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Vaz A, Wathen C, Miranda S, Thomas R, Darlington T, Jabarkheel R, Tomlinson S, Arena J, Bond K, Salwi S, Ajmera S, Bachschmid-Romano L, Gugger J, Sandsmark D, Diaz-Arrastia R, Schuster J, Ramayya AG, Cajigas I, Pesaran B, Chen HI, Petrov D. Return of intracranial beta oscillations and traveling waves with recovery from traumatic brain injury. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.19.604293. [PMID: 39091808 PMCID: PMC11291083 DOI: 10.1101/2024.07.19.604293] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 08/04/2024]
Abstract
Traumatic brain injury (TBI) remains a pervasive clinical problem associated with significant morbidity and mortality. However, TBI remains clinically and biophysically ill-defined, and prognosis remains difficult even with the standardization of clinical guidelines and advent of multimodality monitoring. Here we leverage a unique data set from TBI patients implanted with either intracranial strip electrodes during craniotomy or quad-lumen intracranial bolts with depth electrodes as part of routine clinical practice. By extracting spectral profiles of this data, we found that the presence of narrow-band oscillatory activity in the beta band (12-30 Hz) closely corresponds with the neurological exam as quantified with the standard Glasgow Coma Scale (GCS). Further, beta oscillations were distributed over the cortical surface as traveling waves, and the evolution of these waves corresponded to recovery from coma, consistent with the putative role of waves in perception and cognitive activity. We consequently propose that beta oscillations and traveling waves are potential biomarkers of recovery from TBI. In a broader sense, our findings suggest that emergence from coma results from recovery of thalamo-cortical interactions that coordinate cortical beta rhythms.
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Affiliation(s)
- Alex Vaz
- Department of Neurosurgery, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Surgical Neurology Branch, NINDS, National Institutes of Health, Bethesda, MD 20892, USA
| | - Connor Wathen
- Department of Neurosurgery, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Stephen Miranda
- Department of Neurosurgery, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Rachel Thomas
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Timothy Darlington
- Department of Neurosurgery, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Rashad Jabarkheel
- Department of Neurosurgery, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Samuel Tomlinson
- Department of Neurosurgery, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - John Arena
- Department of Neurosurgery, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Kamila Bond
- Department of Neurosurgery, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Sanjana Salwi
- Department of Neurosurgery, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Sonia Ajmera
- Department of Neurosurgery, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | | | - James Gugger
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Danielle Sandsmark
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Ramon Diaz-Arrastia
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - James Schuster
- Department of Neurosurgery, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Ashwin G Ramayya
- Department of Neurosurgery, Stanford University, Palo Alto, CA, 94305, USA
| | - Iahn Cajigas
- Department of Neurosurgery, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Bijan Pesaran
- Department of Neurosurgery, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - H Isaac Chen
- Department of Neurosurgery, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Corporal Michael J. Crescenz Veterans Affairs Medical Center, Philadelphia, PA 19104, USA
| | - Dmitriy Petrov
- Department of Neurosurgery, University of Pennsylvania, Philadelphia, PA, 19104, USA
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2
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Adham A, Le BT, Bonnal J, Bessaguet H, Ojardias E, Giraux P, Auzou P. Neural basis of lower-limb visual feedback therapy: an EEG study in healthy subjects. J Neuroeng Rehabil 2024; 21:114. [PMID: 38978051 PMCID: PMC11229246 DOI: 10.1186/s12984-024-01408-8] [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: 02/15/2024] [Accepted: 06/20/2024] [Indexed: 07/10/2024] Open
Abstract
BACKGROUND Video-feedback observational therapy (VOT) is an intensive rehabilitation technique based on movement repetition and visualization that has shown benefits for motor rehabilitation of the upper and lower limbs. Despite an increase in recent literature on the neurophysiological effects of VOT in the upper limb, there is little knowledge about the cortical effects of visual feedback therapies when applied to the lower limbs. The aim of our study was to better understand the neurophysiological effects of VOT. Thus, we identified and compared the EEG biomarkers of healthy subjects undergoing lower limb VOT during three tasks: passive observation, observation and motor imagery, observation and motor execution. METHODS We recruited 38 healthy volunteers and monitored their EEG activity while they performed a right ankle dorsiflexion task in the VOT. Three graded motor tasks associated with action observation were tested: action observation alone (O), motor imagery with action observation (OI), and motor execution synchronized with action observation (OM). The alpha and beta event-related desynchronization (ERD) and event-related synchronization (or beta rebound, ERS) rhythms were used as biomarkers of cortical activation and compared between conditions with a permutation test. Changes in connectivity during the task were computed with phase locking value (PLV). RESULTS During the task, in the alpha band, the ERD was comparable between O and OI activities across the precentral, central and parietal electrodes. OM involved the same regions but had greater ERD over the central electrodes. In the beta band, there was a gradation of ERD intensity in O, OI and OM over central electrodes. After the task, the ERS changes were weak during the O task but were strong during the OI and OM (Cz) tasks, with no differences between OI and OM. CONCLUSION Alpha band ERD results demonstrated the recruitment of mirror neurons during lower limb VOT due to visual feedback. Beta band ERD reflects strong recruitment of the sensorimotor cortex evoked by motor imagery and action execution. These results also emphasize the need for an active motor task, either motor imagery or motor execution task during VOT, to elicit a post-task ERS, which is absent during passive observation. Trial Registration NCT05743647.
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Affiliation(s)
- Ahmed Adham
- Department of Physical Rehabilitation, CHU of St Etienne, Saint-Étienne, France.
- Laboratory Trajectoires, INSERM 1028, CNRS 5229, University of Lyon-St-Etienne, Saint-Étienne, France.
- Univ. Grenoble Alpes, CEA, LETI, Clinatec, Grenoble, France.
| | - Ba Thien Le
- Department of Neurology, CHU of Orleans, Orleans, France
| | - Julien Bonnal
- Department of Neurology, CHU of Orleans, Orleans, France
| | - Hugo Bessaguet
- Department of Physical Rehabilitation, CHU of St Etienne, Saint-Étienne, France
- Jean Monnet University, Lyon 1, Université Savoie Mont-Blanc, "Laboratoire Inter-Universitaire de Biologie de La Motricité", 42023, Saint-Étienne, France
| | - Etienne Ojardias
- Department of Physical Rehabilitation, CHU of St Etienne, Saint-Étienne, France
- Jean Monnet University, Lyon 1, Université Savoie Mont-Blanc, "Laboratoire Inter-Universitaire de Biologie de La Motricité", 42023, Saint-Étienne, France
| | - Pascal Giraux
- Department of Physical Rehabilitation, CHU of St Etienne, Saint-Étienne, France
- Laboratory Trajectoires, INSERM 1028, CNRS 5229, University of Lyon-St-Etienne, Saint-Étienne, France
| | - Pascal Auzou
- Department of Neurology, CHU of Orleans, Orleans, France
- "Laboratoire Interdisciplinaire d'innovation et de Recherche en Santé d'Orléans", LI2RSO, University of Orleans, Orleans, France
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Vissani M, Bush A, Lipski WJ, Fischer P, Neudorfer C, Holt LL, Fiez JA, Turner RS, Richardson RM. Spike-phase coupling of subthalamic neurons to posterior opercular cortex predicts speech sound accuracy. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.10.18.562969. [PMID: 37905141 PMCID: PMC10614892 DOI: 10.1101/2023.10.18.562969] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/02/2023]
Abstract
Speech provides a rich context for understanding how cortical interactions with the basal ganglia contribute to unique human behaviors, but opportunities for direct intracranial recordings across cortical-basal ganglia networks are rare. We recorded electrocorticographic signals in the cortex synchronously with single units in the basal ganglia during awake neurosurgeries where subjects spoke syllable repetitions. We discovered that individual STN neurons have transient (200ms) spike-phase coupling (SPC) events with multiple cortical regions. The spike timing of STN neurons was coordinated with the phase of theta-alpha oscillations in the posterior supramarginal and superior temporal gyrus during speech planning and production. Speech sound errors occurred when this STN-cortical interaction was delayed. Our results suggest that the STN supports mechanisms of speech planning and auditory-sensorimotor integration during speech production that are required to achieve high fidelity of the phonological and articulatory representation of the target phoneme. These findings establish a framework for understanding cortical-basal ganglia interaction in other human behaviors, and additionally indicate that firing-rate based models are insufficient for explaining basal ganglia circuit behavior.
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Affiliation(s)
- Matteo Vissani
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, 02114, USA
- Harvard Medical School, Boston, MA, 02115, USA
| | - Alan Bush
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, 02114, USA
- Harvard Medical School, Boston, MA, 02115, USA
| | - Witold J. Lipski
- Department of Neurobiology, Systems Neuroscience Center and Center for Neuroscience, University of Pittsburgh School of Medicine, Pittsburgh, PA, 15213, USA
| | - Petra Fischer
- School of Physiology, Pharmacology & Neuroscience, University of Bristol, University Walk, BS8 1TD Bristol, United Kingdom
| | - Clemens Neudorfer
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, 02114, USA
- Harvard Medical School, Boston, MA, 02115, USA
| | - Lori L. Holt
- Department of Psychology, The University of Texas at Austin, Austin, TX 78712 USA
| | - Julie A. Fiez
- Department of Psychology, University of Pittsburgh, Pittsburgh 15260, PA, USA
| | - Robert S. Turner
- Department of Neurobiology, Systems Neuroscience Center and Center for Neuroscience, University of Pittsburgh School of Medicine, Pittsburgh, PA, 15213, USA
| | - R. Mark Richardson
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, 02114, USA
- Harvard Medical School, Boston, MA, 02115, USA
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Sihn D, Kim SP. Disruption of alpha oscillation propagation in patients with schizophrenia. Clin Neurophysiol 2024; 162:262-270. [PMID: 38480063 DOI: 10.1016/j.clinph.2024.02.028] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2023] [Revised: 01/18/2024] [Accepted: 02/17/2024] [Indexed: 05/19/2024]
Abstract
OBJECTIVE Propagation of electroencephalogram (EEG) oscillations, often referred to as traveling waves, reflects the role of brain oscillations in neural information transmission. This propagation can be distorted by brain disorders such as schizophrenia that features disconnection of neural information transmission (i.e., disconnection syndrome). However, this possibility of the disruption of EEG oscillation propagation in patients with schizophrenia remains largely unexplored. METHODS Using a publicly shared dataset (N = 19 and 24; patients with schizophrenia and healthy controls, respectively), we investigated EEG oscillation propagation by analyzing the local phase gradients (LPG) of alpha (8-12 Hz) oscillations in both healthy participants and patients with schizophrenia. RESULTS Our results showed significant directionality in the propagation of alpha oscillations in healthy participants. Specifically, alpha oscillations propagated in an anterior-to-posterior direction along mid-line and a posterior-to-anterior direction laterally. In patients with schizophrenia, some of alpha oscillation propagation were notably disrupted, particularly in the central midline area where alpha oscillations propagated from anterior to posterior areas. CONCLUSION Our finding lends support to the hypothesis of a disconnection syndrome in schizophrenia, underscoring a disruption in the anterior-to-posterior propagation of alpha oscillations. SIGNIFICANCE This study identified disruption of alpha oscillation propagation observed in scalp EEG as a biomarker for schizophrenia.
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Affiliation(s)
- Duho Sihn
- Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, Ulsan 44919, Republic of Korea
| | - Sung-Phil Kim
- Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, Ulsan 44919, Republic of Korea.
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5
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Mohan UR, Zhang H, Ermentrout B, Jacobs J. The direction of theta and alpha travelling waves modulates human memory processing. Nat Hum Behav 2024; 8:1124-1135. [PMID: 38459263 DOI: 10.1038/s41562-024-01838-3] [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: 07/14/2023] [Accepted: 01/24/2024] [Indexed: 03/10/2024]
Abstract
To support a range of behaviours, the brain must flexibly coordinate neural activity across widespread brain regions. One potential mechanism for this coordination is a travelling wave, in which a neural oscillation propagates across the brain while organizing the order and timing of activity across regions. Although travelling waves are present across the brain in various species, their potential functional relevance has remained unknown. Here, using rare direct human brain recordings, we demonstrate a distinct functional role for travelling waves of theta- and alpha-band (2-13 Hz) oscillations in the cortex. Travelling waves propagate in different directions during separate cognitive processes. In episodic memory, travelling waves tended to propagate in a posterior-to-anterior direction during successful memory encoding and in an anterior-to-posterior direction during recall. Because travelling waves of oscillations correspond to local neuronal spiking, these patterns indicate that rhythmic pulses of activity move across the brain in different directions for separate behaviours. More broadly, our results suggest a fundamental role for travelling waves and oscillations in dynamically coordinating neural connectivity, by flexibly organizing the timing and directionality of network interactions across the cortex to support cognition and behaviour.
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Affiliation(s)
- Uma R Mohan
- Surgical Neurology Branch, NINDS, National Institutes of Health, Bethesda, MD, USA
| | | | - Bard Ermentrout
- Department of Mathematics, University of Pittsburgh, Pittsburgh, PA, USA
| | - Joshua Jacobs
- Department of Biomedical Engineering, Columbia University, New York City, NY, USA.
- Department of Neurological Surgery, Columbia University, New York City, NY, USA.
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6
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Koller DP, Schirner M, Ritter P. Human connectome topology directs cortical traveling waves and shapes frequency gradients. Nat Commun 2024; 15:3570. [PMID: 38670965 PMCID: PMC11053146 DOI: 10.1038/s41467-024-47860-x] [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: 04/29/2023] [Accepted: 04/09/2024] [Indexed: 04/28/2024] Open
Abstract
Traveling waves and neural oscillation frequency gradients are pervasive in the human cortex. While the direction of traveling waves has been linked to brain function and dysfunction, the factors that determine this direction remain elusive. We hypothesized that structural connectivity instrength gradients - defined as the gradually varying sum of incoming connection strengths across the cortex - could shape both traveling wave direction and frequency gradients. We confirm the presence of instrength gradients in the human connectome across diverse cohorts and parcellations. Using a cortical network model, we demonstrate how these instrength gradients direct traveling waves and shape frequency gradients. Our model fits resting-state MEG functional connectivity best in a regime where instrength-directed traveling waves and frequency gradients emerge. We further show how structural subnetworks of the human connectome generate opposing wave directions and frequency gradients observed in the alpha and beta bands. Our findings suggest that structural connectivity instrength gradients affect both traveling wave direction and frequency gradients.
