was compared between groups (controls vs. uCP; and controls vs. each CST-wiring group). Seed-to-voxel analyses from bilateral M1 were compared between groups. Additionally, relations with upper limb motor deficits were explored. Aberrant sensorimotor functional connectivity seemed to be CST-dependent rather than specific from all the uCP population: in the dominant hemisphere, the contralateral CST group showed increased connectivity between M1 and premotor cortices, whereas the bilateral CST group showed higher connectivity between M1 and somatosensory association areas. These results suggest that functional connectivity of the sensorimotor network is CST-wiring-dependent, although the impact on upper limb function remains unclear.
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Affiliation(s)
| | - Ellen Jaspers
- Neural Control of Movement Lab, Department of Health Sciences and Technology, ETH, Zurich, Switzerland
| | - Kaat Alaerts
- KU Leuven Department of Rehabilitation Sciences, Leuven, Belgium
| | - Els Ortibus
- KU Leuven Department of Development and Regeneration, Leuven, Belgium
| | - Joshua Balsters
- Neural Control of Movement Lab, Department of Health Sciences and Technology, ETH, Zurich, Switzerland.,Department of Psychology, Royal Holloway University of London, Egham, United Kingdom
| | - Lisa Mailleux
- KU Leuven Department of Rehabilitation Sciences, Leuven, Belgium
| | | | | | - Katrijn Klingels
- KU Leuven Department of Rehabilitation Sciences, Leuven, Belgium.,Rehabilitation Research Centre, Faculty of Rehabilitation Sciences, Hasselt University, Diepenbeek, Belgium
| | - Frédéric Amant
- KU Leuven Department of Oncology, Leuven, Belgium.,Centre for Gynaecologic Oncology, Antoni van Leeuwenhoek, Amsterdam, Netherlands.,Centre for Gynaecologic Oncology, Amsterdam University Medical Centres, Amsterdam, Netherlands
| | | | - Nicole Wenderoth
- Neural Control of Movement Lab, Department of Health Sciences and Technology, ETH, Zurich, Switzerland
| | - Hilde Feys
- KU Leuven Department of Rehabilitation Sciences, Leuven, Belgium
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41
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Manjaly ZM, Harrison NA, Critchley HD, Do CT, Stefanics G, Wenderoth N, Lutterotti A, Müller A, Stephan KE. Pathophysiological and cognitive mechanisms of fatigue in multiple sclerosis. J Neurol Neurosurg Psychiatry 2019; 90:642-651. [PMID: 30683707 PMCID: PMC6581095 DOI: 10.1136/jnnp-2018-320050] [Citation(s) in RCA: 157] [Impact Index Per Article: 31.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/21/2018] [Revised: 01/03/2019] [Accepted: 01/04/2019] [Indexed: 02/07/2023]
Abstract
Fatigue is one of the most common symptoms in multiple sclerosis (MS), with a major impact on patients' quality of life. Currently, treatment proceeds by trial and error with limited success, probably due to the presence of multiple different underlying mechanisms. Recent neuroscientific advances offer the potential to develop tools for differentiating these mechanisms in individual patients and ultimately provide a principled basis for treatment selection. However, development of these tools for differential diagnosis will require guidance by pathophysiological and cognitive theories that propose mechanisms which can be assessed in individual patients. This article provides an overview of contemporary pathophysiological theories of fatigue in MS and discusses how the mechanisms they propose may become measurable with emerging technologies and thus lay a foundation for future personalised treatments.
