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Xu C, Yuan Z, Chen Z, Liao Z, Li S, Feng Y, Tang Z, Nian J, Huang X, Zhong H, Xie Q. Perturbational complexity index in assessing responsiveness to rTMS treatment in patients with disorders of consciousness: a cross-over randomized controlled trial study. J Neuroeng Rehabil 2024; 21:167. [PMID: 39300529 DOI: 10.1186/s12984-024-01455-1] [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: 02/05/2024] [Accepted: 09/02/2024] [Indexed: 09/22/2024] Open
Abstract
BACKGROUND Disorders of Consciousness (DoC) caused by severe brain injuries represent a challenging clinical entity, which is easy to misdiagnosis and lacks effective treatment options. Repetitive Transcranial Magnetic Stimulation (rTMS) is a non-invasive neuroelectric stimulation method that shows promise in improving consciousness for DoC, especially in minimally conscious state (MCS). However, there is little evidence of its effectiveness, especially in RCT studies. METHODS Twenty MCS patients participated in a double-blind, randomized, crossover, sham-controlled clinical study to evaluate the safety and efficacy of rTMS for MCS. Subjects were randomized into two groups: one group received rTMS-active for 10 consecutive days (n = 10), and the other group received rTMS-sham for 10 consecutive days (n = 10). After a 10-day washout period, the two groups were crossed over and received the opposite treatment. the rTMS protocol consisted of 2,000 pulses per day in the left dorsolateral prefrontal cortex (L-DLPFC), sent at 10 Hz. The stimulation intensity was 90% of the resting motor threshold. Coma Recovery Scale Revised (CRS-R), the main evaluation index, was evaluated before and after each phase in a double-blind manner. Meanwhile RS-EEG and TMS-EEG data were acquired and relative alpha power (RAP), and perturbational complexity index based on state transitions (PCIst) were caculated. RESULTS One-way ANOVA revealed significantly higher scores in rTMS-active treatment compared to rTMS-sham across various measures, including CRS-R total score, RAP, PCIst (all P < 0.05). Among the 20 MCS patients, 7 (35%) were identified as responders following rTMS treatment. Compared to rTMS-sham, responder scores for CRS-R, RAP, and PCIst (all P < 0.05) were significantly elevated after rTMS-active treatment. Conversely, there was no significant difference observed in non-responders. Furthermore, post-hoc analysis revealed that baseline PCIst was significantly higher in responders than non-responders. Upon a 6-month follow-up, CRS-R scores significantly increased in all 20 patients (P = 0.026). However, the responder group exhibited a more favorable prognosis compared to the non-responder group (P = 0.031). CONCLUSIONS Applying 10 Hz rTMS to L-DLPFC significantly increased consciousness level in MCS patients. PCIst is a neurophysiological index that has the potential to evaluate and predict therapeutic efficacy. TRIAL REGISTRATION www. CLINICALTRIALS gov , identifier: NCT05187000.
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Affiliation(s)
- Chengwei Xu
- Joint Research Centre for Disorders of Consciousness, Department of Rehabilitation Medicine, Zhujiang Hospital of Southern Medical University, Guangzhou, China
- School of Rehabilitation Sciences, Southern Medical University, 1023 Shatai SouthRoad, Guangzhou, Guangdong, 510515, China
| | - Zhanxing Yuan
- School of Biomedical Engineering, Southern Medical University, 1023 Shatai SouthRoad, Guangzhou, Guangdong, 510515, China
| | - Zerong Chen
- Joint Research Centre for Disorders of Consciousness, Department of Rehabilitation Medicine, Zhujiang Hospital of Southern Medical University, Guangzhou, China
| | - Ziqin Liao
- Joint Research Centre for Disorders of Consciousness, Department of Rehabilitation Medicine, Zhujiang Hospital of Southern Medical University, Guangzhou, China
| | - Shuiyan Li
- Joint Research Centre for Disorders of Consciousness, Department of Rehabilitation Medicine, Zhujiang Hospital of Southern Medical University, Guangzhou, China
| | - Yanqi Feng
- Joint Research Centre for Disorders of Consciousness, Department of Rehabilitation Medicine, Zhujiang Hospital of Southern Medical University, Guangzhou, China
| | - Ziqiang Tang
- Joint Research Centre for Disorders of Consciousness, Department of Rehabilitation Medicine, Zhujiang Hospital of Southern Medical University, Guangzhou, China
| | - Jichan Nian
- Joint Research Centre for Disorders of Consciousness, Department of Rehabilitation Medicine, Zhujiang Hospital of Southern Medical University, Guangzhou, China
| | - Xiyan Huang
- Joint Research Centre for Disorders of Consciousness, Department of Rehabilitation Medicine, Zhujiang Hospital of Southern Medical University, Guangzhou, China
| | - Haili Zhong
- Joint Research Centre for Disorders of Consciousness, Department of Rehabilitation Medicine, Zhujiang Hospital of Southern Medical University, Guangzhou, China
| | - Qiuyou Xie
- Joint Research Centre for Disorders of Consciousness, Department of Rehabilitation Medicine, Zhujiang Hospital of Southern Medical University, Guangzhou, China.
- Department of hyperbaric oxygenation, Zhujiang Hospital of Southern Medical University, Guangzhou, China.
- School of Biomedical Engineering, Southern Medical University, 1023 Shatai SouthRoad, Guangzhou, Guangdong, 510515, China.
- School of Rehabilitation Sciences, Southern Medical University, 1023 Shatai SouthRoad, Guangzhou, Guangdong, 510515, China.
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Biagioni M, Baronchelli F, Fossati M. Multiscale spatio-temporal dynamics of UBE3A gene in brain physiology and neurodevelopmental disorders. Neurobiol Dis 2024; 201:106669. [PMID: 39293689 DOI: 10.1016/j.nbd.2024.106669] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2024] [Revised: 09/13/2024] [Accepted: 09/15/2024] [Indexed: 09/20/2024] Open
Abstract
The UBE3A gene, located in the chromosomal region 15q11-13, is subject to neuron-specific genomic imprinting and it plays a critical role in brain development. Genetic defects of UBE3A cause severe neurodevelopmental disorders, namely the Angelman syndrome (AS) and the 15q11.2-q13.3 duplication syndrome (Dup15q). In the last two decades, the development of in vitro and in vivo models of AS and Dup15q were fundamental to improve the understanding of UBE3A function in the brain. However, the pathogenic mechanisms of these diseases remain elusive and effective treatments are lacking. Recent evidence suggests that UBE3A functions are both spatially and temporally specific, varying across subcellular compartments, brain regions, and neuronal circuits. In the present review, we summarize current knowledge on the role of UBE3A in neuronal pathophysiology under this spatio-temporal perspective. Additionally, we propose key research questions that will be instrumental to better understand the pathogenic mechanisms underpinning AS and Dup15q disorders and provide the rationale to develop novel therapies.
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Affiliation(s)
- Martina Biagioni
- IRCCS Humanitas Research Hospital, via Manzoni 56, Rozzano 20089, MI, Italy
| | - Federica Baronchelli
- CNR - Institute of Neuroscience, Section of Milano, via Manzoni 56, Rozzano 20089, MI, Italy; Department of Biomedical Sciences, Humanitas University, via Rita Levi Montalcini, 20072 Pieve Emanuele, MI, Italy
| | - Matteo Fossati
- IRCCS Humanitas Research Hospital, via Manzoni 56, Rozzano 20089, MI, Italy; CNR - Institute of Neuroscience, Section of Milano, via Manzoni 56, Rozzano 20089, MI, Italy.
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Li Y, Fang W, Qiu H, Yu H, Dong W, Sun Z. Diurnal biological effects of correlated colour temperature and its exposure timing on alertness, cognition, and mood in an enclosed environment. APPLIED ERGONOMICS 2024; 119:104304. [PMID: 38718532 DOI: 10.1016/j.apergo.2024.104304] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/22/2023] [Revised: 04/06/2024] [Accepted: 05/01/2024] [Indexed: 06/11/2024]
Abstract
Artificial lighting, which profits from the non-visual effects of light, is a potentially promising solution to support residents' psychophysiological health and performance at specific times of the day in enclosed environments. However, few studies have investigated the non-visual effects of daytime correlated colour temperature (CCT) and its exposure timing on human alertness, cognition, and mood. However, the neural mechanisms underlying these effects are largely unknown. The current study evaluated the effects of daytime CCT and its exposure timing on markers of subjective experience, cognitive performance, and cerebral activity in a simulated enclosed environment. Forty-two participants participated a single-blind laboratory study with a 4 within (CCT: 4000 K vs. 6500 K vs. 8500 K vs. 12,000 K) × 2 between (exposure timing: morning vs. afternoon) mixed design. The results showed time of the day dependent benefits of the daytime CCT on subjective experience, vigilant attention, response inhibition, working memory, emotional perception, and risk decisions. The results of the electroencephalogram (EEG) revealed that lower-frequency EEG bands, including theta, alpha, and alpha-theta, were quite sensitive to daytime CCT intervention, which provides a valuable reference for trying to establish the underlying mechanisms that support the performance-enhancement effects of exposure to CCT in the daytime. However, the results revealed no consistent intervention pattern across these measurements. Therefore, future studies should consider personalised optimisation of daytime CCT for different cognitive demands.
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Affiliation(s)
- YanJie Li
- School of Mechanical, Electronic and Control Engineering, Beijing Jiaotong University, No. 3 Shang Yuan Cun, Haidian District, 100044 Beijing, China.
| | - WeiNing Fang
- School of Mechanical, Electronic and Control Engineering, Beijing Jiaotong University, No. 3 Shang Yuan Cun, Haidian District, 100044 Beijing, China; State Key Laboratory of Advanced Rail Autonomous Operation, Beijing Jiaotong University, No. 3 Shang Yuan Cun, Haidian District, 100044 Beijing, China.
| | - HanZhao Qiu
- School of Mechanical, Electronic and Control Engineering, Beijing Jiaotong University, No. 3 Shang Yuan Cun, Haidian District, 100044 Beijing, China.
| | - Hongqiang Yu
- National Key Laboratory of Human Factors Engineering, China Astronaut Research and Training Center, Haidian District, 100094 Beijing, China.
| | - WenLi Dong
- School of Automation and Intelligence, Beijing Jiaotong University, No. 3 Shang Yuan Cun, Haidian District, 100044 Beijing, China.
| | - Zhe Sun
- School of Automation and Intelligence, Beijing Jiaotong University, No. 3 Shang Yuan Cun, Haidian District, 100044 Beijing, China.
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Busch N, Geyer T, Zinchenko A. Individual peak alpha frequency does not index individual differences in inhibitory cognitive control. Psychophysiology 2024; 61:e14586. [PMID: 38594833 DOI: 10.1111/psyp.14586] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2023] [Revised: 03/26/2024] [Accepted: 03/29/2024] [Indexed: 04/11/2024]
Abstract
Previous work has indicated that individual differences in cognitive performance can be predicted by characteristics of resting state oscillations, such as individual peak alpha frequency (IAF). Although IAF has previously been correlated with cognitive functions, such as memory, attention, or mental speed, its link to cognitive conflict processing remains unexplored. The current work investigated the relationship between IAF and inhibitory cognitive control in two well-established conflict tasks, Stroop and Navon task, while also controlling for alpha power, theta power, and the 1/f offset of aperiodic broadband activity. In Bayesian analyses on a large sample of 127 healthy participants, we found substantial evidence against the assumption that IAF predicts individual abilities to spontaneously exert cognitive control. Similarly, our findings yielded substantial evidence against links between cognitive control and resting state power in the alpha and theta bands or between cognitive control and aperiodic 1/f offset. In sum, our results challenge frameworks suggesting that an individual's ability to spontaneously engage attentional control networks may be mirrored in resting state EEG characteristics.
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Affiliation(s)
- Nuno Busch
- School of Management, Technische Universität München, Munich, Germany
- Department of Psychology, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Thomas Geyer
- Department of Psychology, Ludwig-Maximilians-Universität München, Munich, Germany
- Munich Center for NeuroSciences-Brain & Mind, Munich, Germany
- NICUM-NeuroImaging Core Unit Munich, Munich, Germany
| | - Artyom Zinchenko
- Department of Psychology, Ludwig-Maximilians-Universität München, Munich, Germany
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Lum JAG, Barham MP, Hill AT. Pupillometry reveals resting state alpha power correlates with individual differences in adult auditory language comprehension. Cortex 2024; 177:1-14. [PMID: 38821014 DOI: 10.1016/j.cortex.2024.02.019] [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: 11/06/2023] [Revised: 02/09/2024] [Accepted: 02/12/2024] [Indexed: 06/02/2024]
Abstract
Although individual differences in adult language processing are well-documented, the neural basis of this variability remains largely unexplored. The current study addressed this gap in the literature by examining the relationship between resting state alpha activity and individual differences in auditory language comprehension. Alpha oscillations modulate cortical excitability, facilitating efficient information processing in the brain. While resting state alpha oscillations have been tied to individual differences in cognitive performance, their association with auditory language comprehension is less clear. Participants in the study were 80 healthy adults with a mean age of 25.8 years (SD = 7.2 years). Resting state alpha activity was acquired using electroencephalography while participants looked at a benign stimulus for 3 min. Participants then completed a language comprehension task that involved listening to 'syntactically simple' subject-relative clause sentences and 'syntactically complex' object-relative clause sentences. Pupillometry measured real-time processing demand changes, with larger pupil dilation indicating increased processing loads. Replicating past research, comprehending object relative clauses, compared to subject relative clauses, was associated with lower accuracy, slower reaction times, and larger pupil dilation. Resting state alpha power was found to be positively correlated with the pupillometry data. That is, participants with higher resting state alpha activity evidenced larger dilation during sentence comprehension. This effect was more pronounced for the 'complex' object sentences compared to the 'simple' subject sentences. These findings suggest the brain's capacity to generate a robust resting alpha rhythm contributes to variability in processing demands associated with auditory language comprehension, especially when faced with challenging syntactic structures. More generally, the study demonstrates that the intrinsic functional architecture of the brain likely influences individual differences in language comprehension.
