1
|
Spontaneity matters! Network alterations before and after spontaneous and active facial self-touches: An EEG functional connectivity study. Int J Psychophysiol 2023; 184:28-38. [PMID: 36563880 DOI: 10.1016/j.ijpsycho.2022.12.004] [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: 09/19/2022] [Revised: 12/07/2022] [Accepted: 12/09/2022] [Indexed: 12/24/2022]
Abstract
BACKGROUND Despite humans frequently performing spontaneous facial self-touches (sFST), the function of this behavior remains speculative. sFST have been discussed in the context of self-regulation, emotional homeostasis, working memory processes, and attention focus. First evidence indicates that sFST and active facial self-touches (aFST) are neurobiologically different phenomena. The aim of the present analysis was to examine EEG-based connectivity in the course of sFST and aFST to test the hypotheses that sFST affect brain network interactions relevant for other than sensorimotor processes. METHODS To trigger spontaneous FST a previously successful setting was used: 60 healthy participants manually explored two haptic stimuli and held the shapes of the stimuli in memory for a 14 min retention interval. Afterwards the shapes were drawn on a sheet of paper. During the retention interval, artifact-free EEG-data of 97 sFST by 32 participants were recorded. At the end of the experiment, the participants performed aFST with both hands successively. For the EEG-data, connectivity was computed and compared between the phases before and after sFST and aFST and between the respective before-and the after-phases. RESULTS For the before-after comparison, brainwide distributed significant connectivity differences (p < .00079) were observed for sFST, but not for aFST. Additionally, comparing the before- and after-phases of sFST and aFST, respectively, revealed increased similarity between the after-phases than between the before-phases. CONCLUSION The results support the assumption that sFST and aFST are neurobiologically different phenomena. Furthermore, the aligned network properties of the after-phases compared to the before-phases indicate that sFST serve self-regulatory functions that aFST do not serve.
Collapse
|
2
|
Smith EE, Bel-Bahar TS, Kayser J. A systematic data-driven approach to analyze sensor-level EEG connectivity: Identifying robust phase-synchronized network components using surface Laplacian with spectral-spatial PCA. Psychophysiology 2022; 59:e14080. [PMID: 35478408 PMCID: PMC9427703 DOI: 10.1111/psyp.14080] [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: 08/10/2021] [Revised: 04/04/2022] [Accepted: 04/07/2022] [Indexed: 11/27/2022]
Abstract
Although conventional averaging across predefined frequency bands reduces the complexity of EEG functional connectivity (FC), it obscures the identification of resting-state brain networks (RSN) and impedes accurate estimation of FC reliability. Extending prior work, we combined scalp current source density (CSD; spherical spline surface Laplacian) and spectral-spatial PCA to identify FC components. Phase-based FC was estimated via debiased-weighted phase-locking index from CSD-transformed resting EEGs (71 sensors, 8 min, eyes open/closed, 35 healthy adults, 1-week retest). Spectral PCA extracted six robust alpha and theta components (86.6% variance). Subsequent spatial PCA for each spectral component revealed seven robust regionally focused (posterior, central, and frontal) and long-range (posterior-anterior) alpha components (peaks at 8, 10, and 13 Hz) and a midfrontal theta (6 Hz) component, accounting for 37.0% of FC variance. These spatial FC components were consistent with well-known networks (e.g., default mode, visual, and sensorimotor), and four were sensitive to eyes open/closed conditions. Most FC components had good-to-excellent internal consistency (odd/even epochs, eyes open/closed) and test-retest reliability (ICCs ≥ .8). Moreover, the FC component structure was generally present in subsamples (session × odd/even epoch, or smaller subgroups [n = 7-10]), as indicated by high similarity of component loadings across PCA solutions. Apart from systematically reducing FC dimensionality, our approach avoids arbitrary thresholds and allows quantification of meaningful and reliable network components that may prove to be of high relevance for basic and clinical research applications.
