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Wennberg R, Tarazi A, Zumsteg D, Garcia Dominguez L. Electromagnetic evidence that benign epileptiform transients of sleep are traveling, rotating hippocampal spikes. Clin Neurophysiol 2020; 131:2915-2925. [DOI: 10.1016/j.clinph.2020.07.023] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2020] [Revised: 07/05/2020] [Accepted: 07/23/2020] [Indexed: 12/01/2022]
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Litvak V, Florin E, Tamás G, Groppa S, Muthuraman M. EEG and MEG primers for tracking DBS network effects. Neuroimage 2020; 224:117447. [PMID: 33059051 DOI: 10.1016/j.neuroimage.2020.117447] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2020] [Revised: 10/08/2020] [Accepted: 10/08/2020] [Indexed: 10/23/2022] Open
Abstract
Deep brain stimulation (DBS) is an effective treatment method for a range of neurological and psychiatric disorders. It involves implantation of stimulating electrodes in a precisely guided fashion into subcortical structures and, at a later stage, chronic stimulation of these structures with an implantable pulse generator. While the DBS surgery makes it possible to both record brain activity and stimulate parts of the brain that are difficult to reach with non-invasive techniques, electroencephalography (EEG) and magnetoencephalography (MEG) provide complementary information from other brain areas, which can be used to characterize brain networks targeted through DBS. This requires, however, the careful consideration of different types of artifacts in the data acquisition and the subsequent analyses. Here, we review both the technical issues associated with EEG/MEG recordings in DBS patients and the experimental findings to date. One major line of research is simultaneous recording of local field potentials (LFPs) from DBS targets and EEG/MEG. These studies revealed a set of cortico-subcortical coherent networks functioning at distinguishable physiological frequencies. Specific network responses were linked to clinical state, task or stimulation parameters. Another experimental approach is mapping of DBS-targeted networks in chronically implanted patients by recording EEG/MEG responses during stimulation. One can track responses evoked by single stimulation pulses or bursts as well as brain state shifts caused by DBS. These studies have the potential to provide biomarkers for network responses that can be adapted to guide stereotactic implantation or optimization of stimulation parameters. This is especially important for diseases where the clinical effect of DBS is delayed or develops slowly over time. The same biomarkers could also potentially be utilized for the online control of DBS network effects in the new generation of closed-loop stimulators that are currently entering clinical use. Through future studies, the use of network biomarkers may facilitate the integration of circuit physiology into clinical decision making.
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Affiliation(s)
- Vladimir Litvak
- The Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, London, UK
| | - Esther Florin
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich-Heine University Düsseldorf, Düsseldorf, Germany
| | - Gertrúd Tamás
- Department of Neurology, Semmelweis University, Budapest, Hungary
| | - Sergiu Groppa
- Movement disorders and Neurostimulation, Biomedical Statistics and Multimodal Signal Processing Unit, Department of Neurology, University Medical Center of the Johannes Gutenberg University, Langenbeckstrasse 1, 55131 Mainz, Germany
| | - Muthuraman Muthuraman
- Movement disorders and Neurostimulation, Biomedical Statistics and Multimodal Signal Processing Unit, Department of Neurology, University Medical Center of the Johannes Gutenberg University, Langenbeckstrasse 1, 55131 Mainz, Germany.
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53
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Bassez I, Ricci K, Vecchio E, Delussi M, Gentile E, Marinazzo D, de Tommaso M. The effect of painful laser stimuli on EEG gamma-band activity in migraine patients and healthy controls. Clin Neurophysiol 2020; 131:1755-1766. [DOI: 10.1016/j.clinph.2020.04.157] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2020] [Revised: 03/09/2020] [Accepted: 04/15/2020] [Indexed: 01/03/2023]
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Khosropanah P, Ho ETW, Lim KS, Fong SL, Thuy Le MA, Narayanan V. EEG Source Imaging (ESI) utility in clinical practice. BIOMED ENG-BIOMED TE 2020; 65:/j/bmte.ahead-of-print/bmt-2019-0128/bmt-2019-0128.xml. [PMID: 32623371 DOI: 10.1515/bmt-2019-0128] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2019] [Accepted: 02/21/2020] [Indexed: 11/15/2022]
Abstract
Epilepsy surgery is an important treatment modality for medically refractory focal epilepsy. The outcome of surgery usually depends on the localization accuracy of the epileptogenic zone (EZ) during pre-surgical evaluation. Good localization can be achieved with various electrophysiological and neuroimaging approaches. However, each approach has its own merits and limitations. Electroencephalography (EEG) Source Imaging (ESI) is an emerging model-based computational technique to localize cortical sources of electrical activity within the brain volume, three-dimensionally. ESI based pre-surgical evaluation gives an overall clinical yield of 73-91%, depending on choice of head model, inverse solution and EEG electrode density. It is a cost effective, non-invasive method which provides valuable additional information in presurgical evaluation due to its high localizing value specifically in MRI-negative cases, extra or basal temporal lobe epilepsy, multifocal lesions such as tuberous sclerosis or cases with multiple hypotheses. Unfortunately, less than 1% of surgical centers in developing countries use this method as a part of pre-surgical evaluation. This review promotes ESI as a useful clinical tool especially for patients with lesion-negative MRI to determine EZ cost-effectively with high accuracy under the optimized conditions.
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Affiliation(s)
- Pegah Khosropanah
- Division of Neurosurgery, Department of Surgery, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
- Division of Neurology, Department of Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
| | - Eric Tatt-Wei Ho
- Center for Intelligent Signal & Imaging Research, Universiti Teknologi PETRONAS, Seri Iskandar, Malaysia
- Department of Electrical & Electronics Engineering, Universiti Teknologi PETRONAS, Seri Iskandar, Malaysia
| | - Kheng-Seang Lim
- Division of Neurology, Department of Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
| | - Si-Lei Fong
- Division of Neurology, Department of Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
| | - Minh-An Thuy Le
- Division of Neurology, Department of Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
- Department of Neurology, Faculty of Medicine, University of Medicine and Pharmacy at Ho Chi Minh City, Ho Chi Minh City, Viet Nam
| | - Vairavan Narayanan
- Division of Neurosurgery, Department of Surgery, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
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55
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Masson R, Lévêque Y, Demarquay G, ElShafei H, Fornoni L, Lecaignard F, Morlet D, Bidet-Caulet A, Caclin A. Auditory attention alterations in migraine: A behavioral and MEG/EEG study. Clin Neurophysiol 2020; 131:1933-1946. [PMID: 32619799 DOI: 10.1016/j.clinph.2020.05.024] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2019] [Revised: 04/14/2020] [Accepted: 05/05/2020] [Indexed: 01/03/2023]
Abstract
OBJECTIVES To evaluate alterations of top-down and/or bottom-up attention in migraine and their cortical underpinnings. METHODS 19 migraineurs between attacks and 19 matched control participants performed a task evaluating jointly top-down and bottom-up attention, using visually-cued target sounds and unexpected task-irrelevant distracting sounds. Behavioral responses and magneto- and electro-encephalography signals were recorded. Event-related potentials and fields were processed and source reconstruction was applied to event-related fields. RESULTS At the behavioral level, neither top-down nor bottom-up attentional processes appeared to be altered in migraine. However, migraineurs presented heightened evoked responses following distracting sounds (orienting component of the N1 and Re-Orienting Negativity, RON) and following target sounds (orienting component of the N1), concomitant to an increased recruitment of the right temporo-parietal junction. They also displayed an increased effect of the cue informational value on target processing resulting in the elicitation of a negative difference (Nd). CONCLUSIONS Migraineurs appear to display increased bottom-up orienting response to all incoming sounds, and an enhanced recruitment of top-down attention. SIGNIFICANCE The interictal state in migraine is characterized by an exacerbation of the orienting response to attended and unattended sounds. These attentional alterations might participate to the peculiar vulnerability of the migraine brain to all incoming stimuli.
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Affiliation(s)
- Rémy Masson
- Lyon Neuroscience Research Center (CRNL), INSERM UMRS 1028, CNRS UMR 5292, Université Claude Bernard Lyon 1, Université de Lyon, Lyon, France.
| | - Yohana Lévêque
- Lyon Neuroscience Research Center (CRNL), INSERM UMRS 1028, CNRS UMR 5292, Université Claude Bernard Lyon 1, Université de Lyon, Lyon, France
| | - Geneviève Demarquay
- Lyon Neuroscience Research Center (CRNL), INSERM UMRS 1028, CNRS UMR 5292, Université Claude Bernard Lyon 1, Université de Lyon, Lyon, France; Neurological Hospital Pierre Wertheimer, Functional Neurology and Epilepsy Department, Hospices Civils de Lyon and Université Claude Bernard Lyon 1, Université de Lyon, Lyon, France
| | - Hesham ElShafei
- Lyon Neuroscience Research Center (CRNL), INSERM UMRS 1028, CNRS UMR 5292, Université Claude Bernard Lyon 1, Université de Lyon, Lyon, France
| | - Lesly Fornoni
- Lyon Neuroscience Research Center (CRNL), INSERM UMRS 1028, CNRS UMR 5292, Université Claude Bernard Lyon 1, Université de Lyon, Lyon, France
| | - Françoise Lecaignard
- Lyon Neuroscience Research Center (CRNL), INSERM UMRS 1028, CNRS UMR 5292, Université Claude Bernard Lyon 1, Université de Lyon, Lyon, France
| | - Dominique Morlet
- Lyon Neuroscience Research Center (CRNL), INSERM UMRS 1028, CNRS UMR 5292, Université Claude Bernard Lyon 1, Université de Lyon, Lyon, France
| | - Aurélie Bidet-Caulet
- Lyon Neuroscience Research Center (CRNL), INSERM UMRS 1028, CNRS UMR 5292, Université Claude Bernard Lyon 1, Université de Lyon, Lyon, France
| | - Anne Caclin
- Lyon Neuroscience Research Center (CRNL), INSERM UMRS 1028, CNRS UMR 5292, Université Claude Bernard Lyon 1, Université de Lyon, Lyon, France
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56
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Engemann DA, Kozynets O, Sabbagh D, Lemaître G, Varoquaux G, Liem F, Gramfort A. Combining magnetoencephalography with magnetic resonance imaging enhances learning of surrogate-biomarkers. eLife 2020; 9:e54055. [PMID: 32423528 PMCID: PMC7308092 DOI: 10.7554/elife.54055] [Citation(s) in RCA: 40] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2019] [Accepted: 05/09/2020] [Indexed: 12/14/2022] Open
Abstract
Electrophysiological methods, that is M/EEG, provide unique views into brain health. Yet, when building predictive models from brain data, it is often unclear how electrophysiology should be combined with other neuroimaging methods. Information can be redundant, useful common representations of multimodal data may not be obvious and multimodal data collection can be medically contraindicated, which reduces applicability. Here, we propose a multimodal model to robustly combine MEG, MRI and fMRI for prediction. We focus on age prediction as a surrogate biomarker in 674 subjects from the Cam-CAN dataset. Strikingly, MEG, fMRI and MRI showed additive effects supporting distinct brain-behavior associations. Moreover, the contribution of MEG was best explained by cortical power spectra between 8 and 30 Hz. Finally, we demonstrate that the model preserves benefits of stacking when some data is missing. The proposed framework, hence, enables multimodal learning for a wide range of biomarkers from diverse types of brain signals.