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Affiliation(s)
- Jarrad A G Lum
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Australia.
| | - Michael P Barham
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Australia
| | - Aron T Hill
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Australia
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Jiang H, Zhao S, Wu Q, Cao Y, Zhou W, Gong Y, Shao C, Chi A. Dragon boat exercise reshapes the temporal-spatial dynamics of the brain. PeerJ 2024; 12:e17623. [PMID: 38952974 PMCID: PMC11216202 DOI: 10.7717/peerj.17623] [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: 10/30/2023] [Accepted: 06/02/2024] [Indexed: 07/03/2024] Open
Abstract
Although exercise training has been shown to enhance neurological function, there is a shortage of research on how exercise training affects the temporal-spatial synchronization properties of functional networks, which are crucial to the neurological system. This study recruited 23 professional and 24 amateur dragon boat racers to perform simulated paddling on ergometers while recording EEG. The spatiotemporal dynamics of the brain were analyzed using microstates and omega complexity. Temporal dynamics results showed that microstate D, which is associated with attentional networks, appeared significantly altered, with significantly higher duration, occurrence, and coverage in the professional group than in the amateur group. The transition probabilities of microstate D exhibited a similar pattern. The spatial dynamics results showed the professional group had lower brain complexity than the amateur group, with a significant decrease in omega complexity in the α (8-12 Hz) and β (13-30 Hz) bands. Dragon boat training may strengthen the attentive network and reduce the complexity of the brain. This study provides evidence that dragon boat exercise improves the efficiency of the cerebral functional networks on a spatiotemporal scale.
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Affiliation(s)
- Hongke Jiang
- Department of Physical Education, Shanghai Maritime University, Shanghai, China
| | - Shanguang Zhao
- Department of Physical Education, Shanghai Maritime University, Shanghai, China
| | - Qianqian Wu
- School of Physical Education, Shaanxi Normal University, Xian, China
| | - Yingying Cao
- School of Physical Education, Shaanxi Normal University, Xian, China
| | - Wu Zhou
- School of Physical Education, Shaanxi Normal University, Xian, China
| | - Youwu Gong
- Department of Physical Education, Shanghai Maritime University, Shanghai, China
| | - Changzhuan Shao
- Department of Physical Education, Shanghai Maritime University, Shanghai, China
| | - Aiping Chi
- School of Physical Education, Shaanxi Normal University, Xian, China
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Li M, Pan J, Li Y, Gao Y, Qin H, Shen Y. Multimodal Physiological Analysis of Impact of Emotion on Cognitive Control in VR. IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS 2024; 30:2044-2054. [PMID: 38437118 DOI: 10.1109/tvcg.2024.3372101] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/06/2024]
Abstract
Cognitive control is often perplexing to elucidate and can be easily influenced by emotions. Understanding the individual cognitive control level is crucial for enhancing VR interaction and designing adaptive and self-correcting VR/AR applications. Emotions can reallocate processing resources and influence cognitive control performance. However, current research has primarily emphasized the impact of emotional valence on cognitive control tasks, neglecting emotional arousal. In this study, we comprehensively investigate the influence of emotions on cognitive control based on the arousal-valence model. A total of 26 participants are recruited, inducing emotions through VR videos with high ecological validity and then performing related cognitive control tasks. Leveraging physiological data including EEG, HRV, and EDA, we employ classification techniques such as SVM, KNN, and deep learning to categorize cognitive control levels. The experiment results demonstrate that high-arousal emotions significantly enhance users' cognitive control abilities. Utilizing complementary information among multi-modal physiological signal features, we achieve an accuracy of 84.52% in distinguishing between high and low cognitive control. Additionally, time-frequency analysis results confirm the existence of neural patterns related to cognitive control, contributing to a better understanding of the neural mechanisms underlying cognitive control in VR. Our research indicates that physiological signals measured from both the central and autonomic nervous systems can be employed for cognitive control classification, paving the way for novel approaches to improve VR/AR interactions.
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8
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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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Jäger AP, Bailey A, Huntenburg JM, Tardif CL, Villringer A, Gauthier CJ, Nikulin V, Bazin P, Steele CJ. Decreased long-range temporal correlations in the resting-state functional magnetic resonance imaging blood-oxygen-level-dependent signal reflect motor sequence learning up to 2 weeks following training. Hum Brain Mapp 2024; 45:e26539. [PMID: 38124341 PMCID: PMC10915743 DOI: 10.1002/hbm.26539] [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: 05/10/2023] [Revised: 11/03/2023] [Accepted: 11/07/2023] [Indexed: 12/23/2023] Open
Abstract
Decreased long-range temporal correlations (LRTC) in brain signals can be used to measure cognitive effort during task execution. Here, we examined how learning a motor sequence affects long-range temporal memory within resting-state functional magnetic resonance imaging signal. Using the Hurst exponent (HE), we estimated voxel-wise LRTC and assessed changes over 5 consecutive days of training, followed by a retention scan 12 days later. The experimental group learned a complex visuomotor sequence while a complementary control group performed tightly matched movements. An interaction analysis revealed that HE decreases were specific to the complex sequence and occurred in well-known motor sequence learning associated regions including left supplementary motor area, left premotor cortex, left M1, left pars opercularis, bilateral thalamus, and right striatum. Five regions exhibited moderate to strong negative correlations with overall behavioral performance improvements. Following learning, HE values returned to pretraining levels in some regions, whereas in others, they remained decreased even 2 weeks after training. Our study presents new evidence of HE's possible relevance for functional plasticity during the resting-state and suggests that a cortical subset of sequence-specific regions may continue to represent a functional signature of learning reflected in decreased long-range temporal dependence after a period of inactivity.
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Affiliation(s)
- Anna‐Thekla P. Jäger
- Department of NeurologyMax Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
- Center for Stroke Research Berlin (CSB)Charité—Universitätsmedizin BerlinBerlinGermany
- Brain Language LabFreie Universität BerlinBerlinGermany
| | - Alexander Bailey
- Temerty Faculty of MedicineUniversity of TorontoTorontoOntarioCanada
| | - Julia M. Huntenburg
- Department of NeurologyMax Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
- Max Planck Institute for Biological CyberneticsTuebingenGermany
| | - Christine L. Tardif
- Department of Biomedical EngineeringMcGill UniversityMontrealQuébecCanada
- Montreal Neurological InstituteMontrealQuébecCanada
| | - Arno Villringer
- Department of NeurologyMax Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
- Center for Stroke Research Berlin (CSB)Charité—Universitätsmedizin BerlinBerlinGermany
- Clinic for Cognitive NeurologyLeipzigGermany
- Leipzig University Medical Centre, IFB Adiposity DiseasesLeipzigGermany
- Collaborative Research Centre 1052‐A5University of LeipzigLeipzigGermany
| | - Claudine J. Gauthier
- Department of Physics/School of HealthConcordia UniversityMontrealQuébecCanada
- Montreal Heart InstituteMontrealQuébecCanada
| | - Vadim Nikulin
- Department of NeurologyMax Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
| | - Pierre‐Louis Bazin
- Department of NeurologyMax Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
- Faculty of Social and Behavioral SciencesUniversity of AmsterdamAmsterdamNetherlands
| | - Christopher J. Steele
- Department of NeurologyMax Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
- Department of Psychology/School of HealthConcordia UniversityMontrealQuébecCanada
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Zhou W, Wu X. The impact of internal-generated contextual clues on EFL vocabulary learning: insights from EEG. Front Psychol 2024; 15:1332098. [PMID: 38371709 PMCID: PMC10873923 DOI: 10.3389/fpsyg.2024.1332098] [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: 11/24/2023] [Accepted: 01/17/2024] [Indexed: 02/20/2024] Open
Abstract
With the popularity of learning vocabulary online among English as a Foreign Language (EFL) learners today, educators and researchers have been considering ways to enhance the effectiveness of this approach. Prior research has underscored the significance of contextual clues in vocabulary acquisition. However, few studies have compared the context provided by instructional materials and that generated by learners themselves. Hence, this present study sought to explore the impact of internal-generated contextual clues in comparison to those provided by instructional materials on EFL learners' online vocabulary acquisition. A total of 26 university students were enrolled and underwent electroencephalography (EEG). Based on a within-subjects design, all participants learned two groups of vocabulary words through a series of video clips under two conditions: one where the contexts were externally provided and the other where participants themselves generated the contexts. In this regard, participants were tasked with either viewing contextual clues presented on the screen or creating their own contextual clues for word comprehension. EEG signals were recorded during the learning process to explore neural activities, and post-tests were conducted to assess learning performance after each vocabulary learning session. Our behavioral results indicated that comprehending words with internal-generated contextual clues resulted in superior learning performance compared to using context provided by instructional materials. Furthermore, EEG data revealed that learners expended greater cognitive resources and mental effort in semantically integrating the meaning of words when they self-created contextual clues, as evidenced by stronger alpha and beta-band oscillations. Moreover, the stronger alpha-band oscillations and lower inter-subject correlation (ISC) among learners suggested that the generative task of creating context enhanced their top-down attentional control mechanisms and selective visual processing when learning vocabulary from videos. These findings underscored the positive effects of internal-generated contextual clues, indicating that instructors should encourage learners to construct their own contexts in online EFL vocabulary instruction rather than providing pre-defined contexts. Future research should aim to explore the limits and conditions of employing these two types of contextual clues in online EFL vocabulary learning. This could be achieved by manipulating the quality and understandability of contexts and considering learners' language proficiency levels.
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Affiliation(s)
- Weichen Zhou
- School of Teacher Education, Shaoxing University, Shaoxing, China
| | - Xia Wu
- Department of Psychology, Shaoxing University, Shaoxing, China
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Huang Y, Deng Y, Kong L, Zhang X, Wei X, Mao T, Xu Y, Jiang C, Rao H. Vigilant attention mediates the association between resting EEG alpha oscillations and word learning ability. Neuroimage 2023; 281:120369. [PMID: 37690592 DOI: 10.1016/j.neuroimage.2023.120369] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2023] [Revised: 09/05/2023] [Accepted: 09/08/2023] [Indexed: 09/12/2023] Open
Abstract
Individuals exhibit considerable variability in their capacity to learn and retain new information, including novel vocabulary. Prior research has established the importance of vigilance and electroencephalogram (EEG) alpha rhythm in the learning process. However, the interplay between vigilant attention, EEG alpha oscillations, and an individual's word learning ability (WLA) remains elusive. To address this knowledge gap, here we conducted two experiments with a total of 140 young and middle-aged adults who underwent resting EEG recordings prior to completing a paired-associate word learning task and a psychomotor vigilance test (PVT). The results of both experiments consistently revealed significant positive correlations between WLA and resting EEG alpha oscillations in the occipital and frontal regions. Furthermore, the association between resting EEG alpha oscillations and WLA was mediated by vigilant attention, as measured by the PVT. These findings provide compelling evidence supporting the crucial role of vigilant attention in linking EEG alpha oscillations to an individual's learning ability.