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Grants
- P.R. acknowledges funding from the following sources: Digital Europe Grant TEF-Health # 101100700, H2020 Research and Innovation Action Grant Human Brain Project SGA2 785907, H2020 Research and Innovation Action Grant Human Brain Project SGA3 945539, H2020 Research and Innovation Action Grant EOSC VirtualBrainCloud 826421, H2020 Research and Innovation Action Grant AISN 101057655, H2020 Research Infrastructures Grant EBRAINS-PREP 101079717, H2020 European Innovation Council PHRASE 101058240, H2020 Research Infrastructures Grant EBRAIN-Health 101058516, H2020 European Research Council Grant ERC BrainModes 683049, JPND ERA PerMed PatternCog 2522FSB904, Berlin Institute of Health & Foundation Charité, Johanna Quandt Excellence Initiative, German Research Foundation SFB 1436 (project ID 425899996), German Research Foundation SFB 1315 (project ID 327654276), German Research Foundation SFB 936 (project ID 178316478), German Research Foundation SFB-TRR 295 (project ID 424778381) German Research Foundation SPP Computational Connectomics RI 2073/6-1, RI 2073/10-2, RI 2073/9-1.
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Affiliation(s)
- Dominik P Koller
- Berlin Institute of Health (BIH) at Charité - Universitätsmedizin Berlin, Charitéplatz 1, 10117, Berlin, Germany.
- Department of Neurology with Experimental Neurology, Charité, Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin and Humboldt Universität zu Berlin, Charitéplatz 1, 10117, Berlin, Germany.
| | - Michael Schirner
- Berlin Institute of Health (BIH) at Charité - Universitätsmedizin Berlin, Charitéplatz 1, 10117, Berlin, Germany
- Department of Neurology with Experimental Neurology, Charité, Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin and Humboldt Universität zu Berlin, Charitéplatz 1, 10117, Berlin, Germany
- Bernstein Focus State Dependencies of Learning and Bernstein Center for Computational Neuroscience, 10115, Berlin, Germany
- Einstein Center for Neuroscience Berlin, Charitéplatz 1, 10117, Berlin, Germany
- Einstein Center Digital Future, Wilhelmstraße 67, 10117, Berlin, Germany
| | - Petra Ritter
- Berlin Institute of Health (BIH) at Charité - Universitätsmedizin Berlin, Charitéplatz 1, 10117, Berlin, Germany.
- Department of Neurology with Experimental Neurology, Charité, Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin and Humboldt Universität zu Berlin, Charitéplatz 1, 10117, Berlin, Germany.
- Bernstein Focus State Dependencies of Learning and Bernstein Center for Computational Neuroscience, 10115, Berlin, Germany.
- Einstein Center for Neuroscience Berlin, Charitéplatz 1, 10117, Berlin, Germany.
- Einstein Center Digital Future, Wilhelmstraße 67, 10117, Berlin, Germany.
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7
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Weber J, Solbakk AK, Blenkmann AO, Llorens A, Funderud I, Leske S, Larsson PG, Ivanovic J, Knight RT, Endestad T, Helfrich RF. Ramping dynamics and theta oscillations reflect dissociable signatures during rule-guided human behavior. Nat Commun 2024; 15:637. [PMID: 38245516 PMCID: PMC10799948 DOI: 10.1038/s41467-023-44571-7] [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: 02/12/2022] [Accepted: 12/19/2023] [Indexed: 01/22/2024] Open
Abstract
Contextual cues and prior evidence guide human goal-directed behavior. The neurophysiological mechanisms that implement contextual priors to guide subsequent actions in the human brain remain unclear. Using intracranial electroencephalography (iEEG), we demonstrate that increasing uncertainty introduces a shift from a purely oscillatory to a mixed processing regime with an additional ramping component. Oscillatory and ramping dynamics reflect dissociable signatures, which likely differentially contribute to the encoding and transfer of different cognitive variables in a cue-guided motor task. The results support the idea that prefrontal activity encodes rules and ensuing actions in distinct coding subspaces, while theta oscillations synchronize the prefrontal-motor network, possibly to guide action execution. Collectively, our results reveal how two key features of large-scale neural population activity, namely continuous ramping dynamics and oscillatory synchrony, jointly support rule-guided human behavior.
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Affiliation(s)
- Jan Weber
- Hertie Institute for Clinical Brain Research, Center for Neurology, University Medical Center Tübingen, Tübingen, Germany
- International Max Planck Research School for the Mechanisms of Mental Function and Dysfunction, University of Tübingen, Tübingen, Germany
| | - Anne-Kristin Solbakk
- Department of Psychology, University of Oslo, Oslo, Norway
- RITMO Centre for Interdisciplinary Studies in Rhythm, Time and Motion, University of Oslo, Oslo, Norway
- Department of Neurosurgery, Oslo University Hospital, Oslo, Norway
- Department of Neuropsychology, Helgeland Hospital, Mosjøen, Norway
| | - Alejandro O Blenkmann
- Department of Psychology, University of Oslo, Oslo, Norway
- RITMO Centre for Interdisciplinary Studies in Rhythm, Time and Motion, University of Oslo, Oslo, Norway
| | - Anais Llorens
- Department of Psychology, University of Oslo, Oslo, Norway
- RITMO Centre for Interdisciplinary Studies in Rhythm, Time and Motion, University of Oslo, Oslo, Norway
- Helen Wills Neuroscience Institute, UC Berkeley, Berkeley, CA, USA
| | - Ingrid Funderud
- Department of Psychology, University of Oslo, Oslo, Norway
- RITMO Centre for Interdisciplinary Studies in Rhythm, Time and Motion, University of Oslo, Oslo, Norway
- Department of Neuropsychology, Helgeland Hospital, Mosjøen, Norway
| | - Sabine Leske
- Department of Psychology, University of Oslo, Oslo, Norway
- RITMO Centre for Interdisciplinary Studies in Rhythm, Time and Motion, University of Oslo, Oslo, Norway
- Department of Musicology, University of Oslo, Oslo, Norway
| | | | | | - Robert T Knight
- Helen Wills Neuroscience Institute, UC Berkeley, Berkeley, CA, USA
- Department of Psychology, UC Berkeley, Berkeley, CA, USA
| | - Tor Endestad
- Department of Psychology, University of Oslo, Oslo, Norway
- RITMO Centre for Interdisciplinary Studies in Rhythm, Time and Motion, University of Oslo, Oslo, Norway
| | - Randolph F Helfrich
- Hertie Institute for Clinical Brain Research, Center for Neurology, University Medical Center Tübingen, Tübingen, Germany.
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8
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Zabeh E, Foley NC, Jacobs J, Gottlieb JP. Beta traveling waves in monkey frontal and parietal areas encode recent reward history. Nat Commun 2023; 14:5428. [PMID: 37669966 PMCID: PMC10480436 DOI: 10.1038/s41467-023-41125-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Accepted: 08/22/2023] [Indexed: 09/07/2023] Open
Abstract
Brain function depends on neural communication, but the mechanisms of this communication are not well understood. Recent studies suggest that one form of neural communication is through traveling waves (TWs)-patterns of neural oscillations that propagate within and between brain areas. We show that TWs are robust in microarray recordings in frontal and parietal cortex and encode recent reward history. Two adult male monkeys made saccades to obtain probabilistic rewards and were sensitive to the (statistically irrelevant) reward on the previous trial. TWs in frontal and parietal areas were stronger in trials that followed a prior reward versus a lack of reward and, in the frontal lobe, correlated with the monkeys' behavioral sensitivity to the prior reward. The findings suggest that neural communication mediated by TWs within the frontal and parietal lobes contribute to maintaining information about recent reward history and mediating the impact of this history on the monkeys' expectations.
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Affiliation(s)
- Erfan Zabeh
- Department of Biomedical Engineering, Columbia University, New York, NY, USA
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, USA
| | - Nicholas C Foley
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, USA
| | - Joshua Jacobs
- Department of Biomedical Engineering, Columbia University, New York, NY, USA.
- Department of Neurological Surgery, Columbia University, New York, NY, USA.
| | - Jacqueline P Gottlieb
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, USA.
- Department of Neuroscience, Columbia University, New York, NY, USA.
- Kavli Institute for Brain Science, Columbia University, New York, NY, USA.
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9
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Shi X, Li B, Wang W, Qin Y, Wang H, Wang X. Classification Algorithm for Electroencephalogram-based Motor Imagery Using Hybrid Neural Network with Spatio-temporal Convolution and Multi-head Attention Mechanism. Neuroscience 2023; 527:64-73. [PMID: 37517788 DOI: 10.1016/j.neuroscience.2023.07.020] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Revised: 07/11/2023] [Accepted: 07/16/2023] [Indexed: 08/01/2023]
Abstract
Motor imagery (MI) is a brain-computer interface (BCI) technique in which specific brain regions are activated when people imagine their limbs (or muscles) moving, even without actual movement. The technology converts electroencephalogram (EEG) signals generated by the brain into computer-readable commands by measuring neural activity. Classification of motor imagery is one of the tasks in BCI. Researchers have done a lot of work on motor imagery classification, and the existing literature has relatively mature decoding methods for two-class motor tasks. However, as the categories of EEG-based motor imagery tasks increase, further exploration is needed for decoding research on four-class motor imagery tasks. In this study, we designed a hybrid neural network that combines spatiotemporal convolution and attention mechanisms. Specifically, the data is first processed by spatiotemporal convolution to extract features and then processed by a Multi-branch Convolution block. Finally, the processed data is input into the encoder layer of the Transformer for a self-attention calculation to obtain the classification results. Our approach was tested on the well-known MI datasets BCI Competition IV 2a and 2b, and the results show that the 2a dataset has a global average classification accuracy of 83.3% and a kappa value of 0.78. Experimental results show that the proposed method outperforms most of the existing methods.
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Affiliation(s)
- Xingbin Shi
- The School of Electrical Engineering, Shanghai DianJi University, Shanghai, China; Intelligent Decision and Control Technology Institute, Shanghai Dianji University, Shanghai, China
| | - Baojiang Li
- The School of Electrical Engineering, Shanghai DianJi University, Shanghai, China; Intelligent Decision and Control Technology Institute, Shanghai Dianji University, Shanghai, China.
| | - Wenlong Wang
- The School of Electrical Engineering, Shanghai DianJi University, Shanghai, China; Intelligent Decision and Control Technology Institute, Shanghai Dianji University, Shanghai, China
| | - Yuxin Qin
- The School of Electrical Engineering, Shanghai DianJi University, Shanghai, China; Intelligent Decision and Control Technology Institute, Shanghai Dianji University, Shanghai, China
| | - Haiyan Wang
- The School of Electrical Engineering, Shanghai DianJi University, Shanghai, China; Intelligent Decision and Control Technology Institute, Shanghai Dianji University, Shanghai, China
| | - Xichao Wang
- The School of Electrical Engineering, Shanghai DianJi University, Shanghai, China; Intelligent Decision and Control Technology Institute, Shanghai Dianji University, Shanghai, China
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10
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Seifpour S, Šatka A. Tensor Decomposition Analysis of Longitudinal EEG Signals Reveals Differential Oscillatory Dynamics in Eyes-Closed and Eyes-Open Motor Imagery BCI: A Case Report. Brain Sci 2023; 13:1013. [PMID: 37508946 PMCID: PMC10377314 DOI: 10.3390/brainsci13071013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2023] [Revised: 06/15/2023] [Accepted: 06/26/2023] [Indexed: 07/30/2023] Open
Abstract
Functional dissociation of brain neural activity induced by opening or closing the eyes has been well established. However, how the temporal dynamics of the underlying neuronal modulations differ between these eye conditions during movement-related behaviours is less known. Using a robotic-assisted motor imagery brain-computer interface (MI BCI), we measured neural activity over the motor regions with electroencephalography (EEG) in a stroke survivor during his longitudinal rehabilitation training. We investigated lateralized oscillatory sensorimotor rhythm modulations while the patient imagined moving his hemiplegic hand with closed and open eyes to control an external robotic splint. In order to precisely identify the main profiles of neural activation affected by MI with eyes-open (MIEO) and eyes-closed (MIEC), a data-driven approach based on parallel factor analysis (PARAFAC) tensor decomposition was employed. Using the proposed framework, a set of narrow-band, subject-specific sensorimotor rhythms was identified; each of them had its own spatial and time signature. When MIEC trials were compared with MIEO trials, three key narrow-band rhythms whose peak frequencies centred at ∼8.0 Hz, ∼11.5 Hz, and ∼15.5 Hz, were identified with differently modulated oscillatory dynamics during movement preparation, initiation, and completion time frames. Furthermore, we observed that lower and higher sensorimotor oscillations represent different functional mechanisms within the MI paradigm, reinforcing the hypothesis that rhythmic activity in the human sensorimotor system is dissociated. Leveraging PARAFAC, this study achieves remarkable precision in estimating latent sensorimotor neural substrates, aiding the investigation of the specific functional mechanisms involved in the MI process.
