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Popescu M, Popescu EA, DeGraba TJ, Hughes JD. Altered long-range functional connectivity in PTSD: Role of the infraslow oscillations of cortical activity amplitude envelopes. Clin Neurophysiol 2024; 163:22-36. [PMID: 38669765 DOI: 10.1016/j.clinph.2024.03.036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Revised: 02/27/2024] [Accepted: 03/28/2024] [Indexed: 04/28/2024]
Abstract
OBJECTIVE Coupling between the amplitude envelopes (AEs) of regional cortical activity reflects mechanisms that coordinate the excitability of large-scale cortical networks. We used resting-state MEG recordings to investigate the association between alterations in the coupling of cortical AEs and symptoms of post-traumatic stress disorder (PTSD). METHODS Participants (n = 96) were service members with combat exposure and various levels of post-traumatic stress severity (PTSS). We assessed the correlation between PTSS and (1) coupling of broadband cortical AEs of beta band activity, (2) coupling of the low- (<0.5 Hz) and high-frequency (>0.5 Hz) components of the AEs, and (3) their time-varying patterns. RESULTS PTSS was associated with widespread hypoconnectivity assessed from the broadband AE fluctuations, which correlated with subscores for the negative thoughts and feelings/emotional numbing (NTF/EN) and hyperarousal clusters of symptoms. Higher NTF/EN scores were also associated with smaller increases in resting-state functional connectivity (rsFC) with time during the recordings. The distinct patterns of rsFC in PTSD were primarily due to differences in the coupling of low-frequency (infraslow) fluctuations of the AEs of beta band activity. CONCLUSIONS Our findings implicate the mechanisms underlying the regulation/coupling of infraslow oscillations in the alterations of rsFC assessed from broadband AEs and in PTSD symptomatology. SIGNIFICANCE Altered coordination of infraslow amplitude fluctuations across large-scale cortical networks can contribute to network dysfunction and may provide a target for treatment in PTSD.
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Affiliation(s)
- Mihai Popescu
- National Intrepid Center of Excellence, Walter Reed National Military Medical Center, Bethesda, MD, USA
| | - Elena-Anda Popescu
- National Intrepid Center of Excellence, Walter Reed National Military Medical Center, Bethesda, MD, USA
| | - Thomas J DeGraba
- National Intrepid Center of Excellence, Walter Reed National Military Medical Center, Bethesda, MD, USA
| | - John D Hughes
- National Intrepid Center of Excellence, Walter Reed National Military Medical Center, Bethesda, MD, USA; Behavioral Biology Branch, Walter Reed Army Institute of Research, Silver Spring, MD, USA.
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2
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Myrov V, Siebenhühner F, Juvonen JJ, Arnulfo G, Palva S, Palva JM. Rhythmicity of neuronal oscillations delineates their cortical and spectral architecture. Commun Biol 2024; 7:405. [PMID: 38570628 PMCID: PMC10991572 DOI: 10.1038/s42003-024-06083-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Accepted: 03/20/2024] [Indexed: 04/05/2024] Open
Abstract
Neuronal oscillations are commonly analyzed with power spectral methods that quantify signal amplitude, but not rhythmicity or 'oscillatoriness' per se. Here we introduce a new approach, the phase-autocorrelation function (pACF), for the direct quantification of rhythmicity. We applied pACF to human intracerebral stereoelectroencephalography (SEEG) and magnetoencephalography (MEG) data and uncovered a spectrally and anatomically fine-grained cortical architecture in the rhythmicity of single- and multi-frequency neuronal oscillations. Evidencing the functional significance of rhythmicity, we found it to be a prerequisite for long-range synchronization in resting-state networks and to be dynamically modulated during event-related processing. We also extended the pACF approach to measure 'burstiness' of oscillatory processes and characterized regions with stable and bursty oscillations. These findings show that rhythmicity is double-dissociable from amplitude and constitutes a functionally relevant and dynamic characteristic of neuronal oscillations.
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Affiliation(s)
- Vladislav Myrov
- Department of Neuroscience and Biomedical Engineering, Aalto University, Espoo, Finland.
| | - Felix Siebenhühner
- Neuroscience Center, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
- BioMag Laboratory, HUS Medical Imaging Center, Helsinki, Finland
| | - Joonas J Juvonen
- Department of Neuroscience and Biomedical Engineering, Aalto University, Espoo, Finland
- Neuroscience Center, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
| | - Gabriele Arnulfo
- Neuroscience Center, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
- Department of Informatics, Bioengineering, Robotics and System Engineering, University of Genoa, Genoa, Italy
| | - Satu Palva
- Neuroscience Center, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
- Centre for Cognitive Neuroimaging, School of Psychology and Neuroscience, University of Glasgow, Glasgow, UK
| | - J Matias Palva
- Department of Neuroscience and Biomedical Engineering, Aalto University, Espoo, Finland
- Neuroscience Center, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
- Centre for Cognitive Neuroimaging, School of Psychology and Neuroscience, University of Glasgow, Glasgow, UK
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Ao Y, Catal Y, Lechner S, Hua J, Northoff G. Intrinsic neural timescales relate to the dynamics of infraslow neural waves. Neuroimage 2024; 285:120482. [PMID: 38043840 DOI: 10.1016/j.neuroimage.2023.120482] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2023] [Revised: 11/23/2023] [Accepted: 12/01/2023] [Indexed: 12/05/2023] Open
Abstract
The human brain is a highly dynamic organ that operates across a variety of timescales, the intrinsic neural timescales (INT). In addition to the INT, the neural waves featured by its phase-related processes including their cycles with peak/trough and rise/fall play a key role in shaping the brain's neural activity. However, the relationship between the brain's ongoing wave dynamics and INT remains yet unclear. In this study, we utilized functional magnetic resonance imaging (fMRI) rest and task data from the Human Connectome Project (HCP) to investigate the relationship of infraslow wave dynamics [as measured in terms of speed by changes in its peak frequency (PF)] with INT. Our findings reveal that: (i) the speed of phase dynamics (PF) is associated with distinct parts of the ongoing phase cycles, namely higher PF in peak/trough and lower PF in rise/fall; (ii) there exists a negative correlation between phase dynamics (PF) and INT such that slower PF relates to longer INT; (iii) exposure to a movie alters both PF and INT across the different phase cycles, yet their negative correlation remains intact. Collectively, our results demonstrate that INT relates to infraslow phase dynamics during both rest and task states.
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Affiliation(s)
- Yujia Ao
- Mind, Brain Imaging and Neuroethics Research Unit, Institute of Mental Health Research, Faculty of Medicine, University of Ottawa, Ottawa, ON, Canada
| | - Yasir Catal
- Mind, Brain Imaging and Neuroethics Research Unit, Institute of Mental Health Research, Faculty of Medicine, University of Ottawa, Ottawa, ON, Canada
| | - Stephan Lechner
- Mind, Brain Imaging and Neuroethics Research Unit, Institute of Mental Health Research, Faculty of Medicine, University of Ottawa, Ottawa, ON, Canada; Research Group Neuroinformatics, Faculty of Computer Science, University of Vienna, 1010 Vienna, Austria; Vienna Doctoral School Cognition, Behavior and Neuroscience, University of Vienna, 1030 Vienna, Austria
| | - Jingyu Hua
- Department of Psychology, Faculty of Social Sciences, University of Ottawa, Ottawa, ON, Canada
| | - Georg Northoff
- Mind, Brain Imaging and Neuroethics Research Unit, Institute of Mental Health Research, Faculty of Medicine, University of Ottawa, Ottawa, ON, Canada.
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4
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Väyrynen T, Helakari H, Korhonen V, Tuunanen J, Huotari N, Piispala J, Kallio M, Raitamaa L, Kananen J, Järvelä M, Matias Palva J, Kiviniemi V. Infra-slow fluctuations in cortical potentials and respiration drive fast cortical EEG rhythms in sleeping and waking states. Clin Neurophysiol 2023; 156:207-219. [PMID: 37972532 DOI: 10.1016/j.clinph.2023.10.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2023] [Revised: 08/09/2023] [Accepted: 10/23/2023] [Indexed: 11/19/2023]
Abstract
OBJECTIVE Infra-slow fluctuations (ISF, 0.008-0.1 Hz) characterize hemodynamic and electric potential signals of human brain. ISFs correlate with the amplitude dynamics of fast (>1 Hz) neuronal oscillations, and may arise from permeability fluctuations of the blood-brain barrier (BBB). It is unclear if physiological rhythms like respiration drive or track fast cortical oscillations, and the role of sleep in this coupling is unknown. METHODS We used high-density full-band electroencephalography (EEG) in healthy human volunteers (N = 21) to measure concurrently the ISFs, respiratory pulsations, and fast neuronal oscillations during periods of wakefulness and sleep, and to assess the strength and direction of their phase-amplitude coupling. RESULTS The phases of ISFs and respiration were both coupled with the amplitude of fast neuronal oscillations, with stronger ISF coupling being evident during sleep. Phases of ISF and respiration drove the amplitude dynamics of fast oscillations in sleeping and waking states, with different contributions. CONCLUSIONS ISFs in slow cortical potentials and respiration together significantly determine the dynamics of fast cortical oscillations. SIGNIFICANCE We propose that these slow physiological phases play a significant role in coordinating cortical excitability, which is a fundamental aspect of brain function.
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Affiliation(s)
- Tommi Väyrynen
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu 90029, Finland; MIPT group to: Research Unit of Health Sciences and Technology (HST), Faculty of Medicine, University of Oulu, Oulu 90220, Finland; Medical Research Center (MRC), Oulu 90220, Finland.
| | - Heta Helakari
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu 90029, Finland; MIPT group to: Research Unit of Health Sciences and Technology (HST), Faculty of Medicine, University of Oulu, Oulu 90220, Finland; Medical Research Center (MRC), Oulu 90220, Finland
| | - Vesa Korhonen
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu 90029, Finland; MIPT group to: Research Unit of Health Sciences and Technology (HST), Faculty of Medicine, University of Oulu, Oulu 90220, Finland; Medical Research Center (MRC), Oulu 90220, Finland
| | - Johanna Tuunanen
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu 90029, Finland; MIPT group to: Research Unit of Health Sciences and Technology (HST), Faculty of Medicine, University of Oulu, Oulu 90220, Finland; Medical Research Center (MRC), Oulu 90220, Finland
| | - Niko Huotari
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu 90029, Finland; MIPT group to: Research Unit of Health Sciences and Technology (HST), Faculty of Medicine, University of Oulu, Oulu 90220, Finland; Medical Research Center (MRC), Oulu 90220, Finland
| | - Johanna Piispala
- MIPT group to: Research Unit of Health Sciences and Technology (HST), Faculty of Medicine, University of Oulu, Oulu 90220, Finland; Medical Research Center (MRC), Oulu 90220, Finland; Clinical Neurophysiology, Oulu University Hospital, Oulu 90220, Finland
| | - Mika Kallio
- MIPT group to: Research Unit of Health Sciences and Technology (HST), Faculty of Medicine, University of Oulu, Oulu 90220, Finland; Medical Research Center (MRC), Oulu 90220, Finland; Clinical Neurophysiology, Oulu University Hospital, Oulu 90220, Finland
| | - Lauri Raitamaa
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu 90029, Finland; MIPT group to: Research Unit of Health Sciences and Technology (HST), Faculty of Medicine, University of Oulu, Oulu 90220, Finland; Medical Research Center (MRC), Oulu 90220, Finland
| | - Janne Kananen
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu 90029, Finland; MIPT group to: Research Unit of Health Sciences and Technology (HST), Faculty of Medicine, University of Oulu, Oulu 90220, Finland; Medical Research Center (MRC), Oulu 90220, Finland; Clinical Neurophysiology, Oulu University Hospital, Oulu 90220, Finland
| | - Matti Järvelä
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu 90029, Finland; MIPT group to: Research Unit of Health Sciences and Technology (HST), Faculty of Medicine, University of Oulu, Oulu 90220, Finland; Medical Research Center (MRC), Oulu 90220, Finland
| | - J Matias Palva
- Department of Neuroscience and Biomedical Engineering, Aalto University, 02150 Espoo, Finland; Neuroscience Center, Helsinki Institute of Life Science, University of Helsinki, Finland; Centre for Cognitive Neuroimaging, University of Glasgow, United Kingdom
| | - Vesa Kiviniemi
- Oulu Functional NeuroImaging (OFNI), Department of Diagnostic Radiology, Oulu University Hospital, Oulu 90029, Finland; MIPT group to: Research Unit of Health Sciences and Technology (HST), Faculty of Medicine, University of Oulu, Oulu 90220, Finland; Medical Research Center (MRC), Oulu 90220, Finland; Biocenter Oulu, Faculty of Biochemistry and Molecular Medicine, University of Oulu, Oulu 90220, Finland
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M Aghajan Z, Kreiman G, Fried I. Minute-scale periodicity of neuronal firing in the human entorhinal cortex. Cell Rep 2023; 42:113271. [PMID: 37906591 DOI: 10.1016/j.celrep.2023.113271] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2023] [Revised: 07/09/2023] [Accepted: 09/28/2023] [Indexed: 11/02/2023] Open
Abstract
Grid cells in the entorhinal cortex demonstrate spatially periodic firing, thought to provide a spatial map on behaviorally relevant length scales. Whether such periodicity exists for behaviorally relevant time scales in the human brain remains unclear. We investigate neuronal firing during a temporally continuous experience by presenting 14 neurosurgical patients with a video while recording neuronal activity from multiple brain regions. We report on neurons that modulate their activity in a periodic manner across different time scales-from seconds to many minutes, most prevalently in the entorhinal cortex. These neurons remap their dominant periodicity to shorter time scales during a subsequent recognition memory task. When the video is presented at two different speeds, a significant percentage of these temporally periodic cells (TPCs) maintain their time scales, suggesting a degree of invariance. The TPCs' temporal periodicity might complement the spatial periodicity of grid cells and together provide scalable spatiotemporal metrics for human experience.