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Affiliation(s)
- Yan Huang
- Center for Magnetic Resonance Imaging Research & Key Laboratory of Brain-Machine Intelligence for Information Behavior (Ministry of Education and Shanghai), School of Business and Management, Shanghai International Studies University, Shanghai, China; School of Foreign Languages, East China University of Science and Technology, Shanghai, China
| | - Yao Deng
- Center for Magnetic Resonance Imaging Research & Key Laboratory of Brain-Machine Intelligence for Information Behavior (Ministry of Education and Shanghai), School of Business and Management, Shanghai International Studies University, Shanghai, China
| | - Lingda Kong
- Institute of Corpus, Shanghai International Studies University, Shanghai, China
| | - Xiumei Zhang
- Center for Magnetic Resonance Imaging Research & Key Laboratory of Brain-Machine Intelligence for Information Behavior (Ministry of Education and Shanghai), School of Business and Management, Shanghai International Studies University, Shanghai, China
| | - Xiaobao Wei
- School of Foreign Languages, East China University of Science and Technology, Shanghai, China
| | - Tianxin Mao
- Center for Magnetic Resonance Imaging Research & Key Laboratory of Brain-Machine Intelligence for Information Behavior (Ministry of Education and Shanghai), School of Business and Management, Shanghai International Studies University, Shanghai, China
| | - Yong Xu
- Center for Magnetic Resonance Imaging Research & Key Laboratory of Brain-Machine Intelligence for Information Behavior (Ministry of Education and Shanghai), School of Business and Management, Shanghai International Studies University, Shanghai, China
| | - Caihong Jiang
- Center for Magnetic Resonance Imaging Research & Key Laboratory of Brain-Machine Intelligence for Information Behavior (Ministry of Education and Shanghai), School of Business and Management, Shanghai International Studies University, Shanghai, China.
| | - Hengyi Rao
- Center for Magnetic Resonance Imaging Research & Key Laboratory of Brain-Machine Intelligence for Information Behavior (Ministry of Education and Shanghai), School of Business and Management, Shanghai International Studies University, Shanghai, China; Center for Functional Neuroimaging, Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA.
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12
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Kumral D, Matzerath A, Leonhart R, Schönauer M. Spindle-dependent memory consolidation in healthy adults: A meta-analysis. Neuropsychologia 2023; 189:108661. [PMID: 37597610 DOI: 10.1016/j.neuropsychologia.2023.108661] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Revised: 06/23/2023] [Accepted: 08/12/2023] [Indexed: 08/21/2023]
Abstract
Accumulating evidence suggests a central role for sleep spindles in the consolidation of new memories. However, no meta-analysis of the association between sleep spindles and memory performance has been conducted so far. Here, we report meta-analytical evidence for spindle-memory associations and investigate how multiple factors, including memory type, spindle type, spindle characteristics, and EEG topography affect this relationship. The literature search yielded 53 studies reporting 1427 effect sizes, resulting in a small to moderate effect for the average association. We further found that spindle-memory associations were significantly stronger for procedural memory than for declarative memory. Neither spindle types nor EEG scalp topography had an impact on the strength of the spindle-memory relation, but we observed a distinct functional role of global and fast sleep spindles, especially for procedural memory. We also found a moderation effect of spindle characteristics, with power showing the largest effect sizes. Collectively, our findings suggest that sleep spindles are involved in learning, thereby representing a general physiological mechanism for memory consolidation.
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Affiliation(s)
- Deniz Kumral
- Institute of Psychology, Neuropsychology, University of Freiburg, Freiburg Im Breisgau, Germany; Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
| | - Alina Matzerath
- Institute of Psychology, Neuropsychology, University of Freiburg, Freiburg Im Breisgau, Germany
| | - Rainer Leonhart
- Institute of Psychology, Social Psychology and Methodology, University of Freiburg, Freiburg Im Breisgau, Germany
| | - Monika Schönauer
- Institute of Psychology, Neuropsychology, University of Freiburg, Freiburg Im Breisgau, Germany; Bernstein Center Freiburg, Freiburg Im Breisgau, Germany
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13
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Turri C, Di Dona G, Santoni A, Zamfira DA, Franchin L, Melcher D, Ronconi L. Periodic and Aperiodic EEG Features as Potential Markers of Developmental Dyslexia. Biomedicines 2023; 11:1607. [PMID: 37371702 DOI: 10.3390/biomedicines11061607] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Revised: 05/26/2023] [Accepted: 05/26/2023] [Indexed: 06/29/2023] Open
Abstract
Developmental Dyslexia (DD) is a neurobiological condition affecting the ability to read fluently and/or accurately. Analyzing resting-state electroencephalographic (EEG) activity in DD may provide a deeper characterization of the underlying pathophysiology and possible biomarkers. So far, studies investigating resting-state activity in DD provided limited evidence and did not consider the aperiodic component of the power spectrum. In the present study, adults with (n = 26) and without DD (n = 31) underwent a reading skills assessment and resting-state EEG to investigate potential alterations in aperiodic activity, their impact on the periodic counterpart and reading performance. In parieto-occipital channels, DD participants showed a significantly different aperiodic activity as indexed by a flatter and lower power spectrum. These aperiodic measures were significantly related to text reading time, suggesting a link with individual differences in reading difficulties. In the beta band, the DD group showed significantly decreased aperiodic-adjusted power compared to typical readers, which was significantly correlated to word reading accuracy. Overall, here we provide evidence showing alterations of the endogenous aperiodic activity in DD participants consistently with the increased neural noise hypothesis. In addition, we confirm alterations of endogenous beta rhythms, which are discussed in terms of their potential link with magnocellular-dorsal stream deficit.
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Affiliation(s)
- Chiara Turri
- School of Psychology, Vita-Salute San Raffaele University, 20132 Milan, Italy
- Division of Neuroscience, IRCCS San Raffaele Scientific Institute, 20132 Milan, Italy
| | - Giuseppe Di Dona
- School of Psychology, Vita-Salute San Raffaele University, 20132 Milan, Italy
- Division of Neuroscience, IRCCS San Raffaele Scientific Institute, 20132 Milan, Italy
| | - Alessia Santoni
- School of Psychology, Vita-Salute San Raffaele University, 20132 Milan, Italy
- Department of Psychology and Cognitive Science, University of Trento, 38068 Rovereto, Italy
| | - Denisa Adina Zamfira
- School of Psychology, Vita-Salute San Raffaele University, 20132 Milan, Italy
- Division of Neuroscience, IRCCS San Raffaele Scientific Institute, 20132 Milan, Italy
| | - Laura Franchin
- Department of Psychology and Cognitive Science, University of Trento, 38068 Rovereto, Italy
| | - David Melcher
- Department of Psychology and Cognitive Science, University of Trento, 38068 Rovereto, Italy
- Psychology Program, Division of Science, New York University Abu Dhabi, Abu Dhabi 129188, United Arab Emirates
- Center for Brain and Health, NYUAD Research Institute, New York University Abu Dhabi, Abu Dhabi 129188, United Arab Emirates
| | - Luca Ronconi
- School of Psychology, Vita-Salute San Raffaele University, 20132 Milan, Italy
- Division of Neuroscience, IRCCS San Raffaele Scientific Institute, 20132 Milan, Italy
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14
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Gordillo D, Ramos da Cruz J, Moreno D, Garobbio S, Herzog MH. Do we really measure what we think we are measuring? iScience 2023; 26:106017. [PMID: 36844457 PMCID: PMC9947309 DOI: 10.1016/j.isci.2023.106017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Revised: 12/18/2022] [Accepted: 01/16/2023] [Indexed: 01/21/2023] Open
Abstract
Tests used in the empirical sciences are often (implicitly) assumed to be representative of a given research question in the sense that similar tests should lead to similar results. Here, we show that this assumption is not always valid. We illustrate our argument with the example of resting-state electroencephalogram (EEG). We used multiple analysis methods, contrary to typical EEG studies where one analysis method is used. We found, first, that many EEG features correlated significantly with cognitive tasks. However, these EEG features correlated weakly with each other. Similarly, in a second analysis, we found that many EEG features were significantly different in older compared to younger participants. When we compared these EEG features pairwise, we did not find strong correlations. In addition, EEG features predicted cognitive tasks poorly as shown by cross-validated regression analysis. We discuss several explanations of these results.
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Affiliation(s)
- Dario Gordillo
- Laboratory of Psychophysics, Brain Mind Institute, School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland
- Corresponding author
| | - Janir Ramos da Cruz
- Laboratory of Psychophysics, Brain Mind Institute, School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland
- Institute for Systems and Robotics – Lisboa (LARSyS), Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, 1049-001 Lisbon, Portugal
- Wyss Center for Bio and Neuroengineering, CH-1202 Geneva, Switzerland
| | - Dana Moreno
- Laboratory of Psychophysics, Brain Mind Institute, School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland
| | - Simona Garobbio
- Laboratory of Psychophysics, Brain Mind Institute, School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland
| | - Michael H. Herzog
- Laboratory of Psychophysics, Brain Mind Institute, School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland
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15
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One-year-later spontaneous EEG features predict visual exploratory human phenotypes. Commun Biol 2022; 5:1361. [PMID: 36509841 PMCID: PMC9744741 DOI: 10.1038/s42003-022-04294-9] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2021] [Accepted: 11/24/2022] [Indexed: 12/14/2022] Open
Abstract
During visual exploration, eye movements are controlled by multiple stimulus- and goal-driven factors. We recently showed that the dynamics of eye movements -how/when the eye move- during natural scenes' free viewing were similar across individuals and identified two viewing styles: static and dynamic, characterized respectively by longer or shorter fixations. Interestingly, these styles could be revealed at rest, in the absence of any visual stimulus. This result supports a role of intrinsic activity in eye movement dynamics. Here we hypothesize that these two viewing styles correspond to different spontaneous patterns of brain activity. One year after the behavioural experiments, static and dynamic viewers were called back to the lab to record high density EEG activity during eyes open and eyes closed. Static viewers show higher cortical inhibition, slower individual alpha frequency peak, and longer memory of alpha oscillations. The opposite holds for dynamic viewers. We conclude that some properties of spontaneous activity predict exploratory eye movement dynamics during free viewing.
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16
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Ke L, Zhang Y, Fu Y, Shen X, Zhang Y, Ma X, Di Q. Short-term PM 2.5 exposure and cognitive function: Association and neurophysiological mechanisms. ENVIRONMENT INTERNATIONAL 2022; 170:107593. [PMID: 36279737 DOI: 10.1016/j.envint.2022.107593] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/27/2022] [Revised: 10/17/2022] [Accepted: 10/18/2022] [Indexed: 06/16/2023]
Abstract
BACKGROUND Although converging evidence has demonstrated that exposure to fine particulate matter (PM2.5) caused adverse effects on brain structure and cognitive function, the association between the short-term exposure to PM2.5 and cognition dysfunction remained underexplored, especially possible neurophysiological mechanisms. METHODS We conducted a longitudinal observational study with four repeated measurement sessions among 90 young adults from September 2020 to June 2021. During each measurement session, we measured participants' personal-level air pollution exposure for one week with portable monitors, followed by executive function assessment and electrophysiological signal recording at an assessment center. Standard Stroop color-word test was used accompanied with electroencephalogram (EEG) recording to assess performance on executive function. We used linear mixed-effect model with lagged values of PM2.5 levels to analyze the association between PM2.5 exposure and changes in executive function, and mediation analysis to investigate mediation effect by EEG signal. RESULTS Adjusted mixed-effect models demonstrated that elevated PM2.5 exposure three days prior to cognitive assessment (lag-3) was associated with (1) declined performance in both congruent and incongruent tasks in Stroop test, (2) reduced lower and upper alpha event-related desynchronization (ERD) during 500-1000 ms after stimuli, both indicating impaired executive control. Lower and upper alpha ERD also mediated observed associations between short-term PM2.5 exposure and executive function. No significant associations were found between short-term PM2.5 exposure or aperiodic exponents in tonic and phasic states, or periodic alpha oscillations in tonic state. CONCLUSION Our results provided evidence that short-term PM2.5 exposure was associated with executive dysfunction. Reduced alpha ERD was likely to be the underlying pathway through which PM2.5 induced adverse effects on neuron activities during cognitive tasks.
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Affiliation(s)
- Limei Ke
- School of Medicine, Tsinghua University, Beijing 100084, China.
| | - Yao Zhang
- Soochow College, Soochow University, Suzhou 215006, China; Division of Sports Science & Physical Education, Tsinghua University, Beijing 100084, China.
| | - Yingyao Fu
- Division of Sports Science & Physical Education, Tsinghua University, Beijing 100084, China; Department of senior high school, Beijing Jianhua Experimental Etown School, Beijing 100176, China.
| | - Xinke Shen
- Department of Biomedical Engineering, Tsinghua University, Beijing 100084, China.
| | - Yu Zhang
- Institute of Education, Tsinghua University, Beijing 100084, China.
| | - Xindong Ma
- Division of Sports Science & Physical Education, Tsinghua University, Beijing 100084, China.
| | - Qian Di
- Vanke School of Public Health, Tsinghua University, Beijing 100084, China; Institute for Healthy China, Tsinghua University, Beijing 100084, China.
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17
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Huang Y, Deng Y, Jiang X, Chen Y, Mao T, Xu Y, Jiang C, Rao H. Resting-state occipito-frontal alpha connectome is linked to differential word learning ability in adult learners. Front Neurosci 2022; 16:953315. [PMID: 36188469 PMCID: PMC9521374 DOI: 10.3389/fnins.2022.953315] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2022] [Accepted: 08/18/2022] [Indexed: 11/19/2022] Open
Abstract
Adult language learners show distinct abilities in acquiring a new language, yet the underlying neural mechanisms remain elusive. Previous studies suggested that resting-state brain connectome may contribute to individual differences in learning ability. Here, we recorded electroencephalography (EEG) in a large cohort of 106 healthy young adults (50 males) and examined the associations between resting-state alpha band (8-12 Hz) connectome and individual learning ability during novel word learning, a key component of new language acquisition. Behavioral data revealed robust individual differences in the performance of the novel word learning task, which correlated with their performance in the language aptitude test. EEG data showed that individual resting-state alpha band coherence between occipital and frontal regions positively correlated with differential word learning performance (p = 0.001). The significant positive correlations between resting-state occipito-frontal alpha connectome and differential world learning ability were replicated in an independent cohort of 35 healthy adults. These findings support the key role of occipito-frontal network in novel word learning and suggest that resting-state EEG connectome may be a reliable marker for individual ability during new language learning.
