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Rochas V, Montandon ML, Rodriguez C, Herrmann FR, Eytan A, Pegna AJ, Michel CM, Giannakopoulos P. Mentalizing and self-other distinction in visual perspective taking: the analysis of temporal neural processing using high-density EEG. Front Behav Neurosci 2023; 17:1206011. [PMID: 37465000 PMCID: PMC10351605 DOI: 10.3389/fnbeh.2023.1206011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Accepted: 06/16/2023] [Indexed: 07/20/2023] Open
Abstract
This high density EEG report dissects the neural processing in the visual perspective taking using four experimental comparisons (Arrow, Avatar and Self, Other). Early activation differences occurred between the Avatar and the Arrow condition in primary visual pathways concomitantly with alpha and beta phase locked responses predominant in the Avatar condition. In later time points, brain activation was stronger for the Avatar condition in paracentral lobule of frontal lobe. When taking the other's perspective, there was an increased recruitment of generators in the occipital and temporal lobes and later on in mentalizing and salience networks bilaterally before spreading to right frontal lobe subdivisions. Microstate analysis further supported late recruitment of the medial frontal gyrus and precentral lobule in this condition. Other perspective for the Avatar only showed a strong beta response located first in left occipito-temporal and right parietal areas, and later on in frontal lobes. Our EEG data support distinct brain processes for the Avatar condition with an increased recruitment of brain generators that progresses from primary visual areas to the anterior brain. Taking the other's perspective needs an early recruitment of neural processors in posterior areas involved in theory of mind with later involvement of additional frontal generators.
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Affiliation(s)
- Vincent Rochas
- Functional Brain Mapping Laboratory, Department of Basic Neurosciences, University of Geneva, Geneva, Switzerland
- Human Neuroscience Platform, Fondation Campus Biotech Geneva, Geneva, Switzerland
| | - Marie-Louise Montandon
- Department of Psychiatry, Faculty of Medicine, University of Geneva, Geneva, Switzerland
- Department of Rehabilitation and Geriatrics, Geneva University Hospitals, University of Geneva, Geneva, Switzerland
| | - Cristelle Rodriguez
- Department of Psychiatry, Faculty of Medicine, University of Geneva, Geneva, Switzerland
- Division of Institutional Measures, Medical Direction, Geneva University Hospitals, Geneva, Switzerland
| | - François R. Herrmann
- Department of Rehabilitation and Geriatrics, Geneva University Hospitals, University of Geneva, Geneva, Switzerland
| | - Ariel Eytan
- Department of Psychiatry, Faculty of Medicine, University of Geneva, Geneva, Switzerland
- Division of Institutional Measures, Medical Direction, Geneva University Hospitals, Geneva, Switzerland
| | - Alan J. Pegna
- School of Psychology, The University of Queensland, Brisbane, QLD, Australia
| | - Christoph M. Michel
- Functional Brain Mapping Laboratory, Department of Basic Neurosciences, University of Geneva, Geneva, Switzerland
| | - Panteleimon Giannakopoulos
- Department of Psychiatry, Faculty of Medicine, University of Geneva, Geneva, Switzerland
- Division of Institutional Measures, Medical Direction, Geneva University Hospitals, Geneva, Switzerland
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di Biase L, Ricci L, Caminiti ML, Pecoraro PM, Carbone SP, Di Lazzaro V. Quantitative High Density EEG Brain Connectivity Evaluation in Parkinson's Disease: The Phase Locking Value (PLV). J Clin Med 2023; 12. [PMID: 36835985 DOI: 10.3390/jcm12041450] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2023] [Revised: 02/01/2023] [Accepted: 02/07/2023] [Indexed: 02/17/2023] Open
Abstract
INTRODUCTION The present study explores brain connectivity in Parkinson's disease (PD) and in age matched healthy controls (HC), using quantitative EEG analysis, at rest and during a motor tasks. We also evaluated the diagnostic performance of the phase locking value (PLV), a measure of functional connectivity, in differentiating PD patients from HCs. METHODS High-density, 64-channels, EEG data from 26 PD patients and 13 HC were analyzed. EEG signals were recorded at rest and during a motor task. Phase locking value (PLV), as a measure of functional connectivity, was evaluated for each group in a resting state and during a motor task for the following frequency bands: (i) delta: 2-4 Hz; (ii) theta: 5-7 Hz; (iii) alpha: 8-12 Hz; beta: 13-29 Hz; and gamma: 30-60 Hz. The diagnostic performance in PD vs. HC discrimination was evaluated. RESULTS Results showed no significant differences in PLV connectivity between the two groups during the resting state, but a higher PLV connectivity in the delta band during the motor task, in HC compared to PD. Comparing the resting state versus the motor task for each group, only HCs showed a higher PLV connectivity in the delta band during motor task. A ROC curve analysis for HC vs. PD discrimination, showed an area under the ROC curve (AUC) of 0.75, a sensitivity of 100%, and a negative predictive value (NPV) of 100%. CONCLUSIONS The present study evaluated the brain connectivity through quantitative EEG analysis in Parkinson's disease versus healthy controls, showing a higher PLV connectivity in the delta band during the motor task, in HC compared to PD. This neurophysiology biomarkers showed the potentiality to be explored in future studies as a potential screening biomarker for PD patients.
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Kolb FP, Kutz DF, Werner J, Schönecker S, Hürster W, Nida‐Rümelin J. Stimulus-dependent deliberation process in left- and right-handers obtained via current source density analysis. Physiol Rep 2022; 10:e15522. [PMID: 36471659 PMCID: PMC9723376 DOI: 10.14814/phy2.15522] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2022] [Revised: 09/24/2022] [Accepted: 11/02/2022] [Indexed: 12/12/2022] Open
Abstract
The aim of the present study was to compare the activity patterns of young, healthy right- (RH, n = 25) and left-handed (LH, n = 20) subjects in high-density electroencephalograpic (EEG) recordings during a deliberation task. The deliberation task consisted of pressing one of two keys depending on a color-word Stroop task (Stroop, 1935) presented on a computer screen. Depending on the color shown and the meaning of the color word, participants responded with the index finger of the dominant or non-dominant hand. This leads to different activities in the hemispheres depending on the acting hand and on subject's handedness. Presenting the word "black" in black color, subjects were not to press any key (no-go-trial). Prior to this, subjects were tested for simple motor tasks, during which they were informed about the motor action to be performed. The temporal activity patterns obtained from RH and LH were very similar in shape and constituent components. The comparison of the three types of trials lead to the assumption that the deliberation process is based on a two-step decision: The first decision was characterized by the choice between move (match-trials, mismatch-trials) or not to move (no-go-trials). The second decision resulted in the final judgment of which index finger has to be used. The latter decision, in particular, can be tracked via the local spread of activity over the scalp. Our hypothesis is based on a comparison of activities and locations of RH and LH and yields some insights about processing a two-step decision in a deliberation task.