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Affiliation(s)
- Zahra M Aghajan
- Department of Neurosurgery, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90095, USA.
| | - Gabriel Kreiman
- Children's Hospital, Harvard Medical School, Boston, MA 02115, USA; Center for Brains, Minds and Machines, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Itzhak Fried
- Department of Neurosurgery, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90095, USA; Department of Psychiatry and Biobehavioral Sciences, Jane and Terry Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, CA 90095, USA; Faculty of Medicine, Tel Aviv University, Tel-Aviv 69978, Israel.
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6
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Bjerkan J, Lancaster G, Meglič B, Kobal J, Crawford TJ, McClintock PVE, Stefanovska A. Aging affects the phase coherence between spontaneous oscillations in brain oxygenation and neural activity. Brain Res Bull 2023; 201:110704. [PMID: 37451471 DOI: 10.1016/j.brainresbull.2023.110704] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Revised: 07/03/2023] [Accepted: 07/11/2023] [Indexed: 07/18/2023]
Abstract
The risk of neurodegenerative disorders increases with age, due to reduced vascular nutrition and impaired neural function. However, the interactions between cardiovascular dynamics and neural activity, and how these interactions evolve in healthy aging, are not well understood. Here, the interactions are studied by assessment of the phase coherence between spontaneous oscillations in cerebral oxygenation measured by fNIRS, the electrical activity of the brain measured by EEG, and cardiovascular functions extracted from ECG and respiration effort, all simultaneously recorded. Signals measured at rest in 21 younger participants (31.1 ± 6.9 years) and 24 older participants (64.9 ± 6.9 years) were analysed by wavelet transform, wavelet phase coherence and ridge extraction for frequencies between 0.007 and 4 Hz. Coherence between the neural and oxygenation oscillations at ∼ 0.1 Hz is significantly reduced in the older adults in 46/176 fNIRS-EEG probe combinations. This reduction in coherence cannot be accounted for in terms of reduced power, thus indicating that neurovascular interactions change with age. The approach presented promises a noninvasive means of evaluating the efficiency of the neurovascular unit in aging and disease.
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Affiliation(s)
- Juliane Bjerkan
- Lancaster University, Department of Physics, LA1 4YB, Lancaster, United Kingdom
| | - Gemma Lancaster
- Lancaster University, Department of Physics, LA1 4YB, Lancaster, United Kingdom
| | - Bernard Meglič
- University of Ljubljana Medical Centre, Department of Neurology, 1525, Ljubljana, Slovenia
| | - Jan Kobal
- University of Ljubljana Medical Centre, Department of Neurology, 1525, Ljubljana, Slovenia
| | - Trevor J Crawford
- Lancaster University, Department of Psychology, LA1 4YF, Lancaster, United Kingdom
| | | | - Aneta Stefanovska
- Lancaster University, Department of Physics, LA1 4YB, Lancaster, United Kingdom.
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Yu Y, Qiu Y, Li G, Zhang K, Bo B, Pei M, Ye J, Thompson GJ, Cang J, Fang F, Feng Y, Duan X, Tong C, Liang Z. Sleep fMRI with simultaneous electrophysiology at 9.4 T in male mice. Nat Commun 2023; 14:1651. [PMID: 36964161 PMCID: PMC10039056 DOI: 10.1038/s41467-023-37352-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2022] [Accepted: 03/14/2023] [Indexed: 03/26/2023] Open
Abstract
Sleep is ubiquitous and essential, but its mechanisms remain unclear. Studies in animals and humans have provided insights of sleep at vastly different spatiotemporal scales. However, challenges remain to integrate local and global information of sleep. Therefore, we developed sleep fMRI based on simultaneous electrophysiology at 9.4 T in male mice. Optimized un-anesthetized mouse fMRI setup allowed manifestation of NREM and REM sleep, and a large sleep fMRI dataset was collected and openly accessible. State dependent global patterns were revealed, and state transitions were found to be global, asymmetrical and sequential, which can be predicted up to 17.8 s using LSTM models. Importantly, sleep fMRI with hippocampal recording revealed potentiated sharp-wave ripple triggered global patterns during NREM than awake state, potentially attributable to co-occurrence of spindle events. To conclude, we established mouse sleep fMRI with simultaneous electrophysiology, and demonstrated its capability by revealing global dynamics of state transitions and neural events.
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Affiliation(s)
- Yalin Yu
- Institute of Neuroscience, CAS Key Laboratory of Primate Neurobiology, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Yue Qiu
- Department of Anesthesia, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Gen Li
- Department of Biomedical Engineering, College of Future Technology, Academy for Advanced Interdisciplinary Studies, National Biomedical Imaging Centre, Peking University, Beijing, China
| | - Kaiwei Zhang
- Institute of Neuroscience, CAS Key Laboratory of Primate Neurobiology, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China
| | - Binshi Bo
- Institute of Neuroscience, CAS Key Laboratory of Primate Neurobiology, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China
| | - Mengchao Pei
- Institute of Neuroscience, CAS Key Laboratory of Primate Neurobiology, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China
| | - Jingjing Ye
- iHuman Institute, ShanghaiTech University, Shanghai, China
| | | | - Jing Cang
- Department of Anesthesia, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Fang Fang
- Department of Anesthesia, Zhongshan Hospital, Fudan University, Shanghai, China
- The Central Hospital of Xuhui District, Shanghai, China
| | - Yanqiu Feng
- School of Biomedical Engineering, Southern Medical University, Guangzhou, China
| | - Xiaojie Duan
- Department of Biomedical Engineering, College of Future Technology, Academy for Advanced Interdisciplinary Studies, National Biomedical Imaging Centre, Peking University, Beijing, China.
| | - Chuanjun Tong
- Institute of Neuroscience, CAS Key Laboratory of Primate Neurobiology, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China.
- School of Biomedical Engineering, Southern Medical University, Guangzhou, China.
| | - Zhifeng Liang
- Institute of Neuroscience, CAS Key Laboratory of Primate Neurobiology, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China.
- Shanghai Center for Brain Science and Brain-Inspired Intelligence Technology, Shanghai, China.
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Smeele SJ, Adhia DB, De Ridder D. Feasibility and Safety of High-Definition Infraslow Pink Noise Stimulation for Treating Chronic Tinnitus—A Randomized Placebo-Controlled Trial. Neuromodulation 2022:S1094-7159(22)01339-3. [DOI: 10.1016/j.neurom.2022.10.049] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Revised: 10/18/2022] [Accepted: 10/19/2022] [Indexed: 12/03/2022]
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Perez TM, Glue P, Adhia DB, Navid MS, Zeng J, Dillingham P, Smith M, Niazi IK, Young CK, De Ridder D. Infraslow closed-loop brain training for anxiety and depression (ISAD): a protocol for a randomized, double-blind, sham-controlled pilot trial in adult females with internalizing disorders. Trials 2022; 23:949. [DOI: 10.1186/s13063-022-06863-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2021] [Accepted: 10/22/2022] [Indexed: 11/18/2022] Open
Abstract
Abstract
Background
The core intrinsic connectivity networks (core-ICNs), encompassing the default-mode network (DMN), salience network (SN) and central executive network (CEN), have been shown to be dysfunctional in individuals with internalizing disorders (IDs, e.g. major depressive disorder, MDD; generalized anxiety disorder, GAD; social anxiety disorder, SOC). As such, source-localized, closed-loop brain training of electrophysiological signals, also known as standardized low-resolution electromagnetic tomography (sLORETA) neurofeedback (NFB), targeting key cortical nodes within these networks has the potential to reduce symptoms associated with IDs and restore normal core ICN function. We intend to conduct a randomized, double-blind (participant and assessor), sham-controlled, parallel-group (3-arm) trial of sLORETA infraslow (<0.1 Hz) fluctuation neurofeedback (sLORETA ISF-NFB) 3 times per week over 4 weeks in participants (n=60) with IDs. Our primary objectives will be to examine patient-reported outcomes (PROs) and neurophysiological measures to (1) compare the potential effects of sham ISF-NFB to either genuine 1-region ISF-NFB or genuine 2-region ISF-NFB, and (2) assess for potential associations between changes in PRO scores and modifications of electroencephalographic (EEG) activity/connectivity within/between the trained regions of interest (ROIs). As part of an exploratory analysis, we will investigate the effects of additional training sessions and the potential for the potentiation of the effects over time.
Methods
We will randomly assign participants who meet the criteria for MDD, GAD, and/or SOC per the MINI (Mini International Neuropsychiatric Interview for DSM-5) to one of three groups: (1) 12 sessions of posterior cingulate cortex (PCC) ISF-NFB up-training (n=15), (2) 12 sessions of concurrent PCC ISF up-training and dorsal anterior cingulate cortex (dACC) ISF-NFB down-training (n=15), or (3) 6 sessions of yoked-sham training followed by 6 sessions genuine ISF-NFB (n=30). Transdiagnostic PROs (Hospital Anxiety and Depression Scale, HADS; Inventory of Depression and Anxiety Symptoms – Second Version, IDAS-II; Multidimensional Emotional Disorder Inventory, MEDI; Intolerance of Uncertainty Scale – Short Form, IUS-12; Repetitive Thinking Questionnaire, RTQ-10) as well as resting-state neurophysiological measures (full-band EEG and ECG) will be collected from all subjects during two baseline sessions (approximately 1 week apart) then at post 6 sessions, post 12 sessions, and follow-up (1 month later). We will employ Bayesian methods in R and advanced source-localisation software (i.e. exact low-resolution brain electromagnetic tomography; eLORETA) in our analysis.
Discussion
This protocol will outline the rationale and research methodology for a clinical pilot trial of sLORETA ISF-NFB targeting key nodes within the core-ICNs in a female ID population with the primary aims being to assess its potential efficacy via transdiagnostic PROs and relevant neurophysiological measures.
Trial registration
Our study was prospectively registered with the Australia New Zealand Clinical Trials Registry (ANZCTR; Trial ID: ACTRN12619001428156). Registered on October 15, 2019.
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Zhang YS, Takahashi DY, El Hady A, Liao DA, Ghazanfar AA. Active neural coordination of motor behaviors with internal states. Proc Natl Acad Sci U S A 2022; 119:e2201194119. [PMID: 36122243 DOI: 10.1073/pnas.2201194119] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
The brain continuously coordinates skeletomuscular movements with internal physiological states like arousal, but how is this coordination achieved? One possibility is that the brain simply reacts to changes in external and/or internal signals. Another possibility is that it is actively coordinating both external and internal activities. We used functional ultrasound imaging to capture a large medial section of the brain, including multiple cortical and subcortical areas, in marmoset monkeys while monitoring their spontaneous movements and cardiac activity. By analyzing the causal ordering of these different time series, we found that information flowing from the brain to movements and heart-rate fluctuations were significantly greater than in the opposite direction. The brain areas involved in this external versus internal coordination were spatially distinct, but also extensively interconnected. Temporally, the brain alternated between network states for this regulation. These findings suggest that the brain's dynamics actively and efficiently coordinate motor behavior with internal physiology.
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11
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Favaretto C, Allegra M, Deco G, Metcalf NV, Griffis JC, Shulman GL, Brovelli A, Corbetta M. Subcortical-cortical dynamical states of the human brain and their breakdown in stroke. Nat Commun 2022; 13:5069. [PMID: 36038566 PMCID: PMC9424299 DOI: 10.1038/s41467-022-32304-1] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2021] [Accepted: 07/25/2022] [Indexed: 11/17/2022] Open
Abstract
The mechanisms controlling dynamical patterns in spontaneous brain activity are poorly understood. Here, we provide evidence that cortical dynamics in the ultra-slow frequency range (<0.01–0.1 Hz) requires intact cortical-subcortical communication. Using functional magnetic resonance imaging (fMRI) at rest, we identify Dynamic Functional States (DFSs), transient but recurrent clusters of cortical and subcortical regions synchronizing at ultra-slow frequencies. We observe that shifts in cortical clusters are temporally coincident with shifts in subcortical clusters, with cortical regions flexibly synchronizing with either limbic regions (hippocampus/amygdala), or subcortical nuclei (thalamus/basal ganglia). Focal lesions induced by stroke, especially those damaging white matter connections between basal ganglia/thalamus and cortex, provoke anomalies in the fraction times, dwell times, and transitions between DFSs, causing a bias toward abnormal network integration. Dynamical anomalies observed 2 weeks after stroke recover in time and contribute to explaining neurological impairment and long-term outcome. Favaretto et al. show that the brain rapidly alternates between transient connectivity patterns, with cortical regions flexibly synchronizing with two groups of subcortical regions, and that this dynamic is abnormal in stroke patients.