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Affiliation(s)
- Yan Huang
- Center for Magnetic Resonance Imaging Research, Key Laboratory of Applied Brain and Cognitive Sciences, Shanghai International Studies University, Shanghai, China
- School of Foreign Languages, East China University of Science and Technology, Shanghai, China
- Institute of Linguistics, Shanghai International Studies University, Shanghai, China
| | - Yao Deng
- Center for Magnetic Resonance Imaging Research, Key Laboratory of Applied Brain and Cognitive Sciences, Shanghai International Studies University, Shanghai, China
| | - Xiaoming Jiang
- Institute of Linguistics, Shanghai International Studies University, Shanghai, China
| | - Yiyuan Chen
- Center for Magnetic Resonance Imaging Research, Key Laboratory of Applied Brain and Cognitive Sciences, Shanghai International Studies University, Shanghai, China
- Institute of Linguistics, Shanghai International Studies University, Shanghai, China
| | - Tianxin Mao
- Center for Magnetic Resonance Imaging Research, Key Laboratory of Applied Brain and Cognitive Sciences, Shanghai International Studies University, Shanghai, China
| | - Yong Xu
- Center for Magnetic Resonance Imaging Research, Key Laboratory of Applied Brain and Cognitive Sciences, Shanghai International Studies University, Shanghai, China
| | - Caihong Jiang
- Center for Magnetic Resonance Imaging Research, Key Laboratory of Applied Brain and Cognitive Sciences, Shanghai International Studies University, Shanghai, China
| | - Hengyi Rao
- Center for Magnetic Resonance Imaging Research, Key Laboratory of Applied Brain and Cognitive Sciences, Shanghai International Studies University, Shanghai, China
- Institute of Linguistics, Shanghai International Studies University, Shanghai, China
- Center for Functional Neuroimaging, Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States
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18
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Fernández A, Noce G, Del Percio C, Pinal D, Díaz F, Lojo-Seoane C, Zurrón M, Babiloni C. Resting state electroencephalographic rhythms are affected by immediately preceding memory demands in cognitively unimpaired elderly and patients with mild cognitive impairment. Front Aging Neurosci 2022; 14:907130. [PMID: 36062151 PMCID: PMC9435320 DOI: 10.3389/fnagi.2022.907130] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Accepted: 07/18/2022] [Indexed: 11/23/2022] Open
Abstract
Experiments on event-related electroencephalographic oscillations in aged people typically include blocks of cognitive tasks with a few minutes of interval between them. The present exploratory study tested the effect of being engaged on cognitive tasks over the resting state cortical arousal after task completion, and whether it differs according to the level of the participant’s cognitive decline. To investigate this issue, we used a local database including data in 30 healthy cognitively unimpaired (CU) persons and 40 matched patients with amnestic mild cognitive impairment (aMCI). They had been involved in 2 memory tasks for about 40 min and underwent resting-state electroencephalographic (rsEEG) recording after 5 min from the task end. eLORETA freeware estimated rsEEG alpha source activity as an index of general cortical arousal. In the CU but not aMCI group, there was a negative correlation between memory tasks performance and posterior rsEEG alpha source activity. The better the memory tasks performance, the lower the posterior alpha activity (i.e., higher cortical arousal). There was also a negative correlation between neuropsychological test scores of global cognitive status and alpha source activity. These results suggest that engagement in memory tasks may perturb background brain arousal for more than 5 min after the tasks end, and that this effect are dependent on participants global cognitive status. Future studies in CU and aMCI groups may cross-validate and extend these results with experiments including (1) rsEEG recordings before memory tasks and (2) post-tasks rsEEG recordings after 5, 15, and 30 min.
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Affiliation(s)
- Alba Fernández
- Departamento de Psicoloxía Clínica e Psicobioloxía, Facultade de Psicoloxía, Universidade de Santiago de Compostela, Santiago de Compostela, Spain
- *Correspondence: Alba Fernández,
| | | | - Claudio Del Percio
- Department of Physiology and Pharmacology “V. Erspamer”, Sapienza University of Rome, Rome, Italy
| | - Diego Pinal
- Psychological Neuroscience Lab, Escola de Psicologia, Universidade do Minho, Braga, Portugal
| | - Fernando Díaz
- Departamento de Psicoloxía Clínica e Psicobioloxía, Facultade de Psicoloxía, Universidade de Santiago de Compostela, Santiago de Compostela, Spain
| | - Cristina Lojo-Seoane
- Departamento de Psicoloxía Evolutiva e da Educación, Facultade de Psicoloxía, Universidade de Santiago de Compostela, Santiago de Compostela, Spain
| | - Montserrat Zurrón
- Departamento de Psicoloxía Clínica e Psicobioloxía, Facultade de Psicoloxía, Universidade de Santiago de Compostela, Santiago de Compostela, Spain
| | - Claudio Babiloni
- Department of Physiology and Pharmacology “V. Erspamer”, Sapienza University of Rome, Rome, Italy
- San Raffaele Cassino, Cassino, Italy
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19
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Wang P, He Y, Maess B, Yue J, Chen L, Brauer J, Friederici AD, Knösche TR. Alpha power during task performance predicts individual language comprehension. Neuroimage 2022; 260:119449. [PMID: 35835340 DOI: 10.1016/j.neuroimage.2022.119449] [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: 10/24/2021] [Revised: 06/15/2022] [Accepted: 07/03/2022] [Indexed: 11/29/2022] Open
Abstract
Alpha power attenuation during cognitive task performing has been suggested to reflect a process of release of inhibition, increase of excitability, and thereby benefit the improvement of performance. Here, we hypothesized that changes in individual alpha power during the execution of a complex language comprehension task may correlate with the individual performance in that task. We tested this using magnetoencephalography (MEG) recorded during comprehension of German sentences of different syntactic complexity. Results showed that neither the frequency nor the power of the spontaneous oscillatory activity at rest were associated with the individual performance. However, during the execution of a sentences processing task, the individual alpha power attenuation did correlate with individual language comprehension performance. Source reconstruction localized these effects in left temporal-parietal brain regions known to be associated with language processing and their right-hemisphere homologues. Our results support the notion that in-task attenuation of individual alpha power is related to the essential mechanisms of the underlying cognitive processes, rather than merely to general phenomena like attention or vigilance.
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Affiliation(s)
- P Wang
- Max Planck Institute for Human Cognitive and Brain Sciences, Brain Networks Group, Leipzig, Germany
| | - Y He
- Philipps University Marburg, Department of Psychiatry and Psychotherapy, Marburg, Germany
| | - B Maess
- Max Planck Institute for Human Cognitive and Brain Sciences, Brain Networks Group, Leipzig, Germany
| | - J Yue
- Harbin Institute of Technology, Laboratory for Cognitive and Social Neuroscience, School of Management, Harbin, China
| | - L Chen
- Max Planck Institute for Human Cognitive and Brain Sciences, Department of Neuropsychology, Leipzig, Germany; Beijing Normal University, College of Chinese Language and Culture, Beijing, China
| | - J Brauer
- Max Planck Institute for Human Cognitive and Brain Sciences, Department of Neuropsychology, Leipzig, Germany; Friedrich Schiller University, Office of the Vice-President for Young Researchers, Jena, Germany
| | - A D Friederici
- Max Planck Institute for Human Cognitive and Brain Sciences, Department of Neuropsychology, Leipzig, Germany
| | - T R Knösche
- Max Planck Institute for Human Cognitive and Brain Sciences, Brain Networks Group, Leipzig, Germany.
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20
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Inhibitory Control and Brain–Heart Interaction: An HRV-EEG Study. Brain Sci 2022; 12:brainsci12060740. [PMID: 35741625 PMCID: PMC9221218 DOI: 10.3390/brainsci12060740] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Revised: 06/01/2022] [Accepted: 06/02/2022] [Indexed: 12/10/2022] Open
Abstract
Background: Motor inhibition is a complex cognitive function regulated by specific brain regions and influenced by the activity of the Central Autonomic Network. We investigate the two-way Brain–Heart interaction during a Go/NoGo task. Spectral EEG ϑ, α powerbands, and HRV parameters (Complexity Index (CI), Low Frequency (LF) and High Frequency (HF) powers) were recorded. Methods: Fourteen healthy volunteers were enrolled. We used a modified version of the classical Go/NoGo task, based on Rule Shift Cards, characterized by a baseline and two different tasks of different complexity. The participants were divided into subjects with Good (GP) and Poor (PP) performances. Results: In the baseline, CI was negatively correlated with α/ϑ. In task 1, the CI was negatively correlated with the errors and α/ϑ, while the errors were positively correlated with α/ϑ. In task 2, CI was negatively correlated with the Reaction Time and positively with α, and the errors were negatively correlated with the Reaction Time and positively correlated with α/ϑ. The GP group showed, at baseline, a negative correlation between CI and α/ϑ. Conclusions: We provide a new combined Brain–Heart model underlying inhibitory control abilities. The results are consistent with the complementary role of α and ϑ oscillations in cognitive control.
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21
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Scheijbeler EP, van Nifterick AM, Stam CJ, Hillebrand A, Gouw AA, de Haan W. Network-level permutation entropy of resting-state MEG recordings: A novel biomarker for early-stage Alzheimer's disease? Netw Neurosci 2022; 6:382-400. [PMID: 35733433 PMCID: PMC9208018 DOI: 10.1162/netn_a_00224] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Accepted: 12/15/2021] [Indexed: 11/24/2022] Open
Abstract
Increasing evidence suggests that measures of signal variability and complexity could present promising biomarkers for Alzheimer's disease (AD). Earlier studies have however been limited to the characterization of local activity. Here, we investigate whether a network version of permutation entropy could serve as a novel biomarker for early-stage AD. Resting-state source-space magnetoencephalography was recorded in 18 subjects with subjective cognitive decline (SCD) and 18 subjects with mild cognitive impairment (MCI). Local activity was characterized by permutation entropy (PE). Network-level interactions were studied using the inverted joint permutation entropy (JPEinv), corrected for volume conduction. The JPEinv showed a reduction of nonlinear connectivity in MCI subjects in the theta and alpha band. Local PE showed increased theta band entropy. Between-group differences were widespread across brain regions. Receiver operating characteristic (ROC) analysis of classification of MCI versus SCD subjects revealed that a logistic regression model trained on JPEinv features (78.4% [62.5-93.3%]) slightly outperformed PE (76.9% [60.3-93.4%]) and relative theta power-based models (76.9% [60.4-93.3%]). Classification performance of theta JPEinv was at least as good as the relative theta power benchmark. The JPEinv is therefore a potential biomarker for early-stage AD that should be explored in larger studies.
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Affiliation(s)
- Elliz P. Scheijbeler
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
- Department of Clinical Neurophysiology and MEG Center, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Anne M. van Nifterick
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
- Department of Clinical Neurophysiology and MEG Center, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Cornelis J. Stam
- Department of Clinical Neurophysiology and MEG Center, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Arjan Hillebrand
- Department of Clinical Neurophysiology and MEG Center, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Alida A. Gouw
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
- Department of Clinical Neurophysiology and MEG Center, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Willem de Haan
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
- Department of Clinical Neurophysiology and MEG Center, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
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22
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Zhou Q, Cheng R, Yao L, Ye X, Xu K. Neurofeedback Training of Alpha Relative Power Improves the Performance of Motor Imagery Brain-Computer Interface. Front Hum Neurosci 2022; 16:831995. [PMID: 35463935 PMCID: PMC9026187 DOI: 10.3389/fnhum.2022.831995] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2021] [Accepted: 03/16/2022] [Indexed: 01/03/2023] Open
Abstract
Significant variation in performance in motor imagery (MI) tasks impedes their wide adoption for brain-computer interface (BCI) applications. Previous researchers have found that resting-state alpha-band power is positively correlated with MI-BCI performance. In this study, we designed a neurofeedback training (NFT) protocol based on the up-regulation of the alpha band relative power (RP) to investigate its effect on MI-BCI performance. The principal finding of this study is that alpha NFT could successfully help subjects increase alpha-rhythm power and improve their MI-BCI performance. An individual difference was also found in this study in that subjects who increased alpha power more had a better performance improvement. Additionally, the functional connectivity (FC) of the frontal-parietal (FP) network was found to be enhanced after alpha NFT. However, the enhancement failed to reach a significant level after multiple comparisons correction. These findings contribute to a better understanding of the neurophysiological mechanism of cognitive control through alpha regulation.
