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Lamekina Y, Titone L, Maess B, Meyer L. Speech Prosody Serves Temporal Prediction of Language via Contextual Entrainment. J Neurosci 2024; 44:e1041232024. [PMID: 38839302 PMCID: PMC11236583 DOI: 10.1523/jneurosci.1041-23.2024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Revised: 03/08/2024] [Accepted: 04/08/2024] [Indexed: 06/07/2024] Open
Abstract
Temporal prediction assists language comprehension. In a series of recent behavioral studies, we have shown that listeners specifically employ rhythmic modulations of prosody to estimate the duration of upcoming sentences, thereby speeding up comprehension. In the current human magnetoencephalography (MEG) study on participants of either sex, we show that the human brain achieves this function through a mechanism termed entrainment. Through entrainment, electrophysiological brain activity maintains and continues contextual rhythms beyond their offset. Our experiment combined exposure to repetitive prosodic contours with the subsequent presentation of visual sentences that either matched or mismatched the duration of the preceding contour. During exposure to prosodic contours, we observed MEG coherence with the contours, which was source-localized to right-hemispheric auditory areas. During the processing of the visual targets, activity at the frequency of the preceding contour was still detectable in the MEG; yet sources shifted to the (left) frontal cortex, in line with a functional inheritance of the rhythmic acoustic context for prediction. Strikingly, when the target sentence was shorter than expected from the preceding contour, an omission response appeared in the evoked potential record. We conclude that prosodic entrainment is a functional mechanism of temporal prediction in language comprehension. In general, acoustic rhythms appear to endow language for employing the brain's electrophysiological mechanisms of temporal prediction.
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Affiliation(s)
- Yulia Lamekina
- Research Group Language Cycles, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig 04103, Germany
| | - Lorenzo Titone
- Research Group Language Cycles, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig 04103, Germany
| | - Burkhard Maess
- Methods and Development Group Brain Networks, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig 04103, Germany
| | - Lars Meyer
- Research Group Language Cycles, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig 04103, Germany
- University Clinic Münster, Münster 48149, Germany
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2
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Otstavnov N, Riaz A, Moiseeva V, Fedele T. Temporal and Spatial Information Elicit Different Power and Connectivity Profiles during Working Memory Maintenance. J Cogn Neurosci 2024; 36:290-302. [PMID: 38010298 DOI: 10.1162/jocn_a_02089] [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] [Indexed: 11/29/2023]
Abstract
Working memory (WM) is the cognitive ability to store and manipulate information necessary for ongoing tasks. Although frontoparietal areas are involved in the retention of visually presented information, oscillatory neural activity differs for temporal and spatial WM processing. In this study, we corroborated previous findings describing the modulation of neural oscillations and expanded our investigation to the network organization underlying the cognitive processing of temporal and spatial information. We utilized MEG recordings during a Sternberg visual WM task. The spectral oscillatory activity in the maintenance phase revealed increased frontal theta (4-8 Hz) and parietal beta (13-30 Hz) in the temporal condition. Source level coherence analysis delineated the prominent role of parietal areas in all frequency bands during the maintenance of temporal information, whereas frontal and central areas showed major contributions in theta and beta ranges during the maintenance of spatial information. Our study revealed distinct spectral profiles of neural oscillations for separate cognitive subdomains of WM processing. The delineation of specific functional networks might have important implications for clinical applications, enabling the development of stimulation protocols targeting cognitive disabilities associated with WM impairments.
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Affiliation(s)
| | - Abrar Riaz
- RWTH Aachen University, Germany
- Forschungszentrum Jülich, Germany
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3
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Kumar WS, Ray S. Healthy ageing and cognitive impairment alter EEG functional connectivity in distinct frequency bands. Eur J Neurosci 2023; 58:3432-3449. [PMID: 37559505 DOI: 10.1111/ejn.16114] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2023] [Revised: 07/20/2023] [Accepted: 07/24/2023] [Indexed: 08/11/2023]
Abstract
Functional connectivity (FC) indicates the interdependencies between brain signals recorded from spatially distinct locations in different frequency bands, which is modulated by cognitive tasks and is known to change with ageing and cognitive disorders. Recently, the power of narrow-band gamma oscillations induced by visual gratings have been shown to reduce with both healthy ageing and in subjects with mild cognitive impairment (MCI). However, the impact of ageing/MCI on stimulus-induced gamma FC has not been well studied. We recorded electroencephalogram (EEG) from a large cohort (N = 229) of elderly subjects (>49 years) while they viewed large cartesian gratings to induce gamma oscillations and studied changes in alpha and gamma FC with healthy ageing (N = 218) and MCI (N = 11). Surprisingly, we found distinct differences across age and MCI groups in power and FC. With healthy ageing, alpha power did not change but FC decreased significantly. MCI reduced gamma but not alpha FC significantly compared with age and gender matched controls, even when power was matched between the two groups. Overall, our results suggest distinct effects of ageing and disease on EEG power and FC, suggesting different mechanisms underlying ageing and cognitive disorders.