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Affiliation(s)
- Florian P. Kolb
- Department of Physiology Physiological GenomicsFaculty of MedicineLudwig‐Maximilians‐University of MunichMunichGermany
| | - Dieter F. Kutz
- Department of Physiology Physiological GenomicsFaculty of MedicineLudwig‐Maximilians‐University of MunichMunichGermany
- Department of Neuromotor Behavior and ExerciseInstitute of Sport and Exercise Sciences, University of MuensterMuensterGermany
| | - Jana Werner
- Department of NeurologyUniversity Hospital ZürichZürichSwitzerland
| | - Sonja Schönecker
- Department of NeurologyLudwig‐Maximilians‐University of MunichMunichGermany
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Duprez J, Tabbal J, Hassan M, Modolo J, Kabbara A, Mheich A, Drapier S, Vérin M, Sauleau P, Wendling F, Benquet P, Houvenaghel JF. Spatio-temporal dynamics of large-scale electrophysiological networks during cognitive action control in healthy controls and Parkinson's disease patients. Neuroimage 2022; 258:119331. [PMID: 35660459 DOI: 10.1016/j.neuroimage.2022.119331] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2021] [Revised: 05/16/2022] [Accepted: 05/23/2022] [Indexed: 10/18/2022] Open
Abstract
Among the cognitive symptoms that are associated with Parkinson's disease (PD), alterations in cognitive action control (CAC) are commonly reported in patients. CAC enables the suppression of an automatic action, in favor of a goal-directed one. The implementation of CAC is time-resolved and arguably associated with dynamic changes in functional brain networks. However, the electrophysiological functional networks involved, their dynamic changes, and how these changes are affected by PD, still remain unknown. In this study, to address this gap of knowledge, 10 PD patients and 10 healthy controls (HC) underwent a Simon task while high-density electroencephalography (HD-EEG) was recorded. Source-level dynamic connectivity matrices were estimated using the phase-locking value in the beta (12-25 Hz) and gamma (30-45 Hz) frequency bands. Temporal independent component analyses were used as a dimension reduction tool to isolate the task-related brain network states. Typical microstate metrics were quantified to investigate the presence of these states at the subject-level. Our results first confirmed that PD patients experienced difficulties in inhibiting automatic responses during the task. At the group-level, we found three functional network states in the beta band that involved fronto-temporal, temporo-cingulate and fronto-frontal connections with typical CAC-related prefrontal and cingulate nodes (e.g., inferior frontal cortex). The presence of these networks did not differ between PD patients and HC when analyzing microstates metrics, and no robust correlations with behavior were found. In the gamma band, five networks were found, including one fronto-temporal network that was identical to the one found in the beta band. These networks also included CAC-related nodes previously identified in different neuroimaging modalities. Similarly to the beta networks, no subject-level differences were found between PD patients and HC. Interestingly, in both frequency bands, the dominant network at the subject-level was never the one that was the most durably modulated by the task. Altogether, this study identified the dynamic functional brain networks observed during CAC, but did not highlight PD-related changes in these networks that might explain behavioral changes. Although other new methods might be needed to investigate the presence of task-related networks at the subject-level, this study still highlights that task-based dynamic functional connectivity is a promising approach in understanding the cognitive dysfunctions observed in PD and beyond.
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Key Words
- Cognitive control
- DIFFIT, Difference in data fitting
- DLPFC, Dorso-lateral prefrontal cortex
- EEG, Electroencephalography
- FC, Functional connectivity
- Functional connectivity
- HC, Healthy controls
- HD-EEG, High-density EEG
- ICA, Independent component analysis
- IFC, Inferior frontal cortex
- MEG, Magnetoencephalography
- Networks, Dynamics
- PD, Parkinson's disease
- PLV, Phase locking value
- Parkinson's disease Abbreviations CAC, Cognitive action control
- ROIS, Regions of interest
- RT, Reaction time
- Simon task
- dBNS, Dynamic brain network state
- dFC, Dynamic functional connectivity
- fMRI, Functional magnetic resonance imaging
- high density EEG
- pre-SMA, Pre-supplementary motor area
- tICA, Temporal ICA
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Affiliation(s)
- Joan Duprez
- Univ Rennes, LTSI - U1099, F-35000 Rennes, France
| | - Judie Tabbal
- Univ Rennes, LTSI - U1099, F-35000 Rennes, France; Azm Center for Research in Biotechnology and Its Applications, EDST, Lebanese University, Beirut, Lebanon
| | - Mahmoud Hassan
- MINDig, F-35000 Rennes, France; School of Engineering, Reykjavik University, Iceland
| | | | | | | | - Sophie Drapier
- CIC INSERM 1414, Rennes, France; Neurology Department, Pontchaillou Hospital, Rennes University Hospital, France
| | - Marc Vérin
- Neurology Department, Pontchaillou Hospital, Rennes University Hospital, France; Behavioral and Basal Ganglia' Research Unit, University of Rennes 1-Rennes University Hospital, France
| | - Paul Sauleau
- Behavioral and Basal Ganglia' Research Unit, University of Rennes 1-Rennes University Hospital, France; Neurophysiology department, Rennes University Hospital, France
| | | | | | - Jean-François Houvenaghel
- Neurology Department, Pontchaillou Hospital, Rennes University Hospital, France; Behavioral and Basal Ganglia' Research Unit, University of Rennes 1-Rennes University Hospital, France
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Chabin T, Gabriel D, Chansophonkul T, Michelant L, Joucla C, Haffen E, Moulin T, Comte A, Pazart L. Cortical Patterns of Pleasurable Musical Chills Revealed by High-Density EEG. Front Neurosci 2020; 14:565815. [PMID: 33224021 PMCID: PMC7670092 DOI: 10.3389/fnins.2020.565815] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2020] [Accepted: 09/29/2020] [Indexed: 01/02/2023] Open
Abstract
Music has the capacity to elicit strong positive feelings in humans by activating the brain's reward system. Because group emotional dynamics is a central concern of social neurosciences, the study of emotion in natural/ecological conditions is gaining interest. This study aimed to show that high-density EEG (HD-EEG) is able to reveal patterns of cerebral activities previously identified by fMRI or PET scans when the subject experiences pleasurable musical chills. We used HD-EEG to record participants (11 female, 7 male) while listening to their favorite pleasurable chill-inducing musical excerpts; they reported their subjective emotional state from low pleasure up to chills. HD-EEG results showed an increase of theta activity in the prefrontal cortex when arousal and emotional ratings increased, which are associated with orbitofrontal cortex activation localized using source localization algorithms. In addition, we identified two specific patterns of chills: a decreased theta activity in the right central region, which could reflect supplementary motor area activation during chills and may be related to rhythmic anticipation processing, and a decreased theta activity in the right temporal region, which may be related to musical appreciation and could reflect the right superior temporal gyrus activity. The alpha frontal/prefrontal asymmetry did not reflect the felt emotional pleasure, but the increased frontal beta to alpha ratio (measure of arousal) corresponded to increased emotional ratings. These results suggest that EEG may be a reliable method and a promising tool for the investigation of group musical pleasure through musical reward processing.
