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Ameen MS, Petzka M, Peigneux P, Hoedlmoser K. Post-training sleep modulates motor adaptation and task-related beta oscillations. J Sleep Res 2024; 33:e14082. [PMID: 37950689 DOI: 10.1111/jsr.14082] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2023] [Revised: 10/04/2023] [Accepted: 10/12/2023] [Indexed: 11/13/2023]
Abstract
Motor adaptation reflects the ability of the brain's sensorimotor system to flexibly deal with environmental changes to generate effective motor behaviour. Whether sleep contributes to the consolidation of motor adaptation remains controversial. In this study, we investigated the impact of sleep on motor adaptation and its neurophysiological correlates in a novel motor adaptation task that leverages a highly automatised motor skill, that is, typing. We hypothesised that sleep-associated memory consolidation would benefit motor adaptation and induce modulations in task-related beta band (13-30 Hz) activity during adaptation. Healthy young male experts in typing on the regular computer keyboard were trained to type on a vertically mirrored keyboard while brain activity was recorded using electroencephalography. Typing performance was assessed either after a full night of sleep with polysomnography or a similar period of daytime wakefulness. Results showed improved motor adaptation performance after nocturnal sleep but not after daytime wakefulness, and decreased beta power: (a) during mirrored typing as compared with regular typing; and (b) in the post-sleep versus the pre-sleep mirrored typing sessions. Furthermore, the slope of the electroencephalography signal, a measure of aperiodic brain activity, decreased during mirrored as compared with regular typing. Changes in the electroencephalography spectral slope from pre- to post-sleep mirrored typing sessions were correlated with changes in task performance. Finally, increased fast sleep spindle density (13-15 Hz) during the night following motor adaptation training was predictive of successful motor adaptation. These findings suggest that post-training sleep modulates neural activity supporting adaptive motor functions.
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Affiliation(s)
- Mohamed S Ameen
- Laboratory for Sleep, Cognition and Consciousness Research, Department of Psychology, University of Salzburg, Salzburg, Austria
- Centre for Cognitive Neuroscience Salzburg (CCNS), University of Salzburg, Salzburg, Austria
| | - Marit Petzka
- Max Planck Research Group NeuroCode, Max Planck Institute for Human Development, Berlin, Germany
- Institute of Psychology, University of Hamburg, Hamburg, Germany
| | - Philippe Peigneux
- UR2NF, Neuropsychology and Functional Neuroimaging Research Unit at CRCN-Center for Research in Cognition and Neurosciences, UNI-ULB Neurosciences Institute, Université Libre de Bruxelles (ULB), Brussels, Belgium
| | - Kerstin Hoedlmoser
- Laboratory for Sleep, Cognition and Consciousness Research, Department of Psychology, University of Salzburg, Salzburg, Austria
- Centre for Cognitive Neuroscience Salzburg (CCNS), University of Salzburg, Salzburg, Austria
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2
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Alterman BL, Ali S, Keeton E, Binkley K, Hendrix W, Lee PJ, Johnson JT, Wang S, Kling J, Gale MK, Wheaton LA. Grasp Posture Variability Leads to Greater Ipsilateral Sensorimotor Beta Activation During Simulated Prosthesis Use. J Mot Behav 2024; 56:579-591. [PMID: 39041372 PMCID: PMC11343659 DOI: 10.1080/00222895.2024.2364657] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Revised: 03/28/2024] [Accepted: 05/30/2024] [Indexed: 07/24/2024]
Abstract
Motor behaviour using upper-extremity prostheses of different levels is greatly variable, leading to challenges interpreting ideal rehabilitation strategies. Elucidating the underlying neural control mechanisms driving variability benefits our understanding of adaptation after limb loss. In this follow-up study, non-amputated participants completed simple and complex reach-to-grasp motor tasks using a body-powered transradial or partial-hand prosthesis simulator. We hypothesised that under complex task constraints, individuals employing variable grasp postures will show greater sensorimotor beta activation compared to individuals relying on uniform grasping, and activation will occur later in variable compared to uniform graspers. In the simple task, partial-hand variable and transradial users showed increased neural activation from the early to late phase of the reach, predominantly in the hemisphere ipsilateral to device use. In the complex task, only partial-hand variable graspers showed a significant increase in neural activation of the sensorimotor cortex from the early to the late phase of the reach. These results suggest that grasp variability may be a crucial component in the mechanism of neural adaptation to prosthesis use, and may be mediated by device level and task complexity, with implications for rehabilitation after amputation.