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Affiliation(s)
- Chiara Favaretto
- Padova Neuroscience Center (PNC), University of Padova, via Orus 2/B, 35129, Padova, Italy. .,Department of Neuroscience (DNS), University of Padova, via Giustiniani 2, 35128, Padova, Italy.
| | - Michele Allegra
- Padova Neuroscience Center (PNC), University of Padova, via Orus 2/B, 35129, Padova, Italy.,Department of Physics and Astronomy "Galileo Galilei", University of Padova, via Marzolo 8, 35131, Padova, Italy.,Institut de Neurosciences de la Timone UMR 7289, Aix Marseille Université, CNRS, 13005, Marseille, France
| | - Gustavo Deco
- Center for Brain and Cognition (CBC), Department of Information Technologies and Communications (DTIC), Pompeu Fabra University, Edifici Mercè Rodoreda, Carrer Trias i Fargas 25-27, 08005, Barcelona, Catalonia, Spain.,Institució Catalana de Recerca I Estudis Avançats (ICREA), Passeig Lluis Companys 23, 08010, Barcelona, Catalonia, Spain
| | - Nicholas V Metcalf
- Department of Neurology, Washington University School of Medicine, 660S. Euclid Ave, St. Louis, MO, 63110, USA
| | - Joseph C Griffis
- Department of Neurology, Washington University School of Medicine, 660S. Euclid Ave, St. Louis, MO, 63110, USA
| | - Gordon L Shulman
- Department of Neurology, Washington University School of Medicine, 660S. Euclid Ave, St. Louis, MO, 63110, USA.,Department of Radiology, Washington University School of Medicine, 660S. Euclid Ave, St. Louis, MO, 63110, USA
| | - Andrea Brovelli
- Institut de Neurosciences de la Timone UMR 7289, Aix Marseille Université, CNRS, 13005, Marseille, France
| | - Maurizio Corbetta
- Padova Neuroscience Center (PNC), University of Padova, via Orus 2/B, 35129, Padova, Italy. .,Department of Neuroscience (DNS), University of Padova, via Giustiniani 2, 35128, Padova, Italy. .,Department of Neurology, Washington University School of Medicine, 660S. Euclid Ave, St. Louis, MO, 63110, USA. .,Department of Radiology, Washington University School of Medicine, 660S. Euclid Ave, St. Louis, MO, 63110, USA. .,VIMM, Venetian Institute of Molecular Medicine (VIMM), Biomedical Foundation, via Orus 2, 35129, Padova, Italy.
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12
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Abstract
Spontaneous Infra-Slow Fluctuations (ISFs) of the human EEG (EEG-ISFs) were discovered 60 years ago when appropriate amplifiers for their recordings were designed. To avoid skin-related artifacts the recording of EEG-ISFs required puncturing the skin under the electrode. In the beginning of the 21st century the interest in EEG-ISFs was renewed with the appearance of commercially available DC-coupled amplified and by observation of ISFs of the blood oxygen level–dependent (BOLD) functional magnetic resonance imaging signal at a similar frequency. The independent components of irregular EEG-ISFs were shown to correlate with BOLD signals which in turn were driven by changes in arousal level measured by galvanic skin response (GSR), pupil size and HRV. There is no consensus regarding the temporal organization of EEG-ISFs: some studies emphasize the absence of peaks on EEG-ISFs spectra, some studies report prominent oscillations with frequency around 0.1 or 0.02 Hz, while some emphasize multiple discrete infraslow oscillations. No studies used parameters of EEG-ISFs as neuromarkers to discriminate psychiatric patients from healthy controls. Finally, a set of working hypotheses is suggested that must be tested in future research to solve the enigma of EEG-ISFs.
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13
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Yang Y, Wang S, Liu J, Zou G, Jiang J, Jiang B, Cao W, Zou Q. Changes in white matter functional networks during wakefulness and sleep. Hum Brain Mapp 2022; 43:4383-4396. [PMID: 35615855 PMCID: PMC9435017 DOI: 10.1002/hbm.25961] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2021] [Revised: 05/10/2022] [Accepted: 05/10/2022] [Indexed: 11/23/2022] Open
Abstract
Blood oxygenation level‐dependent (BOLD) signals in the white matter (WM) have been demonstrated to encode neural activities by showing structure‐specific temporal correlations during resting‐state and task‐specific imaging of fiber pathways with various degrees of correlations in strength and time delay. Previous neuroimaging studies have shown state‐dependent functional connectivity and regional amplitude of signal fluctuations in brain gray matter across wakefulness and nonrapid eye movement (NREM) sleep cycles. However, the functional characteristics of WM during sleep remain unknown. Using simultaneous electroencephalography and functional magnetic resonance imaging data during wakefulness and NREM sleep collected from 66 healthy participants, we constructed 10 stable WM functional networks using clustering analysis. Functional connectivity between these WM functional networks and regional amplitude of WM signal fluctuations across multiple low‐frequency bands were evaluated. In general, decreased WM functional connectivity between superficial and middle layer WM functional networks was observed from wakefulness to sleep. In addition, functional connectivity between the deep and cerebellar networks was higher during light sleep and lower during both wakefulness and deep sleep. The regional fluctuation amplitude was always higher during light sleep and lower during deep sleep. Importantly, slow‐wave activity during deep sleep negatively correlated with functional connectivity between WM functional networks but positively correlated with fluctuation strength in the WM. These observations provide direct physiological evidence that neural activities in the WM are modulated by the sleep–wake cycle. This study provided the initial mapping of functional changes in WM during sleep.
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Affiliation(s)
- Yang Yang
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China.,Beijing City Key Lab for Medical Physics and Engineering, Institution of Heavy Ion Physics, School of Physics, Peking University, Beijing, China
| | - Shilei Wang
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China.,Beijing City Key Lab for Medical Physics and Engineering, Institution of Heavy Ion Physics, School of Physics, Peking University, Beijing, China
| | - Jiayi Liu
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China.,Beijing City Key Lab for Medical Physics and Engineering, Institution of Heavy Ion Physics, School of Physics, Peking University, Beijing, China
| | - Guangyuan Zou
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China.,Beijing City Key Lab for Medical Physics and Engineering, Institution of Heavy Ion Physics, School of Physics, Peking University, Beijing, China
| | - Jun Jiang
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China.,Beijing City Key Lab for Medical Physics and Engineering, Institution of Heavy Ion Physics, School of Physics, Peking University, Beijing, China
| | - Binghu Jiang
- Department of Radiology, Nanchong Central Hospital, The Second Clinical Medical College, North Sichuan Medical College, Nanchong, China
| | - Wentian Cao
- Beijing City Key Lab for Medical Physics and Engineering, Institution of Heavy Ion Physics, School of Physics, Peking University, Beijing, China
| | - Qihong Zou
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China.,National Clinical Research Center for Mental Health, Peking University Sixth Hospital, China
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14
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Gopan K G, Reddy SA, Rao M, Sinha N. Analysis of single channel electroencephalographic signals for visual creativity: A pilot study. Biomed Signal Process Control 2022. [DOI: 10.1016/j.bspc.2022.103542] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022]
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15
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Qiao J, Li X, Wang Y, Wang Y, Li G, Lu P, Wang S. The Infraslow Frequency Oscillatory Transcranial Direct Current Stimulation Over the Left Dorsolateral Prefrontal Cortex Enhances Sustained Attention. Front Aging Neurosci 2022; 14:879006. [PMID: 35431889 PMCID: PMC9009338 DOI: 10.3389/fnagi.2022.879006] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2022] [Accepted: 02/28/2022] [Indexed: 12/18/2022] Open
Abstract
Background The vigilance fluctuation and decrement of sustained attention have large detrimental consequences to most tasks in daily life, especially among the elderly. Non-invasive brain stimulations (e.g., transcranial direct current stimulation, tDCS) have been widely applied to improve sustained attention, however, with mixed results. Objective An infraslow frequency oscillatory tDCS approach was designed to improve sustained attention. Methods The infraslow frequency oscillatory tDCS (O-tDCS) over the left dorsolateral prefrontal cortex at 0.05 Hz was designed and compared with conventional tDCS (C-tDCS) to test whether this new protocol improves sustained attention more effectively. The sustained attention was evaluated by reaction time and accuracy. Results Compared with the C-tDCS and sham, the O-tDCS significantly enhanced sustained attention by increasing response accuracy, reducing response time, and its variability. These effects were predicted by the evoked oscillation of response time at the stimulation frequency. Conclusion Similar to previous studies, the modulation effect of C-tDCS on sustained attention is weak and unstable. In contrast, the O-tDCS effectively and systematically enhances sustained attention by optimizing vigilance fluctuation. The modulation effect of O-tDCS is probably driven by neural oscillations at the infraslow frequency range.
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Affiliation(s)
- Jingwen Qiao
- Academy for Engineering and Technology, Fudan University, Shanghai, China
| | - Xinyu Li
- Department of Electronic Engineering, Fudan University, Shanghai, China
| | - Youhao Wang
- Academy for Engineering and Technology, Fudan University, Shanghai, China
| | - Yifeng Wang
- Institute of Brain and Psychological Sciences, Sichuan Normal University, Chengdu, China
| | - Gen Li
- Institute of Brain and Psychological Sciences, Sichuan Normal University, Chengdu, China
| | - Ping Lu
- Institute of Brain and Psychological Sciences, Sichuan Normal University, Chengdu, China
| | - Shouyan Wang
- Academy for Engineering and Technology, Fudan University, Shanghai, China
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
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16
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Abstract
The functional role of the brain’s infraslow activity (ISA, 0.01–0.1 Hz) in human behavior has yet to be elucidated. To date, it has been shown that the brain’s ISA correlates with behavioral performance; task performance is more likely to increase when executed at a specific ISA phase. However, it is unclear how the ISA correlates behavioral performance. We hypothesized that the ISA phase correlation of behavioral performance is mediated by arousal. Our data analysis results showed that the electroencephalogram (EEG) ISA phase was correlated with the galvanic skin response (GSR) amplitude, a measure of the arousal level. Furthermore, subjects whose EEG ISA phase correlated with the GSR amplitude more strongly also showed greater EEG ISA modulation during meditation, which implies an intimate relationship between brain ISA and arousal. These results may help improve understanding of the functional role of the brain’s ISA.
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17
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Abstract
The oscillation phase of electroencephalograms (EEGs) is associated with behavioral performance. Several studies have demonstrated this association for relatively fast oscillations (>1 Hz); a similar finding has also been reported for slower oscillations, showing that behavioral performance is correlated with the phase of infraslow activity (ISA, 0.01-0.1 Hz) of electroencephalography (EEG). However, the previous study only investigated ISA in a local brain region using a relatively simple task (somatosensory discrimination task), leaving it difficult to determine how the EEG ISA for various brain regions is associated with behavioral performance. In addition, it is not known whether the EEG ISA phase modulates more complex behavioral task performance. In the present study, we analyzed the ISA of whole-brain EEG of participants performing various behaviors while playing video games. We found that behavior was associated with the specific oscillation phase of EEG ISA when that behavior was independent of other behaviors. In addition, we found that the EEG ISA oscillation phases modulating the different behaviors varied across brain regions. Our results suggest that the EEG ISA for different brain regions modulates behavioral performance in different ways and such modulation of EEG ISA can be generalized to diverse behaviors. This study may deepen the understanding of how EEG ISA modulates behavior and increases the applicability of EEG ISA.
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Affiliation(s)
- Duho Sihn
- Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, Ulsan, Republic of Korea
| | - Sung-Phil Kim
- Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, Ulsan, Republic of Korea
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18
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Hsu AL, Li CW, Qin P, Lo MT, Wu CW. Localizing Spectral Interactions in the Resting State Network Using the Hilbert–Huang Transform. Brain Sci 2022; 12:brainsci12020140. [PMID: 35203903 PMCID: PMC8870154 DOI: 10.3390/brainsci12020140] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Revised: 01/14/2022] [Accepted: 01/18/2022] [Indexed: 11/16/2022] Open
Abstract
Brain synchronizations are orchestrated from neuronal oscillations through frequency interactions, such as the alpha rhythm during relaxation. Nevertheless, how the intrinsic interaction forges functional integrity across brain segregations remains elusive, thereby motivating recent studies to localize frequency interactions of resting-state fMRI (rs-fMRI). To this point, we aim to unveil the fMRI-based spectral interactions using the time-frequency (TF) analysis; however, Fourier-based TF analyses impose restrictions on revealing frequency interactions given the limited time points in fMRI signals. Instead of using the Fourier-based wavelet analysis to identify the fMRI frequency of interests, we employed the Hilbert–Huang transform (HHT) for probing the specific frequency contribution to the functional integration, called ensemble spectral interaction (ESI). By simulating data with time-variant frequency changes, we demonstrated the Hilbert TF maps with high spectro-temporal resolution and full accessibility in comparison with the wavelet TF maps. By detecting amplitude-to-amplitude frequency couplings (AAC) across brain regions, we elucidated the ESI disparity between the eye-closed (EC) and eye-open (EO) conditions in rs-fMRI. In the visual network, the strength of the spectral interaction within 0.03–0.04 Hz was amplified in EC compared with that in EO condition, whereas a canonical connectivity analysis did not present differences between conditions. Collectively, leveraging from the instantaneous frequency of HHT, we firstly addressed the ESI technique to map the fMRI-based functional connectivity in a brand-new AAC perspective. The ESI possesses potential in elucidating the functional connectivity at specific frequency bins, thereby providing additional diagnostic merits for future clinical neuroscience.