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Affiliation(s)
- Thibault Chabin
- Laboratoire de Neurosciences Intégratives et Cliniques, EA 481, Université Bourgogne Franche-Comté, Besançon, France
| | - Damien Gabriel
- Laboratoire de Neurosciences Intégratives et Cliniques, EA 481, Université Bourgogne Franche-Comté, Besançon, France
- INSERM CIC 1431, Centre d’Investigation Clinique de Besançon, Centre Hospitalier Universitaire de Besançon, Besançon, France
- Plateforme de Neuroimagerie Fonctionnelle et Neurostimulation – Neuraxess, Centre Hospitalier Universitaire de Besançon, Université Bourgogne Franche-Comté, Besançon, France
| | - Tanawat Chansophonkul
- INSERM CIC 1431, Centre d’Investigation Clinique de Besançon, Centre Hospitalier Universitaire de Besançon, Besançon, France
| | - Lisa Michelant
- Laboratoire de Neurosciences Intégratives et Cliniques, EA 481, Université Bourgogne Franche-Comté, Besançon, France
| | - Coralie Joucla
- Laboratoire de Neurosciences Intégratives et Cliniques, EA 481, Université Bourgogne Franche-Comté, Besançon, France
| | - Emmanuel Haffen
- Laboratoire de Neurosciences Intégratives et Cliniques, EA 481, Université Bourgogne Franche-Comté, Besançon, France
- INSERM CIC 1431, Centre d’Investigation Clinique de Besançon, Centre Hospitalier Universitaire de Besançon, Besançon, France
- Plateforme de Neuroimagerie Fonctionnelle et Neurostimulation – Neuraxess, Centre Hospitalier Universitaire de Besançon, Université Bourgogne Franche-Comté, Besançon, France
| | - Thierry Moulin
- Laboratoire de Neurosciences Intégratives et Cliniques, EA 481, Université Bourgogne Franche-Comté, Besançon, France
- INSERM CIC 1431, Centre d’Investigation Clinique de Besançon, Centre Hospitalier Universitaire de Besançon, Besançon, France
- Plateforme de Neuroimagerie Fonctionnelle et Neurostimulation – Neuraxess, Centre Hospitalier Universitaire de Besançon, Université Bourgogne Franche-Comté, Besançon, France
| | - Alexandre Comte
- Laboratoire de Neurosciences Intégratives et Cliniques, EA 481, Université Bourgogne Franche-Comté, Besançon, France
- INSERM CIC 1431, Centre d’Investigation Clinique de Besançon, Centre Hospitalier Universitaire de Besançon, Besançon, France
- Plateforme de Neuroimagerie Fonctionnelle et Neurostimulation – Neuraxess, Centre Hospitalier Universitaire de Besançon, Université Bourgogne Franche-Comté, Besançon, France
| | - Lionel Pazart
- Laboratoire de Neurosciences Intégratives et Cliniques, EA 481, Université Bourgogne Franche-Comté, Besançon, France
- INSERM CIC 1431, Centre d’Investigation Clinique de Besançon, Centre Hospitalier Universitaire de Besançon, Besançon, France
- Plateforme de Neuroimagerie Fonctionnelle et Neurostimulation – Neuraxess, Centre Hospitalier Universitaire de Besançon, Université Bourgogne Franche-Comté, Besançon, France
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Carraro U. Thirty years of translational research in Mobility Medicine: Collection of abstracts of the 2020 Padua Muscle Days. Eur J Transl Myol 2020; 30:8826. [PMID: 32499887 PMCID: PMC7254447 DOI: 10.4081/ejtm.2019.8826] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2020] [Accepted: 01/22/2020] [Indexed: 12/11/2022] Open
Abstract
More than half a century of skeletal muscle research is continuing at Padua University (Italy) under the auspices of the Interdepartmental Research Centre of Myology (CIR-Myo), the European Journal of Translational Myology (EJTM) and recently also with the support of the A&CM-C Foundation for Translational Myology, Padova, Italy. The Volume 30(1), 2020 of the EJTM opens with the collection of abstracts for the conference "2020 Padua Muscle Days: Mobility Medicine 30 years of Translational Research". This is an international conference that will be held between March 18-21, 2020 in Euganei Hills and Padova in Italy. The abstracts are excellent examples of translational research and of the multidimensional approaches that are needed to classify and manage (in both the acute and chronic phases) diseases of Mobility that span from neurologic, metabolic and traumatic syndromes to the biological process of aging. One of the typical aim of Physical Medicine and Rehabilitation is indeed to reduce pain and increase mobility enough to enable impaired persons to walk freely, garden, and drive again. The excellent contents of this Collection of Abstracts reflect the high scientific caliber of researchers and clinicians who are eager to present their results at the PaduaMuscleDays. A series of EJTM Communications will also add to this preliminary evidence.