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Affiliation(s)
| | - Supratim Ray
- Centre for Neuroscience, Indian Institute of Science, Bengaluru, India
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4
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Trigeminal stimulation is required for neural representations of bimodal odor localization: A time-resolved multivariate EEG and fNIRS study. Neuroimage 2023; 269:119903. [PMID: 36708974 DOI: 10.1016/j.neuroimage.2023.119903] [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: 07/04/2022] [Revised: 11/28/2022] [Accepted: 01/24/2023] [Indexed: 01/26/2023] Open
Abstract
Whereas neural representations of spatial information are commonly studied in vision, olfactory stimuli might also be able to create such representations via the trigeminal system. We explored in two independent multi-method electroencephalography-functional near-infrared spectroscopy (EEG+fNIRS) experiments (n1=18, n2=14) if monorhinal odor stimuli can evoke spatial representations in the brain. We tested whether this representation depends on trigeminal properties of the stimulus, and if the retention in short-term memory follows the "sensorimotor recruitment theory", using multivariate representational similarity analysis (RSA). We demonstrate that the delta frequency band up to 5 Hz across the scull entail spatial information of which nostril has been stimulated. Delta frequencies were localized in a network involving primary and secondary olfactory, motor-sensory and occipital regions. RSA on fNIRS data showed that monorhinal stimulations evoke neuronal representations in motor-sensory regions and that this representation is kept stable beyond the time of perception. These effects were no longer valid when the odor stimulus did not sufficiently stimulate the trigeminal nerve as well. Our results are first evidence that the trigeminal system can create spatial representations of bimodal odors in the brain and that these representations follow similar principles as the other sensory systems.
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5
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Niso G, Botvinik-Nezer R, Appelhoff S, De La Vega A, Esteban O, Etzel JA, Finc K, Ganz M, Gau R, Halchenko YO, Herholz P, Karakuzu A, Keator DB, Markiewicz CJ, Maumet C, Pernet CR, Pestilli F, Queder N, Schmitt T, Sójka W, Wagner AS, Whitaker KJ, Rieger JW. Open and reproducible neuroimaging: From study inception to publication. Neuroimage 2022; 263:119623. [PMID: 36100172 PMCID: PMC10008521 DOI: 10.1016/j.neuroimage.2022.119623] [Citation(s) in RCA: 29] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Revised: 08/17/2022] [Accepted: 09/09/2022] [Indexed: 10/31/2022] Open
Abstract
Empirical observations of how labs conduct research indicate that the adoption rate of open practices for transparent, reproducible, and collaborative science remains in its infancy. This is at odds with the overwhelming evidence for the necessity of these practices and their benefits for individual researchers, scientific progress, and society in general. To date, information required for implementing open science practices throughout the different steps of a research project is scattered among many different sources. Even experienced researchers in the topic find it hard to navigate the ecosystem of tools and to make sustainable choices. Here, we provide an integrated overview of community-developed resources that can support collaborative, open, reproducible, replicable, robust and generalizable neuroimaging throughout the entire research cycle from inception to publication and across different neuroimaging modalities. We review tools and practices supporting study inception and planning, data acquisition, research data management, data processing and analysis, and research dissemination. An online version of this resource can be found at https://oreoni.github.io. We believe it will prove helpful for researchers and institutions to make a successful and sustainable move towards open and reproducible science and to eventually take an active role in its future development.
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Affiliation(s)
- Guiomar Niso
- Psychological & Brain Sciences, Indiana University, Bloomington, IN, USA; Universidad Politecnica de Madrid, Madrid and CIBER-BBN, Spain; Instituto Cajal, CSIC, Madrid, Spain.
| | - Rotem Botvinik-Nezer
- Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH, USA.