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Affiliation(s)
- Ai-Ling Hsu
- Bachelor Program in Artificial Intelligence, Chang Gung University, Taoyuan 33305, Taiwan;
- Department of Psychiatry, Chang Gung Memorial Hospital at Linkou, Taoyuan 33305, Taiwan
| | - Chia-Wei Li
- Department of Radiology, Wan Fang Hospital, Taipei Medical University, Taipei 11696, Taiwan;
| | - Pengmin Qin
- Key Laboratory of Brain, Cognition and Education Sciences (South China Normal University, Ministry of Education), Center for Studies of Psychological Application and Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou 510631, China;
- Pazhou Lab, Guangzhou 510335, China
- School of Psychology, South China Normal University, Guangzhou 510631, China
| | - Men-Tzung Lo
- Department of Biomedical Sciences and Engineering, National Central University, Taoyuan 32049, Taiwan;
| | - Changwei W. Wu
- Graduate Institute of Mind Brain and Consciousness, Taipei Medical University, Taipei 11031, Taiwan
- Brain and Consciousness Research Center, Shuang Ho Hospital-Taipei Medical University, New Taipei 23561, Taiwan
- Correspondence: ; Tel.: +886-6638-2736 (ext. 1234)
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19
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Saul MA, He X, Black S, Charles F. A Two-Person Neuroscience Approach for Social Anxiety: A Paradigm With Interbrain Synchrony and Neurofeedback. Front Psychol 2022; 12:568921. [PMID: 35095625 PMCID: PMC8796854 DOI: 10.3389/fpsyg.2021.568921] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2021] [Accepted: 12/06/2021] [Indexed: 12/11/2022] Open
Abstract
Social anxiety disorder has been widely recognised as one of the most commonly diagnosed mental disorders. Individuals with social anxiety disorder experience difficulties during social interactions that are essential in the regular functioning of daily routines; perpetually motivating research into the aetiology, maintenance and treatment methods. Traditionally, social and clinical neuroscience studies incorporated protocols testing one participant at a time. However, it has been recently suggested that such protocols are unable to directly assess social interaction performance, which can be revealed by testing multiple individuals simultaneously. The principle of two-person neuroscience highlights the interpersonal aspect of social interactions that observes behaviour and brain activity from both (or all) constituents of the interaction, rather than analysing on an individual level or an individual observation of a social situation. Therefore, two-person neuroscience could be a promising direction for assessment and intervention of the social anxiety disorder. In this paper, we propose a novel paradigm which integrates two-person neuroscience in a neurofeedback protocol. Neurofeedback and interbrain synchrony, a branch of two-person neuroscience, are discussed in their own capacities for their relationship with social anxiety disorder and relevance to the paradigm. The newly proposed paradigm sets out to assess the social interaction performance using interbrain synchrony between interacting individuals, and to employ a multi-user neurofeedback protocol for intervention of the social anxiety.
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Affiliation(s)
- Marcia A. Saul
- Faculty of Media and Communication, Centre for Digital Entertainment, Bournemouth University, Poole, United Kingdom
| | - Xun He
- Department of Psychology, Faculty of Science and Technology, Bournemouth University, Poole, United Kingdom
- *Correspondence: Xun He
| | - Stuart Black
- Applied Neuroscience Solutions Ltd., Frimley Green, United Kingdom
| | - Fred Charles
- Department of Creative Technology, Faculty of Science and Technology, Bournemouth University, Poole, United Kingdom
- Fred Charles
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20
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Sawicki J, Hartmann L, Bader R, Schöll E. Modelling the perception of music in brain network dynamics. Front Netw Physiol 2022; 2:910920. [PMID: 36926090 PMCID: PMC10013054 DOI: 10.3389/fnetp.2022.910920] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Accepted: 07/11/2022] [Indexed: 11/13/2022]
Abstract
We analyze the influence of music in a network of FitzHugh-Nagumo oscillators with empirical structural connectivity measured in healthy human subjects. We report an increase of coherence between the global dynamics in our network and the input signal induced by a specific music song. We show that the level of coherence depends crucially on the frequency band. We compare our results with experimental data, which also describe global neural synchronization between different brain regions in the gamma-band range in a time-dependent manner correlated with musical large-scale form, showing increased synchronization just before transitions between different parts in a musical piece (musical high-level events). The results also suggest a separation in musical form-related brain synchronization between high brain frequencies, associated with neocortical activity, and low frequencies in the range of dance movements, associated with interactivity between cortical and subcortical regions.
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Affiliation(s)
- Jakub Sawicki
- Potsdam Institute for Climate Impact Research, Potsdam, Germany.,Institut für Musikpädagogik, Universität der Künste Berlin, Berlin, Germany.,Fachhochschule Nordwestschweiz FHNW, Basel, Switzerland.,Institut für Theoretische Physik, Technische Universität Berlin, Berlin, Germany
| | - Lenz Hartmann
- Institute of Systematic Musicology, University of Hamburg, Hamburg, Germany
| | - Rolf Bader
- Institute of Systematic Musicology, University of Hamburg, Hamburg, Germany
| | - Eckehard Schöll
- Potsdam Institute for Climate Impact Research, Potsdam, Germany.,Institut für Theoretische Physik, Technische Universität Berlin, Berlin, Germany.,Bernstein Center for Computational Neuroscience Berlin, Humboldt-Universität, Berlin, Germany
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21
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Kahali S, Raichle ME, Yablonskiy DA. The Role of the Human Brain Neuron-Glia-Synapse Composition in Forming Resting-State Functional Connectivity Networks. Brain Sci 2021; 11:1565. [PMID: 34942867 PMCID: PMC8699258 DOI: 10.3390/brainsci11121565] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2021] [Revised: 11/23/2021] [Accepted: 11/24/2021] [Indexed: 11/17/2022] Open
Abstract
While significant progress has been achieved in studying resting-state functional networks in a healthy human brain and in a wide range of clinical conditions, many questions related to their relationship to the brain's cellular constituents remain. Here, we use quantitative Gradient-Recalled Echo (qGRE) MRI for mapping the human brain cellular composition and BOLD (blood-oxygen level-dependent) MRI to explore how the brain cellular constituents relate to resting-state functional networks. Results show that the BOLD signal-defined synchrony of connections between cellular circuits in network-defined individual functional units is mainly associated with the regional neuronal density, while the between-functional units' connectivity strength is also influenced by the glia and synaptic components of brain tissue cellular constituents. These mechanisms lead to a rather broad distribution of resting-state functional network properties. Visual networks with the highest neuronal density (but lowest density of glial cells and synapses) exhibit the strongest coherence of the BOLD signal as well as the strongest intra-network connectivity. The Default Mode Network (DMN) is positioned near the opposite part of the spectrum with relatively low coherence of the BOLD signal but with a remarkably balanced cellular contents, enabling DMN to have a prominent role in the overall organization of the brain and hierarchy of functional networks.
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Affiliation(s)
- Sayan Kahali
- Department of Radiology, Washington University in Saint Louis, Saint Louis, MO 63110, USA; (S.K.); (M.E.R.)
| | - Marcus E. Raichle
- Department of Radiology, Washington University in Saint Louis, Saint Louis, MO 63110, USA; (S.K.); (M.E.R.)
- Department of Neurology, Washington University in Saint Louis, Saint Louis, MO 63110, USA
| | - Dmitriy A. Yablonskiy
- Department of Radiology, Washington University in Saint Louis, Saint Louis, MO 63110, USA; (S.K.); (M.E.R.)
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22
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Jalalvandi M, Riyahi Alam N, Sharini H, Hashemi H, Nadimi M. Brain Cortical Activation during Imagining of the Wrist Movement Using Functional Near-Infrared Spectroscopy (fNIRS). J Biomed Phys Eng 2021; 11:583-594. [PMID: 34722403 PMCID: PMC8546162 DOI: 10.31661/jbpe.v0i0.1051] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2018] [Accepted: 12/29/2018] [Indexed: 12/04/2022]
Abstract
Background: fNIRS is a useful tool designed to record the changes in the density of blood’s oxygenated hemoglobin (oxyHb) and deoxygenated hemoglobin (deoxyHb) molecules during brain activity.
This method has made it possible to evaluate the hemodynamic changes of the brain during neuronal activity in a completely non-aggressive manner. Objective: The present study has been designed to investigate and evaluate the brain cortex activities during imagining of the execution of wrist motor tasks by comparing fMRI and fNIRS imaging methods. Material and Methods: This novel observational Optical Imaging study aims to investigate the brain motor cortex activity during imagining of the right wrist motor tasks
in vertical and horizontal directions. To perform the study, ten healthy young right-handed volunteers were asked to think about right-hand movements in different
directions according to the designed movement patterns. The required data were collected in two wavelengths, including 845 and 763 nanometers using a 48 channeled fNIRS machine. Results: Analysis of the obtained data showed the brain activity patterns during imagining of the execution of a movement are formed in various points of the motor
cortex in terms of location. Moreover, depending on the direction of the movement, activity plans have distinguishable patterns. The results showed contralateral M1 was
mainly activated during imagining of the motor cortex (p<0.05). Conclusion: The results of our study showed that in brain imaging, it is possible to distinguish between patterns of activities during wrist motion in different directions
using the recorded signals obtained through near-infrared Spectroscopy. The findings of this study can be useful in further studies related to movement control and BCI.
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Affiliation(s)
- Maziar Jalalvandi
- MSc, Department of Medical Physics and Biomedical Engineering, School of Medicine, Tehran University of Medical Sciences (TUMS), Tehran, Iran
| | - Nader Riyahi Alam
- PhD, Department of Medical Physics and Biomedical Engineering, School of Medicine, Tehran University of Medical Sciences (TUMS), Tehran, Iran
- PhD, Medical Pharmaceutical Sciences Research Centre (MPRC), The Institute of Pharmaceutical Sciences, Tehran University of Medical Sciences, Tehran, Iran
| | - Hamid Sharini
- PhD, Department of Medical Physics and Biomedical Engineering, School of Medicine, Kermanshah University of Medical Sciences (KUMS), Kermanshah, Iran
| | - Hasan Hashemi
- MD, Department of Radiology, School of Medicine, Tehran University of Medical Sciences (TUMS), Tehran, Iran
- MD, Advanced Diagnostic and Interventional Radiology Research Centre (ADIR), Tehran University of Medical Sciences (TUMS), Tehran, Iran
| | - Mohadeseh Nadimi
- MSc Student, Department of Medical Physics and Biomedical Engineering, School of Medicine, Tehran University of Medical Sciences (TUMS), Tehran, Iran
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23
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Pezzulo G, Zorzi M, Corbetta M. The secret life of predictive brains: what's spontaneous activity for? Trends Cogn Sci 2021; 25:730-743. [PMID: 34144895 PMCID: PMC8363551 DOI: 10.1016/j.tics.2021.05.007] [Citation(s) in RCA: 63] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2020] [Revised: 05/14/2021] [Accepted: 05/19/2021] [Indexed: 01/23/2023]
Abstract
Brains at rest generate dynamical activity that is highly structured in space and time. We suggest that spontaneous activity, as in rest or dreaming, underlies top-down dynamics of generative models. During active tasks, generative models provide top-down predictive signals for perception, cognition, and action. When the brain is at rest and stimuli are weak or absent, top-down dynamics optimize the generative models for future interactions by maximizing the entropy of explanations and minimizing model complexity. Spontaneous fluctuations of correlated activity within and across brain regions may reflect transitions between 'generic priors' of the generative model: low dimensional latent variables and connectivity patterns of the most common perceptual, motor, cognitive, and interoceptive states. Even at rest, brains are proactive and predictive.
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Affiliation(s)
- Giovanni Pezzulo
- Institute of Cognitive Sciences and Technologies, National Research Council, Roma, Italy.
| | - Marco Zorzi
- Department of General Psychology and Padova Neuroscience Center (PNC), University of Padova, Padova, Italy; IRCCS San Camillo Hospital, Venice, Italy
| | - Maurizio Corbetta
- Department of Neuroscience and Padova Neuroscience Center (PNC), University of Padova, Padova, Italy; Venetian Institute of Molecular Medicine (VIMM), Fondazione Biomedica, Padova, Italy
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24
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Raut RV, Snyder AZ, Mitra A, Yellin D, Fujii N, Malach R, Raichle ME. Global waves synchronize the brain's functional systems with fluctuating arousal. Sci Adv 2021; 7:7/30/eabf2709. [PMID: 34290088 PMCID: PMC8294763 DOI: 10.1126/sciadv.abf2709] [Citation(s) in RCA: 76] [Impact Index Per Article: 25.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/14/2020] [Accepted: 06/04/2021] [Indexed: 05/04/2023]
Abstract
We propose and empirically support a parsimonious account of intrinsic, brain-wide spatiotemporal organization arising from traveling waves linked to arousal. We hypothesize that these waves are the predominant physiological process reflected in spontaneous functional magnetic resonance imaging (fMRI) signal fluctuations. The correlation structure ("functional connectivity") of these fluctuations recapitulates the large-scale functional organization of the brain. However, a unifying physiological account of this structure has so far been lacking. Here, using fMRI in humans, we show that ongoing arousal fluctuations are associated with global waves of activity that slowly propagate in parallel throughout the neocortex, thalamus, striatum, and cerebellum. We show that these waves can parsimoniously account for many features of spontaneous fMRI signal fluctuations, including topographically organized functional connectivity. Last, we demonstrate similar, cortex-wide propagation of neural activity measured with electrocorticography in macaques. These findings suggest that traveling waves spatiotemporally pattern brain-wide excitability in relation to arousal.