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Affiliation(s)
- Ugo Carraro
- Interdepartmental Research Centre of Myology (CIR-Myo), Department of Biomedical Sciences, University of Padova, Italy
- A&C M-C Foundation for Translational Myology, Padova, Italy
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Bourel-Ponchel E, Mahmoudzadeh M, Adebimpe A, Wallois F. Functional and Structural Network Disorganizations in Typical Epilepsy With Centro-Temporal Spikes and Impact on Cognitive Neurodevelopment. Front Neurol 2019; 10:809. [PMID: 31555191 PMCID: PMC6727184 DOI: 10.3389/fneur.2019.00809] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2019] [Accepted: 07/15/2019] [Indexed: 12/20/2022] Open
Abstract
Epilepsy with Centrotemporal Spikes (ECTS) is the most common form of self-limited focal epilepsy. The pathophysiological mechanisms by which ECTS induces neuropsychological impairment in 15-30% of affected children remain unclear. The objective of this study is to review the current state of knowledge concerning the brain structural and functional changes that may be involved in cognitive dysfunctions in ECTS. Structural brain imaging suggests the presence of subtle neurodevelopmental changes over the epileptogenic zone and over distant regions in ECTS. This structural remodeling likely occurs prior to the diagnosis and evolves over time, especially in patients with cognitive impairment, suggesting that the epileptogenic processes might interfere with the dynamics of the brain development and/or the normal maturation processes. Functional brain imaging demonstrates profound disorganization accentuated by interictal epileptic spikes (IES) in the epileptogenic zone and in remote networks in ECTS. Over the epileptogenic zone, the literature demonstrates changes in term of neuronal activity and synchronization, which are effective several hundred milliseconds before the IES. In the same time window, functional changes are also observed in bilateral distant networks, notably in the frontal and temporal lobes. Effective connectivity demonstrates that the epileptogenic zone constitutes the key area at the origin of IES propagation toward distant cortical regions, including frontal areas. Altogether, structural and functional network disorganizations, in terms of: (i) power spectral values, (ii) functional and effective connectivity, are likely to participate in the cognitive impairment commonly reported in children with ECTS. These results suggest a central and causal role of network disorganizations related to IES in the neuropsychological impairment described in ECTS children.
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Affiliation(s)
- Emilie Bourel-Ponchel
- INSERM UMR 1105, Research Group on Multimodal Analysis of Brain Function, University of Picardie Jules Verne, Amiens, France
- INSERM UMR 1105, EFSN Pediatric, Amiens University Hospital, Amiens, France
| | - Mahdi Mahmoudzadeh
- INSERM UMR 1105, Research Group on Multimodal Analysis of Brain Function, University of Picardie Jules Verne, Amiens, France
- INSERM UMR 1105, EFSN Pediatric, Amiens University Hospital, Amiens, France
| | - Azeez Adebimpe
- INSERM UMR 1105, Research Group on Multimodal Analysis of Brain Function, University of Picardie Jules Verne, Amiens, France
| | - Fabrice Wallois
- INSERM UMR 1105, Research Group on Multimodal Analysis of Brain Function, University of Picardie Jules Verne, Amiens, France
- INSERM UMR 1105, EFSN Pediatric, Amiens University Hospital, Amiens, France
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Abstract
Deprived of sensory input, as in deafness, the brain tends to reorganize. Cross-modal reorganization occurs when cortices associated with deficient sensory modalities are recruited by other, intact senses for processing of the latter's sensory input. Studies have shown that this type of reorganization may affect outcomes when sensory stimulation is later introduced via intervention devices. One such device is the cochlear implant (CI). Hundreds of thousands of CIs have been fitted on people with hearing impairment worldwide, many of them children. Factors such as age of implantation have proven useful in predicting speech perception outcome with these devices in children. However, a portion of the variance in speech understanding ability remains unexplained. It is possible that the degree of cross-modal reorganization may explain additional variability in listening outcomes. Thus, the current study aimed to examine possible somatosensory cross-modal reorganization of the auditory cortices. To this end we used high density EEG to record cortical responses to vibrotactile stimuli in children with normal hearing (NH) and those with CIs. We first investigated cortical somatosensory evoked potentials (CSEP) in NH children, in order to establish normal patterns of CSEP waveform morphology and sources of cortical activity. We then compared CSEP waveforms and estimations of cortical sources between NH children and those with CIs to assess the degree of somatosensory cross-modal reorganization. Results showed that NH children showed expected patterns of CSEP and current density reconstructions, such that postcentral cortices were activated contralaterally to the side of stimulation. Participants with CIs also showed this pattern of activity. However, in addition, they showed activation of auditory cortical areas in response to somatosensory stimulation. Additionally, certain CSEP waveform components were significantly earlier in the CI group than the children with NH. These results are taken as evidence of cross-modal reorganization by the somatosensory modality in children with CIs. Speech perception in noise scores were negatively associated with CSEP waveform components latencies in the CI group, suggesting that the degree of cross-modal reorganization is related to speech perception outcomes. These findings may have implications for clinical rehabilitation in children with cochlear implants.