| | - Stefan Appelhoff
- Center for Adaptive Rationality, Max Planck Institute for Human Development, Berlin, Germany
| | | | - Oscar Esteban
- Dept. of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland; Department of Psychology, Stanford University, Stanford, CA, USA
| | - Joset A Etzel
- Department of Psychological and Brain Sciences, Washington University in St. Louis, St. Louis, MO, USA
| | - Karolina Finc
- Centre for Modern Interdisciplinary Technologies, Nicolaus Copernicus University, Toruń, Poland
| | - Melanie Ganz
- Neurobiology Research Unit, Rigshospitalet, Copenhagen, Denmark; Department of Computer Science, University of Copenhagen, Copenhagen, Denmark
| | - Rémi Gau
- Institute of Psychology, Université catholique de Louvain, Louvain la Neuve, Belgium
| | - Yaroslav O Halchenko
- Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH, USA
| | - Peer Herholz
- Montreal Neurological Institute-Hospital, McGill University, Montréal, Quebec, Canada
| | - Agah Karakuzu
- Biomedical Engineering Institute, Polytechnique Montréal, Montréal, Quebec, Canada; Montréal Heart Institute, Montréal, Quebec, Canada
| | - David B Keator
- Department of Psychiatry and Human Behavior, University of California, Irvine, CA, USA
| | | | - Camille Maumet
- Inria, Univ Rennes, CNRS, Inserm - IRISA UMR 6074, Empenn ERL U 1228, Rennes, France
| | - Cyril R Pernet
- Neurobiology Research Unit, Rigshospitalet, Copenhagen, Denmark
| | - Franco Pestilli
- Psychological & Brain Sciences, Indiana University, Bloomington, IN, USA; Department of Psychology, The University of Texas at Austin, Austin, TX, USA
| | - Nazek Queder
- Montreal Neurological Institute-Hospital, McGill University, Montréal, Quebec, Canada; Department of Neurobiology and Behavior, University of California, Irvine, CA, USA
| | - Tina Schmitt
- Neuroimaging Unit, Carl-von-Ossietzky Universität, Oldenburg, Germany
| | - Weronika Sójka
- Faculty of Philosophy and Social Sciences, Nicolaus Copernicus University, Toruń, Poland
| | - Adina S Wagner
- Institute for Neuroscience and Medicine, Research Centre Juelich, Germany
| | | | - Jochem W Rieger
- Neuroimaging Unit, Carl-von-Ossietzky Universität, Oldenburg, Germany; Department of Psychology, Carl-von-Ossietzky Universität, Oldenburg, Germany.
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6
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Niso G, Krol LR, Combrisson E, Dubarry AS, Elliott MA, François C, Héjja-Brichard Y, Herbst SK, Jerbi K, Kovic V, Lehongre K, Luck SJ, Mercier M, Mosher JC, Pavlov YG, Puce A, Schettino A, Schön D, Sinnott-Armstrong W, Somon B, Šoškić A, Styles SJ, Tibon R, Vilas MG, van Vliet M, Chaumon M. Good scientific practice in EEG and MEG research: Progress and perspectives. Neuroimage 2022; 257:119056. [PMID: 35283287 PMCID: PMC11236277 DOI: 10.1016/j.neuroimage.2022.119056] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Revised: 02/25/2022] [Accepted: 03/01/2022] [Indexed: 11/22/2022] Open
Abstract
Good scientific practice (GSP) refers to both explicit and implicit rules, recommendations, and guidelines that help scientists to produce work that is of the highest quality at any given time, and to efficiently share that work with the community for further scrutiny or utilization. For experimental research using magneto- and electroencephalography (MEEG), GSP includes specific standards and guidelines for technical competence, which are periodically updated and adapted to new findings. However, GSP also needs to be regularly revisited in a broader light. At the LiveMEEG 2020 conference, a reflection on GSP was fostered that included explicitly documented guidelines and technical advances, but also emphasized intangible GSP: a general awareness of personal, organizational, and societal realities and how they can influence MEEG research. This article provides an extensive report on most of the LiveMEEG contributions and new literature, with the additional aim to synthesize ongoing cultural changes in GSP. It first covers GSP with respect to cognitive biases and logical fallacies, pre-registration as a tool to avoid those and other early pitfalls, and a number of resources to enable collaborative and reproducible research as a general approach to minimize misconceptions. Second, it covers GSP with respect to data acquisition, analysis, reporting, and sharing, including new tools and frameworks to support collaborative work. Finally, GSP is considered in light of ethical implications of MEEG research and the resulting responsibility that scientists have to engage with societal challenges. Considering among other things the benefits of peer review and open access at all stages, the need to coordinate larger international projects, the complexity of MEEG subject matter, and today's prioritization of fairness, privacy, and the environment, we find that current GSP tends to favor collective and cooperative work, for both scientific and for societal reasons.