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Affiliation(s)
- Bennett L Alterman
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, USA
| | - Saif Ali
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, USA
| | - Emily Keeton
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, USA
| | - Katrina Binkley
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, USA
| | - William Hendrix
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, USA
| | - Perry J Lee
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, USA
| | - John T Johnson
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, USA
| | - Shuo Wang
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, USA
| | - James Kling
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, USA
| | - Mary Kate Gale
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, USA
| | - Lewis A Wheaton
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, USA
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3
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Mista CA, Arguissain FG, Ranieri A, Nielsen JF, Andersen H, Biurrun Manresa JA, Andersen OK. Spatio-temporal modulation of cortical activity during motor deadaptation depends on the feedback of task-related error. Behav Brain Res 2024; 468:115024. [PMID: 38705283 DOI: 10.1016/j.bbr.2024.115024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2024] [Revised: 04/26/2024] [Accepted: 04/27/2024] [Indexed: 05/07/2024]
Abstract
Motor adaptations are responsible for recalibrating actions and facilitating the achievement of goals in a constantly changing environment. Once consolidated, the decay of motor adaptation is a process affected by available sensory information during deadaptation. However, the cortical response to task error feedback during the deadaptation phase has received little attention. Here, we explored changes in brain cortical responses due to feedback of task-related error during deadaptation. Twelve healthy volunteers were recruited for the study. Right hand movement and EEG were recorded during repetitive trials of a hand reaching movement. A visuomotor rotation of 30° was introduced to induce motor adaptation. Volunteers participated in two experimental sessions organized in baseline, adaptation, and deadaptation blocks. In the deadaptation block, the visuomotor rotation was removed, and visual feedback was only provided in one session. Performance was quantified using angle end-point error, averaged speed, and movement onset time. A non-parametric spatiotemporal cluster-level permutation test was used to analyze the EEG recordings. During deadaptation, participants experienced a greater error reduction when feedback of the cursor was provided. The EEG responses showed larger activity in the left centro-frontal parietal areas during the deadaptation block when participants received feedback, as opposed to when they did not receive feedback. Centrally distributed clusters were found for the adaptation and deadaptation blocks in the absence of visual feedback. The results suggest that visual feedback of the task-related error activates cortical areas related to performance monitoring, depending on the accessible sensory information.
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Affiliation(s)
- C A Mista
- Institute for Research and Development on Bioengineering and Bioinformatics (IBB), CONICET-UNER, Oro Verde, Argentina; Center for Rehabilitation Engineering and Neuromuscular and Sensory Research (CIRINS), National University of Entre Ríos, Oro Verde, Argentina
| | - F G Arguissain
- Center for Neuroplasticity and Pain (CNAP), Department of Health Science and Technology, Aalborg University, Aalborg, Denmark
| | - A Ranieri
- Center for Neuroplasticity and Pain (CNAP), Department of Health Science and Technology, Aalborg University, Aalborg, Denmark
| | - J F Nielsen
- Hammel Neurorehabilitation and Research Centre, Aarhus University Hospital, Denmark
| | - H Andersen
- Hammel Neurorehabilitation and Research Centre, Aarhus University Hospital, Denmark; Department of Neurology, Aarhus University Hospital, Aarhus, Denmark
| | - J A Biurrun Manresa
- Institute for Research and Development on Bioengineering and Bioinformatics (IBB), CONICET-UNER, Oro Verde, Argentina; Center for Rehabilitation Engineering and Neuromuscular and Sensory Research (CIRINS), National University of Entre Ríos, Oro Verde, Argentina; Center for Neuroplasticity and Pain (CNAP), Department of Health Science and Technology, Aalborg University, Aalborg, Denmark
| | - O K Andersen
- Center for Neuroplasticity and Pain (CNAP), Department of Health Science and Technology, Aalborg University, Aalborg, Denmark.
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Numasawa K, Miyamoto T, Kizuka T, Ono S. Prediction error in implicit adaptation during visually- and memory-guided reaching tasks. Sci Rep 2024; 14:8582. [PMID: 38615053 PMCID: PMC11016115 DOI: 10.1038/s41598-024-59169-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2023] [Accepted: 04/08/2024] [Indexed: 04/15/2024] Open
Abstract
Human movements are adjusted by motor adaptation in order to maintain their accuracy. There are two systems in motor adaptation, referred to as explicit or implicit adaptation. It has been suggested that the implicit adaptation is based on the prediction error and has been used in a number of motor adaptation studies. This study aimed to examine the effect of visual memory on prediction error in implicit visuomotor adaptation by comparing visually- and memory-guided reaching tasks. The visually-guided task is thought to be implicit learning based on prediction error, whereas the memory-guided task requires more cognitive processes. We observed the adaptation to visuomotor rotation feedback that is gradually rotated. We found that the adaptation and retention rates were higher in the visually-guided task than in the memory-guided task. Furthermore, the delta-band power obtained by electroencephalography (EEG) in the visually-guided task was increased immediately following the visual feedback, which indicates that the prediction error was larger in the visually-guided task. Our results show that the visuomotor adaptation is enhanced in the visually-guided task because the prediction error, which contributes update of the internal model, was more reliable than in the memory-guided task. Therefore, we suggest that the processing of the prediction error is affected by the task-type, which in turn affects the rate of the visuomotor adaptation.