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Affiliation(s)
- Garrett Cardon
- Department of Psychology, Colorado State University, Fort Collins, CO, United States
| | - Anu Sharma
- Department of Speech, Language, and Hearing Sciences, University of Colorado Boulder, Boulder, CO, United States
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Kramer MA, Ostrowski LM, Song DY, Thorn EL, Stoyell SM, Parnes M, Chinappen D, Xiao G, Eden UT, Staley KJ, Stufflebeam SM, Chu CJ. Scalp recorded spike ripples predict seizure risk in childhood epilepsy better than spikes. Brain 2019; 142:1296-1309. [PMID: 30907404 PMCID: PMC6487332 DOI: 10.1093/brain/awz059] [Citation(s) in RCA: 50] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2018] [Revised: 01/09/2019] [Accepted: 01/21/2019] [Indexed: 11/12/2022] Open
Abstract
In the past decade, brief bursts of fast oscillations in the ripple range have been identified in the scalp EEG as a promising non-invasive biomarker for epilepsy. However, investigation and clinical application of this biomarker have been limited because standard approaches to identify these brief, low amplitude events are difficult, time consuming, and subjective. Recent studies have demonstrated that ripples co-occurring with epileptiform discharges ('spike ripple events') are easier to detect than ripples alone and have greater pathological significance. Here, we used objective techniques to quantify spike ripples and test whether this biomarker predicts seizure risk in childhood epilepsy. We evaluated spike ripples in scalp EEG recordings from a prospective cohort of children with a self-limited epilepsy syndrome, benign epilepsy with centrotemporal spikes, and healthy control children. We compared the rate of spike ripples between children with epilepsy and healthy controls, and between children with epilepsy during periods of active disease (active, within 1 year of seizure) and after a period of sustained seizure-freedom (seizure-free, >1 year without seizure), using semi-automated and automated detection techniques. Spike ripple rate was higher in subjects with active epilepsy compared to healthy controls (P = 0.0018) or subjects with epilepsy who were seizure-free ON or OFF medication (P = 0.0018). Among epilepsy subjects with spike ripples, each month seizure-free decreased the odds of a spike ripple by a factor of 0.66 [95% confidence interval (0.47, 0.91), P = 0.021]. Comparing the diagnostic accuracy of the presence of at least one spike ripple versus a classic spike event to identify group, we found comparable sensitivity and negative predictive value, but greater specificity and positive predictive value of spike ripples compared to spikes (P = 0.016 and P = 0.006, respectively). We found qualitatively consistent results using a fully automated spike ripple detector, including comparison with an automated spike detector. We conclude that scalp spike ripple events identify disease and track with seizure risk in this epilepsy population, using both semi-automated and fully automated detection methods, and that this biomarker outperforms analysis of spikes alone in categorizing seizure risk. These data provide evidence that spike ripples are a specific non-invasive biomarker for seizure risk in benign epilepsy with centrotemporal spikes and support future work to evaluate the utility of this biomarker to guide medication trials and tapers in these children and predict seizure risk in other at-risk populations.
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Affiliation(s)
- Mark A Kramer
- Boston University, Department of Mathematics and Statistics, Boston, MA, USA
| | - Lauren M Ostrowski
- Massachusetts General Hospital, Department of Neurology, Boston, MA, USA
| | - Daniel Y Song
- Massachusetts General Hospital, Department of Neurology, Boston, MA, USA
| | - Emily L Thorn
- Massachusetts General Hospital, Department of Neurology, Boston, MA, USA
| | - Sally M Stoyell
- Massachusetts General Hospital, Department of Neurology, Boston, MA, USA
| | - McKenna Parnes
- Massachusetts General Hospital, Department of Neurology, Boston, MA, USA
| | | | - Grace Xiao
- Massachusetts General Hospital, Department of Neurology, Boston, MA, USA
| | - Uri T Eden
- Boston University, Department of Mathematics and Statistics, Boston, MA, USA
| | - Kevin J Staley
- Massachusetts General Hospital, Department of Neurology, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Steven M Stufflebeam
- Harvard Medical School, Boston, MA, USA
- Massachusetts General Hospital, Department of Radiology, Boston, MA, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA
| | - Catherine J Chu
- Massachusetts General Hospital, Department of Neurology, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
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Song DY, Stoyell SM, Ross EE, Ostrowski LM, Thorn EL, Stufflebeam SM, Morgan AK, Emerton BC, Kramer MA, Chu CJ. Beta oscillations in the sensorimotor cortex correlate with disease and remission in benign epilepsy with centrotemporal spikes. Brain Behav 2019; 9:e01237. [PMID: 30790472 PMCID: PMC6422718 DOI: 10.1002/brb3.1237] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/02/2018] [Revised: 01/14/2019] [Accepted: 01/16/2019] [Indexed: 12/27/2022] Open
Abstract
INTRODUCTION Benign epilepsy with centrotemporal spikes (BECTS) is a common form of childhood epilepsy with the majority of those afflicted remitting during their early teenage years. Seizures arise from the lower half of the sensorimotor cortex of the brain (e.g. seizure onset zone) and the abnormal epileptiform discharges observed increase during NREM sleep. To date no clinical factors reliably predict disease course, making determination of ongoing seizure risk a significant challenge. Prior work in BECTS have shown abnormalities in beta band (14.9-30 Hz) oscillations during movement and rest. Oscillations in this frequency band are modulated by state of consciousness and thought to reflect intrinsic inhibitory mechanisms. METHODS We used high density EEG and source localization techniques to examine beta band activity in the seizure onset zone (sensorimotor cortex) in a prospective cohort of children with BECTS and healthy controls during sleep. We hypothesized that beta power in the sensorimotor cortex would be different between patients and healthy controls, and that beta abnormalities would improve with resolution of disease in this self-limited epilepsy syndrome. We further explored the specificity of our findings and correlation with clinical features. Statistical testing was performed using logistic and standard linear regression models. RESULTS We found that beta band power in the seizure onset zone is different between healthy controls and BECTS patients. We also found that a longer duration of time spent seizure-free (corresponding to disease remission) correlates with lower beta power in the seizure onset zone. Exploratory spatial analysis suggests this effect is not restricted to the sensorimotor cortex. Exploratory frequency analysis suggests that this phenomenon is also observed in alpha and gamma range activity. We found no relationship between beta power and the presence or rate of epileptiform discharges in the sensorimotor cortex or a test of sensorimotor performance. CONCLUSION These results provide evidence that cortical beta power in the seizure onset zone may provide a dynamic physiological biomarker of disease in BECTS.
