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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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2
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Kramer MA, Chu CJ. A General, Noise-Driven Mechanism for the 1/f-Like Behavior of Neural Field Spectra. Neural Comput 2024; 36:1643-1668. [PMID: 39028955 DOI: 10.1162/neco_a_01682] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2023] [Accepted: 03/25/2024] [Indexed: 07/21/2024]
Abstract
Consistent observations across recording modalities, experiments, and neural systems find neural field spectra with 1/f-like scaling, eliciting many alternative theories to explain this universal phenomenon. We show that a general dynamical system with stochastic drive and minimal assumptions generates 1/f-like spectra consistent with the range of values observed in vivo without requiring a specific biological mechanism or collective critical behavior.
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Affiliation(s)
- Mark A Kramer
- Department of Mathematics and Statistics, and Center for Systems Neuroscience, Boston University, Boston, MA 02214, U.S.A.
| | - Catherine J Chu
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, U.S.A.
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3
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Takacs A, Toth‐Faber E, Schubert L, Tarnok Z, Ghorbani F, Trelenberg M, Nemeth D, Münchau A, Beste C. Neural representations of statistical and rule-based predictions in Gilles de la Tourette syndrome. Hum Brain Mapp 2024; 45:e26719. [PMID: 38826009 PMCID: PMC11144952 DOI: 10.1002/hbm.26719] [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: 12/08/2023] [Revised: 04/11/2024] [Accepted: 05/06/2024] [Indexed: 06/04/2024] Open
Abstract
Gilles de la Tourette syndrome (GTS) is a disorder characterised by motor and vocal tics, which may represent habitual actions as a result of enhanced learning of associations between stimuli and responses (S-R). In this study, we investigated how adults with GTS and healthy controls (HC) learn two types of regularities in a sequence: statistics (non-adjacent probabilities) and rules (predefined order). Participants completed a visuomotor sequence learning task while EEG was recorded. To understand the neurophysiological underpinnings of these regularities in GTS, multivariate pattern analyses on the temporally decomposed EEG signal as well as sLORETA source localisation method were conducted. We found that people with GTS showed superior statistical learning but comparable rule-based learning compared to HC participants. Adults with GTS had different neural representations for both statistics and rules than HC adults; specifically, adults with GTS maintained the regularity representations longer and had more overlap between them than HCs. Moreover, over different time scales, distinct fronto-parietal structures contribute to statistical learning in the GTS and HC groups. We propose that hyper-learning in GTS is a consequence of the altered sensitivity to encode complex statistics, which might lead to habitual actions.
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Affiliation(s)
- Adam Takacs
- Cognitive Neurophysiology, Department of Child and Adolescent Psychiatry, Faculty of MedicineTechnische Universität DresdenDresdenGermany
- University Neuropsychology Center, Faculty of Medicine, Technische Universität DresdenDresdenGermany
| | - Eszter Toth‐Faber
- Institute of PsychologyELTE Eötvös Loránd UniversityBudapestHungary
- Brain, Memory and Language Research Group, Institute of Cognitive Neuroscience and Psychology, HUN‐REN Research Centre for Natural SciencesBudapestHungary
| | - Lina Schubert
- Institute of Systems Motor ScienceUniversity of LübeckLübeckGermany
| | - Zsanett Tarnok
- Vadaskert Child and Adolescent Psychiatry Hospital and Outpatient ClinicBudapestHungary
| | - Foroogh Ghorbani
- Cognitive Neurophysiology, Department of Child and Adolescent Psychiatry, Faculty of MedicineTechnische Universität DresdenDresdenGermany
- University Neuropsychology Center, Faculty of Medicine, Technische Universität DresdenDresdenGermany
| | - Madita Trelenberg
- Cognitive Neurophysiology, Department of Child and Adolescent Psychiatry, Faculty of MedicineTechnische Universität DresdenDresdenGermany
| | - Dezso Nemeth
- INSERMUniversité Claude Bernard Lyon 1, CNRS, Centre de Recherche en Neurosciences de Lyon CRNL U1028 UMR5292BronFrance
- NAP Research Group, Institute of Psychology, Eötvös Loránd University and Institute of Cognitive Neuroscience and Psychology, HUN‐REN Research Centre for Natural SciencesBudapestHungary
- Department of Education and Psychology, Faculty of Social SciencesUniversity of Atlántico MedioLas Palmas de Gran CanariaSpain
| | | | - Christian Beste
- Cognitive Neurophysiology, Department of Child and Adolescent Psychiatry, Faculty of MedicineTechnische Universität DresdenDresdenGermany