Collapse
Affiliation(s)
- Ezra E. Smith
- Division of Translational Epidemiology, New York State Psychiatric Institute, New York, NY, USA
| | - Tarik S. Bel-Bahar
- Division of Translational Epidemiology, New York State Psychiatric Institute, New York, NY, USA
| | - Jürgen Kayser
- Division of Translational Epidemiology, New York State Psychiatric Institute, New York, NY, USA
- Department of Psychiatry, Vagelos College of Physicians & Surgeons, Columbia University, New York, NY, USA
| |
Collapse
|
3
|
Functional connectivity using high density EEG shows competitive reliability and agreement across test/retest sessions. J Neurosci Methods 2022; 367:109424. [PMID: 34826504 DOI: 10.1016/j.jneumeth.2021.109424] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2021] [Revised: 10/26/2021] [Accepted: 11/18/2021] [Indexed: 11/24/2022]
Abstract
BACKGROUND Electrophysiological resting state functional connectivity using high density electroencephalography (hdEEG) is gaining momentum. The increased resolution offered by hdEEG, usually either 128 or 256 channels, permits source localization of EEG signals on the cortical surface. However, the number of methodological options for the acquisition and analysis of resting state hdEEG is extremely large. These include acquisition duration, eyes open/closed, channel density, source localization methods, and functional connectivity metric. NEW METHODS We undertake an extensive examination of the test-retest reliability and methodological agreement of all these options for regional measures of functional connectivity. RESULTS Power envelope connectivity shows larger test-retest reliability than imaginary coherence across all bands. While channel density doesn't strongly impact reliability or agreement, source localization methods produce systematically different functional connectivity, highlighting an important obstacle for replicating results in the literature. Most importantly, reliability and agreement often plateaus at or after 6 minutes of acquisition, well beyond the typical duration of 3 minutes. Finally, our study demonstrates that resting EEG can be as or more reliable than resting fMRI acquired in the same individuals. CONCLUSIONS The competitive reliability and agreement of power envelope connectivity greatly increases our confidence in measuring resting state connectivity using EEG and its capacity to find individual differences.
Collapse
|
4
|
Wang J, Chen T, Jiao X, Liu K, Tong S, Sun J. Test-retest reliability of duration-related and frequency-related mismatch negativity. Neurophysiol Clin 2021; 51:541-548. [PMID: 34750039 DOI: 10.1016/j.neucli.2021.10.004] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Revised: 10/22/2021] [Accepted: 10/22/2021] [Indexed: 10/19/2022] Open
Abstract
OBJECTIVES -Mismatch negativity (MMN) has been demonstrated as a potential biomarker for pre-attentive processing and prognosis in patients with psychosis. However, previous studies mainly evaluated the reliability of MMN across only two repeated sessions, which is inadequate to draw a convincing conclusion. The current study aimed to assess multi-session test-retest reliability in duration-related MMN (dMMN) and frequency-related MMN (fMMN). METHODS -We recorded four repeated sessions of electroencephalography (EEG) from 16 healthy participants in an oddball task. MMNs were extracted and their reliability was evaluated by intra-class coefficient (ICC). We also analyzed the correlation between fMMN and dMMN. RESULTS -Both dMMN and fMMN amplitudes exhibited good test-retest reliability, and fMMN had better reliability (average ICC = 0.7279) than dMMN (average ICC = 0.6974). Moreover, dMMN and fMMN showed more than moderate linear correlation in amplitudes (r = 0.598, CI: [0.100, 0.857]). CONCLUSION -Both the duration- and frequency-related MMN amplitudes were highly reliable across four-session experiments. These results provide further evidence for the potential utility of MMNs as biomarkers in research into brain function, and prognosis in psychotic illness.