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Affiliation(s)
- Guiomar Niso
- Psychological & Brain Sciences, Indiana University, Bloomington, IN, USA; Universidad Politecnica de Madrid and CIBER-BBN, Madrid, Spain
| | - Laurens R Krol
- Neuroadaptive Human-Computer Interaction, Brandenburg University of Technology Cottbus-Senftenberg, Germany
| | - Etienne Combrisson
- Aix-Marseille University, Institut de Neurosciences de la Timone, France
| | | | | | | | - Yseult Héjja-Brichard
- Centre d'Ecologie Fonctionnelle et Evolutive, CNRS, EPHE, IRD, Université Montpellier, Montpellier, France
| | - Sophie K Herbst
- Cognitive Neuroimaging Unit, INSERM, CEA, CNRS, NeuroSpin center, Université Paris-Saclay, Gif/Yvette, France
| | - Karim Jerbi
- Cognitive and Computational Neuroscience Laboratory, Department of Psychology, University of Montreal, Montreal, QC, Canada; Mila - Quebec Artificial Intelligence Institute, Canada
| | - Vanja Kovic
- Faculty of Philosophy, Laboratory for neurocognition and applied cognition, University of Belgrade, Serbia
| | - Katia Lehongre
- Institut du Cerveau - Paris Brain Institute - ICM, Inserm U 1127, CNRS UMR 7225, APHP, Hôpital de la Pitié Salpêtrière, Sorbonne Université, Centre MEG-EEG, Centre de NeuroImagerie Recherche (CENIR), Paris, France
| | - Steven J Luck
- Center for Mind & Brain, University of California, Davis, CA, USA
| | - Manuel Mercier
- Aix Marseille Univ, Inserm, INS, Inst Neurosci Syst, Marseille, France
| | - John C Mosher
- McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Yuri G Pavlov
- University of Tuebingen, Germany; Ural Federal University, Yekaterinburg, Russia
| | - Aina Puce
- Psychological & Brain Sciences, Indiana University, Bloomington, IN, USA
| | - Antonio Schettino
- Erasmus University Rotterdam, Rotterdam, the Netherland; Institute for Globally Distributed Open Research and Education (IGDORE), Sweden
| | - Daniele Schön
- Aix Marseille Univ, Inserm, INS, Inst Neurosci Syst, Marseille, France
| | | | | | - Anđela Šoškić
- Faculty of Philosophy, Laboratory for neurocognition and applied cognition, University of Belgrade, Serbia; Teacher Education Faculty, University of Belgrade, Serbia
| | - Suzy J Styles
- Psychology, Nanyang Technological University, Singapore; Singapore Institute for Clinical Sciences, A*STAR, Singapore
| | - Roni Tibon
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK; School of Psychology, University of Nottingham, Nottingham, UK
| | - Martina G Vilas
- Ernst Strüngmann Institute for Neuroscience, Frankfurt am Main, Germany
| | | | - Maximilien Chaumon
- Institut du Cerveau - Paris Brain Institute - ICM, Inserm U 1127, CNRS UMR 7225, APHP, Hôpital de la Pitié Salpêtrière, Sorbonne Université, Centre MEG-EEG, Centre de NeuroImagerie Recherche (CENIR), Paris, France..
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7
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Investigation of Corticomuscular Functional Coupling during Hand Movements Using Vine Copula. Brain Sci 2022; 12:brainsci12060754. [PMID: 35741639 PMCID: PMC9221488 DOI: 10.3390/brainsci12060754] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2022] [Revised: 05/30/2022] [Accepted: 06/06/2022] [Indexed: 02/05/2023] Open
Abstract
Corticomuscular functional coupling reflects the neuronal communication between cortical oscillations and muscle activity. Although the motor cortex is significantly involved in complex motor tasks, there is still no detailed understanding of the cortical contribution during such tasks. In this paper, we first propose a vine copula model to describe corticomuscular functional coupling and we construct the brain muscle function network. First, we recorded surface electromyography (sEMG) and electroencephalography (EEG) signals corresponding to the hand open, hand close, wrist flexion, and wrist extension motions of 12 participants during the initial experiments. The pre-processed signals were translated into the marginal density functions of different channels through the generalized autoregressive conditional heteroscedasticity model. Subsequently, we calculated the Kendall rank correlation coefficient, and used the R-vine model to decompose the multi-dimensional marginal density function into two-dimensional copula coefficient to determine the structure of the R-vine. Finally, we used the normalized adjacency matrix to structure the corticomuscular network for each hand motion considered. Based on the adjacency matrix, we found that the Kendall rank correlation coefficient between EEG and EMG was low. Moreover, a significant difference was observed in the correlation between the C3 and EMG signals for the different hand-motion activities. We also observed two core nodes in the networks corresponding to the four activities when the vine copula model was applied. Moreover, there was a large difference in the connections of the network models corresponding to the different hand-motion activities. Therefore, we believe that our approach is sufficiently accurate in identifying and classifying motor tasks.