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Affiliation(s)
- Ryan V Raut
- Department of Radiology, Washington University, St. Louis, MO 63110, USA.
| | - Abraham Z Snyder
- Department of Radiology, Washington University, St. Louis, MO 63110, USA
- Department of Neurology, Washington University, St. Louis, MO 63110, USA
| | - Anish Mitra
- Department of Psychiatry, Stanford University, Stanford, CA 94305, USA
| | - Dov Yellin
- Department of Neurobiology, Weizmann Institute of Science, 76100 Rehovot, Israel
| | - Naotaka Fujii
- Laboratory for Adaptive Intelligence, RIKEN Brain Science Institute, Wako, Saitama 351-0198, Japan
| | - Rafael Malach
- Department of Neurobiology, Weizmann Institute of Science, 76100 Rehovot, Israel
| | - Marcus E Raichle
- Department of Radiology, Washington University, St. Louis, MO 63110, USA
- Department of Neurology, Washington University, St. Louis, MO 63110, USA
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25
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Mann K, Deny S, Ganguli S, Clandinin TR. Coupling of activity, metabolism and behaviour across the Drosophila brain. Nature 2021; 593:244-248. [PMID: 33911283 PMCID: PMC10544789 DOI: 10.1038/s41586-021-03497-0] [Citation(s) in RCA: 40] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2020] [Accepted: 03/26/2021] [Indexed: 12/21/2022]
Abstract
Coordinated activity across networks of neurons is a hallmark of both resting and active behavioural states in many species1-5. These global patterns alter energy metabolism over seconds to hours, which underpins the widespread use of oxygen consumption and glucose uptake as proxies of neural activity6,7. However, whether changes in neural activity are causally related to metabolic flux in intact circuits on the timescales associated with behaviour is unclear. Here we combine two-photon microscopy of the fly brain with sensors that enable the simultaneous measurement of neural activity and metabolic flux, across both resting and active behavioural states. We demonstrate that neural activity drives changes in metabolic flux, creating a tight coupling between these signals that can be measured across brain networks. Using local optogenetic perturbation, we demonstrate that even transient increases in neural activity result in rapid and persistent increases in cytosolic ATP, which suggests that neuronal metabolism predictively allocates resources to anticipate the energy demands of future activity. Finally, our studies reveal that the initiation of even minimal behavioural movements causes large-scale changes in the pattern of neural activity and energy metabolism, which reveals a widespread engagement of the brain. As the relationship between neural activity and energy metabolism is probably evolutionarily ancient and highly conserved, our studies provide a critical foundation for using metabolic proxies to capture changes in neural activity.
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Affiliation(s)
- Kevin Mann
- Department of Neurobiology, Stanford University, Stanford, CA, USA
| | - Stephane Deny
- Department of Applied Physics, Stanford University, Stanford, CA, USA
| | - Surya Ganguli
- Department of Neurobiology, Stanford University, Stanford, CA, USA.
- Department of Applied Physics, Stanford University, Stanford, CA, USA.
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26
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Bittencourt-Villalpando M, van der Horn HJ, Maurits NM, van der Naalt J. Disentangling the effects of age and mild traumatic brain injury on brain network connectivity: A resting state fMRI study. Neuroimage Clin 2020; 29:102534. [PMID: 33360020 PMCID: PMC7770973 DOI: 10.1016/j.nicl.2020.102534] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2020] [Revised: 11/20/2020] [Accepted: 12/12/2020] [Indexed: 11/19/2022]
Abstract
INTRODUCTION Cognitive complaints are common shortly after mild traumatic brain injury (mTBI) but may persist up to years. Age-related cognitive decline can worsen these symptoms. However, effects of age on mTBI sequelae have scarcely been investigated. METHODS Fifty-four mTBI patients (median age: 35 years, range 19-64 years, 67% male) and twenty age- and sex-matched healthy controls were studied using resting state functional magnetic resonance imaging in the sub-acute phase. Independent component analysis was used to identify intrinsic connectivity networks (ICNs). A multivariate approach was adopted to evaluate the effects of age and group on the ICNs in terms of (static) functional network connectivity (FNC), intensities of spatial maps (SMs) and time-course spectral power (TC). RESULTS We observed significant age-related changes for a) FNC: changes between 10 pairs of ICNs, mostly involving the default mode (DM) and/or the cognitive-control (CC) domains; b) SMs: intensity decrease in clusters across three domains and intensity increase in clusters across two domains, including the CC but not the DM and c) TC: spectral power decrease within the 0-0.15 Hz range and increase within the 0.20-0.25 Hz range for increasing age within networks located in frontal areas, including the anterior DM. Groups only differed for TC within the 0.065-0.10 Hz range in the cerebellar ICN and no age × group interaction effect was found. CONCLUSIONS We showed robust effects of age on connectivity between and within ICNs that are associated with cognitive functioning. Differences between mTBI patients and controls were only found for activity in the cerebellar network, increasingly recognized to participate in cognition. Our results suggest that to allow for capturing the true effects related to mTBI and its effects on cognitive functioning, age should be included as a covariate in mTBI studies, in addition to age-matching groups.
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Affiliation(s)
- M Bittencourt-Villalpando
- University of Groningen, University Medical Center Groningen, Department of Neurology AB51, 9700RB Groningen, The Netherlands.
| | - H J van der Horn
- University of Groningen, University Medical Center Groningen, Department of Neurology AB51, 9700RB Groningen, The Netherlands
| | - N M Maurits
- University of Groningen, University Medical Center Groningen, Department of Neurology AB51, 9700RB Groningen, The Netherlands
| | - J van der Naalt
- University of Groningen, University Medical Center Groningen, Department of Neurology AB51, 9700RB Groningen, The Netherlands
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27
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Abstract
Multimodal evidence suggests that brain regions accumulate information over timescales that vary according to anatomical hierarchy. Thus, these experimentally defined "temporal receptive windows" are longest in cortical regions that are distant from sensory input. Interestingly, spontaneous activity in these regions also plays out over relatively slow timescales (i.e., exhibits slower temporal autocorrelation decay). These findings raise the possibility that hierarchical timescales represent an intrinsic organizing principle of brain function. Here, using resting-state functional MRI, we show that the timescale of ongoing dynamics follows hierarchical spatial gradients throughout human cerebral cortex. These intrinsic timescale gradients give rise to systematic frequency differences among large-scale cortical networks and predict individual-specific features of functional connectivity. Whole-brain coverage permitted us to further investigate the large-scale organization of subcortical dynamics. We show that cortical timescale gradients are topographically mirrored in striatum, thalamus, and cerebellum. Finally, timescales in the hippocampus followed a posterior-to-anterior gradient, corresponding to the longitudinal axis of increasing representational scale. Thus, hierarchical dynamics emerge as a global organizing principle of mammalian brains.
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28
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Okun M, Steinmetz NA, Lak A, Dervinis M, Harris KD. Distinct Structure of Cortical Population Activity on Fast and Infraslow Timescales. Cereb Cortex 2020; 29:2196-2210. [PMID: 30796825 PMCID: PMC6458908 DOI: 10.1093/cercor/bhz023] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2018] [Revised: 01/26/2019] [Accepted: 01/28/2019] [Indexed: 12/20/2022] Open
Abstract
Cortical activity is organized across multiple spatial and temporal scales. Most research on the dynamics of neuronal spiking is concerned with timescales of 1 ms–1 s, and little is known about spiking dynamics on timescales of tens of seconds and minutes. Here, we used frequency domain analyses to study the structure of individual neurons’ spiking activity and its coupling to local population rate and to arousal level across 0.01–100 Hz frequency range. In mouse medial prefrontal cortex, the spiking dynamics of individual neurons could be quantitatively captured by a combination of interspike interval and firing rate power spectrum distributions. The relative strength of coherence with local population often differed across timescales: a neuron strongly coupled to population rate on fast timescales could be weakly coupled on slow timescales, and vice versa. On slow but not fast timescales, a substantial proportion of neurons showed firing anticorrelated with the population. Infraslow firing rate changes were largely determined by arousal rather than by local factors, which could explain the timescale dependence of individual neurons’ population coupling strength. These observations demonstrate how neurons simultaneously partake in fast local dynamics, and slow brain-wide dynamics, extending our understanding of infraslow cortical activity beyond the mesoscale resolution of fMRI.
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Affiliation(s)
- Michael Okun
- Centre for Systems Neuroscience and Department of Neuroscience, Psychology and Behaviour, University of Leicester, Leicester, UK.,Institute of Neurology, University College London, London, UK
| | | | - Armin Lak
- Institute of Neurology, University College London, London, UK
| | - Martynas Dervinis
- Centre for Systems Neuroscience and Department of Neuroscience, Psychology and Behaviour, University of Leicester, Leicester, UK
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29
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Raut RV, Mitra A, Marek S, Ortega M, Snyder AZ, Tanenbaum A, Laumann TO, Dosenbach NUF, Raichle ME. Organization of Propagated Intrinsic Brain Activity in Individual Humans. Cereb Cortex 2020; 30:1716-1734. [PMID: 31504262 PMCID: PMC7132930 DOI: 10.1093/cercor/bhz198] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2019] [Revised: 07/09/2019] [Accepted: 08/07/2019] [Indexed: 12/11/2022] Open
Abstract
Spontaneous infra-slow (<0.1 Hz) fluctuations in functional magnetic resonance imaging (fMRI) signals are temporally correlated within large-scale functional brain networks, motivating their use for mapping systems-level brain organization. However, recent electrophysiological and hemodynamic evidence suggest state-dependent propagation of infra-slow fluctuations, implying a functional role for ongoing infra-slow activity. Crucially, the study of infra-slow temporal lag structure has thus far been limited to large groups, as analyzing propagation delays requires extensive data averaging to overcome sampling variability. Here, we use resting-state fMRI data from 11 extensively-sampled individuals to characterize lag structure at the individual level. In addition to stable individual-specific features, we find spatiotemporal topographies in each subject similar to the group average. Notably, we find a set of early regions that are common to all individuals, are preferentially positioned proximal to multiple functional networks, and overlap with brain regions known to respond to diverse behavioral tasks-altogether consistent with a hypothesized ability to broadly influence cortical excitability. Our findings suggest that, like correlation structure, temporal lag structure is a fundamental organizational property of resting-state infra-slow activity.
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Affiliation(s)
- Ryan V Raut
- Department of Radiology, Washington University, St. Louis, MO 63110, USA
| | - Anish Mitra
- Department of Radiology, Washington University, St. Louis, MO 63110, USA
| | - Scott Marek
- Department of Psychiatry, Washington University, St. Louis, MO 63110, USA
| | - Mario Ortega
- Department of Neurology, Washington University, St. Louis, MO 63110, USA
| | - Abraham Z Snyder
- Department of Radiology, Washington University, St. Louis, MO 63110, USA
- Department of Neurology, Washington University, St. Louis, MO 63110, USA
| | - Aaron Tanenbaum
- Department of Neurology, Washington University, St. Louis, MO 63110, USA
| | - Timothy O Laumann
- Department of Psychiatry, Washington University, St. Louis, MO 63110, USA
| | - Nico U F Dosenbach
- Department of Radiology, Washington University, St. Louis, MO 63110, USA
- Department of Neurology, Washington University, St. Louis, MO 63110, USA
- Department of Pediatrics, Washington University, St. Louis, MO 63110, USA
- Department of Biomedical Engineering, Washington University, St. Louis, MO 63110, USA
- Department of Occupational Therapy, Washington University, St. Louis, MO 63110, USA
| | - Marcus E Raichle
- Department of Radiology, Washington University, St. Louis, MO 63110, USA
- Department of Neurology, Washington University, St. Louis, MO 63110, USA
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30
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Chen W, Park K, Pan Y, Koretsky AP, Du C. Interactions between stimuli-evoked cortical activity and spontaneous low frequency oscillations measured with neuronal calcium. Neuroimage 2020; 210:116554. [PMID: 31972283 DOI: 10.1016/j.neuroimage.2020.116554] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2019] [Revised: 12/07/2019] [Accepted: 01/14/2020] [Indexed: 02/06/2023] Open
Abstract
Spontaneous brain activity has been widely used to map brain connectivity. The interactions between task-evoked brain responses and the spontaneous cortical oscillations, especially within the low frequency range of ~0.1 Hz, are not fully understood. Trial-to-trial variabilities in brain's response to sensory stimuli and the ability for brain to detect under noisy conditions suggest an appreciable impact of the brain state. Using a multimodality imaging platform, we simultaneously imaged neuronal Ca2+ and cerebral hemodynamics at baseline and in response to single-pulse forepaw stimuli in rat's somatosensory cortex. The high sensitivity of this system enables detection of responses to very weak and strong stimuli and real time determination of low frequency oscillations without averaging. Results show that the ongoing neuronal oscillations inversely modulate Ca2+ transients evoked by sensory stimuli. High intensity stimuli reset the spontaneous neuronal oscillations to an unpreferable excitability following the stimulus. Cerebral hemodynamic responses also inversely interact with the spontaneous hemodynamic oscillations, correlating with the neuronal Ca2+ transient changes. The results reveal competing interactions between spontaneous oscillations and stimulation-evoked brain activities in somatosensory cortex and the resultant hemodynamics.
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Affiliation(s)
- Wei Chen
- Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY, 11794, USA
| | - Kicheon Park
- Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY, 11794, USA
| | - Yingtian Pan
- Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY, 11794, USA
| | - Alan P Koretsky
- Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, 20892, USA.
| | - Congwu Du
- Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY, 11794, USA.