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Affiliation(s)
- Saman Seifpour
- RIKEN Center for Brain Science, Wako, Saitama 351-0198, Japan
- Institute of Measurement Science, Slovak Academy of Sciences, Dubravska cesta 9, 84104 Bratislava, Slovakia
| | - Alexander Šatka
- Institute of Measurement Science, Slovak Academy of Sciences, Dubravska cesta 9, 84104 Bratislava, Slovakia
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Kang K, Stenum J, Roemmich RT, Heller NH, Jouny C, Pantelyat A. Neurologic music therapy combined with EEG-tDCS for upper motor extremity performance in patients with corticobasal syndrome: Study protocol for a novel approach. Contemp Clin Trials 2023; 125:107058. [PMID: 36549380 DOI: 10.1016/j.cct.2022.107058] [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: 09/16/2022] [Revised: 12/15/2022] [Accepted: 12/16/2022] [Indexed: 12/23/2022]
Abstract
BACKGROUND Corticobasal syndrome (CBS) is an atypical parkinsonian disorder that involves degeneration of brain regions associated with motor coordination and sensory processing. Combining transcranial direct current stimulation (tDCS) with rehabilitation training has been shown to improve upper-limb performance in other disease models. Here, we describe the protocol investigating whether tDCS with neurologic music therapy (NMT) (patterned sensory enhancement and therapeutic instrumental music performance) enhances functional arm/hand performance in individuals with CBS. METHODS Study participants are randomly assigned to six 30-min sessions (twice per week for 3 weeks) of NMT + either sham tDCS or active tDCS. We aim to stimulate the frontoparietal cortex, which is associated with movement execution/coordination and sensory processing. The hemisphere contralateral to the more affected arm is stimulated (total stimulation current of 2 mA from 5 dime-sized electrodes). Individualized NMT sessions designed to exercise the upper limb are provided. Participants undergo gross/fine motor, cognitive and emotional assessments at baseline and follow-up (one month after the final session). To investigate the immediate effects of tDCS and NMT training, gross /fine motor, affective level, and kinematic parameter measurements using motion sensors are collected before and after each session. Electroencephalography is used to collect electrical neurophysiological responses before, during, and after tDCS+NMT sessions. The study participants, neurologic music therapist and outcome assessor are blinded to whether participants are in the sham or active tDCS group. CONCLUSION This noninvasive and patient-centered clinical trial for CBS may provide insight into rehabilitation options that are sorely lacking in this population.
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Affiliation(s)
- Kyurim Kang
- School of Medicine, Department of Neurology, Johns Hopkins University, Baltimore, MD, United States of America; Center for Music and Medicine, Department of Neurology, Johns Hopkins University, Baltimore, MD, United States of America
| | - Jan Stenum
- Center for Movement Studies, Kennedy Krieger Institute, Baltimore, MD, United States of America; Department of Physical Medicine and Rehabilitation, Johns Hopkins University School of Medicine, Baltimore, MD, United States of America
| | - Ryan T Roemmich
- Center for Movement Studies, Kennedy Krieger Institute, Baltimore, MD, United States of America; Department of Physical Medicine and Rehabilitation, Johns Hopkins University School of Medicine, Baltimore, MD, United States of America
| | - Nathan H Heller
- Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH, United States of America
| | - Christophe Jouny
- School of Medicine, Department of Neurology, Johns Hopkins University, Baltimore, MD, United States of America
| | - Alexander Pantelyat
- School of Medicine, Department of Neurology, Johns Hopkins University, Baltimore, MD, United States of America; Center for Music and Medicine, Department of Neurology, Johns Hopkins University, Baltimore, MD, United States of America.
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12
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Pomper U, Ansorge U. Motor-induced oscillations in choice response performance. Psychophysiology 2023; 60:e14172. [PMID: 36040756 PMCID: PMC10078311 DOI: 10.1111/psyp.14172] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2021] [Revised: 08/02/2022] [Accepted: 08/03/2022] [Indexed: 01/04/2023]
Abstract
Recently, numerous studies have revealed 4-12 Hz fluctuations of behavioral performance in a multitude of tasks. The majority has utilized stimuli near detection threshold and observed related fluctuations in hit-rates, attributing these to perceptual or attentional processes. As neural oscillations in the 8-20 Hz range also feature prominently in cortical motor areas, they might cause fluctuations in the ability to induce responses, independent of attentional capabilities. Additionally, different effectors (e.g., the left versus right hand) might be cyclically prioritized in an alternating fashion, similar to the attentional sampling of distinct locations, objects, or memory templates. Here, we investigated these questions via a behavioral dense-sampling approach. Twenty-six participants performed a simple visual discrimination task using highly salient stimuli. We varied the interval between each motor response and the subsequent target from 330 to 1040 ms, and analyzed performance as a function of this interval. Our data show significant fluctuations of both RTs and sensitivity between 12.5 and 25 Hz, but no evidence for an alternating prioritization of left- versus right-hand responses. While our results suggest an impact of motor-related signals on performance oscillations, they might additionally be influenced by perceptual processes earlier in the processing hierarchy. In summary, we demonstrate that behavioral oscillations generalize to situations involving highly salient stimuli, closer to everyday life. Moreover, our work adds to the literature by showing fluctuations at a high speed, which might be a consequence of both low task difficulty and the involvement of sensorimotor rhythms.
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Affiliation(s)
- Ulrich Pomper
- Department of Cognition, Emotion, and Methods in Psychology, Faculty of Psychology, University of Vienna, Vienna, Austria
| | - Ulrich Ansorge
- Department of Cognition, Emotion, and Methods in Psychology, Faculty of Psychology, University of Vienna, Vienna, Austria.,Cognitive Science Research Hub, University of Vienna, Vienna, Austria.,Research Platform Mediatised Lifeworlds, University of Vienna, Vienna, Austria
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13
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Ghilardi T, Meyer M, Hunnius S. Predictive motor activation: Modulated by expectancy or predictability? Cognition 2023; 231:105324. [PMID: 36402084 DOI: 10.1016/j.cognition.2022.105324] [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: 02/01/2022] [Revised: 09/26/2022] [Accepted: 11/07/2022] [Indexed: 11/18/2022]
Abstract
Predicting actions is a fundamental ability that helps us to comprehend what is happening in our environment and to interact with others. The motor system was previously identified as source of action predictions. Yet, which aspect of the statistical likelihood of upcoming actions the motor system is sensitive to remains an open question. This EEG study investigated how regularities in observed actions are reflected in the motor system and utilized to predict upcoming actions. Prior to measuring EEG, participants watched videos of action sequences with different transitional probabilities. After training, participants' brain activity over motor areas was measured using EEG while watching videos of action sequences with the same statistical structure. Focusing on the mu and beta frequency bands we tested whether activity of the motor system reflects the statistical likelihood of upcoming actions. We also explored two distinct aspects of the statistical structure that capture different prediction processes, expectancy and predictability. Expectancy describes participants' expectation of the most likely action, whereas predictability represents all possible actions and their relative probabilities. Results revealed that mu and beta oscillations play different roles during action prediction. While the mu rhythm reflected anticipatory activity without any link to the statistical structure, the beta rhythm was related to the expectancy of an action. Our findings support theories proposing that the motor system underlies action prediction, and they extend such theories by showing that multiple forms of statistical information are extracted when observing action sequences. This information is integrated in the prediction generated by the neural motor system of which action is going to happen next.
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Affiliation(s)
- Tommaso Ghilardi
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Thomas van Aquinostraat 4, 6525GD Nijmegen, the Netherlands.
| | - Marlene Meyer
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Thomas van Aquinostraat 4, 6525GD Nijmegen, the Netherlands
| | - Sabine Hunnius
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Thomas van Aquinostraat 4, 6525GD Nijmegen, the Netherlands
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14
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Rockhill AP, Mantovani A, Stedelin B, Nerison CS, Raslan AM, Swann NC. Stereo-EEG recordings extend known distributions of canonical movement-related oscillations. J Neural Eng 2023; 20:10.1088/1741-2552/acae0a. [PMID: 36548996 PMCID: PMC9976588 DOI: 10.1088/1741-2552/acae0a] [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: 06/21/2022] [Accepted: 12/22/2022] [Indexed: 12/24/2022]
Abstract
Objective.Previous electrophysiological research has characterized canonical oscillatory patterns associated with movement mostly from recordings of primary sensorimotor cortex. Less work has attempted to decode movement based on electrophysiological recordings from a broader array of brain areas such as those sampled by stereoelectroencephalography (sEEG), especially in humans. We aimed to identify and characterize different movement-related oscillations across a relatively broad sampling of brain areas in humans and if they extended beyond brain areas previously associated with movement.Approach.We used a linear support vector machine to decode time-frequency spectrograms time-locked to movement, and we validated our results with cluster permutation testing and common spatial pattern decoding.Main results.We were able to accurately classify sEEG spectrograms during a keypress movement task versus the inter-trial interval. Specifically, we found these previously-described patterns: beta (13-30 Hz) desynchronization, beta synchronization (rebound), pre-movement alpha (8-15 Hz) modulation, a post-movement broadband gamma (60-90 Hz) increase and an event-related potential. These oscillatory patterns were newly observed in a wide range of brain areas accessible with sEEG that are not accessible with other electrophysiology recording methods. For example, the presence of beta desynchronization in the frontal lobe was more widespread than previously described, extending outside primary and secondary motor cortices.Significance.Our classification revealed prominent time-frequency patterns which were also observed in previous studies that used non-invasive electroencephalography and electrocorticography, but here we identified these patterns in brain regions that had not yet been associated with movement. This provides new evidence for the anatomical extent of the system of putative motor networks that exhibit each of these oscillatory patterns.
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Affiliation(s)
| | - Alessandra Mantovani
- Oregon Health & Science University, Department of Neurosurgery, Portland, OR, USA 97239
| | - Brittany Stedelin
- Oregon Health & Science University, Department of Neurosurgery, Portland, OR, USA 97239
| | - Caleb S. Nerison
- Oregon Health & Science University, Department of Neurosurgery, Portland, OR, USA 97239
| | - Ahmed M. Raslan
- Oregon Health & Science University, Department of Neurosurgery, Portland, OR, USA 97239
| | - Nicole C. Swann
- University of Oregon, Department of Human Physiology, Eugene, OR, USA 97403,University of Oregon, Institute of Neuroscience, Eugene, OR, USA 97403
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15
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Beta rhythmicity in human motor cortex reflects neural population coupling that modulates subsequent finger coordination stability. Commun Biol 2022; 5:1375. [PMID: 36522455 PMCID: PMC9755311 DOI: 10.1038/s42003-022-04326-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2022] [Accepted: 11/30/2022] [Indexed: 12/23/2022] Open
Abstract
Human behavior is not performed completely as desired, but is influenced by the inherent rhythmicity of the brain. Here we show that anti-phase bimanual coordination stability is regulated by the dynamics of pre-movement neural oscillations in bi-hemispheric primary motor cortices (M1) and supplementary motor area (SMA). In experiment 1, pre-movement bi-hemispheric M1 phase synchrony in beta-band (M1-M1 phase synchrony) was online estimated from 129-channel scalp electroencephalograms. Anti-phase bimanual tapping preceded by lower M1-M1 phase synchrony exhibited significantly longer duration than tapping preceded by higher M1-M1 phase synchrony. Further, the inter-individual variability of duration was explained by the interaction of pre-movement activities within the motor network; lower M1-M1 phase synchrony and spectral power at SMA were associated with longer duration. The necessity of cortical interaction for anti-phase maintenance was revealed by sham-controlled repetitive transcranial magnetic stimulation over SMA in another experiment. Our results demonstrate that pre-movement cortical oscillatory coupling within the motor network unknowingly influences bimanual coordination performance in humans after consolidation, suggesting the feasibility of augmenting human motor ability by covertly monitoring preparatory neural dynamics.
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16
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Llinás RR, Rykunov S, Walton KD, Boyko A, Ustinin M. Splitting of the magnetic encephalogram into «brain» and «non-brain» physiological signals based on the joint analysis of frequency-pattern functional tomograms and magnetic resonance images. Front Neural Circuits 2022; 16:834434. [PMID: 36092277 PMCID: PMC9458866 DOI: 10.3389/fncir.2022.834434] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2021] [Accepted: 08/09/2022] [Indexed: 11/13/2022] Open
Abstract
The article considers the problem of dividing the encephalography data into two time series, that generated by the brain and that generated by other electrical sources located in the human head. The magnetic encephalograms and magnetic resonance images of the head were recorded in the Center for Neuromagnetism at NYU Grossman School of Medicine. Data obtained at McGill University and Montreal University were also used. Recordings were made in a magnetically shielded room and the gradiometers were designed to suppress external noise, making it possible to eliminate them from the data analysis. Magnetic encephalograms were analyzed by the method of functional tomography, based on the Fourier transform and on the solution of inverse problem for all frequencies. In this method, one spatial position is assigned to each frequency component. Magnetic resonance images of the head were evaluated to annotate the space to be included in the analysis. The included space was divided into two parts: «brain» and «non-brain». The frequency components were classified by the feature of their inclusion in one or the other part. The set of frequencies, designated as «brain», represented the partial spectrum of the brain signal, while the set of frequencies designated as «non-brain», represented the partial spectrum of the physiological noise produced by the head. Both partial spectra shared the same frequency band. From the partial spectra, a time series of the «brain» area signal and «non-brain» area head noise were reconstructed. Summary spectral power of the signal was found to be ten times greater than the noise. The proposed method makes it possible to analyze in detail both the signal and the noise components of the encephalogram and to filter the magnetic encephalogram.
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Affiliation(s)
- Rodolfo R. Llinás
- Department of Neuroscience, Center for Neuromagnetism, New York University Grossman School of Medicine, New York, NY, United States
| | - Stanislav Rykunov
- Keldysh Institute of Applied Mathematics, Russian Academy of Sciences, Moscow, Russia
- *Correspondence: Stanislav Rykunov,
| | - Kerry D. Walton
- Department of Neuroscience, Center for Neuromagnetism, New York University Grossman School of Medicine, New York, NY, United States
| | - Anna Boyko
- Keldysh Institute of Applied Mathematics, Russian Academy of Sciences, Moscow, Russia
| | - Mikhail Ustinin
- Keldysh Institute of Applied Mathematics, Russian Academy of Sciences, Moscow, Russia
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17
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Mustile M, Kourtis D, Edwards MG, Donaldson DI, Ietswaart M. The neural response is heightened when watching a person approaching compared to walking away: Evidence for dynamic social neuroscience. Neuropsychologia 2022; 175:108352. [PMID: 36007672 DOI: 10.1016/j.neuropsychologia.2022.108352] [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: 12/06/2021] [Revised: 07/30/2022] [Accepted: 08/15/2022] [Indexed: 11/24/2022]
Abstract
The action observation network has been proposed to play a key role in predicting the action intentions (or goals) of others, thereby facilitating social interaction. Key information when interacting with others is whether someone (an agent) is moving towards or away from us, indicating whether we are likely to interact with the person. In addition, to determine the nature of a social interaction, we also need to take into consideration the distance of the agent relative to us as the observer. How this kind of information is processed within the brain is unknown, at least in part because prior studies have not involved live whole-body motion. Consequently, here we recorded mobile EEG in 18 healthy participants, assessing the neural response to the modulation of direction (walking towards or away) and distance (near vs. far distance) during the observation of an agent walking. We evaluated whether cortical alpha and beta oscillations were modulated differently by direction and distance during action observation. We found that alpha was only modulated by distance, with a stronger decrease of power when the agent was further away from the observer, regardless of direction. Critically, by contrast, beta was found to be modulated by both distance and direction, with a stronger decrease of power when the agent was near and facing the participant (walking towards) compared to when they were near but viewed from the back (walking away). Analysis revealed differences in both the timing and distribution of alpha and beta oscillations. We argue that these data suggest a full understanding of action observation requires a new dynamic neuroscience, investigating actual interactions between real people, in real world environments.