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Podvalny E, King LE, He BJ. Spectral signature and behavioral consequence of spontaneous shifts of pupil-linked arousal in human. eLife 2021; 10:68265. [PMID: 34463255 PMCID: PMC8486382 DOI: 10.7554/elife.68265] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2021] [Accepted: 08/27/2021] [Indexed: 12/21/2022] Open
Abstract
Arousal levels perpetually rise and fall spontaneously. How markers of arousal—pupil size and frequency content of brain activity—relate to each other and influence behavior in humans is poorly understood. We simultaneously monitored magnetoencephalography and pupil in healthy volunteers at rest and during a visual perceptual decision-making task. Spontaneously varying pupil size correlates with power of brain activity in most frequency bands across large-scale resting state cortical networks. Pupil size recorded at prestimulus baseline correlates with subsequent shifts in detection bias (c) and sensitivity (d’). When dissociated from pupil-linked state, prestimulus spectral power of resting state networks still predicts perceptual behavior. Fast spontaneous pupil constriction and dilation correlate with large-scale brain activity as well but not perceptual behavior. Our results illuminate the relation between central and peripheral arousal markers and their respective roles in human perceptual decision-making.
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Affiliation(s)
- Ella Podvalny
- Neuroscience Institute, New York University School of Medicine, New York, United States
| | - Leana E King
- Neuroscience Institute, New York University School of Medicine, New York, United States
| | - Biyu J He
- Neuroscience Institute, New York University School of Medicine, New York, United States.,Departments of Neurology, Neuroscience & Physiology, and Radiology, New York University School of Medicine, New York, United States
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9
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Kołodziej A, Magnuski M, Ruban A, Brzezicka A. No relationship between frontal alpha asymmetry and depressive disorders in a multiverse analysis of five studies. eLife 2021; 10:e60595. [PMID: 34037520 PMCID: PMC8154036 DOI: 10.7554/elife.60595] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2020] [Accepted: 04/21/2021] [Indexed: 11/13/2022] Open
Abstract
For decades, the frontal alpha asymmetry (FAA) - a disproportion in EEG alpha oscillations power between right and left frontal channels - has been one of the most popular measures of depressive disorders (DD) in electrophysiology studies. Patients with DD often manifest a left-sided FAA: relatively higher alpha power in the left versus right frontal lobe. Recently, however, multiple studies failed to confirm this effect, questioning its reproducibility. Our purpose is to thoroughly test the validity of FAA in depression by conducting a multiverse analysis - running many related analyses and testing the sensitivity of the effect to changes in the analytical approach - on data from five independent studies. Only 13 of the 270 analyses revealed significant results. We conclude the paper by discussing theoretical assumptions underlying the FAA and suggest a list of guidelines for improving and expanding the EEG data analysis in future FAA studies.
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Affiliation(s)
| | | | | | - Aneta Brzezicka
- University of Social Sciences and HumanitiesWarsawPoland
- Cedars-Sinai Medical Center Department of NeurosurgeryLos AngelesUnited States
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10
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Calabrò RS, Billeri L, Ciappina F, Balletta T, Porcari B, Cannavò A, Pignolo L, Manuli A, Naro A. Toward improving functional recovery in spinal cord injury using robotics: a pilot study focusing on ankle rehabilitation. Expert Rev Med Devices 2021; 19:83-95. [PMID: 33616471 DOI: 10.1080/17434440.2021.1894125] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Background: Conventional physical therapy interventions are strongly recommended to improve ambulation potential and upright mobility in persons with incomplete spinal cord injury (iSCI). Ankle rehabilitation plays a significant role, as it aims to stem drop foot consequences.Research question: This pilot study aimed to assess the neurophysiological underpinnings of robot-aided ankle rehabilitation (using a platform robot) compared to conventional physiotherapy and its efficacy in improving gait performance and balance in persons with iSCI.Methods: Ten individuals with subacute/chronic iSCI (six males and four females, 39 ± 13 years, time since injury 8 ± 4 months, ASIA impairment scale grade C-D) were provided with one-month intensive training for robot-aided ankle rehabilitation (24 sessions, 1 h daily, six times a week). Clinical (10-Meter Walk Test (10MWT), 6-Minute Walk Test (6MWT), and Timed Up and Go test (TUG)), and electrophysiological aftereffects (surface-EMG from tibialis anterior and medial gastrocnemius muscles to estimate muscle activation patterns; and corticomuscular coherence-CMC-to assess functional synchronization between sensorimotor cortex and muscles, i.e. the functional