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Affiliation(s)
- Qing Zhou
- Qiushi Academy for Advanced Studies (QAAS), Zhejiang University, Hangzhou, China
- Zhejiang Lab, Hangzhou, China
- Zhejiang Provincial Key Laboratory of Cardio-Cerebral Vascular Detection Technology and Medicinal Effectiveness Appraisal, Key Laboratory of Biomedical Engineering of Education Ministry, Zhejiang University, Hangzhou, China
| | - Ruidong Cheng
- Center for Rehabilitation Medicine, Rehabilitation and Sports Medicine Research Institute of Zhejiang Province, Department of Rehabilitation Medicine, Zhejiang Provincial People’s Hospital (Affiliated People’s Hospital, Hangzhou Medical College), Hangzhou, China
| | - Lin Yao
- MOE Frontiers Science Center for Brain and Brain-Machine Integration, Zhejiang University, Hangzhou, China
- Department of Neurobiology, Affiliated Mental Health Center and Hangzhou Seventh People’s Hospital, Zhejiang University School of Medicine, Hangzhou, China
- The College of Computer Science, Zhejiang University, Hangzhou, China
| | - Xiangming Ye
- Center for Rehabilitation Medicine, Rehabilitation and Sports Medicine Research Institute of Zhejiang Province, Department of Rehabilitation Medicine, Zhejiang Provincial People’s Hospital (Affiliated People’s Hospital, Hangzhou Medical College), Hangzhou, China
- Xiangming Ye,
| | - Kedi Xu
- Qiushi Academy for Advanced Studies (QAAS), Zhejiang University, Hangzhou, China
- Zhejiang Lab, Hangzhou, China
- Zhejiang Provincial Key Laboratory of Cardio-Cerebral Vascular Detection Technology and Medicinal Effectiveness Appraisal, Key Laboratory of Biomedical Engineering of Education Ministry, Zhejiang University, Hangzhou, China
- MOE Frontiers Science Center for Brain and Brain-Machine Integration, Zhejiang University, Hangzhou, China
- *Correspondence: Kedi Xu,
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23
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Pscherer C, Mückschel M, Bluschke A, Beste C. Resting-state theta activity is linked to information content-specific coding levels during response inhibition. Sci Rep 2022; 12:4530. [PMID: 35296740 PMCID: PMC8927579 DOI: 10.1038/s41598-022-08510-8] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2021] [Accepted: 03/07/2022] [Indexed: 11/16/2022] Open
Abstract
The neurophysiological processes underlying the inhibition of impulsive responses have been studied extensively. While also the role of theta oscillations during response inhibition is well examined, the relevance of resting-state theta activity for inhibitory control processes is largely unknown. We test the hypothesis that there are specific relationships between resting-state theta activity and sensory/motor coding levels during response inhibition using EEG methods. We show that resting theta activity is specifically linked to the stimulus-related fraction of neurophysiological activity in specific time windows during motor inhibition. In contrast, concomitantly coded processes related to decision-making or response selection as well as the behavioral inhibition performance were not associated with resting theta activity. Even at the peak of task-related theta power, where task-related theta activity and resting theta activity differed the most, there was still predominantly a significant correlation between both types of theta activity. This suggests that aspects similar to resting dynamics are evident in the proportion of inhibition-related neurophysiological activity that reflects an “alarm” signal, whose function is to process and indicate the need for cognitive control. Thus, specific aspects of task-related theta power may build upon resting theta activity when cognitive control is necessary.
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Affiliation(s)
- Charlotte Pscherer
- Cognitive Neurophysiology, Department of Child and Adolescent Psychiatry, Faculty of Medicine, TU Dresden, Schubertstrasse 42, 01309, Dresden, Germany.
| | - Moritz Mückschel
- Cognitive Neurophysiology, Department of Child and Adolescent Psychiatry, Faculty of Medicine, TU Dresden, Schubertstrasse 42, 01309, Dresden, Germany
| | - Annet Bluschke
- Cognitive Neurophysiology, Department of Child and Adolescent Psychiatry, Faculty of Medicine, TU Dresden, Schubertstrasse 42, 01309, Dresden, Germany
| | - Christian Beste
- Cognitive Neurophysiology, Department of Child and Adolescent Psychiatry, Faculty of Medicine, TU Dresden, Schubertstrasse 42, 01309, Dresden, Germany
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24
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Sadaghiani S, Brookes MJ, Baillet S. Connectomics of human electrophysiology. Neuroimage 2022; 247:118788. [PMID: 34906715 PMCID: PMC8943906 DOI: 10.1016/j.neuroimage.2021.118788] [Citation(s) in RCA: 48] [Impact Index Per Article: 24.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Revised: 11/03/2021] [Accepted: 12/06/2021] [Indexed: 12/15/2022] Open
Abstract
We present both a scientific overview and conceptual positions concerning the challenges and assets of electrophysiological measurements in the search for the nature and functions of the human connectome. We discuss how the field has been inspired by findings and approaches from functional magnetic resonance imaging (fMRI) and informed by a small number of significant multimodal empirical studies, which show that the canonical networks that are commonplace in fMRI are in fact rooted in electrophysiological processes. This review is also an opportunity to produce a brief, up-to-date critical survey of current data modalities and analytical methods available for deriving both static and dynamic connectomes from electrophysiology. We review hurdles that challenge the significance and impact of current electrophysiology connectome research. We then encourage the field to take a leap of faith and embrace the wealth of electrophysiological signals, despite their apparent, disconcerting complexity. Our position is that electrophysiology connectomics is poised to inform testable mechanistic models of information integration in hierarchical brain networks, constructed from observable oscillatory and aperiodic signal components and their polyrhythmic interactions.
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Affiliation(s)
- Sepideh Sadaghiani
- Department of Psychology, University of Illinois, Urbana-Champaign, IL, United States; Beckman Institute for Advanced Science and Technology, University of Illinois, Urbana-Champaign, IL, United States
| | - Matthew J Brookes
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham NG72RD, United Kingdom
| | - Sylvain Baillet
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
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25
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Shephard E, McEwen FS, Earnest T, Friedrich N, Mörtl I, Liang H, Woodhouse E, Tye C, Bolton PF. Oscillatory neural network alterations in young people with tuberous sclerosis complex and associations with co-occurring symptoms of autism spectrum disorder and attention-deficit/hyperactivity disorder. Cortex 2021; 146:50-65. [PMID: 34839218 DOI: 10.1016/j.cortex.2021.10.007] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2021] [Revised: 08/25/2021] [Accepted: 10/20/2021] [Indexed: 12/20/2022]
Abstract
Tuberous sclerosis complex (TSC) is a genetic disorder caused by mutations on the TSC1/TSC2 genes, which result in alterations in molecular signalling pathways involved in neurogenesis and hamartomas in the brain and other organs. TSC carries a high risk for autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD), although the reasons for this are unclear. One proposal is that TSC-related alterations in molecular signalling during neurogenesis lead to atypical development of neural networks, which are involved in the occurrence of ASD and ADHD in TSC. We investigated this proposal in young people with TSC who have been studied longitudinally since their diagnosis in childhood. Electroencephalography (EEG) was used to examine oscillatory connectivity in functional neural networks and local and global network organisation during three tasks (resting-state, attentional and inhibitory control Go/Nogo task, upright and inverted face processing task) in participants with TSC (n = 48) compared to an age- and sex-matched group of typically developing Controls (n = 20). Compared to Controls, the TSC group showed hypoconnected neural networks in the alpha frequency during the resting-state and in the theta and alpha frequencies during the Go/Nogo task (P ≤ .008), as well as reduced local network organisation in the theta and alpha frequencies during the Go/Nogo task (F = 3.95, P = .010). There were no significant group differences in network metrics during the face processing task. Increased connectivity in the hypoconnected alpha-range resting-state network was associated with greater ASD and inattentive ADHD symptoms (rho≥.40, P ≤ .036). Reduced local network organisation in the theta-range during the Go/Nogo task was significantly associated with higher hyperactive/impulsive ADHD symptoms (rho = -.43, P = .041). These findings suggest that TSC is associated with widespread hypoconnectivity in neural networks and support the proposal that altered network function may be involved in the co-occurrence of ASD and ADHD in TSC.
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Affiliation(s)
- Elizabeth Shephard
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology & Neuroscience (IoPPN), King's College London, UK; Department of Psychiatry, University of São Paulo, Brazil.
| | - Fiona S McEwen
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology & Neuroscience (IoPPN), King's College London, UK; Department of Psychology, Queen Mary University of London, UK
| | - Thomas Earnest
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology & Neuroscience (IoPPN), King's College London, UK
| | - Nina Friedrich
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology & Neuroscience (IoPPN), King's College London, UK
| | - Isabelle Mörtl
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology & Neuroscience (IoPPN), King's College London, UK
| | - Holan Liang
- Population, Policy and Practice Department, UCL Great Ormond Street Institute of Child Health, London, UK
| | - Emma Woodhouse
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience (IoPPN), King's College London, UK
| | | | - Charlotte Tye
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology & Neuroscience (IoPPN), King's College London, UK; Department of Psychology, Institute of Psychiatry, Psychology & Neuroscience (IoPPN), King's College London, UK
| | - Patrick F Bolton
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology & Neuroscience (IoPPN), King's College London, UK; The Maudsley NIHR Biomedical Research Centre in Mental Health, King's College London and South London and Maudsley NHS Foundation Trust, London, UK
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26
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Kumral D, Cesnaite E, Beyer F, Hofmann SM, Hensch T, Sander C, Hegerl U, Haufe S, Villringer A, Witte AV, Nikulin VV. Relationship between regional white matter hyperintensities and alpha oscillations in older adults. Neurobiol Aging 2021; 112:1-11. [PMID: 35007997 DOI: 10.1016/j.neurobiolaging.2021.10.006] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2020] [Revised: 09/22/2021] [Accepted: 10/12/2021] [Indexed: 11/17/2022]
Abstract
Aging is associated with increased white matter hyperintensities (WMHs) and with alterations of alpha oscillations (7-13 Hz). However, a crucial question remains, whether changes in alpha oscillations relate to aging per se or whether this relationship is mediated by age-related neuropathology like WMHs. Using a large cohort of cognitively healthy older adults (N = 907, 60-80 years), we assessed relative alpha power, alpha peak frequency, and long-range temporal correlations from resting-state EEG. We further associated these parameters with voxel-wise WMHs from 3T MRI. We found that a higher prevalence of WMHs in the superior and posterior corona radiata as well as in the thalamic radiation was related to elevated alpha power, with the strongest association in the bilateral occipital cortex. In contrast, we observed no significant relation of the WMHs probability with alpha peak frequency and long-range temporal correlations. Finally, higher age was associated with elevated alpha power via total WMH volume. We suggest that an elevated alpha power is a consequence of WMHs affecting a spatial organization of alpha sources.
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Affiliation(s)
- Deniz Kumral
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Institute of Psychology, Neuropsychology, University of Freiburg, Freiburg im Breisgau, Germany; Clinical Psychology and Psychotherapy Unit, Institute of Psychology, University of Freiburg, Freiburg im Breisgau, Germany.
| | - Elena Cesnaite
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Frauke Beyer
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; CRC Obesity Mechanisms, Subproject A1, University of Leipzig, Leipzig, Germany
| | - Simon M Hofmann
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Tilman Hensch
- Department of Psychiatry and Psychotherapy, University of Leipzig Medical Center, Leipzig, Germany; LIFE - Leipzig Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany; Department of Psychology, IU International University of Applied Sciences, Erfurt, Germany
| | - Christian Sander
- Department of Psychiatry and Psychotherapy, University of Leipzig Medical Center, Leipzig, Germany; LIFE - Leipzig Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany
| | - Ulrich Hegerl
- Department of Psychiatry, Psychosomatics and Psychotherapy, Goethe University Frankfurt, Frankfurt, Germany
| | - Stefan Haufe
- Berlin Center for Advanced Neuroimaging, Charité - Universitätsmedizin Berlin, Berlin, Germany; Bernstein Center for Computational Neuroscience Berlin, Berlin, Germany
| | - Arno Villringer
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Clinic for Cognitive Neurology, University Medical Center Leipzig, Germany
| | - A Veronica Witte
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; CRC Obesity Mechanisms, Subproject A1, University of Leipzig, Leipzig, Germany; Clinic for Cognitive Neurology, University Medical Center Leipzig, Germany
| | - Vadim V Nikulin
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Bernstein Center for Computational Neuroscience Berlin, Berlin, Germany; Centre for Cognition and Decision making, Institute for Cognitive Neuroscience, HSE University, Moscow, Russia; Neurophysics Group, Department of Neurology, Charité-Universitätsmedizin Berlin, Berlin, Germany
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27
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Golemme M, Tatti E, Di Bernardi Luft C, Bhattacharya J, Herrojo Ruiz M, Cappelletti M. Multivariate patterns and long-range temporal correlations of alpha oscillations are associated with flexible manipulation of visual working memory representations. Eur J Neurosci 2021; 54:7260-7273. [PMID: 34618375 DOI: 10.1111/ejn.15486] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2019] [Revised: 09/26/2021] [Accepted: 09/27/2021] [Indexed: 11/29/2022]
Abstract
The ability to flexibly manipulate memory representations is embedded in visual working memory (VWM) and can be tested using paradigms with retrospective cues. Although valid retrospective cues often facilitate memory recall, invalid ones may or may not result in performance costs. We investigated individual differences in utilising retrospective cues and evaluated how these individual differences are associated with brain oscillatory activity at rest. At the behavioural level, we operationalised flexibility as the ability to make effective use of retrospective cues or disregard them if required. At the neural level, we tested whether individual differences in such flexibility were associated with properties of resting-state alpha oscillatory activity (8-12 Hz). To capture distinct aspects of these brain oscillations, we evaluated their power spectral density and temporal dynamics using long-range temporal correlations (LRTCs). In addition, we performed multivariate patterns analysis (MVPA) to classify individuals' level of behavioural flexibility based on these neural measures. We observed that alpha power alone (magnitude) at rest was not associated with flexibility. However, we found that the participants' ability to manipulate VWM representations was correlated with alpha LRTC and could be decoded using MVPA on patterns of alpha power. Our findings suggest that alpha LRTC and multivariate patterns of alpha power at rest may underlie some of the individual differences in using retrospective cues in working memory tasks.
