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Nono AST, Anziano M, Mouthon M, Chabwine JN, Spierer L. The Role of Anatomic Connectivity in Inhibitory Control Revealed by Combining Connectome-based Lesion-symptom Mapping with Event-related Potentials. Brain Topogr 2024; 37:1033-1042. [PMID: 38858320 PMCID: PMC11408543 DOI: 10.1007/s10548-024-01057-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2024] [Accepted: 05/10/2024] [Indexed: 06/12/2024]
Abstract
Inhibitory control refers to the ability to suppress cognitive or motor processes. Current neurocognitive models indicate that this function mainly involves the anterior cingulate cortex and the inferior frontal cortex. However, how the communication between these areas influence inhibitory control performance and their functional response remains unknown. We addressed this question by injecting behavioral and electrophysiological markers of inhibitory control recorded during a Go/NoGo task as the 'symptoms' in a connectome-based lesion-symptom mapping approach in a sample of 96 first unilateral stroke patients. This approach enables us to identify the white matter tracts whose disruption by the lesions causally influences brain functional activity during inhibitory control. We found a central role of left frontotemporal and frontobasal intrahemispheric connections, as well as of the connections between the left temporoparietal and right temporal areas in inhibitory control performance. We also found that connections between the left temporal and right superior parietal areas modulate the conflict-related N2 event-related potential component and between the left temporal parietal area and right temporal and occipital areas for the inhibition P3 component. Our study supports the role of a distributed bilateral network in inhibitory control and reveals that combining lesion-symptom mapping approaches with functional indices of cognitive processes could shed new light on post-stroke functional reorganization. It may further help to refine the interpretation of classical electrophysiological markers of executive control in stroke patients.
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Affiliation(s)
- Alex S T Nono
- Laboratory for Neurorehabilitation Science, Medicine Section, Faculty of Science and Medicine, University of Fribourg, PER 09, Chemin du Musée 5, 1700, Fribourg, Switzerland
| | - Marco Anziano
- Laboratory for Neurorehabilitation Science, Medicine Section, Faculty of Science and Medicine, University of Fribourg, PER 09, Chemin du Musée 5, 1700, Fribourg, Switzerland
| | - Michael Mouthon
- Laboratory for Neurorehabilitation Science, Medicine Section, Faculty of Science and Medicine, University of Fribourg, PER 09, Chemin du Musée 5, 1700, Fribourg, Switzerland
| | - Joelle N Chabwine
- Laboratory for Neurorehabilitation Science, Medicine Section, Faculty of Science and Medicine, University of Fribourg, PER 09, Chemin du Musée 5, 1700, Fribourg, Switzerland
- Neurology Unit, Department of Internal Medicine and Specialties, Fribourg Hospital, Fribourg, Switzerland
| | - Lucas Spierer
- Laboratory for Neurorehabilitation Science, Medicine Section, Faculty of Science and Medicine, University of Fribourg, PER 09, Chemin du Musée 5, 1700, Fribourg, Switzerland.
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2
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Lin Y, Atad D, Zanesco AP. Using EEG to advance mindfulness science: A survey of emerging methods and approaches. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2024:S2451-9022(24)00280-5. [PMID: 39369988 DOI: 10.1016/j.bpsc.2024.09.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/15/2024] [Revised: 09/22/2024] [Accepted: 09/25/2024] [Indexed: 10/08/2024]
Abstract
Throughout the brief history of contemplative neuroscience, electroencephalography (EEG) has been a valuable and enduring methodology used to elucidate the neural correlates and mechanisms of mindfulness. In this review article, we provide a reminder that longevity should not be conflated with obsoletion, and that EEG continues to offer exceptional promise for addressing key questions and challenges that pervade the field today. Toward this end, we outline the unique advantages of EEG from a research strategy and experimental design perspective, before highlighting an array of new sophisticated data analytic approaches and translational paradigms. Along the way, we provide illustrative examples from our own work and the broader literature to showcase how these innovations can be leveraged to spark new insights and stimulate progress across both basic science and translational applications of mindfulness. Ultimately, we argue that EEG still has much to contribute to contemplative neuroscience, and hope to solicit the interest of other investigators to make full use of its capabilities in service of maximizing its potential within the field.
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Affiliation(s)
- Yanli Lin
- Department of Psychological Science, University of Arkansas, Fayetteville, Arkansas, USA.
| | - Daniel Atad
- Faculty of Education, Department of Counseling and Human Development, University of Haifa, Haifa, Israel; The Integrated Brain and Behavior Research Center (IBBRC), University of Haifa, Haifa, Israel; Edmond Safra Brain Research Center, Faculty of Education, University of Haifa, Haifa, Israel
| | - Anthony P Zanesco
- Department of Psychology, University of Kentucky, Lexington, Kentucky, USA
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3
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Wong BWL, Huo S, Maurer U. Adaptation patterns and their associations with mismatch negativity: An electroencephalogram (EEG) study with controlled expectations. Eur J Neurosci 2024. [PMID: 39363511 DOI: 10.1111/ejn.16546] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Revised: 07/20/2024] [Accepted: 08/29/2024] [Indexed: 10/05/2024]
Abstract
Adaptation refers to the decreased neural response that occurs after repeated exposure to a stimulus. While many electroencephalogram (EEG) studies have investigated adaptation by using either single or multiple repetitions, the adaptation patterns under controlled expectations manifested in the two main auditory components, N1 and P2, are still largely unknown. Additionally, although multiple repetitions are commonly used in mismatch negativity (MMN) experiments, it is unclear how adaptation at different time windows contributes to this phenomenon. In this study, we conducted an EEG experiment with 37 healthy adults using a random stimulus arrangement and extended tone sequences to control expectations. We tracked the amplitudes of the N1 and P2 components across the first 10 tones to examine adaptation patterns. Our findings revealed an L-shaped adaptation pattern characterised by a significant decrease in N1 amplitude after the first repetition (N1 initial adaptation), followed by a continuous, linear increase in P2 amplitude after the first repetition (P2 subsequent adaptation), possibly indicating model adjustment. Regression analysis demonstrated that the peak amplitudes of both the N1 initial adaptation and the P2 subsequent adaptation significantly accounted for variance in MMN amplitude. These results suggest distinct adaptation patterns for multiple repetitions across different components and indicate that the MMN reflects a combination of two processes: the initial adaptation in the N1 and a continuous model adjustment effect in the P2. Understanding these processes separately could have implications for models of cognitive processing and clinical disorders.
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Affiliation(s)
- Brian W L Wong
- Department of Psychology, The Chinese University of Hong Kong, Hong Kong, China
- BCBL, Basque Center on Brain, Language and Cognition, Donostia-San Sebastián, Spain
| | - Shuting Huo
- Department of Psychology, The Chinese University of Hong Kong, Hong Kong, China
- Department of Applied Social Sciences, The Hong Kong Polytechnic University, Hong Kong, China
| | - Urs Maurer
- Department of Psychology, The Chinese University of Hong Kong, Hong Kong, China
- Brain and Mind Institute, The Chinese University of Hong Kong, Hong Kong, China
- Centre for Developmental Psychology, The Chinese University of Hong Kong, Hong Kong, China
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4
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Toffoli L, Zdorovtsova N, Epihova G, Duma GM, Cristaldi FDP, Pastore M, Astle DE, Mento G. Dynamic transient brain states in preschoolers mirror parental report of behavior and emotion regulation. Hum Brain Mapp 2024; 45:e70011. [PMID: 39327923 PMCID: PMC11427750 DOI: 10.1002/hbm.70011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2024] [Revised: 08/01/2024] [Accepted: 08/13/2024] [Indexed: 09/28/2024] Open
Abstract
The temporal dynamics of resting-state networks may represent an intrinsic functional repertoire supporting cognitive control performance across the lifespan. However, little is known about brain dynamics during the preschool period, which is a sensitive time window for cognitive control development. The fast timescale of synchronization and switching characterizing cortical network functional organization gives rise to quasi-stable patterns (i.e., brain states) that recur over time. These can be inferred at the whole-brain level using hidden Markov models (HMMs), an unsupervised machine learning technique that allows the identification of rapid oscillatory patterns at the macroscale of cortical networks. The present study used an HMM technique to investigate dynamic neural reconfigurations and their associations with behavioral (i.e., parental questionnaires) and cognitive (i.e., neuropsychological tests) measures in typically developing preschoolers (4-6 years old). We used high-density EEG to better capture the fast reconfiguration patterns of the HMM-derived metrics (i.e., switching rates, entropy rates, transition probabilities and fractional occupancies). Our results revealed that the HMM-derived metrics were reliable indices of individual neural variability and differed between boys and girls. However, only brain state transition patterns toward prefrontal and default-mode brain states, predicted differences on parental-report questionnaire scores. Overall, these findings support the importance of resting-state brain dynamics as functional scaffolds for behavior and cognition. Brain state transitions may be crucial markers of individual differences in cognitive control development in preschoolers.
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Affiliation(s)
- Lisa Toffoli
- NeuroDev Lab, Department of General PsychologyUniversity of PaduaPaduaItaly
| | | | - Gabriela Epihova
- MRC Cognition and Brain Sciences UnitUniversity of CambridgeCambridgeUK
| | - Gian Marco Duma
- Scientific Institute, IRCCS E. Medea, ConeglianoTrevisoItaly
| | | | - Massimiliano Pastore
- Department of Developmental Psychology and SocialisationUniversity of PaduaPaduaItaly
| | - Duncan E. Astle
- MRC Cognition and Brain Sciences UnitUniversity of CambridgeCambridgeUK
- Department of PsychiatryUniversity of CambridgeCambridgeUK
| | - Giovanni Mento
- NeuroDev Lab, Department of General PsychologyUniversity of PaduaPaduaItaly
- Scientific Institute, IRCCS E. Medea, ConeglianoTrevisoItaly
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Yun S. Advances, challenges, and prospects of electroencephalography-based biomarkers for psychiatric disorders: a narrative review. JOURNAL OF YEUNGNAM MEDICAL SCIENCE 2024; 41:261-268. [PMID: 39246060 DOI: 10.12701/jyms.2024.00668] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/01/2024] [Accepted: 08/09/2024] [Indexed: 09/10/2024]
Abstract
Owing to a lack of appropriate biomarkers for accurate diagnosis and treatment, psychiatric disorders cause significant distress and functional impairment, leading to social and economic losses. Biomarkers are essential for diagnosing, predicting, treating, and monitoring various diseases. However, their absence in psychiatry is linked to the complex structure of the brain and the lack of direct monitoring modalities. This review examines the potential of electroencephalography (EEG) as a neurophysiological tool for identifying psychiatric biomarkers. EEG noninvasively measures brain electrophysiological activity and is used to diagnose neurological disorders, such as depression, bipolar disorder (BD), and schizophrenia, and identify psychiatric biomarkers. Despite extensive research, EEG-based biomarkers have not been clinically utilized owing to measurement and analysis constraints. EEG studies have revealed spectral and complexity measures for depression, brainwave abnormalities in BD, and power spectral abnormalities in schizophrenia. However, no EEG-based biomarkers are currently used clinically for the treatment of psychiatric disorders. The advantages of EEG include real-time data acquisition, noninvasiveness, cost-effectiveness, and high temporal resolution. Challenges such as low spatial resolution, susceptibility to interference, and complexity of data interpretation limit its clinical application. Integrating EEG with other neuroimaging techniques, advanced signal processing, and standardized protocols is essential to overcome these limitations. Artificial intelligence may enhance EEG analysis and biomarker discovery, potentially transforming psychiatric care by providing early diagnosis, personalized treatment, and improved disease progression monitoring.
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Affiliation(s)
- Seokho Yun
- Department of Psychiatry, Yeungnam University College of Medicine, Daegu, Korea
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6
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Wang L, Li M, Xu D, Yang Y. Cortical ROI Importance Improves MI Decoding From EEG Using Fused Light Neural Network. IEEE Trans Neural Syst Rehabil Eng 2024; 32:3636-3646. [PMID: 39283802 DOI: 10.1109/tnsre.2024.3461339] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/26/2024]
Abstract
Decoding motor imagery (MI) using deep learning in cortical level has potential in brain computer interface based intelligent rehabilitation. However, a mass of dipoles is inconvenient to extract the personalized features and requires a more complex neural network. In consideration of the structural and functional similarity of the neurons in a neuroanatomical region, i.e., a region of interest (ROI), we propose that the comprehensive performance of each ROI may be reflected by a specific representative dipole (RD), and the time-frequency spectrums of all RDs are applied simultaneously to Random Forest algorithm to give a quantitative metric of each ROI importance (RI). Then, the more divided sub-band spectral powers are reinforced by RI, and they are interpolated to a 2-dimensional (2D) plane transformed from 3D space of all RDs, yielding an ensemble representation of RD feature image sequences (ERDFIS). Furthermore, a lightweight network, including 2D separable convolution and gated recurrent unit (2DSCG), is developed to extract and classify the frequency-spatial and temporal features from ERDFIS, forming a novel MI decoding method in cortical level (called ERDFIS-2DSCG). Based on two public datasets, the decoding accuracies of ten-fold cross-validation are 89.89% and 94.35%, respectively. The results suggest that RD can embody the overall property of ROI in time-frequency-space domains, and ROI importance is helpful to highlight the subject-based characteristics of MI-EEG. Meanwhile, 2DSCG is matched well with ERDFIS, jointly improving the decoding performance.
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Tanaka K, Tsukahara A, Miyanaga H, Tsunematsu S, Kato T, Matsubara Y, Sakai H. Superconducting Self-Shielded and Zero-Boil-Off Magnetoencephalogram Systems: A Dry Phantom Evaluation. SENSORS (BASEL, SWITZERLAND) 2024; 24:6044. [PMID: 39338790 PMCID: PMC11435837 DOI: 10.3390/s24186044] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/01/2024] [Revised: 09/11/2024] [Accepted: 09/16/2024] [Indexed: 09/30/2024]
Abstract
Magnetoencephalography (MEG) systems are advanced neuroimaging tools used to measure the magnetic fields produced by neuronal activity in the human brain. However, they require significant amounts of liquid helium to keep the superconducting quantum interference device (SQUID) sensors in a stable superconducting state. Additionally, MEG systems must be installed in a magnetically shielded room to minimize interference from external magnetic fields. We have developed an advanced MEG system that incorporates a superconducting magnetic shield and a zero-boil-off system. This system overcomes the typical limitations of traditional MEG systems, such as the frequent need for liquid helium refills and the spatial constraints imposed by magnetically shielded rooms. To validate the system, we conducted an evaluation using signal source estimation. This involved a phantom with 50 current sources of known location and magnitude under active zero-boil-off conditions. Our evaluations focused on the precision of the magnetic field distribution and the quantification of estimation errors. We achieved a consistent magnetic field distribution that matched the source current, maintaining an estimation error margin within 3.5 mm, regardless of the frequency of the signal source current. These findings affirm the practicality and efficacy of the system.
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Affiliation(s)
- Keita Tanaka
- Department of Science and Engineering, Tokyo Denki University, Saitama 350-0394, Japan
| | - Akihiko Tsukahara
- Department of Science and Engineering, Tokyo Denki University, Saitama 350-0394, Japan
| | | | | | - Takanori Kato
- Sumitomo Heavy Industries, Ltd., Yokosuka 237-0061, Japan
| | - Yuji Matsubara
- Sumitomo Heavy Industries, Ltd., Yokosuka 237-0061, Japan
| | - Hiromu Sakai
- Faculty of Science and Engineering, Waseda University, Tokyo 169-8555, Japan
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8
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Liu S, Yang S, Feng K, Wang C, Wang L. A Study on the Effects of Repetitive Transcranial Magnetic Stimulation on EEG Microstate in Patients With Parkinson's Disease. IEEE Trans Neural Syst Rehabil Eng 2024; 32:3369-3377. [PMID: 38917289 DOI: 10.1109/tnsre.2024.3418846] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/27/2024]
Abstract
Repetitive transcranial magnetic stimulation (rTMS) is a non-invasive neuromodulation technology that can modulate cerebral cortical excitability. Electroencephalography (EEG) microstate analysis is an important tool for studying dynamic changes in brain functional activity. This study explores the pathophysiological changes in Parkinson's disease (PD) patients by analyzing the EEG microstate of PD patients, and analyzes the impact of rTMS on the clinical symptoms of PD patients. In a trial, 25 patients with PD and 18 healthy subjects of the same age were included. The clinical scale (the third part of Movement Disorder Society-Sponsored Revision of the Unified Parkinson's Disease Rating Scale (UPDRS-III) and Montreal Cognitive Assessment (MoCA)) scores of each patient were evaluated and the microstate characteristic parameters of all subjects were calculated. 10 Hz rTMS was used to stimulate the bilateral primary motor cortex (M1) of PD patients. After two weeks of treatment (10 times), the clinical scale score of each patient was re-evaluated and the microstate characteristic parameters were calculated. At the baseline, the occurrence, duration and coverage of microstate C in PD patients were significantly higher than those in healthy controls (P <0.05),and were significantly negatively correlated with the MoCA score (P <0.05). The duration and coverage of microstate D in PD patients were significantly lower than those in healthy controls (P <0.05), and were significantly negatively correlated with UPDRS-III score (P <0.05). After rTMS treatment in the PD group, the scale score of UPDRS-III was significantly reduced (P <0.05) and the scale score of MoCA was significantly increased. Moreover, the occurrence and coverage of microstate B were significantly increased (p <0.05). The occurrence, duration and coverage of microstate C were significantly reduced (P <0.05). The occurrence, duration and coverage of microstate D were significantly increased (P <0.05). This study shows that abnormal brain functional activity of PD patients can change microstate characteristic parameters, and these changes are significantly related to the decline of motor and cognitive functions. Furthermore, rTMS can improve the motor and cognitive functions and adjust the microstate characteristic parameters of PD patients. EEG microstate analysis can reflect the therapeutic effect of rTMS on PD patients.