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31
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Abstract
Slow wave activity (SWA; the EEG power between 0.5 and 4 Hz during non-rapid eye movement sleep [NREM]) is the best electrophysiological marker of sleep need; SWA dissipates across the night and increases following sleep deprivation. In addition to these well-documented homeostatic SWA trends, SWA exhibits extensive variability across shorter timescales (seconds to minutes) and between local cortical regions. The physiological underpinnings of SWA variability, however, remain poorly characterized. In male Sprague-Dawley rats, we observed that SWA exhibits pronounced infraslow fluctuations (~40- to 120-s periods) that are coordinated across disparate cortical locations. Peaks in SWA across infraslow cycles were associated with increased slope, amplitude, and duration of individual slow waves and a reduction in the total number of waves and proportion of multipeak waves. Using a freely available data set comprised of extracellular unit recordings during consolidated NREM episodes in male Long-Evans rats, we further show that infraslow SWA does not appear to arise as a consequence of firing rate modulation of putative excitatory or inhibitory neurons. Instead, infraslow SWA was associated with alterations in neuronal synchrony surrounding "On"/"Off" periods and changes in the number and duration of "Off" periods. Collectively, these data provide a mechanism by which SWA can be coordinated across disparate cortical locations and thereby connect local and global expression of this patterned neuronal activity. In doing so, infraslow SWA may contribute to the regulation of cortical circuits during sleep and thereby play a critical role in sleep function.
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Affiliation(s)
- Michael B Dash
- Department of Psychology, Middlebury College, Middlebury, VT
- Program in Neuroscience, Middlebury College, Middlebury, VT
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32
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Abstract
Emotions are often assumed to manifest in subcortical limbic and brainstem structures. While these areas are clearly important for representing affect (e.g., valence and arousal), we propose that the default mode network (DMN) is additionally important for constructing discrete emotional experiences (of anger, fear, disgust, etc.). Findings from neuroimaging studies, invasive electrical stimulation studies, and lesion studies support this proposal. Importantly, our framework builds on a constructionist theory of emotion to explain how instances involving diverse physiological and behavioral patterns can be conceptualized as belonging to the same emotion category. We argue that this ability requires abstraction (from concrete features to broad mental categories), which the DMN is well positioned to support, and we make novel predictions from our proposed framework.
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Affiliation(s)
- Ajay B Satpute
- Department of Psychology, Northeastern University, Boston, MA, USA.
| | - Kristen A Lindquist
- Department of Psychology and Neuroscience, University of North Carolina, Chapel Hill, NC, USA
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33
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Gutierrez-Barragan D, Basson MA, Panzeri S, Gozzi A. Infraslow State Fluctuations Govern Spontaneous fMRI Network Dynamics. Curr Biol 2019; 29:2295-2306.e5. [PMID: 31303490 PMCID: PMC6657681 DOI: 10.1016/j.cub.2019.06.017] [Citation(s) in RCA: 72] [Impact Index Per Article: 14.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2019] [Revised: 04/19/2019] [Accepted: 06/07/2019] [Indexed: 01/11/2023]
Abstract
Spontaneous brain activity as assessed with resting-state fMRI exhibits rich spatiotemporal structure. However, the principles by which brain-wide patterns of spontaneous fMRI activity reconfigure and interact with each other remain unclear. We used a framewise clustering approach to map spatiotemporal dynamics of spontaneous fMRI activity with voxel resolution in the resting mouse brain. We show that brain-wide patterns of fMRI co-activation can be reliably mapped at the group and subject level, defining a restricted set of recurring brain states characterized by rich network structure. Importantly, we document that the identified fMRI states exhibit contrasting patterns of functional activity and coupled infraslow network dynamics, with each network state occurring at specific phases of global fMRI signal fluctuations. Finally, we show that autism-associated genetic alterations entail the engagement of atypical functional states and altered infraslow network dynamics. Our results reveal a novel set of fundamental principles guiding the spatiotemporal organization of resting-state fMRI activity and its disruption in brain disorders.
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Affiliation(s)
- Daniel Gutierrez-Barragan
- Neural Computation Laboratory, Istituto Italiano di Tecnologia, Center for Neuroscience and Cognitive Systems @ UniTn, 38068 Rovereto (TN), Italy; Center for Mind/Brain Sciences, University of Trento, 38068 Rovereto (TN), Italy; Functional Neuroimaging Laboratory, Istituto Italiano di Tecnologia, Center for Neuroscience and Cognitive Systems @ UniTn, 38068 Rovereto (TN), Italy
| | - M Albert Basson
- Centre for Craniofacial and Regenerative Biology and MRC Centre for Neurodevelopmental Disorders, King's College London, London SE1 9RT, UK
| | - Stefano Panzeri
- Neural Computation Laboratory, Istituto Italiano di Tecnologia, Center for Neuroscience and Cognitive Systems @ UniTn, 38068 Rovereto (TN), Italy.
| | - Alessandro Gozzi
- Functional Neuroimaging Laboratory, Istituto Italiano di Tecnologia, Center for Neuroscience and Cognitive Systems @ UniTn, 38068 Rovereto (TN), Italy.
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34
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Jiang Y, Song L, Li X, Zhang Y, Chen Y, Jiang S, Hou C, Yao D, Wang X, Luo C. Dysfunctional white-matter networks in medicated and unmedicated benign epilepsy with centrotemporal spikes. Hum Brain Mapp 2019; 40:3113-3124. [PMID: 30937973 PMCID: PMC6865396 DOI: 10.1002/hbm.24584] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2019] [Revised: 03/11/2019] [Accepted: 03/18/2019] [Indexed: 12/18/2022] Open
Abstract
Benign epilepsy with centrotemporal spikes (BECT) is the most common childhood idiopathic focal epilepsy syndrome, which characterized with white-matter abnormalities in the rolandic cortex. Although diffusion tensor imaging research could characterize white-matter structural architecture, it cannot detect neural activity or white-matter functions. Recent studies demonstrated the functional organization of white-matter by using functional magnetic resonance imaging (fMRI), suggesting that it is feasible to investigate white-matter dysfunctions in BECT. Resting-state fMRI data were collected from 24 new-onset drug-naive (unmedicated [NMED]), 21 medicated (MED) BECT patients, and 27 healthy controls (HC). Several white-matter functional networks were obtained using a clustering analysis on voxel-by-voxel correlation profiles. Subsequently, conventional functional connectivity (FC) was calculated in four frequency sub-bands (Slow-5:0.01-0.027, Slow-4:0.027-0.073, Slow-3:0.073-0.198, and Slow-2:0.198-0.25 Hz). We also employed a functional covariance connectivity (FCC) to estimate the covariant relationship between two white-matter networks based on their correlations with multiple gray-matter regions. Compared with HC, the NMED showed increased FC and/or FCC in rolandic network (RN) and precentral/postcentral network, and decreased FC and/or FCC in dorsal frontal network, while these alterations were not observed in the MED group. Moreover, the changes exhibited frequency-specific properties. Specifically, only two alterations were shared in at least two frequency bands. Most of these alterations were observed in the frequency bands of Slow-3 and Slow-4. This study provided further support on the existence of white-matter functional networks which exhibited frequency-specific properties, and extended abnormalities of rolandic area from the perspective of white-matter dysfunction in BECT.
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Affiliation(s)
- Yuchao Jiang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduPeople's Republic of China
| | - Li Song
- Neurology DepartmentAffiliated Hospital of North Sichuan Medical College North Sichuan Medical CollegeNanchongChina
| | - Xuan Li
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduPeople's Republic of China
| | - Yaodan Zhang
- Neurology DepartmentAffiliated Hospital of North Sichuan Medical College North Sichuan Medical CollegeNanchongChina
- Chengdu University of Traditional Chinese MedicineChengdu, SichuanChina
| | - Yan Chen
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduPeople's Republic of China
| | - Sisi Jiang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduPeople's Republic of China
| | - Changyue Hou
- Neurology DepartmentAffiliated Hospital of North Sichuan Medical College North Sichuan Medical CollegeNanchongChina
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduPeople's Republic of China
| | - Xiaoming Wang
- Neurology DepartmentAffiliated Hospital of North Sichuan Medical College North Sichuan Medical CollegeNanchongChina
| | - Cheng Luo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduPeople's Republic of China
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35
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Abstract
Event-related fMRI have been widely used in locating brain regions which respond to specific tasks. However, activities of brain regions which modulate or indirectly participate in the response to a specific task are not event-related. Event-related fMRI can't locate these regulatory regions, detrimental to the integrity of the result that event-related fMRI revealed. Direct-current EEG shifts (DC shifts) have been found linked to the inner brain activity, a fusion DC shifts-fMRI method may have the ability to reveal a more complete response of the brain. In this study, we used DC shifts-fMRI to verify that even when responding to a very simple task, (1) The response of the brain is more complicated than event-related fMRI generally revealed and (2) DC shifts-fMRI have the ability of revealing brain regions whose responses are not in event-related way. We used a classical and simple paradigm which is often used in auditory cortex tonotopic mapping. Data were recorded from 50 subjects (25 male, 25 female) who were presented with randomly presented pure tone sequences with six different frequencies (200, 400, 800, 1,600, 3,200, 6,400 Hz). Our traditional fMRI results are consistent with previous findings that the activations are concentrated on the auditory cortex. Our DC shifts-fMRI results showed that the cingulate-caudate-thalamus network which underpins sustained attention is positively activated while the dorsal attention network and the right middle frontal gyrus which underpin attention orientation are negatively activated. The regional-specific correlations between DC shifts and brain networks indicate the complexity of the response of the brain even to a simple task and that the DC shifts can effectively reflect these non-event-related inner brain activities.
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Affiliation(s)
- Qiang Li
- Education Science College, Guizhou Normal College, Guiyang, China
| | - Guangyuan Liu
- College of Electronic and Information Engineering, Southwest University, Chongqing, China.,Chongqing Collaborative Innovation Center for Brain Science, Southwest University, Chongqing, China
| | - Guangjie Yuan
- College of Electronic and Information Engineering, Southwest University, Chongqing, China
| | - Gaoyuan Wang
- College of Music, Southwest University, Chongqing, China
| | - Zonghui Wu
- Southwest University Hospital, Southwest University, Chongqing, China
| | - Xingcong Zhao
- College of Electronic and Information Engineering, Southwest University, Chongqing, China
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36
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Hare SM, Ford JM, Mathalon DH, Damaraju E, Bustillo J, Belger A, Lee HJ, Mueller BA, Lim KO, Brown GG, Preda A, van Erp TGM, Potkin SG, Calhoun VD, Turner JA. Salience-Default Mode Functional Network Connectivity Linked to Positive and Negative Symptoms of Schizophrenia. Schizophr Bull 2019; 45:892-901. [PMID: 30169884 PMCID: PMC6581131 DOI: 10.1093/schbul/sby112] [Citation(s) in RCA: 62] [Impact Index Per Article: 12.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
Schizophrenia is a complex, debilitating mental disorder characterized by wide-ranging symptoms including delusions, hallucinations (so-called positive symptoms), and impaired motor and speech/language production (so-called negative symptoms). Salience-monitoring theorists propose that abnormal functional communication between the salience network (SN) and default mode network (DMN) begets positive and negative symptoms of schizophrenia, yet prior studies have predominately reported links between disrupted SN/DMN functional communication and positive symptoms. It remains unclear whether disrupted SN/DMN functional communication explains (1) solely positive symptoms or (2) both positive and negative symptoms of schizophrenia. To address this question, we incorporate time-lag-shifted functional network connectivity (FNC) analyses that explored coherence of the resting-state functional magnetic resonance imaging signal of 3 networks (anterior DMN, posterior DMN, and SN) with fixed time lags introduced between network time series (1 TR = 2 s; 2 TR = 4 s). Multivariate linear regression analysis revealed that severity of disordered thought and attentional deficits were negatively associated with 2 TR-shifted FNC between anterior DMN and posterior DMN. Meanwhile, severity of flat affect and bizarre behavior were positively associated with 1 TR-shifted FNC between anterior DMN and SN. These results provide support favoring the hypothesis that lagged SN/DMN functional communication is associated with both positive and negative symptoms of schizophrenia.
