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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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2
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Pi Y, Yan J, Pscherer C, Gao S, Mückschel M, Colzato L, Hommel B, Beste C. Interindividual aperiodic resting-state EEG activity predicts cognitive-control styles. Psychophysiology 2024; 61:e14576. [PMID: 38556626 DOI: 10.1111/psyp.14576] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Revised: 03/01/2024] [Accepted: 03/20/2024] [Indexed: 04/02/2024]
Abstract
The ability to find the right balance between more persistent and more flexible cognitive-control styles is known as "metacontrol." Recent findings suggest a relevance of aperiodic EEG activity and task conditions that are likely to elicit a specific metacontrol style. Here we investigated whether individual differences in aperiodic EEG activity obtained off-task (during resting state) predict individual cognitive-control styles under task conditions that pose different demands on metacontrol. We analyzed EEG resting-state data, task-EEG, and behavioral outcomes from a sample of N = 65 healthy participants performing a Go/Nogo task. We examined aperiodic activity as indicator of "neural noise" in the EEG power spectrum, and participants were assigned to a high-noise or low-noise group according to a median split of the exponents obtained for resting state. We found that off-task aperiodic exponents predicted different cognitive-control styles in Go and Nogo conditions: Overall, aperiodic exponents were higher (i.e., noise was lower) in the low-noise group, who however showed no difference between Go and Nogo trials, whereas the high-noise group exhibited significant noise reduction in the more persistence-heavy Nogo condition. This suggests that trait-like biases determine the default cognitive-control style, which however can be overwritten or compensated for under challenging task demands. We suggest that aperiodic activity in EEG signals represents valid indicators of highly dynamic arbitration between metacontrol styles, representing the brain's capability to reorganize itself and adapt its neural activity patterns to changing environmental conditions.
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Affiliation(s)
- Yu Pi
- Department of Psychology, Shandong Normal University, Jinan, China
| | - Jimin Yan
- Department of Psychology, Shandong Normal University, Jinan, China
| | - Charlotte Pscherer
- Cognitive Neurophysiology, Department of Child and Adolescent Psychiatry, Faculty of Medicine, TU Dresden, Dresden, Germany
| | - Shudan Gao
- Department of Psychology, Shandong Normal University, Jinan, China
| | - Moritz Mückschel
- Cognitive Neurophysiology, Department of Child and Adolescent Psychiatry, Faculty of Medicine, TU Dresden, Dresden, Germany
| | - Lorenza Colzato
- Department of Psychology, Shandong Normal University, Jinan, China
- Cognitive Neurophysiology, Department of Child and Adolescent Psychiatry, Faculty of Medicine, TU Dresden, Dresden, Germany
| | - Bernhard Hommel
- Department of Psychology, Shandong Normal University, Jinan, China
| | - Christian Beste
- Department of Psychology, Shandong Normal University, Jinan, China
- Cognitive Neurophysiology, Department of Child and Adolescent Psychiatry, Faculty of Medicine, TU Dresden, Dresden, Germany
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3
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Stanyard RA, Mason D, Ellis C, Dickson H, Short R, Batalle D, Arichi T. Aperiodic and Hurst EEG exponents across early human brain development: A systematic review. Dev Cogn Neurosci 2024; 68:101402. [PMID: 38917647 DOI: 10.1016/j.dcn.2024.101402] [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: 02/20/2024] [Revised: 04/12/2024] [Accepted: 06/03/2024] [Indexed: 06/27/2024] Open
Abstract
In electroencephalographic (EEG) data, power-frequency slope exponents (1/f_β) can provide non-invasive markers of in vivo neural activity excitation-inhibition (E:I) balance. E:I balance may be altered in neurodevelopmental conditions; hence, understanding how 1/fβ evolves across infancy/childhood has implications for developing early assessments/interventions. This systematic review (PROSPERO-ID: CRD42023363294) explored the early maturation (0-26 yrs) of resting-state EEG 1/f measures (aperiodic [AE], power law [PLE] and Hurst [HE] exponents), including studies containing ≥1 1/f measures and ≥10 typically developing participants. Five databases (including Embase and Scopus) were searched during March 2023. Forty-two studies were identified (Nparticipants=3478). Risk of bias was assessed using the Quality Assessment with Diverse Studies tool. Narrative synthesis of HE data suggests non-stationary EEG activity occurs throughout development. Age-related trends were complex, with rapid decreases in AEs during infancy and heterogenous changes thereafter. Regionally, AE maxima shifted developmentally, potentially reflecting spatial trends in maturing brain connectivity. This work highlights the importance of further characterising the development of 1/f measures to better understand how E:I balance shapes brain and cognitive development.