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Affiliation(s)
- Kosuke Numasawa
- Graduate School of Comprehensive Human Sciences, University of Tsukuba, 1-1-1, Tennodai, Tsukuba, Ibaraki, 305-8574, Japan
| | - Takeshi Miyamoto
- Graduate School of Informatics, Nagoya University, Furo-cho, Chikusa-ku, Nagoya, 464-8601, Japan
| | - Tomohiro Kizuka
- Institute of Health and Sport Sciences, University of Tsukuba, 1-1-1, Tennodai, Tsukuba, Ibaraki, 305-8574, Japan
| | - Seiji Ono
- Institute of Health and Sport Sciences, University of Tsukuba, 1-1-1, Tennodai, Tsukuba, Ibaraki, 305-8574, Japan.
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Schwey A, Battaglia D, Bahuguna J, Malfait N. Different Faces of Medial Beta-Band Activity Reflect Distinct Visuomotor Feedback Signals. J Neurosci 2023; 43:8472-8486. [PMID: 37845035 PMCID: PMC10711699 DOI: 10.1523/jneurosci.2238-22.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Revised: 09/07/2023] [Accepted: 09/08/2023] [Indexed: 10/18/2023] Open
Abstract
Beta-band (13-35 Hz) modulations following reward, task outcome feedback, and error have been described in cognitive and/or motor adaptation tasks. Observations from different studies are, however, difficult to conciliate. Among the studies that used cognitive response selection tasks, several reported an increase in beta-band activity following reward, whereas others observed increased beta power after negative feedback. Moreover, in motor adaptation tasks, an attenuation of the postmovement beta rebound follows a movement execution error induced by visual or mechanical perturbations. Given that kinematic error typically leads to negative task-outcome feedback (e.g., target missed), one may wonder how contradictory modulations, beta power decrease with movement error versus beta power increase with negative feedback, may coexist. We designed a motor adaptation task in which female and male participants experience varied feedbacks-binary success/failure feedback, kinematic error, and sensory-prediction error-and demonstrate that beta-band modulations in opposite directions coexist at different spatial locations, time windows, and frequency ranges. First, high beta power in the medial frontal cortex showed opposite modulations well separated in time when compared in success and failure trials; that is, power was higher in success trials just after the binary success feedback, whereas it was lower in the postmovement period compared with failure trials. Second, although medial frontal high-beta activity was sensitive to task outcome, low-beta power in the medial parietal cortex was strongly attenuated following movement execution error but was not affected by either the outcome of the task or sensory-prediction error. These findings suggest that medial beta activity in different spatio-temporal-spectral configurations play a multifaceted role in encoding qualitatively distinct feedback signals.SIGNIFICANCE STATEMENT Beta-band activity reflects neural processes well beyond sensorimotor functions, including cognition and motivation. By disentangling alternative spatio-temporal-spectral patterns of possible beta-oscillatory activity, we reconcile a seemingly discrepant literature. First, high-beta power in the medial frontal cortex showed opposite modulations separated in time in success and failure trials; power was higher in success trials just after success feedback and lower in the postmovement period compared with failure trials. Second, although medial frontal high-beta activity was sensitive to task outcome, low-beta power in the medial parietal cortex was strongly attenuated following movement execution error but was not affected by the task outcome or the sensory-prediction error. We propose that medial beta activity reflects distinct feedback signals depending on its anatomic location, time window, and frequency range.
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Affiliation(s)
- Antoine Schwey
- Institut de Neurosciences de la Timone, Unité Mixte de Recherche 7289, Centre National de la Recherche Scientifique, Aix-Marseille Université, 13005 Marseille, France
| | - Demian Battaglia
- Institut de Neurosciences des Systèmes, Unité Mixte de Recherche 7289, Institut National de la Santé et de la Recherche Médicale, Aix-Marseille Université, 13005 Marseille, France
- Institut d'Etudes Avancées de l'Université de Strasbourg, Université de Strasbourg, 67084 Strasbourg, France
| | - Jyotika Bahuguna
- Institut d'Etudes Avancées de l'Université de Strasbourg, Université de Strasbourg, 67084 Strasbourg, France
- Department of Psychology, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213
| | - Nicole Malfait
- Institut de Neurosciences de la Timone, Unité Mixte de Recherche 7289, Centre National de la Recherche Scientifique, Aix-Marseille Université, 13005 Marseille, France
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Iwane F, Sobolewski A, Chavarriaga R, Millán JDR. EEG error-related potentials encode magnitude of errors and individual perceptual thresholds. iScience 2023; 26:107524. [PMID: 37636067 PMCID: PMC10448161 DOI: 10.1016/j.isci.2023.107524] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Revised: 06/15/2023] [Accepted: 07/28/2023] [Indexed: 08/29/2023] Open
Abstract
Error-related potentials (ErrPs) are a prominent electroencephalogram (EEG) correlate of performance monitoring, and so crucial for learning and adapting our behavior. It is poorly understood whether ErrPs encode further information beyond error awareness. We report an experiment with sixteen participants over three sessions in which occasional visual rotations of varying magnitude occurred during a cursor reaching task. We designed a brain-computer interface (BCI) to detect ErrPs that provided real-time feedback. The individual ErrP-BCI decoders exhibited good transfer across sessions and scalability over the magnitude of errors. A non-linear relationship between the ErrP-BCI output and the magnitude of errors predicts individual perceptual thresholds to detect errors. We also reveal theta-gamma oscillatory coupling that co-varied with the magnitude of the required adjustment. Our findings open new avenues to probe and extend current theories of performance monitoring by incorporating continuous human interaction tasks and analysis of the ErrP complex rather than individual peaks.