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Affiliation(s)
- Zina-Mary Manjaly
- Department of Neurology, Schulthess Clinic, Zürich, Switzerland .,Department of Health Sciences and Technology, ETH Zurich, Zürich, Switzerland
| | - Neil A Harrison
- Department of Neuroscience, Brighton and Sussex Medical School, University of Sussex, Brighton, UK.,Sussex Partnership NHS Foundation Trust, Brighton, UK
| | - Hugo D Critchley
- Department of Neuroscience, Brighton and Sussex Medical School, University of Sussex, Brighton, UK.,Sussex Partnership NHS Foundation Trust, Brighton, UK
| | - Cao Tri Do
- Translational Neuromodeling Unit (TNU), Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - Gabor Stefanics
- Translational Neuromodeling Unit (TNU), Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland.,Laboratory for Social and Neural Systems Research (SNS), Department of Economics, University of Zurich, Zurich, Switzerland
| | - Nicole Wenderoth
- Department of Health Sciences and Technology, ETH Zurich, Zürich, Switzerland
| | - Andreas Lutterotti
- Department of Neurology, University Hospital Zurich, Zurich, Switzerland
| | - Alfred Müller
- Department of Neurology, Schulthess Clinic, Zürich, Switzerland
| | - Klaas Enno Stephan
- Translational Neuromodeling Unit (TNU), Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland.,Wellcome Centre for Human Neuroimaging, University College London, London, UK.,Max Planck Institute for Metabolism Research, Cologne, Germany
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42
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Zerbi V, Markicevic M, Gasparini F, Schroeter A, Rudin M, Wenderoth N. Inhibiting mGluR5 activity by AFQ056/Mavoglurant rescues circuit-specific functional connectivity in Fmr1 knockout mice. Neuroimage 2019; 191:392-402. [DOI: 10.1016/j.neuroimage.2019.02.051] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2018] [Revised: 02/11/2019] [Accepted: 02/19/2019] [Indexed: 12/12/2022] Open
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43
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Abstract
When learning new information, contextual information about the encoding situation is stored in addition to the focal memory content. Later, these strings of extra information can help retrieve the learned content as demonstrated by experiments where contextual cues from an encoding situation facilitate remembering and improve memory performance when reinstated during retrieval. This context-dependent memory effect has been investigated over the course of several decades and has been demonstrated with many different types of contexts. Based on this, the widely held belief is that context-dependent memory is a strong and robust effect, with transferable substance for everyday learning and potential clinical applications. Here we report the results of a multi-study design investigating the influence of reinstated visual contexts on memory performance. Data from 120 participants were included in three studies comprising a variety of visual cues. We show convincingly that even rich, salient and fully surrounding visual contexts provided by virtual reality are not sufficient to induce effects of context-dependency in a free recall memory task. We also investigated contextual modulation of oscillatory brain activity in order to test the effect of reinstated neural contexts, which failed to evoke a robust effect when re-tested in an internal conceptual replication study. Moreover, a Bayesian sequential statistical analysis revealed moderate to strong evidence against the hypothesis that reinstatement of visual contexts benefits free recall memory tasks indicating that effects are small and may not be suitable for transfer into everyday learning.
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Affiliation(s)
- Michel Juhani Wälti
- Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
- Neuroscience Center Zurich (ZNZ), University and ETH Zurich, Zurich, Switzerland
| | | | - Nicole Wenderoth
- Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
- Neuroscience Center Zurich (ZNZ), University and ETH Zurich, Zurich, Switzerland
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44
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van der Groen O, Mattingley JB, Wenderoth N. Altering brain dynamics with transcranial random noise stimulation. Sci Rep 2019; 9:4029. [PMID: 30858404 PMCID: PMC6411772 DOI: 10.1038/s41598-019-40335-w] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2017] [Accepted: 02/14/2019] [Indexed: 11/26/2022] Open
Abstract
Random noise can enhance the detectability of weak signals in nonlinear systems, a phenomenon known as stochastic resonance (SR). This concept is not only applicable to single threshold systems but can also be applied to dynamical systems with multiple attractor states, such as observed during the phenomenon of binocular rivalry. Binocular rivalry can be characterized by marginally stable attractor states between which the brain switches in a spontaneous, stochastic manner. Here we used a computational model to predict the effect of noise on perceptual dominance durations. Subsequently we compared the model prediction to a series of experiments where we measured binocular rivalry dynamics when noise (zero-mean Gaussian random noise) was added either to the visual stimulus (Exp. 1) or directly to the visual cortex (Exp. 2) by applying transcranial Random Noise Stimulation (tRNS 1 mA, 100–640 Hz zero -mean Gaussian random noise). We found that adding noise significantly reduced the mixed percept duration (Exp. 1 and Exp. 2). Our results are the first to demonstrate that both central and peripheral noise can influence state-switching dynamics of binocular rivalry under specific conditions (e.g. low visual contrast stimuli), in line with a SR-mechanism.