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Leupin V, Britz J. Interoceptive signals shape the earliest markers and neural pathway to awareness at the visual threshold. Proc Natl Acad Sci U S A 2024; 121:e2311953121. [PMID: 39226342 PMCID: PMC11406234 DOI: 10.1073/pnas.2311953121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Accepted: 05/28/2024] [Indexed: 09/05/2024] Open
Abstract
Variations in interoceptive signals from the baroreceptors (BRs) across the cardiac and respiratory cycle can modulate cortical excitability and so affect awareness. It remains debated at what stages of processing they affect awareness-related event-related potentials (ERPs) in different sensory modalities. We investigated the influence of the cardiac (systole/diastole) and the respiratory (inhalation/exhalation) phase on awareness-related ERPs. Subjects discriminated visual threshold stimuli while their electroencephalogram, electrocardiogram, and respiration were simultaneously recorded. We compared ERPs and their intracranial generators for stimuli classified correctly with and without awareness as a function of the cardiac and respiratory phase. Cyclic variations of interoceptive signals from the BRs modulated both the earliest electrophysiological markers and the trajectory of brain activity when subjects became aware of the stimuli: an early sensory component (P1) was the earliest marker of awareness for low (diastole/inhalation) and a perceptual component (visual awareness negativity) for high (systole/exhalation) BR activity, indicating that BR signals interfere with the sensory processing of the visual input. Likewise, activity spread from the primary visceral cortex (posterior insula) to posterior parietal cortices during high and from associative interoceptive centers (anterior insula) to the prefrontal cortex during low BR activity. Consciousness is thereby resolved in cognitive/associative regions when BR is low and in perceptual centers when it is high. Our results suggest that cyclic fluctuations of BR signaling affect both the earliest markers of awareness and the brain processes underlying conscious awareness.
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Affiliation(s)
- Viviana Leupin
- Department of Psychology, University of Fribourg, Fribourg CH-1700, Switzerland
| | - Juliane Britz
- Department of Psychology, University of Fribourg, Fribourg CH-1700, Switzerland
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Cheng S, Wang J, Luo R, Hao N. Brain to brain musical interaction: A systematic review of neural synchrony in musical activities. Neurosci Biobehav Rev 2024; 164:105812. [PMID: 39029879 DOI: 10.1016/j.neubiorev.2024.105812] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2024] [Revised: 07/02/2024] [Accepted: 07/13/2024] [Indexed: 07/21/2024]
Abstract
The use of hyperscanning technology has revealed the neural mechanisms underlying multi-person interaction in musical activities. However, there is currently a lack of integration among various research findings. This systematic review aims to provide a comprehensive understanding of the social dynamics and brain synchronization in music activities through the analysis of 32 studies. The findings illustrate a strong correlation between inter-brain synchronization (IBS) and various musical activities, with the frontal, central, parietal, and temporal lobes as the primary regions involved. The application of hyperscanning not only advances theoretical research but also holds practical significance in enhancing the effectiveness of music-based interventions in therapy and education. The review also utilizes Predictive Coding Models (PCM) to provide a new perspective for interpreting neural synchronization in music activities. To address the limitations of current research, future studies could integrate multimodal data, adopt novel technologies, use non-invasive techniques, and explore additional research directions.
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Affiliation(s)
- Shate Cheng
- Shanghai Key Laboratory of Mental Health and Psychological Crisis Intervention, School of Psychology and Cognitive Science, East China Normal University, Shanghai 200062, China; Key Laboratory of Philosophy and Social Science of Anhui Province on Adolescent Mental Health and Crisis Intelligence Intervention, Hefei Normal University, Hefei 200062, China.
| | - Jiayi Wang
- Shanghai Key Laboratory of Mental Health and Psychological Crisis Intervention, School of Psychology and Cognitive Science, East China Normal University, Shanghai 200062, China; Key Laboratory of Philosophy and Social Science of Anhui Province on Adolescent Mental Health and Crisis Intelligence Intervention, Hefei Normal University, Hefei 200062, China.
| | - Ruiyi Luo
- Shanghai Key Laboratory of Mental Health and Psychological Crisis Intervention, School of Psychology and Cognitive Science, East China Normal University, Shanghai 200062, China; Key Laboratory of Philosophy and Social Science of Anhui Province on Adolescent Mental Health and Crisis Intelligence Intervention, Hefei Normal University, Hefei 200062, China.
| | - Ning Hao
- Shanghai Key Laboratory of Mental Health and Psychological Crisis Intervention, School of Psychology and Cognitive Science, East China Normal University, Shanghai 200062, China; Key Laboratory of Philosophy and Social Science of Anhui Province on Adolescent Mental Health and Crisis Intelligence Intervention, Hefei Normal University, Hefei 200062, China.
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11
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Chen T, Liu Y, Zhang B, Wu Y, Yan F, Yan L. Electrophysiological correlation between executive vigilance and attention network based on cognitive resource control theory. Int J Psychophysiol 2024; 203:112393. [PMID: 39029532 DOI: 10.1016/j.ijpsycho.2024.112393] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2024] [Revised: 07/03/2024] [Accepted: 07/10/2024] [Indexed: 07/21/2024]
Abstract
Attention is comprised of three independent and interacting attention networks: phasic alertness, orienting, and executive control. Previous studies have explored event-related potentials associated with these attention networks and executive vigilance, there is a lack of research on the relationship between executive vigilance and the three attention networks. However, there is a lack of research on the relationship between executive vigilance and the three attention networks. The present study aims to investigate this relationship. Based on the theory of cognitive resource control, two experimental blocks were designed with the vigilance task as the control variable. A total of 39 participants completed both ANTI and ANTI-V trials (two variants of the traditional attention network test ANT) in the same period. Through analysis of behavior measures (RT) and electrophysiological results related to phasic alertness (N1, P2, and contingent negative variation), orienting (P1, N1, and P3), and executive control (N2 and slow positive potential), we found that the reaction time of the ANTI block was lower than that of the ANTI-V block under all conditions, This suggests that adding a vigilance task may lead to reduced allocation of attention resources across all three attention networks. Furthermore, the orienting ability was weaker in the ANTI-V experimental block compared to that in the ANTI block due to effects on P1 and P3 regulation by the vigilance task. The N2 amplitude of the ANTI-V block was consistently reduced under similar conditions, indicating a weakening of executive control ability. The electrophysiological results revealed that executive vigilance inhibited the component of early attention perception related to the orienting network and was also related to the ability to detect conflict in the executive control network.
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Affiliation(s)
- Tianran Chen
- School of Automotive Engineering, Wuhan University of Technology, Wuhan, Hubei, China
| | - Yan Liu
- School of Automotive Engineering, Wuhan University of Technology, Wuhan, Hubei, China
| | - Bingzhao Zhang
- School of Automotive Engineering, Wuhan University of Technology, Wuhan, Hubei, China
| | - Yibo Wu
- Wuhan Leishen Special Equipment Co. Ltd, Wuhan, Hubei, China
| | - Fuwu Yan
- School of Automotive Engineering, Wuhan University of Technology, Wuhan, Hubei, China; Foshan Xianhu Laboratory of the Advanced Energy Science and Technology Guangdong Laboratory, Foshan, Guangdong, China
| | - Lirong Yan
- School of Automotive Engineering, Wuhan University of Technology, Wuhan, Hubei, China; Foshan Xianhu Laboratory of the Advanced Energy Science and Technology Guangdong Laboratory, Foshan, Guangdong, China.
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12
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Ponrani MA, Anand M, Alsaadi M, Dutta AK, Fayaz R, Mathew S, Chaurasia MA, Sunila, Bhende M. Brain-computer interfaces inspired spiking neural network model for depression stage identification. J Neurosci Methods 2024; 409:110203. [PMID: 38880343 DOI: 10.1016/j.jneumeth.2024.110203] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2024] [Revised: 05/30/2024] [Accepted: 06/13/2024] [Indexed: 06/18/2024]
Abstract
BACKGROUND Depression is a global mental disorder, and traditional diagnostic methods mainly rely on scales and subjective evaluations by doctors, which cannot effectively identify symptoms and even carry the risk of misdiagnosis. Brain-Computer Interfaces inspired deep learning-assisted diagnosis based on physiological signals holds promise for improving traditional methods lacking physiological basis and leads next generation neuro-technologies. However, traditional deep learning methods rely on immense computational power and mostly involve end-to-end network learning. These learning methods also lack physiological interpretability, limiting their clinical application in assisted diagnosis. METHODOLOGY A brain-like learning model for diagnosing depression using electroencephalogram (EEG) is proposed. The study collects EEG data using 128-channel electrodes, producing a 128×128 brain adjacency matrix. Given the assumption of undirected connectivity, the upper half of the 128×128 matrix is chosen in order to minimise the input parameter size, producing 8,128-dimensional data. After eliminating 28 components derived from irrelevant or reference electrodes, a 90×90 matrix is produced, which can be used as an input for a single-channel brain-computer interface image. RESULT At the functional level, a spiking neural network is constructed to classify individuals with depression and healthy individuals, achieving an accuracy exceeding 97.5 %. COMPARISON WITH EXISTING METHODS Compared to deep convolutional methods, the spiking method reduces energy consumption. CONCLUSION At the structural level, complex networks are utilized to establish spatial topology of brain connections and analyse their graph features, identifying potential abnormal brain functional connections in individuals with depression.
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Affiliation(s)
- M Angelin Ponrani
- Department of ECE, St. Joseph's College of Engineering, Chennai -119, India.
| | - Monika Anand
- Computer Science & Engineering, Chandigarh University, Mohali, India
| | - Mahmood Alsaadi
- Department of computer science, Al-Maarif University College, Al Anbar 31001, Iraq
| | - Ashit Kumar Dutta
- Department of Computer Science and Information Systems, College of Applied Sciences, AlMaarefa University, Ad Diriyah, Riyadh 13713, Saudi Arabia
| | - Roma Fayaz
- Dapartmemt of computer science, college of computer science and information technology, Jazan university, Jazan, Saudi Arabia
| | | | - Mousmi Ajay Chaurasia
- Dept of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Hyderabad, India
| | - Sunila
- Guru Jambheshwar University of Science and Technology, Hisar, Haryana, India
| | - Manisha Bhende
- Dr. D. Y. Patil Vidyapeeth, Pune, Dr. D. Y. Patil School of Science & Technology, Tathawade, Pune, India
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13
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Franco J, Laganaro M. Are brain activity changes underlying rare word production after learning specific or do they extend to semantically related rare words? Cortex 2024; 178:174-189. [PMID: 39018954 DOI: 10.1016/j.cortex.2024.06.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Revised: 03/12/2024] [Accepted: 06/10/2024] [Indexed: 07/19/2024]
Abstract
Learning words in the mother tongue is a fundamental lifelong skill that involves complex cognitive and neural changes. In adults, newly learned words affect the organization of the lexical-semantic network and, compared to words that have been in the lexicon for longer, they activate the same cortical areas, but more extensively and/or intensively. It is however still unclear (1) which brain and cognitive processes underlying word production change when infrequent/unknown words are compared before and after learning and (2) whether integrating newly learned words impacts word specific processes or has a broader impact on unlearned words. The present study aims to investigate the electrophysiological changes underlying the production of rare words induced by learning and the effect of learning on an unlearned list of rare words belonging to the same semantic categories. To this end, 24 neurotypical adults learned one of two matched lists of 40 concrete rare words from 4 semantic categories. EEG (electroencephalographic) recordings were acquired during a referential word production task (picture naming) of the learned and unlearned words before and after the learning phase. The results show that the production of rare word is associated with event-related (ERP) differences between before and after learning in the period from 300 to 800 msec following the presentation of the imaged concept (picture). These differences consisted in a larger involvement of left temporal and parietal regions after learning between 300 and 400 msec i.e., the time window likely corresponding to lexical and phonological encoding processes. Crucially, the ERP changes are not restricted to the production of the learned rare words, but are also observed when participants try to retrieve words of a list of semantically and lexically matched rare words that they have not learned. The ERP changes on unlearned rare words are weaker and suggest that learning new words induces boarder effects also on unlearned words.
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Affiliation(s)
- Julie Franco
- Faculty of Psychology and Educational Science, University of Geneva, Geneva, Switzerland.
| | - Marina Laganaro
- Faculty of Psychology and Educational Science, University of Geneva, Geneva, Switzerland.
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14
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Marino M, Mantini D. Human brain imaging with high-density electroencephalography: Techniques and applications. J Physiol 2024. [PMID: 39173191 DOI: 10.1113/jp286639] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2024] [Accepted: 07/30/2024] [Indexed: 08/24/2024] Open
Abstract
Electroencephalography (EEG) is a technique for non-invasively measuring neuronal activity in the human brain using electrodes placed on the participant's scalp. With the advancement of digital technologies, EEG analysis has evolved over time from the qualitative analysis of amplitude and frequency modulations to a comprehensive analysis of the complex spatiotemporal characteristics of the recorded signals. EEG is now considered a powerful tool for measuring neural processes in the same time frame in which they happen (i.e. the subsecond range). However, it is commonly argued that EEG suffers from low spatial resolution, which makes it difficult to localize the generators of EEG activity accurately and reliably. Today, the availability of high-density EEG (hdEEG) systems, combined with methods for incorporating information on head anatomy and sophisticated source-localization algorithms, has transformed EEG into an important neuroimaging tool. hdEEG offers researchers and clinicians a rich and varied range of applications. It can be used not only for investigating neural correlates in motor and cognitive neuroscience experiments, but also for clinical diagnosis, particularly in the detection of epilepsy and the characterization of neural impairments in a wide range of neurological disorders. Notably, the integration of hdEEG systems with other physiological recordings, such as kinematic and/or electromyography data, might be especially beneficial to better understand the neuromuscular mechanisms associated with deconditioning in ageing and neuromotor disorders, by mapping the neurokinematic and neuromuscular connectivity patterns directly in the brain.
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Affiliation(s)
- Marco Marino
- Movement Control and Neuroplasticity Research Group, KU Leuven, Belgium
- Department of General Psychology, University of Padua, Padua, Italy
| | - Dante Mantini
- Movement Control and Neuroplasticity Research Group, KU Leuven, Belgium
- Leuven Brain Institute, KU Leuven, Belgium
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15
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Pigorini A, Avanzini P, Barborica A, Bénar CG, David O, Farisco M, Keller CJ, Manfridi A, Mikulan E, Paulk AC, Roehri N, Subramanian A, Vulliémoz S, Zelmann R. Simultaneous invasive and non-invasive recordings in humans: A novel Rosetta stone for deciphering brain activity. J Neurosci Methods 2024; 408:110160. [PMID: 38734149 DOI: 10.1016/j.jneumeth.2024.110160] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2023] [Revised: 04/10/2024] [Accepted: 05/01/2024] [Indexed: 05/13/2024]
Abstract
Simultaneous noninvasive and invasive electrophysiological recordings provide a unique opportunity to achieve a comprehensive understanding of human brain activity, much like a Rosetta stone for human neuroscience. In this review we focus on the increasingly-used powerful combination of intracranial electroencephalography (iEEG) with scalp electroencephalography (EEG) or magnetoencephalography (MEG). We first provide practical insight on how to achieve these technically challenging recordings. We then provide examples from clinical research on how simultaneous recordings are advancing our understanding of epilepsy. This is followed by the illustration of how human neuroscience and methodological advances could benefit from these simultaneous recordings. We conclude with a call for open data sharing and collaboration, while ensuring neuroethical approaches and argue that only with a true collaborative approach the promises of simultaneous recordings will be fulfilled.