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Affiliation(s)
- R A Stanyard
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, United Kingdom; Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, United Kingdom.
| | - D Mason
- Social, Genetic, and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, United Kingdom
| | - C Ellis
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, United Kingdom
| | - H Dickson
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, United Kingdom
| | - R Short
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, United Kingdom
| | - D Batalle
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, United Kingdom; Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, United Kingdom
| | - T Arichi
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, United Kingdom; MRC Centre for Neurodevelopmental Disorders, King's College London, United Kingdom; Children's Neurosciences, Evelina London Children's Hospital, Guy's and St Thomas' NHS Foundation Trust, United Kingdom; Department of Bioengineering, Imperial College London, United Kingdom
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4
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Bonetti L, Fernández-Rubio G, Carlomagno F, Dietz M, Pantazis D, Vuust P, Kringelbach ML. Spatiotemporal brain hierarchies of auditory memory recognition and predictive coding. Nat Commun 2024; 15:4313. [PMID: 38773109 PMCID: PMC11109219 DOI: 10.1038/s41467-024-48302-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2023] [Accepted: 04/25/2024] [Indexed: 05/23/2024] Open
Abstract
Our brain is constantly extracting, predicting, and recognising key spatiotemporal features of the physical world in order to survive. While neural processing of visuospatial patterns has been extensively studied, the hierarchical brain mechanisms underlying conscious recognition of auditory sequences and the associated prediction errors remain elusive. Using magnetoencephalography (MEG), we describe the brain functioning of 83 participants during recognition of previously memorised musical sequences and systematic variations. The results show feedforward connections originating from auditory cortices, and extending to the hippocampus, anterior cingulate gyrus, and medial cingulate gyrus. Simultaneously, we observe backward connections operating in the opposite direction. Throughout the sequences, the hippocampus and cingulate gyrus maintain the same hierarchical level, except for the final tone, where the cingulate gyrus assumes the top position within the hierarchy. The evoked responses of memorised sequences and variations engage the same hierarchical brain network but systematically differ in terms of temporal dynamics, strength, and polarity. Furthermore, induced-response analysis shows that alpha and beta power is stronger for the variations, while gamma power is enhanced for the memorised sequences. This study expands on the predictive coding theory by providing quantitative evidence of hierarchical brain mechanisms during conscious memory and predictive processing of auditory sequences.
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Affiliation(s)
- L Bonetti
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University & The Royal Academy of Music, Aarhus/Aalborg, Denmark.
- Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, Oxford, United Kingdom.
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom.
- Department of Psychology, University of Bologna, Bologna, Italy.
| | - G Fernández-Rubio
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University & The Royal Academy of Music, Aarhus/Aalborg, Denmark
| | - F Carlomagno
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University & The Royal Academy of Music, Aarhus/Aalborg, Denmark
- Department of Education, Psychology, Communication, University of Bari Aldo Moro, Bari, Italy
| | - M Dietz
- Center of Functionally Integrative Neuroscience, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - D Pantazis
- McGovern Institute for Brain Research, Massachusetts Institute of Technology (MIT), Cambridge, MA, 02139, USA
| | - P Vuust
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University & The Royal Academy of Music, Aarhus/Aalborg, Denmark
| | - M L Kringelbach
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University & The Royal Academy of Music, Aarhus/Aalborg, Denmark
- Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, Oxford, United Kingdom
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom
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5
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Marder MA, Miller GA. The future of psychophysiology, then and now. Biol Psychol 2024; 189:108792. [PMID: 38588815 DOI: 10.1016/j.biopsycho.2024.108792] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Revised: 03/30/2024] [Accepted: 04/02/2024] [Indexed: 04/10/2024]
Abstract
Since its founding in 1973, Biological Psychology has showcased and provided invaluable support to psychophysiology, a field that has grown and changed enormously. This article discusses some constancies that have remained fundamental to the journal and to the field as well as some important trends. Some aspects of our science have not received due consideration, affecting not only the generalizability of our findings but the way we develop and evaluate our research questions and the potential of our field to contribute to the common good. The article offers a number of predictions and recommendations for the next period of growth of psychophysiology.