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Affiliation(s)
- Fumiaki Iwane
- Department of Electrical and Computer Engineering, The University of Texas at Austin, Austin, TX 78712, USA
- Department of Neurology, The University of Texas at Austin, Austin, TX 78712, USA
- Learning Algorithms and Systems Laboratory (LASA), École Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne, Switzerland
| | - Aleksander Sobolewski
- Wyss Center for Bio and Neuroengineering, Campus Biotech, 1202 Genève, Switzerland
- École Polytechnique Fédérale de Lausanne (EPFL), Campus Biotech, 1202 Genève, Switzerland
| | - Ricardo Chavarriaga
- École Polytechnique Fédérale de Lausanne (EPFL), Campus Biotech, 1202 Genève, Switzerland
- Centre for Artificial Intelligence, Zurich University of Applied Sciences (ZHAW), 8401 Winterthur, Switzerland
| | - José del R. Millán
- Department of Electrical and Computer Engineering, The University of Texas at Austin, Austin, TX 78712, USA
- Department of Neurology, The University of Texas at Austin, Austin, TX 78712, USA
- École Polytechnique Fédérale de Lausanne (EPFL), Campus Biotech, 1202 Genève, Switzerland
- Mulva Clinic for the Neurosciences, The University of Texas at Austin, Austin, TX 78712, USA
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Korka B, Will M, Avci I, Dukagjini F, Stenner MP. Strategy-based motor learning decreases the post-movement β power. Cortex 2023; 166:43-58. [PMID: 37295237 DOI: 10.1016/j.cortex.2023.05.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2023] [Revised: 04/26/2023] [Accepted: 05/05/2023] [Indexed: 06/12/2023]
Abstract
Motor learning depends on the joint contribution of several processes including cognitive strategies aiming at goal achievement and prediction error-driven implicit adaptation. Understanding this functional interplay and its clinical implications requires insight into the individual learning processes, including at a neural level. Here, we set out to examine the impact of learning a cognitive strategy, over and above implicit adaptation, on the oscillatory post-movement β rebound (PMBR), which typically decreases in power following (visuo)motor perturbations. Healthy participants performed reaching movements towards a target, with online visual feedback replacing the view of their moving hand. The feedback was sometimes rotated, either relative to their movements (visuomotor rotation) or invariant to their movements (and relative to the target; clamped feedback), always for two consecutive trials interspersed between non-rotated trials. In both conditions, the first trial with a rotation was unpredictable. On the second trial, the task was either to re-aim, and thereby compensate for the rotation experienced in the first trial (visuomotor rotation; Compensate condition), or to ignore the rotation and keep on aiming at the target (clamped feedback; Ignore condition). After-effects did not differ between conditions, indicating that the amount of implicit learning was similar, while large differences in movement direction in the second rotated trial between conditions indicated that participants successfully acquired re-aiming strategies. Importantly, PMBR power following the first rotated trial was modulated differently in the two conditions. Specifically, it decreased in both conditions, but this effect was larger when participants had to acquire a cognitive strategy and prepare to re-aim. Our results therefore suggest that the PMBR is modulated by cognitive demands of motor learning, possibly reflecting the evaluation of a behaviourally significant goal achievement error.