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Affiliation(s)
- Magda Mustile
- Psychology, Faculty of Natural Sciences, University of Stirling, Stirling, UK.
| | - Dimitrios Kourtis
- Psychology, Faculty of Natural Sciences, University of Stirling, Stirling, UK
| | - Martin G Edwards
- Institute of Research in the Psychological Sciences, Université Catholique de Louvain, Louvain- la- Neuve, Belgium
| | - David I Donaldson
- School of Psychology and Neuroscience, University of St Andrews, St. Andrews, UK
| | - Magdalena Ietswaart
- Psychology, Faculty of Natural Sciences, University of Stirling, Stirling, UK
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18
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Hussain SJ, Vollmer MK, Iturrate I, Quentin R. Voluntary Motor Command Release Coincides with Restricted Sensorimotor Beta Rhythm Phases. J Neurosci 2022; 42:5771-5781. [PMID: 35701160 PMCID: PMC9302459 DOI: 10.1523/jneurosci.1495-21.2022] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2021] [Revised: 05/09/2022] [Accepted: 05/11/2022] [Indexed: 01/22/2023] Open
Abstract
Sensory perception and memory are enhanced during restricted phases of ongoing brain rhythms, but whether voluntary movement is constrained by brain rhythm phase is not known. Voluntary movement requires motor commands to be released from motor cortex (M1) and transmitted to spinal motoneurons and effector muscles. Here, we tested the hypothesis that motor commands are preferentially released from M1 during circumscribed phases of ongoing sensorimotor rhythms. Healthy humans of both sexes performed a self-paced finger movement task during electroencephalography (EEG) and electromyography (EMG) recordings. We first estimated the time of motor command release preceding each finger movement by subtracting individually measured corticomuscular transmission latencies from EMG-determined movement onset times. Then, we determined the phase of ipsilateral and contralateral sensorimotor mu (8-12 Hz) and beta (13-35 Hz) rhythms during release of each motor command. We report that motor commands were most often released between 120 and 140° along the contralateral beta cycle but were released uniformly along the contralateral mu cycle. Motor commands were also released uniformly along ipsilateral mu and beta cycles. Results demonstrate that motor command release coincides with restricted phases of the contralateral sensorimotor beta rhythm, suggesting that sensorimotor beta rhythm phase may sculpt the timing of voluntary human movement.SIGNIFICANCE STATEMENT Perceptual and cognitive function is optimal during specific brain rhythm phases. Although brain rhythm phase influences motor cortical neuronal activity and communication between the motor cortex and spinal cord, its role in voluntary movement is poorly understood. Here, we show that the motor commands needed to produce voluntary movements are preferentially released from the motor cortex during contralateral sensorimotor beta rhythm phases. Our findings are consistent with the notion that sensorimotor rhythm phase influences the timing of voluntary human movement.
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Affiliation(s)
- Sara J Hussain
- Movement and Cognitive Rehabilitation Science Program, Department of Kinesiology and Health Education, University of Texas at Austin, Austin, Texas 78712
- Human Cortical Physiology and Neurorehabilitation Section, National Institute of Neurological Disorders and Stroke, Bethesda, Maryland 20892
| | - Mary K Vollmer
- Human Cortical Physiology and Neurorehabilitation Section, National Institute of Neurological Disorders and Stroke, Bethesda, Maryland 20892
| | - Iñaki Iturrate
- Human Cortical Physiology and Neurorehabilitation Section, National Institute of Neurological Disorders and Stroke, Bethesda, Maryland 20892
- Amazon EU, Spain
| | - Romain Quentin
- Human Cortical Physiology and Neurorehabilitation Section, National Institute of Neurological Disorders and Stroke, Bethesda, Maryland 20892
- MEL Group, EDUWELL Team, Lyon Neuroscience Research Center, Institut National de la Santé et de la Recherche Médicale U1028, Centre National de la Recherche Scientifique UMR5292, Université Claude Bernard Lyon 1, 69500 Bron, France
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19
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Zrenner C, Belardinelli P, Ermolova M, Gordon PC, Stenroos M, Zrenner B, Ziemann U. µ-rhythm phase from somatosensory but not motor cortex correlates with corticospinal excitability in EEG-triggered TMS. J Neurosci Methods 2022; 379:109662. [PMID: 35803405 DOI: 10.1016/j.jneumeth.2022.109662] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Revised: 05/18/2022] [Accepted: 07/04/2022] [Indexed: 10/17/2022]
Abstract
BACKGROUND Sensorimotor µ-rhythm phase is correlated with corticospinal excitability. Transcranial magnetic stimulation (TMS) of motor cortex results in larger motor evoked potentials (MEPs) during the negative peak of the EEG oscillation as extracted with a surface Laplacian. However, the anatomical source of the relevant oscillation is not clear and demonstration of the relationship is sensitive to the choice of EEG montage. OBJECTIVE/HYPOTHESIS Here, we compared two EEG montages preferentially sensitive to oscillations originating from the crown of precentral gyrus (dorsal premotor cortex) vs. postcentral gyrus (secondary somatosensory cortex). We hypothesized that the EEG signal from precentral gyrus would correlate more strongly with MEP amplitude, given that the corticospinal neurons are located in the anterior wall of the sulcus and the corticospinal tract has input from premotor cortex. NEW METHOD Real-time EEG-triggered TMS of motor cortex was applied in 6 different conditions in randomly interleaved order, 3 phase conditions (positive peak, negative peak, random phase of the ongoing µ-oscillation), and each phase condition for 2 different EEG montages corresponding to oscillations preferentially originating in precentral gyrus (premotor cortex) vs. postcentral gyrus (somatosensory cortex), extracted using FCC3h vs. C3 centered EEG montages. RESULTS The negative vs. positive peak of sensorimotor µ-rhythm as extracted from the C3 montage (postcentral gyrus, somatosensory cortex) correlated with states of high vs. low corticospinal excitability (p < 0.001), replicating previous findings. However, no significant correlation was found for sensorimotor µ-rhythm as extracted from the neighboring FCC3 montage (precentral gyrus, premotor cortex). This implies that EEG-signals from the somatosensory cortex are better predictors of corticospinal excitability than EEG-signals from the motor areas. CONCLUSIONS The extraction of a brain oscillation whose phase corresponds to corticospinal excitability is highly sensitive to the selected EEG montage and the location of the EEG sensors on the scalp. Here, the cortical source of EEG oscillations predicting response amplitude does not correspond to the cortical target of the stimulation, indicating that even in this simple case, a specific neuronal pathway from somatosensory cortex to primary motor cortex is involved.
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Affiliation(s)
- Christoph Zrenner
- Department of Neurology & Stroke, University of Tübingen, Germany; Hertie Institute for Clinical Brain Research, University of Tübingen, Germany; Department of Psychiatry, University of Toronto, Toronto, Canada; Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, Canada; Institute for Biomedical Engineering, University of Toronto, Toronto, Canada
| | - Paolo Belardinelli
- Department of Neurology & Stroke, University of Tübingen, Germany; Hertie Institute for Clinical Brain Research, University of Tübingen, Germany; Center for Mind/Brain Sciences - CIMeC, University of Trento, Rovereto, Italy
| | - Maria Ermolova
- Department of Neurology & Stroke, University of Tübingen, Germany; Hertie Institute for Clinical Brain Research, University of Tübingen, Germany
| | - Pedro Caldana Gordon
- Department of Neurology & Stroke, University of Tübingen, Germany; Hertie Institute for Clinical Brain Research, University of Tübingen, Germany
| | - Matti Stenroos
- Department of Neuroscience and Biomedical Engineering, Aalto University, Finland
| | - Brigitte Zrenner
- Department of Neurology & Stroke, University of Tübingen, Germany; Hertie Institute for Clinical Brain Research, University of Tübingen, Germany; Department of Psychiatry, University of Toronto, Toronto, Canada; Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, Canada
| | - Ulf Ziemann
- Department of Neurology & Stroke, University of Tübingen, Germany; Hertie Institute for Clinical Brain Research, University of Tübingen, Germany.
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20
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Nugent AC, Benitez Andonegui A, Holroyd T, Robinson SE. On-scalp magnetocorticography with optically pumped magnetometers: Simulated performance in resolving simultaneous sources. NEUROIMAGE. REPORTS 2022; 2:100093. [PMID: 35692456 PMCID: PMC9186482 DOI: 10.1016/j.ynirp.2022.100093] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Currently, the gold standard for high-resolution mapping of cortical electrophysiological activity is invasive electrocorticography (ECoG), a procedure that carries with it the risk of serious morbidity and mortality. Due to these risks, the use of ECoG is largely limited to pre-surgical mapping in intractable epilepsy. Nevertheless, many seminal studies in neuroscience have utilized ECoG to explore domains such as visual perception, attention, auditory processing, and sensorimotor behavior. Studies such as these, occurring in patients with epilepsy rather than healthy controls, may lack generalizability, and are limited by the placement of the electrode arrays over the presumed seizure focus. This manuscript explores the use of optically pumped magnetometers (OPMs) to create a non-invasive alternative to ECoG, which we refer to as magnetocorticography. Because prior ECoG studies reveal that most cognitive processes are driven by multiple, simultaneous independent neuronal assemblies, we characterize the ability of a theoretical 56-channel dense OPM array to resolve simultaneous independent sources, and compare it to currently available SQUID devices, as well as OPM arrays with inter-sensor spacings more typical of other systems in development. Our evaluation of this theoretical system assesses many potential sources of error, including errors of sensor calibration and position. In addition, we investigate the influence of geometrical and anatomical factors on array performance. Our simulations reveal the potential of high-density, on-scalp OPM MEG devices to localize electrophysiological brain responses at unprecedented resolution for a non-invasive device.
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21
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Das A, Myers J, Mathura R, Shofty B, Metzger BA, Bijanki K, Wu C, Jacobs J, Sheth SA. Spontaneous neuronal oscillations in the human insula are hierarchically organized traveling waves. eLife 2022; 11:76702. [PMID: 35616527 PMCID: PMC9200407 DOI: 10.7554/elife.76702] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2021] [Accepted: 05/25/2022] [Indexed: 11/16/2022] Open
Abstract
The insula plays a fundamental role in a wide range of adaptive human behaviors, but its electrophysiological dynamics are poorly understood. Here, we used human intracranial electroencephalographic recordings to investigate the electrophysiological properties and hierarchical organization of spontaneous neuronal oscillations within the insula. We analyzed the neuronal oscillations of the insula directly and found that rhythms in the theta and beta frequency oscillations are widespread and spontaneously present. These oscillations are largely organized along the anterior–posterior (AP) axis of the insula. Both the left and right insula showed anterior-to-posterior decreasing gradients for the power of oscillations in the beta frequency band. The left insula also showed a posterior-to-anterior decreasing frequency gradient and an anterior-to-posterior decreasing power gradient in the theta frequency band. In addition to measuring the power of these oscillations, we also examined the phase of these signals across simultaneous recording channels and found that the insula oscillations in the theta and beta bands are traveling waves. The strength of the traveling waves in each frequency was positively correlated with the amplitude of each oscillation. However, the theta and beta traveling waves were uncoupled to each other in terms of phase and amplitude, which suggested that insular traveling waves in the theta and beta bands operate independently. Our findings provide new insights into the spatiotemporal dynamics and hierarchical organization of neuronal oscillations within the insula, which, given its rich connectivity with widespread cortical regions, indicates that oscillations and traveling waves have an important role in intrainsular and interinsular communications.
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Affiliation(s)
- Anup Das
- Department of Biomedical Engineering, Columbia University, New York, United States
| | - John Myers
- Department of Neurosurgery, Baylor College of Medicine, Houston, United States
| | - Raissa Mathura
- Department of Neurosurgery, Baylor College of Medicine, Houston, United States
| | - Ben Shofty
- Department of Neurosurgery, Baylor College of Medicine, Houston, United States
| | - Brian A Metzger
- Department of Neurosurgery, Baylor College of Medicine, Houston, United States
| | - Kelly Bijanki
- Department of Neurosurgery, Baylor College of Medicine, Houston, United States
| | - Chengyuan Wu
- Department of Neurosurgery, Thomas Jefferson University, Philadelphia, United States
| | - Joshua Jacobs
- Department of Biomedical Engineering, Columbia University, New York, United States
| | - Sameer A Sheth
- Department of Neurosurgery, Baylor College of Medicine, Houston, United States
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22
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Kostyalik D, Kelemen K, Lendvai B, Hernádi I, Román V, Lévay G. Response-related sensorimotor rhythms under scopolamine and MK-801 exposures in the touchscreen visual discrimination test in rats. Sci Rep 2022; 12:8168. [PMID: 35581280 PMCID: PMC9114334 DOI: 10.1038/s41598-022-12146-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2021] [Accepted: 04/21/2022] [Indexed: 11/10/2022] Open
Abstract
The human mu rhythm has been suggested to represent an important function in information processing. Rodent homologue rhythms have been assumed though no study has investigated them from the cognitive aspect yet. As voluntary goal-directed movements induce the desynchronization of mu rhythm, we aimed at exploring whether the response-related brain activity during the touchscreen visual discrimination (VD) task is suitable to detect sensorimotor rhythms and their change under cognitive impairment. Different doses of scopolamine or MK-801 were injected subcutaneously to rats, and epidural electroencephalogram (EEG) was recorded during task performance. Arciform ~ 10 Hz oscillations appeared during visual processing, then two characteristic alpha/beta desynchronization-resynchronization patterns emerged mainly above the sensorimotor areas, serving presumably different motor functions. Beyond causing cognitive impairment, both drugs supressed the touch-related upper alpha (10–15 Hz) reactivity for desynchronization. Reaction time predominantly correlated positively with movement-related alpha and beta power both in normal and impaired conditions. These results support the existence of a mu homologue rodent rhythm whose upper alpha component appeared to be modulated by cholinergic and glutamatergic mechanisms and its power change might indicate a potential EEG correlate of processing speed. The VD task can be utilized for the investigation of sensorimotor rhythms in rats.