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Affiliation(s)
- Denis A Engemann
- Université Paris-Saclay, Inria, CEAPalaiseauFrance
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
| | | | - David Sabbagh
- Université Paris-Saclay, Inria, CEAPalaiseauFrance
- Inserm, UMRS-942, Paris Diderot UniversityParisFrance
- Department of Anaesthesiology and Critical Care, Lariboisière Hospital, Assistance Publique Hôpitaux de ParisParisFrance
| | | | | | - Franziskus Liem
- University Research Priority Program Dynamics of Healthy Aging, University of ZürichZürichSwitzerland
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57
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Previously Reward-Associated Stimuli Capture Spatial Attention in the Absence of Changes in the Corresponding Sensory Representations as Measured with MEG. J Neurosci 2020; 40:5033-5050. [PMID: 32366722 PMCID: PMC7314418 DOI: 10.1523/jneurosci.1172-19.2020] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2019] [Revised: 03/26/2020] [Accepted: 03/31/2020] [Indexed: 12/23/2022] Open
Abstract
Studies of selective attention typically consider the role of task goals or physical salience, but attention can also be captured by previously reward-associated stimuli, even if they are currently task irrelevant. One theory underlying this value-driven attentional capture (VDAC) is that reward-associated stimulus representations undergo plasticity in sensory cortex, thereby automatically capturing attention during early processing. To test this, we used magnetoencephalography to probe whether stimulus location and identity representations in sensory cortex are modulated by reward learning. We furthermore investigated the time course of these neural effects, and their relationship to behavioral VDAC. Male and female human participants first learned stimulus-reward associations. Next, we measured VDAC in a separate task by presenting these stimuli in the absence of reward contingency and probing their effects on the processing of separate target stimuli presented at different time lags. Using time-resolved multivariate pattern analysis, we found that learned value modulated the spatial selection of previously rewarded stimuli in posterior visual and parietal cortex from ∼260 ms after stimulus onset. This value modulation was related to the strength of participants' behavioral VDAC effect and persisted into subsequent target processing. Importantly, learned value did not influence cortical signatures of early processing (i.e., earlier than ∼200 ms); nor did it influence the decodability of stimulus identity. Our results suggest that VDAC is underpinned by learned value signals that modulate spatial selection throughout posterior visual and parietal cortex. We further suggest that VDAC can occur in the absence of changes in early visual processing in cortex.SIGNIFICANCE STATEMENT Attention is our ability to focus on relevant information at the expense of irrelevant information. It can be affected by previously learned but currently irrelevant stimulus-reward associations, a phenomenon termed "value-driven attentional capture" (VDAC). The neural mechanisms underlying VDAC remain unclear. It has been speculated that reward learning induces visual cortical plasticity, which modulates early visual processing to capture attention. Although we find that learned value modulates spatial signals in visual cortical areas, an effect that correlates with VDAC, we find no relevant signatures of changes in early visual processing in cortex.
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58
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Corsi MC, Chavez M, Schwartz D, George N, Hugueville L, Kahn AE, Dupont S, Bassett DS, De Vico Fallani F. Functional disconnection of associative cortical areas predicts performance during BCI training. Neuroimage 2020; 209:116500. [PMID: 31927130 PMCID: PMC7056534 DOI: 10.1016/j.neuroimage.2019.116500] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2019] [Revised: 12/13/2019] [Accepted: 12/25/2019] [Indexed: 11/21/2022] Open
Abstract
Brain-computer interfaces (BCIs) have been largely developed to allow communication, control, and neurofeedback in human beings. Despite their great potential, BCIs perform inconsistently across individuals and the neural processes that enable humans to achieve good control remain poorly understood. To address this question, we performed simultaneous high-density electroencephalographic (EEG) and magnetoencephalographic (MEG) recordings in a motor imagery-based BCI training involving a group of healthy subjects. After reconstructing the signals at the cortical level, we showed that the reinforcement of motor-related activity during the BCI skill acquisition is paralleled by a progressive disconnection of associative areas which were not directly targeted during the experiments. Notably, these network connectivity changes reflected growing automaticity associated with BCI performance and predicted future learning rate. Altogether, our findings provide new insights into the large-scale cortical organizational mechanisms underlying BCI learning, which have implications for the improvement of this technology in a broad range of real-life applications.
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Affiliation(s)
- Marie-Constance Corsi
- Inria Paris, Aramis Project-team, F-75013, Paris, France; Institut du Cerveau et de la Moelle Epinière, ICM, Inserm, U 1127, CNRS, UMR 7225, Sorbonne Université, F-75013, Paris, France.
| | | | - Denis Schwartz
- Institut du Cerveau et de la Moelle Epinière, ICM, Inserm U 1127, CNRS UMR 7225, Sorbonne Université, Ecole Normale Supérieure, ENS, Centre MEG-EEG, F-75013, Paris, France
| | - Nathalie George
- Institut du Cerveau et de la Moelle Epinière, ICM, Inserm, U 1127, CNRS, UMR 7225, Sorbonne Université, F-75013, Paris, France; Institut du Cerveau et de la Moelle Epinière, ICM, Inserm U 1127, CNRS UMR 7225, Sorbonne Université, Ecole Normale Supérieure, ENS, Centre MEG-EEG, F-75013, Paris, France
| | - Laurent Hugueville
- Institut du Cerveau et de la Moelle Epinière, ICM, Inserm U 1127, CNRS UMR 7225, Sorbonne Université, Ecole Normale Supérieure, ENS, Centre MEG-EEG, F-75013, Paris, France
| | - Ari E Kahn
- Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Sophie Dupont
- Institut du Cerveau et de la Moelle Epinière, ICM, Inserm, U 1127, CNRS, UMR 7225, Sorbonne Université, F-75013, Paris, France
| | - Danielle S Bassett
- Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA, 19104, USA; Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA; Department of Physics and Astronomy, College of Arts and Sciences, University of Pennsylvania, Philadelphia, PA, 19104, USA; Department of Electrical and Systems Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA, 19104, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA; Santa Fe Institute, Santa Fe, NM, 87501, USA
| | - Fabrizio De Vico Fallani
- Inria Paris, Aramis Project-team, F-75013, Paris, France; Institut du Cerveau et de la Moelle Epinière, ICM, Inserm, U 1127, CNRS, UMR 7225, Sorbonne Université, F-75013, Paris, France.
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59
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Murphy N, Ramakrishnan N, Walker CP, Polizzotto NR, Cho RY. Intact Auditory Cortical Cross-Frequency Coupling in Early and Chronic Schizophrenia. Front Psychiatry 2020; 11:507. [PMID: 32581881 PMCID: PMC7287164 DOI: 10.3389/fpsyt.2020.00507] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/21/2020] [Accepted: 05/18/2020] [Indexed: 01/01/2023] Open
Abstract
BACKGROUND Previous work has identified a hierarchical organization of neural oscillations that supports performance of complex cognitive and perceptual tasks, and can be indexed with phase-amplitude coupling (PAC) between low- and high-frequency oscillations. Our aim was to employ enhanced source localization afforded by magnetoencephalography (MEG) to expand on earlier reports of intact auditory cortical PAC in schizophrenia and to investigate how PAC may evolve over the early and chronic phases of the illness. METHODS Individuals with early schizophrenia (n=12) (≤5 years of illness duration), chronic schizophrenia (n=16) (>5 years of illness duration) and healthy comparators (n = 17) performed the auditory steady state response (ASSR) to 40, 30, and 20 Hz stimuli during MEG recordings. We estimated amplitude and PAC on the MEG ASSR source localized to the auditory cortices. RESULTS Gamma amplitude during 40-Hz ASSR exhibited a significant group by hemisphere interaction, with both patient groups showing reduced right hemisphere amplitude and no overall lateralization in contrast to the right hemisphere lateralization demonstrated in controls. We found significant PAC in the right auditory cortex during the 40-Hz entrainment condition relative to baseline, however, PAC did not differ significantly between groups. CONCLUSIONS In the current study, we demonstrated an apparent sparing of ASSR-related PAC across phases of the illness, in contrast with impaired cortical gamma oscillation amplitudes. The distinction between our PAC and evoked ASSR findings supports the notion of separate but interacting circuits for the generation and maintenance of sensory gamma oscillations. The apparent sparing of PAC in both early and chronic schizophrenia patients could imply that the neuropathology of schizophrenia differentially affects these mechanisms across different stages of the disease. Future studies should investigate the distinction between PAC during passive tasks and more cognitively demanding task such as working memory so that we can begin to understand the influence of schizophrenia neuropathology on the larger framework for modulating neurocomputational capacity.
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Affiliation(s)
- Nicholas Murphy
- Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, United States.,Research Service Line, Michael E. DeBakey Veterans Affairs Medical Center, Houston, TX, United States
| | - Nithya Ramakrishnan
- Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, United States.,Research Service Line, Michael E. DeBakey Veterans Affairs Medical Center, Houston, TX, United States
| | - Christopher P Walker
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Nicola R Polizzotto
- Psychiatry and Behavioral Sciences, University of Texas Health Science Center at Houston, Houston, TX, United States
| | - Raymond Y Cho
- Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, United States.,Research Service Line, Michael E. DeBakey Veterans Affairs Medical Center, Houston, TX, United States.,Menninger Clinic, Houston, TX, United States
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60
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Zhao M, Marino M, Samogin J, Swinnen SP, Mantini D. Hand, foot and lip representations in primary sensorimotor cortex: a high-density electroencephalography study. Sci Rep 2019; 9:19464. [PMID: 31857602 PMCID: PMC6923477 DOI: 10.1038/s41598-019-55369-3] [Citation(s) in RCA: 48] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2019] [Accepted: 11/22/2019] [Indexed: 11/09/2022] Open
Abstract
The primary sensorimotor cortex plays a major role in the execution of movements of the contralateral side of the body. The topographic representation of different body parts within this brain region is commonly investigated through functional magnetic resonance imaging (fMRI). However, fMRI does not provide direct information about neuronal activity. In this study, we used high-density electroencephalography (hdEEG) to map the representations of hand, foot, and lip movements in the primary sensorimotor cortex, and to study their neural signatures. Specifically, we assessed the event-related desynchronization (ERD) in the cortical space. We found that the performance of hand, foot, and lip movements elicited an ERD in beta and gamma frequency bands. The primary regions showing significant beta- and gamma-band ERD for hand and foot movements, respectively, were consistent with previously reported using fMRI. We observed relatively weaker ERD for lip movements, which may be explained by the fact that less fine movement control was required. Overall, our study demonstrated that ERD based on hdEEG data can support the study of motor-related neural processes, with relatively high spatial resolution. An interesting avenue may be the use of hdEEG for deeper investigations into the pathophysiology of neuromotor disorders.
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Affiliation(s)
- Mingqi Zhao
- Research Center for Motor Control and Neuroplasticity, KU Leuven, 3001, Leuven, Belgium
| | - Marco Marino
- Research Center for Motor Control and Neuroplasticity, KU Leuven, 3001, Leuven, Belgium.,Brain Imaging and Neural Dynamics Research Group, IRCCS San Camillo Hospital, 30126, Venice, Italy
| | - Jessica Samogin
- Research Center for Motor Control and Neuroplasticity, KU Leuven, 3001, Leuven, Belgium
| | - Stephan P Swinnen
- Research Center for Motor Control and Neuroplasticity, KU Leuven, 3001, Leuven, Belgium.,Leuven Brain Institute, KU Leuven, 3000, Leuven, Belgium
| | - Dante Mantini
- Research Center for Motor Control and Neuroplasticity, KU Leuven, 3001, Leuven, Belgium. .,Brain Imaging and Neural Dynamics Research Group, IRCCS San Camillo Hospital, 30126, Venice, Italy.
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61
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Barzegaran E, Bosse S, Kohler PJ, Norcia AM. EEGSourceSim: A framework for realistic simulation of EEG scalp data using MRI-based forward models and biologically plausible signals and noise. J Neurosci Methods 2019; 328:108377. [PMID: 31381946 PMCID: PMC6815881 DOI: 10.1016/j.jneumeth.2019.108377] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2019] [Revised: 07/13/2019] [Accepted: 07/29/2019] [Indexed: 02/02/2023]
Abstract
BACKGROUND Electroencephalography (EEG) is widely used to investigate human brain function. Simulation studies are essential for assessing the validity of EEG analysis methods and the interpretability of results. NEW METHOD Here we present a simulation environment for generating EEG data by embedding biologically plausible signal and noise into MRI-based forward models that incorporate individual-subject variability in structure and function. RESULTS The package includes pipelines for the evaluation and validation of EEG analysis tools for source estimation, functional connectivity, and spatial filtering. EEG dynamics can be simulated using realistic noise and signal models with user specifiable signal-to-noise ratio (SNR). We also provide a set of quantitative metrics tailored to source estimation, connectivity and spatial filtering applications. COMPARISON WITH EXISTING METHOD(S) We provide a larger set of forward solutions for individual MRI-based head models than has been available previously. These head models are surface-based and include two sets of regions-of-interest (ROIs) that have been brought into registration with the brain of each individual using surface-based alignment - one from a whole brain and the other from a visual cortex atlas. We derive a realistic model of noise by fitting different model components to measured resting state EEG. We also provide a set of quantitative metrics for evaluating source-localization, functional connectivity and spatial filtering methods. CONCLUSIONS The inclusion of a larger number of individual head-models, combined with surface-atlas based labeling of ROIs and plausible models of signal and noise, allows for simulation of EEG data with greater realism than previous packages.