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Affiliation(s)
- Betina Korka
- Department of Neurology, Otto-von-Guericke University, Magdeburg, Germany; Leibniz Institute for Neurobiology, Magdeburg, Germany.
| | - Matthias Will
- Department of Neurology, Otto-von-Guericke University, Magdeburg, Germany; Leibniz Institute for Neurobiology, Magdeburg, Germany
| | - Izel Avci
- Leibniz Institute for Neurobiology, Magdeburg, Germany
| | | | - Max-Philipp Stenner
- Department of Neurology, Otto-von-Guericke University, Magdeburg, Germany; Leibniz Institute for Neurobiology, Magdeburg, Germany; Center for Behavioral Brain Sciences, Magdeburg, Germany
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8
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Herz DM, Bange M, Gonzalez-Escamilla G, Auer M, Muthuraman M, Glaser M, Bogacz R, Pogosyan A, Tan H, Groppa S, Brown P. Dynamic modulation of subthalamic nucleus activity facilitates adaptive behavior. PLoS Biol 2023; 21:e3002140. [PMID: 37262014 PMCID: PMC10234560 DOI: 10.1371/journal.pbio.3002140] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2022] [Accepted: 04/26/2023] [Indexed: 06/03/2023] Open
Abstract
Adapting actions to changing goals and environments is central to intelligent behavior. There is evidence that the basal ganglia play a crucial role in reinforcing or adapting actions depending on their outcome. However, the corresponding electrophysiological correlates in the basal ganglia and the extent to which these causally contribute to action adaptation in humans is unclear. Here, we recorded electrophysiological activity and applied bursts of electrical stimulation to the subthalamic nucleus, a core area of the basal ganglia, in 16 patients with Parkinson's disease (PD) on medication using temporarily externalized deep brain stimulation (DBS) electrodes. Patients as well as 16 age- and gender-matched healthy participants attempted to produce forces as close as possible to a target force to collect a maximum number of points. The target force changed over trials without being explicitly shown on the screen so that participants had to infer target force based on the feedback they received after each movement. Patients and healthy participants were able to adapt their force according to the feedback they received (P < 0.001). At the neural level, decreases in subthalamic beta (13 to 30 Hz) activity reflected poorer outcomes and stronger action adaptation in 2 distinct time windows (Pcluster-corrected < 0.05). Stimulation of the subthalamic nucleus reduced beta activity and led to stronger action adaptation if applied within the time windows when subthalamic activity reflected action outcomes and adaptation (Pcluster-corrected < 0.05). The more the stimulation volume was connected to motor cortex, the stronger was this behavioral effect (Pcorrected = 0.037). These results suggest that dynamic modulation of the subthalamic nucleus and interconnected cortical areas facilitates adaptive behavior.
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Affiliation(s)
- Damian M. Herz
- MRC Brain Network Dynamics Unit at the University of Oxford, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
- Movement Disorders and Neurostimulation, Department of Neurology, Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Manuel Bange
- Movement Disorders and Neurostimulation, Department of Neurology, Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Gabriel Gonzalez-Escamilla
- Movement Disorders and Neurostimulation, Department of Neurology, Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Miriam Auer
- Movement Disorders and Neurostimulation, Department of Neurology, Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Muthuraman Muthuraman
- Movement Disorders and Neurostimulation, Department of Neurology, Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
- Neural Engineering with Signal Analytics and Artificial Intelligence, Department of Neurology, University Hospital of Wuerzburg, Wuerzburg, Germany
| | - Martin Glaser
- Department of Neurosurgery, University Medical Center of the Johannes Gutenberg-University Mainz, Germany
| | - Rafal Bogacz
- MRC Brain Network Dynamics Unit at the University of Oxford, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Alek Pogosyan
- MRC Brain Network Dynamics Unit at the University of Oxford, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Huiling Tan
- MRC Brain Network Dynamics Unit at the University of Oxford, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Sergiu Groppa
- Movement Disorders and Neurostimulation, Department of Neurology, Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Peter Brown
- MRC Brain Network Dynamics Unit at the University of Oxford, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
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9
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Wiegel P, Elizabeth Spedden M, Ramsenthaler C, Malling Beck M, Lundbye-Jensen J. Trial-to-trial Variability and Cortical Processing Depend on Recent Outcomes During Human Reinforcement Motor Learning. Neuroscience 2022; 501:85-102. [PMID: 35970424 DOI: 10.1016/j.neuroscience.2022.08.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2022] [Revised: 07/22/2022] [Accepted: 08/09/2022] [Indexed: 10/15/2022]
Abstract
The history of our actions and their outcomes represent important information, informing choices and efficiently guiding future behavior. While unsuccessful (S-) outcomes are expected to lead to more explorative motor states and increased behavioral variability, successful (S+) outcomes are expected to reinforce the use of the previous action. Here, we show that humans attribute different values to previous actions during reinforcement motor learning when they experience S- compared to S+ outcomes. Behavioral variability after an S- outcome is influenced more by the previous outcome than after S+ outcomes. Using electroencephalography, we show that theta band oscillations of the prefrontal cortex are most prominent during changes in two consecutive outcomes, potentially reflecting the need for enhanced cognitive control. Our results suggest that S+ experiences 'overwrite' previous motor states to a greater extent than S- experiences and that modulations in neural oscillations in the prefrontal cortex play a potential role in encoding changes in movement variability state during reinforcement motor learning.