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Affiliation(s)
- Andrea Pigorini
- Department of Biomedical, Surgical and Dental Sciences, Università degli Studi di Milano, Milan, Italy; UOC Maxillo-facial Surgery and dentistry, Fondazione IRCCS Cà Granda, Ospedale Maggiore Policlinico, Milan, Italy.
| | - Pietro Avanzini
- Institute of Neuroscience, Consiglio Nazionale delle Ricerche, Parma, Italy
| | | | - Christian-G Bénar
- Aix Marseille Univ, Inserm, U1106, INS, Institut de Neurosciences des Systèmes, Marseille, France
| | - Olivier David
- Aix Marseille Univ, Inserm, U1106, INS, Institut de Neurosciences des Systèmes, Marseille, France
| | - Michele Farisco
- Centre for Research Ethics and Bioethics, Department of Public Health and Caring Sciences, Uppsala University, P.O. Box 256, Uppsala, SE 751 05, Sweden; Science and Society Unit Biogem, Biology and Molecular Genetics Institute, Via Camporeale snc, Ariano Irpino, AV 83031, Italy
| | - Corey J Keller
- Department of Psychiatry & Behavioral Sciences, Stanford University Medical Center, Stanford, CA 94305, USA; Wu Tsai Neurosciences Institute, Stanford University Medical Center, Stanford, CA 94305, USA; Veterans Affairs Palo Alto Healthcare System, and the Sierra Pacific Mental Illness, Research, Education, and Clinical Center (MIRECC), Palo Alto, CA 94394, USA
| | - Alfredo Manfridi
- Department of Pathophysiology and Transplantation, Università degli Studi di Milano, Milan, Italy
| | - Ezequiel Mikulan
- Department of Health Sciences, Università degli Studi di Milano, Milan, Italy
| | - Angelique C Paulk
- Department of Neurology and Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Nicolas Roehri
- EEG and Epilepsy Unit, Dpt of Clinical Neurosciences, Geneva University Hospitals and University of Geneva, Switzerland
| | - Ajay Subramanian
- Department of Psychiatry & Behavioral Sciences, Stanford University Medical Center, Stanford, CA 94305, USA; Wu Tsai Neurosciences Institute, Stanford University Medical Center, Stanford, CA 94305, USA; Veterans Affairs Palo Alto Healthcare System, and the Sierra Pacific Mental Illness, Research, Education, and Clinical Center (MIRECC), Palo Alto, CA 94394, USA
| | - Serge Vulliémoz
- EEG and Epilepsy Unit, Dpt of Clinical Neurosciences, Geneva University Hospitals and University of Geneva, Switzerland
| | - Rina Zelmann
- Department of Neurology and Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
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16
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Gogulski J, Cline CC, Ross JM, Truong J, Sarkar M, Parmigiani S, Keller CJ. Mapping cortical excitability in the human dorsolateral prefrontal cortex. Clin Neurophysiol 2024; 164:138-148. [PMID: 38865780 PMCID: PMC11246810 DOI: 10.1016/j.clinph.2024.05.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2023] [Revised: 04/10/2024] [Accepted: 05/22/2024] [Indexed: 06/14/2024]
Abstract
BACKGROUND Transcranial magnetic stimulation (TMS) to the dorsolateral prefrontal cortex (dlPFC) is an effective treatment for depression, but the neural effects after TMS remains unclear. TMS paired with electroencephalography (TMS-EEG) can causally probe these neural effects. Nonetheless, variability in single pulse TMS-evoked potentials (TEPs) across dlPFC subregions, and potential artifact induced by muscle activation, necessitate detailed mapping for accurate treatment monitoring. OBJECTIVE To characterize early TEPs anatomically and temporally (20-50 ms) close to the TMS pulse (EL-TEPs), as well as associated muscle artifacts (<20 ms), across the dlPFC. We hypothesized that TMS location and angle influence EL-TEPs, and specifically that conditions with larger muscle artifact may exhibit lower observed EL-TEPs due to over-rejection during preprocessing. Additionally, we sought to determine an optimal group-level TMS target and angle, while investigating the potential benefits of a personalized approach. METHODS In 16 healthy participants, we applied single-pulse TMS to six targets within the dlPFC at two coil angles and measured EEG responses. RESULTS Stimulation location significantly influenced observed EL-TEPs, with posterior and medial targets yielding larger EL-TEPs. Regions with high EL-TEP amplitude had less muscle artifact, and vice versa. The best group-level target yielded 102% larger EL-TEP responses compared to other dlPFC targets. Optimal dlPFC target differed across subjects, suggesting that a personalized targeting approach might boost the EL-TEP by an additional 36%. SIGNIFICANCE EL-TEPs can be probed without significant muscle-related confounds in posterior-medial regions of the dlPFC. The identification of an optimal group-level target and the potential for further refinement through personalized targeting hold significant implications for optimizing depression treatment protocols.
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Affiliation(s)
- Juha Gogulski
- Department of Psychiatry & Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94305, USA; Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA; Department of Clinical Neurophysiology, HUS Diagnostic Center, Clinical Neurosciences, Helsinki University Hospital and University of Helsinki, Helsinki, FI-00029 HUS, Finland
| | - Christopher C Cline
- Department of Psychiatry & Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94305, USA; Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
| | - Jessica M Ross
- Veterans Affairs Palo Alto Healthcare System, and the Sierra Pacific Mental Illness, Research, Education, and Clinical Center (MIRECC), Palo Alto, CA, 94394, USA; Department of Psychiatry & Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94305, USA; Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
| | - Jade Truong
- Department of Psychiatry & Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94305, USA; Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
| | - Manjima Sarkar
- Department of Psychiatry & Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94305, USA; Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
| | - Sara Parmigiani
- Department of Psychiatry & Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94305, USA; Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
| | - Corey J Keller
- Department of Psychiatry & Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94305, USA; Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA; Veterans Affairs Palo Alto Healthcare System, and the Sierra Pacific Mental Illness, Research, Education, and Clinical Center (MIRECC), Palo Alto, CA, 94394, USA.
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17
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Xia M, Zhao X, Deng R, Lu Z, Cao J. EEGNet classification of sleep EEG for individual specialization based on data augmentation. Cogn Neurodyn 2024; 18:1539-1547. [PMID: 39104682 PMCID: PMC11297866 DOI: 10.1007/s11571-023-10062-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2023] [Revised: 11/19/2023] [Accepted: 12/18/2023] [Indexed: 08/07/2024] Open
Abstract
Sleep is an essential part of human life, and the quality of one's sleep is also an important indicator of one's health. Analyzing the Electroencephalogram (EEG) signals of a person during sleep makes it possible to understand the sleep status and give relevant rest or medical advice. In this paper, a decent amount of artificial data generated with a data augmentation method based on Discrete Cosine Transform from a small amount of real experimental data of a specific individual is introduced. A classification model with an accuracy of 92.85% has been obtained. By mixing the data augmentation with the public database and training with the EEGNet, we obtained a classification model with significantly higher accuracy for the specific individual. The experiments have demonstrated that we can circumvent the subject-independent problem in sleep EEG in this way and use only a small amount of labeled data to customize a dedicated classification model with high accuracy.
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Affiliation(s)
- Mo Xia
- Graduate School of Engineering, Saitama Institute of Technology, 1690 Fusaiji, Fukaya, Saitama 369-0203 Japan
| | - Xuyang Zhao
- Graduate School of Engineering, Tokyo University of Agriculture and Technology, 3-8-1 Harumicho, Fuchu, Tokyo 183-8538 Japan
- RIKEN Center for Advanced Intelligence Project (AIP), 1-4-1 Nihonbashi, Chuo, Tokyo 103-0027 Japan
| | - Rui Deng
- Graduate School of Engineering, Saitama Institute of Technology, 1690 Fusaiji, Fukaya, Saitama 369-0203 Japan
| | - Zheng Lu
- Department of Psychiatry, Tongji Hospital, Tongji University, 40 Chifeng Rd, Yangpu District, Shanghai, 200086 China
| | - Jianting Cao
- Graduate School of Engineering, Saitama Institute of Technology, 1690 Fusaiji, Fukaya, Saitama 369-0203 Japan
- RIKEN Center for Advanced Intelligence Project (AIP), 1-4-1 Nihonbashi, Chuo, Tokyo 103-0027 Japan
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18
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Hssain-Khalladi S, Giron A, Huneau C, Gitton C, Schwartz D, George N, Le Van Quyen M, Marrelec G, Marchand-Pauvert V. Further characterisation of late somatosensory evoked potentials using electroencephalogram and magnetoencephalogram source imaging. Eur J Neurosci 2024; 60:3772-3794. [PMID: 38726801 DOI: 10.1111/ejn.16379] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2021] [Revised: 09/27/2023] [Accepted: 04/18/2024] [Indexed: 07/06/2024]
Abstract
Beside the well-documented involvement of secondary somatosensory area, the cortical network underlying late somatosensory evoked potentials (P60/N60 and P100/N100) is still unknown. Electroencephalogram and magnetoencephalogram source imaging were performed to further investigate the origin of the brain cortical areas involved in late somatosensory evoked potentials, using sensory inputs of different strengths and by testing the correlation between cortical sources. Simultaneous high-density electroencephalograms and magnetoencephalograms were performed in 19 participants, and electrical stimulation was applied to the median nerve (wrist level) at intensity between 1.5 and 9 times the perceptual threshold. Source imaging was undertaken to map the stimulus-induced brain cortical activity according to each individual brain magnetic resonance imaging, during three windows of analysis covering early and late somatosensory evoked potentials. Results for P60/N60 and P100/N100 were compared with those for P20/N20 (early response). According to literature, maximal activity during P20/N20 was found in central sulcus contralateral to stimulation site. During P60/N60 and P100/N100, activity was observed in contralateral primary sensorimotor area, secondary somatosensory area (on both hemispheres) and premotor and multisensory associative cortices. Late responses exhibited similar characteristics but different from P20/N20, and no significant correlation was found between early and late generated activities. Specific clusters of cortical activities were activated with specific input/output relationships underlying early and late somatosensory evoked potentials. Cortical networks, partly common to and distinct from early somatosensory responses, contribute to late responses, all participating in the complex somatosensory brain processing.
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Affiliation(s)
- Sahar Hssain-Khalladi
- Sorbonne Université, Inserm, CNRS, Laboratoire d'Imagerie Biomédicale, LIB, Paris, France
- Sorbonne Université, Laboratoire d'Excellence SMART, Paris, France
| | - Alain Giron
- Sorbonne Université, Inserm, CNRS, Laboratoire d'Imagerie Biomédicale, LIB, Paris, France
| | - Clément Huneau
- Université de Nantes, CNRS, Laboratoire des Sciences du Numérique de Nantes, LS2N, Nantes, France
| | - Christophe Gitton
- Sorbonne Université, Inserm, CNRS, Institut du Cerveau, ICM, Paris, France
| | - Denis Schwartz
- Sorbonne Université, Inserm, CNRS, Institut du Cerveau, ICM, Paris, France
| | - Nathalie George
- Sorbonne Université, Inserm, CNRS, Institut du Cerveau, ICM, Paris, France
| | - Michel Le Van Quyen
- Sorbonne Université, Inserm, CNRS, Laboratoire d'Imagerie Biomédicale, LIB, Paris, France
| | - Guillaume Marrelec
- Sorbonne Université, Inserm, CNRS, Laboratoire d'Imagerie Biomédicale, LIB, Paris, France
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19
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Retsa C, Turpin H, Geiser E, Ansermet F, Müller-Nix C, Murray MM. Longstanding Auditory Sensory and Semantic Differences in Preterm Born Children. Brain Topogr 2024; 37:536-551. [PMID: 38010487 PMCID: PMC11199270 DOI: 10.1007/s10548-023-01022-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Accepted: 11/06/2023] [Indexed: 11/29/2023]
Abstract
More than 10% of births are preterm, and the long-term consequences on sensory and semantic processing of non-linguistic information remain poorly understood. 17 very preterm-born children (born at < 33 weeks gestational age) and 15 full-term controls were tested at 10 years old with an auditory object recognition task, while 64-channel auditory evoked potentials (AEPs) were recorded. Sounds consisted of living (animal and human vocalizations) and manmade objects (e.g. household objects, instruments, and tools). Despite similar recognition behavior, AEPs strikingly differed between full-term and preterm children. Starting at 50ms post-stimulus onset, AEPs from preterm children differed topographically from their full-term counterparts. Over the 108-224ms post-stimulus period, full-term children showed stronger AEPs in response to living objects, whereas preterm born children showed the reverse pattern; i.e. stronger AEPs in response to manmade objects. Differential brain activity between semantic categories could reliably classify children according to their preterm status. Moreover, this opposing pattern of differential responses to semantic categories of sounds was also observed in source estimations within a network of occipital, temporal and frontal regions. This study highlights how early life experience in terms of preterm birth shapes sensory and object processing later on in life.
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Affiliation(s)
- Chrysa Retsa
- The Radiology Department, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.
- The Sense Innovation and Research Center, Lausanne and Sion, Lausanne, Switzerland.
- CIBM Center for Biomedical Imaging, Lausanne, Switzerland.
| | - Hélène Turpin
- The Radiology Department, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- University Service of Child and Adolescent Psychiatry, University Hospital of Lausanne and University of Lausanne, Lausanne, Switzerland
| | - Eveline Geiser
- The Radiology Department, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - François Ansermet
- University Service of Child and Adolescent Psychiatry, University Hospital of Lausanne and University of Lausanne, Lausanne, Switzerland
- Department of Child and Adolescent Psychiatry, University Hospital, Geneva, Switzerland
| | - Carole Müller-Nix
- University Service of Child and Adolescent Psychiatry, University Hospital of Lausanne and University of Lausanne, Lausanne, Switzerland
| | - Micah M Murray
- The Radiology Department, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- The Sense Innovation and Research Center, Lausanne and Sion, Lausanne, Switzerland
- CIBM Center for Biomedical Imaging, Lausanne, Switzerland
- Department of Hearing and Speech Sciences, Vanderbilt University, Nashville, TN, USA
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20
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Weglage A, Layer N, Meister H, Müller V, Lang-Roth R, Walger M, Sandmann P. Changes in visually and auditory attended audiovisual speech processing in cochlear implant users: A longitudinal ERP study. Hear Res 2024; 447:109023. [PMID: 38733710 DOI: 10.1016/j.heares.2024.109023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/31/2024] [Revised: 03/25/2024] [Accepted: 04/26/2024] [Indexed: 05/13/2024]
Abstract
Limited auditory input, whether caused by hearing loss or by electrical stimulation through a cochlear implant (CI), can be compensated by the remaining senses. Specifically for CI users, previous studies reported not only improved visual skills, but also altered cortical processing of unisensory visual and auditory stimuli. However, in multisensory scenarios, it is still unclear how auditory deprivation (before implantation) and electrical hearing experience (after implantation) affect cortical audiovisual speech processing. Here, we present a prospective longitudinal electroencephalography (EEG) study which systematically examined the deprivation- and CI-induced alterations of cortical processing of audiovisual words by comparing event-related potentials (ERPs) in postlingually deafened CI users before and after implantation (five weeks and six months of CI use). A group of matched normal-hearing (NH) listeners served as controls. The participants performed a word-identification task with congruent and incongruent audiovisual words, focusing their attention on either the visual (lip movement) or the auditory speech signal. This allowed us to study the (top-down) attention effect on the (bottom-up) sensory cortical processing of audiovisual speech. When compared to the NH listeners, the CI candidates (before implantation) and the CI users (after implantation) exhibited enhanced lipreading abilities and an altered cortical response at the N1 latency range (90-150 ms) that was characterized by a decreased theta oscillation power (4-8 Hz) and a smaller amplitude in the auditory cortex. After implantation, however, the auditory-cortex response gradually increased and developed a stronger intra-modal connectivity. Nevertheless, task efficiency and activation in the visual cortex was significantly modulated in both groups by focusing attention on the visual as compared to the auditory speech signal, with the NH listeners additionally showing an attention-dependent decrease in beta oscillation power (13-30 Hz). In sum, these results suggest remarkable deprivation effects on audiovisual speech processing in the auditory cortex, which partially reverse after implantation. Although even experienced CI users still show distinct audiovisual speech processing compared to NH listeners, pronounced effects of (top-down) direction of attention on (bottom-up) audiovisual processing can be observed in both groups. However, NH listeners but not CI users appear to show enhanced allocation of cognitive resources in visually as compared to auditory attended audiovisual speech conditions, which supports our behavioural observations of poorer lipreading abilities and reduced visual influence on audition in NH listeners as compared to CI users.
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Affiliation(s)
- Anna Weglage
- Head and Neck Surgery, Audiology and Pediatric Audiology, Cochlear Implant Centre, University of Cologne, Faculty of Medicine and University Hospital Cologne, Department of Otorhinolaryngology, Germany.
| | - Natalie Layer
- Head and Neck Surgery, Audiology and Pediatric Audiology, Cochlear Implant Centre, University of Cologne, Faculty of Medicine and University Hospital Cologne, Department of Otorhinolaryngology, Germany
| | - Hartmut Meister
- Head and Neck Surgery, Audiology and Pediatric Audiology, Cochlear Implant Centre, University of Cologne, Faculty of Medicine and University Hospital Cologne, Department of Otorhinolaryngology, Germany; Jean-Uhrmacher-Institute for Clinical ENT Research, University of Cologne, Germany
| | - Verena Müller
- Head and Neck Surgery, Audiology and Pediatric Audiology, Cochlear Implant Centre, University of Cologne, Faculty of Medicine and University Hospital Cologne, Department of Otorhinolaryngology, Germany
| | - Ruth Lang-Roth
- Head and Neck Surgery, Audiology and Pediatric Audiology, Cochlear Implant Centre, University of Cologne, Faculty of Medicine and University Hospital Cologne, Department of Otorhinolaryngology, Germany
| | - Martin Walger
- Head and Neck Surgery, Audiology and Pediatric Audiology, Cochlear Implant Centre, University of Cologne, Faculty of Medicine and University Hospital Cologne, Department of Otorhinolaryngology, Germany; Jean-Uhrmacher-Institute for Clinical ENT Research, University of Cologne, Germany
| | - Pascale Sandmann
- Department of Otolaryngology, Head and Neck Surgery, Carl von Ossietzky University of Oldenburg, Germany; Research Center Neurosensory Science University of Oldenburg, Germany; Cluster of Excellence "Hearing4all", University of Oldenburg, Germany
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21
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Guo Q, Liu S, Wang L, Feng K, Yang S. Analysis of microstate features for Parkinson's disease based on reliability validation. J Neurosci Methods 2024; 406:110115. [PMID: 38531478 DOI: 10.1016/j.jneumeth.2024.110115] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2023] [Revised: 03/13/2024] [Accepted: 03/20/2024] [Indexed: 03/28/2024]
Abstract
BACKGROUND Parkinson's disease (PD) is a disorder with abnormal changes in brain activity. The lack of objective indicators makes the assessment of PD progression difficult. Assessment of brain activity changes in PD may offer a potential solution. NEW METHOD Electroencephalogram (EEG) microstates reflect global dynamic changes in the brain. Therefore, we utilized microstates to assess changes in PD brain activity. However, the effect of epoch duration on the reliability of microstate analyses in PD is unclear. Thus, we first assessed the effect of data duration on the reliability of microstate topography and temporal features in PD and older healthy individuals. According to the reliability assessment, EEG epochs with high reliability were selected for microstate analysis in PD. Finally, we investigated the correlation between microstate features and clinical scales to determine whether these features could serve as objective indicators to evaluate PD progression. RESULTS Microstate analysis features that show high reliability for 3 min and above epoch durations. The topology of microstate D was significantly changed in PD compared to healthy controls, as well as the temporal features of microstates C and D. Additionally, the occurrence of C was negatively correlated with MoCA, and the duration of D was positively correlated with UPDRS. COMPARISON WITH EXISTING METHOD(S) High reliability of PD microstate features obtained by our approach. CONCLUSION EEG for PD microstate analysis should be at least 3 min. Microstate analysis is expected to provide new ideas and objective indicators for assessing Parkinson's disease progression in the clinical setting.