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Affiliation(s)
- Elham Barzegaran
- Department of Psychology, Jordan Hall, Building 420, Stanford University, Stanford, CA 94305, USA.
| | - Sebastian Bosse
- Department of Video Coding & Analytics, Fraunhofer Heinrich Hertz Institute, 10587 Berlin, Germany.
| | - Peter J Kohler
- Department of Psychology, Jordan Hall, Building 420, Stanford University, Stanford, CA 94305, USA; Department of Psychology and Centre for Vision Research, Core Member, Vision: Science to Applications (VISTA), York University, 4700 Keele St., Toronto, ON, M3J 1P3, Canada.
| | - Anthony M Norcia
- Department of Psychology, Jordan Hall, Building 420, Stanford University, Stanford, CA 94305, USA.
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Knyazev GG, Savostyanov AN, Bocharov AV, Aftanas LI. EEG cross-frequency correlations as a marker of predisposition to affective disorders. Heliyon 2019; 5:e02942. [PMID: 31844779 PMCID: PMC6895656 DOI: 10.1016/j.heliyon.2019.e02942] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2019] [Revised: 09/18/2019] [Accepted: 11/25/2019] [Indexed: 01/10/2023] Open
Abstract
EEG cross-frequency amplitude-amplitude correlation (CF-AAC) has been considered as a potential marker of social anxiety and other affective disturbances. Functional significance of this phenomenon remains unclear, partly because the majority of studies used channel-level analysis, which precluded the spatial localization of observed effects. It is not also clear whether CF-AAC may serve as a marker of specific pathological conditions and specific states, or a more general predisposition to affective disturbances. We used source-level analysis of EEG data obtained in resting conditions in a nonclinical sample and patients with major depressive disorder (MDD) and investigated associations of CF-AAC measures with a broad range of known risk factors for affective disorders, including age, gender, genotype, stress exposure, personality, and self-reported ‘neurotic’ symptomatology. A consistent pattern of associations showed that all investigated risk factors were associated with an enhancement of CF-AAC in cortical regions associated with emotional and self-referential processing. It could be concluded that CF-AAC is a promising candidate marker of a general predisposition to affective disorders at preclinical stages.
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Affiliation(s)
- Gennady G Knyazev
- Institute of Physiology and Basic Medicine, Timakova str., 4, Novosibirsk, 630117, Russia
| | - Alexander N Savostyanov
- Institute of Physiology and Basic Medicine, Timakova str., 4, Novosibirsk, 630117, Russia.,Novosibirsk State University, Pirogova str., 2, Novosibirsk, 630090, Russia
| | - Andrey V Bocharov
- Institute of Physiology and Basic Medicine, Timakova str., 4, Novosibirsk, 630117, Russia.,Novosibirsk State University, Pirogova str., 2, Novosibirsk, 630090, Russia
| | - Lyubomir I Aftanas
- Institute of Physiology and Basic Medicine, Timakova str., 4, Novosibirsk, 630117, Russia.,Novosibirsk State University, Pirogova str., 2, Novosibirsk, 630090, Russia
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63
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Manca AD, Di Russo F, Sigona F, Grimaldi M. Electrophysiological evidence of phonemotopic representations of vowels in the primary and secondary auditory cortex. Cortex 2019; 121:385-398. [PMID: 31678684 DOI: 10.1016/j.cortex.2019.09.016] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2018] [Revised: 05/18/2019] [Accepted: 09/20/2019] [Indexed: 11/25/2022]
Abstract
How the brain encodes the speech acoustic signal into phonological representations is a fundamental question for the neurobiology of language. Determining whether this process is characterized by tonotopic maps in primary or secondary auditory areas, with bilateral or leftward activity, remains a long-standing challenge. Magnetoencephalographic studies failed to show hierarchical and asymmetric hints for speech processing. We employed high-density electroencephalography to map the Salento Italian vowel system onto cortical sources using the N1 auditory evoked component. We found evidence that the N1 is characterized by hierarchical and asymmetrical indexes in primary and secondary auditory areas structuring vowel representations. Importantly, the N1 was characterized by early and late phases. The early N1 peaked at 125-135 msec and was localized in the primary auditory cortex; the late N1 peaked at 145-155 msec and was localized in the left superior temporal gyrus. We showed that early in the primary auditory cortex, the cortical spatial arrangements-along the lateral-medial and anterior-posterior gradients-are broadly warped by phonemotopic patterns according to the distinctive feature principle. These phonemotopic patterns are carefully refined in the superior temporal gyrus along the inferior-superior and anterior-posterior gradients. The dynamical and hierarchical interface between primary and secondary auditory areas and the interaction effects between Height and Place features generate the categorical representation of the Salento Italian vowels.
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Affiliation(s)
- Anna Dora Manca
- Centro di Ricerca Interdisciplinare sul Linguaggio (CRIL), University of Salento, Lecce, Italy; Laboratorio Diffuso di Ricerca interdisciplinare Applicata alla Medicina (DReAM), Lecce, Italy
| | - Francesco Di Russo
- Dipartimento di Scienze Motorie, Umane e della Salute, University of Rome "Foro Italico", Rome, Italy; IRCCS Fondazione Santa Lucia, Rome, Italy
| | - Francesco Sigona
- Centro di Ricerca Interdisciplinare sul Linguaggio (CRIL), University of Salento, Lecce, Italy; Laboratorio Diffuso di Ricerca interdisciplinare Applicata alla Medicina (DReAM), Lecce, Italy
| | - Mirko Grimaldi
- Centro di Ricerca Interdisciplinare sul Linguaggio (CRIL), University of Salento, Lecce, Italy; Laboratorio Diffuso di Ricerca interdisciplinare Applicata alla Medicina (DReAM), Lecce, Italy.
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64
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Eriksson Hagberg E, Ackerley R, Lundqvist D, Schneiderman J, Jousmäki V, Wessberg J. Spatio-temporal profile of brain activity during gentle touch investigated with magnetoencephalography. Neuroimage 2019; 201:116024. [DOI: 10.1016/j.neuroimage.2019.116024] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2018] [Revised: 07/03/2019] [Accepted: 07/15/2019] [Indexed: 12/12/2022] Open
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65
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van Mierlo P, Höller Y, Focke NK, Vulliemoz S. Network Perspectives on Epilepsy Using EEG/MEG Source Connectivity. Front Neurol 2019; 10:721. [PMID: 31379703 PMCID: PMC6651209 DOI: 10.3389/fneur.2019.00721] [Citation(s) in RCA: 36] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2019] [Accepted: 06/18/2019] [Indexed: 12/17/2022] Open
Abstract
The evolution of EEG/MEG source connectivity is both, a promising, and controversial advance in the characterization of epileptic brain activity. In this narrative review we elucidate the potential of this technology to provide an intuitive view of the epileptic network at its origin, the different brain regions involved in the epilepsy, without the limitation of electrodes at the scalp level. Several studies have confirmed the added value of using source connectivity to localize the seizure onset zone and irritative zone or to quantify the propagation of epileptic activity over time. It has been shown in pilot studies that source connectivity has the potential to obtain prognostic correlates, to assist in the diagnosis of the epilepsy type even in the absence of visually noticeable epileptic activity in the EEG/MEG, and to predict treatment outcome. Nevertheless, prospective validation studies in large and heterogeneous patient cohorts are still lacking and are needed to bring these techniques into clinical use. Moreover, the methodological approach is challenging, with several poorly examined parameters that most likely impact the resulting network patterns. These fundamental challenges affect all potential applications of EEG/MEG source connectivity analysis, be it in a resting, spiking, or ictal state, and also its application to cognitive activation of the eloquent area in presurgical evaluation. However, such method can allow unique insights into physiological and pathological brain functions and have great potential in (clinical) neuroscience.
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Affiliation(s)
- Pieter van Mierlo
- Medical Image and Signal Processing Group, Ghent University, Ghent, Belgium
| | - Yvonne Höller
- Faculty of Psychology, University of Akureyri, Akureyri, Iceland
| | - Niels K Focke
- Clinical Neurophysiology, University Medicine Göttingen, Göttingen, Germany
| | - Serge Vulliemoz
- EEG and Epilepsy Unit, University Hospital of Geneva, Geneva, Switzerland
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66
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How meaning unfolds in neural time: Embodied reactivations can precede multimodal semantic effects during language processing. Neuroimage 2019; 197:439-449. [PMID: 31059796 DOI: 10.1016/j.neuroimage.2019.05.002] [Citation(s) in RCA: 31] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2018] [Revised: 03/08/2019] [Accepted: 05/02/2019] [Indexed: 02/08/2023] Open
Abstract
Research on how the brain construes meaning during language use has prompted two conflicting accounts. According to the 'grounded view', word understanding involves quick reactivations of sensorimotor (embodied) experiences evoked by the stimuli, with simultaneous or later engagement of multimodal (conceptual) systems integrating information from various sensory streams. Contrariwise, for the 'symbolic view', this capacity depends crucially on multimodal operations, with embodied systems playing epiphenomenal roles after comprehension. To test these contradictory hypotheses, the present magnetoencephalography study assessed implicit semantic access to grammatically constrained action and non-action verbs (n = 100 per category) while measuring spatiotemporally precise signals from the primary motor cortex (M1, a core region subserving bodily movements) and the anterior temporal lobe (ATL, a putative multimodal semantic hub). Convergent evidence from sensor- and source-level analyses revealed that increased modulations for action verbs occurred earlier in M1 (∼130-190 ms) than in specific ATL hubs (∼250-410 ms). Moreover, machine-learning decoding showed that trial-by-trial classification peaks emerged faster in M1 (∼100-175 ms) than in the ATL (∼345-500 ms), with over 71% accuracy in both cases. Considering their latencies, these results challenge the 'symbolic view' and its implication that sensorimotor mechanisms play only secondary roles in semantic processing. Instead, our findings support the 'grounded view', showing that early semantic effects are critically driven by embodied reactivations and that these cannot be reduced to post-comprehension epiphenomena, even when words are individually classified. Briefly, our study offers non-trivial insights to constrain fine-grained models of language and understand how meaning unfolds in neural time.
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67
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Mamashli F, Khan S, Obleser J, Friederici AD, Maess B. Oscillatory dynamics of cortical functional connections in semantic prediction. Hum Brain Mapp 2019; 40:1856-1866. [PMID: 30537025 PMCID: PMC6865711 DOI: 10.1002/hbm.24495] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2018] [Revised: 11/20/2018] [Accepted: 11/28/2018] [Indexed: 01/22/2023] Open
Abstract
An event related potential, known as the N400, has been particularly useful in investigating language processing as it serves as a neural index for semantic prediction. There are numerous studies on the functional segregation of N400 neural sources; however, the oscillatory dynamics of functional connections among the relevant sources has remained elusive. In this study we acquired magnetoencephalography data during a classic N400 paradigm, where the semantic predictability of a fixed target noun was manipulated in simple German sentences. We conducted inter-regional functional connectivity (FC) and time-frequency analysis on known regions of the semantic network, encompassing bilateral temporal, and prefrontal cortices. Increased FC was found in less predicted (LP) nouns compared with highly predicted (HP) nouns in three connections: (a) right inferior frontal gyrus (IFG) and right middle temporal gyrus (MTG) from 0 to 300 ms mainly within the alpha band, (b) left lateral orbitofrontal (LOF) and right IFG around 400 ms within the beta band, and (c) left superior temporal gyrus (STG) and left LOF from 300 to 700 ms in the beta and low gamma bands. Furthermore, gamma spectral power (31-70 Hz) was stronger in HP nouns than in LP nouns in left anterior temporal cortices in earlier time windows (0-200 ms). Our findings support recent theories in language comprehension, suggesting fronto-temporal top-down connections are mainly mediated through beta oscillations while gamma band frequencies are involved in matching between prediction and input.