- University Neuropsychology Center, Faculty of Medicine, Technische Universität DresdenDresdenGermany
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4
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Kurvits L, Stenner MP, Guo S, Neumann WJ, Haggard P, Ganos C. Rapid Compensation for Noisy Voluntary Movements in Adults with Primary Tic Disorders. Mov Disord 2024; 39:955-964. [PMID: 38661451 DOI: 10.1002/mds.29775] [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: 10/21/2023] [Revised: 01/17/2024] [Accepted: 02/22/2024] [Indexed: 04/26/2024] Open
Abstract
BACKGROUND It has been proposed that tics and premonitory urges in primary tic disorders (PTD), like Tourette syndrome, are a manifestation of sensorimotor noise. However, patients with tics show no obvious movement imprecision in everyday life. One reason could be that patients have strategies to compensate for noise that disrupts performance (ie, noise that is task-relevant). OBJECTIVES Our goal was to unmask effects of elevated sensorimotor noise on the variability of voluntary movements in patients with PTD. METHODS We tested 30 adult patients with PTD (23 male) and 30 matched controls in a reaching task designed to unmask latent noise. Subjects reached to targets whose shape allowed for variability either in movement direction or extent. This enabled us to decompose variability into task-relevant versus less task-relevant components, where the latter should be less affected by compensatory strategies than the former. In alternating blocks, the task-relevant target dimension switched, allowing us to explore the temporal dynamics with which participants adjusted movement variability to changes in task demands. RESULTS Both groups accurately reached to targets, and adjusted movement precision based on target shape. However, when task-relevant dimensions of the target changed, patients initially produced movements that were more variable than controls, before regaining precision after several reaches. This effect persisted across repeated changes in the task-relevant dimension across the experiment, and therefore did not reflect an effect of novelty, or differences in learning. CONCLUSIONS Our results suggest that patients with PTD generate noisier voluntary movements compared with controls, but rapidly compensate according to current task demands. © 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Lille Kurvits
- Department of Neurology, University Medical Center Göttingen, Göttingen, Germany
- Department of Neurology, Charité University Hospital, Berlin, Germany
| | - Max-Philipp Stenner
- Department of Neurology, University Hospital Magdeburg, Magdeburg, Germany
- Department of Behavioral Neurology, Leibniz Institute for Neurobiology, Magdeburg, Germany
- Center for Behavioral Brain Sciences, Magdeburg, Germany
- Center for Intervention and Research on Adaptive and Maladaptive Brain Circuits Underlying Mental Health, Jena-Magdeburg-Halle, Germany
| | - Siqi Guo
- Department of Neurology, Charité University Hospital, Berlin, Germany
| | | | - Patrick Haggard
- Institute of Cognitive Neuroscience, University College London, London, UK
| | - Christos Ganos
- Department of Neurology, Charité University Hospital, Berlin, Germany
- Movement Disorder Clinic, Edmond J. Safra Program in Parkinson's Disease, Division of Neurology, University of Toronto, Toronto Western Hospital, Toronto, Ontario, Canada
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5
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Jia S, Liu D, Song W, Beste C, Colzato L, Hommel B. Tracing conflict-induced cognitive-control adjustments over time using aperiodic EEG activity. Cereb Cortex 2024; 34:bhae185. [PMID: 38771238 DOI: 10.1093/cercor/bhae185] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2024] [Revised: 04/10/2024] [Accepted: 04/11/2024] [Indexed: 05/22/2024] Open
Abstract
Cognitive-control theories assume that the experience of response conflict can trigger control adjustments. However, while some approaches focus on adjustments that impact the selection of the present response (in trial N), other approaches focus on adjustments in the next upcoming trial (N + 1). We aimed to trace control adjustments over time by quantifying cortical noise by means of the fitting oscillations and one over f algorithm, a measure of aperiodic activity. As predicted, conflict trials increased the aperiodic exponent in a large sample of 171 healthy adults, thus indicating noise reduction. While this adjustment was visible in trial N already, it did not affect response selection before the next trial. This suggests that control adjustments do not affect ongoing response-selection processes but prepare the system for tighter control in the next trial. We interpret the findings in terms of a conflict-induced switch from metacontrol flexibility to metacontrol persistence, accompanied or even implemented by a reduction of cortical noise.