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Affiliation(s)
- Qingfang Guo
- Hebei Key Laboratory of Bioelectromagnetics and Neural Engineering, School of Health Sciences and Biomedical Engineering, Hebei University of Technology, Tianjin 300131, China; State Key Laboratory of Reliable and Intelligence of Electrical Equipment, Hebei University of Technology, Tianjin 300130, China
| | - Shuo Liu
- Hebei Key Laboratory of Bioelectromagnetics and Neural Engineering, School of Health Sciences and Biomedical Engineering, Hebei University of Technology, Tianjin 300131, China; State Key Laboratory of Reliable and Intelligence of Electrical Equipment, Hebei University of Technology, Tianjin 300130, China
| | - Lei Wang
- Hebei Key Laboratory of Bioelectromagnetics and Neural Engineering, School of Health Sciences and Biomedical Engineering, Hebei University of Technology, Tianjin 300131, China; State Key Laboratory of Reliable and Intelligence of Electrical Equipment, Hebei University of Technology, Tianjin 300130, China
| | - Keke Feng
- Department of Neurosurgery, Tianjin Huanhu Hospital, Tianjin, China.
| | - Shuo Yang
- Hebei Key Laboratory of Bioelectromagnetics and Neural Engineering, School of Health Sciences and Biomedical Engineering, Hebei University of Technology, Tianjin 300131, China; State Key Laboratory of Reliable and Intelligence of Electrical Equipment, Hebei University of Technology, Tianjin 300130, China.
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22
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Lützow Holm E, Fernández Slezak D, Tagliazucchi E. Contribution of low-level image statistics to EEG decoding of semantic content in multivariate and univariate models with feature optimization. Neuroimage 2024; 293:120626. [PMID: 38677632 DOI: 10.1016/j.neuroimage.2024.120626] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2024] [Revised: 04/23/2024] [Accepted: 04/24/2024] [Indexed: 04/29/2024] Open
Abstract
Spatio-temporal patterns of evoked brain activity contain information that can be used to decode and categorize the semantic content of visual stimuli. However, this procedure can be biased by low-level image features independently of the semantic content present in the stimuli, prompting the need to understand the robustness of different models regarding these confounding factors. In this study, we trained machine learning models to distinguish between concepts included in the publicly available THINGS-EEG dataset using electroencephalography (EEG) data acquired during a rapid serial visual presentation paradigm. We investigated the contribution of low-level image features to decoding accuracy in a multivariate model, utilizing broadband data from all EEG channels. Additionally, we explored a univariate model obtained through data-driven feature selection applied to the spatial and frequency domains. While the univariate models exhibited better decoding accuracy, their predictions were less robust to the confounding effect of low-level image statistics. Notably, some of the models maintained their accuracy even after random replacement of the training dataset with semantically unrelated samples that presented similar low-level content. In conclusion, our findings suggest that model optimization impacts sensitivity to confounding factors, regardless of the resulting classification performance. Therefore, the choice of EEG features for semantic decoding should ideally be informed by criteria beyond classifier performance, such as the neurobiological mechanisms under study.
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Affiliation(s)
- Eric Lützow Holm
- National Scientific and Technical Research Council (CONICET), Godoy Cruz 2290, CABA 1425, Argentina; Institute of Applied and Interdisciplinary Physics and Department of Physics, University of Buenos Aires, Pabellón 1, Ciudad Universitaria, CABA 1425, Argentina.
| | - Diego Fernández Slezak
- National Scientific and Technical Research Council (CONICET), Godoy Cruz 2290, CABA 1425, Argentina; Departamento de Computación, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Pabellón 1, Ciudad Universitaria, CABA 1425, Argentina; Instituto de Investigación en Ciencias de la Computación (ICC), CONICET-Universidad de Buenos Aires, Pabellón 1, Ciudad Universitaria, CABA 1425, Argentina
| | - Enzo Tagliazucchi
- National Scientific and Technical Research Council (CONICET), Godoy Cruz 2290, CABA 1425, Argentina; Institute of Applied and Interdisciplinary Physics and Department of Physics, University of Buenos Aires, Pabellón 1, Ciudad Universitaria, CABA 1425, Argentina; Latin American Brain Health (BrainLat), Universidad Adolfo Ibáñez, Av. Diag. Las Torres 2640, Peñalolén 7941169, Santiago Región Metropolitana, Chile.
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23
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Liang Y, Zhang C, An S, Wang Z, Shi K, Peng T, Ma Y, Xie X, He J, Zheng K. FetchEEG: a hybrid approach combining feature extraction and temporal-channel joint attention for EEG-based emotion classification. J Neural Eng 2024; 21:036011. [PMID: 38701773 DOI: 10.1088/1741-2552/ad4743] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2024] [Accepted: 05/03/2024] [Indexed: 05/05/2024]
Abstract
Objective. Electroencephalogram (EEG) analysis has always been an important tool in neural engineering, and the recognition and classification of human emotions are one of the important tasks in neural engineering. EEG data, obtained from electrodes placed on the scalp, represent a valuable resource of information for brain activity analysis and emotion recognition. Feature extraction methods have shown promising results, but recent trends have shifted toward end-to-end methods based on deep learning. However, these approaches often overlook channel representations, and their complex structures pose certain challenges to model fitting.Approach. To address these challenges, this paper proposes a hybrid approach named FetchEEG that combines feature extraction and temporal-channel joint attention. Leveraging the advantages of both traditional feature extraction and deep learning, the FetchEEG adopts a multi-head self-attention mechanism to extract representations between different time moments and channels simultaneously. The joint representations are then concatenated and classified using fully-connected layers for emotion recognition. The performance of the FetchEEG is verified by comparison experiments on a self-developed dataset and two public datasets.Main results. In both subject-dependent and subject-independent experiments, the FetchEEG demonstrates better performance and stronger generalization ability than the state-of-the-art methods on all datasets. Moreover, the performance of the FetchEEG is analyzed for different sliding window sizes and overlap rates in the feature extraction module. The sensitivity of emotion recognition is investigated for three- and five-frequency-band scenarios.Significance. FetchEEG is a novel hybrid method based on EEG for emotion classification, which combines EEG feature extraction with Transformer neural networks. It has achieved state-of-the-art performance on both self-developed datasets and multiple public datasets, with significantly higher training efficiency compared to end-to-end methods, demonstrating its effectiveness and feasibility.
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Affiliation(s)
- Yu Liang
- Faculty of Information Technology, Beijing University of Technology, Beijing, People's Republic of China
| | - Chenlong Zhang
- Faculty of Information Technology, Beijing University of Technology, Beijing, People's Republic of China
| | - Shan An
- JD Health International Inc., Beijing, People's Republic of China
| | - Zaitian Wang
- Faculty of Information Technology, Beijing University of Technology, Beijing, People's Republic of China
| | - Kaize Shi
- University of Technology Sydney, Sydney, Australia
| | - Tianhao Peng
- Beihang University, Beijing, People's Republic of China
| | - Yuqing Ma
- Beihang University, Beijing, People's Republic of China
| | - Xiaoyang Xie
- Faculty of Information Technology, Beijing University of Technology, Beijing, People's Republic of China
| | - Jian He
- Faculty of Information Technology, Beijing University of Technology, Beijing, People's Republic of China
| | - Kun Zheng
- Faculty of Information Technology, Beijing University of Technology, Beijing, People's Republic of China
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24
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Krethlow G, Fargier R, Atanasova T, Ménétré E, Laganaro M. Asynchronous behavioral and neurophysiological changes in word production in the adult lifespan. Cereb Cortex 2024; 34:bhae187. [PMID: 38715409 PMCID: PMC11077060 DOI: 10.1093/cercor/bhae187] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2023] [Revised: 04/05/2024] [Accepted: 04/18/2024] [Indexed: 05/12/2024] Open
Abstract
Behavioral and brain-related changes in word production have been claimed to predominantly occur after 70 years of age. Most studies investigating age-related changes in adulthood only compared young to older adults, failing to determine whether neural processes underlying word production change at an earlier age than observed in behavior. This study aims to fill this gap by investigating whether changes in neurophysiological processes underlying word production are aligned with behavioral changes. Behavior and the electrophysiological event-related potential patterns of word production were assessed during a picture naming task in 95 participants across five adult lifespan age groups (ranging from 16 to 80 years old). While behavioral performance decreased starting from 70 years of age, significant neurophysiological changes were present at the age of 40 years old, in a time window (between 150 and 220 ms) likely associated with lexical-semantic processes underlying referential word production. These results show that neurophysiological modifications precede the behavioral changes in language production; they can be interpreted in line with the suggestion that the lexical-semantic reorganization in mid-adulthood influences the maintenance of language skills longer than for other cognitive functions.
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Affiliation(s)
- Giulia Krethlow
- Faculty of Psychology and Educational Sciences, University of Geneva, Bd du Pont d’Arve 40, 1205, Geneva, Switzerland
| | | | - Tanja Atanasova
- Faculty of Psychology and Educational Sciences, University of Geneva, Bd du Pont d’Arve 40, 1205, Geneva, Switzerland
| | - Eric Ménétré
- Faculty of Psychology and Educational Sciences, University of Geneva, Bd du Pont d’Arve 40, 1205, Geneva, Switzerland
| | - Marina Laganaro
- Faculty of Psychology and Educational Sciences, University of Geneva, Bd du Pont d’Arve 40, 1205, Geneva, Switzerland
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25
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Turk-Browne NB, Aslin RN. Infant neuroscience: how to measure brain activity in the youngest minds. Trends Neurosci 2024; 47:338-354. [PMID: 38570212 DOI: 10.1016/j.tins.2024.02.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Revised: 01/08/2024] [Accepted: 02/09/2024] [Indexed: 04/05/2024]
Abstract
The functional properties of the infant brain are poorly understood. Recent advances in cognitive neuroscience are opening new avenues for measuring brain activity in human infants. These include novel uses of existing technologies such as electroencephalography (EEG) and magnetoencephalography (MEG), the availability of newer technologies including functional near-infrared spectroscopy (fNIRS) and optically pumped magnetometry (OPM), and innovative applications of functional magnetic resonance imaging (fMRI) in awake infants during cognitive tasks. In this review article we catalog these available non-invasive methods, discuss the challenges and opportunities encountered when applying them to human infants, and highlight the potential they may ultimately hold for advancing our understanding of the youngest minds.
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Affiliation(s)
- Nicholas B Turk-Browne
- Department of Psychology, Yale University, New Haven, CT 06520, USA; Wu Tsai Institute, Yale University, New Haven, CT 06510, USA.
| | - Richard N Aslin
- Department of Psychology, Yale University, New Haven, CT 06520, USA; Child Study Center, Yale School of Medicine, New Haven, CT 06520, USA
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26
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S A A, C S, P D, G A, Maniyan Lathikakumari A, V Thomas S, N Menon R. Analysis of EEG microstates as biomarkers in neuropsychological processes - Review. Comput Biol Med 2024; 173:108266. [PMID: 38531248 DOI: 10.1016/j.compbiomed.2024.108266] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2023] [Revised: 02/08/2024] [Accepted: 03/06/2024] [Indexed: 03/28/2024]
Abstract
Microstate analysis is a spatiotemporal method where instantaneous scalp potential topography represents the current state of the brain. The temporal evolution of these scalp topographies gives an understanding of quasi-stable periods of long-range coherence between distant electrodes, reflecting functional coordination within large-scale cortical networks. It has been proven potential in identification and characterization of neurophysiological indicators associated with neuropsychiatric conditions. Changes in microstates connected to symptoms and cognitive impairments of neuropsychiatric conditions. It is useful in the study of cognitive processes and disorders related to memory. Researchers may probe into the relationships between microstates and other cognitive processes, such as memory retrieval and encoding. This is a tool for clinicians to enhance the precision of diagnosis and inform possibilities for treatment by acquiring information regarding individual diversity in microstates could lead to tailored medical methods. Customizing treatment according to a patient's microstate patterns could improve the efficacy of treatment. The papers selected for the review span a broad-spectrum including memory related disorders, psychiatry and neurological disorders. A section in the review article has been dedicated to source localization of EEG microstates. The selection of review papers shed light on the importance and huge potential of application of EEG microstate analysis in various neuropsychological processes. The review concludes with the need for standardization of microstate analysis. It suggests the incorporation of widely accepted machine learning techniques for increasing the accuracy, reliability and acceptability of microstate analysis as reliable biomarkers for neurological conditions in the future.
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Affiliation(s)
- Asha S A
- Health Technology Group, Centre for Development of Advanced Computing (CDAC), Thiruvananthapuram, Kerala, India.
| | - Sudalaimani C
- Health Technology Group, Centre for Development of Advanced Computing (CDAC), Thiruvananthapuram, Kerala, India.
| | - Devanand P
- Health Technology Group, Centre for Development of Advanced Computing (CDAC), Thiruvananthapuram, Kerala, India.
| | - Alexander G
- Health Technology Group, Centre for Development of Advanced Computing (CDAC), Thiruvananthapuram, Kerala, India.
| | - Arya Maniyan Lathikakumari
- R Madhavan Nayar Centre for Comprehensive Epilepsy Care, Sree Chitra Tirunal Institute of Medical Sciences & Technology (SCTIMST), Thiruvananthapuram, Kerala, India.
| | - Sanjeev V Thomas
- R Madhavan Nayar Centre for Comprehensive Epilepsy Care, Sree Chitra Tirunal Institute of Medical Sciences & Technology (SCTIMST), Thiruvananthapuram, Kerala, India.
| | - Ramshekhar N Menon
- R Madhavan Nayar Centre for Comprehensive Epilepsy Care, Sree Chitra Tirunal Institute of Medical Sciences & Technology (SCTIMST), Thiruvananthapuram, Kerala, India.
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27
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Bonassi G, Zhao M, Samogin J, Mantini D, Marchese R, Contrino L, Tognetti P, Putzolu M, Botta A, Pelosin E, Avanzino L. Brain Networks Modulation during Simple and Complex Gait: A "Mobile Brain/Body Imaging" Study. SENSORS (BASEL, SWITZERLAND) 2024; 24:2875. [PMID: 38732980 PMCID: PMC11086305 DOI: 10.3390/s24092875] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/22/2024] [Revised: 04/24/2024] [Accepted: 04/29/2024] [Indexed: 05/13/2024]
Abstract
Walking encompasses a complex interplay of neuromuscular coordination and cognitive processes. Disruptions in gait can impact personal independence and quality of life, especially among the elderly and neurodegenerative patients. While traditional biomechanical analyses and neuroimaging techniques have contributed to understanding gait control, they often lack the temporal resolution needed for rapid neural dynamics. This study employs a mobile brain/body imaging (MoBI) platform with high-density electroencephalography (hd-EEG) to explore event-related desynchronization and synchronization (ERD/ERS) during overground walking. Simultaneous to hdEEG, we recorded gait spatiotemporal parameters. Participants were asked to walk under usual walking and dual-task walking conditions. For data analysis, we extracted ERD/ERS in α, β, and γ bands from 17 selected regions of interest encompassing not only the sensorimotor cerebral network but also the cognitive and affective networks. A correlation analysis was performed between gait parameters and ERD/ERS intensities in different networks in the different phases of gait. Results showed that ERD/ERS modulations across gait phases in the α and β bands extended beyond the sensorimotor network, over the cognitive and limbic networks, and were more prominent in all networks during dual tasks with respect to usual walking. Correlation analyses showed that a stronger α ERS in the initial double-support phases correlates with shorter step length, emphasizing the role of attention in motor control. Additionally, β ERD/ERS in affective and cognitive networks during dual-task walking correlated with dual-task gait performance, suggesting compensatory mechanisms in complex tasks. This study advances our understanding of neural dynamics during overground walking, emphasizing the multidimensional nature of gait control involving cognitive and affective networks.
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Affiliation(s)
- Gaia Bonassi
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genoa, 16132 Genoa, Italy;
| | - Mingqi Zhao
- Research Center for Motor Control and Neuroplasticity, KU Leuven, 3001 Leuven, Belgium; (M.Z.); (J.S.); (D.M.)
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, Lanzhou 730000, China
| | - Jessica Samogin
- Research Center for Motor Control and Neuroplasticity, KU Leuven, 3001 Leuven, Belgium; (M.Z.); (J.S.); (D.M.)
| | - Dante Mantini
- Research Center for Motor Control and Neuroplasticity, KU Leuven, 3001 Leuven, Belgium; (M.Z.); (J.S.); (D.M.)
| | - Roberta Marchese
- IRCCS Ospedale Policlinico San Martino, 16132 Genoa, Italy; (R.M.); (A.B.); (L.A.)
| | - Luciano Contrino
- S.C. Medicina Fisica e Riabilitazione Ospedaliera, Azienda Sanitaria Locale Chiavarese, 16043 Chiavari, Italy; (L.C.); (P.T.)
| | - Paola Tognetti
- S.C. Medicina Fisica e Riabilitazione Ospedaliera, Azienda Sanitaria Locale Chiavarese, 16043 Chiavari, Italy; (L.C.); (P.T.)
| | - Martina Putzolu
- Department of Experimental Medicine, Section of Human Physiology, University of Genoa, Viale Benedetto XV 3, 16132 Genoa, Italy;
| | - Alessandro Botta
- IRCCS Ospedale Policlinico San Martino, 16132 Genoa, Italy; (R.M.); (A.B.); (L.A.)
| | - Elisa Pelosin
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genoa, 16132 Genoa, Italy;
- IRCCS Ospedale Policlinico San Martino, 16132 Genoa, Italy; (R.M.); (A.B.); (L.A.)
| | - Laura Avanzino
- IRCCS Ospedale Policlinico San Martino, 16132 Genoa, Italy; (R.M.); (A.B.); (L.A.)