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Affiliation(s)
- Fahimeh Mamashli
- Department of RadiologyMassachusetts General Hospital, Athinoula A. Martinos Center for Biomedical Imaging, Harvard Medical SchoolBostonMassachusetts
| | - Sheraz Khan
- Department of RadiologyMassachusetts General Hospital, Athinoula A. Martinos Center for Biomedical Imaging, Harvard Medical SchoolBostonMassachusetts
| | - Jonas Obleser
- Department of PsychologyUniversity of LübeckLübeckGermany
| | - Angela D. Friederici
- Department of NeuropsychologyMax Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
| | - Burkhard Maess
- MEG and Cortical Networks Group, Max Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
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68
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Rosen BQ, Krishnan GP, Sanda P, Komarov M, Sejnowski T, Rulkov N, Ulbert I, Eross L, Madsen J, Devinsky O, Doyle W, Fabo D, Cash S, Bazhenov M, Halgren E. Simulating human sleep spindle MEG and EEG from ion channel and circuit level dynamics. J Neurosci Methods 2019; 316:46-57. [PMID: 30300700 PMCID: PMC6380919 DOI: 10.1016/j.jneumeth.2018.10.002] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2018] [Revised: 10/03/2018] [Accepted: 10/04/2018] [Indexed: 11/16/2022]
Abstract
BACKGROUND Although they form a unitary phenomenon, the relationship between extracranial M/EEG and transmembrane ion flows is understood only as a general principle rather than as a well-articulated and quantified causal chain. METHOD We present an integrated multiscale model, consisting of a neural simulation of thalamus and cortex during stage N2 sleep and a biophysical model projecting cortical current densities to M/EEG fields. Sleep spindles were generated through the interactions of local and distant network connections and intrinsic currents within thalamocortical circuits. 32,652 cortical neurons were mapped onto the cortical surface reconstructed from subjects' MRI, interconnected based on geodesic distances, and scaled-up to current dipole densities based on laminar recordings in humans. MRIs were used to generate a quasi-static electromagnetic model enabling simulated cortical activity to be projected to the M/EEG sensors. RESULTS The simulated M/EEG spindles were similar in amplitude and topography to empirical examples in the same subjects. Simulated spindles with more core-dominant activity were more MEG weighted. COMPARISON WITH EXISTING METHODS Previous models lacked either spindle-generating thalamic neural dynamics or whole head biophysical modeling; the framework presented here is the first to simultaneously capture these disparate scales. CONCLUSIONS This multiscale model provides a platform for the principled quantitative integration of existing information relevant to the generation of sleep spindles, and allows the implications of future findings to be explored. It provides a proof of principle for a methodological framework allowing large-scale integrative brain oscillations to be understood in terms of their underlying channels and synapses.
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Affiliation(s)
- B Q Rosen
- Neurosciences Graduate Program, University of California, San Diego, La Jolla, CA, United States.
| | - G P Krishnan
- Department of Medicine, University of California, San Diego, La Jolla, CA, United States.
| | - P Sanda
- Department of Medicine, University of California, San Diego, La Jolla, CA, United States; Institute of Computer Science, Czech Academy of Sciences, Prague, Czech Republic.
| | - M Komarov
- Department of Medicine, University of California, San Diego, La Jolla, CA, United States.
| | - T Sejnowski
- Neurosciences Graduate Program, University of California, San Diego, La Jolla, CA, United States; The Salk Institute, La Jolla, CA, United States.
| | - N Rulkov
- BioCiruits Institute, University of California, San Diego, La Jolla, CA, United States.
| | - I Ulbert
- Institute of Cognitive Neuroscience and Psychology, Hungarian Academy of Science, Budapest, Hungary; Faculty of Information Technology and Bionics, Peter Pazmany Catholic University, Budapest, Hungary.
| | - L Eross
- Faculty of Information Technology and Bionics, Peter Pazmany Catholic University, Budapest, Hungary; Department of Functional Neurosurgery, National Institute of Clinical Neurosciences, Budapest, Hungary.
| | - J Madsen
- Departments of Neurosurgery, Boston Children's Hospital and Harvard Medical School, Boston, MA, United States.
| | - O Devinsky
- Comprehensive Epilepsy Center, New York University School of Medicine, New York, NY, United States.
| | - W Doyle
- Comprehensive Epilepsy Center, New York University School of Medicine, New York, NY, United States.
| | - D Fabo
- Epilepsy Centrum, National Institute of Clinical Neurosciences, Budapest, Hungary.
| | - S Cash
- Neurosciences Graduate Program, University of California, San Diego, La Jolla, CA, United States; Department of Medicine, University of California, San Diego, La Jolla, CA, United States; Departments of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States.
| | - M Bazhenov
- Neurosciences Graduate Program, University of California, San Diego, La Jolla, CA, United States; Department of Medicine, University of California, San Diego, La Jolla, CA, United States.
| | - E Halgren
- Neurosciences Graduate Program, University of California, San Diego, La Jolla, CA, United States; Department of Radiology, University of California, San Diego, La Jolla, CA, United States; Department of Neurosciences, University of California, San Diego, La Jolla, CA, United States.
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69
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Bharadwaj HM, Mai AR, Simpson JM, Choi I, Heinz MG, Shinn-Cunningham BG. Non-Invasive Assays of Cochlear Synaptopathy - Candidates and Considerations. Neuroscience 2019; 407:53-66. [PMID: 30853540 DOI: 10.1016/j.neuroscience.2019.02.031] [Citation(s) in RCA: 73] [Impact Index Per Article: 14.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2018] [Revised: 02/21/2019] [Accepted: 02/25/2019] [Indexed: 12/31/2022]
Abstract
Studies in multiple species, including in post-mortem human tissue, have shown that normal aging and/or acoustic overexposure can lead to a significant loss of afferent synapses innervating the cochlea. Hypothetically, this cochlear synaptopathy can lead to perceptual deficits in challenging environments and can contribute to central neural effects such as tinnitus. However, because cochlear synaptopathy can occur without any measurable changes in audiometric thresholds, synaptopathy can remain hidden from standard clinical diagnostics. To understand the perceptual sequelae of synaptopathy and to evaluate the efficacy of emerging therapies, sensitive and specific non-invasive measures at the individual patient level need to be established. Pioneering experiments in specific mice strains have helped identify many candidate assays. These include auditory brainstem responses, the middle-ear muscle reflex, envelope-following responses, and extended high-frequency audiograms. Unfortunately, because these non-invasive measures can be also affected by extraneous factors other than synaptopathy, their application and interpretation in humans is not straightforward. Here, we systematically examine six extraneous factors through a series of interrelated human experiments aimed at understanding their effects. Using strategies that may help mitigate the effects of such extraneous factors, we then show that these suprathreshold physiological assays exhibit across-individual correlations with each other indicative of contributions from a common physiological source consistent with cochlear synaptopathy. Finally, we discuss the application of these assays to two key outstanding questions, and discuss some barriers that still remain. This article is part of a Special Issue entitled: Hearing Loss, Tinnitus, Hyperacusis, Central Gain.
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Affiliation(s)
- Hari M Bharadwaj
- Department of Speech, Language, and Hearing Sciences, Purdue University, West Lafayette, IN; Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN.
| | - Alexandra R Mai
- Department of Speech, Language, and Hearing Sciences, Purdue University, West Lafayette, IN
| | - Jennifer M Simpson
- Department of Speech, Language, and Hearing Sciences, Purdue University, West Lafayette, IN
| | - Inyong Choi
- Department of Communication Sciences and Disorders, University of Iowa, Iowa City, IA
| | - Michael G Heinz
- Department of Speech, Language, and Hearing Sciences, Purdue University, West Lafayette, IN; Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN
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70
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Thomschewski A, Hincapié AS, Frauscher B. Localization of the Epileptogenic Zone Using High Frequency Oscillations. Front Neurol 2019; 10:94. [PMID: 30804887 PMCID: PMC6378911 DOI: 10.3389/fneur.2019.00094] [Citation(s) in RCA: 83] [Impact Index Per Article: 16.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2018] [Accepted: 01/23/2019] [Indexed: 01/22/2023] Open
Abstract
For patients with drug-resistant focal epilepsy, surgery is the therapy of choice in order to achieve seizure freedom. Epilepsy surgery foremost requires the identification of the epileptogenic zone (EZ), defined as the brain area indispensable for seizure generation. The current gold standard for identification of the EZ is the seizure-onset zone (SOZ). The fact, however that surgical outcomes are unfavorable in 40-50% of well-selected patients, suggests that the SOZ is a suboptimal biomarker of the EZ, and that new biomarkers resulting in better postsurgical outcomes are needed. Research of recent years suggested that high-frequency oscillations (HFOs) are a promising biomarker of the EZ, with a potential to improve surgical success in patients with drug-resistant epilepsy without the need to record seizures. Nonetheless, in order to establish HFOs as a clinical biomarker, the following issues need to be addressed. First, evidence on HFOs as a clinically relevant biomarker stems predominantly from retrospective assessments with visual marking, leading to problems of reproducibility and reliability. Prospective assessments of the use of HFOs for surgery planning using automatic detection of HFOs are needed in order to determine their clinical value. Second, disentangling physiologic from pathologic HFOs is still an unsolved issue. Considering the appearance and the topographic location of presumed physiologic HFOs could be immanent for the interpretation of HFO findings in a clinical context. Third, recording HFOs non-invasively via scalp electroencephalography (EEG) and magnetoencephalography (MEG) is highly desirable, as it would provide us with the possibility to translate the use of HFOs to the scalp in a large number of patients. This article reviews the literature regarding these three issues. The first part of the article focuses on the clinical value of invasively recorded HFOs in localizing the EZ, the detection of HFOs, as well as their separation from physiologic HFOs. The second part of the article focuses on the current state of the literature regarding non-invasively recorded HFOs with emphasis on findings and technical considerations regarding their localization.
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Affiliation(s)
- Aljoscha Thomschewski
- Department of Neurology, Christian Doppler Medical Center, Paracelsus Medical University, Salzburg, Austria
- Department of Psychology, Paris-Lodron University of Salzburg, Salzburg, Austria
| | - Ana-Sofía Hincapié
- Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Birgit Frauscher
- Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
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71
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Matchin W, Brodbeck C, Hammerly C, Lau E. The temporal dynamics of structure and content in sentence comprehension: Evidence from fMRI-constrained MEG. Hum Brain Mapp 2019; 40:663-678. [PMID: 30259599 PMCID: PMC6865621 DOI: 10.1002/hbm.24403] [Citation(s) in RCA: 44] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2018] [Revised: 09/04/2018] [Accepted: 09/07/2018] [Indexed: 01/10/2023] Open
Abstract
Humans have a striking capacity to combine words into sentences that express new meanings. Previous research has identified key brain regions involved in this capacity, but little is known about the time course of activity in these regions, as hemodynamic methods such as fMRI provide little insight into temporal dynamics of neural activation. We performed an MEG experiment to elucidate the temporal dynamics of structure and content processing within four brain regions implicated by fMRI data from the same experiment: the temporo-parietal junction (TPJ), the posterior temporal lobe (PTL), the anterior temporal lobe (ATL), and the anterior inferior frontal gyrus (IFG). The TPJ showed increased activity for both structure and content near the end of the sentence, consistent with a role in incremental interpretation of event semantics. The PTL, a region not often associated with core aspects of syntax, showed a strong early effect of structure, consistent with predictive parsing models, and both structural and semantic context effects on function words. These results provide converging evidence that the PTL plays an important role in lexicalized syntactic processing. The ATL and IFG, regions traditionally associated with syntax, showed minimal effects of sentence structure. The ATL, PTL and IFG all showed effects of semantic content: increased activation for real words relative to nonwords. Our fMRI-guided MEG investigation therefore helps identify syntactic and semantic aspects of sentence comprehension in the brain in both spatial and temporal dimensions.
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Affiliation(s)
- William Matchin
- Department of Communication Sciences and DisordersUniversity of South CarolinaColumbiaSouth Carolina
| | - Christian Brodbeck
- Institute for Systems ResearchUniversity of MarylandCollege ParkMaryland
| | | | - Ellen Lau
- Department of LinguisticsUniversity of MarylandCollege ParkMaryland
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72
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Samuelsson JG, Khan S, Sundaram P, Peled N, Hämäläinen MS. Cortical Signal Suppression (CSS) for Detection of Subcortical Activity Using MEG and EEG. Brain Topogr 2019; 32:215-228. [PMID: 30604048 DOI: 10.1007/s10548-018-00694-5] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2018] [Accepted: 12/17/2018] [Indexed: 11/28/2022]
Abstract
Magnetoencephalography (MEG) and electroencephalography (EEG) use non-invasive sensors to detect neural currents. Since the contribution of superficial neural sources to the measured M/EEG signals are orders-of-magnitude stronger than the contribution of subcortical sources, most MEG and EEG studies have focused on cortical activity. Subcortical structures, however, are centrally involved in both healthy brain function as well as in many neurological disorders such as Alzheimer's disease and Parkinson's disease. In this paper, we present a method that can separate and suppress the cortical signals while preserving the subcortical contributions to the M/EEG data. The resulting signal subspace of the data mainly originates from subcortical structures. Our method works by utilizing short-baseline planar gradiometers with short-sighted sensitivity distributions as reference sensors for cortical activity. Since the method is completely data-driven, forward and inverse modeling are not required. In this study, we use simulations and auditory steady state response experiments in a human subject to demonstrate that the method can remove the cortical signals while sparing the subcortical signals. We also test our method on MEG data recorded in an essential tremor patient with a deep brain stimulation implant and show how it can be used to reduce the DBS artifact in the MEG data by ~ 99.9% without affecting low frequency brain rhythms.