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Affiliation(s)
| | - Gregory A Miller
- University of Illinois Urbana-Champaign, USA; University of California, Los Angeles, USA
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Hu S, Zhang Z, Zhang X, Wu X, Valdes-Sosa PA. [Formula: see text]-[Formula: see text]: A Nonparametric Model for Neural Power Spectra Decomposition. IEEE J Biomed Health Inform 2024; 28:2624-2635. [PMID: 38335090 DOI: 10.1109/jbhi.2024.3364499] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/12/2024]
Abstract
The power spectra estimated from the brain recordings are the mixed representation of aperiodic transient activity and periodic oscillations, i.e., aperiodic component (AC) and periodic component (PC). Quantitative neurophysiology requires precise decomposition preceding parameterizing each component. However, the shape, statistical distribution, scale, and mixing mechanism of AC and PCs are unclear, challenging the effectiveness of current popular parametric models such as FOOOF, IRASA, BOSC, etc. Here, ξ- π was proposed to decompose the neural spectra by embedding the nonparametric spectra estimation with penalized Whittle likelihood and the shape language modeling into the expectation maximization framework. ξ- π was validated on the synthesized spectra with loss statistics and on the sleep EEG and the large sample iEEG with evaluation metrics and neurophysiological evidence. Compared to FOOOF, both the simulation presenting shape irregularities and the batch simulation with multiple isolated peaks indicated that ξ- π improved the fit of AC and PCs with less loss and higher F1-score in recognizing the centering frequencies and the number of peaks; the sleep EEG revealed that ξ- π produced more distinguishable AC exponents and improved the sleep state classification accuracy; the iEEG showed that ξ- π approached the clinical findings in peak discovery. Overall, ξ- π offered good performance in the spectra decomposition, which allows flexible parameterization using descriptive statistics or kernel functions. ξ- π is a seminal tool for brain signal decoding in fields such as cognitive neuroscience, brain-computer interface, neurofeedback, and brain diseases.
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Mendes AJ, Galdo-Álvarez S, Lema A, Carvalho S, Leite J. Transcranial Direct Current Stimulation Decreases P3 Amplitude and Inherent Delta Activity during a Waiting Impulsivity Paradigm: Crossover Study. Brain Sci 2024; 14:168. [PMID: 38391742 PMCID: PMC10887229 DOI: 10.3390/brainsci14020168] [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: 01/05/2024] [Revised: 02/05/2024] [Accepted: 02/06/2024] [Indexed: 02/24/2024] Open
Abstract
The inability to wait for a target before initiating an action (i.e., waiting impulsivity) is one of the main features of addictive behaviors. Current interventions for addiction, such as transcranial Direct Current Stimulation (tDCS), have been suggested to improve this inability. Nonetheless, the effects of tDCS on waiting impulsivity and underlying electrophysiological (EEG) markers are still not clear. Therefore, this study aimed to evaluate the effects of neuromodulation over the right inferior frontal gyrus (rIFG) on the behavior and EEG markers of reward anticipation (i.e., cue and target-P3 and underlying delta/theta power) during a premature responding task. For that, forty healthy subjects participated in two experimental sessions, where they received active and sham tDCS over the rIFG combined with EEG recording during the task. To evaluate transfer effects, participants also performed two control tasks to assess delay discounting and motor inhibition. The active tDCS decreased the cue-P3 and target-P3 amplitudes, as well as delta power during target-P3. While no tDCS effects were found for motor inhibition, active tDCS increased the discounting of future rewards when compared to sham. These findings suggest a tDCS-induced modulation of the P3 component and underlying oscillatory activity during waiting impulsivity and the discounting of future rewards.
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Affiliation(s)
- Augusto J Mendes
- Psychological Neuroscience Laboratory, CIPsi, School of Psychology, University of Minho, Campus de Gualtar, 4704-553 Braga, Portugal
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, 1205 Geneva, Switzerland
- Geneva Memory Center, Department of Rehabilitation and Geriatrics, Geneva University Hospitals, 1205 Geneva, Switzerland
| | - Santiago Galdo-Álvarez
- Laboratorio de Neurociencia Cognitiva, Departamento de Psicoloxía Clínica e Psicobioloxía, Facultade de Psicoloxía, Universidade de Santiago de Compostela, 1205 Galicia, Spain
| | - Alberto Lema
- Psychological Neuroscience Laboratory, CIPsi, School of Psychology, University of Minho, Campus de Gualtar, 4704-553 Braga, Portugal
| | - Sandra Carvalho
- Department of Education and Psychology, William James Center for Research (WJCR), University of Aveiro, Campus Universitário de Santiago, 3810-193 Aveiro, Portugal
- CINTESIS@RISE, Center for Health Technology and Services Research at the Associate Laboratory RISE-Health Research Network, Department of Education and Psychology, University of Aveiro, 3810-193 Aveiro, Portugal
| | - Jorge Leite
- CINTESIS@RISE, CINTESIS.UPT, Portucalense University, 4200-072 Porto, Portugal
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Elhamiasl M, Sanches Braga Figueira J, Barry-Anwar R, Pestana Z, Keil A, Scott LS. The emergence of the EEG dominant rhythm across the first year of life. Cereb Cortex 2024; 34:bhad425. [PMID: 37955646 DOI: 10.1093/cercor/bhad425] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2023] [Revised: 10/05/2023] [Accepted: 10/06/2023] [Indexed: 11/14/2023] Open
Abstract
The spectral composition of EEG provides important information on the function of the developing brain. For example, the frequency of the dominant rhythm, a salient features of EEG data, increases from infancy to adulthood. Changes of the dominant rhythm during infancy are yet to be fully characterized, in terms of their developmental trajectory and spectral characteristics. In this study, the development of dominant rhythm frequency was examined during a novel sustained attention task across 6-month-old (n = 39), 9-month-old (n = 30), and 12-month-old (n = 28) infants. During this task, computer-generated objects and faces floated down a computer screen for 10 s after a 5-second fixation cross. The peak frequency in the range between 5 and 9 Hz was calculated using center of gravity (CoG) and examined in response to faces and objects. Results indicated that peak frequency increased from 6 to 9 to 12 months of age in face and object conditions. We replicated the same result for the baseline. There was high reliability between the CoGs in the face, object, and baseline conditions across all channels. The developmental increase in CoG was more reliable than measures of mode frequency across different conditions. These findings suggest that CoG is a robust index of brain development across infancy.