Collapse
Affiliation(s)
- Jingyi Wang
- Shanghai Med-X Engineering Research Center, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200030, China
| | - Tingting Chen
- Shanghai Med-X Engineering Research Center, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200030, China
| | - Xiong Jiao
- Shanghai Med-X Engineering Research Center, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200030, China; Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Kai Liu
- Shanghai Med-X Engineering Research Center, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200030, China
| | - Shanbao Tong
- Shanghai Med-X Engineering Research Center, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200030, China; Brain Science and Technology Research Center, Shanghai Jiao Tong University, Shanghai, China
| | - Junfeng Sun
- Shanghai Med-X Engineering Research Center, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200030, China; Brain Science and Technology Research Center, Shanghai Jiao Tong University, Shanghai, China.
| |
Collapse
|
5
|
Thomschewski A, Trinka E, Jacobs J. Temporo-Frontal Coherences and High-Frequency iEEG Responses during Spatial Navigation in Patients with Drug-Resistant Epilepsy. Brain Sci 2021; 11:brainsci11020162. [PMID: 33530531 PMCID: PMC7911024 DOI: 10.3390/brainsci11020162] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2020] [Revised: 01/19/2021] [Accepted: 01/24/2021] [Indexed: 11/16/2022] Open
Abstract
The prefrontal cortex and hippocampus function in tight coordination during multiple cognitive processes. During spatial navigation, prefrontal neurons are linked to hippocampal theta oscillations, presumably in order to enhance communication. Hippocampal ripples have been suggested to reflect spatial memory processes. Whether prefrontal-hippocampal-interaction also takes place within the ripple band is unknown. This intracranial EEG study aimed to investigate whether ripple band coherences can also be used to show this communication. Twelve patients with epilepsy and intracranial EEG evaluation completed a virtual spatial navigation task. We calculated ordinary coherence between prefrontal and temporal electrodes during retrieval, re-encoding, and pre-task rest. Coherences were compared between the conditions via permutation testing. Additionally, ripples events were automatically detected and changes in occurrence rates were investigated excluding ripples on epileptic spikes. Ripple-band coherences yielded no general effect of the task on coherences across all patients. Furthermore, we did not find significant effects of task conditions on ripple rates. Subsequent analyses pointed to rather short periods of synchrony as opposed to general task-related changes in ripple-band coherence. Specifically designed tasks and adopted measures might be necessary in order to map these interactions in future studies.
Collapse
Affiliation(s)
- Aljoscha Thomschewski
- Affiliated Centre of the European Reference Network EpiCARE, Department of Neurology and Centre for Cognitive Neuroscience, Christian-Doppler Medical Centre, Paracelsus Medical University, Ignaz-Harrer-Str. 79, 5020 Salzburg, Austria;
- Department of Psychology, Paris-Lodron University of Salzburg, Hellbrunnerstraße 34, 5020 Salzburg, Austria
- Correspondence:
| | - Eugen Trinka
- Affiliated Centre of the European Reference Network EpiCARE, Department of Neurology and Centre for Cognitive Neuroscience, Christian-Doppler Medical Centre, Paracelsus Medical University, Ignaz-Harrer-Str. 79, 5020 Salzburg, Austria;
| | - Julia Jacobs
- Member of the European Reference Network EpiCARE, Epilepsy Center, Medical Center, Faculty of Medicine, University of Freiburg, Breisacher Straße 64, 79106 Freiburg, Germany;
- Department of Neuropediatrics and Muscle Disorders, University Hospital Freiburg, Mathildenstraße 1, 79106 Freiburg, Germany
- Room 293, Alberta Children’s Hospital Research Institute and Hotchkiss Brain Institute, University of Calgary, Heritage Medical Research Building, 3330 Hospital Dr. NW, Calgary, AB T2N 4N1, Canada
| |
Collapse
|
6
|
Höller Y, Nardone R. Quantitative EEG biomarkers for epilepsy and their relation to chemical biomarkers. Adv Clin Chem 2020; 102:271-336. [PMID: 34044912 DOI: 10.1016/bs.acc.2020.08.004] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