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Affiliation(s)
- John G Samuelsson
- Harvard-MIT Division of Health Sciences and Technology (HST), Massachusetts Institute of Technology (MIT), Cambridge, MA, 02139, USA. .,Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, 02129, USA. .,Harvard Medical School, Boston, MA, 02115, USA.
| | - Sheraz Khan
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, 02129, USA.,Harvard Medical School, Boston, MA, 02115, USA
| | - Padmavathi Sundaram
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, 02129, USA.,Harvard Medical School, Boston, MA, 02115, USA
| | - Noam Peled
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, 02129, USA.,Harvard Medical School, Boston, MA, 02115, USA
| | - Matti S Hämäläinen
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, 02129, USA.,Harvard Medical School, Boston, MA, 02115, USA
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73
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74
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Comparing the potential of MEG and EEG to uncover brain tracking of speech temporal envelope. Neuroimage 2019; 184:201-213. [DOI: 10.1016/j.neuroimage.2018.09.006] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2018] [Revised: 08/22/2018] [Accepted: 09/03/2018] [Indexed: 11/20/2022] Open
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75
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Revisiting the Contribution of Auditory Cortex to Frequency-Following Responses. J Neurosci 2018; 37:5218-5220. [PMID: 28539348 DOI: 10.1523/jneurosci.0794-17.2017] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2017] [Revised: 04/17/2017] [Accepted: 04/21/2017] [Indexed: 11/21/2022] Open
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76
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Knyazev GG, Merkulova EA, Savostyanov AN, Bocharov AV, Saprigyn AE. Effect of Cultural Priming on Social Behavior and EEG Correlates of Self-Processing. Front Behav Neurosci 2018; 12:236. [PMID: 30349465 PMCID: PMC6186948 DOI: 10.3389/fnbeh.2018.00236] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2018] [Accepted: 09/21/2018] [Indexed: 11/30/2022] Open
Abstract
Humans are social beings and the self is inevitably conceptualized in terms of social environment. The degree to which the self is perceived as fundamentally similar or fundamentally different from other people is modulated by cultural stereotypes, such as collectivism and individualism. These stereotypes are not hardwired in our brains and individuals differ in the degree to which they adopt the attitudes that define their culture. Moreover, individuals can acquire multiple sets of cultural knowledge and, depending on the context, either individualistic or collectivistic cultural mindset could be activated. In this study, we used cultural priming techniques to activate either individualistic or collectivistic mindset and investigated the association between source-level EEG connectivity in the default mode network (DMN) and spontaneous self-related thoughts in the subsequent resting state. Afterward, participants performed a social interaction task, in which they were allowed to choose between friendly, avoidant, or aggressive behavior. After collectivism priming, self-related thoughts were associated with increased connectivity of DMN with the right temporoparietal junction (TPJ), which is involved in taking the perspective of others and is more active in representatives of collectivistic cultures, whereas after individualism priming they were associated with increased connectivity with the temporal pole, which is involved in self/other discrimination and is more active in representatives of individualistic cultures. Individual differences in the intensity of post-priming self-related thoughts and the strength of DMN-temporal pole connectivity predicted individual differences in behavior during the social interaction task, with individualistic mindset predisposing to more friendly and trustful social behavior.
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Affiliation(s)
- Gennady G. Knyazev
- Laboratory of Psychophysiology of Individual Differences, Institute of Physiology and Basic Medicine, Novosibirsk, Russia
| | - Ekaterina A. Merkulova
- Laboratory of Psychophysiology of Individual Differences, Institute of Physiology and Basic Medicine, Novosibirsk, Russia
| | - Alexander N. Savostyanov
- Laboratory of Psychophysiology of Individual Differences, Institute of Physiology and Basic Medicine, Novosibirsk, Russia
- Humanitarian Institute, Novosibirsk State University, Novosibirsk, Russia
| | - Andrey V. Bocharov
- Laboratory of Psychophysiology of Individual Differences, Institute of Physiology and Basic Medicine, Novosibirsk, Russia
- Humanitarian Institute, Novosibirsk State University, Novosibirsk, Russia
| | - Alexander E. Saprigyn
- Laboratory of Psychophysiology of Individual Differences, Institute of Physiology and Basic Medicine, Novosibirsk, Russia
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77
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Faulkner M, Hannan S, Aristovich K, Avery J, Holder D. Feasibility of imaging evoked activity throughout the rat brain using electrical impedance tomography. Neuroimage 2018; 178:1-10. [DOI: 10.1016/j.neuroimage.2018.05.022] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2018] [Revised: 04/26/2018] [Accepted: 05/08/2018] [Indexed: 10/16/2022] Open
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78
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Impaired neural mechanism for online novel word acquisition in dyslexic children. Sci Rep 2018; 8:12779. [PMID: 30143722 PMCID: PMC6109122 DOI: 10.1038/s41598-018-31211-0] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2018] [Accepted: 08/13/2018] [Indexed: 11/08/2022] Open
Abstract
Developmental dyslexia is characterised as an inability to read fluently. Apart from literacy problems, dyslexics have other language difficulties including inefficient speech encoding and deficient novel word learning. Yet, the neural mechanisms underlying these impairments are largely unknown. We tracked online formation of neural memory traces for a novel spoken word-form in dyslexic and normal-reading children by recording the brain’s electrophysiological response dynamics in a passive perceptual exposure session. Crucially, no meaning was assigned to the new word-form nor was there any task related to the stimulus, enabling us to explore the memory-trace formation of a purely phonological form in the absence of any short-term or working memory demands. Similar to previously established neural index of rapid word learning in adults, the control children demonstrated an early brain response enhancement within minutes of exposure to the novel word-form that originated in frontal cortices. Dyslexic children, however, lacked this neural enhancement over the entire course of exposure. Furthermore, the magnitude of the rapid neural enhancement for the novel word-form was positively associated with reading and writing fluency. This suggests that the rapid neural learning mechanism for online acquisition of novel speech material is associated with reading skills. Furthermore, the deficient online learning of novel words in dyslexia, consistent with poor rapid adaptation to familiar stimuli, may underlie the difficulty of learning to read.
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79
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van de Vijver I, van Driel J, Hillebrand A, Cohen MX. Interactions between frontal and posterior oscillatory dynamics support adjustment of stimulus processing during reinforcement learning. Neuroimage 2018; 181:170-181. [PMID: 29990582 DOI: 10.1016/j.neuroimage.2018.07.014] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2018] [Revised: 06/15/2018] [Accepted: 07/05/2018] [Indexed: 11/29/2022] Open
Abstract
Reinforcement learning (RL) in humans is subserved by a network of striatal and frontal brain areas. The electrophysiological signatures of feedback evaluation are increasingly well understood, but how those signatures relate to the use of feedback to guide subsequent behavioral adjustment remains unclear. One mechanism for post-feedback behavioral optimization is the modulation of sensory processing. We used source-reconstructed MEG to test whether feedback affects the interactions between sources of oscillatory activity in the learning network and task-relevant stimulus-processing areas. Participants performed a probabilistic RL task in which they learned associations between colored faces and response buttons using trial-and-error feedback. Delta-band (2-4 Hz) and theta-band (4-8 Hz) power in multiple frontal regions were sensitive to feedback valence. Low and high beta-band power (12-20 and 20-30 Hz) in occipital, parietal, and temporal regions differentiated between color and face information. Consistent with our hypothesis, single-trial power-power correlations between frontal and posterior-sensory areas were modulated by the interaction between feedback valence and the relevant stimulus characteristic (color versus identity). These results suggest that long-range oscillatory coupling supports post-feedback updating of stimulus processing.
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Affiliation(s)
- Irene van de Vijver
- University of Amsterdam, Department of Psychology, Amsterdam, The Netherlands; Radboud University, Behavioural Science Institute, Nijmegen, The Netherlands.
| | - Joram van Driel
- University of Amsterdam, Department of Psychology, Amsterdam, The Netherlands; Vrije Universiteit, Department of Cognitive Psychology, Amsterdam, The Netherlands
| | - Arjan Hillebrand
- Department of Clinical Neurophysiology and Magnetoencephalography Center, VU University Medical Center, Amsterdam, The Netherlands
| | - Michael X Cohen
- University of Amsterdam, Department of Psychology, Amsterdam, The Netherlands
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80
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Ongoing brain rhythms shape I-wave properties in a computational model. Brain Stimul 2018; 11:828-838. [DOI: 10.1016/j.brs.2018.03.010] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2017] [Revised: 03/07/2018] [Accepted: 03/12/2018] [Indexed: 01/27/2023] Open
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81
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Xie Z, Reetzke R, Chandrasekaran B. Taking Attention Away from the Auditory Modality: Context-dependent Effects on Early Sensory Encoding of Speech. Neuroscience 2018; 384:64-75. [PMID: 29802881 DOI: 10.1016/j.neuroscience.2018.05.023] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2017] [Revised: 05/14/2018] [Accepted: 05/16/2018] [Indexed: 02/06/2023]
Abstract
Increasing visual perceptual load can reduce pre-attentive auditory cortical activity to sounds, a reflection of the limited and shared attentional resources for sensory processing across modalities. Here, we demonstrate that modulating visual perceptual load can impact the early sensory encoding of speech sounds, and that the impact of visual load is highly dependent on the predictability of the incoming speech stream. Participants (n = 20, 9 females) performed a visual search task of high (target similar to distractors) and low (target dissimilar to distractors) perceptual load, while early auditory electrophysiological responses were recorded to native speech sounds. Speech sounds were presented either in a 'repetitive context', or a less predictable 'variable context'. Independent of auditory stimulus context, pre-attentive auditory cortical activity was reduced during high visual load, relative to low visual load. We applied a data-driven machine learning approach to decode speech sounds from the early auditory electrophysiological responses. Decoding performance was found to be poorer under conditions of high (relative to low) visual load, when the incoming acoustic stream was predictable. When the auditory stimulus context was less predictable, decoding performance was substantially greater for the high (relative to low) visual load conditions. Our results provide support for shared attentional resources between visual and auditory modalities that substantially influence the early sensory encoding of speech signals in a context-dependent manner.
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Affiliation(s)
- Zilong Xie
- Department of Communication Sciences and Disorders, The University of Texas at Austin, Austin, TX 78712, USA
| | - Rachel Reetzke
- Department of Communication Sciences and Disorders, The University of Texas at Austin, Austin, TX 78712, USA
| | - Bharath Chandrasekaran
- Department of Communication Sciences and Disorders, The University of Texas at Austin, Austin, TX 78712, USA; Department of Psychology, The University of Texas at Austin, Austin, TX 78712, USA; Department of Linguistics, The University of Texas at Austin, Austin, TX 78712, USA; Institute for Neuroscience, The University of Texas at Austin, Austin, TX 78712, USA; Institute for Mental Health Research, The University of Texas at Austin, Austin, TX 78712, USA.
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82
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Melynyte S, Pipinis E, Genyte V, Voicikas A, Rihs T, Griskova-Bulanova I. 40 Hz Auditory Steady-State Response: The Impact of Handedness and Gender. Brain Topogr 2017; 31:419-429. [PMID: 29218677 DOI: 10.1007/s10548-017-0611-x] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2017] [Accepted: 12/04/2017] [Indexed: 01/31/2023]
Abstract
The 40 Hz auditory steady-state response (ASSR) is a periodic response to a periodic stimulation. Its sources are located in the primary auditory cortex and the asymmetry of the planum temporale has previously been associated with hand preference and gender-related differences; thus subject's handedness and gender could potentially influence ASSRs. Nevertheless, electrophysiological studies of ASSRs are mainly dominated by right-handed participants and the observed findings can only be generalized to the right-handed populations. However, for a potential use of 40 Hz ASSR as a translational biomarker of neuropsychiatric disorders, it is important to investigate the response in association to handedness and gender. We included an equal number of left-handed and right-handed males and females and recorded EEG responses during left-ear, right-ear and both ears stimulation. The results of the study suggest that the processing of 40 Hz auditory stimulation depends on the subjects' gender and handedness: significantly lower phase-locking and strength of 40 Hz ASSRs were observed in left-handed females as compared to left-handed males, but right-handers did not differ in 40 Hz ASSRs. Our observation of the opposite impact of gender in the examined handedness groups stresses the importance of careful consideration of handedness and gender factors when evaluating the determinants of inter individual variability of 40 Hz ASSRs. This finding is of particular importance for clinical studies in psychiatry and neurology.