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Affiliation(s)
- Mina Elhamiasl
- Department of Psychology, University of Florida, Gainesville, FL 32611, United States
| | | | - Ryan Barry-Anwar
- Department of Psychology, University of Florida, Gainesville, FL 32611, United States
| | - Zoe Pestana
- Department of Psychology, University of California, Davis, CA 95616, United States
| | - Andreas Keil
- Department of Psychology, University of Florida, Gainesville, FL 32611, United States
| | - Lisa S Scott
- Department of Psychology, University of Florida, Gainesville, FL 32611, United States
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Ke Y, Wang T, He F, Liu S, Ming D. Enhancing EEG-based cross-day mental workload classification using periodic component of power spectrum. J Neural Eng 2023; 20:066028. [PMID: 37995362 DOI: 10.1088/1741-2552/ad0f3d] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Accepted: 11/23/2023] [Indexed: 11/25/2023]
Abstract
Objective. The day-to-day variability of electroencephalogram (EEG) poses a significant challenge to decode human brain activity in EEG-based passive brain-computer interfaces (pBCIs). Conventionally, a time-consuming calibration process is required to collect data from users on a new day to ensure the performance of the machine learning-based decoding model, which hinders the application of pBCIs to monitor mental workload (MWL) states in real-world settings.Approach. This study investigated the day-to-day stability of the raw power spectral density (PSD) and their periodic and aperiodic components decomposed by the Fitting Oscillations and One-Over-F algorithm. In addition, we validated the feasibility of using periodic components to improve cross-day MWL classification performance.Main results. Compared to the raw PSD (69.9% ± 18.5%) and the aperiodic component (69.4% ± 19.2%), the periodic component had better day-to-day stability and significantly higher cross-day classification accuracy (84.2% ± 11.0%).Significance. These findings indicate that periodic components of EEG have the potential to be applied in decoding brain states for more robust pBCIs.
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Affiliation(s)
- Yufeng Ke
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, People's Republic of China
- Haihe Laboratory of Brain-computer Interaction and Human-machine Integration, Tianjin, People's Republic of China
| | - Tao Wang
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, People's Republic of China
- Haihe Laboratory of Brain-computer Interaction and Human-machine Integration, Tianjin, People's Republic of China
| | - Feng He
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, People's Republic of China
- Haihe Laboratory of Brain-computer Interaction and Human-machine Integration, Tianjin, People's Republic of China
| | - Shuang Liu
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, People's Republic of China
- Haihe Laboratory of Brain-computer Interaction and Human-machine Integration, Tianjin, People's Republic of China
| | - Dong Ming
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, People's Republic of China
- Haihe Laboratory of Brain-computer Interaction and Human-machine Integration, Tianjin, People's Republic of China
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10
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Thornberry C, Caffrey M, Commins S. Theta oscillatory power decreases in humans are associated with spatial learning in a virtual water maze task. Eur J Neurosci 2023; 58:4341-4356. [PMID: 37957526 DOI: 10.1111/ejn.16185] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Accepted: 10/20/2023] [Indexed: 11/15/2023]
Abstract
Theta oscillations (4-8 Hz) in humans play a role in navigation processes, including spatial encoding, retrieval and sensorimotor integration. Increased theta power at frontal and parietal midline regions is known to contribute to successful navigation. However, the dynamics of cortical theta and its role in spatial learning are not fully understood. This study aimed to investigate theta oscillations via electroencephalogram (EEG) during spatial learning in a virtual water maze. Participants were separated into a learning group (n = 25) who learned the location of a hidden goal across 12 trials, or a time-matched non-learning group (n = 25) who were required to simply navigate the same arena, but without a goal. We compared all trials, at two phases of learning, the trial start and the goal approach. We also compared the first six trials with the last six trials within-groups. The learning group showed reduced low-frequency theta power at the frontal and parietal midline during the start phase and largely reduced theta combined with a short increase at both midlines during the goal-approach phase. These patterns were not found in the non-learning group, who instead displayed extensive increases in low-frequency oscillations at both regions during the trial start and at the parietal midline during goal approach. Our results support the theory that theta plays a crucial role in spatial encoding during exploration, as opposed to sensorimotor integration. We suggest our findings provide evidence for a link between learning and a reduction of theta oscillations in humans.