The electroencephalogram (EEG) is the most important method to diagnose epilepsy. In clinical settings, it is evaluated by experts who identify patterns visually. Quantitative EEG is the application of digital signal processing to clinical recordings in order to automatize diagnostic procedures, and to make patterns visible that are hidden to the human eye. The EEG is related to chemical biomarkers, as electrical activity is based on chemical signals. The most well-known chemical biomarkers are blood laboratory tests to identify seizures after they have happened. However, research on chemical biomarkers is much less extensive than research on quantitative EEG, and combined studies are rarely published, but highly warranted. Quantitative EEG is as old as the EEG itself, but still, the methods are not yet standard in clinical practice. The most evident application is an automation of manual work, but also a quantitative description and localization of interictal epileptiform events as well as seizures can reveal important hints for diagnosis and contribute to presurgical evaluation. In addition, the assessment of network characteristics and entropy measures were found to reveal important insights into epileptic brain activity. Application scenarios of quantitative EEG in epilepsy include seizure prediction, pharmaco-EEG, treatment monitoring, evaluation of cognition, and neurofeedback. The main challenges to quantitative EEG are poor reliability and poor generalizability of measures, as well as the need for individualization of procedures. A main hindrance for quantitative EEG to enter clinical routine is also that training is not yet part of standard curricula for clinical neurophysiologists.
Collapse
Affiliation(s)
- Yvonne Höller
- Faculty of Psychology, University of Akureyri, Akureyri, Iceland.
| | - Raffaele Nardone
- Department of Neurology, Franz Tappeiner Hospital, Merano, Italy; Spinal Cord Injury and Tissue Regeneration Center, Salzburg, Austria; Department of Neurology, Christian Doppler Klinik, Paracelsus Medical University, Salzburg, Austria
| |
Collapse
|
7
|
Marquetand J, Vannoni S, Carboni M, Li Hegner Y, Stier C, Braun C, Focke NK. Reliability of Magnetoencephalography and High-Density Electroencephalography Resting-State Functional Connectivity Metrics. Brain Connect 2019; 9:539-553. [PMID: 31115272 DOI: 10.1089/brain.2019.0662] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
Resting-state connectivity, for example, based on magnetoencephalography (MEG) or electroencephalography (EEG), is a widely used method for characterizing brain networks and a promising imaging biomarker. However, there is no established standard as to which method, modality, and analysis variant is preferable and there is only limited knowledge on the reproducibility, an important prerequisite for clinical application. We conducted an MEG-/high-density (hd)-EEG-study on 22 young healthy adults, who were measured twice in a scan/rescan design after 7 ± 2 days. Reliability of resting-state (15 min, eyes-closed) connectivity in source space was calculated via intraclass correlation coefficient (ICC) in classical frequency bands (delta-gamma). We investigated the reliability of two commonly used connectivity metrics, namely the imaginary part of coherency and the weighted phase-lag index and the influence of frequency band, vigilance, and the number of trials. We found a strong increase of reliability with more trials and relatively mild effects of vigilance. Reliability was excellent in the alpha band for MEG, as well as hd-EEG (ICC >0.85); in the theta band, reliability was good for MEG and poor for EEG. Other frequency bands showed lower reliability, with delta band being the worst. Furthermore, we investigated the spatial reliability of resting-state connectivity in a vertex-based approach, which reached fair to good reliability (ICC up to 0.67) with 5 min of data. Our results indicate that excellent reliability of global connectivity is achievable in alpha band, and vertex-based connectivity was still fair to good. Moreover, electrophysiological resting-state studies could benefit from more data than used previously. MEG and hd-EEG were similar in their overall performance but showed frequency band-specific differences.