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Affiliation(s)
- Mara Golemme
- Department of Psychology, Goldsmiths, University of London, London, UK.,UK Dementia Research Institute, Imperial College London, London, UK
| | - Elisa Tatti
- Department of Psychology, Goldsmiths, University of London, London, UK.,CUNY, School of Medicine, City College Of New York, New York, New York, USA
| | | | | | - Maria Herrojo Ruiz
- Department of Psychology, Goldsmiths, University of London, London, UK.,Center for Cognition and Decision Making, Institute for Cognitive Neuroscience, National Research University Higher School of Economics, Moscow, Russian Federation
| | - Marinella Cappelletti
- Department of Psychology, Goldsmiths, University of London, London, UK.,Institute of Cognitive Neuroscience, University College London, London, UK
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28
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Zhou Q, Lin J, Yao L, Wang Y, Han Y, Xu K. Relative Power Correlates With the Decoding Performance of Motor Imagery Both Across Time and Subjects. Front Hum Neurosci 2021; 15:701091. [PMID: 34483866 PMCID: PMC8414415 DOI: 10.3389/fnhum.2021.701091] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2021] [Accepted: 07/15/2021] [Indexed: 11/23/2022] Open
Abstract
One of the most significant challenges in the application of brain-computer interfaces (BCI) is the large performance variation, which often occurs over time or across users. Recent evidence suggests that the physiological states may explain this performance variation in BCI, however, the underlying neurophysiological mechanism is unclear. In this study, we conducted a seven-session motor-imagery (MI) experiment on 20 healthy subjects to investigate the neurophysiological mechanism on the performance variation. The classification accuracy was calculated offline by common spatial pattern (CSP) and support vector machine (SVM) algorithms to measure the MI performance of each subject and session. Relative Power (RP) values from different rhythms and task stages were used to reflect the physiological states and their correlation with the BCI performance was investigated. Results showed that the alpha band RP from the supplementary motor area (SMA) within a few seconds before MI was positively correlated with performance. Besides, the changes of RP between task and pre-task stage from theta, alpha, and gamma band were also found to be correlated with performance both across time and subjects. These findings reveal a neurophysiological manifestation of the performance variations, and would further provide a way to improve the BCI performance.
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Affiliation(s)
- Qing Zhou
- Zhejiang Lab, Hangzhou, China.,Key Laboratory of Biomedical Engineering of Education Ministry, Department of Biomedical Engineering, Qiushi Academy for Advanced Studies, Zhejiang University, Hangzhou, China
| | - Jiafan Lin
- Key Laboratory of Biomedical Engineering of Education Ministry, Department of Biomedical Engineering, Qiushi Academy for Advanced Studies, Zhejiang University, Hangzhou, China
| | - Lin Yao
- Frontiers Science Center for Brain and Brain-Machine Integration, Zhejiang University, Hangzhou, China.,The College of Computer Science and Technology, Zhejiang University, Hangzhou, China
| | - Yueming Wang
- Zhejiang Lab, Hangzhou, China.,Key Laboratory of Biomedical Engineering of Education Ministry, Department of Biomedical Engineering, Qiushi Academy for Advanced Studies, Zhejiang University, Hangzhou, China.,Frontiers Science Center for Brain and Brain-Machine Integration, Zhejiang University, Hangzhou, China.,The College of Computer Science and Technology, Zhejiang University, Hangzhou, China
| | - Yan Han
- Zhejiang Key Laboratory of Neuroelectronics and Brain Computer Interface Technology, Hangzhou, China
| | - Kedi Xu
- Zhejiang Lab, Hangzhou, China.,Key Laboratory of Biomedical Engineering of Education Ministry, Department of Biomedical Engineering, Qiushi Academy for Advanced Studies, Zhejiang University, Hangzhou, China.,Frontiers Science Center for Brain and Brain-Machine Integration, Zhejiang University, Hangzhou, China.,The College of Computer Science and Technology, Zhejiang University, Hangzhou, China
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29
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Viviani G, Vallesi A. EEG-neurofeedback and executive function enhancement in healthy adults: A systematic review. Psychophysiology 2021; 58:e13874. [PMID: 34117795 PMCID: PMC8459257 DOI: 10.1111/psyp.13874] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2020] [Revised: 04/03/2021] [Accepted: 05/17/2021] [Indexed: 01/19/2023]
Abstract
Electroencephalographic (EEG)-neurofeedback training (NFT) is a promising technique that supports individuals in learning to modulate their brain activity to obtain cognitive and behavioral improvements. EEG-NFT is gaining increasing attention for its potential "peak performance" applications on healthy individuals. However, evidence for clear cognitive performance enhancements with healthy adults is still lacking. In particular, whether EEG-NFT represents an effective technique for enhancing healthy adults' executive functions is still controversial. Therefore, the main objective of this systematic review is to assess whether the existing EEG-NFT studies targeting executive functions have provided reliable evidence for NFT effectiveness. To this end, we conducted a qualitative analysis of the literature since the limited number of retrieved studies did not allow us meta-analytical comparisons. Moreover, a second aim was to identify optimal frequencies as NFT targets for specifically improving executive functions. Overall, our systematic review provides promising evidence for NFT effectiveness in boosting healthy adults' executive functions. However, more rigorous NFT studies are required in order to overcome the methodological weaknesses that we encountered in our qualitative analysis.
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Affiliation(s)
- Giada Viviani
- Department of Neuroscience and Padova Neuroscience CenterUniversity of PadovaPadovaItaly
| | - Antonino Vallesi
- Department of Neuroscience and Padova Neuroscience CenterUniversity of PadovaPadovaItaly
- IRCCS San Camillo HospitalVeniceItaly
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30
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Ostrowski LM, Spencer ER, Bird LM, Thibert R, Komorowski RW, Kramer MA, Chu CJ. Delta power robustly predicts cognitive function in Angelman syndrome. Ann Clin Transl Neurol 2021; 8:1433-1445. [PMID: 34047077 PMCID: PMC8283185 DOI: 10.1002/acn3.51385] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2021] [Revised: 05/05/2021] [Accepted: 05/06/2021] [Indexed: 12/15/2022] Open
Abstract
Objective Angelman syndrome (AS) is a severe neurodevelopmental disorder caused by loss of function of the maternally inherited UBE3A gene in neurons. Promising disease‐modifying treatments to reinstate UBE3A expression are under development and an early measure of treatment response is critical to their deployment in clinical trials. Increased delta power in EEG recordings, reflecting abnormal neuronal synchrony, occurs in AS across species and correlates with genotype. Whether delta power provides a reliable biomarker for clinical symptoms remains unknown. Methods We analyzed combined EEG recordings and developmental assessments in a large cohort of individuals with AS (N = 82 subjects, 133 combined EEG and cognitive assessments, 1.08–28.16 years; 32F) and evaluated delta power as a biomarker for cognitive function, as measured by the Bayley Cognitive Score. We examined the robustness of this biomarker to varying states of consciousness, recording techniques and analysis procedures. Results Delta power predicted the Bayley Scale cognitive score (P < 10−5, R2 = 0.9374) after controlling for age (P < 10−24), genotype:age (P < 10−11), and repeat assessments (P < 10−8), with the excellent fit on cross validation (R2 = 0.95). There were no differences in model performance across states of consciousness or bipolar versus average montages (ΔAIC < 2). Models using raw data excluding frontal channels outperformed other models (ΔAIC > 4) and predicted performance in expressive (P = 0.0209) and receptive communication (P < 10−3) and fine motor skills (P < 10−4). Interpretation Delta power is a simple, direct measure of neuronal activity that reliably correlates with cognitive function in AS. This electrophysiological biomarker offers an objective, clinically relevant endpoint for treatment response in emerging clinical trials.
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Affiliation(s)
- Lauren M. Ostrowski
- Department of NeurologyMassachusetts General HospitalBostonMassachusettsUSA
- School of MedicineUniversity of CaliforniaSan DiegoCaliforniaUSA
| | - Elizabeth R. Spencer
- Department of NeurologyMassachusetts General HospitalBostonMassachusettsUSA
- Department of Mathematics and StatisticsBoston UniversityBostonMassachusettsUSA
| | - Lynne M. Bird
- Department of PediatricsUniversity of CaliforniaSan DiegoCaliforniaUSA
| | - Ronald Thibert
- Department of NeurologyMassachusetts General HospitalBostonMassachusettsUSA
- Harvard Medical SchoolBostonMassachusettsUSA
| | | | - Mark A. Kramer
- Department of Mathematics and StatisticsBoston UniversityBostonMassachusettsUSA
| | - Catherine J. Chu
- Department of NeurologyMassachusetts General HospitalBostonMassachusettsUSA
- Harvard Medical SchoolBostonMassachusettsUSA
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31
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Pscherer C, Bluschke A, Mückschel M, Beste C. The interplay of resting and inhibitory control-related theta-band activity depends on age. Hum Brain Mapp 2021; 42:3845-3857. [PMID: 33982854 PMCID: PMC8288092 DOI: 10.1002/hbm.25469] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2021] [Revised: 04/26/2021] [Accepted: 04/28/2021] [Indexed: 02/06/2023] Open
Abstract
Resting‐state neural activity plays an important role for cognitive control processes. Regarding response inhibition processes, an important facet of cognitive control, especially theta‐band activity has been the focus of research. Theoretical considerations suggest that the interrelation of resting and task‐related theta activity is subject to maturational effects. To investigate whether the relationship between resting theta activity and task‐related theta activity during a response inhibition task changes even in young age, we tested N = 166 healthy participants between 8 and 30 years of age. We found significant correlations between resting and inhibitory control‐related theta activity as well as behavioral inhibition performance. Importantly, these correlations were moderated by age. The moderation analysis revealed that higher resting theta activity was associated with stronger inhibition‐related theta activity in individuals above the age of ~10.7 years. The EEG beamforming analysis showed that this activity is associated with superior frontal region function (BA6). The correlation between resting and superior frontal response inhibition‐related theta activity became stronger with increasing age. A similar pattern was found for response inhibition performance, albeit only evident from the age of ~19.5 years. The results suggest that with increasing age, resting theta activity becomes increasingly important for processing the alarm/surprise signals in superior frontal brain regions during inhibitory control. Possible causes for these developmental changes are discussed.
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Affiliation(s)
- Charlotte Pscherer
- Faculty of Medicine, Cognitive Neurophysiology, Department of Child and Adolescent Psychiatry, TU Dresden, Dresden, Germany
| | - Annet Bluschke
- Faculty of Medicine, Cognitive Neurophysiology, Department of Child and Adolescent Psychiatry, TU Dresden, Dresden, Germany
| | - Moritz Mückschel
- Faculty of Medicine, Cognitive Neurophysiology, Department of Child and Adolescent Psychiatry, TU Dresden, Dresden, Germany
| | - Christian Beste
- Faculty of Medicine, Cognitive Neurophysiology, Department of Child and Adolescent Psychiatry, TU Dresden, Dresden, Germany
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32
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Herzog ND, Steinfath TP, Tarrasch R. Critical Dynamics in Spontaneous Resting-State Oscillations Are Associated With the Attention-Related P300 ERP in a Go/Nogo Task. Front Neurosci 2021; 15:632922. [PMID: 33828446 PMCID: PMC8019703 DOI: 10.3389/fnins.2021.632922] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2020] [Accepted: 02/26/2021] [Indexed: 11/13/2022] Open
Abstract
Sustained attention is the ability to continually concentrate on task-relevant information, even in the presence of distraction. Understanding the neural mechanisms underlying this ability is critical for comprehending attentional processes as well as neuropsychiatric disorders characterized by attentional deficits, such as attention deficit hyperactivity disorder (ADHD). In this study, we aimed to investigate how trait-like critical oscillations during rest relate to the P300 evoked potential-a biomarker commonly used to assess attentional deficits. We measured long-range temporal correlations (LRTC) in resting-state EEG oscillations as index for criticality of the signal. In addition, the attentional performance of the subjects was assessed as reaction time variability (RTV) in a continuous performance task following an oddball paradigm. P300 amplitude and latencies were obtained from EEG recordings during this task. We found that, after controlling for individual variability in task performance, LRTC were positively associated with P300 amplitudes but not latencies. In line with previous findings, good performance in the sustained attention task was related to higher P300 amplitudes and earlier peak latencies. Unexpectedly, we observed a positive relationship between LRTC in ongoing oscillations during rest and RTV, indicating that greater criticality in brain oscillations during rest relates to worse task performance. In summary, our results show that resting-state neuronal activity, which operates near a critical state, relates to the generation of higher P300 amplitudes. Brain dynamics close to criticality potentially foster a computationally advantageous state which promotes the ability to generate higher event-related potential (ERP) amplitudes.