integrity of corticospinal output) were assessed at baseline (PRE) and after the trial completion (POST). The experimental group (EG) data were compared with those coming from a retrospective control group (CG; n = 10) matched for clinical-demographic characteristics, who previously underwent conventional ankle rehabilitation.Results: the EG achieved a greater improvement in balance and gait as compared to the CG (TUG EG from 70 ± 18 to 45 ± 15 s, p = 0.002; CG from 68 ± 21 to 48 ± 18 s, p = 0.01; group-comparison p = 0.001; 10MWT EG from 0.43 ± 0.11 to 0.51 ± 0.09 m/s, p = 0.006; CG from 0.4 ± 0.13 to 0.45 ± 0.12, p = 0.01; group-comparison p = 0.006; 6 MWT EG from 231 ± 13 to 274 ± 15 m, p < 0.001; CG from 236 ± 13 to 262 ± 15 m, p = 0.003; group-comparison p = 0.01). Furthermore, the EG showed a retraining of muscle activation (an increase within proper movements, with a reduction of co-contractions) and CMC (beta frequency increase within proper movements, i.e. in a framework of preserved motor coordination). The improvements in CMC, gait, balance, and muscle activation were not correlated with each other.Conclusions: Robot-aided ankle rehabilitation improved gait performance by selectively ameliorating CMC, muscle activation patterns, and, lastly, gait balance and speed. Despite CMC, gait, balance, and muscle activation were not correlated, this pilot study suggests that robot-aided ankle rehabilitation may favor a better communication between above-SCI and below-SCI structures. This communication improvement may depend on a more synchronized corticospinal output (as per CMC increase) and a better responsiveness of below-SCI motorneurons to corticospinal output (as per specific and ankle movement focused muscle activation increases at the surface EMG), thus favoring greater recruitment of spinal motor units and, ultimately, improving muscle activation pattern and strength.Significance: Adopting robot-aided ankle rehabilitation protocols for persons with iSCI in the subacute/chronic phase may allow achieving a clinically significant improvement in gait performance.
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Affiliation(s)
| | - Luana Billeri
- IRCCS Centro Neurolesi Bonino Pulejo, Messina, Italy
| | | | - Tina Balletta
- IRCCS Centro Neurolesi Bonino Pulejo, Messina, Italy
| | - Bruno Porcari
- IRCCS Centro Neurolesi Bonino Pulejo, Messina, Italy
| | | | | | | | - Antonino Naro
- IRCCS Centro Neurolesi Bonino Pulejo, Messina, Italy
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11
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Youssofzadeh V, Stout J, Ustine C, Gross WL, Conant LL, Humphries CJ, Binder JR, Raghavan M. Mapping language from MEG beta power modulations during auditory and visual naming. Neuroimage 2020; 220:117090. [DOI: 10.1016/j.neuroimage.2020.117090] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2020] [Revised: 06/06/2020] [Accepted: 06/23/2020] [Indexed: 01/22/2023] Open
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12
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Affiliation(s)
- Marijn van Vliet
- Department of Neuroscience and Biomedical Engineering, Aalto University, Espoo, Finland
- * E-mail:
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13
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Saarinen T, Kujala J, Laaksonen H, Jalava A, Salmelin R. Task-Modulated Corticocortical Synchrony in the Cognitive-Motor Network Supporting Handwriting. Cereb Cortex 2020; 30:1871-1886. [PMID: 31670795 PMCID: PMC7132916 DOI: 10.1093/cercor/bhz210] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2018] [Revised: 08/18/2019] [Accepted: 08/19/2019] [Indexed: 01/06/2023] Open
Abstract
Both motor and cognitive aspects of behavior depend on dynamic, accurately timed neural processes in large-scale brain networks. Here, we studied synchronous interplay between cortical regions during production of cognitive-motor sequences in humans. Specifically, variants of handwriting that differed in motor variability, linguistic content, and memorization of movement cues were contrasted to unveil functional sensitivity of corticocortical connections. Data-driven magnetoencephalography mapping (n = 10) uncovered modulation of mostly left-hemispheric corticocortical interactions, as quantified by relative changes in phase synchronization. At low frequencies (~2–13 Hz), enhanced frontoparietal synchrony was related to regular handwriting, whereas premotor cortical regions synchronized for simple loop production and temporo-occipital areas for a writing task substituting normal script with loop patterns. At the beta-to-gamma band (~13–45 Hz), enhanced synchrony was observed for regular handwriting in the central and frontoparietal regions, including connections between the sensorimotor and supplementary motor cortices and between the parietal and dorsal premotor/precentral cortices. Interpreted within a modular framework, these modulations of synchrony mainly highlighted interactions of the putative pericentral subsystem of hand coordination and the frontoparietal subsystem mediating working memory operations. As part of cortical dynamics, interregional phase synchrony varies depending on task demands in production of cognitive-motor sequences.