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Affiliation(s)
- Shiwei Jia
- School of Psychology, Shandong Normal University, No. 88 East Wenhua Road, Jinan, 250014 Shandong Province, China
| | - Dandan Liu
- School of Psychology, Shandong Normal University, No. 88 East Wenhua Road, Jinan, 250014 Shandong Province, China
| | - Wenqi Song
- School of Psychology, Shandong Normal University, No. 88 East Wenhua Road, Jinan, 250014 Shandong Province, China
| | - Christian Beste
- School of Psychology, Shandong Normal University, No. 88 East Wenhua Road, Jinan, 250014 Shandong Province, China
- Cognitive Neurophysiology, Department of Child and Adolescent Psychiatry, Faculty of Medicine, Technische Universitaet Dresden, Schubertstrasse 42, 01309 Dresden, Germany
| | - Lorenza Colzato
- School of Psychology, Shandong Normal University, No. 88 East Wenhua Road, Jinan, 250014 Shandong Province, China
| | - Bernhard Hommel
- School of Psychology, Shandong Normal University, No. 88 East Wenhua Road, Jinan, 250014 Shandong Province, China
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6
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Chung H, Wilkinson CL, Job Said A, Tager-Flusberg H, Nelson CA. Evaluating early EEG correlates of restricted and repetitive behaviors for toddlers with or without autism. RESEARCH SQUARE 2024:rs.3.rs-3871138. [PMID: 38313269 PMCID: PMC10836096 DOI: 10.21203/rs.3.rs-3871138/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/06/2024]
Abstract
Background Restricted and repetitive behaviors (RRB) are among the primary characteristics of autism spectrum disorder (ASD). Despite the potential impact on later developmental outcomes, our understanding of the neural underpinnings of RRBs is limited. Alterations in EEG alpha activity have been observed in ASD and implicated in RRBs, however, developmental changes within the alpha band requires careful methodological considerations when studying its role in brain-behavior relationships during infancy and early childhood. Novel approaches now enable the parameterization of the power spectrum into periodic and aperiodic components. This study aimed to characterize the neural correlates of RRBs in infancy by (1) comparing infant resting-state measures (periodic alpha and aperiodic activity) between infants who develop ASD, elevated likelihood infants without ASD, and low likelihood infants without ASD, and (2) evaluate whether these infant EEG measures are associated with frequency of RRBs measured at 24 months. Methods Baseline non-task related EEG data were collected from 12-to-14-month-old infants with and without elevated likelihood of autism (N=160), and periodic alpha activity (periodic alpha power, individual peak alpha frequency and amplitude), and aperiodic activity measures (aperiodic exponent) were calculated. Parent-reported RRBs were obtained at 24 months using the Repetitive Behavior Scale-Revised questionnaire. Group differences in EEG measures were evaluated using ANCOVA, and multiple linear regressions were conducted to assess relationships between EEG and RRB measures. Results No group-level differences in infant EEG measures were observed. Marginal effects analysis of linear regressions revealed significant associations within the ASD group, such that higher periodic alpha power, lower peak alpha frequency, and lower aperiodic exponent, were associated with elevated RRBs at 24 months. No significant associations were observed for non-ASD outcome groups. Limitations The sample size for ASD (N=19) was modest for examining brain-behavior relations. Larger sample sizes are needed to increase statistical power. Conclusion For infants with later ASD diagnoses, measures of alpha and aperiodic activity measured at 1-year of age were associated with later manifestation of RRBs at 2-years. Longitudinal studies are needed to elucidate whether the early trajectory of these EEG measures and their dynamic relations in development influence manifestations of RRBs in ASD.