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Affiliation(s)
- Conor Thornberry
- Department of Psychology, Maynooth University, Maynooth, Ireland
| | - Michelle Caffrey
- Department of Psychology, Maynooth University, Maynooth, Ireland
| | - Sean Commins
- Department of Psychology, Maynooth University, Maynooth, Ireland
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11
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Berwal D, Telkes I, Agarwal S, Paniccioli S, McCarthy K, DiMarzio M, McLaughlin B, Pilitsis JG. Investigation of the intraoperative cortical responses to spinal motor mapping in a patient with chronic pain. J Neurophysiol 2023; 130:768-774. [PMID: 37609700 PMCID: PMC10649839 DOI: 10.1152/jn.00221.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2023] [Revised: 08/02/2023] [Accepted: 08/15/2023] [Indexed: 08/24/2023] Open
Abstract
Intraoperative neurophysiological monitoring (IONM) in spinal cord stimulation (SCS) surgery for chronic pain is shown to provide effective guidance during device placement. Electromyography (EMG) is used to determine the laterality of the paddle. In some SCS cases, laterality cannot be obtained via EMG due to patient physiology. Electroencephalography (EEG) is already used in IONM to monitor cortical responses. Here, we show proof-of-concept of assessing the responses of epidurally evoked EMGs simultaneously with EEGs to determine laterality during IONM using a high-resolution (HR) SCS paddle. An 8-column HR-SCS paddle was acutely placed at T9-T10 interspace in patients with failed back surgery syndrome. EMG signals from 18 muscle groups were recorded simultaneously with 60-channel EEG signals at various stimulation amplitudes (0-10 mA). Particular attention was paid to regions associated with pain including the somatosensory cortex (S1), prefrontal cortex (PFC), and motor cortex (M1). When left and right lateral contacts were stimulated at low amplitudes (1-2 mA), significant changes were seen in θ, α, and β powers in the contralateral PFC but not in M1 or S1. There was a significant correlation between M1 and contralateral contacts in α power. At higher currents (7-8 mA), right-sided contacts resulted in α power change. We found significant differences in α, θ, and β powers in PFC for contralateral stimulation of the lateral SCS contacts at low amplitudes and in α power at higher amplitudes. The changes in PFC suggest the potential of EEG for understanding a cortical mechanism of action of SCS and provide insight into the pathophysiology of chronic pain.NEW & NOTEWORTHY Here, we present proof of concept of assessing the responses of epidurally evoked electromyography simultaneously with scalp electroencephalography to determine whether both laterality and insights into pain mechanisms can be elucidated. With stimulation, significant changes were seen in θ, α, and β band power in the contralateral prefrontal cortex and in α power in the motor cortex. We provide insight into the mechanism of action of SCS in preventing pain in this patient.
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Affiliation(s)
- Deepak Berwal
- Charles E. Schmidt College of Medicine, Florida Atlantic University, Boca Raton, Florida, United States
| | - Ilknur Telkes
- Charles E. Schmidt College of Medicine, Florida Atlantic University, Boca Raton, Florida, United States
| | - Shruti Agarwal
- Charles E. Schmidt College of Medicine, Florida Atlantic University, Boca Raton, Florida, United States
| | | | - Kevin McCarthy
- Nuvasive Clinical Services, San Diego, California, United States
| | - Marisa DiMarzio
- Charles E. Schmidt College of Medicine, Florida Atlantic University, Boca Raton, Florida, United States
- Department of Neuroscience and Experimental Therapeutics, Albany Medical College, Albany, New York, United States
| | | | - Julie G Pilitsis
- Charles E. Schmidt College of Medicine, Florida Atlantic University, Boca Raton, Florida, United States
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Pant R, Ossandón J, Stange L, Shareef I, Kekunnaya R, Röder B. Stimulus-evoked and resting-state alpha oscillations show a linked dependence on patterned visual experience for development. Neuroimage Clin 2023; 38:103375. [PMID: 36963312 PMCID: PMC10064270 DOI: 10.1016/j.nicl.2023.103375] [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: 11/26/2022] [Revised: 03/07/2023] [Accepted: 03/09/2023] [Indexed: 03/16/2023]
Abstract
Persistent visual impairments after congenital blindness due to dense bilateral cataracts have been attributed to altered visual cortex development within a sensitive period. Occipital alpha (8-14 Hz) oscillations were found to be reduced after congenital cataract reversal, while participants performed visual motion tasks. However, it has been unclear whether reduced alpha oscillations were task-specific, or linked to impaired visual behavior in cataract-reversed individuals. Here, we compared resting-state and stimulus-evoked alpha activity between individuals who had been treated for dense bilateral congenital cataracts (CC, n = 13, mean duration of blindness = 11.0 years) and age-matched, normally sighted individuals (SC, n = 13). We employed the visual impulse response function, adapted from VanRullen and MacDonald (2012), to test for the characteristic alpha response to visual white noise. Participants observed white noise stimuli changing in luminance with equal power at frequencies between 0 and 30 Hz. Compared to SC individuals, CC individuals demonstrated a reduced likelihood of exhibiting an evoked alpha response. Moreover, stimulus-evoked alpha power was reduced and correlated with a corresponding reduction of resting-state alpha power in the same CC individuals. Finally, CC individuals with an above-threshold evoked alpha peak had better visual acuity than CC individual without an evoked alpha peak. Since alpha oscillations have been linked to feedback communication, we suggest that the concurrent impairment in resting-state and stimulus-evoked alpha oscillations indicates an altered interaction of top-down and bottom-up processing in the visual hierarchy, which likely contributes to incomplete behavioral recovery in individuals who experienced transient congenital blindness.