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Affiliation(s)
- Onno van der Groen
- Neural Control of Movement Laboratory, Health Sciences and Technology, ETH Zurich, Zurich, 8057, Switzerland. .,School of Medical and Health Sciences, Edith Cowan University, Joondalup, Western Australia, 6027, Australia.
| | - Jason B Mattingley
- Queensland Brain Institute, The University of Queensland, St Lucia, Queensland, 4072, Australia.,School of Psychology, The University of Queensland, St Lucia, Queensland, 4072, Australia.,Canadian Institute for Advanced Research (CIFAR), Toronto, Canada
| | - Nicole Wenderoth
- Neural Control of Movement Laboratory, Health Sciences and Technology, ETH Zurich, Zurich, 8057, Switzerland
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45
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Cretu AL, Ruddy K, Germann M, Wenderoth N. Uncertainty in contextual and kinematic cues jointly modulates motor resonance in primary motor cortex. J Neurophysiol 2019; 121:1451-1464. [PMID: 30811258 DOI: 10.1152/jn.00655.2018] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022] Open
Abstract
Contextual information accompanying others' actions modulates "motor resonance", i.e., neural activity within motor areas that is elicited by movement observation. One possibility is that we weigh and combine such information in a Bayesian manner according to their relative uncertainty. Therefore, contextual information becomes particularly useful when others' actions are difficult to discriminate. It is unclear, however, whether this uncertainty modulates the neural activity in primary motor cortex (M1) during movement observation. Here, we applied single-pulse transcranial magnetic stimulation (TMS) while subjects watched different grasping actions. We operationalized motor resonance as grip-specific modulation of corticomotor excitability measured in the index (FDI) versus the little finger abductor (ADM). We experimentally modulated either the availability of kinematic information ( experiment 1) or the reliability of contextual cues ( experiment 2). Our results indicate that even in the absence of movement kinematics, reliable contextual information is enough to trigger significant muscle-specific corticomotor excitability changes in M1, which are strongest when both kinematics and contextual information are available. These findings suggest that bottom-up mechanisms that activate motor representations as a function of the observed kinematics and top-down mechanisms that activate motor representations associated with arbitrary cues converge in M1. NEW & NOTEWORTHY Our study reveals new neurophysiological insights in support of the Bayesian account of action observation by showing that "motor resonance", i.e., neural activity evoked by observing others' actions, incorporates the uncertainty related to both contextual (prior beliefs) and kinematic (sensory evidence) cues. Notably, we show that muscle-specific modulation of M1 is strongest when context and movement kinematics are available, and it can be elicited even in the absence of movement kinematics.
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Affiliation(s)
- Andreea Loredana Cretu
- Neural Control of Movement Group, Department of Health Sciences and Technology, ETH Zurich, Zurich , Switzerland
| | - Kathy Ruddy
- Neural Control of Movement Group, Department of Health Sciences and Technology, ETH Zurich, Zurich , Switzerland.,Trinity College Institute of Neuroscience, Trinity College Dublin , Dublin , Ireland
| | - Maria Germann
- Neural Control of Movement Group, Department of Health Sciences and Technology, ETH Zurich, Zurich , Switzerland
| | - Nicole Wenderoth
- Neural Control of Movement Group, Department of Health Sciences and Technology, ETH Zurich, Zurich , Switzerland
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Alaerts K, Bernaerts S, Vanaudenaerde B, Daniels N, Wenderoth N. Amygdala-Hippocampal Connectivity Is Associated With Endogenous Levels of Oxytocin and Can Be Altered by Exogenously Administered Oxytocin in Adults With Autism. Biol Psychiatry Cogn Neurosci Neuroimaging 2019; 4:655-663. [PMID: 30846366 DOI: 10.1016/j.bpsc.2019.01.008] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/09/2018] [Revised: 01/22/2019] [Accepted: 01/22/2019] [Indexed: 12/12/2022]
Abstract
BACKGROUND Oxytocin (OT) plays a pivotal role in interpersonal bonding, affiliation, and trust, and its intranasal administration is increasingly considered as a potential treatment for autism spectrum disorder. METHODS We explored whether variations in endogenous salivary OT concentration are related to interindividual differences in core autism symptoms and expressions of attachment in 38 male adults with autism spectrum disorder. Further, resting-state functional magnetic resonance imaging was adopted to specifically explore whether interindividual differences are reflected in the intrinsic network organization of key regions of the central oxytocinergic system. RESULTS Positive correlations were identified between peripheral OT and expressions of secure attachment (the State Adult Attachment Measure and the Inventory of Peer Attachment), but no significant relationships were identified with scales assessing core autism symptom domains (the Social Responsiveness Scale and the Repetitive Behavior Scale). At the neural level, higher levels of endogenous OT were associated with lower degrees of interregional functional coupling between the amygdala and hippocampal regions. Interestingly, a single dose of exogenously administered OT induced a further reduction in amygdala-hippocampal connectivity, indicating that a higher availability of OT can alter the degree of amygdala-hippocampal connectivity. CONCLUSIONS The identified associations between the oxytocinergic system, expressions of secure attachment, and amygdala-hippocampal pathways are anticipated to be of relevance for understanding the role of OT in modulating appropriate neural and physiological responses to stress and restoring homeostasis.