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Affiliation(s)
- Diána Kostyalik
- Cognitive Pharmacology Laboratory, Department of Pharmacology and Drug Safety, Gedeon Richter Plc., Gyömrői út 19-21, Budapest, 1103, Hungary
| | - Kristóf Kelemen
- Cognitive Pharmacology Laboratory, Department of Pharmacology and Drug Safety, Gedeon Richter Plc., Gyömrői út 19-21, Budapest, 1103, Hungary
| | - Balázs Lendvai
- Department of Pharmacology and Drug Safety, Gedeon Richter Plc., Budapest, 1103, Hungary
| | - István Hernádi
- Department of Pharmacology and Drug Safety, Gedeon Richter Plc., Budapest, 1103, Hungary.,Department of Experimental Zoology and Neurobiology, Faculty of Sciences, University of Pécs, Pécs, 7622, Hungary.,Institute of Physiology, Medical School, University of Pécs, Pécs, 7622, Hungary.,Grastyán Translational Research Center, University of Pécs, Pécs, 7622, Hungary.,Szentágothai Research Center, University of Pécs, Pécs, 7622, Hungary
| | - Viktor Román
- Department of Pharmacology and Drug Safety, Gedeon Richter Plc., Budapest, 1103, Hungary
| | - György Lévay
- Cognitive Pharmacology Laboratory, Department of Pharmacology and Drug Safety, Gedeon Richter Plc., Gyömrői út 19-21, Budapest, 1103, Hungary. .,Department of Morphology and Physiology, Faculty of Health Sciences, Semmelweis University, Budapest, 1085, Hungary.
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23
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Zhao M, Bonassi G, Samogin J, Taberna GA, Pelosin E, Nieuwboer A, Avanzino L, Mantini D. Frequency-dependent modulation of neural oscillations across the gait cycle. Hum Brain Mapp 2022; 43:3404-3415. [PMID: 35384123 PMCID: PMC9248303 DOI: 10.1002/hbm.25856] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Revised: 03/08/2022] [Accepted: 03/22/2022] [Indexed: 12/14/2022] Open
Abstract
Balance and walking are fundamental to support common daily activities. Relatively accurate characterizations of normal and impaired gait features were attained at the kinematic and muscular levels. Conversely, the neural processes underlying gait dynamics still need to be elucidated. To shed light on gait‐related modulations of neural activity, we collected high‐density electroencephalography (hdEEG) signals and ankle acceleration data in young healthy participants during treadmill walking. We used the ankle acceleration data to segment each gait cycle in four phases: initial double support, right leg swing, final double support, left leg swing. Then, we processed hdEEG signals to extract neural oscillations in alpha, beta, and gamma bands, and examined event‐related desynchronization/synchronization (ERD/ERS) across gait phases. Our results showed that ERD/ERS modulations for alpha, beta, and gamma bands were strongest in the primary sensorimotor cortex (M1), but were also found in premotor cortex, thalamus and cerebellum. We observed a modulation of neural oscillations across gait phases in M1 and cerebellum, and an interaction between frequency band and gait phase in premotor cortex and thalamus. Furthermore, an ERD/ERS lateralization effect was present in M1 for the alpha and beta bands, and in the cerebellum for the beta and gamma bands. Overall, our findings demonstrate that an electrophysiological source imaging approach based on hdEEG can be used to investigate dynamic neural processes of gait control. Future work on the development of mobile hdEEG‐based brain–body imaging platforms may enable overground walking investigations, with potential applications in the study of gait disorders.
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Affiliation(s)
- Mingqi Zhao
- Movement Control and Neuroplasticity Research Group, KU Leuven, Leuven, Belgium
| | - Gaia Bonassi
- S.C. Medicina Fisica e Riabilitazione Ospedaliera, Chiavari, Italy
| | - Jessica Samogin
- Movement Control and Neuroplasticity Research Group, KU Leuven, Leuven, Belgium
| | | | - Elisa Pelosin
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics and Maternal Child Health, University of Genova, Genova, Italy.,IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | - Alice Nieuwboer
- Department of Rehabilitation Sciences, KU Leuven, Leuven, Belgium
| | - Laura Avanzino
- IRCCS Ospedale Policlinico San Martino, Genoa, Italy.,Department of Experimental Medicine, Section of Human Physiology, University of Genoa, Genoa, Italy
| | - Dante Mantini
- Movement Control and Neuroplasticity Research Group, KU Leuven, Leuven, Belgium
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24
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Tabarelli D, Brancaccio A, Zrenner C, Belardinelli P. Functional Connectivity States of Alpha Rhythm Sources in the Human Cortex at Rest: Implications for Real-Time Brain State Dependent EEG-TMS. Brain Sci 2022; 12:348. [PMID: 35326304 PMCID: PMC8946162 DOI: 10.3390/brainsci12030348] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2022] [Revised: 02/13/2022] [Accepted: 02/24/2022] [Indexed: 02/04/2023] Open
Abstract
Alpha is the predominant rhythm of the human electroencephalogram, but its function, multiple generators and functional coupling patterns are still relatively unknown. In this regard, alpha connectivity patterns can change between different cortical generators depending on the status of the brain. Therefore, in the light of the communication through coherence framework, an alpha functional network depends on the functional coupling patterns in a determined state. This notion has a relevance for brain-state dependent EEG-TMS because, beyond the local state, a network connectivity overview at rest could provide further and more comprehensive information for the definition of 'instantaneous state' at the stimulation moment, rather than just the local state around the stimulation site. For this reason, we studied functional coupling at rest in 203 healthy subjects with MEG data. Sensor signals were source localized and connectivity was studied at the Individual Alpha Frequency (IAF) between three different cortical areas (occipital, parietal and prefrontal). Two different and complementary phase-coherence metrices were used. Our results show a consistent connectivity between parietal and prefrontal regions whereas occipito-prefrontal connectivity is less marked and occipito-parietal connectivity is extremely low, despite physical closeness. We consider our results a relevant add-on for informed, individualized real-time brain state dependent stimulation, with possible contributions to novel, personalized non-invasive therapeutic approaches.
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Affiliation(s)
- Davide Tabarelli
- Center for Mind/Brain Sciences—CIMeC, University of Trento, I-38123 Trento, Italy; (D.T.); (A.B.)
| | - Arianna Brancaccio
- Center for Mind/Brain Sciences—CIMeC, University of Trento, I-38123 Trento, Italy; (D.T.); (A.B.)
| | - Christoph Zrenner
- Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Department of Psychiatry, University of Toronto, Toronto, ON M6J 1H4, Canada;
| | - Paolo Belardinelli
- Center for Mind/Brain Sciences—CIMeC, University of Trento, I-38123 Trento, Italy; (D.T.); (A.B.)
- Department of Neurology & Stroke, University of Tübingen, D-72070 Tübingen, Germany
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25
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Johnson EL, Yin Q, O'Hara NB, Tang L, Jeong JW, Asano E, Ofen N. Dissociable oscillatory theta signatures of memory formation in the developing brain. Curr Biol 2022; 32:1457-1469.e4. [PMID: 35172128 PMCID: PMC9007830 DOI: 10.1016/j.cub.2022.01.053] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2021] [Revised: 12/15/2021] [Accepted: 01/19/2022] [Indexed: 11/16/2022]
Abstract
Understanding complex human brain functions is critically informed by studying such functions during development. Here, we addressed a major gap in models of human memory by leveraging rare direct electrophysiological recordings from children and adolescents. Specifically, memory relies on interactions between the medial temporal lobe (MTL) and prefrontal cortex (PFC), and the maturation of these interactions is posited to play a key role in supporting memory development. To understand the nature of MTL-PFC interactions, we examined subdural recordings from MTL and PFC in 21 neurosurgical patients aged 5.9-20.5 years as they performed an established scene memory task. We determined signatures of memory formation by comparing the study of subsequently recognized to forgotten scenes in single trials. Results establish that MTL and PFC interact via two distinct theta mechanisms, an ∼3-Hz oscillation that supports amplitude coupling and slows down with age and an ∼7-Hz oscillation that supports phase coupling and speeds up with age. Slow and fast theta interactions immediately preceding scene onset further explained age-related differences in recognition performance. Last, with additional diffusion imaging data, we linked both functional mechanisms to the structural maturation of the cingulum tract. Our findings establish system-level dynamics of memory formation and suggest that MTL and PFC interact via increasingly dissociable mechanisms as memory improves across development.
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Affiliation(s)
- Elizabeth L Johnson
- Life-Span Cognitive Neuroscience Program, Institute of Gerontology and Merrill Palmer Skillman Institute, Wayne State University, Detroit, MI 48202, USA; Departments of Medical Social Sciences and Pediatrics, Northwestern University, Chicago, IL 60611, USA; Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA 94720, USA.
| | - Qin Yin
- Life-Span Cognitive Neuroscience Program, Institute of Gerontology and Merrill Palmer Skillman Institute, Wayne State University, Detroit, MI 48202, USA; Department of Psychology, Wayne State University, Detroit, MI 48202, USA
| | - Nolan B O'Hara
- Translational Neuroscience Program, Wayne State University, Detroit, MI 48201, USA
| | - Lingfei Tang
- Life-Span Cognitive Neuroscience Program, Institute of Gerontology and Merrill Palmer Skillman Institute, Wayne State University, Detroit, MI 48202, USA; Department of Psychology, Wayne State University, Detroit, MI 48202, USA
| | - Jeong-Won Jeong
- Translational Neuroscience Program, Wayne State University, Detroit, MI 48201, USA; Departments of Pediatrics and Neurology, Children's Hospital of Michigan, Wayne State University, Detroit, MI 48201, USA
| | - Eishi Asano
- Translational Neuroscience Program, Wayne State University, Detroit, MI 48201, USA; Departments of Pediatrics and Neurology, Children's Hospital of Michigan, Wayne State University, Detroit, MI 48201, USA
| | - Noa Ofen
- Life-Span Cognitive Neuroscience Program, Institute of Gerontology and Merrill Palmer Skillman Institute, Wayne State University, Detroit, MI 48202, USA; Department of Psychology, Wayne State University, Detroit, MI 48202, USA; Translational Neuroscience Program, Wayne State University, Detroit, MI 48201, USA.
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26
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Tensor Decomposition of Human Narrowband Oscillatory Brain Activity in Frequency, Space and Time. Biol Psychol 2022; 169:108287. [PMID: 35143920 DOI: 10.1016/j.biopsycho.2022.108287] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2021] [Revised: 12/16/2021] [Accepted: 02/04/2022] [Indexed: 12/14/2022]
Abstract
Many brain processes in health and disease are associated with modulation of narrowband brain oscillations (NBOs) in the scalp-recorded EEG, which exhibit specific frequency spectra and scalp topography. Isolating and tracking NBOs over time using algorithms is useful in domains such as brain-computer interfaces or when measuring the EEG effects of experimental manipulations. Previously, we successfully applied modified tensor methods for identifying and tracking NBO activity over time or conditions. We introduced frequency and spatial constraints that greatly improved their physiological plausibility. In this paper we rigorously demonstrate the power and precision of tensor methods to separate, isolate and track NBOs using sources simulated with forward models. This allows us to control the attributes of NBOs and validate tensor solutions. We find that tensor methods can accurately identify, separate and track NBOs over time, using realistic sources either alone or in combination, and compare favorably to well-known spatio-spectral decomposition method for NBO estimation.
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27
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Yu H, Ba S, Guo Y, Guo L, Xu G. Effects of Motor Imagery Tasks on Brain Functional Networks Based on EEG Mu/Beta Rhythm. Brain Sci 2022; 12:brainsci12020194. [PMID: 35203957 PMCID: PMC8870302 DOI: 10.3390/brainsci12020194] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Revised: 01/27/2022] [Accepted: 01/28/2022] [Indexed: 02/01/2023] Open
Abstract
Motor imagery (MI) refers to the mental rehearsal of movement in the absence of overt motor action, which can activate or inhibit cortical excitability. EEG mu/beta oscillations recorded over the human motor cortex have been shown to be consistently suppressed during both the imagination and performance of movements, although the specific effect on brain function remains to be confirmed. In this study, Granger causality (GC) was used to construct the brain functional network of subjects during motor imagery and resting state based on EEG in order to explore the effects of motor imagery on brain function. Parameters of the brain functional network were compared and analyzed, including degree, clustering coefficient, characteristic path length and global efficiency of EEG mu/beta rhythm in different states. The results showed that the clustering coefficient and efficiency of EEG mu/beta rhythm decreased significantly during motor imagery (p < 0.05), while degree distribution and characteristic path length increased significantly (p < 0.05), mainly concentrated in the frontal lobe and sensorimotor area. For the resting state after motor imagery, the changes of brain functional characteristics were roughly similar to those of the task state. Therefore, it is concluded that motor imagery plays an important role in activation of cortical excitability.
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Affiliation(s)
- Hongli Yu
- State Key Laboratory of Reliability and Intelligence of Electrical Equipment, Hebei University of Technology, Tianjin 300130, China; (L.G.); (G.X.)
- Tianjin Key Laboratory of Bioelectromagnetic Technology and Intelligent Health, Hebei University of Technology, Tianjin 300130, China; (S.B.); (Y.G.)
- Correspondence: ; Tel.: +86-137-5249-0401
| | - Sidi Ba
- Tianjin Key Laboratory of Bioelectromagnetic Technology and Intelligent Health, Hebei University of Technology, Tianjin 300130, China; (S.B.); (Y.G.)
| | - Yuxue Guo
- Tianjin Key Laboratory of Bioelectromagnetic Technology and Intelligent Health, Hebei University of Technology, Tianjin 300130, China; (S.B.); (Y.G.)
| | - Lei Guo
- State Key Laboratory of Reliability and Intelligence of Electrical Equipment, Hebei University of Technology, Tianjin 300130, China; (L.G.); (G.X.)