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Affiliation(s)
- Patrick Wiegel
- Movement & Neuroscience, Department of Nutrition, Exercise & Sports, University of Copenhagen, Denmark.
| | - Meaghan Elizabeth Spedden
- Movement & Neuroscience, Department of Nutrition, Exercise & Sports, University of Copenhagen, Denmark
| | - Christina Ramsenthaler
- Clinic for Palliative Care, University Medical Center Freiburg, Freiburg, Germany; Wolfson Palliative Care Research Centre, Hull & York Medical School, University of Hull, Hull, UK; Cicely Saunders Institute, Department of Palliative Care, Policy & Rehabilitation, King's College London, London, UK
| | - Mikkel Malling Beck
- Movement & Neuroscience, Department of Nutrition, Exercise & Sports, University of Copenhagen, Denmark
| | - Jesper Lundbye-Jensen
- Movement & Neuroscience, Department of Nutrition, Exercise & Sports, University of Copenhagen, Denmark
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10
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Lai HJ, Deng CR, Wang RW, Lee LHN, Kuo CC. The genesis and functional consequences of cortico-subthalamic beta augmentation and excessive subthalamic burst discharges after dopaminergic deprivation. Exp Neurol 2022; 356:114153. [PMID: 35752209 DOI: 10.1016/j.expneurol.2022.114153] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2022] [Revised: 05/19/2022] [Accepted: 06/18/2022] [Indexed: 11/24/2022]
Abstract
The cardinal electrophysiological signs in Parkinson's disease (PD) include augmented beta oscillations in the motor cortex-subthalamic nucleus (MC-STN) axis and excessive burst discharges in STN. We have shown that excessive STN burst discharges have a direct causal relation with the locomotor deficits in PD. To investigate the correlation between the two cardinal signs, we characterized the courses of development of the electrophysiological abnormalities in the hemiparkinsonian rat model. The loss of dopaminergic neurons develops fast, and is histologically completed within 4-7 days of the lesion. The increase in STN burst discharges is limited to the lesioned side, and follows a very similar course. In contrast, beta augmentation has a bilateral presentation, and requires 14-21 days for full development. Behaviorally, the gross locomotor deficits in open field test and limb akinesia in stepping test match the foregoing fast and slow time courses, respectively. A further look into the spike entrainment shows that the oscillations in local field potential (LFP) of the MC effectively entrain the multi-unit (MU) spikes of MC, STN and entopeduncular nucleus (EPN), a rat homolog of human globus pallidus interna (GPi), whereas the LFP of STN or EPN (GPi) cannot entrain the spikes in MC. We conclude that excessive STN burst discharges are a direct consequence, whereas beta augmentation is probably a secondary or adaptive changes in the cortico-subcortical re-entrant loops, to dopaminergic deprivation. Beta augmentation is therefore not so consistently present as excessive STN burst discharges, but could signal more delicate derangements at the level of cortical programming in PD.
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Affiliation(s)
- Hsing-Jung Lai
- Institute of Physiology, National Taiwan University College of Medicine, Taipei, Taiwan.; Department of Neurology, National Taiwan University Hospital, Taipei, Taiwan; National Taiwan University Hospital, Jin-Shan Branch, New Taipei, Taiwan
| | - Chuan-Rou Deng
- Institute of Physiology, National Taiwan University College of Medicine, Taipei, Taiwan
| | - Ren-Wei Wang
- Institute of Physiology, National Taiwan University College of Medicine, Taipei, Taiwan
| | - Lan-Hsin Nancy Lee
- Institute of Physiology, National Taiwan University College of Medicine, Taipei, Taiwan
| | - Chung-Chin Kuo
- Institute of Physiology, National Taiwan University College of Medicine, Taipei, Taiwan..
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Using EEG to study sensorimotor adaptation. Neurosci Biobehav Rev 2022; 134:104520. [PMID: 35016897 DOI: 10.1016/j.neubiorev.2021.104520] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2021] [Revised: 12/10/2021] [Accepted: 12/30/2021] [Indexed: 11/23/2022]
Abstract
Sensorimotor adaptation, or the capacity to flexibly adapt movements to changes in the body or the environment, is crucial to our ability to move efficiently in a dynamic world. The field of sensorimotor adaptation is replete with rigorous behavioural and computational methods, which support strong conceptual frameworks. An increasing number of studies have combined these methods with electroencephalography (EEG) to unveil insights into the neural mechanisms of adaptation. We review these studies: discussing EEG markers of adaptation in the frequency and the temporal domain, EEG predictors for successful adaptation and how EEG can be used to unmask latent processes resulting from adaptation, such as the modulation of spatial attention. With its high temporal resolution, EEG can be further exploited to deepen our understanding of sensorimotor adaptation.