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Affiliation(s)
- Timo Saarinen
- Department of Neuroscience and Biomedical Engineering, Aalto University, FI-00076 AALTO, Espoo, Finland
- Aalto NeuroImaging, Aalto University, FI-00076 AALTO, Espoo, Finland
- Address correspondence to Timo Saarinen, Department of Neuroscience and Biomedical Engineering, Aalto University, P.O. Box 12200, FI-00076 AALTO, Espoo, Finland.
| | - Jan Kujala
- Department of Neuroscience and Biomedical Engineering, Aalto University, FI-00076 AALTO, Espoo, Finland
- Department of Psychology, University of Jyväskylä, FI-40014, Jyväskylä, Finland
| | - Hannu Laaksonen
- Department of Neuroscience and Biomedical Engineering, Aalto University, FI-00076 AALTO, Espoo, Finland
- Aalto NeuroImaging, Aalto University, FI-00076 AALTO, Espoo, Finland
| | - Antti Jalava
- Department of Neuroscience and Biomedical Engineering, Aalto University, FI-00076 AALTO, Espoo, Finland
| | - Riitta Salmelin
- Department of Neuroscience and Biomedical Engineering, Aalto University, FI-00076 AALTO, Espoo, Finland
- Aalto NeuroImaging, Aalto University, FI-00076 AALTO, Espoo, Finland
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14
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Iivanainen J, Zetter R, Parkkonen L. Potential of on-scalp MEG: Robust detection of human visual gamma-band responses. Hum Brain Mapp 2019; 41:150-161. [PMID: 31571310 PMCID: PMC7267937 DOI: 10.1002/hbm.24795] [Citation(s) in RCA: 37] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2019] [Revised: 08/09/2019] [Accepted: 09/03/2019] [Indexed: 11/25/2022] Open
Abstract
Electrophysiological signals recorded intracranially show rich frequency content spanning from near‐DC to hundreds of hertz. Noninvasive electromagnetic signals measured with electroencephalography (EEG) or magnetoencephalography (MEG) typically contain less signal power in high frequencies than invasive recordings. Particularly, noninvasive detection of gamma‐band activity (>30 Hz) is challenging since coherently active source areas are small at such frequencies and the available imaging methods have limited spatial resolution. Compared to EEG and conventional SQUID‐based MEG, on‐scalp MEG should provide substantially improved spatial resolution, making it an attractive method for detecting gamma‐band activity. Using an on‐scalp array comprised of eight optically pumped magnetometers (OPMs) and a conventional whole‐head SQUID array, we measured responses to a dynamic visual stimulus known to elicit strong gamma‐band responses. OPMs had substantially higher signal power than SQUIDs, and had a slightly larger relative gamma‐power increase over the baseline. With only eight OPMs, we could obtain gamma‐activity source estimates comparable to those of SQUIDs at the group level. Our results show the feasibility of OPMs to measure gamma‐band activity. To further facilitate the noninvasive detection of gamma‐band activity, the on‐scalp OPM arrays should be optimized with respect to sensor noise, the number of sensors and intersensor spacing.
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Affiliation(s)
- Joonas Iivanainen
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, Finland
| | - Rasmus Zetter
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, Finland
| | - Lauri Parkkonen
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, Finland.,Aalto Neuroimaging, Aalto University, Espoo, Finland
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15
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Liu J, Sheng Y, Zeng J, Liu H. Corticomuscular Coherence for Upper Arm Flexor and Extensor Muscles During Isometric Exercise and Cyclically Isokinetic Movement. Front Neurosci 2019; 13:522. [PMID: 31178688 PMCID: PMC6538811 DOI: 10.3389/fnins.2019.00522] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2019] [Accepted: 05/06/2019] [Indexed: 01/27/2023] Open
Abstract
Cortical-muscular functional coupling reflects the interaction between the cerebral cortex and the muscle activities. Corticomuscular coherence (CMC) has been extensively revealed in sustained contractions of various upper- and lower-limb muscles during static and dynamic force outputs. However, it is not well-understood that the CMC modulation mechanisms, i.e., the relation between a cerebral hemisphere and dynamic motor controlling limbs at constant speeds, such as isokinetic movement. In this paper, we explore the CMC between upper arm flexors/extensors movement and motor cortex during isometric exercise and cyclically isokinetic movement. We also provide further insights of frequency-shift and the neural pathway mechanisms in isokinetic movement by evaluating the coherence between motor cortex and agonistic or antagonistic muscles. This study is the first to investigate the relationship between cortical-muscular functional connections in elbow flexion-extension movement with constant speeds. The result shows that gamma-range coherence for isokinetic movement is greatly increased compared with isometric exercise, and significant CMC is observed in the entire flexion-extension stage regardless the nature of muscles contraction, although dominant synchronization of cortical oscillation and muscular activity resonated in sustained contraction stage principally. Besides, the CMC for extensors and flexors are explicitly consistent in contraction stage during cyclically isokinetic elbow movement. It is concluded that cortical-muscular coherence can be dynamically modulated as well as selective by cognitive demands of the body, and the time-varying mechanisms of the synchronous motor oscillation exist in healthy individuals during dynamic movement.