- Tianjin Key Laboratory of Bioelectromagnetic Technology and Intelligent Health, Hebei University of Technology, Tianjin 300130, China; (S.B.); (Y.G.)
| | - Guizhi Xu
- State Key Laboratory of Reliability and Intelligence of Electrical Equipment, Hebei University of Technology, Tianjin 300130, China; (L.G.); (G.X.)
- Tianjin Key Laboratory of Bioelectromagnetic Technology and Intelligent Health, Hebei University of Technology, Tianjin 300130, China; (S.B.); (Y.G.)
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28
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Cao Y, Oostenveld R, Alday PM, Piai V. Are alpha and beta oscillations spatially dissociated over the cortex in context-driven spoken-word production? Psychophysiology 2022; 59:e13999. [PMID: 35066874 PMCID: PMC9285923 DOI: 10.1111/psyp.13999] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2021] [Revised: 10/19/2021] [Accepted: 12/06/2021] [Indexed: 11/28/2022]
Abstract
Decreases in oscillatory alpha‐ and beta‐band power have been consistently found in spoken‐word production. These have been linked to both motor preparation and conceptual‐lexical retrieval processes. However, the observed power decreases have a broad frequency range that spans two “classic” (sensorimotor) bands: alpha and beta. It remains unclear whether alpha‐ and beta‐band power decreases contribute independently when a spoken word is planned. Using a re‐analysis of existing magnetoencephalography data, we probed whether the effects in alpha and beta bands are spatially distinct. Participants read a sentence that was either constraining or non‐constraining toward the final word, which was presented as a picture. In separate blocks participants had to name the picture or score its predictability via button press. Irregular‐resampling auto‐spectral analysis (IRASA) was used to isolate the oscillatory activity in the alpha and beta bands from the background 1‐over‐f spectrum. The sources of alpha‐ and beta‐band oscillations were localized based on the participants’ individualized peak frequencies. For both tasks, alpha‐ and beta‐power decreases overlapped in left posterior temporal and inferior parietal cortex, regions that have previously been associated with conceptual and lexical processes. The spatial distributions of the alpha and beta power effects were spatially similar in these regions to the extent we could assess it. By contrast, for left frontal regions, the spatial distributions differed between alpha and beta effects. Our results suggest that for conceptual‐lexical retrieval, alpha and beta oscillations do not dissociate spatially and, thus, are distinct from the classical sensorimotor alpha and beta oscillations. It remains unclear whether the consistently found alpha‐ and beta‐band power decreases in spoken‐word production support a single operation or contribute independently. Using novel methodology, we probed whether the alpha and beta bands are distinct from an anatomical perspective. We found anatomical overlap in the left posterior temporal and inferior parietal cortex, whereas for the left frontal region, the spatial overlap was limited. Our results suggest that for conceptual‐lexical retrieval, alpha and beta oscillations do not dissociate and, thus, are distinct from the classical sensorimotor alpha and beta.
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Affiliation(s)
- Yang Cao
- Donders Centre for Cognition, Radboud University, Nijmegen, The Netherlands
| | - Robert Oostenveld
- Donders Centre for Cognitive Neuroimaging, Radboud University, Nijmegen, The Netherlands.,NatMEG, Karolinska Institutet, Stockholm, Sweden
| | - Phillip M Alday
- Max-Planck-Institute for Psycholinguistics, Nijmegen, The Netherlands
| | - Vitória Piai
- Donders Centre for Cognition, Radboud University, Nijmegen, The Netherlands.,Donders Centre for Medical Neuroscience, Department of Medical Psychology, Radboud University Medical Center, Nijmegen, The Netherlands
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29
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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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30
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Li D, Vlisides PE, Mashour GA. Dynamic reconfiguration of frequency-specific cortical coactivation patterns during psychedelic and anesthetized states induced by ketamine. Neuroimage 2022; 249:118891. [PMID: 35007718 PMCID: PMC8903080 DOI: 10.1016/j.neuroimage.2022.118891] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2021] [Revised: 12/16/2021] [Accepted: 01/06/2022] [Indexed: 01/08/2023] Open
Abstract
Recent neuroimaging studies have demonstrated that spontaneous brain activity exhibits rich spatiotemporal structure that can be characterized as the exploration of a repertoire of spatially distributed patterns that recur over time. The repertoire of brain states may reflect the capacity for consciousness, since general anesthetics suppress and psychedelic drugs enhance such dynamics. However, the modulation of brain activity repertoire across varying states of consciousness has not yet been studied in a systematic and unified framework. As a unique drug that has both psychedelic and anesthetic properties depending on the dose, ketamine offers an opportunity to examine brain reconfiguration dynamics along a continuum of consciousness. Here we investigated the dynamic organization of cortical activity during wakefulness and during altered states of consciousness induced by different doses of ketamine. Through k-means clustering analysis of the envelope data of source-localized electroencephalographic (EEG) signals, we identified a set of recurring states that represent frequency-specific spatial coactivation patterns. We quantified the effect of ketamine on individual brain states in terms of fractional occupancy and transition probabilities and found that ketamine anesthesia tends to shift the configuration toward brain states with low spatial variability. Furthermore, by assessing the temporal dynamics of the occurrence and transitions of brain states, we showed that subanesthetic ketamine is associated with a richer repertoire, while anesthetic ketamine induces dynamic changes in brain state organization, with the repertoire richness evolving from a reduced level to one comparable to that of normal wakefulness before recovery of consciousness. These results provide a novel description of ketamine's modulation of the dynamic configuration of cortical activity and advance understanding of the neurophysiological mechanism of ketamine in terms of the spatial, temporal, and spectral structures of underlying whole-brain dynamics.
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Affiliation(s)
- Duan Li
- Center for Consciousness Science; Department of Anesthesiology.
| | | | - George A Mashour
- Center for Consciousness Science; Department of Anesthesiology; Neuroscience Graduate Program; Department of Pharmacology, University of Michigan Medical School, Ann Arbor, United States
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31
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Separating Neural Oscillations from Aperiodic 1/f Activity: Challenges and Recommendations. Neuroinformatics 2022; 20:991-1012. [PMID: 35389160 PMCID: PMC9588478 DOI: 10.1007/s12021-022-09581-8] [Citation(s) in RCA: 50] [Impact Index Per Article: 25.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/25/2022] [Indexed: 12/31/2022]
Abstract
Electrophysiological power spectra typically consist of two components: An aperiodic part usually following an 1/f power law [Formula: see text] and periodic components appearing as spectral peaks. While the investigation of the periodic parts, commonly referred to as neural oscillations, has received considerable attention, the study of the aperiodic part has only recently gained more interest. The periodic part is usually quantified by center frequencies, powers, and bandwidths, while the aperiodic part is parameterized by the y-intercept and the 1/f exponent [Formula: see text]. For investigation of either part, however, it is essential to separate the two components. In this article, we scrutinize two frequently used methods, FOOOF (Fitting Oscillations & One-Over-F) and IRASA (Irregular Resampling Auto-Spectral Analysis), that are commonly used to separate the periodic from the aperiodic component. We evaluate these methods using diverse spectra obtained with electroencephalography (EEG), magnetoencephalography (MEG), and local field potential (LFP) recordings relating to three independent research datasets. Each method and each dataset poses distinct challenges for the extraction of both spectral parts. The specific spectral features hindering the periodic and aperiodic separation are highlighted by simulations of power spectra emphasizing these features. Through comparison with the simulation parameters defined a priori, the parameterization error of each method is quantified. Based on the real and simulated power spectra, we evaluate the advantages of both methods, discuss common challenges, note which spectral features impede the separation, assess the computational costs, and propose recommendations on how to use them.
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32
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Vatinno AA, Schranz C, Simpson A, Ramakrishnan V, Bonilha L, Seo NJ. Predicting upper extremity motor improvement following therapy using EEG-based connectivity in chronic stroke. NeuroRehabilitation 2022; 50:105-113. [PMID: 34776421 PMCID: PMC8821328 DOI: 10.3233/nre-210171] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
BACKGROUND Uncertain prognosis presents a challenge for therapists in determining the most efficient course of rehabilitation treatment for individual patients. Cortical Sensorimotor network connectivity may have prognostic utility for upper extremity motor improvement because the integrity of the communication within the sensorimotor network forms the basis for neuroplasticity and recovery. OBJECTIVE To investigate if pre-intervention sensorimotor connectivity predicts post-stroke upper extremity motor improvement following therapy. METHODS Secondary analysis of a pilot triple-blind randomized controlled trial. Twelve chronic stroke survivors underwent 2-week task-practice therapy, while receiving vibratory stimulation for the treatment group and no stimulation for the control group. EEG connectivity was obtained pre-intervention. Motor improvement was quantified as change in the Box and Block Test from pre to post-therapy. The association between ipsilesional sensorimotor connectivity and motor improvement was examined using regression, controlling for group. For negative control, contralesional/interhemispheric connectivity and conventional predictors (initial clinical motor score, age, time post-stroke, lesion volume) were examined. RESULTS Greater ipsilesional sensorimotor alpha connectivity was associated with greater upper extremity motor improvement following therapy for both groups (p < 0.05). Other factors were not significant. CONCLUSION EEG connectivity may have a prognostic utility for individual patients' upper extremity motor improvement following therapy in chronic stroke.
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Affiliation(s)
- Amanda A Vatinno
- Department of Health Sciences and Research, College of Health Professions, Medical University of South Carolina (MUSC), Charleston, SC
| | - Christian Schranz
- Department of Health Sciences and Research, College of Health Professions, MUSC
| | - Annie Simpson
- Department of Healthcare Leadership and Management, Department of Health Sciences and Research, College of Health Professions, MUSC
| | | | | | - Na Jin Seo
- Division of Occupational Therapy, Department of Rehabilitation Sciences, Department of Health Sciences and Research, MUSC, Ralph H. Johnson VA Medical Center
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33
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Sugino H, Ushiyama J. Gymnasts' Ability to Modulate Sensorimotor Rhythms During Kinesthetic Motor Imagery of Sports Non-specific Movements Superior to Non-gymnasts. Front Sports Act Living 2021; 3:757308. [PMID: 34805979 PMCID: PMC8600039 DOI: 10.3389/fspor.2021.757308] [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: 08/12/2021] [Accepted: 09/30/2021] [Indexed: 11/30/2022] Open
Abstract
Previous psychological studies using questionnaires have consistently reported that athletes have superior motor imagery ability, both for sports-specific and for sports-non-specific movements. However, regarding motor imagery of sports-non-specific movements, no physiological studies have demonstrated differences in neural activity between athletes and non-athletes. The purpose of this study was to examine the differences in sensorimotor rhythms during kinesthetic motor imagery (KMI) of sports-non-specific movements between gymnasts and non-gymnasts. We selected gymnasts as an example population because they are likely to have particularly superior motor imagery ability due to frequent usage of motor imagery, including KMI as part of daily practice. Healthy young participants (16 gymnasts and 16 non-gymnasts) performed repeated motor execution and KMI of sports-non-specific movements (wrist dorsiflexion and shoulder abduction of the dominant hand). Scalp electroencephalogram (EEG) was recorded over the contralateral sensorimotor cortex. During motor execution and KMI, sensorimotor EEG power is known to decrease in the α- (8–15 Hz) and β-bands (16–35 Hz), referred to as event-related desynchronization (ERD). We calculated the maximal peak of ERD both in the α- (αERDmax) and β-bands (βERDmax) as a measure of changes in corticospinal excitability. αERDmax was significantly greater in gymnasts, who subjectively evaluated their KMI as being more vivid in the psychological questionnaire. On the other hand, βERDmax was greater in gymnasts only for shoulder abduction KMI. These findings suggest gymnasts' signature of flexibly modulating sensorimotor rhythms with no movements, which may be the basis of their superior ability of KMI for sports-non-specific movements.
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Affiliation(s)
- Hirotaka Sugino
- Graduate School of Media and Governance, Keio University, Fujisawa, Japan
| | - Junichi Ushiyama
- Faculty of Environment and Information Studies, Keio University, Fujisawa, Japan.,Department of Rehabilitation Medicine, Keio University School of Medicine, Tokyo, Japan
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Herrero JL, Smith A, Mishra A, Markowitz N, Mehta AD, Bickel S. Inducing neuroplasticity through intracranial θ-burst stimulation in the human sensorimotor cortex. J Neurophysiol 2021; 126:1723-1739. [PMID: 34644179 PMCID: PMC8782667 DOI: 10.1152/jn.00320.2021] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2021] [Revised: 09/20/2021] [Accepted: 10/08/2021] [Indexed: 01/04/2023] Open
Abstract
The progress of therapeutic neuromodulation greatly depends on improving stimulation parameters to most efficiently induce neuroplasticity effects. Intermittent θ-burst stimulation (iTBS), a form of electrical stimulation that mimics natural brain activity patterns, has proved to efficiently induce such effects in animal studies and rhythmic transcranial magnetic stimulation studies in humans. However, little is known about the potential neuroplasticity effects of iTBS applied through intracranial electrodes in humans. This study characterizes the physiological effects of intracranial iTBS in humans and compare them with α-frequency stimulation, another frequently used neuromodulatory pattern. We applied these two stimulation patterns to well-defined regions in the sensorimotor cortex, which elicited contralateral hand muscle contractions during clinical mapping, in patients with epilepsy implanted with intracranial electrodes. Treatment effects were evaluated using oscillatory coherence across areas connected to the treatment site, as defined with corticocortical-evoked potentials. Our results show that iTBS increases coherence in the β-frequency band within the sensorimotor network indicating a potential neuroplasticity effect. The effect is specific to the sensorimotor system, the β band, and the stimulation pattern and outlasted the stimulation period by ∼3 min. The effect occurred in four out of seven subjects depending on the buildup of the effect during iTBS treatment and other patterns of oscillatory activity related to ceiling effects within the β band and to preexistent coherence within the α band. By characterizing the neurophysiological effects of iTBS within well-defined cortical networks, we hope to provide an electrophysiological framework that allows clinicians/researchers to optimize brain stimulation protocols which may have translational value.NEW & NOTEWORTHY θ-Burst stimulation (TBS) protocols in transcranial magnetic stimulation studies have shown improved treatment efficacy in a variety of neuropsychiatric disorders. The optimal protocol to induce neuroplasticity in invasive direct electrical stimulation approaches is not known. We report that intracranial TBS applied in human sensorimotor cortex increases local coherence of preexistent β rhythms. The effect is specific to the stimulation frequency and the stimulated network and outlasts the stimulation period by ∼3 min.