Collapse
Affiliation(s)
- Justus Marquetand
- Department of Epileptology, Hertie-Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
| | - Silvia Vannoni
- Department of Epileptology, Hertie-Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany.,MEG-Center, University of Tübingen, Tübingen, Germany.,Section of Movement Disorders and Neurostimulation, Department of Neurology, Focus Program Translational Neurosciences (FTN), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Margherita Carboni
- EEG and Epilepsy, Neuroscience Department, University Hospital and Faculty of Medicine of Geneva, Geneva, Switzerland.,Functional Brain Mapping Lab, Department of Fundamental Neurosciences, University of Geneva, Geneva, Switzerland
| | - Yiwen Li Hegner
- Department of Epileptology, Hertie-Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany.,MEG-Center, University of Tübingen, Tübingen, Germany
| | - Christina Stier
- Department of Epileptology, Hertie-Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany.,Clinical Neurophysiology, Georg-August University Göttingen, Göttingen, Germany
| | | | - Niels K Focke
- Department of Epileptology, Hertie-Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany.,Clinical Neurophysiology, Georg-August University Göttingen, Göttingen, Germany
| |
Collapse
|
8
|
Yokochi F, Kato K, Iwamuro H, Kamiyama T, Kimura K, Yugeta A, Okiyama R, Taniguchi M, Kumada S, Ushiba J. Resting-State Pallidal-Cortical Oscillatory Couplings in Patients With Predominant Phasic and Tonic Dystonia. Front Neurol 2018; 9:375. [PMID: 29904367 PMCID: PMC5990626 DOI: 10.3389/fneur.2018.00375] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2018] [Accepted: 05/08/2018] [Indexed: 11/13/2022] Open
Abstract
Pallidal deep brain stimulation (DBS) improves the symptoms of dystonia. The improvement processes of dystonic movements (phasic symptoms) and tonic symptoms differ. Phasic symptoms improve rapidly after starting DBS treatment, but tonic symptoms improve gradually. This difference implies distinct neuronal mechanisms for phasic and tonic symptoms in the underlying cortico-basal ganglia neuronal network. Phasic symptoms are related to the pallido-thalamo-cortical pathway. The pathway related to tonic symptoms has been assumed to be different from that for phasic symptoms. In the present study, local field potentials of the globus pallidus internus (GPi) and globus pallidus externus (GPe) and electroencephalograms from the motor cortex (MCx) were recorded in 19 dystonia patients to analyze the differences between the two types of symptoms. The 19 patients were divided into two groups, 10 with predominant phasic symptoms (phasic patients) and 9 with predominant tonic symptoms (tonic patients). To investigate the distinct features of oscillations and functional couplings across the GPi, GPe, and MCx by clinical phenotype, power and coherence were calculated over the delta (2-4 Hz), theta (5-7 Hz), alpha (8-13 Hz), and beta (14-35 Hz) frequencies. In phasic patients, the alpha spectral peaks emerged in the GPi oscillatory activities, and alpha GPi coherence with the GPe and MCx was higher than in tonic patients. On the other hand, delta GPi oscillatory activities were prominent, and delta GPi-GPe coherence was significantly higher in tonic than in phasic patients. However, there was no significant delta coherence between the GPi/GPe and MCx in tonic patients. These results suggest that different pathophysiological cortico-pallidal oscillations are related to tonic and phasic symptoms.