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7
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Kramer MA, Chu CJ. The 1/f-like behavior of neural field spectra are a natural consequence of noise driven brain dynamics. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.10.532077. [PMID: 37214869 PMCID: PMC10197559 DOI: 10.1101/2023.03.10.532077] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/24/2023]
Abstract
Consistent observations across recording modalities, experiments, and neural systems find neural field spectra with 1/f-like scaling, eliciting many alternative theories to explain this universal phenomenon. We show that a general dynamical system with stochastic drive and minimal assumptions generates 1/f-like spectra consistent with the range of values observed in vivo, without requiring a specific biological mechanism or collective critical behavior.
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Affiliation(s)
- Mark A Kramer
- Department of Mathematics and Statistics, and Center for Systems Neuroscience, Boston University, Boston MA, 02214
| | - Catherine J Chu
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston MA, 02114
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8
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Rosenblum Y, Shiner T, Bregman N, Giladi N, Maidan I, Fahoum F, Mirelman A. Decreased aperiodic neural activity in Parkinson's disease and dementia with Lewy bodies. J Neurol 2023:10.1007/s00415-023-11728-9. [PMID: 37138179 DOI: 10.1007/s00415-023-11728-9] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2023] [Revised: 04/11/2023] [Accepted: 04/12/2023] [Indexed: 05/05/2023]
Abstract
Neural oscillations and signal complexity have been widely studied in neurodegenerative diseases, whereas aperiodic activity has not been explored yet in those disorders. Here, we assessed whether the study of aperiodic activity brings new insights relating to disease as compared to the conventional spectral and complexity analyses. Eyes-closed resting-state electroencephalography (EEG) was recorded in 21 patients with dementia with Lewy bodies (DLB), 28 patients with Parkinson's disease (PD), 27 patients with mild cognitive impairment (MCI) and 22 age-matched healthy controls. Spectral power was differentiated into its oscillatory and aperiodic components using the Irregularly Resampled Auto-Spectral Analysis. Signal complexity was explored using the Lempel-Ziv algorithm (LZC). We found that DLB patients showed steeper slopes of the aperiodic power component with large effect sizes compared to the controls and MCI and with a moderate effect size compared to PD. PD patients showed steeper slopes with a moderate effect size compared to controls and MCI. Oscillatory power and LZC differentiated only between DLB and other study groups and were not sensitive enough to detect differences between PD, MCI, and controls. In conclusion, both DLB and PD are characterized by alterations in aperiodic dynamics, which are more sensitive in detecting disease-related neural changes than the traditional spectral and complexity analyses. Our findings suggest that steeper aperiodic slopes may serve as a marker of network dysfunction in DLB and PD features.
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Affiliation(s)
- Yevgenia Rosenblum
- Laboratory of Early Markers of Neurodegeneration, Center for the Study of Movement, Cognition and Mobility, Neurological Institute, Tel Aviv Medical Center, Tel Aviv, Israel
- Cognitive Neurology Unit, Neurological Institute, Tel Aviv Medical Center, Tel Aviv, Israel
- Department of Neurology and Neurosurgery, Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Tamara Shiner
- Cognitive Neurology Unit, Neurological Institute, Tel Aviv Medical Center, Tel Aviv, Israel
- Department of Neurology and Neurosurgery, Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
| | - Noa Bregman
- Cognitive Neurology Unit, Neurological Institute, Tel Aviv Medical Center, Tel Aviv, Israel
- Department of Neurology and Neurosurgery, Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
| | - Nir Giladi
- Laboratory of Early Markers of Neurodegeneration, Center for the Study of Movement, Cognition and Mobility, Neurological Institute, Tel Aviv Medical Center, Tel Aviv, Israel
- Cognitive Neurology Unit, Neurological Institute, Tel Aviv Medical Center, Tel Aviv, Israel
- Epilepsy Unit, Neurological Institute, Tel Aviv Medical Center, Tel Aviv, Israel
- Department of Neurology and Neurosurgery, Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
| | - Inbal Maidan
- Laboratory of Early Markers of Neurodegeneration, Center for the Study of Movement, Cognition and Mobility, Neurological Institute, Tel Aviv Medical Center, Tel Aviv, Israel
- Department of Neurology and Neurosurgery, Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
| | - Firas Fahoum
- Epilepsy Unit, Neurological Institute, Tel Aviv Medical Center, Tel Aviv, Israel
- Department of Neurology and Neurosurgery, Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Anat Mirelman
- Laboratory of Early Markers of Neurodegeneration, Center for the Study of Movement, Cognition and Mobility, Neurological Institute, Tel Aviv Medical Center, Tel Aviv, Israel.