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Affiliation(s)
- Stephanie M Hare
- Neuroscience Institute, Georgia State University, Atlanta, GA,To whom correspondence should be addressed; Neuroscience Institute, Georgia State University, PO Box 5030, Atlanta, GA 30302-5030, USA; tel: 262-364-7427, fax: 404-413-5446, e-mail:
| | - Judith M Ford
- Psychiatry Service, San Francisco VA Medical Center, San Francisco, CA,Department of Psychiatry, University of California, San Francisco, CA
| | - Daniel H Mathalon
- Psychiatry Service, San Francisco VA Medical Center, San Francisco, CA,Department of Psychiatry, University of California, San Francisco, CA
| | | | - Juan Bustillo
- Department of Psychiatry and Behavioral Sciences, The University of New Mexico, Albuquerque, NM
| | - Aysenil Belger
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Hyo Jong Lee
- Division of Computer Science and Engineering, CAIIT, Chonbuk National University, Jeonju, Republic of Korea
| | - Bryon A Mueller
- Department of Psychiatry, University of Minnesota, Minneapolis, MN
| | - Kelvin O Lim
- Department of Psychiatry, University of Minnesota, Minneapolis, MN,Geriatric Research, Education and Clinical Center (GRECC), Minneapolis VA Health Care System, Minneapolis, MN
| | - Gregory G Brown
- Department of Psychiatry, School of Medicine, University of California San Diego, San Diego, CA
| | - Adrian Preda
- Department of Psychiatry and Human Behavior, University of California, Irvine, Irvine, CA
| | - Theo G M van Erp
- Department of Psychiatry and Human Behavior, University of California, Irvine, Irvine, CA
| | - Steven G Potkin
- Department of Psychiatry and Human Behavior, University of California, Irvine, Irvine, CA
| | - Vince D Calhoun
- The Mind Research Network, Albuquerque, NM,Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, NM
| | - Jessica A Turner
- Neuroscience Institute, Georgia State University, Atlanta, GA,The Mind Research Network, Albuquerque, NM,Department of Psychology, Georgia State University, Atlanta, GA
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37
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Jo HG, Naranjo JR, Hinterberger T, Winter U, Schmidt S. Phase synchrony in slow cortical potentials is decreased in both expert and trained novice meditators. Neurosci Lett 2019; 701:142-5. [PMID: 30802464 DOI: 10.1016/j.neulet.2019.02.035] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2018] [Revised: 02/12/2019] [Accepted: 02/21/2019] [Indexed: 11/24/2022]
Abstract
Neuronal interactions coupled by phase synchronization have been studied in a wide range of frequency bands, but fluctuations below the delta frequency have often been neglected. In the present study, phase synchrony in slow cortical potentials (SCPs, 0.01-0.1 Hz) was examined during two different mental states; a resting state and a breath-focused mindfulness meditation. SCP phase synchrony in 9 long-term expert meditators (on average 22 years of experience) were compared with the data obtained from 11 novices. Additionally, after the novices attended an 8-week mindfulness-based stress reduction (MBSR) program, SCP phase synchrony was measured again. While expert meditators and novices exhibited the same amount of SCP phase synchrony in the resting state, decreased synchronization was found during meditation among expert meditators as well as novices who had participated in the MBSR program (but not prior to the program). These findings suggest that phase synchrony in slow cortical activity is context-dependent and could provide crucial information in the study of the human mind.
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Abstract
Processing units are interconnected in the visual system, where a sensory organ and downstream cortical regions communicate through hierarchical connections, and local sites within the regions communicate through horizontal connections. In such networks, neural activities at local sites are likely to influence one another in complex ways and thus are intricately correlated. Recognizing the functional importance of correlated activity in sensory representation, spontaneous activities have been studied via diverse local or global measures in various time scales. Here, measuring functional magnetic resonance imaging (fMRI) signals in human early visual cortex, we explored systematic patterns that govern the correlated activities arising spontaneously. Specifically, guided by previously identified biases in anatomical connection patterns, we characterized all possible pairs of gray matter sites in 3 relational factors: "retinotopic distance," "cortical distance," and "stimulus tuning similarity." By evaluating and comparing the unique contributions of these factors to the correlated activity, we found that tuning similarity factors overrode distance factors in accounting for the structure of correlated fMRI activity both within and between V1, V2, and V3, irrespective of the presence or degree of visual stimulation. Our findings indicate that the early human visual cortex is intrinsically organized as a network tuned to the stimulus features.
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Affiliation(s)
- Jungwon Ryu
- Department of Brain and Cognitive Sciences, Seoul National University, Seoul 151-742, Republic of Korea
| | - Sang-Hun Lee
- Department of Brain and Cognitive Sciences, Seoul National University, Seoul 151-742, Republic of Korea
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Raut RV, Mitra A, Snyder AZ, Raichle ME. On time delay estimation and sampling error in resting-state fMRI. Neuroimage 2019; 194:211-227. [PMID: 30902641 DOI: 10.1016/j.neuroimage.2019.03.020] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2018] [Revised: 01/26/2019] [Accepted: 03/08/2019] [Indexed: 01/21/2023] Open
Abstract
Accumulating evidence indicates that resting-state functional magnetic resonance imaging (rsfMRI) signals correspond to propagating electrophysiological infra-slow activity (<0.1 Hz). Thus, pairwise correlations (zero-lag functional connectivity (FC)) and temporal delays among regional rsfMRI signals provide useful, complementary descriptions of spatiotemporal structure in infra-slow activity. However, the slow nature of fMRI signals implies that practical scan durations cannot provide sufficient independent temporal samples to stabilize either of these measures. Here, we examine factors affecting sampling variability in both time delay estimation (TDE) and FC. Although both TDE and FC accuracy are highly sensitive to data quantity, we use surrogate fMRI time series to study how the former is additionally related to the magnitude of a given pairwise correlation and, to a lesser extent, the temporal sampling rate. These contingencies are further explored in real data comprising 30-min rsfMRI scans, where sampling error (i.e., limited accuracy owing to insufficient data quantity) emerges as a significant but underappreciated challenge to FC and, even more so, to TDE. Exclusion of high-motion epochs exacerbates sampling error; thus, both sides of the bias-variance (or data quality-quantity) tradeoff associated with data exclusion should be considered when analyzing rsfMRI data. Finally, we present strategies for TDE in motion-corrupted data, for characterizing sampling error in TDE and FC, and for mitigating the influence of sampling error on lag-based analyses.
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Affiliation(s)
- Ryan V Raut
- Departments of Radiology, Washington University, St. Louis, MO, 63110, USA.
| | - Anish Mitra
- Departments of Radiology, Washington University, St. Louis, MO, 63110, USA
| | - Abraham Z Snyder
- Departments of Radiology, Washington University, St. Louis, MO, 63110, USA; Departments of Neurology, Washington University, St. Louis, MO, 63110, USA
| | - Marcus E Raichle
- Departments of Radiology, Washington University, St. Louis, MO, 63110, USA; Departments of Neurology, Washington University, St. Louis, MO, 63110, USA
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40
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Abbas A, Belloy M, Kashyap A, Billings J, Nezafati M, Schumacher EH, Keilholz S. Quasi-periodic patterns contribute to functional connectivity in the brain. Neuroimage 2019; 191:193-204. [PMID: 30753928 DOI: 10.1016/j.neuroimage.2019.01.076] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2018] [Revised: 01/07/2019] [Accepted: 01/30/2019] [Indexed: 02/03/2023] Open
Abstract
Functional connectivity is widely used to study the coordination of activity between brain regions over time. Functional connectivity in the default mode and task positive networks is particularly important for normal brain function. However, the processes that give rise to functional connectivity in the brain are not fully understood. It has been postulated that low-frequency neural activity plays a key role in establishing the functional architecture of the brain. Quasi-periodic patterns (QPPs) are a reliably observable form of low-frequency neural activity that involve the default mode and task positive networks. Here, QPPs from resting-state and working memory task-performing individuals were acquired. The spatiotemporal pattern, strength, and frequency of the QPPs between the two groups were compared and the contribution of QPPs to functional connectivity in the brain was measured. In task-performing individuals, the spatiotemporal pattern of the QPP changes, particularly in task-relevant regions, and the QPP tends to occur with greater strength and frequency. Differences in the QPPs between the two groups could partially account for the variance in functional connectivity between resting-state and task-performing individuals. The QPPs contribute strongly to connectivity in the default mode and task positive networks and to the strength of anti-correlation seen between the two networks. Many of the connections affected by QPPs are also disrupted during several neurological disorders. These findings contribute to understanding the dynamic neural processes that give rise to functional connectivity in the brain and how they may be disrupted during disease.
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Affiliation(s)
- Anzar Abbas
- Neuroscience, Emory University, 1760 Haygood Dr NE Suite W-200, Atlanta, GA, 30322, USA
| | - Michaël Belloy
- Bio-Imaging Lab, University of Antwerp, Universiteitsplein 1, 2610, Wilrijk, Antwerp, Belgium
| | - Amrit Kashyap
- Biomedical Engineering, Emory University and Georgia Institute of Technology, 1760, Haygood Dr NE Suite, W-200, Atlanta, GA, 30322, USA
| | - Jacob Billings
- Neuroscience, Emory University, 1760 Haygood Dr NE Suite W-200, Atlanta, GA, 30322, USA
| | - Maysam Nezafati
- Biomedical Engineering, Emory University and Georgia Institute of Technology, 1760, Haygood Dr NE Suite, W-200, Atlanta, GA, 30322, USA
| | - Eric H Schumacher
- School of Psychology, Georgia Institute of Technology, 654 Cherry Street, Atlanta, GA 30332, USA
| | - Shella Keilholz
- Neuroscience, Emory University, 1760 Haygood Dr NE Suite W-200, Atlanta, GA, 30322, USA; Biomedical Engineering, Emory University and Georgia Institute of Technology, 1760, Haygood Dr NE Suite, W-200, Atlanta, GA, 30322, USA.
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41
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La Rocca D, Zilber N, Abry P, van Wassenhove V, Ciuciu P. Self-similarity and multifractality in human brain activity: A wavelet-based analysis of scale-free brain dynamics. J Neurosci Methods 2018; 309:175-187. [DOI: 10.1016/j.jneumeth.2018.09.010] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2018] [Revised: 09/06/2018] [Accepted: 09/06/2018] [Indexed: 12/16/2022]
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Abstract
Research on brain oscillations has brought up a picture of coupled oscillators. Some of the most important questions that will be analyzed are, how many frequencies are there, what are the coupling principles, what their functional meaning is, and whether body oscillations follow similar coupling principles. It is argued that physiologically, two basic coupling principles govern brain as well as body oscillations: (i) amplitude (envelope) modulation between any frequencies m and n, where the phase of the slower frequency m modulates the envelope of the faster frequency n, and (ii) phase coupling between m and n, where the frequency of n is a harmonic multiple of m. An analysis of the center frequency of traditional frequency bands and their coupling principles suggest a binary hierarchy of frequencies. This principle leads to the foundation of the binary hierarchy brain body oscillation theory. Its central hypotheses are that the frequencies of body oscillations can be predicted from brain oscillations and that brain and body oscillations are aligned to each other. The empirical evaluation of the predicted frequencies for body oscillations is discussed on the basis of findings for heart rate, heart rate variability, breathing frequencies, fluctuations in the BOLD signal, and other body oscillations. The conclusion is that brain and many body oscillations can be described by a single system, where the cross talk - reflecting communication - within and between brain and body oscillations is governed by m : n phase to envelope and phase to phase coupling.
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Affiliation(s)
- Wolfgang Klimesch
- Centre of Cognitive NeuroscienceUniversity of SalzburgSalzburgAustria
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43
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Belloy ME, Shah D, Abbas A, Kashyap A, Roßner S, Van der Linden A, Keilholz SD, Keliris GA, Verhoye M. Quasi-Periodic Patterns of Neural Activity improve Classification of Alzheimer's Disease in Mice. Sci Rep 2018; 8:10024. [PMID: 29968786 PMCID: PMC6030071 DOI: 10.1038/s41598-018-28237-9] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2018] [Accepted: 06/14/2018] [Indexed: 12/17/2022] Open
Abstract
Resting state (rs)fMRI allows measurement of brain functional connectivity and has identified default mode (DMN) and task positive (TPN) network disruptions as promising biomarkers for Alzheimer's disease (AD). Quasi-periodic patterns (QPPs) of neural activity describe recurring spatiotemporal patterns that display DMN with TPN anti-correlation. We reasoned that QPPs could provide new insights into AD network dysfunction and improve disease diagnosis. We therefore used rsfMRI to investigate QPPs in old TG2576 mice, a model of amyloidosis, and age-matched controls. Multiple QPPs were determined and compared across groups. Using linear regression, we removed their contribution from the functional scans and assessed how they reflected functional connectivity. Lastly, we used elastic net regression to determine if QPPs improved disease classification. We present three prominent findings: (1) Compared to controls, TG2576 mice were marked by opposing neural dynamics in which DMN areas were anti-correlated and displayed diminished anti-correlation with the TPN. (2) QPPs reflected lowered DMN functional connectivity in TG2576 mice and revealed significantly decreased DMN-TPN anti-correlations. (3) QPP-derived measures significantly improved classification compared to conventional functional connectivity measures. Altogether, our findings provide insight into the neural dynamics of aberrant network connectivity in AD and indicate that QPPs might serve as a translational diagnostic tool.
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Affiliation(s)
- Michaël E Belloy
- Department of Pharmaceutical, Veterinary and Biomedical Sciences, Bio-Imaging Lab, University of Antwerp, Universiteitsplein 1, 2610, Wilrijk, Antwerp, Belgium.