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Affiliation(s)
- Kaat Alaerts
- Department of Rehabilitation Sciences, Group Biomedical Sciences, Neuromotor Rehabilitation Research Group, University of Leuven, Katholieke Universiteit Leuven, Belgium.
| | - Sylvie Bernaerts
- Department of Rehabilitation Sciences, Group Biomedical Sciences, Neuromotor Rehabilitation Research Group, University of Leuven, Katholieke Universiteit Leuven, Belgium
| | - Bart Vanaudenaerde
- Department of Chronic Diseases, Metabolism and Ageing, Group Biomedical Sciences, Pneumology Research Group, University of Leuven, Katholieke Universiteit Leuven, Belgium
| | - Nicky Daniels
- Department of Rehabilitation Sciences, Group Biomedical Sciences, Neuromotor Rehabilitation Research Group, University of Leuven, Katholieke Universiteit Leuven, Belgium
| | - Nicole Wenderoth
- Department of Health Sciences and Technology, Neural Control of Movement Lab, Eidgenössische Technische Hochschule, Zurich, Switzerland
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Porcaro C, Balsters JH, Mantini D, Robertson IH, Wenderoth N. P3b amplitude as a signature of cognitive decline in the older population: An EEG study enhanced by Functional Source Separation. Neuroimage 2019; 184:535-546. [DOI: 10.1016/j.neuroimage.2018.09.057] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2018] [Revised: 09/03/2018] [Accepted: 09/20/2018] [Indexed: 10/28/2022] Open
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48
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Ruddy K, Balsters J, Mantini D, Liu Q, Kassraian-Fard P, Enz N, Mihelj E, Subhash Chander B, Soekadar SR, Wenderoth N. Neural activity related to volitional regulation of cortical excitability. eLife 2018; 7:e40843. [PMID: 30489255 PMCID: PMC6294548 DOI: 10.7554/elife.40843] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2018] [Accepted: 11/26/2018] [Indexed: 12/26/2022] Open
Abstract
To date there exists no reliable method to non-invasively upregulate or downregulate the state of the resting human motor system over a large dynamic range. Here we show that an operant conditioning paradigm which provides neurofeedback of the size of motor evoked potentials (MEPs) in response to transcranial magnetic stimulation (TMS), enables participants to self-modulate their own brain state. Following training, participants were able to robustly increase (by 83.8%) and decrease (by 30.6%) their MEP amplitudes. This volitional up-versus down-regulation of corticomotor excitability caused an increase of late-cortical disinhibition (LCD), a TMS derived read-out of presynaptic GABAB disinhibition, which was accompanied by an increase of gamma and a decrease of alpha oscillations in the trained hemisphere. This approach paves the way for future investigations into how altered brain state influences motor neurophysiology and recovery of function in a neurorehabilitation context.
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Affiliation(s)
- Kathy Ruddy
- Neural Control of Movement LabETH ZürichZürichSwitzerland
- Institute of NeuroscienceTrinity College DublinDublinIreland
| | - Joshua Balsters
- Neural Control of Movement LabETH ZürichZürichSwitzerland
- Department of PsychologyRoyal Holloway University of LondonLondonUnited Kingdom
| | - Dante Mantini
- Neural Control of Movement LabETH ZürichZürichSwitzerland
- Movement Control and Neuroplasticity Research GroupKU LeuvenLeuvenBelgium
| | - Quanying Liu
- Neural Control of Movement LabETH ZürichZürichSwitzerland
- Movement Control and Neuroplasticity Research GroupKU LeuvenLeuvenBelgium
| | | | - Nadja Enz
- Neural Control of Movement LabETH ZürichZürichSwitzerland
| | - Ernest Mihelj
- Neural Control of Movement LabETH ZürichZürichSwitzerland
| | | | - Surjo R Soekadar
- Applied Neurotechnology LaboratoryUniversity of TübingenTübingenGermany
- Clinical Neurotechnology Laboratory, Neuroscience Research Center (NWFZ), Department of Psychiatry and PsychotherapyCharité – University Medicine BerlinBerlinGermany
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Abstract
Behavioral changes characteristic for motor learning result from synaptic plasticity within the sensorimotor system. This review summarizes how the central nervous system responds rapidly to motor activity while awake. It then discusses evidence for the hypothesis that sleep is essential for both stabilizing previously acquired motor memories and maintaining the brain's efficacy to undergo plastic changes to learn new skills.