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Affiliation(s)
- Nadine D Herzog
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.,School of Education and Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
| | - Tim P Steinfath
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Ricardo Tarrasch
- School of Education and Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
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33
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Resting-state brain oscillations predict cognitive function in psychiatric disorders: A transdiagnostic machine learning approach. NEUROIMAGE-CLINICAL 2021; 30:102617. [PMID: 33752077 PMCID: PMC7985402 DOI: 10.1016/j.nicl.2021.102617] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/03/2020] [Revised: 02/03/2021] [Accepted: 02/28/2021] [Indexed: 11/23/2022]
Abstract
Resting EEG activity associated with cognitive function in psychiatric disorders. Using EEG, random forest modeling predicts cognitive performance but not diagnosis. High alpha oscillations associated with better episodic memory and processing speed. Beta oscillations associated with worse performance in several cognitive domains. EEG power changes in psychiatric disorders may be related to cognitive dysfunction.
Background Cognitive dysfunction is widespread in psychiatric disorders and can significantly impact quality of life. Deficits cut across traditional diagnostic boundaries, necessitating new approaches to understand how cognitive function relates to large-scale brain activity and psychiatric symptoms across the diagnostic spectrum. Objective Using random forest regression, we aimed to identify transdiagnostic patterns linking cognitive function to resting-state EEG oscillations. Methods 216 participants recruited through an outpatient psychiatric clinic completed the Cambridge Neuropsychological Test Automated Battery and underwent a 5-minute eyes-closed resting state EEG recording. We built random forest regression models to predict performance on each cognitive test using the resting-state EEG power spectrum as input, and we compared model performance to a sampling distribution constructed with random permutations. For models that performed significantly better than chance, we used feature importance estimates to identify features of the EEG power spectrum that are predictive of cognitive functioning. Results Random forest models successfully predicted performance on measures of episodic memory and associative learning (Paired Associates Learning, PAL), information processing speed (Choice Reaction Time, CRT), and attentional set-shifting and executive function (Intra-Extra Dimensional Set Shift, IED). Oscillatory power in the upper alpha range was associated with better performance on PAL and CRT, while low alpha power was associated with worse CRT performance. Beta power predicted poor performance on all three tests. Theta power was associated with good performance on PAL, and delta and theta oscillations were identified as predictors of good performance on IED. No differences in cognitive performance were found between diagnostic categories. Conclusion Resting oscillations are predictive of certain dimensions of cognitive function across various psychiatric disorders. These findings may inform treatment development to improve cognition.
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Clements GM, Bowie DC, Gyurkovics M, Low KA, Fabiani M, Gratton G. Spontaneous Alpha and Theta Oscillations Are Related to Complementary Aspects of Cognitive Control in Younger and Older Adults. Front Hum Neurosci 2021; 15:621620. [PMID: 33841114 PMCID: PMC8025241 DOI: 10.3389/fnhum.2021.621620] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2020] [Accepted: 02/15/2021] [Indexed: 12/18/2022] Open
Abstract
The resting-state human electroencephalogram (EEG) power spectrum is dominated by alpha (8-12 Hz) and theta (4-8 Hz) oscillations, and also includes non-oscillatory broadband activity inversely related to frequency (1/f activity). Gratton proposed that alpha and theta oscillations are both related to cognitive control function, though in a complementary manner. Alpha activity is hypothesized to facilitate the maintenance of representations, such as task sets in preparation for expected task conditions. In contrast, theta activity would facilitate changes in representations, such as the updating of task sets in response to unpredicted task demands. Therefore, theta should be related to reactive control (which may prompt changes in task representations), while alpha may be more relevant to proactive control (which implies the maintenance of current task representations). Less is known about the possible relationship between 1/f activity and cognitive control, which was analyzed here in an exploratory fashion. To investigate these hypothesized relationships, we recorded eyes-open and eyes-closed resting-state EEG from younger and older adults and subsequently tested their performance on a cued flanker task, expected to elicit both proactive and reactive control processes. Results showed that alpha power and 1/f offset were smaller in older than younger adults, whereas theta power did not show age-related reductions. Resting alpha power and 1/f offset were associated with proactive control processes, whereas theta power was related to reactive control as measured by the cued flanker task. All associations were present over and above the effect of age, suggesting that these resting-state EEG correlates could be indicative of trait-like individual differences in cognitive control performance, which may be already evident in younger adults, and are still similarly present in healthy older adults.
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Affiliation(s)
- Grace M Clements
- Beckman Institute, The University of Illinois at Urbana-Champaign, Champaign, IL, United States.,Psychology Department, The University of Illinois at Urbana-Champaign, Champaign, IL, United States
| | - Daniel C Bowie
- Beckman Institute, The University of Illinois at Urbana-Champaign, Champaign, IL, United States.,Psychology Department, The University of Illinois at Urbana-Champaign, Champaign, IL, United States
| | - Mate Gyurkovics
- Beckman Institute, The University of Illinois at Urbana-Champaign, Champaign, IL, United States
| | - Kathy A Low
- Beckman Institute, The University of Illinois at Urbana-Champaign, Champaign, IL, United States
| | - Monica Fabiani
- Beckman Institute, The University of Illinois at Urbana-Champaign, Champaign, IL, United States.,Psychology Department, The University of Illinois at Urbana-Champaign, Champaign, IL, United States
| | - Gabriele Gratton
- Beckman Institute, The University of Illinois at Urbana-Champaign, Champaign, IL, United States.,Psychology Department, The University of Illinois at Urbana-Champaign, Champaign, IL, United States
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35
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Zangrossi A, Zanzotto G, Lorenzoni F, Indelicato G, Cannas Aghedu F, Cermelli P, Bisiacchi PS. Resting-state functional brain connectivity predicts cognitive performance: An exploratory study on a time-based prospective memory task. Behav Brain Res 2021; 402:113130. [PMID: 33444694 DOI: 10.1016/j.bbr.2021.113130] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2020] [Revised: 12/22/2020] [Accepted: 01/05/2021] [Indexed: 11/16/2022]
Abstract
Resting-state functional brain connectivity (rsFC) is in wide use for the investigation of a variety of cognitive neuroscience phenomena. In the first phase of this study, we explored the changes in EEG-reconstructed rsFC in young vs. older adults, in the both the open-eyes (OE) and the closed-eyes (CE) conditions. The results showed significant differences in several rsFC network metrics in the two age groups, confirming and detailing established knowledge that aging modulates brain functional organisation. In the study's second phase we investigated the role of rsFC architecture on cognitive performance through a time-based Prospective Memory task involving participants who monitored the passage of time to perform a specific action at an appropriate time in the future. Regression models revealed that the monitoring strategy (i.e. the number of clock checks) can be predicted by rsFC graph metric, specifically, eccentricity and betweenness in the OE condition, and assortativity in the CE condition. These results show for the first time how metrics qualifying functional brain connectivity at rest can account for the differences in the way individuals strategically handle cognitive loads in the Prospective Memory domain.
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Affiliation(s)
- Andrea Zangrossi
- Department of Neuroscience, University of Padova, Padova, Italy; Padova Neuroscience Center (PNC), University of Padova, Padova, Italy.
| | - Giovanni Zanzotto
- Padova Neuroscience Center (PNC), University of Padova, Padova, Italy; Department of General Psychology, University of Padova, Padova, Italy
| | | | - Giuliana Indelicato
- York Cross-disciplinary Centre for Systems Analysis, Department of Mathematics, University of York, UK
| | | | | | - Patrizia Silvia Bisiacchi
- Padova Neuroscience Center (PNC), University of Padova, Padova, Italy; Department of General Psychology, University of Padova, Padova, Italy
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36
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Mondino A, Cavelli M, González J, Osorio L, Castro-Zaballa S, Costa A, Vanini G, Torterolo P. Power and Coherence in the EEG of the Rat: Impact of Behavioral States, Cortical Area, Lateralization and Light/Dark Phases. Clocks Sleep 2020; 2:536-556. [PMID: 33317018 PMCID: PMC7768537 DOI: 10.3390/clockssleep2040039] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2020] [Revised: 11/28/2020] [Accepted: 12/03/2020] [Indexed: 11/16/2022] Open
Abstract
The sleep-wake cycle is constituted by three behavioral states: wakefulness (W), non-REM (NREM) and REM sleep. These states are associated with drastic changes in cognitive capacities, mostly determined by the function of the thalamo-cortical system, whose activity can be examined by means of intra-cranial electroencephalogram (iEEG). With the purpose to study in depth the basal activity of the iEEG in adult rats, we analyzed the spectral power and coherence of the iEEG during W and sleep in the paleocortex (olfactory bulb), and in neocortical areas. We also analyzed the laterality of the signals, as well as the influence of the light and dark phases. We found that the iEEG power and coherence of the whole spectrum were largely affected by behavioral states and highly dependent on the cortical areas recorded. We also determined that there are night/day differences in power and coherence during sleep, but not in W. Finally, we observed that, during REM sleep, intra-hemispheric coherence differs between right and left hemispheres. We conclude that the iEEG dynamics are highly dependent on the cortical area and behavioral states. Moreover, there are light/dark phases disparities in the iEEG during sleep, and intra-hemispheric connectivity differs between both hemispheres during REM sleep.
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Affiliation(s)
- Alejandra Mondino
- Laboratorio de Neurobiología del Sueño, Departamento de Fisiología, Facultad de Medicina, Universidad de la República, Av. Gral. Flores 2125, Montevideo 11800, Uruguay; (A.M.); (M.C.); (J.G.); (L.O.); (S.C.-Z.); (A.C.)
- Department of Anesthesiology, University of Michigan, 7433 Medical Science Building 1, 1150 West Medical Center Drive, Ann Arbor, MI 48109-5615, USA;
| | - Matías Cavelli
- Laboratorio de Neurobiología del Sueño, Departamento de Fisiología, Facultad de Medicina, Universidad de la República, Av. Gral. Flores 2125, Montevideo 11800, Uruguay; (A.M.); (M.C.); (J.G.); (L.O.); (S.C.-Z.); (A.C.)
- Department of Psychiatry, University of Wisconsin, 6001 Research Park Blvd, Madison, WI 53719, USA
| | - Joaquín González
- Laboratorio de Neurobiología del Sueño, Departamento de Fisiología, Facultad de Medicina, Universidad de la República, Av. Gral. Flores 2125, Montevideo 11800, Uruguay; (A.M.); (M.C.); (J.G.); (L.O.); (S.C.-Z.); (A.C.)
| | - Lucía Osorio
- Laboratorio de Neurobiología del Sueño, Departamento de Fisiología, Facultad de Medicina, Universidad de la República, Av. Gral. Flores 2125, Montevideo 11800, Uruguay; (A.M.); (M.C.); (J.G.); (L.O.); (S.C.-Z.); (A.C.)
| | - Santiago Castro-Zaballa
- Laboratorio de Neurobiología del Sueño, Departamento de Fisiología, Facultad de Medicina, Universidad de la República, Av. Gral. Flores 2125, Montevideo 11800, Uruguay; (A.M.); (M.C.); (J.G.); (L.O.); (S.C.-Z.); (A.C.)
| | - Alicia Costa
- Laboratorio de Neurobiología del Sueño, Departamento de Fisiología, Facultad de Medicina, Universidad de la República, Av. Gral. Flores 2125, Montevideo 11800, Uruguay; (A.M.); (M.C.); (J.G.); (L.O.); (S.C.-Z.); (A.C.)
| | - Giancarlo Vanini
- Department of Anesthesiology, University of Michigan, 7433 Medical Science Building 1, 1150 West Medical Center Drive, Ann Arbor, MI 48109-5615, USA;
| | - Pablo Torterolo
- Laboratorio de Neurobiología del Sueño, Departamento de Fisiología, Facultad de Medicina, Universidad de la República, Av. Gral. Flores 2125, Montevideo 11800, Uruguay; (A.M.); (M.C.); (J.G.); (L.O.); (S.C.-Z.); (A.C.)