- Department of Experimental Medicine, Section of Human Physiology, University of Genoa, Viale Benedetto XV 3, 16132 Genoa, Italy;
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28
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Kang JH, Bae JH, Jeon YJ. Age-Related Characteristics of Resting-State Electroencephalographic Signals and the Corresponding Analytic Approaches: A Review. Bioengineering (Basel) 2024; 11:418. [PMID: 38790286 PMCID: PMC11118246 DOI: 10.3390/bioengineering11050418] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2024] [Revised: 04/18/2024] [Accepted: 04/23/2024] [Indexed: 05/26/2024] Open
Abstract
The study of the effects of aging on neural activity in the human brain has attracted considerable attention in neurophysiological, neuropsychiatric, and neurocognitive research, as it is directly linked to an understanding of the neural mechanisms underlying the disruption of the brain structures and functions that lead to age-related pathological disorders. Electroencephalographic (EEG) signals recorded during resting-state conditions have been widely used because of the significant advantage of non-invasive signal acquisition with higher temporal resolution. These advantages include the capability of a variety of linear and nonlinear signal analyses and state-of-the-art machine-learning and deep-learning techniques. Advances in artificial intelligence (AI) can not only reveal the neural mechanisms underlying aging but also enable the assessment of brain age reliably by means of the age-related characteristics of EEG signals. This paper reviews the literature on the age-related features, available analytic methods, large-scale resting-state EEG databases, interpretations of the resulting findings, and recent advances in age-related AI models.
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Affiliation(s)
- Jae-Hwan Kang
- Digital Health Research Division, Korea Institute of Oriental Medicine, Daejeon 34054, Republic of Korea; (J.-H.K.); (J.-H.B.)
- Aging Convergence Research Center, Korea Research Institute of Bioscience and Biotechnology, Daejeon 34141, Republic of Korea
| | - Jang-Han Bae
- Digital Health Research Division, Korea Institute of Oriental Medicine, Daejeon 34054, Republic of Korea; (J.-H.K.); (J.-H.B.)
- Aging Convergence Research Center, Korea Research Institute of Bioscience and Biotechnology, Daejeon 34141, Republic of Korea
| | - Young-Ju Jeon
- Digital Health Research Division, Korea Institute of Oriental Medicine, Daejeon 34054, Republic of Korea; (J.-H.K.); (J.-H.B.)
- Aging Convergence Research Center, Korea Research Institute of Bioscience and Biotechnology, Daejeon 34141, Republic of Korea
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29
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Russo S, Claar L, Marks L, Krishnan G, Furregoni G, Zauli FM, Hassan G, Solbiati M, d’Orio P, Mikulan E, Sarasso S, Rosanova M, Sartori I, Bazhenov M, Pigorini A, Massimini M, Koch C, Rembado I. Thalamic feedback shapes brain responses evoked by cortical stimulation in mice and humans. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.31.578243. [PMID: 38352535 PMCID: PMC10862802 DOI: 10.1101/2024.01.31.578243] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/23/2024]
Abstract
Cortical stimulation with single pulses is a common technique in clinical practice and research. However, we still do not understand the extent to which it engages subcortical circuits which contribute to the associated evoked potentials (EPs). Here we find that cortical stimulation generates remarkably similar EPs in humans and mice, with a late component similarly modulated by the subject's behavioral state. We optogenetically dissect the underlying circuit in mice, demonstrating that the late component of these EPs is caused by a thalamic hyperpolarization and rebound. The magnitude of this late component correlates with the bursting frequency and synchronicity of thalamic neurons, modulated by the subject's behavioral state. A simulation of the thalamo-cortical circuit highlights that both intrinsic thalamic currents as well as cortical and thalamic GABAergic neurons contribute to this response profile. We conclude that the cortical stimulation engages cortico-thalamo-cortical circuits highly preserved across different species and stimulation modalities.
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Affiliation(s)
- Simone Russo
- Department of Biomedical and Clinical Sciences, Università degli Studi di Milano, Milan 20157, Italy
- Department of Philosophy ‘Piero Martinetti’, University of Milan, Milan, Italy
- Brain and Consciousness, Allen Institute, Seattle, United States
- Wallace H Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, USA
| | - Leslie Claar
- Brain and Consciousness, Allen Institute, Seattle, United States
| | - Lydia Marks
- Brain and Consciousness, Allen Institute, Seattle, United States
| | - Giri Krishnan
- Department of Medicine, University of California San Diego, La Jolla, CA, 92093, USA
| | - Giulia Furregoni
- Department of Biomedical and Clinical Sciences, Università degli Studi di Milano, Milan 20157, Italy
| | - Flavia Maria Zauli
- Department of Biomedical and Clinical Sciences, Università degli Studi di Milano, Milan 20157, Italy
- Department of Philosophy ‘Piero Martinetti’, University of Milan, Milan, Italy
- ASST Grande Ospedale Metropolitano Niguarda, “C. Munari” Epilepsy Surgery Centre, Department of Neuroscience, Italy
| | - Gabriel Hassan
- Department of Biomedical and Clinical Sciences, Università degli Studi di Milano, Milan 20157, Italy
- Department of Philosophy ‘Piero Martinetti’, University of Milan, Milan, Italy
| | - Michela Solbiati
- Department of Biomedical and Clinical Sciences, Università degli Studi di Milano, Milan 20157, Italy
- ASST Grande Ospedale Metropolitano Niguarda, “C. Munari” Epilepsy Surgery Centre, Department of Neuroscience, Italy
| | - Piergiorgio d’Orio
- ASST Grande Ospedale Metropolitano Niguarda, “C. Munari” Epilepsy Surgery Centre, Department of Neuroscience, Italy
- University of Parma, Parma 43121, Italy
| | - Ezequiel Mikulan
- Department of Biomedical and Clinical Sciences, Università degli Studi di Milano, Milan 20157, Italy
| | - Simone Sarasso
- Department of Biomedical and Clinical Sciences, Università degli Studi di Milano, Milan 20157, Italy
| | - Mario Rosanova
- Department of Biomedical and Clinical Sciences, Università degli Studi di Milano, Milan 20157, Italy
| | - Ivana Sartori
- ASST Grande Ospedale Metropolitano Niguarda, “C. Munari” Epilepsy Surgery Centre, Department of Neuroscience, Italy
| | - Maxim Bazhenov
- Department of Medicine, University of California San Diego, La Jolla, CA, 92093, USA
- Neurosciences Graduate Program, University of California San Diego, La Jolla, CA, 92093, USA
| | - Andrea Pigorini
- Department of Biomedical, Surgical and Dental Sciences, Università degli Studi di Milano, Milan 20122, Italy
- UOC Maxillo-facial Surgery and dentistry, Fondazione IRCCS Cà Granda, Ospedale Maggiore Policlinico, Milan, Italy
| | - Marcello Massimini
- Department of Biomedical and Clinical Sciences, Università degli Studi di Milano, Milan 20157, Italy
- Istituto Di Ricovero e Cura a Carattere Scientifico, Fondazione Don Carlo Gnocchi, Milan 20122, Italy
- Azrieli Program in Brain, Mind and Consciousness, Canadian Institute for Advanced Research (CIFAR), Toronto, Ontario M5G 1M1, Canada
| | - Christof Koch
- Brain and Consciousness, Allen Institute, Seattle, United States
| | - Irene Rembado
- Brain and Consciousness, Allen Institute, Seattle, United States
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30
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Gogulski J, Cline CC, Ross JM, Parmigiani S, Keller CJ. Reliability of the TMS-evoked potential in dorsolateral prefrontal cortex. Cereb Cortex 2024; 34:bhae130. [PMID: 38596882 PMCID: PMC11004671 DOI: 10.1093/cercor/bhae130] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2023] [Revised: 03/06/2024] [Accepted: 03/07/2024] [Indexed: 04/11/2024] Open
Abstract
We currently lack a reliable method to probe cortical excitability noninvasively from the human dorsolateral prefrontal cortex (dlPFC). We recently found that the strength of early and local dlPFC transcranial magnetic stimulation (TMS)-evoked potentials (EL-TEPs) varied widely across dlPFC subregions. Despite these differences in response amplitude, reliability at each target is unknown. Here we quantified within-session reliability of dlPFC EL-TEPs after TMS to six left dlPFC subregions in 15 healthy subjects. We evaluated reliability (concordance correlation coefficient [CCC]) across targets, time windows, quantification methods, regions of interest, sensor- vs. source-space, and number of trials. On average, the medial target was most reliable (CCC = 0.78) and the most anterior target was least reliable (CCC = 0.24). However, all targets except the most anterior were reliable (CCC > 0.7) using at least one combination of the analytical parameters tested. Longer (20 to 60 ms) and later (30 to 60 ms) windows increased reliability compared to earlier and shorter windows. Reliable EL-TEPs (CCC up to 0.86) were observed using only 25 TMS trials at a medial dlPFC target. Overall, medial dlPFC targeting, wider windows, and peak-to-peak quantification improved reliability. With careful selection of target and analytic parameters, highly reliable EL-TEPs can be extracted from the dlPFC after only a small number of trials.
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Affiliation(s)
- Juha Gogulski
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, 401 Quarry Road, Stanford, CA 94305, United States
- Wu Tsai Neurosciences Institute, Stanford University, 290 Jane Stanford Way, Stanford, CA 94305, United States
- Department of Clinical Neurophysiology, HUS Diagnostic Center, Clinical Neurosciences, Helsinki University Hospital and University of Helsinki, Haartmaninkatu 4, Helsinki FI-00029, Finland
| | - Christopher C Cline
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, 401 Quarry Road, Stanford, CA 94305, United States
- Wu Tsai Neurosciences Institute, Stanford University, 290 Jane Stanford Way, Stanford, CA 94305, United States
| | - Jessica M Ross
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, 401 Quarry Road, Stanford, CA 94305, United States
- Wu Tsai Neurosciences Institute, Stanford University, 290 Jane Stanford Way, Stanford, CA 94305, United States
- Veterans Affairs Palo Alto Healthcare System, and the Sierra Pacific Mental Illness, Research, Education, and Clinical Center (MIRECC), 3801 Miranda Avenue, Palo Alto, CA 94394, United States
| | - Sara Parmigiani
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, 401 Quarry Road, Stanford, CA 94305, United States
- Wu Tsai Neurosciences Institute, Stanford University, 290 Jane Stanford Way, Stanford, CA 94305, United States
| | - Corey J Keller
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, 401 Quarry Road, Stanford, CA 94305, United States
- Wu Tsai Neurosciences Institute, Stanford University, 290 Jane Stanford Way, Stanford, CA 94305, United States
- Veterans Affairs Palo Alto Healthcare System, and the Sierra Pacific Mental Illness, Research, Education, and Clinical Center (MIRECC), 3801 Miranda Avenue, Palo Alto, CA 94394, United States
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31
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Orsher Y, Rom A, Perel R, Lahini Y, Blinder P, Shein-Idelson M. Sequentially activated discrete modules appear as traveling waves in neuronal measurements with limited spatiotemporal sampling. eLife 2024; 12:RP92254. [PMID: 38451063 PMCID: PMC10942589 DOI: 10.7554/elife.92254] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/08/2024] Open
Abstract
Numerous studies have identified traveling waves in the cortex and suggested they play important roles in brain processing. These waves are most often measured using macroscopic methods that are unable to assess the local spiking activity underlying wave dynamics. Here, we investigated the possibility that waves may not be traveling at the single neuron scale. We first show that sequentially activating two discrete brain areas can appear as traveling waves in EEG simulations. We next reproduce these results using an analytical model of two sequentially activated regions. Using this model, we were able to generate wave-like activity with variable directions, velocities, and spatial patterns, and to map the discriminability limits between traveling waves and modular sequential activations. Finally, we investigated the link between field potentials and single neuron excitability using large-scale measurements from turtle cortex ex vivo. We found that while field potentials exhibit wave-like dynamics, the underlying spiking activity was better described by consecutively activated spatially adjacent groups of neurons. Taken together, this study suggests caution when interpreting phase delay measurements as continuously propagating wavefronts in two different spatial scales. A careful distinction between modular and wave excitability profiles across scales will be critical for understanding the nature of cortical computations.
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Affiliation(s)
- Yuval Orsher
- School of Neurobiology, Biochemistry, and Biophysics, Tel Aviv UniversityTel AvivIsrael
- School of Physics & Astronomy, Faculty of Exact Sciences, Tel Aviv UniversityTel AvivIsrael
| | - Ariel Rom
- School of Neurobiology, Biochemistry, and Biophysics, Tel Aviv UniversityTel AvivIsrael
- Sagol School of Neuroscience, Tel Aviv University, IsraelTel AvivIsrael
| | - Rotem Perel
- School of Neurobiology, Biochemistry, and Biophysics, Tel Aviv UniversityTel AvivIsrael
| | - Yoav Lahini
- School of Physics & Astronomy, Faculty of Exact Sciences, Tel Aviv UniversityTel AvivIsrael
- Sagol School of Neuroscience, Tel Aviv University, IsraelTel AvivIsrael
| | - Pablo Blinder
- School of Neurobiology, Biochemistry, and Biophysics, Tel Aviv UniversityTel AvivIsrael
- Sagol School of Neuroscience, Tel Aviv University, IsraelTel AvivIsrael
| | - Mark Shein-Idelson
- School of Neurobiology, Biochemistry, and Biophysics, Tel Aviv UniversityTel AvivIsrael
- Sagol School of Neuroscience, Tel Aviv University, IsraelTel AvivIsrael
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32
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Koenig T, Diezig S, Kalburgi SN, Antonova E, Artoni F, Brechet L, Britz J, Croce P, Custo A, Damborská A, Deolindo C, Heinrichs M, Kleinert T, Liang Z, Murphy MM, Nash K, Nehaniv C, Schiller B, Smailovic U, Tarailis P, Tomescu M, Toplutaş E, Vellante F, Zanesco A, Zappasodi F, Zou Q, Michel CM. EEG-Meta-Microstates: Towards a More Objective Use of Resting-State EEG Microstate Findings Across Studies. Brain Topogr 2024; 37:218-231. [PMID: 37515678 PMCID: PMC10884358 DOI: 10.1007/s10548-023-00993-6] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2023] [Accepted: 07/16/2023] [Indexed: 07/31/2023]
Abstract
Over the last decade, EEG resting-state microstate analysis has evolved from a niche existence to a widely used and well-accepted methodology. The rapidly increasing body of empirical findings started to yield overarching patterns of associations of biological and psychological states and traits with specific microstate classes. However, currently, this cross-referencing among apparently similar microstate classes of different studies is typically done by "eyeballing" of printed template maps by the individual authors, lacking a systematic procedure. To improve the reliability and validity of future findings, we present a tool to systematically collect the actual data of template maps from as many published studies as possible and present them in their entirety as a matrix of spatial similarity. The tool also allows importing novel template maps and systematically extracting the findings associated with specific microstate maps from ongoing or published studies. The tool also allows importing novel template maps and systematically extracting the findings associated with specific microstate maps in the literature. The analysis of 40 included sets of template maps indicated that: (i) there is a high degree of similarity of template maps across studies, (ii) similar template maps were associated with converging empirical findings, and (iii) representative meta-microstates can be extracted from the individual studies. We hope that this tool will be useful in coming to a more comprehensive, objective, and overarching representation of microstate findings.
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Affiliation(s)
- Thomas Koenig
- Translational Research Center, University Hospital of Psychiatry, University of Bern, Bern, Switzerland.
- Department of Neurobiology, Care Sciences and Society, Center for Alzheimer Research, Division of Clinical Geriatrics, Karolinska Institutet, Huddinge, Sweden.