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Affiliation(s)
- Jinbiao Liu
- State Key Laboratory of Mechanical System and Vibration, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Yixuan Sheng
- State Key Laboratory of Mechanical System and Vibration, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Jia Zeng
- State Key Laboratory of Mechanical System and Vibration, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Honghai Liu
- State Key Laboratory of Mechanical System and Vibration, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China
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16
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Kaltiainen H, Liljeström M, Helle L, Salo A, Hietanen M, Renvall H, Forss N. Mild Traumatic Brain Injury Affects Cognitive Processing and Modifies Oscillatory Brain Activity during Attentional Tasks. J Neurotrauma 2019; 36:2222-2232. [PMID: 30896274 PMCID: PMC6653790 DOI: 10.1089/neu.2018.6306] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
Abstract
Despite the high prevalence of mild traumatic brain injury (mTBI), current diagnostic tools to objectively assess cognitive complaints after mTBI continue to be inadequate. Our aim was to identify neuronal correlates for cognitive difficulties in mTBI patients by evaluating the possible alterations in oscillatory brain activity during a behavioral task known to be sensitive to cognitive impairment after mTBI. We compared oscillatory brain activity during rest and cognitive tasks (Paced Auditory Serial Addition Test [PASAT] and a vigilance test [VT]) with magnetoencephalography between 25 mTBI patients and 20 healthy controls. Whereas VT induced no significant differences compared with resting state in either group, patients exhibited stronger attenuation of 8- to 14-Hz oscillatory activity during PASAT than healthy controls in the left parietotemporal cortex (p ≤ 0.05). Further, significant task-related modulation in the left superior frontal gyrus and right prefrontal cortex was detected only in patients. The ∼10-Hz (alpha) peak frequency declined in frontal, temporal, and parietal regions during PASAT compared with rest (p < 0.016) in patients, whereas in controls it remained the same or showed a tendency to increase. In patients, the ∼10-Hz peak amplitude was negatively correlated with behavioral performance in the Trail Making Test. The observed alterations in the cortical oscillatory activity during cognitive load may provide measurable neurophysiological correlates of cognitive difficulties in mTBI patients, even at the individual level.
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Affiliation(s)
- Hanna Kaltiainen
- 1 Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, Finland.,2 Aalto Neuroimaging, MEG Core, Aalto University, Espoo, Finland.,3 Lohja District Hospital, Department of Neurology, Lohja, Finland.,5 Clinical Neurosciences, University of Helsinki, and Department of Neurology, Helsinki University Hospital, BioMag Laboratory, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Mia Liljeström
- 1 Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, Finland.,2 Aalto Neuroimaging, MEG Core, Aalto University, Espoo, Finland
| | - Liisa Helle
- 1 Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, Finland.,2 Aalto Neuroimaging, MEG Core, Aalto University, Espoo, Finland.,4 MEGIN (Elekta Oy), Helsinki, Finland
| | - Anne Salo
- 5 Clinical Neurosciences, University of Helsinki, and Department of Neurology, Helsinki University Hospital, BioMag Laboratory, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Marja Hietanen
- 5 Clinical Neurosciences, University of Helsinki, and Department of Neurology, Helsinki University Hospital, BioMag Laboratory, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Hanna Renvall
- 1 Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, Finland.,2 Aalto Neuroimaging, MEG Core, Aalto University, Espoo, Finland.,5 Clinical Neurosciences, University of Helsinki, and Department of Neurology, Helsinki University Hospital, BioMag Laboratory, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.,6 HUS Medical Imaging Center, BioMag Laboratory, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Nina Forss
- 1 Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, Finland.,2 Aalto Neuroimaging, MEG Core, Aalto University, Espoo, Finland.,5 Clinical Neurosciences, University of Helsinki, and Department of Neurology, Helsinki University Hospital, BioMag Laboratory, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
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