Collapse
Affiliation(s)
- Fusako Yokochi
- Department of Neurology, Tokyo Metropolitan Neurological Hospital, Tokyo, Japan
| | - Kenji Kato
- Department of Neurology, Tokyo Metropolitan Neurological Hospital, Tokyo, Japan.,Department of Biosciences and Informatics, Faculty of Science and Technology, Keio University, Kanagawa, Japan
| | - Hirokazu Iwamuro
- Department of Neurosurgery, Tokyo Metropolitan Neurological Hospital, Tokyo, Japan
| | - Tsutomu Kamiyama
- Department of Neurology, Tokyo Metropolitan Neurological Hospital, Tokyo, Japan
| | - Katsuo Kimura
- Department of Neurology, Tokyo Metropolitan Neurological Hospital, Tokyo, Japan
| | - Akihiro Yugeta
- Department of Neurology, Tokyo Metropolitan Neurological Hospital, Tokyo, Japan
| | - Ryoichi Okiyama
- Department of Neurology, Tokyo Metropolitan Neurological Hospital, Tokyo, Japan
| | - Makoto Taniguchi
- Department of Neurosurgery, Tokyo Metropolitan Neurological Hospital, Tokyo, Japan
| | - Satoko Kumada
- Department of Pediatric Neurology, Tokyo Metropolitan Neurological Hospital, Tokyo, Japan
| | - Junichi Ushiba
- Department of Biosciences and Informatics, Faculty of Science and Technology, Keio University, Kanagawa, Japan
| |
Collapse
|
9
|
Fraschini M, Lai M, Demuru M, Puligheddu M, Floris G, Borghero G, Marrosu F. Functional brain connectivity analysis in amyotrophic lateral sclerosis: an EEG source-space study. Biomed Phys Eng Express 2018. [DOI: 10.1088/2057-1976/aa9c64] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/29/2023]
|
10
|
Abstract
Pharmaco-electroencephalography (pharmaco-EEG) has never gained great popularity in epilepsy research. Nevertheless, the electroencephalogram (EEG) is the most important neurological examination technique in this patient population. Development and investigation of antiepileptic drugs (AEDs) involves EEG for diagnosis and outcome evaluation. In contrast to the common use of the EEG for documenting the effect of AEDs on the presence of interictal epileptiform activities or seizures, quantitative analysis of drug responses in the EEG are not yet standard in pharmacological studies. We provide an overview of dedicated pharmaco-EEG studies with AEDs in humans. A systematic search in PubMed yielded 43 articles, which were reviewed for their relevance. After excluding studies according to our exclusion criteria, nine studies remained. These studies plus the retrieved references from the bibliographies of the identified studies yielded 37 studies to be included in the review. The most prominent method in pharmaco-EEG research for AEDs was analysis of the frequency content in response to drug intake, often with quantitative methods such as spectral analysis. Despite documenting the effect of the drug on brain activity, some studies were conducted in order to document treatment response, detect neurotoxic effects, and measure reversibility of AED-induced changes. There were some attempts to predict treatment response or side effects. We suggest that pharmaco-EEG deserves more attention in AED research, specifically because the newest drugs and techniques have not yet been subject to investigation.
Collapse
Affiliation(s)
- Yvonne Höller
- Department of Neurology, Christian Doppler Medical Centre and Centre for Cognitive Neuroscience, Paracelsus Medical University, Ignaz Harrer Str. 79, 5020, Salzburg, Austria. .,Department of Psychology, University of Akureyri, Norðurslóð 2, 600, Akureyri, Iceland.