- Children's Hospital Los Angeles, The Saban Research Institute, Los Angeles, CA, 90027, USA.
| | - Sarah Diezig
- Translational Research Center, University Hospital of Psychiatry, University of Bern, Bern, Switzerland
| | | | - Elena Antonova
- Division of Psychology, Department of Life Sciences, College of Health, Medicine and Life Sciences & Centre for Cognitive Neuroscience, Brunel University London, Kingston Lane, Uxbridge, UB8 3PH, UK
| | - Fiorenzo Artoni
- Human Neuron Lab, Faculty of Medicine, Department of Clinical Neurosciences, University of Geneva, Geneva, Switzerland
| | - Lucie Brechet
- Department of Basic Neurosciences, University of Geneva, Campus Biotech, 9 Chemin des Mines, Geneva, 1202, Switzerland
| | - Juliane Britz
- Department of Psychology, University of Fribourg, Fribourg, Switzerland
| | - Pierpaolo Croce
- Department of Neurosciences, Imaging and Clinical Sciences, Behavioral Imaging and Neural Dynamics Center, Institute for Advanced Biomedical Technologies, "Gabriele d'Annunzio" University, Chieti, 66100, Italy
| | - Anna Custo
- Department of Nuclear Medicine, Geneva University Hospital (HUG), Geneva, Switzerland
| | - Alena Damborská
- Department of Psychiatry, Faculty of Medicine, University Hospital Brno, Masaryk University, Brno, Czechia
| | - Camila Deolindo
- Center of Functionally Integrative Neuroscience, Aarhus University, Aarhus, Denmark
| | - Markus Heinrichs
- Department of Psychology, Laboratory for Biological Psychology, Clinical Psychology and Psychotherapy, Albert-Ludwigs-University of Freiburg, Breisgau, Germany
| | - Tobias Kleinert
- Department of Psychology, Laboratory for Biological Psychology, Clinical Psychology and Psychotherapy, Albert-Ludwigs-University of Freiburg, Breisgau, Germany
- Department of Ergonomics, Leibniz Research Centre for Working Environment and Human Factors, Ardeystr. 67, Dortmund, 44139, Germany
| | - Zhen Liang
- School of Biomedical Engineering, Medical School, Shenzhen University, Shenzhen, China
| | - Michael M Murphy
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
- McLean Hospital, Belmont, MA, USA
| | - Kyle Nash
- Department of Psychology, University of Alberta, Edmonton, AB, T6G 2E9, Canada
| | - Chrystopher Nehaniv
- Departments of Systems Design Engineering and Electrical & Computer Engineering, University of Waterloo, 200 University Avenue W, Waterloo, ON, N2L 3G1, Canada
| | - Bastian Schiller
- Department of Psychology, Laboratory for Biological Psychology, Clinical Psychology and Psychotherapy, Albert-Ludwigs-University of Freiburg, Breisgau, Germany
| | - Una Smailovic
- Department of Neurobiology, Care Sciences and Society, Center for Alzheimer Research, Division of Clinical Geriatrics, Karolinska Institutet, Huddinge, Sweden
- Department of Clinical Neurophysiology, Karolinska University Hospital, Stockholm, Sweden
| | - Povilas Tarailis
- Life Sciences Centre, Institute of Biosciences, Vilnius University, Vilnius, Lithuania
| | - Miralena Tomescu
- CINETic Center, National University of Theatre and Film "I.L. Caragiale" Bucharest, Bucharest, Romania
- Faculty of Educational Sciences, Department of Psychology, University "Stefan cel Mare" of Suceava, Suceava, Romania
- Faculty of Psychology and Educational Sciences, Department of Cognitive Sciences, University of Bucharest, Bucharest, Romania
| | - Eren Toplutaş
- Department of Neurology, Istanbul Eyupsultan Public Hospital, Istanbul, Turkey
- Program of Neuroscience Ph.D, Graduate School of Health Sciences, Istanbul Medipol University, Istanbul, Turkey
| | - Federica Vellante
- Department of Neurosciences, Imaging and Clinical Sciences, Behavioral Imaging and Neural Dynamics Center, Institute for Advanced Biomedical Technologies, "Gabriele d'Annunzio" University, Chieti, 66100, Italy
| | - Anthony Zanesco
- Department of Psychology, University of Miami, Coral Gables, FL, USA
| | - Filippo Zappasodi
- Department of Neurosciences, Imaging and Clinical Sciences, Behavioral Imaging and Neural Dynamics Center, Institute for Advanced Biomedical Technologies, "Gabriele d'Annunzio" University, Chieti, 66100, Italy
| | - Qihong Zou
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, 100871, China
| | - Christoph M Michel
- Department of Basic Neurosciences, University of Geneva, Campus Biotech, 9 Chemin des Mines, Geneva, 1202, Switzerland
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Zhang W, Chen B, Feng J, Lu W. On a framework of data assimilation for hyperparameter estimation of spiking neuronal networks. Neural Netw 2024; 171:293-307. [PMID: 37973499 DOI: 10.1016/j.neunet.2023.11.016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Revised: 09/20/2023] [Accepted: 11/07/2023] [Indexed: 11/19/2023]
Abstract
When handling real-world data modeled by a complex network dynamical system, the number of the parameters is often much more than the size of the data. Therefore, in many cases, it is impossible to estimate these parameters and the exact value of each parameter is frequently less interesting than the distribution of the parameters. In this paper, we aim to estimate the distribution of the parameters in the mesoscopic neuronal network model from the macroscopic experimental data, for example, the BOLD (blood oxygen level dependent) signal. Herein, we assume that the parameters of the neurons and synapses are inhomogeneous but independently and identically distributed from certain distributions with unknown hyperparameters. Thus, we estimate these hyperparameters of the distributions of the parameters, instead of estimating the parameters themselves. We formulate this problem under the framework of data assimilation and hierarchical Bayesian method and present an efficient method named Hierarchical Data Assimilation (HDA) to conduct the statistical inference on the neuronal network model with the BOLD signal data simulated by the hemodynamic model. We consider the Leaky Integral-Fire (LIF) neuronal networks with four synapses and show that the proposed algorithm can estimate the BOLD signals and the hyperparameters with high preciseness. In addition, we discuss the influence on the performance of the algorithm configuration and the LIF network model setup.
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Affiliation(s)
- Wenyong Zhang
- School of Mathematical Sciences, Fudan University, No. 220 Handan Road, Shanghai, 200433, Shanghai, China
| | - Boyu Chen
- School of Mathematical Sciences, Fudan University, No. 220 Handan Road, Shanghai, 200433, Shanghai, China
| | - Jianfeng Feng
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, No. 220 Handan Road, Shanghai, 200433, Shanghai, China; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, No. 220 Handan Road, Shanghai, 200433, Shanghai, China
| | - Wenlian Lu
- School of Mathematical Sciences, Fudan University, No. 220 Handan Road, Shanghai, 200433, Shanghai, China; Shanghai Center for Mathematical Sciences, No. 220 Handan Road, Shanghai, 200433, Shanghai, China; Shanghai Key Laboratory for Contemporary Applied Mathematics, No. 220 Handan Road, Shanghai, 200433, Shanghai, China; Key Laboratory of Mathematics for Nonlinear Science, No. 220 Handan Road, Shanghai, 200433, Shanghai, China; Fudan ISTBI-ZJNU Algorithm Centre for Brain-Inspired Intelligence, No. 220 Handan Road, Shanghai, 200433, Shanghai, China.
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34
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Bueno FD, Nobre AC, Cravo AM. Time for What? Dissociating Explicit Timing Tasks through Electrophysiological Signatures. eNeuro 2024; 11:ENEURO.0351-23.2023. [PMID: 38272676 PMCID: PMC10884563 DOI: 10.1523/eneuro.0351-23.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Revised: 11/17/2023] [Accepted: 12/04/2023] [Indexed: 01/27/2024] Open
Abstract
Estimating durations between hundreds of milliseconds and seconds is essential for several daily tasks. Explicit timing tasks, which require participants to estimate durations to make a comparison (time for perception) or to reproduce them (time for action), are often used to investigate psychological and neural timing mechanisms. Recent studies have proposed that mechanisms may depend on specific task requirements. In this study, we conducted electroencephalogram (EEG) recordings on human participants as they estimated intervals in different task contexts to investigate the extent to which timing mechanisms depend on the nature of the task. We compared the neural processing of identical visual reference stimuli in two different tasks, in which stimulus durations were either perceptually compared or motorically reproduced in separate experimental blocks. Using multivariate pattern analyses, we could successfully decode the duration and the task of reference stimuli. We found evidence for both overlapping timing mechanisms across tasks as well as recruitment of task-dependent processes for comparing intervals for different purposes. Our findings suggest both core and specialized timing functions are recruited to support explicit timing tasks.
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Affiliation(s)
- Fernanda D Bueno
- Center for Mathematics, Computing and Cognition (CMCC), Federal University of ABC (UFABC), São Bernardo do Campo 09606-045, Brazil
| | - Anna C Nobre
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford OX3 7JX, United Kingdom
- Department of Experimental Psychology, University of Oxford, Oxford OX2 6GG, United Kingdom
| | - André M Cravo
- Center for Mathematics, Computing and Cognition (CMCC), Federal University of ABC (UFABC), São Bernardo do Campo 09606-045, Brazil
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Giustiniani J, Nicolier M, Diwoux A, Chabin T, Pazart L, Haffen E, Gabriel D. Impact of online poker gambling on behavioural and neurophysiological responses to a virtual gambling task. Addict Biol 2024; 29:e13373. [PMID: 38380791 PMCID: PMC10898831 DOI: 10.1111/adb.13373] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Revised: 11/10/2023] [Accepted: 01/09/2024] [Indexed: 02/22/2024]
Abstract
Online poker gambling (OPG) involves various executive control processes and emotion regulation. In this context, we hypothesized that online poker players, accustomed to handling virtual cards, would show high performance on computerized decision-making tasks such as the Iowa Gambling Task (IGT). Using press advertisements, we recruited a non-gambler group (NG; n = 20) and an OPG group (n = 22). All participants performed the IGT while their cerebral activity was recorded by electroencephalography. Compared with the OPG group, the NG group showed significantly better progression in the IGT in the last trials. Recording of brain activity revealed the appearance of a temporal map between 150 and 175 ms specific to the gain condition in both groups. A second map was observed at 215-295 ms specifically in the NG group, and the generators were identified in the occipital regions. This activity is indicative of a high level of visual awareness; thus, it reflects additional processing of visual information, which can be assumed to be induced by the lower exposure of the NGs to online card games. We hypothesize that the absence of this activity in the OPG group might be due to their online habituation to virtual environments.
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Affiliation(s)
- Julie Giustiniani
- UMR INSERM 1322LINCUniversité de Franche‐ComtéBesançonFrance
- Département clinique de psychiatrieCentre hospitalier universitaire de BesançonBesançonFrance
- Centre hospitalier Universitaire de BesançonBesançonFrance
| | - Magali Nicolier
- UMR INSERM 1322LINCUniversité de Franche‐ComtéBesançonFrance
- Département clinique de psychiatrieCentre hospitalier universitaire de BesançonBesançonFrance
- Centre hospitalier Universitaire de BesançonBesançonFrance
- Neuraxess département de neuroimagerie et neurostimulationUniversité de Franche ComtéBesançonFrance
| | - Audrey Diwoux
- Neuraxess département de neuroimagerie et neurostimulationUniversité de Franche ComtéBesançonFrance
| | - Thibaut Chabin
- Département clinique de psychiatrieCentre hospitalier universitaire de BesançonBesançonFrance
- Neuraxess département de neuroimagerie et neurostimulationUniversité de Franche ComtéBesançonFrance
| | - Lionel Pazart
- UMR INSERM 1322LINCUniversité de Franche‐ComtéBesançonFrance
- Centre hospitalier Universitaire de BesançonBesançonFrance
| | - Emmanuel Haffen
- UMR INSERM 1322LINCUniversité de Franche‐ComtéBesançonFrance
- Département clinique de psychiatrieCentre hospitalier universitaire de BesançonBesançonFrance
- Centre hospitalier Universitaire de BesançonBesançonFrance
- FondaMental FondationCréteilFrance
| | - Damien Gabriel
- UMR INSERM 1322LINCUniversité de Franche‐ComtéBesançonFrance
- Centre hospitalier Universitaire de BesançonBesançonFrance
- Neuraxess département de neuroimagerie et neurostimulationUniversité de Franche ComtéBesançonFrance
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Chmiel J, Rybakowski F, Leszek J. EEG in Down Syndrome-A Review and Insights into Potential Neural Mechanisms. Brain Sci 2024; 14:136. [PMID: 38391711 PMCID: PMC10886507 DOI: 10.3390/brainsci14020136] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2023] [Revised: 01/23/2024] [Accepted: 01/26/2024] [Indexed: 02/24/2024] Open
Abstract
Introduction: Down syndrome (DS) stands out as one of the most prevalent genetic disorders, imposing a significant burden on both society and the healthcare system. Scientists are making efforts to understand the neural mechanisms behind the pathophysiology of this disorder. Among the valuable methods for studying these mechanisms is electroencephalography (EEG), a non-invasive technique that measures the brain's electrical activity, characterised by its excellent temporal resolution. This review aims to consolidate studies examining EEG usage in individuals with DS. The objective was to identify shared elements of disrupted EEG activity and, crucially, to elucidate the neural mechanisms underpinning these deviations. Searches were conducted on Pubmed/Medline, Research Gate, and Cochrane databases. Results: The literature search yielded 17 relevant articles. Despite the significant time span, small sample size, and overall heterogeneity of the included studies, three common features of aberrant EEG activity in people with DS were found. Potential mechanisms for this altered activity were delineated. Conclusions: The studies included in this review show altered EEG activity in people with DS compared to the control group. To bolster these current findings, future investigations with larger sample sizes are imperative.
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Affiliation(s)
- James Chmiel
- Institute of Neurofeedback and tDCS Poland, 70-393 Szczecin, Poland
| | - Filip Rybakowski
- Department and Clinic of Psychiatry, Poznan University of Medical Sciences, 61-701 Poznań, Poland
| | - Jerzy Leszek
- Department and Clinic of Psychiatry, Wrocław Medical University, 54-235 Wrocław, Poland
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De Pascalis V. Brain Functional Correlates of Resting Hypnosis and Hypnotizability: A Review. Brain Sci 2024; 14:115. [PMID: 38391691 PMCID: PMC10886478 DOI: 10.3390/brainsci14020115] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Revised: 01/12/2024] [Accepted: 01/18/2024] [Indexed: 02/24/2024] Open
Abstract
This comprehensive review delves into the cognitive neuroscience of hypnosis and variations in hypnotizability by examining research employing functional magnetic resonance imaging (fMRI), positron emission tomography (PET), and electroencephalography (EEG) methods. Key focus areas include functional brain imaging correlations in hypnosis, EEG band oscillations as indicators of hypnotic states, alterations in EEG functional connectivity during hypnosis and wakefulness, drawing critical conclusions, and suggesting future research directions. The reviewed functional connectivity findings support the notion that disruptions in the available integration between different components of the executive control network during hypnosis may correspond to altered subjective appraisals of the agency during the hypnotic response, as per dissociated and cold control theories of hypnosis. A promising exploration avenue involves investigating how frontal lobes' neurochemical and aperiodic components of the EEG activity at waking-rest are linked to individual differences in hypnotizability. Future studies investigating the effects of hypnosis on brain function should prioritize examining distinctive activation patterns across various neural networks.
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Affiliation(s)
- Vilfredo De Pascalis
- Department of Psychology, La Sapienza University of Rome, 00185 Rome, Italy
- School of Psychology, University of New England, Armidale, NSW 2351, Australia
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38
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Erickson B, Rich R, Shankar S, Kim B, Driscoll N, Mentzelopoulos G, Fernandez-Nuñez G, Vitale F, Medaglia JD. Evaluating and benchmarking the EEG signal quality of high-density, dry MXene-based electrode arrays against gelled Ag/AgCl electrodes. J Neural Eng 2024; 21:016005. [PMID: 38081060 PMCID: PMC10788783 DOI: 10.1088/1741-2552/ad141e] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2023] [Revised: 09/17/2023] [Accepted: 12/11/2023] [Indexed: 01/13/2024]
Abstract
Objective.To evaluate the signal quality of dry MXene-based electrode arrays (also termed 'MXtrodes') for electroencephalographic (EEG) recordings where gelled Ag/AgCl electrodes are a standard.Approach.We placed 4 × 4 MXtrode arrays and gelled Ag/AgCl electrodes on different scalp locations. The scalp was cleaned with alcohol and rewetted with saline before application. We recorded from both electrode types simultaneously while participants performed a vigilance task.Main results.The root mean squared amplitude of MXtrodes was slightly higher than that of Ag/AgCl electrodes (.24-1.94 uV). Most MXtrode pairs had slightly lower broadband spectral coherence (.05 to .1 dB) and Delta- and Theta-band timeseries correlation (.05 to .1 units) compared to the Ag/AgCl pair (p< .001). However, the magnitude of correlation and coherence was high across both electrode types. Beta-band timeseries correlation and spectral coherence were higher between neighboring MXtrodes in the array (.81 to .84 units) than between any other pair (.70 to .75 units). This result suggests the close spacing of the nearest MXtrodes (3 mm) more densely sampled high spatial-frequency topographies. Event-related potentials were more similar between MXtrodes (ρ⩾ .95) than equally spaced Ag/AgCl electrodes (ρ⩽ .77,p< .001). Dry MXtrode impedance (x̄= 5.15 KΩ cm2) was higher and more variable than gelled Ag/AgCl electrodes (x̄= 1.21 KΩ cm2,p< .001). EEG was also recorded on the scalp across diverse hair types.Significance.Dry MXene-based electrodes record EEG at a quality comparable to conventional gelled Ag/AgCl while requiring minimal scalp preparation and no gel. MXtrodes can record independent signals at a spatial density four times higher than conventional electrodes, including through hair, thus opening novel opportunities for research and clinical applications that could benefit from dry and higher-density configurations.