- Department of Neurology and Neurosurgery, Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel.
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel.
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9
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Wiest C, Torrecillos F, Pogosyan A, Bange M, Muthuraman M, Groppa S, Hulse N, Hasegawa H, Ashkan K, Baig F, Morgante F, Pereira EA, Mallet N, Magill PJ, Brown P, Sharott A, Tan H. The aperiodic exponent of subthalamic field potentials reflects excitation/inhibition balance in Parkinsonism. eLife 2023; 12:e82467. [PMID: 36810199 PMCID: PMC10005762 DOI: 10.7554/elife.82467] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2022] [Accepted: 02/22/2023] [Indexed: 02/24/2023] Open
Abstract
Periodic features of neural time-series data, such as local field potentials (LFPs), are often quantified using power spectra. While the aperiodic exponent of spectra is typically disregarded, it is nevertheless modulated in a physiologically relevant manner and was recently hypothesised to reflect excitation/inhibition (E/I) balance in neuronal populations. Here, we used a cross-species in vivo electrophysiological approach to test the E/I hypothesis in the context of experimental and idiopathic Parkinsonism. We demonstrate in dopamine-depleted rats that aperiodic exponents and power at 30-100 Hz in subthalamic nucleus (STN) LFPs reflect defined changes in basal ganglia network activity; higher aperiodic exponents tally with lower levels of STN neuron firing and a balance tipped towards inhibition. Using STN-LFPs recorded from awake Parkinson's patients, we show that higher exponents accompany dopaminergic medication and deep brain stimulation (DBS) of STN, consistent with untreated Parkinson's manifesting as reduced inhibition and hyperactivity of STN. These results suggest that the aperiodic exponent of STN-LFPs in Parkinsonism reflects E/I balance and might be a candidate biomarker for adaptive DBS.
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Affiliation(s)
- Christoph Wiest
- Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Flavie Torrecillos
- Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Alek Pogosyan
- Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Manuel Bange
- Movement Disorders and Neurostimulation, Biomedical Statistics and Multimodal Signal Processing Unit, Department of Neurology, University Medical Center of the Johannes Gutenberg University MainzMainzGermany
| | - Muthuraman Muthuraman
- Movement Disorders and Neurostimulation, Biomedical Statistics and Multimodal Signal Processing Unit, Department of Neurology, University Medical Center of the Johannes Gutenberg University MainzMainzGermany
| | - Sergiu Groppa
- Movement Disorders and Neurostimulation, Biomedical Statistics and Multimodal Signal Processing Unit, Department of Neurology, University Medical Center of the Johannes Gutenberg University MainzMainzGermany
| | - Natasha Hulse
- Department of Neurosurgery, King's College LondonLondonUnited Kingdom
| | - Harutomo Hasegawa
- Department of Neurosurgery, King's College LondonLondonUnited Kingdom
| | - Keyoumars Ashkan
- Department of Neurosurgery, King's College LondonLondonUnited Kingdom
| | - Fahd Baig
- Neurosciences Research Centre, Molecular and Clinical Sciences Institute, St. George' s, University of LondonLondonUnited Kingdom
| | - Francesca Morgante
- Neurosciences Research Centre, Molecular and Clinical Sciences Institute, St. George' s, University of LondonLondonUnited Kingdom
| | - Erlick A Pereira
- Neurosciences Research Centre, Molecular and Clinical Sciences Institute, St. George' s, University of LondonLondonUnited Kingdom
| | - Nicolas Mallet
- Institut des Maladies Neurodégénératives, CNRS UMR5293, Université de BordeauxBordeauxFrance
| | - Peter J Magill
- Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Peter Brown
- Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Andrew Sharott
- Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Huiling Tan
- Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
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10
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Wu D, Zhao B, Xie H, Xu Y, Yin Z, Bai Y, Fan H, Zhang Q, Liu D, Hu T, Jiang Y, An Q, Zhang X, Yang A, Zhang J. Profiling the low-beta characteristics of the subthalamic nucleus in early- and late-onset Parkinson's disease. Front Aging Neurosci 2023; 15:1114466. [PMID: 36875708 PMCID: PMC9978704 DOI: 10.3389/fnagi.2023.1114466] [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: 12/02/2022] [Accepted: 01/30/2023] [Indexed: 02/18/2023] Open
Abstract