| | - Christoph Helmstaedter
- 0000 0001 2240 3300grid.10388.32Department of Epileptology, University of Bonn, Sigmund Freud Straße 25, 53105 Bonn, Germany
| | - Klaus Lehnertz
- 0000 0001 2240 3300grid.10388.32Department of Epileptology, University of Bonn, Sigmund Freud Straße 25, 53105 Bonn, Germany ,0000 0001 2240 3300grid.10388.32Interdisciplinary Center for Complex Systems, University of Bonn, Brühler Straße 7, 53175 Bonn, Germany
| |
Collapse
|
11
|
Höller Y, Uhl A, Bathke A, Thomschewski A, Butz K, Nardone R, Fell J, Trinka E. Reliability of EEG Measures of Interaction: A Paradigm Shift Is Needed to Fight the Reproducibility Crisis. Front Hum Neurosci 2017; 11:441. [PMID: 28912704 PMCID: PMC5582168 DOI: 10.3389/fnhum.2017.00441] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2017] [Accepted: 08/16/2017] [Indexed: 12/04/2022] Open
Abstract
Measures of interaction (connectivity) of the EEG are at the forefront of current neuroscientific research. Unfortunately, test-retest reliability can be very low, depending on the measure and its estimation, the EEG-frequency of interest, the length of the signal, and the population under investigation. In addition, artifacts can hamper the continuity of the EEG signal, and in some clinical situations it is impractical to exclude artifacts. We aimed to examine factors that moderate test-retest reliability of measures of interaction. The study involved 40 patients with a range of neurological diseases and memory impairments (age median: 60; range 21–76; 40% female; 22 mild cognitive impairment, 5 subjective cognitive complaints, 13 temporal lobe epilepsy), and 20 healthy controls (age median: 61.5; range 23–74; 70% female). We calculated 14 measures of interaction based on the multivariate autoregressive model from two EEG-recordings separated by 2 weeks. We characterized test-retest reliability by correlating the measures between the two EEG-recordings for variations of data length, data discontinuity, artifact exclusion, model order, and frequency over all combinations of channels and all frequencies, individually for each subject, yielding a correlation coefficient for each participant. Excluding artifacts had strong effects on reliability of some measures, such as classical, real valued coherence (~0.1 before, ~0.9 after artifact exclusion). Full frequency directed transfer function was highly reliable and robust against artifacts. Variation of data length decreased reliability in relation to poor adjustment of model order and signal length. Variation of discontinuity had no effect, but reliabilities were different between model orders, frequency ranges, and patient groups depending on the measure. Pathology did not interact with variation of signal length or discontinuity. Our results emphasize the importance of documenting reliability, which may vary considerably between measures of interaction. We recommend careful selection of measures of interaction in accordance with the properties of the data. When only short data segments are available and when the signal length varies strongly across subjects after exclusion of artifacts, reliability becomes an issue. Finally, measures which show high reliability irrespective of the presence of artifacts could be extremely useful in clinical situations when exclusion of artifacts is impractical.
Collapse
Affiliation(s)
- Yvonne Höller
- Department of Neurology, Christian Doppler Medical Centre and Centre for Cognitive Neuroscience, Paracelsus Medical UniversitySalzburg, Austria
| | - Andreas Uhl
- Department of Computer Sciences, Paris Lodron UniversitySalzburg, Austria
| | - Arne Bathke
- Department of Mathematics, Paris Lodron UniversitySalzburg, Austria
| | - Aljoscha Thomschewski
- Department of Neurology, Christian Doppler Medical Centre and Centre for Cognitive Neuroscience, Paracelsus Medical UniversitySalzburg, Austria.,Spinal Cord Injury and Tissue Regeneration Center, Paracelsus Medical UniversitySalzburg, Austria
| | - Kevin Butz
- Department of Neurology, Christian Doppler Medical Centre and Centre for Cognitive Neuroscience, Paracelsus Medical UniversitySalzburg, Austria.,Spinal Cord Injury and Tissue Regeneration Center, Paracelsus Medical UniversitySalzburg, Austria
| | - Raffaele Nardone
- Department of Neurology, Christian Doppler Medical Centre and Centre for Cognitive Neuroscience, Paracelsus Medical UniversitySalzburg, Austria.,Spinal Cord Injury and Tissue Regeneration Center, Paracelsus Medical UniversitySalzburg, Austria.,Department of Neurology, Franz Tappeiner HospitalMerano, Italy
| | - Jürgen Fell
- Department of Epileptology, University of BonnBonn, Germany
| | - Eugen Trinka
- Department of Neurology, Christian Doppler Medical Centre and Centre for Cognitive Neuroscience, Paracelsus Medical UniversitySalzburg, Austria.,Spinal Cord Injury and Tissue Regeneration Center, Paracelsus Medical UniversitySalzburg, Austria
| |
Collapse
|