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Affiliation(s)
- Rashi Pant
- Biological Psychology and Neuropsychology, University of Hamburg, Von-Melle-Park 11, 20146 Hamburg, Germany.
| | - José Ossandón
- Biological Psychology and Neuropsychology, University of Hamburg, Von-Melle-Park 11, 20146 Hamburg, Germany
| | - Liesa Stange
- Biological Psychology and Neuropsychology, University of Hamburg, Von-Melle-Park 11, 20146 Hamburg, Germany
| | - Idris Shareef
- Jasti V Ramanamma Children's Eye Care Center, Child Sight Institute, LV Prasad Eye Institute, 500034 Hyderabad, India; Department of Psychology, University of Nevada, 1664 N Virginia St, Reno, NV 89557, United States
| | - Ramesh Kekunnaya
- Jasti V Ramanamma Children's Eye Care Center, Child Sight Institute, LV Prasad Eye Institute, 500034 Hyderabad, India
| | - Brigitte Röder
- Biological Psychology and Neuropsychology, University of Hamburg, Von-Melle-Park 11, 20146 Hamburg, Germany
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13
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Gyurkovics M, Clements GM, Low KA, Fabiani M, Gratton G. Stimulus-Induced Changes in 1/ f-like Background Activity in EEG. J Neurosci 2022; 42:7144-7151. [PMID: 35970561 PMCID: PMC9480870 DOI: 10.1523/jneurosci.0414-22.2022] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2022] [Revised: 07/20/2022] [Accepted: 08/01/2022] [Indexed: 11/21/2022] Open
Abstract
Research into the nature of 1/f-like, nonoscillatory electrophysiological activity has grown exponentially in recent years in cognitive neuroscience. The shape of this activity has been linked to the balance between excitatory and inhibitory neural circuits, which is thought to be important for information processing. However, to date, it is not known whether the presentation of a stimulus induces changes in the parameters of 1/f activity in scalp recordings, separable from event-related potentials (ERPs). Here, we analyzed event-related broadband changes in human EEG both before and after removing ERPs to demonstrate their confounding effect, and to establish whether there are genuine stimulus-induced changes in 1/f Using data from a passive and an active auditory task (n = 23, 61% female), we found that the shape of the post-event spectra between 2 and 25 Hz differed significantly from the pre-event spectra even after removing the frequency-content of ERPs. Further, a significant portion of this difference could be accounted for by a rotational shift in 1/f activity, manifesting as an increase in low and a decrease in high frequencies. Importantly, the magnitude of this rotational shift was related to the attentional demands of the task. This change in 1/f is consistent with increased inhibition following stimulus onset, and likely reflects a disruption of ongoing excitatory activity proportional to processing demands. Finally, these findings contradict the central assumption of baseline normalization strategies in time-frequency analyses, namely, that background EEG activity is stationary across time. As such, they have far-reaching consequences relevant for several subfields of neuroscience.SIGNIFICANCE STATEMENT Interest in the functional role of the 1/f-like background brain activity has been growing exponentially in neuroscience. Yet, no study to date has demonstrated a clear relationship between information processing and 1/f activity by investigating event-related effects on its parameters in noninvasive recordings of neural activity. Here, we demonstrate, for the first time, that stimuli induce rotational changes in 1/f activity, detectable at lower frequencies and independent from the occurrence of event-related potentials. These findings suggest the presence of large-scale inhibition following stimulus onset, largest when the stimulus is novel, and indicate that the assumption of stationary background activity in the analysis of neural oscillations is untenable. These results have far-reaching consequences that cut across several subfields of neuroscience.