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37
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Eqlimi E, Bockstael A, De Coensel B, Schönwiesner M, Talsma D, Botteldooren D. EEG Correlates of Learning From Speech Presented in Environmental Noise. Front Psychol 2020; 11:1850. [PMID: 33250798 PMCID: PMC7676901 DOI: 10.3389/fpsyg.2020.01850] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2020] [Accepted: 07/06/2020] [Indexed: 01/07/2023] Open
Abstract
How the human brain retains relevant vocal information while suppressing irrelevant sounds is one of the ongoing challenges in cognitive neuroscience. Knowledge of the underlying mechanisms of this ability can be used to identify whether a person is distracted during listening to a target speech, especially in a learning context. This paper investigates the neural correlates of learning from the speech presented in a noisy environment using an ecologically valid learning context and electroencephalography (EEG). To this end, the following listening tasks were performed while 64-channel EEG signals were recorded: (1) attentive listening to the lectures in background sound, (2) attentive listening to the background sound presented alone, and (3) inattentive listening to the background sound. For the first task, 13 lectures of 5 min in length embedded in different types of realistic background noise were presented to participants who were asked to focus on the lectures. As background noise, multi-talker babble, continuous highway, and fluctuating traffic sounds were used. After the second task, a written exam was taken to quantify the amount of information that participants have acquired and retained from the lectures. In addition to various power spectrum-based EEG features in different frequency bands, the peak frequency and long-range temporal correlations (LRTC) of alpha-band activity were estimated. To reduce these dimensions, a principal component analysis (PCA) was applied to the different listening conditions resulting in the feature combinations that discriminate most between listening conditions and persons. Linear mixed-effect modeling was used to explain the origin of extracted principal components, showing their dependence on listening condition and type of background sound. Following this unsupervised step, a supervised analysis was performed to explain the link between the exam results and the EEG principal component scores using both linear fixed and mixed-effect modeling. Results suggest that the ability to learn from the speech presented in environmental noise can be predicted by the several components over the specific brain regions better than by knowing the background noise type. These components were linked to deterioration in attention, speech envelope following, decreased focusing during listening, cognitive prediction error, and specific inhibition mechanisms.
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Affiliation(s)
- Ehsan Eqlimi
- WAVES Research Group, Department of Information Technology, Ghent University, Ghent, Belgium
| | - Annelies Bockstael
- WAVES Research Group, Department of Information Technology, Ghent University, Ghent, Belgium.,École d'Orthophonie et d'Audiologie, Université de Montréal, Montreal, QC, Canada.,Erasmushogeschool Brussel, Brussels, Belgium
| | - Bert De Coensel
- WAVES Research Group, Department of Information Technology, Ghent University, Ghent, Belgium.,ASAsense, Bruges, Belgium
| | - Marc Schönwiesner
- Faculty of Biosciences, Pharmacy and Psychology, Institute of Biology, University of Leipzig, Leipzig, Germany.,International Laboratory for Brain, Music and Sound Research (BRAMS), Université de Montréal, Montreal, QC, Canada
| | - Durk Talsma
- Department of Experimental Psychology, Ghent University, Ghent, Belgium
| | - Dick Botteldooren
- WAVES Research Group, Department of Information Technology, Ghent University, Ghent, Belgium
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38
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Zanesco AP, King BG, Skwara AC, Saron CD. Within and between-person correlates of the temporal dynamics of resting EEG microstates. Neuroimage 2020; 211:116631. [DOI: 10.1016/j.neuroimage.2020.116631] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2019] [Revised: 12/20/2019] [Accepted: 02/10/2020] [Indexed: 10/25/2022] Open
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Kosciessa JQ, Kloosterman NA, Garrett DD. Standard multiscale entropy reflects neural dynamics at mismatched temporal scales: What's signal irregularity got to do with it? PLoS Comput Biol 2020; 16:e1007885. [PMID: 32392250 PMCID: PMC7241858 DOI: 10.1371/journal.pcbi.1007885] [Citation(s) in RCA: 33] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2020] [Revised: 05/21/2020] [Accepted: 04/18/2020] [Indexed: 01/10/2023] Open
Abstract
Multiscale Entropy (MSE) is used to characterize the temporal irregularity of neural time series patterns. Due to its' presumed sensitivity to non-linear signal characteristics, MSE is typically considered a complementary measure of brain dynamics to signal variance and spectral power. However, the divergence between these measures is often unclear in application. Furthermore, it is commonly assumed (yet sparingly verified) that entropy estimated at specific time scales reflects signal irregularity at those precise time scales of brain function. We argue that such assumptions are not tenable. Using simulated and empirical electroencephalogram (EEG) data from 47 younger and 52 older adults, we indicate strong and previously underappreciated associations between MSE and spectral power, and highlight how these links preclude traditional interpretations of MSE time scales. Specifically, we show that the typical definition of temporal patterns via "similarity bounds" biases coarse MSE scales-that are thought to reflect slow dynamics-by high-frequency dynamics. Moreover, we demonstrate that entropy at fine time scales-presumed to indicate fast dynamics-is highly sensitive to broadband spectral power, a measure dominated by low-frequency contributions. Jointly, these issues produce counterintuitive reflections of frequency-specific content on MSE time scales. We emphasize the resulting inferential problems in a conceptual replication of cross-sectional age differences at rest, in which scale-specific entropy age effects could be explained by spectral power differences at mismatched temporal scales. Furthermore, we demonstrate how such problems may be alleviated, resulting in the indication of scale-specific age differences in rhythmic irregularity. By controlling for narrowband contributions, we indicate that spontaneous alpha rhythms during eyes open rest transiently reduce broadband signal irregularity. Finally, we recommend best practices that may better permit a valid estimation and interpretation of neural signal irregularity at time scales of interest.
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Affiliation(s)
- Julian Q. Kosciessa
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, Berlin, Germany
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany
- Department of Psychology, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Niels A. Kloosterman
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, Berlin, Germany
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany
| | - Douglas D. Garrett
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, Berlin, Germany
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany
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40
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Neural oscillations in the fronto-striatal network predict vocal output in bats. PLoS Biol 2020; 18:e3000658. [PMID: 32191695 PMCID: PMC7081985 DOI: 10.1371/journal.pbio.3000658] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2019] [Accepted: 02/13/2020] [Indexed: 12/22/2022] Open
Abstract
The ability to vocalize is ubiquitous in vertebrates, but neural networks underlying vocal control remain poorly understood. Here, we performed simultaneous neuronal recordings in the frontal cortex and dorsal striatum (caudate nucleus, CN) during the production of echolocation pulses and communication calls in bats. This approach allowed us to assess the general aspects underlying vocal production in mammals and the unique evolutionary adaptations of bat echolocation. Our data indicate that before vocalization, a distinctive change in high-gamma and beta oscillations (50–80 Hz and 12–30 Hz, respectively) takes place in the bat frontal cortex and dorsal striatum. Such precise fine-tuning of neural oscillations could allow animals to selectively activate motor programs required for the production of either echolocation or communication vocalizations. Moreover, the functional coupling between frontal and striatal areas, occurring in the theta oscillatory band (4–8 Hz), differs markedly at the millisecond level, depending on whether the animals are in a navigational mode (that is, emitting echolocation pulses) or in a social communication mode (emitting communication calls). Overall, this study indicates that fronto-striatal oscillations could provide a neural correlate for vocal control in bats. In bats, rhythmic activity in frontal and striatal areas of the brain provide a neural correlate for vocal control, which can be used to predict whether the ensuing vocalizations are for echolocation or social communication.
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41
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Decomposing alpha and 1/f brain activities reveals their differential associations with cognitive processing speed. Neuroimage 2020; 205:116304. [DOI: 10.1016/j.neuroimage.2019.116304] [Citation(s) in RCA: 72] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2019] [Revised: 10/12/2019] [Accepted: 10/19/2019] [Indexed: 11/22/2022] Open
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42
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Hsu SM, Tseng CH, Hsieh CH, Hsieh CW. Slow-paced inspiration regularizes alpha phase dynamics in the human brain. J Neurophysiol 2019; 123:289-299. [PMID: 31747328 DOI: 10.1152/jn.00624.2019] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
The phase of low-frequency, rhythmic cortical activity is essential for organizing brain processes because it provides a recurrent temporal frame for information coding. However, the low-frequency cortical phase exhibits great flexibility in response to external influences. Given that brain rhythms have been found to track respiratory inputs, we hypothesized that slow breathing, commonly associated with mental regulation, could reorganize the relationship between these two rhythmic systems through the adjustment of the cortical phase to such a slow train of inputs. Based on simultaneous magnetoencephalography and respiratory measurements, we report that while participants performed paced breathing, slow relative to normal breathing modulated cortical phase activity in the alpha range across widespread brain areas. Such modulation effects were specifically locked to the middle of the inspiration stage and exhibited a well-structured pattern. At the single-subject level, the phase angles underlying the effects became more likely to be diametrically opposed across breaths, indicating unique and consistent phase adjustment to slow inspiratory inputs. Neither cardiac fluctuations nor breathing-unrelated task effects could account for the findings. We suggest that slow-paced inspiration could organize the cortical phase in a regularized phase pattern, revealing a rhythmic but dynamic neural network integrated with different neurophysiological systems through volitional control.NEW & NOTEWORTHY Breathing is more complicated than a simple gas exchange, as it is integrated with numerous cognitive and emotional functions. Controlled slow breathing has often been used to regulate mental processes. This magnetoencephalography study demonstrates that slow-paced relative to normal-paced inspiration could organize the timing of alpha rhythmic activities across breathing cycles in a structured manner over widespread brain areas. Our results reveal how a volitionally controlled change in respiratory behavior could systematically modulate cortical activity.
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Affiliation(s)
- Shen-Mou Hsu
- Imaging Center for Integrated Body, Mind and Culture Research, National Taiwan University, Taipei, Taiwan (R.O.C.).,MOST AI Biomedical Research Center, Taiwan (R.O.C.)
| | - Chih-Hsin Tseng
- Graduate Institute of Biomedical Electronic and Bioinformatics, National Taiwan University, Taipei, Taiwan (R.O.C.)
| | - Chao-Hsien Hsieh
- Imaging Center for Integrated Body, Mind and Culture Research, National Taiwan University, Taipei, Taiwan (R.O.C.).,Interdisciplinary MRI/MRS Laboratory, Department of Electrical Engineering, National Taiwan University, Taipei, Taiwan (R.O.C.)
| | - Chang-Wei Hsieh
- Department of Photonic and Communication Engineering, Asia University, Taichung, Taiwan (R.O.C.)
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43
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Pscherer C, Mückschel M, Summerer L, Bluschke A, Beste C. On the relevance of EEG resting theta activity for the neurophysiological dynamics underlying motor inhibitory control. Hum Brain Mapp 2019; 40:4253-4265. [PMID: 31219652 DOI: 10.1002/hbm.24699] [Citation(s) in RCA: 37] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2019] [Revised: 05/27/2019] [Accepted: 06/09/2019] [Indexed: 12/13/2022] Open
Abstract
The modulation of theta frequency activity plays a major role in inhibitory control processes. However, the relevance of resting theta band activity and of the ability to spontaneously modulate this resting theta activity for neural mechanisms underlying inhibitory control is elusive. Various theoretical conceptions suggest to take these aspects into consideration. In the current study, we examine whether the strength of resting theta band activity or the ability to modulate the resting state theta activity affects response inhibition. We combined EEG-time frequency decomposition and beamforming in a conflict-modulated Go/Nogo task. A sample of N = 66 healthy subjects was investigated. We show that the strength of resting state theta activity modulates the effects of conflicts during motor inhibitory control. Especially when resting theta activity was low, conflicts strongly affected response inhibition performance and total theta band activity during Nogo trials. These effects were associated with theta-related activity differences in the superior (BA7) and inferior parietal cortex (BA40). The results were very specific for total theta band activity since evoked theta activity and measures of intertrial phase coherency (phase-locking factor) were not affected. The data suggest that the strength of resting state theta activity modulates processing of a theta-related alarm or surprise signal during inhibitory control. The ability to voluntarily modulate theta band activity did not affect conflict-modulated inhibitory control. These findings have important implications for approaches aiming to optimize human cognitive control.
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Affiliation(s)
- Charlotte Pscherer
- Cognitive Neurophysiology, Department of Child and Adolescent Psychiatry, Faculty of Medicine of the TU Dresden, Dresden, Germany
| | - Moritz Mückschel
- Cognitive Neurophysiology, Department of Child and Adolescent Psychiatry, Faculty of Medicine of the TU Dresden, Dresden, Germany
| | - Lena Summerer
- Cognitive Neurophysiology, Department of Child and Adolescent Psychiatry, Faculty of Medicine of the TU Dresden, Dresden, Germany
| | - Annet Bluschke
- Cognitive Neurophysiology, Department of Child and Adolescent Psychiatry, Faculty of Medicine of the TU Dresden, Dresden, Germany
| | - Christian Beste
- Cognitive Neurophysiology, Department of Child and Adolescent Psychiatry, Faculty of Medicine of the TU Dresden, Dresden, Germany
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