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Affiliation(s)
- Jose L Herrero
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, New York
- Department of Neurosurgery, Zucker School of Medicine at Hofstra/Northwell, Manhasset, New York
| | - Alexander Smith
- Department of Neurosurgery, Zucker School of Medicine at Hofstra/Northwell, Manhasset, New York
| | - Akash Mishra
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, New York
- Department of Neurosurgery, Zucker School of Medicine at Hofstra/Northwell, Manhasset, New York
| | - Noah Markowitz
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, New York
- Department of Neurosurgery, Zucker School of Medicine at Hofstra/Northwell, Manhasset, New York
| | - Ashesh D Mehta
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, New York
- Department of Neurosurgery, Zucker School of Medicine at Hofstra/Northwell, Manhasset, New York
| | - Stephan Bickel
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, New York
- Department of Neurosurgery, Zucker School of Medicine at Hofstra/Northwell, Manhasset, New York
- Department of Neurology, Zucker School of Medicine at Hofstra/Northwell, Manhasset, New York
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Schaworonkow N, Voytek B. Enhancing oscillations in intracranial electrophysiological recordings with data-driven spatial filters. PLoS Comput Biol 2021; 17:e1009298. [PMID: 34411096 PMCID: PMC8407590 DOI: 10.1371/journal.pcbi.1009298] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2021] [Revised: 08/31/2021] [Accepted: 07/22/2021] [Indexed: 11/19/2022] Open
Abstract
In invasive electrophysiological recordings, a variety of neural oscillations can be detected across the cortex, with overlap in space and time. This overlap complicates measurement of neural oscillations using standard referencing schemes, like common average or bipolar referencing. Here, we illustrate the effects of spatial mixing on measuring neural oscillations in invasive electrophysiological recordings and demonstrate the benefits of using data-driven referencing schemes in order to improve measurement of neural oscillations. We discuss referencing as the application of a spatial filter. Spatio-spectral decomposition is used to estimate data-driven spatial filters, a computationally fast method which specifically enhances signal-to-noise ratio for oscillations in a frequency band of interest. We show that application of these data-driven spatial filters has benefits for data exploration, investigation of temporal dynamics and assessment of peak frequencies of neural oscillations. We demonstrate multiple use cases, exploring between-participant variability in presence of oscillations, spatial spread and waveform shape of different rhythms as well as narrowband noise removal with the aid of spatial filters. We find high between-participant variability in the presence of neural oscillations, a large variation in spatial spread of individual rhythms and many non-sinusoidal rhythms across the cortex. Improved measurement of cortical rhythms will yield better conditions for establishing links between cortical activity and behavior, as well as bridging scales between the invasive intracranial measurements and noninvasive macroscale scalp measurements.
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Affiliation(s)
- Natalie Schaworonkow
- Department of Cognitive Science, University of California, San Diego, California, United States of America
| | - Bradley Voytek
- Department of Cognitive Science, University of California, San Diego, California, United States of America
- Halıcıoğlu Data Science Institute, University of California, San Diego, California, United States of America
- Neurosciences Graduate Program, University of California, San Diego, California, United States of America
- Kavli Institute for Brain and Mind, University of California, San Diego, California, United States of America
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36
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Shibuya S, Unenaka S, Shimada S, Ohki Y. Distinct modulation of mu and beta rhythm desynchronization during observation of embodied fake hand rotation. Neuropsychologia 2021; 159:107952. [PMID: 34252417 DOI: 10.1016/j.neuropsychologia.2021.107952] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2021] [Revised: 06/16/2021] [Accepted: 07/06/2021] [Indexed: 12/17/2022]
Abstract
The rubber hand illusion (RHI) is a phenomenon whereby participants recognize a fake hand as their own. Studies have examined the effects of observing fake hand movements after the RHI on brain sensorimotor activity, although results remain controversial. To address these discrepancies, we investigated the effects of observation of fake hand rotation after the RHI on sensorimotor mu (μ: 8-13 Hz) and beta (β: 15-25 Hz) rhythm event-related desynchronization (ERD) using electroencephalography (EEG). Questionnaire results and proprioceptive drift revealed that the RHI occurred in participants when their invisible hand and fake visible hand were stroked synchronously but not during asynchronous stroking. Independent component (IC) clustering from EEG data during movement observation identified three IC clusters, including the right sensorimotor, left sensorimotor, and left occipital cluster. In the right sensorimotor cluster, we observed distinct modulation of μ and β ERD during fake hand rotation. Illusory ownership over the fake hand enhanced μ ERD but inversely attenuated β ERD. Further, the extent of μ ERD correlated with proprioceptive drift, but not with questionnaire ratings, whereas the converse results were obtained for β ERD. No ownership-dependent ERD modulation was detected in the left sensorimotor cluster. Alpha (α: 8-13 Hz) rhythm ERD of the left occipital cluster was smaller in the synchronous condition than in the asynchronous condition, but α ERD was not correlated with questionnaire rating or drift. These findings suggest that observing embodied fake hand rotation induces distinct cortical processing in sensorimotor brain areas.
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Affiliation(s)
- Satoshi Shibuya
- Department of Integrative Physiology, Kyorin University School of Medicine, 6-20-2 Shinkawa, Mitaka, Tokyo, Japan.
| | - Satoshi Unenaka
- Department of Sport Education, School of Lifelong Sport, Hokusho University, 23 Bunkyodai, Ebetsu, Hokkaido, Japan
| | - Sotaro Shimada
- Department of Electronics and Bioinformatics, School of Science and Technology, Meiji University, 1-1-1 Higashi-Mita, Tama-ku, Kawasaki, Kanagawa, Japan
| | - Yukari Ohki
- Department of Integrative Physiology, Kyorin University School of Medicine, 6-20-2 Shinkawa, Mitaka, Tokyo, Japan
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Barone J, Rossiter HE. Understanding the Role of Sensorimotor Beta Oscillations. Front Syst Neurosci 2021; 15:655886. [PMID: 34135739 PMCID: PMC8200463 DOI: 10.3389/fnsys.2021.655886] [Citation(s) in RCA: 64] [Impact Index Per Article: 21.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2021] [Accepted: 05/05/2021] [Indexed: 12/15/2022] Open
Abstract
Beta oscillations have been predominantly observed in sensorimotor cortices and basal ganglia structures and they are thought to be involved in somatosensory processing and motor control. Although beta activity is a distinct feature of healthy and pathological sensorimotor processing, the role of this rhythm is still under debate. Here we review recent findings about the role of beta oscillations during experimental manipulations (i.e., drugs and brain stimulation) and their alteration in aging and pathology. We show how beta changes when learning new motor skills and its potential to integrate sensory input with prior contextual knowledge. We conclude by discussing a novel methodological approach analyzing beta oscillations as a series of transient bursting events.
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Affiliation(s)
- Jacopo Barone
- Cardiff University Brain Research Imaging Centre, School of Psychology, Cardiff University, Cardiff, United Kingdom
| | - Holly E Rossiter
- Cardiff University Brain Research Imaging Centre, School of Psychology, Cardiff University, Cardiff, United Kingdom
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Bidirectional propagation of low frequency oscillations over the human hippocampal surface. Nat Commun 2021; 12:2764. [PMID: 33980852 PMCID: PMC8115072 DOI: 10.1038/s41467-021-22850-5] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2020] [Accepted: 04/01/2021] [Indexed: 02/03/2023] Open
Abstract
The hippocampus is diversely interconnected with other brain systems along its axis. Cycles of theta-frequency activity are believed to propagate from the septal to temporal pole, yet it is unclear how this one-way route supports the flexible cognitive capacities of this structure. We leveraged novel thin-film microgrid arrays conformed to the human hippocampal surface to track neural activity two-dimensionally in vivo. All oscillation frequencies identified between 1-15 Hz propagated across the tissue. Moreover, they dynamically shifted between two roughly opposite directions oblique to the long axis. This predominant propagation axis was mirrored across participants, hemispheres, and consciousness states. Directionality was modulated in a participant who performed a behavioral task, and it could be predicted by wave amplitude topography over the hippocampal surface. Our results show that propagation directions may thus represent distinct meso-scale network computations, operating along versatile spatiotemporal processing routes across the hippocampal body.
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Cross KA, Malekmohammadi M, Woo Choi J, Pouratian N. Movement-related changes in pallidocortical synchrony differentiate action execution and observation in humans. Clin Neurophysiol 2021; 132:1990-2001. [PMID: 33980469 DOI: 10.1016/j.clinph.2021.03.037] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2020] [Revised: 02/02/2021] [Accepted: 03/15/2021] [Indexed: 01/21/2023]
Abstract
OBJECTIVE Suppression of local and network alpha and beta oscillations in the human basal ganglia-thalamocortical (BGTC) circuit is a prominent feature of movement, including suppression of local alpha/beta power, cross-region beta phase coupling, and cortical and subcortical phase-amplitude coupling (PAC). We hypothesized that network-level coupling is more directly related to movement execution than local power changes, given the role of pathological network hypersynchrony in movement disorders such as Parkinson disease (PD). Understanding the specificity of these movement-related signals is important for designing novel therapeutics. METHODS We recorded globus pallidus internus (GPi) and motor cortical local field potentials during movement execution, passive movement observation and rest in 12 patients with PD undergoing deep brain stimulator implantation. RESULTS Local alpha/beta power is suppressed in the globus pallidus and motor cortex during both action execution and action observation, although less so during action observation. In contrast, pallidocortical phase synchrony and GPi and motor cortical alpha/beta-gamma PAC are suppressed only during action execution. CONCLUSIONS The functional dissociation across tasks in pallidocortical network activity suggests a particularly important role of network coupling in motor execution. SIGNIFICANCE Network level recordings provide important specificity in differentiating motor behavior and may provide significant value for future closed loop therapies.
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Affiliation(s)
- Katy A Cross
- Department of Neurology, University of California, Los Angeles, USA.
| | | | - Jeong Woo Choi
- Department of Neurosurgery, University of California, Los Angeles, USA
| | - Nader Pouratian
- Department of Neurosurgery, University of California, Los Angeles, USA
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40
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Shih PC, Steele CJ, Nikulin VV, Gundlach C, Kruse J, Villringer A, Sehm B. Alpha and beta neural oscillations differentially reflect age-related differences in bilateral coordination. Neurobiol Aging 2021; 104:82-91. [PMID: 33979705 DOI: 10.1016/j.neurobiolaging.2021.03.016] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2020] [Revised: 03/27/2021] [Accepted: 03/28/2021] [Indexed: 10/21/2022]
Abstract
Bilateral in-phase (IP) and anti-phase (AP) movements represent two fundamental modes of bilateral coordination that are essential for daily living. Although previous studies have shown that aging is behaviorally associated with decline in bilateral coordination, especially in AP movements, the underlying neural mechanisms remain unclear. Here, we use kinematic measurements and electroencephalography to compare motor performance of young and older adults executing bilateral IP and AP hand movements. On the behavioral level, inter-limb synchronization was reduced during AP movements compared to IP and this reduction was stronger in the older adults. On the neural level, we found interactions between group and condition for task-related power change in different frequency bands. The interaction was driven by smaller alpha power decreases over the non-dominant cortical motor area in young adults during IP movements and larger beta power decreases over the midline region in older adults during AP movements. In addition, the decrease in inter-limb synchronization during AP movements was predicted by stronger directional connectivity in the beta-band: an effect more pronounced in older adults. Our results therefore show that age-related differences in the two bilateral coordination modes are reflected on the neural level by differences in alpha and beta oscillatory power as well as interhemispheric directional connectivity.
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Affiliation(s)
- Pei-Cheng Shih
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Institute of Neuroscience, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Christopher J Steele
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Department of Psychology, Concordia University, Montreal, Quebec, Canada
| | - Vadim V Nikulin
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Centre for Cognition and Decision Making, Institute for Cognitive Neuroscience, National Research University Higher School of Economics, Moscow, Russia; Neurophysics Group, Department of Neurology, Campus Benjamin Franklin, Charité Universitätsmedizin Berlin, Berlin, Germany
| | - Christopher Gundlach
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Institute of Psychology, University of Leipzig, Leipzig, Germany
| | - Johanna Kruse
- Department of General Psychology, Technische Universität Dresden, Dresden, Germany
| | - Arno Villringer
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Department of Cognitive Neurology, University Hospital Leipzig, Leipzig, Germany
| | - Bernhard Sehm
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Department of Cognitive Neurology, University Hospital Leipzig, Leipzig, Germany; Department of Neurology, University Hospital Halle (Saale), Halle, Germany.
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41
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Van der Lubbe RHJ, Sobierajewicz J, Jongsma MLA, Verwey WB, Przekoracka-Krawczyk A. Frontal brain areas are more involved during motor imagery than during motor execution/preparation of a response sequence. Int J Psychophysiol 2021; 164:71-86. [PMID: 33647383 DOI: 10.1016/j.ijpsycho.2021.02.020] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2020] [Revised: 01/23/2021] [Accepted: 02/24/2021] [Indexed: 11/16/2022]
Abstract
Results of several neuroimaging studies support the functional equivalence model, which states that motor imagery (MI) and motor execution (ME) involve the same processes, except for the final execution component. In contrast, the motor-cognitive model implies that MI additionally involves frontal executive control processes. However, according to some authors MI may actually be more comparable to motor preparation (MP). In the current electroencephalographic study, a version of the discrete sequence production paradigm was employed in which human participants initially had to prepare a sequence of five finger movements that subsequently had to be executed, imagined, or withheld. MI, ME, and MP were compared by computing event-related (de)-synchronization in the theta, alpha/mu, and beta bands. Results revealed a major increase in frontal theta power during MI as compared to ME and MP. At the end of the examined intervals, a posterior reduction in alpha power was present during ME and MP, but not during MI. Finally, above sensorimotor areas a decrease in beta power was observed that was most pronounced in the case of ME. The increase of frontal theta activity during MI may reflect increased effort, while the absence of a reduction in posterior alpha power suggests no major involvement of visuospatial attention and/or visual imagery. The present findings favor the motor-cognitive model, as it predicts extra involvement of frontal executive processes during MI.