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Affiliation(s)
- Dan Y Song
- Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts
| | - Sally M Stoyell
- Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts
| | - Erin E Ross
- Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts
| | - Lauren M Ostrowski
- Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts
| | - Emily L Thorn
- Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts
| | - Steven M Stufflebeam
- Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts.,Athinoula A. Martinos Center for Biomedical Imaging, Boston, Massachusetts.,Harvard Medical School, Boston, Massachusetts
| | - Amy K Morgan
- Psychological Assessment Center, Massachusetts General Hospital, Boston, Massachusetts
| | - Britt C Emerton
- Psychological Assessment Center, Massachusetts General Hospital, Boston, Massachusetts
| | - Mark A Kramer
- Department of Mathematics and Statistics, Boston University, Boston, Massachusetts
| | - Catherine J Chu
- Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts.,Harvard Medical School, Boston, Massachusetts
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11
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Lee S, Kim S, Choi JH. A Novel Visualization Method for Sleep Spindles Based on Source Localization of High Density EEG. Exp Neurobiol 2018; 26:362-368. [PMID: 29302203 PMCID: PMC5746501 DOI: 10.5607/en.2017.26.6.362] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2017] [Revised: 11/30/2017] [Accepted: 12/07/2017] [Indexed: 11/19/2022] Open
Abstract
Equivalent dipole source localization is a well-established approach to localizing the electrical activity in electroencephalogram (EEG). So far, source localization has been used primarily in localizing the epileptic source in human epileptic patients. Currently, source localization techniques have been applied to account for localizing epileptic source among the epileptic patients. Here, we present the first application of source localization in the field of sleep spindle in mouse brain. The spatial distribution of cortical potential was obtained by high density EEG and then the anterior and posterior sleep spindles were classified based on the K-mean clustering algorithm. To solve the forward problem, a realistic geometry brain model was produced based on boundary element method (BEM) using mouse MRI. Then, we applied four different source estimation algorithms (minimum norm, eLORETA, sLORETA, and LORETA) to estimate the spatial location of equivalent dipole source of sleep spindles. The estimated sources of anterior and posterior spindles were plotted in a cine-mode that revealed different topographic patterns of spindle propagation. The characterization of sleep spindles may be better be distinguished by our novel visualization method.
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Affiliation(s)
- Soohyun Lee
- Department of Physics, Pohang University of Science and Technology, Pohang 37673, Korea
| | - Seunghwan Kim
- Department of Physics, Pohang University of Science and Technology, Pohang 37673, Korea
| | - Jee Hyun Choi
- Center for Neuroscience, Korea Institute of Science and Technology, Seoul 02792, Korea
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12
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Routier L, Mahmoudzadeh M, Panzani M, Azizollahi H, Goudjil S, Kongolo G, Wallois F. Plasticity of neonatal neuronal networks in very premature infants: Source localization of temporal theta activity, the first endogenous neural biomarker, in temporoparietal areas. Hum Brain Mapp 2017; 38:2345-2358. [PMID: 28112458 DOI: 10.1002/hbm.23521] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2016] [Revised: 01/06/2017] [Accepted: 01/08/2017] [Indexed: 01/01/2023] Open
Abstract
Temporal theta slow-wave activity (TTA-SW) in premature infants is a specific signature of the early development of temporal networks, as it is observed at the turning point between non-sensory driven spontaneous local processing and cortical network functioning. The role in development and the precise location of TTA-SW remain unknown. Previous studies have demonstrated that preterms from 28 weeks of gestational age (wGA) are able to discriminate phonemes and voice, supporting the idea of a prior genetic structural or activity-dependent fingerprint that would prepare the auditory network to compute auditory information at the onset of thalamocortical connectivity. They recorded TTA-SW in 26-32 wGA preterms. The rate of TTA-SW in response to click stimuli was evaluated using low-density EEG in 30 preterms. The sources of TTA-SW were localized by high-density EEG using different tissues conductivities, head models and mathematical models. They observed that TTA-SW is not sensory driven. Regardless of age, conductivities, head models and mathematical models, sources of TTA-SW were located adjacent to auditory and temporal junction areas. These sources become situated closer to the surface during development. TTA-SW corresponds to spontaneous transient endogenous activities independent of sensory information at this period which might participate in the implementation of auditory, language, memory, attention and or social cognition convergent and does not simply represent a general interaction between the subplate and the cortical plate. Hum Brain Mapp 38:2345-2358, 2017. © 2017 Wiley Periodicals, Inc.
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Affiliation(s)
- L Routier
- Inserm U 1105, University of Picardie Instead of Picardy, Amiens University Hospital, Amiens, France.,Pediatric Nervous System Investigation Unit, Amiens University Hospital, Amiens, France
| | - M Mahmoudzadeh
- Inserm U 1105, University of Picardie Instead of Picardy, Amiens University Hospital, Amiens, France
| | - M Panzani
- Inserm U 1105, University of Picardie Instead of Picardy, Amiens University Hospital, Amiens, France
| | - H Azizollahi
- Inserm U 1105, University of Picardie Instead of Picardy, Amiens University Hospital, Amiens, France
| | - S Goudjil
- Inserm U 1105, University of Picardie Instead of Picardy, Amiens University Hospital, Amiens, France.,NICU Amiens University Hospital, Amiens, France
| | - G Kongolo
- Inserm U 1105, University of Picardie Instead of Picardy, Amiens University Hospital, Amiens, France.,NICU Amiens University Hospital, Amiens, France
| | - F Wallois
- Inserm U 1105, University of Picardie Instead of Picardy, Amiens University Hospital, Amiens, France.,Pediatric Nervous System Investigation Unit, Amiens University Hospital, Amiens, France
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13
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Kurth S, Dean DC, Achermann P, O'Muircheartaigh J, Huber R, Deoni SCL, LeBourgeois MK. Increased Sleep Depth in Developing Neural Networks: New Insights from Sleep Restriction in Children. Front Hum Neurosci 2016; 10:456. [PMID: 27708567 PMCID: PMC5030292 DOI: 10.3389/fnhum.2016.00456] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2016] [Accepted: 08/30/2016] [Indexed: 12/25/2022] Open
Abstract
Brain networks respond to sleep deprivation or restriction with increased sleep depth, which is quantified as slow-wave activity (SWA) in the sleep electroencephalogram (EEG). When adults are sleep deprived, this homeostatic response is most pronounced over prefrontal brain regions. However, it is unknown how children’s developing brain networks respond to acute sleep restriction, and whether this response is linked to myelination, an ongoing process in childhood that is critical for brain development and cortical integration. We implemented a bedtime delay protocol in 5- to 12-year-old children to obtain partial sleep restriction (1-night; 50% of their habitual sleep). High-density sleep EEG was assessed during habitual and restricted sleep and brain myelin content was obtained using mcDESPOT magnetic resonance imaging. The effect of sleep restriction was analyzed using statistical non-parametric mapping with supra-threshold cluster analysis. We observed a localized homeostatic SWA response following sleep restriction in a specific parieto-occipital region. The restricted/habitual SWA ratio was negatively associated with myelin water fraction in the optic radiation, a developing fiber bundle. This relationship occurred bilaterally over parieto-temporal areas and was adjacent to, but did not overlap with the parieto-occipital region showing the most pronounced homeostatic SWA response. These results provide evidence for increased sleep need in posterior neural networks in children. Sleep need in parieto-temporal areas is related to myelin content, yet it remains speculative whether age-related myelin growth drives the fading of the posterior homeostatic SWA response during the transition to adulthood. Whether chronic insufficient sleep in the sensitive period of early life alters the anatomical generators of deep sleep slow-waves is an important unanswered question.