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Affiliation(s)
- Brian Erickson
- Applied Cognitive and Brain Sciences, Department of Psychology, Drexel University, Philadelphia, PA 19104, United States of America
| | - Ryan Rich
- Applied Cognitive and Brain Sciences, Department of Psychology, Drexel University, Philadelphia, PA 19104, United States of America
| | - Sneha Shankar
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA 19104, United States of America
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, United States of America
- Center for Neurotrauma, Neurodegeneration, and Restoration, Corporal Michael J. Crescenz Veterans Affairs Medical Center, Philadelphia, PA 19104, United States of America
| | - Brian Kim
- Applied Cognitive and Brain Sciences, Department of Psychology, Drexel University, Philadelphia, PA 19104, United States of America
| | - Nicolette Driscoll
- Laboratory of Electronics Research, Massachusetts Institute of Technology, Cambridge, MA 02139, United States of America
| | - Georgios Mentzelopoulos
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA 19104, United States of America
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, United States of America
- Center for Neurotrauma, Neurodegeneration, and Restoration, Corporal Michael J. Crescenz Veterans Affairs Medical Center, Philadelphia, PA 19104, United States of America
| | - Guadalupe Fernandez-Nuñez
- Applied Cognitive and Brain Sciences, Department of Psychology, Drexel University, Philadelphia, PA 19104, United States of America
| | - Flavia Vitale
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA 19104, United States of America
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, United States of America
- Department of Neurology, University of Pennsylvania, Philadelphia, PA 19104, United States of America
- Department of Physical Medicine and Rehabilitation, University of Pennsylvania, Philadelphia, PA 19104, United States of America
| | - John D Medaglia
- Applied Cognitive and Brain Sciences, Department of Psychology, Drexel University, Philadelphia, PA 19104, United States of America
- Department of Neurology, University of Pennsylvania, Philadelphia, PA 19104, United States of America
- Department of Neurology, Drexel University, Philadelphia, PA 19104, United States of America
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Botta A, Zhao M, Samogin J, Pelosin E, Bonassi G, Lagravinese G, Mantini D, Avenanti A, Avanzino L. Early modulations of neural oscillations during the processing of emotional body language. Psychophysiology 2024; 61:e14436. [PMID: 37681463 DOI: 10.1111/psyp.14436] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2022] [Revised: 08/01/2023] [Accepted: 08/24/2023] [Indexed: 09/09/2023]
Abstract
The processing of threat-related emotional body language (EBL) has been shown to engage sensorimotor cortical areas early on and induce freezing in the observers' motor system, particularly when observing fearful EBL. To provide insights into the interplay between somatosensory and motor areas during observation of EBL, here, we used high-density electroencephalography (hd-EEG) in healthy humans while they observed EBL stimuli involving fearful and neutral expressions. To capture early sensorimotor brain response, we focused on P100 fronto-central event-related potentials (ERPs) and event-related desynchronization/synchronization (ERD/ERS) in the mu-alpha (8-13 Hz) and lower beta (13-20 Hz) bands over the primary motor (M1) and somatosensory (S1) cortices. Source-level ERP and ERD/ERS analyses were conducted using eLORETA. Results revealed higher P100 amplitudes in motor and premotor channels for 'Neutral' compared with 'Fear'. Additionally, analysis of ERD/ERS showed increased beta band desynchronization in M1 for 'Neutral', and the opposite pattern in S1. Source-level estimation showed significant differences between conditions mainly observed in the beta band over sensorimotor areas. These findings provide high-temporal resolution evidence suggesting that seeing fearful EBL induces early activation of somatosensory areas, which in turn could suppress M1 activity. These findings highlight early dynamics within the observer's sensorimotor system and hint at a sensorimotor mechanism supporting freezing during the processing of EBL.
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Affiliation(s)
| | - Mingqi Zhao
- Movement Control and Neuroplasticity Research Group, KU Leuven, Leuven, Belgium
| | - Jessica Samogin
- Movement Control and Neuroplasticity Research Group, KU Leuven, Leuven, Belgium
| | - Elisa Pelosin
- IRCCS Ospedale Policlinico San Martino, Genoa, Italy
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, and Maternal Child Health (DINOGMI), University of Genoa, Genoa, Italy
| | - Gaia Bonassi
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, and Maternal Child Health (DINOGMI), University of Genoa, Genoa, Italy
| | - Giovanna Lagravinese
- IRCCS Ospedale Policlinico San Martino, Genoa, Italy
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, and Maternal Child Health (DINOGMI), University of Genoa, Genoa, Italy
| | - Dante Mantini
- Movement Control and Neuroplasticity Research Group, KU Leuven, Leuven, Belgium
| | - Alessio Avenanti
- Centro studi e ricerche in Neuroscienze Cognitive, Dipartimento di Psicologia "Renzo Canestrari", Campus Cesena, Alma Mater Studiorum Università di Bologna, Cesena, Italy
- Centro de Investigación en Neuropsicología y Neurociencias Cognitivas, Universidad Católica del Maule, Talca, Chile
| | - Laura Avanzino
- IRCCS Ospedale Policlinico San Martino, Genoa, Italy
- Department of Experimental Medicine (DIMES), Section of Human Physiology, University of Genoa, Genoa, Italy
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40
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Osumi M, Sumitani M, Iwatsuki K, Hoshiyama M, Imai R, Morioka S, Hirata H. Resting-state Electroencephalography Microstates Correlate with Pain Intensity in Patients with Complex Regional Pain Syndrome. Clin EEG Neurosci 2024; 55:121-129. [PMID: 37844609 DOI: 10.1177/15500594231204174] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/18/2023]
Abstract
Objective: Severe pain and other symptoms in complex regional pain syndrome (CRPS), such as allodynia and hyperalgesia, are associated with abnormal resting-state brain network activity. No studies to date have examined resting-state brain networks in CRPS patients using electroencephalography (EEG), which can clarify the temporal dynamics of brain networks. Methods: We conducted microstate analysis using resting-state EEG signals to prospectively reveal direct correlations with pain intensity in CRPS patients (n = 17). Five microstate topographies were fitted back to individual CRPS patients' EEG data, and temporal microstate measures were subsequently calculated. Results: Our results revealed five distinct microstates, termed microstates A to E, from resting EEG data in patients with CRPS. Microstates C, D and E were significantly correlated with pain intensity before pain treatment. Particularly, microstates D and E were significantly improved together with pain alleviation after pain treatment. As microstates D and E in the present study have previously been related to attentional networks and the default mode network, improvement in these networks might be related to pain relief in CRPS patients. Conclusions: The functional alterations of these brain networks affected the pain intensity of CRPS patients. Therefore, EEG microstate analyses may be used to identify surrogate markers for pain intensity.
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Affiliation(s)
- Michihiro Osumi
- Graduate School of Health Science, Kio University. 4-2-2 Umaminaka, Kitakatsuragigun, Nara, Japan
- Neurorehabilitation Research Center, Kio University. 4-2-2 Umaminaka, Kitakatsuragigun, Nara, Japan
| | - Masahiko Sumitani
- Department of Pain and Palliative Medicine, The University of Tokyo Hospital. 7-3-1 Hongo, Bunkyo-ku, Tokyo, Japan
| | - Katsuyuki Iwatsuki
- Department of Hand Surgery, Graduate School of Medicine, Nagoya University, 65 Tsurumai-cho, Showa-ku, Nagoya, Aichi, Japan
| | - Minoru Hoshiyama
- Department of Health Sciences, Faculty of Medicine, Nagoya University, 1-1-20 Daiko-minami, Higashi-ku, Nagoya, Aichi, Japan
| | - Ryota Imai
- School of Rehabilitation, Osaka Kawasaki Rehabilitation University, Kaizuka, Osaka, Japan
| | - Shu Morioka
- Graduate School of Health Science, Kio University. 4-2-2 Umaminaka, Kitakatsuragigun, Nara, Japan
- Neurorehabilitation Research Center, Kio University. 4-2-2 Umaminaka, Kitakatsuragigun, Nara, Japan
| | - Hitoshi Hirata
- Department of Hand Surgery, Graduate School of Medicine, Nagoya University, 65 Tsurumai-cho, Showa-ku, Nagoya, Aichi, Japan
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41
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Kaltsouni E, Schmidt F, Zsido RG, Eriksson A, Sacher J, Sundström-Poromaa I, Sumner RL, Comasco E. Electroencephalography findings in menstrually-related mood disorders: A critical review. Front Neuroendocrinol 2024; 72:101120. [PMID: 38176542 DOI: 10.1016/j.yfrne.2023.101120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Revised: 12/21/2023] [Accepted: 12/31/2023] [Indexed: 01/06/2024]
Abstract
The female reproductive years are characterized by fluctuations in ovarian hormones across the menstrual cycle, which have the potential to modulate neurophysiological and behavioral dynamics. Menstrually-related mood disorders (MRMDs) comprise cognitive-affective or somatic symptoms that are thought to be triggered by the rapid fluctuations in ovarian hormones in the luteal phase of the menstrual cycle. MRMDs include premenstrual syndrome (PMS), premenstrual dysphoric disorder (PMDD), and premenstrual exacerbation (PME) of other psychiatric disorders. Electroencephalography (EEG) non-invasively records in vivo synchronous activity from populations of neurons with high temporal resolution. The present overview sought to systematically review the current state of task-related and resting-state EEG investigations on MRMDs. Preliminary evidence indicates lower alpha asymmetry at rest being associated with MRMDs, while one study points to the effect being luteal-phase specific. Moreover, higher luteal spontaneous frontal brain activity (slow/fast wave ratio as measured by the delta/beta power ratio) has been observed in persons with MRMDs, while sleep architecture results point to potential circadian rhythm disturbances. In this review, we discuss the quality of study designs as well as future perspectives and challenges of supplementing the diagnostic and scientific toolbox for MRMDs with EEG.
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Affiliation(s)
- Elisavet Kaltsouni
- Department of Womeńs and Childreńs Health, Science for Life Laboratory, Uppsala University, Sweden
| | - Felix Schmidt
- Department of Womeńs and Childreńs Health, Science for Life Laboratory, Uppsala University, Sweden; Centre for Women's Mental Health during the Reproductive Lifespan, Uppsala University, 751 85 Uppsala, Sweden
| | - Rachel G Zsido
- Cognitive Neuroendocrinology, Max Planck Institute for Human Cognitive and Brain Sciences, Germany; Department of Psychiatry, Clinical Neuroscience Laboratory for Sex Differences in the Brain, Massachusetts General Hospital, Harvard Medical School, USA
| | - Allison Eriksson
- Centre for Women's Mental Health during the Reproductive Lifespan, Uppsala University, 751 85 Uppsala, Sweden; Department of Womeńs and Childreńs Health, Uppsala University, Sweden
| | - Julia Sacher
- Cognitive Neuroendocrinology, Max Planck Institute for Human Cognitive and Brain Sciences, Germany; Clinic of Cognitive Neurology, University of Leipzig, Germany
| | | | | | - Erika Comasco
- Department of Womeńs and Childreńs Health, Science for Life Laboratory, Uppsala University, Sweden.
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42
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Xiang J, Sun Y, Wu X, Guo Y, Xue J, Niu Y, Cui X. Abnormal Spatial and Temporal Overlap of Time-Varying Brain Functional Networks in Patients with Schizophrenia. Brain Sci 2023; 14:40. [PMID: 38248255 PMCID: PMC10813230 DOI: 10.3390/brainsci14010040] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2023] [Revised: 12/25/2023] [Accepted: 12/27/2023] [Indexed: 01/23/2024] Open
Abstract
Schizophrenia (SZ) is a complex psychiatric disorder with unclear etiology and pathological features. Neuroscientists are increasingly proposing that schizophrenia is an abnormality in the dynamic organization of brain networks. Previous studies have found that the dynamic brain networks of people with SZ are abnormal in both space and time. However, little is known about the interactions and overlaps between hubs of the brain underlying spatiotemporal dynamics. In this study, we aimed to investigate different patterns of spatial and temporal overlap of hubs between SZ patients and healthy individuals. Specifically, we obtained resting-state functional magnetic resonance imaging data from the public dataset for 43 SZ patients and 49 healthy individuals. We derived a representation of time-varying functional connectivity using the Jackknife Correlation (JC) method. We employed the Betweenness Centrality (BC) method to identify the hubs of the brain's functional connectivity network. We then applied measures of temporal overlap, spatial overlap, and hierarchical clustering to investigate differences in the organization of brain hubs between SZ patients and healthy controls. Our findings suggest significant differences between SZ patients and healthy controls at the whole-brain and subnetwork levels. Furthermore, spatial overlap and hierarchical clustering analysis showed that quasi-periodic patterns were disrupted in SZ patients. Analyses of temporal overlap revealed abnormal pairwise engagement preferences in the hubs of SZ patients. These results provide new insights into the dynamic characteristics of the network organization of the SZ brain.
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Affiliation(s)
- Jie Xiang
- College of Computer Science and Technology, Taiyuan University of Technology, Taiyuan 030024, China; (J.X.); (Y.S.); (X.W.); (J.X.); (Y.N.)
| | - Yumeng Sun
- College of Computer Science and Technology, Taiyuan University of Technology, Taiyuan 030024, China; (J.X.); (Y.S.); (X.W.); (J.X.); (Y.N.)
| | - Xubin Wu
- College of Computer Science and Technology, Taiyuan University of Technology, Taiyuan 030024, China; (J.X.); (Y.S.); (X.W.); (J.X.); (Y.N.)
| | - Yuxiang Guo
- School of Software, Taiyuan University of Technology, Taiyuan 030024, China;
| | - Jiayue Xue
- College of Computer Science and Technology, Taiyuan University of Technology, Taiyuan 030024, China; (J.X.); (Y.S.); (X.W.); (J.X.); (Y.N.)
| | - Yan Niu
- College of Computer Science and Technology, Taiyuan University of Technology, Taiyuan 030024, China; (J.X.); (Y.S.); (X.W.); (J.X.); (Y.N.)
| | - Xiaohong Cui
- College of Computer Science and Technology, Taiyuan University of Technology, Taiyuan 030024, China; (J.X.); (Y.S.); (X.W.); (J.X.); (Y.N.)
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43
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Lin S, Jiang J, Huang K, Li L, He X, Du P, Wu Y, Liu J, Li X, Huang Z, Zhou Z, Yu Y, Gao J, Lei M, Wu H. Advanced Electrode Technologies for Noninvasive Brain-Computer Interfaces. ACS NANO 2023; 17:24487-24513. [PMID: 38064282 DOI: 10.1021/acsnano.3c06781] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/27/2023]
Abstract
Brain-computer interfaces (BCIs) have garnered significant attention in recent years due to their potential applications in medical, assistive, and communication technologies. Building on this, noninvasive BCIs stand out as they provide a safe and user-friendly method for interacting with the human brain. In this work, we provide a comprehensive overview of the latest developments and advancements in material, design, and application of noninvasive BCIs electrode technology. We also explore the challenges and limitations currently faced by noninvasive BCI electrode technology and sketch out the technological roadmap from three dimensions: Materials and Design; Performances; Mode and Function. We aim to unite research efforts within the field of noninvasive BCI electrode technology, focusing on the consolidation of shared goals and fostering integrated development strategies among a diverse array of multidisciplinary researchers.
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Affiliation(s)
- Sen Lin
- School of Physical Science and Technology, Guangxi University, Nanning 530004, China
| | - Jingjing Jiang
- School of Physical Science and Technology, Guangxi University, Nanning 530004, China
| | - Kai Huang
- State Key Laboratory of New Ceramics and Fine Processing, School of Materials Science and Engineering, Tsinghua University, Beijing 100084, China
- State Key Laboratory of Information Photonics and Optical Communications and School of Science, Beijing University of Posts and Telecommunications, Beijing 100876, China
| | - Lei Li
- National Engineering Research Center of Electric Vehicles, Beijing Institute of Technology, Beijing 100081, China
| | - Xian He
- State Key Laboratory of New Ceramics and Fine Processing, School of Materials Science and Engineering, Tsinghua University, Beijing 100084, China
| | - Peng Du
- State Key Laboratory of New Ceramics and Fine Processing, School of Materials Science and Engineering, Tsinghua University, Beijing 100084, China
| | - Yufeng Wu
- State Key Laboratory of New Ceramics and Fine Processing, School of Materials Science and Engineering, Tsinghua University, Beijing 100084, China
| | - Junchen Liu
- State Key Laboratory of New Ceramics and Fine Processing, School of Materials Science and Engineering, Tsinghua University, Beijing 100084, China
- State Key Laboratory of Information Photonics and Optical Communications and School of Science, Beijing University of Posts and Telecommunications, Beijing 100876, China
| | - Xilin Li
- School of Physical Science and Technology, Guangxi University, Nanning 530004, China
- Advanced Institute for Brain and Intelligence, Guangxi University, Nanning 530004, China
| | - Zhibao Huang
- School of Physical Science and Technology, Guangxi University, Nanning 530004, China
| | - Zenan Zhou
- School of Physical Science and Technology, Guangxi University, Nanning 530004, China
| | - Yuanhang Yu
- School of Physical Science and Technology, Guangxi University, Nanning 530004, China
| | - Jiaxin Gao
- School of Physical Science and Technology, Guangxi University, Nanning 530004, China
| | - Ming Lei
- State Key Laboratory of Information Photonics and Optical Communications and School of Science, Beijing University of Posts and Telecommunications, Beijing 100876, China
| | - Hui Wu
- State Key Laboratory of New Ceramics and Fine Processing, School of Materials Science and Engineering, Tsinghua University, Beijing 100084, China
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44
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Paban V, Mheich A, Spieser L, Sacher M. A multidimensional model of memory complaints in older individuals and the associated hub regions. Front Aging Neurosci 2023; 15:1324309. [PMID: 38187362 PMCID: PMC10771290 DOI: 10.3389/fnagi.2023.1324309] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Accepted: 11/27/2023] [Indexed: 01/09/2024] Open
Abstract
Memory complaints are highly prevalent among middle-aged and older adults, and they are frequently reported in individuals experiencing subjective cognitive decline (SCD). SCD has received increasing attention due to its implications for the early detection of dementia. This study aims to advance our comprehension of individuals with SCD by elucidating potential cognitive/psychologic-contributing factors and characterizing cerebral hubs within the brain network. To identify these potential contributing factors, a structural equation modeling approach was employed to investigate the relationships between various factors, such as metacognitive beliefs, personality, anxiety, depression, self-esteem, and resilience, and memory complaints. Our findings revealed that self-esteem and conscientiousness significantly influenced memory complaints. At the cerebral level, analysis of delta and theta electroencephalographic frequency bands recorded during rest was conducted to identify hub regions using a local centrality metric known as betweenness centrality. Notably, our study demonstrated that certain brain regions undergo changes in their hub roles in response to the pathology of SCD. Specifically, the inferior temporal gyrus and the left orbitofrontal area transition into hubs, while the dorsolateral prefrontal cortex and the middle temporal gyrus lose their hub function in the presence of SCD. This rewiring of the neural network may be interpreted as a compensatory response employed by the brain in response to SCD, wherein functional connectivity is maintained or restored by reallocating resources to other regions.