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Affiliation(s)
- Sigita Melynyte
- Institute of Biosciences, Life Sciences Centre, Vilnius University, Sauletekio ave 7, 10257, Vilnius, Lithuania
| | - Evaldas Pipinis
- Institute of Biosciences, Life Sciences Centre, Vilnius University, Sauletekio ave 7, 10257, Vilnius, Lithuania
| | - Vaida Genyte
- Institute of Biosciences, Life Sciences Centre, Vilnius University, Sauletekio ave 7, 10257, Vilnius, Lithuania
| | - Aleksandras Voicikas
- Institute of Biosciences, Life Sciences Centre, Vilnius University, Sauletekio ave 7, 10257, Vilnius, Lithuania
| | - Tonia Rihs
- Department of Fundamental Neurosciences, University of Geneva, Geneva, Switzerland
| | - Inga Griskova-Bulanova
- Institute of Biosciences, Life Sciences Centre, Vilnius University, Sauletekio ave 7, 10257, Vilnius, Lithuania.
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83
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Resting state connectivity mediates the relationship between collectivism and social cognition. Int J Psychophysiol 2017; 123:17-24. [PMID: 29208492 DOI: 10.1016/j.ijpsycho.2017.12.002] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2017] [Revised: 11/13/2017] [Accepted: 12/02/2017] [Indexed: 01/15/2023]
Abstract
Humans are intrinsically social beings and it is natural that self-processing is associated with social cognition. The degree to which the self is perceived as a part of social environment is modulated by cultural stereotypes, such as collectivism and individualism. Here, we tested the hypothesis that individuals who endorse collectivist values would spontaneously think more about their relationships with other people and this association would be mediated by connectivity between the medial prefrontal cortex (MPFC) and the rest of the brain. Connectivity was evaluated based on resting state EEG data using the recently developed methods, which combine beamformer spatial filtering with seed based connectivity estimation. The formal mediation analysis revealed that collectivism is associated with an enhanced connectivity of MPFC with a set of cortical regions that are frequently co-activated in moral reasoning, empathy, and theory of mind tasks and with diminished connectivity with the precuneus\posterior cingulate cortex, which is involved in self-centered cognition. The relationship between collectivism and social cognition was mediated by MPFC connectivity with the left middle temporal gyrus implying that in participants with collectivistic attitude, thinking about relationships with other people may be associated with semantic memory retrieval and reasoning on moral issues and others' intentions.
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84
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Chowdhury RA, Pellegrino G, Aydin Ü, Lina JM, Dubeau F, Kobayashi E, Grova C. Reproducibility of EEG-MEG fusion source analysis of interictal spikes: Relevance in presurgical evaluation of epilepsy. Hum Brain Mapp 2017; 39:880-901. [PMID: 29164737 DOI: 10.1002/hbm.23889] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2017] [Revised: 11/03/2017] [Accepted: 11/07/2017] [Indexed: 11/06/2022] Open
Abstract
Fusion of electroencephalography (EEG) and magnetoencephalography (MEG) data using maximum entropy on the mean method (MEM-fusion) takes advantage of the complementarities between EEG and MEG to improve localization accuracy. Simulation studies demonstrated MEM-fusion to be robust especially in noisy conditions such as single spike source localizations (SSSL). Our objective was to assess the reliability of SSSL using MEM-fusion on clinical data. We proposed to cluster SSSL results to find the most reliable and consistent source map from the reconstructed sources, the so-called consensus map. Thirty-four types of interictal epileptic discharges (IEDs) were analyzed from 26 patients with well-defined epileptogenic focus. SSSLs were performed on EEG, MEG, and fusion data and consensus maps were estimated using hierarchical clustering. Qualitative (spike-to-spike reproducibility rate, SSR) and quantitative (localization error and spatial dispersion) assessments were performed using the epileptogenic focus as clinical reference. Fusion SSSL provided significantly better results than EEG or MEG alone. Fusion found at least one cluster concordant with the clinical reference in all cases. This concordant cluster was always the one involving the highest number of spikes. Fusion yielded highest reproducibility (SSR EEG = 55%, MEG = 71%, fusion = 90%) and lowest localization error. Also, using only few channels from either modality (21EEG + 272MEG or 54EEG + 25MEG) was sufficient to reach accurate fusion. MEM-fusion with consensus map approach provides an objective way of finding the most reliable and concordant generators of IEDs. We, therefore, suggest the pertinence of SSSL using MEM-fusion as a valuable clinical tool for presurgical evaluation of epilepsy.
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Affiliation(s)
- Rasheda Arman Chowdhury
- Multimodal Functional Imaging Lab, Biomedical Engineering Department, McGill University, Montreal, Québec, Canada
| | | | - Ümit Aydin
- Multimodal Functional Imaging Lab, Department of Physics and PERFORM Centre, Concordia University, Montreal, Québec, Canada
| | - Jean-Marc Lina
- Ecole de Technologie Supérieure, Montréal, Québec, Canada.,Centre de Recherches Mathématiques, Université de Montréal, Montréal, Québec, Canada
| | - François Dubeau
- Neurology and Neurosurgery Department, Montreal Neurological Institute, McGill University, Montreal, Québec, Canada
| | - Eliane Kobayashi
- Neurology and Neurosurgery Department, Montreal Neurological Institute, McGill University, Montreal, Québec, Canada
| | - Christophe Grova
- Multimodal Functional Imaging Lab, Biomedical Engineering Department, McGill University, Montreal, Québec, Canada.,Centre de Recherches Mathématiques, Université de Montréal, Montréal, Québec, Canada.,Neurology and Neurosurgery Department, Montreal Neurological Institute, McGill University, Montreal, Québec, Canada.,Multimodal Functional Imaging Lab, Department of Physics and PERFORM Centre, Concordia University, Montreal, Québec, Canada
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85
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Resting State Networks Mediate the Effect of Genotype by Environment Interaction on Mental Health. Neuroscience 2017; 369:139-151. [PMID: 29129791 DOI: 10.1016/j.neuroscience.2017.11.010] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2017] [Revised: 08/21/2017] [Accepted: 11/04/2017] [Indexed: 12/12/2022]
Abstract
A number of studies have shown that the presence of short (S) allele of the serotonin transporter-linked polymorphic region (5-HTTLPR) is associated with a higher risk for depression following exposure to stressful life events. These findings are in line with neuroimaging studies showing that 5-HTTLPR polymorphism has an effect on the connectivity among key areas involved in emotion regulation. Here using mediated moderation analysis, we show that electrophysiological manifestations of resting state networks in the alpha frequency band mediate the effect of 5-HTTLPR by stress interaction on depression/anxiety symptoms in a nonclinical sample. Specifically, at the brain level, both L-allele homozygotes and S-allele carriers are similarly responsive to stress exposure. However, these brain responses seem to act as triggers of psychopathological symptoms in S-allele carriers, but as suppressors in L-allele homozygotes. This finding implies that the interpretation of the effect of gene by environment interaction on psychopathology seems more complicated than behavioral results alone would imply. It is not just differential sensitivity to stress, but rather different ways of coping with stress, which distinguish S-allele carriers and L-allele homozygotes.
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86
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Andersen LM, Oostenveld R, Pfeiffer C, Ruffieux S, Jousmäki V, Hämäläinen M, Schneiderman JF, Lundqvist D. Similarities and differences between on-scalp and conventional in-helmet magnetoencephalography recordings. PLoS One 2017; 12:e0178602. [PMID: 28742118 PMCID: PMC5524409 DOI: 10.1371/journal.pone.0178602] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2017] [Accepted: 05/16/2017] [Indexed: 11/19/2022] Open
Abstract
The development of new magnetic sensor technologies that promise sensitivities approaching that of conventional MEG technology while operating at far lower operating temperatures has catalysed the growing field of on-scalp MEG. The feasibility of on-scalp MEG has been demonstrated via benchmarking of new sensor technologies performing neuromagnetic recordings in close proximity to the head surface against state-of-the-art in-helmet MEG sensor technology. However, earlier work has provided little information about how these two approaches compare, or about the reliability of observed differences. Herein, we present such a comparison, based on recordings of the N20m component of the somatosensory evoked field as elicited by electric median nerve stimulation. As expected from the proximity differences between the on-scalp and in-helmet sensors, the magnitude of the N20m activation as recorded with the on-scalp sensor was higher than that of the in-helmet sensors. The dipole pattern of the on-scalp recordings was also more spatially confined than that of the conventional recordings. Our results furthermore revealed unexpected temporal differences in the peak of the N20m component. An analysis protocol was therefore developed for assessing the reliability of this observed difference. We used this protocol to examine our findings in terms of differences in sensor sensitivity between the two types of MEG recordings. The measurements and subsequent analysis raised attention to the fact that great care has to be taken in measuring the field close to the zero-line crossing of the dipolar field, since it is heavily dependent on the orientation of sensors. Taken together, our findings provide reliable evidence that on-scalp and in-helmet sensors measure neural sources in mostly similar ways.
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Affiliation(s)
- Lau M. Andersen
- NatMEG, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- * E-mail:
| | - Robert Oostenveld
- NatMEG, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, HE Nijmegen, The Netherlands
| | - Christoph Pfeiffer
- Department of Microtechnology and Nanoscience—MC2, Chalmers University of Technology, Gothenburg, Sweden
| | - Silvia Ruffieux
- Department of Microtechnology and Nanoscience—MC2, Chalmers University of Technology, Gothenburg, Sweden
| | - Veikko Jousmäki
- NatMEG, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Department of Neuroscience and Biomedical Engineering, Aalto University, Aalto, Espoo, Finland
- Aalto NeuroImaging, Aalto University, Aalto, Espoo, Finland
| | - Matti Hämäläinen
- NatMEG, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Department of Neuroscience and Biomedical Engineering, Aalto University, Aalto, Espoo, Finland
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital/Harvard Medical School, Charlestown, MA, United States of America
- Harvard-MIT Division of Health Sciences and Technology, Cambridge, MA, United States of America
| | - Justin F. Schneiderman
- Institute of Neuroscience and Physiology, University of Gothenburg and MedTech West, Göteborg, Sweden
| | - Daniel Lundqvist
- NatMEG, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
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87
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Zerouali Y, Ghaziri J, Nguyen DK. Multimodal investigation of epileptic networks: The case of insular cortex epilepsy. PROGRESS IN BRAIN RESEARCH 2017; 226:1-33. [PMID: 27323937 DOI: 10.1016/bs.pbr.2016.04.004] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
The insula is a deep cortical structure sharing extensive synaptic connections with a variety of brain regions, including several frontal, temporal, and parietal structures. The identification of the insular connectivity network is obviously valuable for understanding a number of cognitive processes, but also for understanding epilepsy since insular seizures involve a number of remote brain regions. Ultimately, knowledge of the structure and causal relationships within the epileptic networks associated with insular cortex epilepsy can offer deeper insights into this relatively neglected type of epilepsy enabling the refining of the clinical approach in managing patients affected by it. In the present chapter, we first review the multimodal noninvasive tests performed during the presurgical evaluation of epileptic patients with drug refractory focal epilepsy, with particular emphasis on their value for the detection of insular cortex epilepsy. Second, we review the emerging multimodal investigation techniques in the field of epilepsy, that aim to (1) enhance the detection of insular cortex epilepsy and (2) unveil the architecture and causal relationships within epileptic networks. We summarize the results of these approaches with emphasis on the specific case of insular cortex epilepsy.
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Affiliation(s)
- Y Zerouali
- Research Centre, Centre hospitalier de l'Université de Montréal, Montreal, QC, Canada; Ecole Polytechnique de Montréal, Montreal, QC, Canada
| | - J Ghaziri
- Research Centre, Centre hospitalier de l'Université de Montréal, Montreal, QC, Canada
| | - D K Nguyen
- Research Centre, Centre hospitalier de l'Université de Montréal, Montreal, QC, Canada; CHUM-Hôpital Notre-Dame, Montreal, QC, Canada.