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Affiliation(s)
- Salome Kurth
- Sleep and Development Laboratory, Department of Integrative Physiology, University of Colorado Boulder, BoulderCO, USA; Pulmonary Clinic, Division of Pulmonology, University Hospital ZurichZurich, Switzerland
| | - Douglas C Dean
- Advanced Baby Imaging Laboratory, School of Engineering, Brown University, ProvidenceRI, USA; Waisman Laboratory for Brain Imaging and Behavior, University of Wisconsin-Madison, MadisonWI, USA
| | - Peter Achermann
- Chronobiology and Sleep Research, Institute of Pharmacology and Toxicology, University of Zurich Zurich, Switzerland
| | - Jonathan O'Muircheartaigh
- Advanced Baby Imaging Laboratory, School of Engineering, Brown University, ProvidenceRI, USA; Centre for the Developing Brain, Division of Imaging Sciences & Biomedical Engineering, King's College LondonLondon, UK; Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College LondonLondon, UK
| | - Reto Huber
- Child Development Center, University Children's Hospital ZurichZurich, Switzerland; Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric Hospital University of ZurichZurich, Switzerland
| | - Sean C L Deoni
- Advanced Baby Imaging Laboratory, School of Engineering, Brown University, ProvidenceRI, USA; Children's Hospital Colorado, School of Medicine, University of Colorado, AuroraCO, USA
| | - Monique K LeBourgeois
- Sleep and Development Laboratory, Department of Integrative Physiology, University of Colorado Boulder, Boulder CO, USA
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14
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Colombo MA, Ramautar JR, Wei Y, Gomez-Herrero G, Stoffers D, Wassing R, Benjamins JS, Tagliazucchi E, van der Werf YD, Cajochen C, Van Someren EJ. Wake High-Density Electroencephalographic Spatiospectral Signatures of Insomnia. Sleep 2016; 39:1015-27. [PMID: 26951395 PMCID: PMC4835299 DOI: 10.5665/sleep.5744] [Citation(s) in RCA: 38] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2015] [Accepted: 12/23/2015] [Indexed: 01/20/2023] Open
Abstract
STUDY OBJECTIVES Although daytime complaints are a defining characteristic of insomnia, most EEG studies evaluated sleep only. We used high-density electroencephalography to investigate wake resting state oscillations characteristic of insomnia disorder (ID) at a fine-grained spatiospectral resolution. METHODS A case-control assessment during eyes open (EO) and eyes closed (EC) was performed in a laboratory for human physiology. Participants (n = 94, 74 female, 21-70 y) were recruited through www.sleepregistry.nl: 51 with ID, according to DSM-5 and 43 matched controls. Exclusion criteria were any somatic, neurological or psychiatric condition. Group differences in the spectral power topographies across multiple frequencies (1.5 to 40 Hz) were evaluated using permutation-based inference with Threshold-Free Cluster-Enhancement, to correct for multiple comparisons. RESULTS As compared to controls, participants with ID showed less power in a narrow upper alpha band (11-12.7 Hz, peak: 11.7 Hz) over bilateral frontal and left temporal regions during EO, and more power in a broad beta frequency range (16.3-40 Hz, peak: 19 Hz) globally during EC. Source estimates suggested global rather than cortically localized group differences. CONCLUSIONS The widespread high power in a broad beta band reported previously during sleep in insomnia is present as well during eyes closed wakefulness, suggestive of a round-the-clock hyperarousal. Low power in the upper alpha band during eyes open is consistent with low cortical inhibition and attentional filtering. The fine-grained HD-EEG findings suggest that, while more feasible than PSG, wake EEG of short duration with a few well-chosen electrodes and frequency bands, can provide valuable features of insomnia.