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Affiliation(s)
- Véronique Paban
- Aix-Marseille Université, CNRS, LNC (Laboratoire de Neurosciences Cognitives–UMR 7291), Marseille, France
| | - A. Mheich
- CHUV-Centre Hospitalier Universitaire Vaudois, Service des Troubles du Spectre de l’Autisme et Apparentés, Lausanne University Hospital, Lausanne, Switzerland
| | - L. Spieser
- Aix-Marseille Université, CNRS, LNC (Laboratoire de Neurosciences Cognitives–UMR 7291), Marseille, France
| | - M. Sacher
- University of Toulouse Jean-Jaurès, CNRS, LCLLE (Laboratoire Cognition, Langues, Langage, Ergonomie–UMR 5263), Toulouse, France
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45
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Ross JM, Cline CC, Sarkar M, Truong J, Keller CJ. Neural effects of TMS trains on the human prefrontal cortex. Sci Rep 2023; 13:22700. [PMID: 38123591 PMCID: PMC10733322 DOI: 10.1038/s41598-023-49250-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Accepted: 12/06/2023] [Indexed: 12/23/2023] Open
Abstract
How does a train of TMS pulses modify neural activity in humans? Despite adoption of repetitive TMS (rTMS) for the treatment of neuropsychiatric disorders, we still do not understand how rTMS changes the human brain. This limited understanding stems in part from a lack of methods for noninvasively measuring the neural effects of a single TMS train-a fundamental building block of treatment-as well as the cumulative effects of consecutive TMS trains. Gaining this understanding would provide foundational knowledge to guide the next generation of treatments. Here, to overcome this limitation, we developed methods to noninvasively measure causal and acute changes in cortical excitability and evaluated this neural response to single and sequential TMS trains. In 16 healthy adults, standard 10 Hz trains were applied to the dorsolateral prefrontal cortex in a randomized, sham-controlled, event-related design and changes were assessed based on the TMS-evoked potential (TEP), a measure of cortical excitability. We hypothesized that single TMS trains would induce changes in the local TEP amplitude and that those changes would accumulate across sequential trains, but primary analyses did not indicate evidence in support of either of these hypotheses. Exploratory analyses demonstrated non-local neural changes in sensor and source space and local neural changes in phase and source space. Together these results suggest that single and sequential TMS trains may not be sufficient to modulate local cortical excitability indexed by typical TEP amplitude metrics but may cause neural changes that can be detected outside the stimulation area or using phase or source space metrics. This work should be contextualized as methods development for the monitoring of transient noninvasive neural changes during rTMS and contributes to a growing understanding of the neural effects of rTMS.
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Affiliation(s)
- Jessica M Ross
- Department of Psychiatry and Behavioral Sciences, Stanford University Medical Center, 401 Quarry Road, Stanford, CA, 94305-5797, USA
- Veterans Affairs Palo Alto Healthcare System, and the Sierra Pacific Mental Illness, Research, Education, and Clinical Center (MIRECC), 3801 Miranda Avenue, Palo Alto, CA, 94304, USA
- Wu Tsai Neuroscience Institute, Stanford University, Stanford, CA, USA
| | - Christopher C Cline
- Department of Psychiatry and Behavioral Sciences, Stanford University Medical Center, 401 Quarry Road, Stanford, CA, 94305-5797, USA
- Wu Tsai Neuroscience Institute, Stanford University, Stanford, CA, USA
| | - Manjima Sarkar
- Department of Psychiatry and Behavioral Sciences, Stanford University Medical Center, 401 Quarry Road, Stanford, CA, 94305-5797, USA
- Wu Tsai Neuroscience Institute, Stanford University, Stanford, CA, USA
| | - Jade Truong
- Department of Psychiatry and Behavioral Sciences, Stanford University Medical Center, 401 Quarry Road, Stanford, CA, 94305-5797, USA
- Wu Tsai Neuroscience Institute, Stanford University, Stanford, CA, USA
| | - Corey J Keller
- Department of Psychiatry and Behavioral Sciences, Stanford University Medical Center, 401 Quarry Road, Stanford, CA, 94305-5797, USA.
- Veterans Affairs Palo Alto Healthcare System, and the Sierra Pacific Mental Illness, Research, Education, and Clinical Center (MIRECC), 3801 Miranda Avenue, Palo Alto, CA, 94304, USA.
- Wu Tsai Neuroscience Institute, Stanford University, Stanford, CA, USA.
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46
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Zhang H, Zhou QQ, Chen H, Hu XQ, Li WG, Bai Y, Han JX, Wang Y, Liang ZH, Chen D, Cong FY, Yan JQ, Li XL. The applied principles of EEG analysis methods in neuroscience and clinical neurology. Mil Med Res 2023; 10:67. [PMID: 38115158 PMCID: PMC10729551 DOI: 10.1186/s40779-023-00502-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/25/2023] [Accepted: 11/23/2023] [Indexed: 12/21/2023] Open
Abstract
Electroencephalography (EEG) is a non-invasive measurement method for brain activity. Due to its safety, high resolution, and hypersensitivity to dynamic changes in brain neural signals, EEG has aroused much interest in scientific research and medical fields. This article reviews the types of EEG signals, multiple EEG signal analysis methods, and the application of relevant methods in the neuroscience field and for diagnosing neurological diseases. First, three types of EEG signals, including time-invariant EEG, accurate event-related EEG, and random event-related EEG, are introduced. Second, five main directions for the methods of EEG analysis, including power spectrum analysis, time-frequency analysis, connectivity analysis, source localization methods, and machine learning methods, are described in the main section, along with different sub-methods and effect evaluations for solving the same problem. Finally, the application scenarios of different EEG analysis methods are emphasized, and the advantages and disadvantages of similar methods are distinguished. This article is expected to assist researchers in selecting suitable EEG analysis methods based on their research objectives, provide references for subsequent research, and summarize current issues and prospects for the future.
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Affiliation(s)
- Hao Zhang
- School of Systems Science, Beijing Normal University, Beijing, 100875, China
| | - Qing-Qi Zhou
- College of Electrical and Control Engineering, North China University of Technology, Beijing, 100041, China
| | - He Chen
- School of Automation Science and Engineering, South China University of Technology, Guangzhou, 510641, China
| | - Xiao-Qing Hu
- Department of Psychology, the State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong SAR, 999077, China
- HKU-Shenzhen Institute of Research and Innovation, Shenzhen, 518057, Guangdong, China
| | - Wei-Guang Li
- Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong SAR, 999077, China
| | - Yang Bai
- Department of Rehabilitation Medicine, the First Affiliated Hospital of Nanchang University, Nanchang, 330006, China
- Rehabilitation Medicine Clinical Research Center of Jiangxi Province, Nanchang, 330006, China
| | - Jun-Xia Han
- Beijing Key Laboratory of Learning and Cognition, School of Psychology, Capital Normal University, Beijing, 100048, China
| | - Yao Wang
- School of Communication Science, Beijing Language and Culture University, Beijing, 100083, China
| | - Zhen-Hu Liang
- Institute of Electrical Engineering, Yanshan University, Qinhuangdao, 066004, Hebei, China.
| | - Dan Chen
- School of Computer Science, Wuhan University, Wuhan, 430072, China.
| | - Feng-Yu Cong
- School of Biomedical Engineering, Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian, 116081, Liaoning, China.
| | - Jia-Qing Yan
- College of Electrical and Control Engineering, North China University of Technology, Beijing, 100041, China.
| | - Xiao-Li Li
- School of Automation Science and Engineering, South China University of Technology, Guangzhou, 510641, China.
- Guangdong Artificial Intelligence and Digital Economy Laboratory (Guangzhou), Guangzhou, 510335, China.
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47
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Paitel ER, Nielson KA. Cerebellar EEG source localization reveals age-related compensatory activity moderated by genetic risk for Alzheimer's disease. Psychophysiology 2023; 60:e14395. [PMID: 37493042 DOI: 10.1111/psyp.14395] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Revised: 06/24/2023] [Accepted: 07/03/2023] [Indexed: 07/27/2023]
Abstract
The apolipoprotein-E (APOE) ε4 allele is the greatest genetic risk factor for late-onset Alzheimer's disease (AD), but alone it is not sufficiently predictive. Because neuropathological changes associated with AD begin decades before cognitive symptoms, neuroimaging of healthy, cognitively intact ε4 carriers (ε4+) may enable early characterization of patterns associated with risk for future decline. Research in the cerebral cortex highlights a period of compensatory recruitment in elders and ε4+, which serves to maintain cognitive functioning. Yet, AD-related changes may occur even earlier in the cerebellum. Advances in electroencephalography (EEG) source localization now allow effective modeling of cerebellar activity. Importantly, healthy aging and AD are associated with declines in both cerebellar functions and executive functioning (EF). However, it is not known whether cerebellar activity can detect pre-symptomatic AD risk. Thus, the current study analyzed cerebellar EEG source localization during an EF-dependent stop-signal task (i.e., inhibitory control) in healthy, intact older adults (Mage = 80 years; 20 ε4+, 25 ε4-). Task performance was comparable between groups. Older age predicted greater activity in left crus II and lobule VIIb during the P300 window (i.e., performance evaluation), consistent with age-related compensation. Age*ε4 moderations specifically showed that compensatory patterns were evident only in ε4-, suggesting that cerebellar compensatory resources may already be depleted in healthy ε4+ elders. Thus, the posterolateral cerebellum is sensitive to AD-related neural deficits in healthy elders. Characterization of these patterns may be essential for the earliest possible detection of AD risk, which would enable critical early intervention prior to symptom onset.
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Affiliation(s)
- Elizabeth R Paitel
- Department of Psychology, Marquette University, Milwaukee, Wisconsin, USA
| | - Kristy A Nielson
- Department of Psychology, Marquette University, Milwaukee, Wisconsin, USA
- Department of Neurology, Center for Imaging Research, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
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48
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Ross JM, Cline CC, Sarkar M, Truong J, Keller CJ. Neural effects of TMS trains on the human prefrontal cortex. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.30.526374. [PMID: 36778457 PMCID: PMC9915614 DOI: 10.1101/2023.01.30.526374] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
How does a train of TMS pulses modify neural activity in humans? Despite adoption of repetitive TMS (rTMS) for the treatment of neuropsychiatric disorders, we still do not understand how rTMS changes the human brain. This limited understanding stems in part from a lack of methods for noninvasively measuring the neural effects of a single TMS train - a fundamental building block of treatment - as well as the cumulative effects of consecutive TMS trains. Gaining this understanding would provide foundational knowledge to guide the next generation of treatments. Here, to overcome this limitation, we developed methods to noninvasively measure causal and acute changes in cortical excitability and evaluated this neural response to single and sequential TMS trains. In 16 healthy adults, standard 10 Hz trains were applied to the dorsolateral prefrontal cortex (dlPFC) in a randomized, sham-controlled, event-related design and changes were assessed based on the TMS-evoked potential (TEP), a measure of cortical excitability. We hypothesized that single TMS trains would induce changes in the local TEP amplitude and that those changes would accumulate across sequential trains, but primary analyses did not indicate evidence in support of either of these hypotheses. Exploratory analyses demonstrated non-local neural changes in sensor and source space and local neural changes in phase and source space. Together these results suggest that single and sequential TMS trains may not be sufficient to modulate local cortical excitability indexed by typical TEP amplitude metrics but may cause neural changes that can be detected outside the stimulation area or using phase or source space metrics. This work should be contextualized as methods development for the monitoring of transient noninvasive neural changes during rTMS and contributes to a growing understanding of the neural effects of rTMS.
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Affiliation(s)
- Jessica M. Ross
- Department of Psychiatry and Behavioral Sciences, Stanford University Medical Center, 401 Quarry Road, Stanford, CA, 94305, USA
- Veterans Affairs Palo Alto Healthcare System, and the Sierra Pacific Mental Illness, Research, Education, and Clinical Center (MIRECC), 3801 Miranda Avenue, Palo Alto, CA 94304, USA
- Wu Tsai Neuroscience Institute, Stanford University, Stanford, CA, USA
| | - Christopher C. Cline
- Department of Psychiatry and Behavioral Sciences, Stanford University Medical Center, 401 Quarry Road, Stanford, CA, 94305, USA
- Wu Tsai Neuroscience Institute, Stanford University, Stanford, CA, USA
| | - Manjima Sarkar
- Department of Psychiatry and Behavioral Sciences, Stanford University Medical Center, 401 Quarry Road, Stanford, CA, 94305, USA
- Wu Tsai Neuroscience Institute, Stanford University, Stanford, CA, USA
| | - Jade Truong
- Department of Psychiatry and Behavioral Sciences, Stanford University Medical Center, 401 Quarry Road, Stanford, CA, 94305, USA
- Wu Tsai Neuroscience Institute, Stanford University, Stanford, CA, USA
| | - Corey J. Keller
- Department of Psychiatry and Behavioral Sciences, Stanford University Medical Center, 401 Quarry Road, Stanford, CA, 94305, USA
- Veterans Affairs Palo Alto Healthcare System, and the Sierra Pacific Mental Illness, Research, Education, and Clinical Center (MIRECC), 3801 Miranda Avenue, Palo Alto, CA 94304, USA
- Wu Tsai Neuroscience Institute, Stanford University, Stanford, CA, USA
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49
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Han Y, Huang J, Yin Y, Chen H. From brain to worksite: the role of fNIRS in cognitive studies and worker safety. Front Public Health 2023; 11:1256895. [PMID: 37954053 PMCID: PMC10634210 DOI: 10.3389/fpubh.2023.1256895] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2023] [Accepted: 10/11/2023] [Indexed: 11/14/2023] Open
Abstract
Effective hazard recognition and decision-making are crucial factors in ensuring workplace safety in the construction industry. Workers' cognition closely relates to that hazard-handling behavior. Functional near-infrared spectroscopy (fNIRS) is a neurotechique tool that can evaluate the concentration vibration of oxygenated hemoglobin [ H b O 2 ] and deoxygenated hemoglobin [H b R ] to reflect the cognition process. It is essential to monitor workers' brain activity by fNIRS to analyze their cognitive status and reveal the mechanism in hazard recognition and decision-making process, providing guidance for capability evaluation and management enhancement. This review offers a systematic assessment of fNIRS, encompassing the basic theory, experiment analysis, data analysis, and discussion. A literature search and content analysis are conducted to identify the application of fNIRS in construction safety research, the limitations of selected studies, and the prospects of fNIRS in future research. This article serves as a guide for researchers keen on harnessing fNIRS to bolster construction safety standards and forwards insightful recommendations for subsequent studies.
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Affiliation(s)
| | | | | | - Huihua Chen
- School of Civil Engineering, Central South University, Changsha, China
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Gu Y, Gagnon JF, Kaminska M. Sleep electroencephalography biomarkers of cognition in obstructive sleep apnea. J Sleep Res 2023; 32:e13831. [PMID: 36941194 DOI: 10.1111/jsr.13831] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Revised: 12/20/2022] [Accepted: 01/04/2023] [Indexed: 03/23/2023]
Abstract
Obstructive sleep apnea has been associated with cognitive impairment and may be linked to disorders of cognitive function. These associations may be a result of intermittent hypoxaemia, sleep fragmentation and changes in sleep microstructure in obstructive sleep apnea. Current clinical metrics of obstructive sleep apnea, such as the apnea-hypopnea index, are poor predictors of cognitive outcomes in obstructive sleep apnea. Sleep microstructure features, which can be identified on sleep electroencephalography of traditional overnight polysomnography, are increasingly being characterized in obstructive sleep apnea and may better predict cognitive outcomes. Here, we summarize the literature on several major sleep electroencephalography features (slow-wave activity, sleep spindles, K-complexes, cyclic alternating patterns, rapid eye movement sleep quantitative electroencephalography, odds ratio product) identified in obstructive sleep apnea. We will review the associations between these sleep electroencephalography features and cognition in obstructive sleep apnea, and examine how treatment of obstructive sleep apnea affects these associations. Lastly, evolving technologies in sleep electroencephalography analyses will also be discussed (e.g. high-density electroencephalography, machine learning) as potential predictors of cognitive function in obstructive sleep apnea.
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Affiliation(s)
- Yusing Gu
- Department of Medicine, Dalhousie University, Halifax, Nova Scotia, Canada
| | - Jean-François Gagnon
- Department of Psychology, Université du Québec à Montréal, Montréal, Québec, Canada
- Center for Advanced Research in Sleep Medicine, CIUSSS-NÎM - Hôpital du Sacré-Coeur de Montréal, Montreal, Quebec, Canada
| | - Marta Kaminska
- Respiratory Epidemiology and Clinical Research Unit, Research Institute of the McGill University Health Centre, Montreal, Québec, Canada
- Respiratory Division & Sleep Laboratory, McGill University Health Centre, Montreal, Québec, Canada
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