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12
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Asci F, Eusebio A, Suppa A. Are beta oscillations always anti-kinetic in Parkinson’s disease? Clin Neurophysiol 2022; 136:235-236. [DOI: 10.1016/j.clinph.2022.01.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2022] [Accepted: 01/18/2022] [Indexed: 11/25/2022]
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13
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De Havas J, Haggard P, Gomi H, Bestmann S, Ikegaya Y, Hagura N. Evidence that endpoint feedback facilitates intermanual transfer of visuomotor force learning by a cognitive strategy. J Neurophysiol 2022; 127:16-26. [PMID: 34879215 PMCID: PMC8794053 DOI: 10.1152/jn.00008.2021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Humans continuously adapt their movement to a novel environment by recalibrating their sensorimotor system. Recent evidence, however, shows that explicit planning to compensate for external changes, i.e., a cognitive strategy, can also aid performance. If such a strategy is planned in external space, it should improve performance in an effector-independent manner. We tested this hypothesis by examining whether promoting a cognitive strategy during a visual-force adaptation task performed in one hand can facilitate learning for the opposite hand. Participants rapidly adjusted the height of visual bar on screen to a target level by isometrically exerting force on a handle using their right hand. Visuomotor gain increased during the task and participants learned the increased gain. Visual feedback was continuously provided for one group, whereas for another group only the endpoint of the force trajectory was presented. The latter has been reported to promote cognitive strategy use. We found that endpoint feedback produced stronger intermanual transfer of learning and slower response times than continuous feedback. In a separate experiment, we found evidence that aftereffects are reduced when only endpoint feedback is provided, a finding that has been consistently observed when cognitive strategies are used. The results suggest that intermanual transfer can be facilitated by a cognitive strategy. This indicates that the behavioral observation of intermanual transfer can be achieved either by forming an effector-independent motor representation or by sharing an effector-independent cognitive strategy between the hands. NEW & NOTEWORTHY The causes and consequences of cognitive strategy use are poorly understood. We tested whether a visuomotor task learned in a manner that may promote cognitive strategy use causes greater generalization across effectors. Visual feedback was manipulated to promote cognitive strategy use. Learning consistent with cognitive strategy use for one hand transferred to the unlearned hand. Our result suggests that intermanual transfer can result from a common cognitive strategy used to control both hands.
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Affiliation(s)
- Jack De Havas
- NTT Communication Science Laboratories, Atsugi, Japan.,Institute of Cognitive Neuroscience, University College London, London, United Kingdom.,Center for Information and Neural Networks, National Institute for Information and Communications Technology, Osaka, Japan
| | - Patrick Haggard
- Institute of Cognitive Neuroscience, University College London, London, United Kingdom
| | - Hiroaki Gomi
- NTT Communication Science Laboratories, Atsugi, Japan
| | - Sven Bestmann
- UCL Queen Square Institute of Neurology, Department of Clinical and Movement Neurosciences, University College London, London, United Kingdom.,Wellcome Centre for Human Neuroimaging, University College London, London, United Kingdom
| | - Yuji Ikegaya
- Center for Information and Neural Networks, National Institute for Information and Communications Technology, Osaka, Japan.,Faculty of Pharmaceutical Sciences, Graduate School of Pharmaceutical Sciences, The University of Tokyo, Tokyo, Japan
| | - Nobuhiro Hagura
- Center for Information and Neural Networks, National Institute for Information and Communications Technology, Osaka, Japan.,Graduate School of Frontier Biosciences, Osaka University, Osaka, Japan
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14
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Struber L, Baumont M, Barraud PA, Nougier V, Cignetti F. Brain oscillatory correlates of visuomotor adaptive learning. Neuroimage 2021; 245:118645. [PMID: 34687861 DOI: 10.1016/j.neuroimage.2021.118645] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2021] [Revised: 10/06/2021] [Accepted: 10/10/2021] [Indexed: 11/24/2022] Open
Abstract
Sensorimotor adaptation involves the recalibration of the mapping between motor command and sensory feedback in response to movement errors. Although adaptation operates within individual movements on a trial-to-trial basis, it can also undergo learning when adaptive responses improve over the course of many trials. Brain oscillatory activities related to these "adaptation" and "learning" processes remain unclear. The main reason for this is that previous studies principally focused on the beta band, which confined the outcome message to trial-to-trial adaptation. To provide a wider understanding of adaptive learning, we decoded visuomotor tasks with constant, random or no perturbation from EEG recordings in different bandwidths and brain regions using a multiple kernel learning approach. These different experimental tasks were intended to separate trial-to-trial adaptation from the formation of the new visuomotor mapping across trials. We found changes in EEG power in the post-movement period during the course of the visuomotor-constant rotation task, in particular an increased (i) theta power in prefrontal region, (ii) beta power in supplementary motor area, and (iii) gamma power in motor regions. Classifying the visuomotor task with constant rotation versus those with random or no rotation, we were able to relate power changes in beta band mainly to trial-to-trial adaptation to error while changes in theta band would relate rather to the learning of the new mapping. Altogether, this suggested that there is a tight relationship between modulation of the synchronization of low (theta) and higher (essentially beta) frequency oscillations in prefrontal and sensorimotor regions, respectively, and adaptive learning.