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88
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Hedrich T, Pellegrino G, Kobayashi E, Lina JM, Grova C. Comparison of the spatial resolution of source imaging techniques in high-density EEG and MEG. Neuroimage 2017; 157:531-544. [PMID: 28619655 DOI: 10.1016/j.neuroimage.2017.06.022] [Citation(s) in RCA: 77] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2016] [Revised: 04/29/2017] [Accepted: 06/09/2017] [Indexed: 11/17/2022] Open
Abstract
BACKGROUND The present study aims at evaluating and comparing electrical and magnetic distributed source imaging methods applied to high-density Electroencephalography (hdEEG) and Magnetoencephalography (MEG) data. We used resolution matrices to characterize spatial resolution properties of Minimum Norm Estimate (MNE), dynamic Statistical Parametric Mapping (dSPM), standardized Low-Resolution Electromagnetic Tomography (sLORETA) and coherent Maximum Entropy on the Mean (cMEM, an entropy-based technique). The resolution matrix provides information of the Point Spread Functions (PSF) and of the Crosstalk functions (CT), this latter being also called source leakage, as it reflects the influence of a source on its neighbors. METHODS The spatial resolution of the inverse operators was first evaluated theoretically and then with real data acquired using electrical median nerve stimulation on five healthy participants. We evaluated the Dipole Localization Error (DLE) and the Spatial Dispersion (SD) of each PSF and CT map. RESULTS cMEM showed the smallest spatial spread (SD) for both PSF and CT maps, whereas localization errors (DLE) were similar for all methods. Whereas cMEM SD values were lower in MEG compared to hdEEG, the other methods slightly favored hdEEG over MEG. In real data, cMEM provided similar localization error and significantly less spatial spread than other methods for both MEG and hdEEG. Whereas both MEG and hdEEG provided very accurate localizations, all the source imaging methods actually performed better in MEG compared to hdEEG according to all evaluation metrics, probably due to the higher signal-to-noise ratio of the data in MEG. CONCLUSION Our overall results show that all investigated methods provide similar localization errors, suggesting very accurate localization for both MEG and hdEEG when similar number of sensors are considered for both modalities. Intrinsic properties of source imaging methods as well as their behavior for well-controlled tasks, suggest an overall better performance of cMEM in regards to spatial resolution and spatial leakage for both hdEEG and MEG. This indicates that cMEM would be a good candidate for studying source localization of focal and extended generators as well as functional connectivity studies.
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Affiliation(s)
- T Hedrich
- Multimodal Functional Imaging Lab, Biomedical Engineering Dpt., McGill University, Montreal, Canada.
| | - G Pellegrino
- Multimodal Functional Imaging Lab, Biomedical Engineering Dpt., McGill University, Montreal, Canada; Neurology and Neurosurgery Department, Montreal Neurological Institute (MNI), McGill University, Montreal, Canada; San Camillo Hospital IRCCS, Venice, Italy
| | - E Kobayashi
- Neurology and Neurosurgery Department, Montreal Neurological Institute (MNI), McGill University, Montreal, Canada
| | - J M Lina
- Département de Génie Électrique, École de Technologie Supérieure, Canada; Centre de recherches mathémathiques, Université de Montréal, Montreal, Canada; Center for Advanced Research on Sleep Medecine (CEAMS), hôpital du Sacré-Coeur, Montreal, Canada
| | - C Grova
- Multimodal Functional Imaging Lab, Biomedical Engineering Dpt., McGill University, Montreal, Canada; Neurology and Neurosurgery Department, Montreal Neurological Institute (MNI), McGill University, Montreal, Canada; Physics Dpt., PERFORM Centre, Concordia University, Canada; Centre de recherches mathémathiques, Université de Montréal, Montreal, Canada
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89
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Burra N, Baker S, George N. Processing of gaze direction within the N170/M170 time window: A combined EEG/MEG study. Neuropsychologia 2017; 100:207-219. [PMID: 28450203 DOI: 10.1016/j.neuropsychologia.2017.04.028] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2016] [Revised: 04/14/2017] [Accepted: 04/22/2017] [Indexed: 11/18/2022]
Abstract
Gaze direction is an important social signal for human beings. Beside the role of gaze in attention orienting, direct gaze (that is, gaze directed toward an observer) is a highly relevant biological stimulus that elicits attention capture and increases face encoding. Brain imaging studies have emphasized the role of the superior temporal sulcus (STS) in the coding of gaze direction and in the integration of gaze and head cues of social attention. The dynamics of the processing and integration of these cues remains, however, unclear. In order to address this question, we used deviated and frontal faces with averted and direct gaze in a combined electro- and magneto- encephalography (EEG-MEG) study. We showed distinct effects of gaze direction on the N170 and M170 responses. There was an interaction between gaze direction and head orientation between 134 and 162ms in MEG and a main effect of gaze direction between 171 and 186ms in EEG. These effects involved the posterior and anterior regions of the STS respectively. Both effects also emphasized the sensitivity to direct gaze. These data highlight the central role of the STS in gaze processing.
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Affiliation(s)
- Nicolas Burra
- Faculté de Psychologie et des Sciences de l'Education, Université de Genève, Genève, Suisse; Institut du Cerveau et de la Moelle Epinière, ICM, Social and Affective Neuroscience (SAN) Laboratory and Centre MEG-EEG, Paris, France
| | - Sara Baker
- Faculty of Education, University of Cambridge, Cambridge, UK
| | - Nathalie George
- Institut du Cerveau et de la Moelle Epinière, ICM, Social and Affective Neuroscience (SAN) Laboratory and Centre MEG-EEG, Paris, France; Sorbonne Universités, UPMC Univ Paris 06, UMR_S 1127 and Centre MEG-EEG, Paris, France; CNRS, UMR 7225 and Centre MEG-EEG, Paris, France; Inserm, U 1127 and Centre MEG-EEG, Paris, France; ENS, Centre MEG-EEG, Paris, France
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90
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Legget KT, Hild AK, Steinmetz SE, Simon ST, Rojas DC. MEG and EEG demonstrate similar test-retest reliability of the 40Hz auditory steady-state response. Int J Psychophysiol 2017; 114:16-23. [PMID: 28161286 PMCID: PMC5348916 DOI: 10.1016/j.ijpsycho.2017.01.013] [Citation(s) in RCA: 30] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2016] [Revised: 01/25/2017] [Accepted: 01/31/2017] [Indexed: 01/11/2023]
Abstract
The auditory steady-state response (ASSR) is increasingly being used as a biomarker in neuropsychiatric disorders, but research investigating the test-retest reliability of this measure is needed. We previously reported ASSR reliability, measured by electroencephalography (EEG), to 40Hz amplitude-modulated white noise and click train stimuli. The purpose of the current study was to (a) assess the reliability of the MEG-measured ASSR to 40Hz amplitude-modulated white noise and click train stimuli, and (b) compare test-retest reliability between MEG and EEG measures of ASSR, which has not previously been investigated. Additionally, impact of stimulus parameter choice on reliability was assessed, by comparing responses to white noise and click train stimuli. Test-retest reliability, across sessions approximately one week apart, was assessed in 17 healthy adults. On each study day, participants completed two passive listening tasks (white noise and click train stimuli) during separate MEG and EEG recordings. Between-session correlations for evoked power and inter-trial phase coherence (ITPC) were assessed following source-space projection. Overall, the MEG-measured ASSR was significantly correlated between sessions (p<0.05, FDR corrected), suggesting acceptable test-retest reliability. Results suggest greater response reproducibility for ITPC compared to evoked responses and for click train compared to white noise stimuli, although further study is warranted. No significant differences in reliability were observed between MEG and EEG measures, suggesting they are similarly reliable. This work supports use of the ASSR as a biomarker in clinical interventions with repeated measures.
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Affiliation(s)
- Kristina T Legget
- Department of Psychiatry, University of Colorado School of Medicine, Anschutz Medical Campus, Aurora, CO, United States; Department of Medicine, University of Colorado School of Medicine, Anschutz Medical Campus, Aurora, CO, United States.
| | - Allison K Hild
- Department of Psychiatry, University of Colorado School of Medicine, Anschutz Medical Campus, Aurora, CO, United States; Department of Medicine, University of Colorado School of Medicine, Anschutz Medical Campus, Aurora, CO, United States
| | - Sarah E Steinmetz
- Department of Psychiatry, University of Colorado School of Medicine, Anschutz Medical Campus, Aurora, CO, United States; Department of Medicine, University of Colorado School of Medicine, Anschutz Medical Campus, Aurora, CO, United States
| | - Steven T Simon
- Department of Medicine, University of Colorado School of Medicine, Anschutz Medical Campus, Aurora, CO, United States
| | - Donald C Rojas
- Department of Psychology, Colorado State University, Fort Collins, CO, United States
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91
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Knyazev GG, Savostyanov AN, Bocharov AV, Slobodskaya HR, Bairova NB, Tamozhnikov SS, Stepanova VV. Effortful control and resting state networks: A longitudinal EEG study. Neuroscience 2017; 346:365-381. [DOI: 10.1016/j.neuroscience.2017.01.031] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2016] [Revised: 01/14/2017] [Accepted: 01/17/2017] [Indexed: 10/20/2022]
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92
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Southwell R, Baumann A, Gal C, Barascud N, Friston K, Chait M. Is predictability salient? A study of attentional capture by auditory patterns. Philos Trans R Soc Lond B Biol Sci 2017; 372:rstb.2016.0105. [PMID: 28044016 PMCID: PMC5206273 DOI: 10.1098/rstb.2016.0105] [Citation(s) in RCA: 66] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/28/2016] [Indexed: 01/08/2023] Open
Abstract
In this series of behavioural and electroencephalography (EEG) experiments, we investigate the extent to which repeating patterns of sounds capture attention. Work in the visual domain has revealed attentional capture by statistically predictable stimuli, consistent with predictive coding accounts which suggest that attention is drawn to sensory regularities. Here, stimuli comprised rapid sequences of tone pips, arranged in regular (REG) or random (RAND) patterns. EEG data demonstrate that the brain rapidly recognizes predictable patterns manifested as a rapid increase in responses to REG relative to RAND sequences. This increase is reminiscent of the increase in gain on neural responses to attended stimuli often seen in the neuroimaging literature, and thus consistent with the hypothesis that predictable sequences draw attention. To study potential attentional capture by auditory regularities, we used REG and RAND sequences in two different behavioural tasks designed to reveal effects of attentional capture by regularity. Overall, the pattern of results suggests that regularity does not capture attention. This article is part of the themed issue ‘Auditory and visual scene analysis’.
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Affiliation(s)
- Rosy Southwell
- Ear Institute, University College London, London WC1X 8EE, UK
| | - Anna Baumann
- Ear Institute, University College London, London WC1X 8EE, UK
| | - Cécile Gal
- Ear Institute, University College London, London WC1X 8EE, UK
| | | | - Karl Friston
- Wellcome Trust Centre for Neuroimaging, University College London, London WC1N 3BG, UK
| | - Maria Chait
- Ear Institute, University College London, London WC1X 8EE, UK
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93
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Sohrabpour A, Ye S, Worrell GA, Zhang W, He B. Noninvasive Electromagnetic Source Imaging and Granger Causality Analysis: An Electrophysiological Connectome (eConnectome) Approach. IEEE Trans Biomed Eng 2016; 63:2474-2487. [PMID: 27740473 PMCID: PMC5152676 DOI: 10.1109/tbme.2016.2616474] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023]
Abstract
OBJECTIVE Combined source-imaging techniques and directional connectivity analysis can provide useful information about the underlying brain networks in a noninvasive fashion. Source-imaging techniques have been used successfully to either determine the source of activity or to extract source time-courses for Granger causality analysis, previously. In this work, we utilize source-imaging algorithms to both find the network nodes [regions of interest (ROI)] and then extract the activation time series for further Granger causality analysis. The aim of this work is to find network nodes objectively from noninvasive electromagnetic signals, extract activation time-courses, and apply Granger analysis on the extracted series to study brain networks under realistic conditions. METHODS Source-imaging methods are used to identify network nodes and extract time-courses and then Granger causality analysis is applied to delineate the directional functional connectivity of underlying brain networks. Computer simulations studies where the underlying network (nodes and connectivity pattern) is known were performed; additionally, this approach has been evaluated in partial epilepsy patients to study epilepsy networks from interictal and ictal signals recorded by EEG and/or Magnetoencephalography (MEG). RESULTS Localization errors of network nodes are less than 5 mm and normalized connectivity errors of ∼20% in estimating underlying brain networks in simulation studies. Additionally, two focal epilepsy patients were studied and the identified nodes driving the epileptic network were concordant with clinical findings from intracranial recordings or surgical resection. CONCLUSION Our study indicates that combined source-imaging algorithms with Granger causality analysis can identify underlying networks precisely (both in terms of network nodes location and internodal connectivity). SIGNIFICANCE The combined source imaging and Granger analysis technique is an effective tool for studying normal or pathological brain conditions.