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Affiliation(s)
- Rob H J Van der Lubbe
- Cognitive Psychology and Ergonomics, Faculty of Behavior, Management, and Social Sciences, University of Twente, the Netherlands; Laboratory of Vision Science and Optometry, Faculty of Physics, Adam Mickiewicz University, Poznań, Poland; Laboratory of Vision and Neuroscience, NanoBiomedical Center, Adam Mickiewicz University, Poznań, Poland.
| | - Jagna Sobierajewicz
- Laboratory of Vision Science and Optometry, Faculty of Physics, Adam Mickiewicz University, Poznań, Poland; Laboratory of Vision and Neuroscience, NanoBiomedical Center, Adam Mickiewicz University, Poznań, Poland
| | - Marijtje L A Jongsma
- Behavioral Science Institute, Radboud University Nijmegen, Nijmegen, the Netherlands
| | - Willem B Verwey
- Cognitive Psychology and Ergonomics, Faculty of Behavior, Management, and Social Sciences, University of Twente, the Netherlands
| | - Anna Przekoracka-Krawczyk
- Laboratory of Vision Science and Optometry, Faculty of Physics, Adam Mickiewicz University, Poznań, Poland; Laboratory of Vision and Neuroscience, NanoBiomedical Center, Adam Mickiewicz University, Poznań, Poland
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42
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He Y, Luell S, Muralikrishnan R, Straube B, Nagels A. Gesture's body orientation modulates the N400 for visual sentences primed by gestures. Hum Brain Mapp 2020; 41:4901-4911. [PMID: 32808721 PMCID: PMC7643362 DOI: 10.1002/hbm.25166] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2020] [Revised: 07/16/2020] [Accepted: 07/23/2020] [Indexed: 01/08/2023] Open
Abstract
Body orientation of gesture entails social-communicative intention, and may thus influence how gestures are perceived and comprehended together with auditory speech during face-to-face communication. To date, despite the emergence of neuroscientific literature on the role of body orientation on hand action perception, limited studies have directly investigated the role of body orientation in the interaction between gesture and language. To address this research question, we carried out an electroencephalography (EEG) experiment presenting to participants (n = 21) videos of frontal and lateral communicative hand gestures of 5 s (e.g., raising a hand), followed by visually presented sentences that are either congruent or incongruent with the gesture (e.g., "the mountain is high/low…"). Participants underwent a semantic probe task, judging whether a target word is related or unrelated to the gesture-sentence event. EEG results suggest that, during the perception phase of handgestures, while both frontal and lateral gestures elicited a power decrease in both the alpha (8-12 Hz) and the beta (16-24 Hz) bands, lateral versus frontal gestures elicited reduced power decrease in the beta band, source-located to the medial prefrontal cortex. For sentence comprehension, at the critical word whose meaning is congruent/incongruent with the gesture prime, frontal gestures elicited an N400 effect for gesture-sentence incongruency. More importantly, this incongruency effect was significantly reduced for lateral gestures. These findings suggest that body orientation plays an important role in gesture perception, and that its inferred social-communicative intention may influence gesture-language interaction at semantic level.
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Affiliation(s)
- Yifei He
- Department of Psychiatry and PsychotherapyPhilipps‐University MarburgMarburgGermany
| | - Svenja Luell
- Department of General LinguisticsJohannes‐Gutenberg University MainzMainzGermany
| | - R. Muralikrishnan
- Department of NeuroscienceMax Planck Institute for Empirical AestheticsFrankfurtGermany
| | - Benjamin Straube
- Department of Psychiatry and PsychotherapyPhilipps‐University MarburgMarburgGermany
| | - Arne Nagels
- Department of General LinguisticsJohannes‐Gutenberg University MainzMainzGermany
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Wang DD, Choi JT. Brain Network Oscillations During Gait in Parkinson's Disease. Front Hum Neurosci 2020; 14:568703. [PMID: 33192399 PMCID: PMC7645204 DOI: 10.3389/fnhum.2020.568703] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2020] [Accepted: 09/29/2020] [Indexed: 11/15/2022] Open
Abstract
Human bipedal walking is a complex motor task that requires supraspinal control for balance and flexible coordination of timing and scaling of many muscles in different environment. Gait impairments are a hallmark of Parkinson’s disease (PD), reflecting dysfunction of cortico-basal ganglia-brainstem circuits. Recent studies using implanted electrodes and surface electroencephalography have demonstrated gait-related brain oscillations in the basal ganglia and cerebral cortex. Here, we review the physiological and pathophysiological roles of (1) basal ganglia oscillations, (2) cortical oscillations, and (3) basal ganglia-cortical interactions during walking. These studies extend a novel framework for movement of disorders where specific patterns of abnormal oscillatory synchronization in the basal ganglia thalamocortical network are associated with specific signs and symptoms. Therefore, we propose that many gait dysfunctions in PD arise from derangements in brain network, and discuss potential therapies aimed at restoring gait impairments through modulation of brain network in PD.
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Affiliation(s)
- Doris D Wang
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, United States
| | - Julia T Choi
- Department of Applied Physiology and Kinesiology, University of Florida, Gainesville, FL, United States
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Shifts in broadband power and alpha peak frequency observed during long-term isolation. Sci Rep 2020; 10:17987. [PMID: 33093553 PMCID: PMC7581825 DOI: 10.1038/s41598-020-75127-0] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2020] [Accepted: 10/12/2020] [Indexed: 12/23/2022] Open
Abstract
Prolonged periods of social isolation and spatial confinement do not only represent an issue that needs to be faced by a few astronauts during space missions, but can affect all of us as recently shown during pandemic situations. The fundamental question, how the brain adapts to periods of sensory deprivation and re-adapts to normality, has only received little attention. Here, we use eyes closed and eyes open resting-state electroencephalographic (EEG) recordings to investigate how neural activity is altered during 120 days of isolation in a spatially confined, space-analogue environment. After disentangling oscillatory patterns from 1/f activity, we show that isolation leads to a reduction in broadband power and a flattening of the 1/f spectral slope. Beyond that, we observed a reduction in alpha peak frequency during isolation, but did not find strong evidence for isolation-induced changes that are of oscillatory nature. Critically, all effects reversed upon release from isolation. These findings suggest that isolation and concomitant sensory deprivation lead to an enhanced cortical deactivation which might be explained by a reduction in the mean neuronal population firing rate.
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45
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Tomassini A, Maris E, Hilt P, Fadiga L, D’Ausilio A. Visual detection is locked to the internal dynamics of cortico-motor control. PLoS Biol 2020; 18:e3000898. [PMID: 33079930 PMCID: PMC7598921 DOI: 10.1371/journal.pbio.3000898] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2020] [Revised: 10/30/2020] [Accepted: 09/14/2020] [Indexed: 12/13/2022] Open
Abstract
Movements overtly sample sensory information, making sensory analysis an active-sensing process. In this study, we show that visual information sampling is not just locked to the (overt) movement dynamics but to the internal (covert) dynamics of cortico-motor control. We asked human participants to perform continuous isometric contraction while detecting unrelated and unpredictable near-threshold visual stimuli. The motor output (force) shows zero-lag coherence with brain activity (recorded via electroencephalography) in the beta-band, as previously reported. In contrast, cortical rhythms in the alpha-band systematically forerun the motor output by 200 milliseconds. Importantly, visual detection is facilitated when cortico-motor alpha (not beta) synchronization is enhanced immediately before stimulus onset, namely, at the optimal phase relationship for sensorimotor communication. These findings demonstrate an ongoing coupling between visual sampling and motor control, suggesting the operation of an internal and alpha-cycling visuomotor loop.
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Affiliation(s)
- Alice Tomassini
- Istituto Italiano di Tecnologia, Center for Translational Neurophysiology of Speech and Communication (CTNSC), Ferrara, Italy
- * E-mail:
| | - Eric Maris
- Radboud University, Donders Institute for Brain, Cognition and Behavior, Centre for Cognition (DCC), Nijmegen, The Netherlands
| | - Pauline Hilt
- Istituto Italiano di Tecnologia, Center for Translational Neurophysiology of Speech and Communication (CTNSC), Ferrara, Italy
| | - Luciano Fadiga
- Istituto Italiano di Tecnologia, Center for Translational Neurophysiology of Speech and Communication (CTNSC), Ferrara, Italy
- Università di Ferrara, Dipartimento di Scienze Biomediche e Chirurgico Specialistiche, Ferrara, Italy
| | - Alessandro D’Ausilio
- Istituto Italiano di Tecnologia, Center for Translational Neurophysiology of Speech and Communication (CTNSC), Ferrara, Italy
- Università di Ferrara, Dipartimento di Scienze Biomediche e Chirurgico Specialistiche, Ferrara, Italy
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Jenson D, Bowers AL, Hudock D, Saltuklaroglu T. The Application of EEG Mu Rhythm Measures to Neurophysiological Research in Stuttering. Front Hum Neurosci 2020; 13:458. [PMID: 31998103 PMCID: PMC6965028 DOI: 10.3389/fnhum.2019.00458] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2019] [Accepted: 12/13/2019] [Indexed: 11/29/2022] Open
Abstract
Deficits in basal ganglia-based inhibitory and timing circuits along with sensorimotor internal modeling mechanisms are thought to underlie stuttering. However, much remains to be learned regarding the precise manner how these deficits contribute to disrupting both speech and cognitive functions in those who stutter. Herein, we examine the suitability of electroencephalographic (EEG) mu rhythms for addressing these deficits. We review some previous findings of mu rhythm activity differentiating stuttering from non-stuttering individuals and present some new preliminary findings capturing stuttering-related deficits in working memory. Mu rhythms are characterized by spectral peaks in alpha (8-13 Hz) and beta (14-25 Hz) frequency bands (mu-alpha and mu-beta). They emanate from premotor/motor regions and are influenced by basal ganglia and sensorimotor function. More specifically, alpha peaks (mu-alpha) are sensitive to basal ganglia-based inhibitory signals and sensory-to-motor feedback. Beta peaks (mu-beta) are sensitive to changes in timing and capture motor-to-sensory (i.e., forward model) projections. Observing simultaneous changes in mu-alpha and mu-beta across the time-course of specific events provides a rich window for observing neurophysiological deficits associated with stuttering in both speech and cognitive tasks and can provide a better understanding of the functional relationship between these stuttering symptoms. We review how independent component analysis (ICA) can extract mu rhythms from raw EEG signals in speech production tasks, such that changes in alpha and beta power are mapped to myogenic activity from articulators. We review findings from speech production and auditory discrimination tasks demonstrating that mu-alpha and mu-beta are highly sensitive to capturing sensorimotor and basal ganglia deficits associated with stuttering with high temporal precision. Novel findings from a non-word repetition (working memory) task are also included. They show reduced mu-alpha suppression in a stuttering group compared to a typically fluent group. Finally, we review current limitations and directions for future research.
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Affiliation(s)
- David Jenson
- Department of Speech and Hearing Sciences, Elson S. Floyd College of Medicine, Washington State University, Spokane, WA, United States
| | - Andrew L. Bowers
- Epley Center for Health Professions, Communication Sciences and Disorders, University of Arkansas, Fayetteville, AR, United States
| | - Daniel Hudock
- Department of Communication Sciences and Disorders, Idaho State University, Pocatello, ID, United States
| | - Tim Saltuklaroglu
- College of Health Professions, Department of Audiology and Speech-Pathology, University of Tennessee Health Science Center, Knoxville, TN, United States
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Pulsed Facilitation of Corticospinal Excitability by the Sensorimotor μ-Alpha Rhythm. J Neurosci 2019; 39:10034-10043. [PMID: 31685655 PMCID: PMC6978939 DOI: 10.1523/jneurosci.1730-19.2019] [Citation(s) in RCA: 53] [Impact Index Per Article: 10.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2019] [Revised: 09/05/2019] [Accepted: 10/17/2019] [Indexed: 11/21/2022] Open
Abstract
Alpha oscillations (8-14 Hz) are assumed to gate information flow in the brain by means of pulsed inhibition; that is, the phasic suppression of cortical excitability and information processing once per alpha cycle, resulting in stronger net suppression for larger alpha amplitudes due to the assumed amplitude asymmetry of the oscillation. While there is evidence for this hypothesis regarding occipital alpha oscillations, it is less clear for the central sensorimotor μ-alpha rhythm. Probing corticospinal excitability via transcranial magnetic stimulation (TMS) of the primary motor cortex and the measurement of motor evoked potentials (MEPs), we have previously demonstrated that corticospinal excitability is modulated by both amplitude and phase of the sensorimotor μ-alpha rhythm. However, the direction of this modulation, its proposed asymmetry, and its underlying mechanisms remained unclear. We therefore used real-time EEG-triggered single- and paired-pulse TMS in healthy humans of both sexes to assess corticospinal excitability and GABA-A-receptor mediated short-latency intracortical inhibition (SICI) at rest during spontaneous high amplitude μ-alpha waves at different phase angles (peaks, troughs, rising and falling flanks) and compared them to periods of low amplitude (desynchronized) μ-alpha. MEP amplitude was facilitated during troughs and rising flanks, but no phasic suppression was observed at any time, nor any modulation of SICI. These results are best compatible with sensorimotor μ-alpha reflecting asymmetric pulsed facilitation but not pulsed inhibition of motor cortical excitability. The asymmetric excitability with respect to rising and falling flanks of the μ-alpha cycle further reveals that voltage differences alone cannot explain the impact of phase.SIGNIFICANCE STATEMENT The pulsed inhibition hypothesis, which assumes that alpha oscillations actively inhibit neuronal processing in a phasic manner, is highly influential and has substantially shaped our understanding of these oscillations. However, some of its basic assumptions, in particular its asymmetry and inhibitory nature, have rarely been tested directly. Here, we explicitly investigated the asymmetry of modulation and its direction for the human sensorimotor μ-alpha rhythm. We found clear evidence of pulsed facilitation, but not inhibition, in the human motor cortex, challenging the generalizability of the pulsed inhibition hypothesis and advising caution when interpreting sensorimotor μ-alpha changes in the sensorimotor system. This study also demonstrates how specific assumptions about the neurophysiological underpinnings of cortical oscillations can be experimentally tested noninvasively in humans.
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