Objectives Low-beta oscillation (13-20 Hz) has rarely been studied in patients with early-onset Parkinson's disease (EOPD, age of onset ≤50 years). We aimed to explore the characteristics of low-beta oscillation in the subthalamic nucleus (STN) of patients with EOPD and investigate the differences between EOPD and late-onset Parkinson's disease (LOPD). Methods We enrolled 31 EOPD and 31 LOPD patients, who were matched using propensity score matching. Patients underwent bilateral STN deep brain stimulation (DBS). Local field potentials were recorded using intraoperative microelectrode recording. We analyzed the low-beta band parameters, including aperiodic/periodic components, beta burst, and phase-amplitude coupling. We compared low-beta band activity between EOPD and LOPD. Correlation analyses were performed between the low-beta parameters and clinical assessment results for each group. Results We found that the EOPD group had lower aperiodic parameters, including offset (p = 0.010) and exponent (p = 0.047). Low-beta burst analysis showed that EOPD patients had significantly higher average burst amplitude (p = 0.016) and longer average burst duration (p = 0.011). Furthermore, EOPD had higher proportion of long burst (500-650 ms, p = 0.008), while LOPD had higher proportion of short burst (200-350 ms, p = 0.007). There was a significant difference in phase-amplitude coupling values between low-beta phase and fast high frequency oscillation (300-460 Hz) amplitude (p = 0.019). Conclusion We found that low-beta activity in the STN of patients with EOPD had characteristics that varied when compared with LOPD, and provided electrophysiological evidence for different pathological mechanisms between the two types of PD. These differences need to be considered when applying adaptive DBS on patients of different ages.
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Affiliation(s)
- Delong Wu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Baotian Zhao
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Hutao Xie
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Yichen Xu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Zixiao Yin
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Yutong Bai
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,Beijing Key Laboratory of Neurostimulation, Beijing, China.,Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Houyou Fan
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Quan Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Defeng Liu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Tianqi Hu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Yin Jiang
- Beijing Key Laboratory of Neurostimulation, Beijing, China.,Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Qi An
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Xin Zhang
- Beijing Key Laboratory of Neurostimulation, Beijing, China.,Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Anchao Yang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,Beijing Key Laboratory of Neurostimulation, Beijing, China.,Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Jianguo Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,Beijing Key Laboratory of Neurostimulation, Beijing, China.,Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
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Hartmann A, Andrén P, Atkinson-Clement C, Czernecki V, Delorme C, Debes NM, Szejko N, Ueda K, Black K. Tourette syndrome research highlights from 2021. F1000Res 2022; 11:716. [PMID: 35923292 PMCID: PMC9315233 DOI: 10.12688/f1000research.122708.2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 09/05/2022] [Indexed: 11/05/2022] Open
Abstract
We summarize selected research reports from 2021 relevant to Tourette syndrome that the authors consider most important or interesting. The authors welcome article suggestions and thoughtful feedback from readers.
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Affiliation(s)
- Andreas Hartmann
- Department of Neurology, APHP, Sorbonne University, Hôpital de la Pitié-Salpêtrière, Paris, 75013, France,
| | - Per Andrén
- Department of Clinical Neuroscience, Karolinska Institutet and Stockholm Health Care Services, Stockholm, Sweden
| | - Cyril Atkinson-Clement
- Paris Brain Institute (ICM), Sorbonne Université, Inserm, CNRS, APHP, Paris, 75013, France
| | - Virginie Czernecki
- Department of Neurology, APHP, Sorbonne University, Hôpital de la Pitié-Salpêtrière, Paris, 75013, France
| | - Cécile Delorme
- Department of Neurology, APHP, Sorbonne University, Hôpital de la Pitié-Salpêtrière, Paris, 75013, France
| | | | - Natalia Szejko
- Department of Neurology, Medical University of Warsaw, Warsaw, Poland
| | - Keisuke Ueda
- Department of Psychiatry, Neurology, Radiology and Neuroscience, Washington University in St. Louis, Saint Louis, Missouri, USA
| | - Kevin Black
- Department of Psychiatry, Neurology, Radiology and Neuroscience, Washington University in St. Louis, Saint Louis, Missouri, USA
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