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Affiliation(s)
- Máté Gyurkovics
- Beckman Institute, University of Illinois at Urbana-Champaign, Urbana-Champaign, Illinois 61801
| | - Grace M Clements
- Beckman Institute, University of Illinois at Urbana-Champaign, Urbana-Champaign, Illinois 61801
- Psychology Department, University of Illinois at Urbana-Champaign, Urbana-Champaign, Illinois 61820
| | - Kathy A Low
- Beckman Institute, University of Illinois at Urbana-Champaign, Urbana-Champaign, Illinois 61801
| | - Monica Fabiani
- Beckman Institute, University of Illinois at Urbana-Champaign, Urbana-Champaign, Illinois 61801
- Psychology Department, University of Illinois at Urbana-Champaign, Urbana-Champaign, Illinois 61820
| | - Gabriele Gratton
- Beckman Institute, University of Illinois at Urbana-Champaign, Urbana-Champaign, Illinois 61801
- Psychology Department, University of Illinois at Urbana-Champaign, Urbana-Champaign, Illinois 61820
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14
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Manyukhina VO, Prokofyev AO, Galuta IA, Goiaeva DE, Obukhova TS, Schneiderman JF, Altukhov DI, Stroganova TA, Orekhova EV. Globally elevated excitation-inhibition ratio in children with autism spectrum disorder and below-average intelligence. Mol Autism 2022; 13:20. [PMID: 35550191 PMCID: PMC9102291 DOI: 10.1186/s13229-022-00498-2] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2021] [Accepted: 04/25/2022] [Indexed: 12/04/2022] Open
Abstract
Background Altered neuronal excitation–inhibition (E–I) balance is strongly implicated in ASD. However, it is not known whether the direction and degree of changes in the E–I ratio in individuals with ASD correlates with intellectual disability often associated with this developmental disorder. The spectral slope of the aperiodic 1/f activity reflects the E–I balance at the scale of large neuronal populations and may uncover its putative alternations in individuals with ASD with and without intellectual disability. Methods Herein, we used magnetoencephalography (MEG) to test whether the 1/f slope would differentiate ASD children with average and below–average (< 85) IQ. MEG was recorded at rest with eyes open/closed in 49 boys with ASD aged 6–15 years with IQ ranging from 54 to 128, and in 49 age-matched typically developing (TD) boys. The cortical source activity was estimated using the beamformer approach and individual brain models. We then extracted the 1/f slope by fitting a linear function to the log–log-scale power spectra in the high-frequency range. Results The global 1/f slope averaged over all cortical sources demonstrated high rank-order stability between the two conditions. Consistent with previous research, it was steeper in the eyes-closed than in the eyes-open condition and flattened with age. Regardless of condition, children with ASD and below-average IQ had flatter slopes than either TD or ASD children with average or above-average IQ. These group differences could not be explained by differences in signal-to-noise ratio or periodic (alpha and beta) activity. Limitations Further research is needed to find out whether the observed changes in E–I ratios are characteristic of children with below-average IQ of other diagnostic groups. Conclusions The atypically flattened spectral slope of aperiodic activity in children with ASD and below-average IQ suggests a shift of the global E–I balance toward hyper-excitation. The spectral slope can provide an accessible noninvasive biomarker of the E–I ratio for making objective judgments about treatment effectiveness in people with ASD and comorbid intellectual disability. Supplementary Information The online version contains supplementary material available at 10.1186/s13229-022-00498-2.
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Affiliation(s)
- Viktoriya O Manyukhina
- Center for Neurocognitive Research (MEG Center), Moscow State University of Psychology and Education, Moscow, Russian Federation.,Department of Psychology, National Research University Higher School of Economics, Moscow, Russian Federation
| | - Andrey O Prokofyev
- Center for Neurocognitive Research (MEG Center), Moscow State University of Psychology and Education, Moscow, Russian Federation
| | - Ilia A Galuta
- Center for Neurocognitive Research (MEG Center), Moscow State University of Psychology and Education, Moscow, Russian Federation
| | - Dzerassa E Goiaeva
- Center for Neurocognitive Research (MEG Center), Moscow State University of Psychology and Education, Moscow, Russian Federation
| | - Tatiana S Obukhova
- Center for Neurocognitive Research (MEG Center), Moscow State University of Psychology and Education, Moscow, Russian Federation
| | - Justin F Schneiderman
- MedTech West and the Institute of Neuroscience and Physiology, Sahlgrenska Academy, The University of Gothenburg, Gothenburg, Sweden
| | - Dmitrii I Altukhov
- Department of Psychology, National Research University Higher School of Economics, Moscow, Russian Federation
| | - Tatiana A Stroganova
- Center for Neurocognitive Research (MEG Center), Moscow State University of Psychology and Education, Moscow, Russian Federation
| | - Elena V Orekhova
- Center for Neurocognitive Research (MEG Center), Moscow State University of Psychology and Education, Moscow, Russian Federation.