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Affiliation(s)
- Nicole Wenderoth
- Neural Control of Movement Lab, Department of Health Sciences and Technology, ETH Zurich, Switzerland
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50
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Simon-Martinez C, Mailleux L, Ortibus E, Fehrenbach A, Sgandurra G, Cioni G, Desloovere K, Wenderoth N, Demaerel P, Sunaert S, Molenaers G, Feys H, Klingels K. Combining constraint-induced movement therapy and action-observation training in children with unilateral cerebral palsy: a randomized controlled trial. BMC Pediatr 2018; 18:250. [PMID: 30064396 PMCID: PMC6069849 DOI: 10.1186/s12887-018-1228-2] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/22/2017] [Accepted: 07/19/2018] [Indexed: 11/26/2022] Open
Abstract
BACKGROUND Upper limb (UL) deficits in children with unilateral cerebral palsy (uCP) have traditionally been targeted with motor execution treatment models, such as modified Constraint-Induced Movement Therapy (mCIMT). However, new approaches based on a neurophysiological model such as Action-Observation Training (AOT) may provide new opportunities for enhanced motor learning. The aim of this study is to describe a randomised controlled trial (RCT) protocol investigating the effects of an intensive treatment model, combining mCIMT and AOT compared to mCIMT alone on UL function in children with uCP. Additionally, the role of neurological factors as potential biomarkers of treatment response will be analysed. METHODS An evaluator-blinded RCT will be conducted in 42 children aged between 6 and 12 years. Before randomization, children will be stratified according to their House Functional Classification Scale, age and type of corticospinal tract wiring. A 2-week day-camp will be set up in which children receive intensive mCIMT therapy for 6 hours a day on 9 out of 11 consecutive days (54 h) including AOT or control condition (15 h). During AOT, these children watch video sequences showing goal-directed actions and subsequently execute the observed actions with the more impaired UL. The control group performs the same actions after watching computer games without human motion. The primary outcome measure will be the Assisting Hand Assessment. Secondary outcomes comprise clinical assessments across body function, activity and participation level of the International Classification of Function, Disability and Health. Furthermore, to quantitatively evaluate UL movement patterns, a three-dimensional motion analysis will be conducted. UL function will be assessed at baseline, immediately before and after intervention and at 6 months follow up. Brain imaging comprising structural and functional connectivity measures as well as Transcranial Magnetic Stimulation (TMS) to evaluate corticospinal tract wiring will be acquired before the intervention. DISCUSSION This paper describes the methodology of an RCT with two main objectives: (1) to evaluate the added value of AOT to mCIMT on UL outcome in children with uCP and (2) to investigate the role of neurological factors as potential biomarkers of treatment response. TRIAL REGISTRATION NCT03256357 registered on 21st August 2017 (retrospectively registered).
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Affiliation(s)
| | - Lisa Mailleux
- Department of Rehabilitation Sciences, KU Leuven - University of Leuven, Leuven, Belgium
| | - Els Ortibus
- Department of Development and Regeneration, KU Leuven - University of Leuven, Leuven, Belgium
| | - Anna Fehrenbach
- Department of Rehabilitation Sciences, KU Leuven - University of Leuven, Leuven, Belgium
| | - Giuseppina Sgandurra
- Department of Developmental Neuroscience, IRCCS Fondazione Stella Maris, Calambrone, Italy
- Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Giovanni Cioni
- Department of Developmental Neuroscience, IRCCS Fondazione Stella Maris, Calambrone, Italy
- Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Kaat Desloovere
- Department of Rehabilitation Sciences, KU Leuven - University of Leuven, Leuven, Belgium
- Clinical Motion Analysis Laboratory, University Hospitals Leuven, Pellenberg, Belgium
| | - Nicole Wenderoth
- Neural Control of Movement Lab, Department of Health Sciences and Technology, ETH, Zurich, Switzerland
| | - Philippe Demaerel
- Department of Radiology, University Hospitals Leuven, Leuven, Belgium
| | - Stefan Sunaert
- Department of Radiology, University Hospitals Leuven, Leuven, Belgium
| | - Guy Molenaers
- Department of Development and Regeneration, KU Leuven - University of Leuven, Leuven, Belgium
| | - Hilde Feys
- Department of Rehabilitation Sciences, KU Leuven - University of Leuven, Leuven, Belgium
| | - Katrijn Klingels
- Department of Rehabilitation Sciences, KU Leuven - University of Leuven, Leuven, Belgium
- Rehabilitation Research Centre, BIOMED, Hasselt University, Diepenbeek, Belgium
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