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Affiliation(s)
- Lucas Struber
- Univ. Grenoble Alpes, CNRS, UMR 5525, VetAgro Sup, Grenoble INP, TIMC, 38000 Grenoble, France.
| | - Marie Baumont
- Univ. Grenoble Alpes, CNRS, UMR 5525, VetAgro Sup, Grenoble INP, TIMC, 38000 Grenoble, France
| | - Pierre-Alain Barraud
- Univ. Grenoble Alpes, CNRS, UMR 5525, VetAgro Sup, Grenoble INP, TIMC, 38000 Grenoble, France
| | - Vincent Nougier
- Univ. Grenoble Alpes, CNRS, UMR 5525, VetAgro Sup, Grenoble INP, TIMC, 38000 Grenoble, France
| | - Fabien Cignetti
- Univ. Grenoble Alpes, CNRS, UMR 5525, VetAgro Sup, Grenoble INP, TIMC, 38000 Grenoble, France
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15
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Maresch J, Mudrik L, Donchin O. Measures of explicit and implicit in motor learning: what we know and what we don't. Neurosci Biobehav Rev 2021; 128:558-568. [PMID: 34214514 DOI: 10.1016/j.neubiorev.2021.06.037] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2021] [Revised: 06/21/2021] [Accepted: 06/25/2021] [Indexed: 11/19/2022]
Abstract
Adaptation tasks are a key tool in characterizing the contribution of explicit and implicit processes to sensorimotor learning. However, different assumptions and ideas underlie methods used to measure these processes, leading to inconsistencies between studies. For instance, it is still unclear explicit and implicit combine additively. Cognitive studies of explicit and implicit processes show how non-additivity and bias in measurement can distort results. We argue that to understand explicit and implicit processes in visuomotor adaptation, we need a stronger characterization of the phenomenology and a richer set of models to test it on.
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Affiliation(s)
- Jana Maresch
- Department of Brain and Cognitive Sciences, Ben Gurion University of the Negev, Be'er Sheva, Israel.
| | - Liad Mudrik
- Sagol School of Neuroscience and School of Psychological Sciences, Tel Aviv University, PO Box 39040, Tel Aviv, 69978, Israel.
| | - Opher Donchin
- Department of Biomedical Engineering and Zlotowski Center for Neuroscience, Ben-Gurion University of the Negev, P.O.B. 653, Be'er Sheva, 8410501, Israel.
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Haar S, Faisal AA. Brain Activity Reveals Multiple Motor-Learning Mechanisms in a Real-World Task. Front Hum Neurosci 2020; 14:354. [PMID: 32982707 PMCID: PMC7492608 DOI: 10.3389/fnhum.2020.00354] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2020] [Accepted: 08/05/2020] [Indexed: 11/22/2022] Open
Abstract
Many recent studies found signatures of motor learning in neural beta oscillations (13-30 Hz), and specifically in the post-movement beta rebound (PMBR). All these studies were in controlled laboratory-tasks in which the task designed to induce the studied learning mechanism. Interestingly, these studies reported opposing dynamics of the PMBR magnitude over learning for the error-based and reward-based tasks (increase vs. decrease, respectively). Here, we explored the PMBR dynamics during real-world motor-skill-learning in a billiards task using mobile-brain-imaging. Our EEG recordings highlight the opposing dynamics of PMBR magnitudes (increase vs. decrease) between different subjects performing the same task. The groups of subjects, defined by their neural dynamics, also showed behavioral differences expected for different learning mechanisms. Our results suggest that when faced with the complexity of the real-world different subjects might use different learning mechanisms for the same complex task. We speculate that all subjects combine multi-modal mechanisms of learning, but different subjects have different predominant learning mechanisms.
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Affiliation(s)
- Shlomi Haar
- Brain and Behaviour Laboratory, Department of Bioengineering, Imperial College London, London, United Kingdom
- Behaviour Analytics Lab, Data Science Institute, Imperial College London, London, United Kingdom
| | - A. Aldo Faisal
- Brain and Behaviour Laboratory, Department of Bioengineering, Imperial College London, London, United Kingdom
- Behaviour Analytics Lab, Data Science Institute, Imperial College London, London, United Kingdom
- Department of Computing, Imperial College London, London, United Kingdom
- MRC London Institute of Medical Sciences, London, United Kingdom
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