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Affiliation(s)
- Abbas Sohrabpour
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN 55455 USA
| | - Shuai Ye
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN 55455 USA
| | | | - Wenbo Zhang
- Minnesota Epilepsy Group, United Hospital, MN 55102 USA and also with the Department of Neurology, University of Minnesota, Minneapolis, 55455 USA
| | - Bin He
- Department of Biomedical Engineering, and the Institute for Engineering in Medicine, University of Minnesota, Minneapolis, MN 55455 USA
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94
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Complex patterns of spatially extended generators of epileptic activity: Comparison of source localization methods cMEM and 4-ExSo-MUSIC on high resolution EEG and MEG data. Neuroimage 2016; 143:175-195. [DOI: 10.1016/j.neuroimage.2016.08.044] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2016] [Revised: 08/18/2016] [Accepted: 08/20/2016] [Indexed: 11/23/2022] Open
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95
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Abstract
Magnetoencephalography (MEG) is a method to study electrical activity in the human brain by recording the neuromagnetic field outside the head. MEG, like electroencephalography (EEG), provides an excellent, millisecond-scale time resolution, and allows the estimation of the spatial distribution of the underlying activity, in favorable cases with a localization accuracy of a few millimeters. To detect the weak neuromagnetic signals, superconducting sensors, magnetically shielded rooms, and advanced signal processing techniques are used. The analysis and interpretation of MEG data typically involves comparisons between subject groups and experimental conditions using various spatial, temporal, and spectral measures of cortical activity and connectivity. The application of MEG to cognitive neuroscience studies is illustrated with studies of spoken language processing in subjects with normal and impaired reading ability. The mapping of spatiotemporal patterns of activity within networks of cortical areas can provide useful information about the functional architecture of the brain related to sensory and cognitive processing, including language, memory, attention, and perception.
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Affiliation(s)
- Seppo P Ahlfors
- MGH/HST Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, 149 13th St., Mailcode 149-2301, Charlestown, MA 02129; U.S.A. Tel. +1-617-726-0663
| | - Maria Mody
- MGH/HST Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, 149 13th St., Mailcode 149-2301, Charlestown, MA 02129; U.S.A. Tel. +1-617-726-0663
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96
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Babo-Rebelo M, Wolpert N, Adam C, Hasboun D, Tallon-Baudry C. Is the cardiac monitoring function related to the self in both the default network and right anterior insula? Philos Trans R Soc Lond B Biol Sci 2016; 371:rstb.2016.0004. [PMID: 28080963 PMCID: PMC5062094 DOI: 10.1098/rstb.2016.0004] [Citation(s) in RCA: 44] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/05/2016] [Indexed: 11/12/2022] Open
Abstract
The self has been proposed to be rooted in the neural monitoring of internal bodily signals and might thus involve interoceptive areas, notably the right anterior insula (rAI). However, studies on the self consistently showed the involvement of midline default network (DN) nodes, without referring to visceral monitoring. Here, we investigate this apparent discrepancy. We previously showed that neural responses to heartbeats in the DN encode two different self-dimensions, the agentive ‘I’ and the introspective ‘Me’, in a whole-brain analysis of magnetoencephalography (MEG) data. Here, we confirm and anatomically refine this result with intracranial recordings (intracranial electroencephalography, iEEG). In two patients, we show a parametric modulation of neural responses to heartbeats by the self-relatedness of thoughts, at the single trial level. A region-of-interest analysis of the insula reveals that MEG responses to heartbeats in the rAI encode the ‘I’ self-dimension. The effect in rAI was weaker than in the DN and was replicated in iEEG data in one patient out of two. We propose that a common mechanism, the neural monitoring of cardiac signals, underlies the self in both the DN and rAI. This might reconcile studies on the self highlighting the DN, with studies on interoception focusing on the insula. This article is part of the themed issue ‘Interoception beyond homeostasis: affect, cognition and mental health’.
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Affiliation(s)
- Mariana Babo-Rebelo
- Laboratoire de Neurosciences Cognitives (ENS - INSERM U960), Département d'Etudes Cognitives, Ecole Normale Supérieure - PSL Research University, 75005 Paris, France
| | - Nicolai Wolpert
- Laboratoire de Neurosciences Cognitives (ENS - INSERM U960), Département d'Etudes Cognitives, Ecole Normale Supérieure - PSL Research University, 75005 Paris, France
| | - Claude Adam
- AP-HP, Groupe Hospitalier Pitié-Salpêtrière, Paris 75013, France
| | | | - Catherine Tallon-Baudry
- Laboratoire de Neurosciences Cognitives (ENS - INSERM U960), Département d'Etudes Cognitives, Ecole Normale Supérieure - PSL Research University, 75005 Paris, France
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97
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Manca AD, Grimaldi M. Vowels and Consonants in the Brain: Evidence from Magnetoencephalographic Studies on the N1m in Normal-Hearing Listeners. Front Psychol 2016; 7:1413. [PMID: 27713712 PMCID: PMC5031792 DOI: 10.3389/fpsyg.2016.01413] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2016] [Accepted: 09/05/2016] [Indexed: 01/07/2023] Open
Abstract
Speech sound perception is one of the most fascinating tasks performed by the human brain. It involves a mapping from continuous acoustic waveforms onto the discrete phonological units computed to store words in the mental lexicon. In this article, we review the magnetoencephalographic studies that have explored the timing and morphology of the N1m component to investigate how vowels and consonants are computed and represented within the auditory cortex. The neurons that are involved in the N1m act to construct a sensory memory of the stimulus due to spatially and temporally distributed activation patterns within the auditory cortex. Indeed, localization of auditory fields maps in animals and humans suggested two levels of sound coding, a tonotopy dimension for spectral properties and a tonochrony dimension for temporal properties of sounds. When the stimulus is a complex speech sound, tonotopy and tonochrony data may give important information to assess whether the speech sound parsing and decoding are generated by pure bottom-up reflection of acoustic differences or whether they are additionally affected by top-down processes related to phonological categories. Hints supporting pure bottom-up processing coexist with hints supporting top-down abstract phoneme representation. Actually, N1m data (amplitude, latency, source generators, and hemispheric distribution) are limited and do not help to disentangle the issue. The nature of these limitations is discussed. Moreover, neurophysiological studies on animals and neuroimaging studies on humans have been taken into consideration. We compare also the N1m findings with the investigation of the magnetic mismatch negativity (MMNm) component and with the analogous electrical components, the N1 and the MMN. We conclude that N1 seems more sensitive to capture lateralization and hierarchical processes than N1m, although the data are very preliminary. Finally, we suggest that MEG data should be integrated with EEG data in the light of the neural oscillations framework and we propose some concerns that should be addressed by future investigations if we want to closely line up language research with issues at the core of the functional brain mechanisms.
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Affiliation(s)
- Anna Dora Manca
- Dipartimento di Studi Umanistici, Centro di Ricerca Interdisciplinare sul Linguaggio, University of SalentoLecce, Italy; Laboratorio Diffuso di Ricerca Interdisciplinare Applicata alla MedicinaLecce, Italy
| | - Mirko Grimaldi
- Dipartimento di Studi Umanistici, Centro di Ricerca Interdisciplinare sul Linguaggio, University of SalentoLecce, Italy; Laboratorio Diffuso di Ricerca Interdisciplinare Applicata alla MedicinaLecce, Italy
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98
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Drakesmith M, El-Deredy W, Welbourne S. Differential Phonological and Semantic Modulation of Neurophysiological Responses to Visual Word Recognition. Neuropsychobiology 2016; 72:46-56. [PMID: 26337735 DOI: 10.1159/000379752] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/30/2014] [Accepted: 06/15/2015] [Indexed: 11/19/2022]
Abstract
BACKGROUND Reading words for meaning relies on orthographic, phonological and semantic processing. The triangle model implicates a direct orthography-to-semantics pathway and a phonologically mediated orthography-to-semantics pathway, which interact with each other. The temporal evolution of processing in these routes is not well understood, although theoretical evidence predicts early phonological processing followed by interactive phonological and semantic processing. METHOD This study used electroencephalography-event-related potential (ERP) analysis and magnetoencephalography (MEG) source localisation to identify temporal markers and the corresponding neural generators of these processes in early (∼200 ms) and late (∼400 ms) neurophysiological responses to visual words, pseudowords and consonant strings. RESULTS ERP showed an effect of phonology but not semantics in both time windows, although at ∼400 ms there was an effect of stimulus familiarity. Phonological processing at ~200 ms was localised to the left occipitotemporal cortex and the inferior frontal gyrus. At 400 ms, there was continued phonological processing in the inferior frontal gyrus and additional semantic processing in the anterior temporal cortex. There was also an area in the left temporoparietal junction which was implicated in both phonological and semantic processing. In ERP, the semantic response at ∼400 ms appeared to be masked by concurrent processes relating to familiarity, while MEG successfully differentiated these processes. DISCUSSION The results support the prediction of early phonological processing followed by an interaction of phonological and semantic processing during word recognition. Neuroanatomical loci of these processes are consistent with previous neuropsychological and functional magnetic resonance imaging studies. The results also have implications for the classical interpretation of N400-like responses as markers for semantic processing.
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99
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Hunold A, Funke ME, Eichardt R, Stenroos M, Haueisen J. EEG and MEG: sensitivity to epileptic spike activity as function of source orientation and depth. Physiol Meas 2016; 37:1146-62. [DOI: 10.1088/0967-3334/37/7/1146] [Citation(s) in RCA: 35] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
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100
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Knyazev GG, Savostyanov AN, Bocharov AV, Tamozhnikov SS, Saprigyn AE. Task-positive and task-negative networks and their relation to depression: EEG beamformer analysis. Behav Brain Res 2016; 306:160-9. [PMID: 27001453 DOI: 10.1016/j.bbr.2016.03.033] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2015] [Revised: 03/12/2016] [Accepted: 03/18/2016] [Indexed: 02/06/2023]
Abstract
Major Depressive Disorder (MDD) has been associated with predominance of the default-mode network (DMN) over the task-positive network (TPN), which is considered a neurobiological base for ruminative responding. It is not known whether this predominance is a signature of the full-blown MDD or it already exists at preclinical stages. Besides, all relevant evidence has been obtained using fMRI, which allows for a precise spatial characterization of resting state networks (RSNs), but their neural correlates remain elusive. Here we show that after leakage correction of beamformer-projected resting EEG time series, seed-based oscillatory-power envelope correlation analysis allows revealing RSNs with significant similarity to respective fMRI RSNs. In a non-clinical sample, depressive symptoms, as measured by the Beck Depression Inventory, are associated with predominance of DMN over TPN connectivity in the right insula and the right temporal lobe in the delta frequency band. These findings imply that in individuals with heightened level of depressive symptoms, emotional circuits are stronger connected with DMN than TPN and should be more easily engaged in self-referential rumination than in responding to environmental challenges. The study's findings are in agreement with fMRI evidence, thus confirming the neural base of the observed in fMRI research effects and showing that implicated in depression neural mechanism may already be in action even at preclinical stages.
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Affiliation(s)
- Gennady G Knyazev
- Institute of Physiology and Basic Medicine, Timakova str., 4, Novosibirsk 630117, Russia.
| | - Alexander N Savostyanov
- Institute of Physiology and Basic Medicine, Timakova str., 4, Novosibirsk 630117, Russia; Novosibirsk State University, Pirogova str., 2, Novosibirsk 630090, Russia
| | - Andrey V Bocharov
- Institute of Physiology and Basic Medicine, Timakova str., 4, Novosibirsk 630117, Russia; Novosibirsk State University, Pirogova str., 2, Novosibirsk 630090, Russia
| | - Sergey S Tamozhnikov
- Institute of Physiology and Basic Medicine, Timakova str., 4, Novosibirsk 630117, Russia
| | - Alexander E Saprigyn
- Institute of Physiology and Basic Medicine, Timakova str., 4, Novosibirsk 630117, Russia
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