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Affiliation(s)
- Michele A. Colombo
- Department of Sleep and Cognition, Netherlands Institute for Neuroscience (NIN), an institute of the Royal Netherlands Academy of Arts and Sciences, Amsterdam, the Netherlands
- Faculty of Biology, and Bernstein Center Freiburg, University of Freiburg, Freiburg, Germany
- Centre for Chronobiology, Psychiatric Hospital of the University of Basel (UPK), Basel, Switzerland
| | - Jennifer R. Ramautar
- Department of Sleep and Cognition, Netherlands Institute for Neuroscience (NIN), an institute of the Royal Netherlands Academy of Arts and Sciences, Amsterdam, the Netherlands
| | - Yishul Wei
- Department of Sleep and Cognition, Netherlands Institute for Neuroscience (NIN), an institute of the Royal Netherlands Academy of Arts and Sciences, Amsterdam, the Netherlands
| | - Germán Gomez-Herrero
- Department of Sleep and Cognition, Netherlands Institute for Neuroscience (NIN), an institute of the Royal Netherlands Academy of Arts and Sciences, Amsterdam, the Netherlands
| | - Diederick Stoffers
- Department of Sleep and Cognition, Netherlands Institute for Neuroscience (NIN), an institute of the Royal Netherlands Academy of Arts and Sciences, Amsterdam, the Netherlands
| | - Rick Wassing
- Department of Sleep and Cognition, Netherlands Institute for Neuroscience (NIN), an institute of the Royal Netherlands Academy of Arts and Sciences, Amsterdam, the Netherlands
| | - Jeroen S. Benjamins
- Department of Sleep and Cognition, Netherlands Institute for Neuroscience (NIN), an institute of the Royal Netherlands Academy of Arts and Sciences, Amsterdam, the Netherlands
- Department of Clinical and Health Psychology, Department of Experimental Psychology, Utrecht University, Utrecht, The Netherlands
| | - Enzo Tagliazucchi
- Department of Sleep and Cognition, Netherlands Institute for Neuroscience (NIN), an institute of the Royal Netherlands Academy of Arts and Sciences, Amsterdam, the Netherlands
| | - Ysbrand D. van der Werf
- Department of Sleep and Cognition, Netherlands Institute for Neuroscience (NIN), an institute of the Royal Netherlands Academy of Arts and Sciences, Amsterdam, the Netherlands
- Department of Anatomy and Neurosciences, VU University Medical Center, Amsterdam, the Netherlands
| | - Christian Cajochen
- Centre for Chronobiology, Psychiatric Hospital of the University of Basel (UPK), Basel, Switzerland
| | - Eus J.W. Van Someren
- Department of Sleep and Cognition, Netherlands Institute for Neuroscience (NIN), an institute of the Royal Netherlands Academy of Arts and Sciences, Amsterdam, the Netherlands
- Departments of Integrative Neurophysiology and Psychiatry, Center for Neurogenomics and Cognitive Research (CNCR), Neuroscience Campus Amsterdam, VU University and Medical Center, Amsterdam, the Netherlands
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15
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Doucette MR, Kurth S, Chevalier N, Munakata Y, LeBourgeois MK. Topography of Slow Sigma Power during Sleep is Associated with Processing Speed in Preschool Children. Brain Sci 2015; 5:494-508. [PMID: 26556377 DOI: 10.3390/brainsci5040494] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2015] [Revised: 10/23/2015] [Accepted: 10/29/2015] [Indexed: 12/04/2022] Open
Abstract
Cognitive development is influenced by maturational changes in processing speed, a construct reflecting the rapidity of executing cognitive operations. Although cognitive ability and processing speed are linked to spindles and sigma power in the sleep electroencephalogram (EEG), little is known about such associations in early childhood, a time of major neuronal refinement. We calculated EEG power for slow (10–13 Hz) and fast (13.25–17 Hz) sigma power from all-night high-density electroencephalography (EEG) in a cross-sectional sample of healthy preschool children (n = 10, 4.3 ± 1.0 years). Processing speed was assessed as simple reaction time. On average, reaction time was 1409 ± 251 ms; slow sigma power was 4.0 ± 1.5 μV2; and fast sigma power was 0.9 ± 0.2 μV2. Both slow and fast sigma power predominated over central areas. Only slow sigma power was correlated with processing speed in a large parietal electrode cluster (p < 0.05, r ranging from −0.6 to −0.8), such that greater power predicted faster reaction time. Our findings indicate regional correlates between sigma power and processing speed that are specific to early childhood and provide novel insights into the neurobiological features of the EEG that may underlie developing cognitive abilities.
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16
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Henz S, Kutz DF, Werner J, Hürster W, Kolb FP, Nida-Ruemelin J. Stimulus-dependent deliberation process leading to a specific motor action demonstrated via a multi-channel EEG analysis. Front Hum Neurosci 2015; 9:355. [PMID: 26190987 PMCID: PMC4488757 DOI: 10.3389/fnhum.2015.00355] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2015] [Accepted: 06/02/2015] [Indexed: 11/13/2022] Open
Abstract
The aim of the study was to determine whether a deliberative process, leading to a motor action, is detectable in high density EEG recordings. Subjects were required to press one of two buttons. In a simple motor task the subject knew which button to press, whilst in a color-word Stroop task subjects had to press the right button with the right index finger when meaning and color coincided, or the left button with the left index finger when meaning and color were disparate. EEG recordings obtained during the simple motor task showed a sequence of positive (P) and negative (N) cortical potentials (P1-N1-P2) which are assumed to be related to the processing of the movement. The sequence of cortical potentials was similar in EEG recordings of subjects having to deliberate over how to respond, but the above sequence (P1-N1-P2) was preceded by slowly increasing negativity (N0), with N0 being assumed to represent the end of the deliberation process. Our data suggest the existence of neurophysiological correlates of deliberative processes.
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Affiliation(s)
- Sonja Henz
- Department of Physiological Genomics, Motor Research, Institute of Physiology, Ludwig-Maximilians-University of Munich Munich, Germany
| | - Dieter F Kutz
- Department of Physiological Genomics, Motor Research, Institute of Physiology, Ludwig-Maximilians-University of Munich Munich, Germany
| | - Jana Werner
- Department of Physiological Genomics, Motor Research, Institute of Physiology, Ludwig-Maximilians-University of Munich Munich, Germany
| | | | - Florian P Kolb
- Department of Physiological Genomics, Motor Research, Institute of Physiology, Ludwig-Maximilians-University of Munich Munich, Germany
| | - Julian Nida-Ruemelin
- Department of Philosophy IV, Ludwig-Maximilians-University of Munich Munich, Germany
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Lustenberger C, Huber R. High density electroencephalography in sleep research: potential, problems, future perspective. Front Neurol 2012; 3:77. [PMID: 22593753 PMCID: PMC3350944 DOI: 10.3389/fneur.2012.00077] [Citation(s) in RCA: 39] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2012] [Accepted: 04/20/2012] [Indexed: 12/30/2022] Open
Abstract
High density EEG (hdEEG) during sleep combines the superior temporal resolution of EEG recordings with high spatial resolution. Thus, this method allows a topographical analysis of sleep EEG activity and thereby fosters the shift from a global view of sleep to a local one. HdEEG allowed to investigate sleep rhythms in terms of their characteristic behavior (e.g., the traveling of slow waves) and in terms of their relationship to cortical functioning (e.g., consciousness and cognitive abilities). Moreover, recent studies successfully demonstrated that hdEEG can be used to study brain functioning in neurological and neuro-developmental disorders, and to evaluate therapeutic approaches. This review highlights the potential, the problems, and future perspective of hdEEG in sleep research.
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