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15
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Keil A, Bernat EM, Cohen MX, Ding M, Fabiani M, Gratton G, Kappenman ES, Maris E, Mathewson KE, Ward RT, Weisz N. Recommendations and publication guidelines for studies using frequency domain and time-frequency domain analyses of neural time series. Psychophysiology 2022; 59:e14052. [PMID: 35398913 PMCID: PMC9717489 DOI: 10.1111/psyp.14052] [Citation(s) in RCA: 28] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2022] [Accepted: 03/08/2022] [Indexed: 01/29/2023]
Abstract
Since its beginnings in the early 20th century, the psychophysiological study of human brain function has included research into the spectral properties of electrical and magnetic brain signals. Now, dramatic advances in digital signal processing, biophysics, and computer science have enabled increasingly sophisticated methodology for neural time series analysis. Innovations in hardware and recording techniques have further expanded the range of tools available to researchers interested in measuring, quantifying, modeling, and altering the spectral properties of neural time series. These tools are increasingly used in the field, by a growing number of researchers who vary in their training, background, and research interests. Implementation and reporting standards also vary greatly in the published literature, causing challenges for authors, readers, reviewers, and editors alike. The present report addresses this issue by providing recommendations for the use of these methods, with a focus on foundational aspects of frequency domain and time-frequency analyses. It also provides publication guidelines, which aim to (1) foster replication and scientific rigor, (2) assist new researchers who wish to enter the field of brain oscillations, and (3) facilitate communication among authors, reviewers, and editors.
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Affiliation(s)
- Andreas Keil
- Department and Psychology and Center for the Study of Emotion and Attention, University of Florida, Gainesville, Florida, USA
| | - Edward M. Bernat
- Department of Psychology, University of Maryland, College Park, Maryland, USA
| | - Michael X. Cohen
- Radboud University and University Medical Center, Nijmegen, the Netherlands
| | - Mingzhou Ding
- J Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, Florida, USA
| | - Monica Fabiani
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA,Psychology Department, University of Illinois at Urbana-Champaign, Champaign, Illinois, USA
| | - Gabriele Gratton
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA,Psychology Department, University of Illinois at Urbana-Champaign, Champaign, Illinois, USA
| | - Emily S. Kappenman
- Department of Psychology, San Diego State University, San Diego, California, USA
| | - Eric Maris
- Donders Institute for Brain, Cognition, and Behaviour & Faculty of Social Sciences Radboud University, Nijmegen, the Netherlands
| | - Kyle E. Mathewson
- Department of Psychology, Faculty of Science, University of Alberta, Edmonton, Alberta, Canada
| | - Richard T. Ward
- Department and Psychology and Center for the Study of Emotion and Attention, University of Florida, Gainesville, Florida, USA
| | - Nathan Weisz
- Psychology, University of Salzburg, Salzburg, Austria,Neuroscience Institute, Christian Doppler University Hospital, Paracelsus Medical University, Salzburg, Austria
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16
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Weisz N, Keil A. Introduction to the special issue of human oscillatory brain activity: Methods, models, and mechanisms. Psychophysiology 2022; 59:e14038. [DOI: 10.1111/psyp.14038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Accepted: 02/17/2022] [Indexed: 11/29/2022]
Affiliation(s)
- Nathan Weisz
- Department of Psychology University of Salzburg Salzburg Austria
- Neuroscience Institute Christian Doppler University Hospital, Paracelsus Medical University Salzburg Austria
| | - Andreas Keil
- Department of Psychology, Center for the Study of Emotion and Attention University of Florida Gainesville Florida USA
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17
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Chevalier N, Hadley LV, Balthrop K. Midfrontal theta oscillations and conflict monitoring in children and adults. Dev Psychobiol 2021; 63:e22216. [PMID: 34813101 DOI: 10.1002/dev.22216] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2021] [Revised: 09/28/2021] [Accepted: 10/30/2021] [Indexed: 12/31/2022]
Abstract
Conflict monitoring is central in cognitive control, as detection of conflict serves as a signal for the need to engage control. This study examined whether (1) midfrontal theta oscillations similarly support conflict monitoring in children and adults, and (2) performance monitoring difficulty influences conflict monitoring and resolution. Children (n = 25) and adults (n = 24) completed a flanker task with fair or rigged response feedback. Relative to adults, children showed a smaller congruency effect on midfrontal theta power, overall lower midfrontal theta power and coherence, and (unlike adults) no correlation between midfrontal theta power and N2 amplitude, suggesting that reduced neural communication efficiency contributes to less efficient conflict monitoring in children than adults. In both age groups, response feedback fairness affected response times and the P3, but neither midfrontal theta oscillations nor the N2, indicating that performance monitoring difficulty influenced conflict resolution but not conflict monitoring.
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Affiliation(s)
| | - Lauren V Hadley
- Hearing Sciences-Scottish Section, Glasgow Royal Infirmary, University of Nottingham, Glasgow, UK
| | - Kullen Balthrop
- University Counseling Services, Murray State University, Murray, Kentucky, USA
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