- Department of Biomedical Engineering, Emory University, 1760 Haygood Dr. NE, Atlanta, GA, 30322, USA.
| | - Disha Shah
- Department of Pharmaceutical, Veterinary and Biomedical Sciences, Bio-Imaging Lab, University of Antwerp, Universiteitsplein 1, 2610, Wilrijk, Antwerp, Belgium
| | - Anzar Abbas
- Department of Neuroscience, Emory University, 1760 Haygood Dr. NE, Atlanta, GA, 30322, USA
| | - Amrit Kashyap
- Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, 1760 Haygood Dr. NE, Atlanta, GA, 30322, USA
| | - Steffen Roßner
- Paul Flechsig Institute for Brain Research, University of Leipzig, Liebigstraße 19. Haus C, 04103, Leipzig, Germany
| | - Annemie Van der Linden
- Department of Pharmaceutical, Veterinary and Biomedical Sciences, Bio-Imaging Lab, University of Antwerp, Universiteitsplein 1, 2610, Wilrijk, Antwerp, Belgium
| | - Shella D Keilholz
- Department of Biomedical Engineering, Emory University, 1760 Haygood Dr. NE, Atlanta, GA, 30322, USA
- Department of Neuroscience, Emory University, 1760 Haygood Dr. NE, Atlanta, GA, 30322, USA
- Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, 1760 Haygood Dr. NE, Atlanta, GA, 30322, USA
| | - Georgios A Keliris
- Department of Pharmaceutical, Veterinary and Biomedical Sciences, Bio-Imaging Lab, University of Antwerp, Universiteitsplein 1, 2610, Wilrijk, Antwerp, Belgium
| | - Marleen Verhoye
- Department of Pharmaceutical, Veterinary and Biomedical Sciences, Bio-Imaging Lab, University of Antwerp, Universiteitsplein 1, 2610, Wilrijk, Antwerp, Belgium
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44
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Krishnan GP, González OC, Bazhenov M. Origin of slow spontaneous resting-state neuronal fluctuations in brain networks. Proc Natl Acad Sci U S A 2018; 115:6858-63. [PMID: 29884650 DOI: 10.1073/pnas.1715841115] [Citation(s) in RCA: 39] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2023] Open
Abstract
Resting- or baseline-state low-frequency (0.01-0.2 Hz) brain activity is observed in fMRI, EEG, and local field potential recordings. These fluctuations were found to be correlated across brain regions and are thought to reflect neuronal activity fluctuations between functionally connected areas of the brain. However, the origin of these infra-slow resting-state fluctuations remains unknown. Here, using a detailed computational model of the brain network, we show that spontaneous infra-slow (<0.05 Hz) activity could originate due to the ion concentration dynamics. The computational model implemented dynamics for intra- and extracellular K+ and Na+ and intracellular Cl- ions, Na+/K+ exchange pump, and KCC2 cotransporter. In the network model simulating resting awake-like brain state, we observed infra-slow fluctuations in the extracellular K+ concentration, Na+/K+ pump activation, firing rate of neurons, and local field potentials. Holding K+ concentration constant prevented generation of the infra-slow fluctuations. The amplitude and peak frequency of this activity were modulated by the Na+/K+ pump, AMPA/GABA synaptic currents, and glial properties. Further, in a large-scale network with long-range connections based on CoCoMac connectivity data, the infra-slow fluctuations became synchronized among remote clusters similar to the resting-state activity observed in vivo. Overall, our study proposes that ion concentration dynamics mediated by neuronal and glial activity may contribute to the generation of very slow spontaneous fluctuations of brain activity that are reported as the resting-state fluctuations in fMRI and EEG recordings.
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45
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Grooms JK, Thompson GJ, Pan WJ, Billings J, Schumacher EH, Epstein CM, Keilholz SD. Infraslow Electroencephalographic and Dynamic Resting State Network Activity. Brain Connect 2018; 7:265-280. [PMID: 28462586 DOI: 10.1089/brain.2017.0492] [Citation(s) in RCA: 53] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
A number of studies have linked the blood oxygenation level dependent (BOLD) signal to electroencephalographic (EEG) signals in traditional frequency bands (δ, θ, α, β, and γ), but the relationship between BOLD and its direct frequency correlates in the infraslow band (<1 Hz) has been little studied. Previously, work in rodents showed that infraslow local field potentials play a role in functional connectivity, particularly in the dynamic organization of large-scale networks. To examine the relationship between infraslow activity and network dynamics in humans, direct current (DC) EEG and resting state magnetic resonance imaging data were acquired simultaneously. The DC EEG signals were correlated with the BOLD signal in patterns that resembled resting state networks. Subsequent dynamic analysis showed that the correlation between DC EEG and the BOLD signal varied substantially over time, even within individual subjects. The variation in DC EEG appears to reflect the time-varying contribution of different resting state networks. Furthermore, some of the patterns of DC EEG and BOLD correlation are consistent with previous work demonstrating quasiperiodic spatiotemporal patterns of large-scale network activity in resting state. These findings demonstrate that infraslow electrical activity is linked to BOLD fluctuations in humans and that it may provide a basis for large-scale organization comparable to that observed in animal studies.
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Affiliation(s)
- Joshua K Grooms
- 1 Department of Biomedical Engineering, Georgia Institute of Technology and Emory University , Atlanta, Georgia
| | - Garth J Thompson
- 2 Magnetic Resonance Research Center (MRRC) and Radiology and Biomedical Imaging, Yale University , New Haven, Connecticut
| | - Wen-Ju Pan
- 1 Department of Biomedical Engineering, Georgia Institute of Technology and Emory University , Atlanta, Georgia
| | - Jacob Billings
- 3 Department of Neuroscience, Emory University , Atlanta, Georgia
| | - Eric H Schumacher
- 4 Department of Psychology, Georgia Institute of Technology , Atlanta, Georgia
| | - Charles M Epstein
- 5 Department of Neurology, Emory University School of Medicine , Atlanta, Georgia
| | - Shella D Keilholz
- 1 Department of Biomedical Engineering, Georgia Institute of Technology and Emory University , Atlanta, Georgia .,3 Department of Neuroscience, Emory University , Atlanta, Georgia
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Pfurtscheller G, Schwerdtfeger A, Seither‐Preisler A, Brunner C, Aigner CS, Calisto J, Gens J, Andrade A. Synchronization of intrinsic 0.1-Hz blood-oxygen-level-dependent oscillations in amygdala and prefrontal cortex in subjects with increased state anxiety. Eur J Neurosci 2018; 47:417-426. [PMID: 29368814 PMCID: PMC5887876 DOI: 10.1111/ejn.13845] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2017] [Revised: 01/16/2018] [Accepted: 01/18/2018] [Indexed: 12/30/2022]
Abstract
Low-frequency oscillations with a dominant frequency at 0.1 Hz are one of the most influential intrinsic blood-oxygen-level-dependent (BOLD) signals. This raises the question if vascular BOLD oscillations (originating from blood flow in the brain) and intrinsic slow neural activity fluctuations (neural BOLD oscillations) can be differentiated. In this study, we report on two different approaches: first, on computing the phase-locking value in the frequency band 0.07-0.13 Hz between heart beat-to-beat interval (RRI) and BOLD oscillations and second, between multiple BOLD oscillations (functional connectivity) in four resting states in 23 scanner-naïve, anxious healthy subjects. The first method revealed that vascular 0.1-Hz BOLD oscillations preceded those in RRI signals by 1.7 ± 0.6 s and neural BOLD oscillations lagged RRI oscillations by 0.8 ± 0.5 s. Together, vascular BOLD oscillations preceded neural BOLD oscillations by ~90° or ~2.5 s. To verify this discrimination, connectivity patterns of neural and vascular 0.1-Hz BOLD oscillations were compared in 26 regions involved in processing of emotions. Neural BOLD oscillations revealed significant phase-coupling between amygdala and medial frontal cortex, while vascular BOLD oscillations showed highly significant phase-coupling between amygdala and multiple regions in the supply areas of the anterior and medial cerebral arteries. This suggests that not only slow neural and vascular BOLD oscillations can be dissociated but also that two strategies may exist to optimize regulation of anxiety, that is increased functional connectivity between amygdala and medial frontal cortex, and increased cerebral blood flow in amygdala and related structures.
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Affiliation(s)
- Gert Pfurtscheller
- Institute of Neural EngineeringGraz University of TechnologyGrazAustria
- BioTechMed GrazGrazAustria
| | - Andreas Schwerdtfeger
- BioTechMed GrazGrazAustria
- Institute of PsychologyUniversity of Graz8010GrazAustria
- Health Psychology and Applied DiagnosticsUniversity of WuppertalWuppertalGermany
| | - Annemarie Seither‐Preisler
- BioTechMed GrazGrazAustria
- Department of Neuroradiology and NeurologyUniversity of Heidelberg Medical SchoolHeidelbergGermany
- Centre for Systematic MusicologyUniversity of GrazGrazAustria
| | - Clemens Brunner
- BioTechMed GrazGrazAustria
- Institute of PsychologyUniversity of Graz8010GrazAustria
| | - Christoph Stefan Aigner
- BioTechMed GrazGrazAustria
- Institute of Medical EngineeringGraz University of TechnologyGrazAustria
| | - João Calisto
- Institute of Biophysics and Biomedical EngineeringFaculty of SciencesUniversity of LisbonLisbonPortugal
| | - João Gens
- Institute of Biophysics and Biomedical EngineeringFaculty of SciencesUniversity of LisbonLisbonPortugal
| | - Alexandre Andrade
- Institute of Biophysics and Biomedical EngineeringFaculty of SciencesUniversity of LisbonLisbonPortugal
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Huang Z, Zhang J, Longtin A, Dumont G, Duncan NW, Pokorny J, Qin P, Dai R, Ferri F, Weng X, Northoff G. Is There a Nonadditive Interaction Between Spontaneous and Evoked Activity? Phase-Dependence and Its Relation to the Temporal Structure of Scale-Free Brain Activity. Cereb Cortex 2018; 27:1037-1059. [PMID: 26643354 DOI: 10.1093/cercor/bhv288] [Citation(s) in RCA: 49] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
The aim of our study was to use functional magnetic resonance imaging to investigate how spontaneous activity interacts with evoked activity, as well as how the temporal structure of spontaneous activity, that is, long-range temporal correlations, relate to this interaction. Using an extremely sparse event-related design (intertrial intervals: 52-60 s), a novel blood oxygen level-dependent signal correction approach (accounting for spontaneous fluctuations using pseudotrials) and phase analysis, we provided direct evidence for a nonadditive interaction between spontaneous and evoked activity. We demonstrated the discrepancy between the present and previous observations on why a linear superposition between spontaneous and evoked activity can be seen by using co-occurring signals from homologous brain regions. Importantly, we further demonstrated that the nonadditive interaction can be characterized by phase-dependent effects of spontaneous activity, which is closely related to the degree of long-range temporal correlations in spontaneous activity as indexed by both power-law exponent and phase-amplitude coupling. Our findings not only contribute to the understanding of spontaneous brain activity and its scale-free properties, but also bear important implications for our understanding of neural activity in general.
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Affiliation(s)
- Zirui Huang
- Institute of Mental Health Research, University of Ottawa, Ottawa, ON K1Z 7K4, Canada
| | - Jianfeng Zhang
- Center for Cognition and Brain Disorders, Hangzhou Normal University, Hangzhou 311121, PR China.,Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou Normal University, Hangzhou 310015, PR China
| | - André Longtin
- Department of Physics, University of Ottawa, Ottawa, ON K1N 6N5, Canada
| | - Grégory Dumont
- Institute of Mental Health Research, University of Ottawa, Ottawa, ON K1Z 7K4, Canada.,Department of Physics, University of Ottawa, Ottawa, ON K1N 6N5, Canada
| | - Niall W Duncan
- Institute of Mental Health Research, University of Ottawa, Ottawa, ON K1Z 7K4, Canada.,Center for Cognition and Brain Disorders, Hangzhou Normal University, Hangzhou 311121, PR China.,Brain and Consciousness Research Center, Taipei Medical University-Shuang Ho Hospital, New Taipei City 23561, Taiwan
| | - Johanna Pokorny
- Department of Anthropology, University of Toronto, Toronto, ON M5S 2S2, Canada
| | - Pengmin Qin
- Institute of Mental Health Research, University of Ottawa, Ottawa, ON K1Z 7K4, Canada.,Brain and Consciousness Research Center, Taipei Medical University-Shuang Ho Hospital, New Taipei City 23561, Taiwan
| | - Rui Dai
- Center for Cognition and Brain Disorders, Hangzhou Normal University, Hangzhou 311121, PR China.,Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou Normal University, Hangzhou 310015, PR China.,School of Life Science, South China Normal University, Guangzhou 510613, PR China
| | - Francesca Ferri
- Institute of Mental Health Research, University of Ottawa, Ottawa, ON K1Z 7K4, Canada
| | - Xuchu Weng
- Center for Cognition and Brain Disorders, Hangzhou Normal University, Hangzhou 311121, PR China.,Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou Normal University, Hangzhou 310015, PR China
| | - Georg Northoff
- Institute of Mental Health Research, University of Ottawa, Ottawa, ON K1Z 7K4, Canada.,Center for Cognition and Brain Disorders, Hangzhou Normal University, Hangzhou 311121, PR China.,Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou Normal University, Hangzhou 310015, PR China.,Brain and Consciousness Research Center, Taipei Medical University-Shuang Ho Hospital, New Taipei City 23561, Taiwan
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48
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Hofmeijer J, van Kaam CR, van de Werff B, Vermeer SE, Tjepkema-Cloostermans MC, van Putten MJAM. Detecting Cortical Spreading Depolarization with Full Band Scalp Electroencephalography: An Illusion? Front Neurol 2018; 9:17. [PMID: 29422883 PMCID: PMC5788886 DOI: 10.3389/fneur.2018.00017] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2017] [Accepted: 01/10/2018] [Indexed: 12/03/2022] Open
Abstract
Introduction There is strong evidence suggesting detrimental effects of cortical spreading depolarization (CSD) in patients with acute ischemic stroke and severe traumatic brain injury. Previous studies implicated scalp electroencephalography (EEG) features to be correlates of CSD based on retrospective analysis of EEG epochs after having detected “CSD” in time aligned electrocorticography. We studied the feasibility of CSD detection in a prospective cohort study with continuous EEG in 18 patients with acute ischemic stroke and 18 with acute severe traumatic brain injury. Methods Full band EEG with 21 silver/silver chloride electrodes was started within 48 h since symptom onset. Five additional electrodes were used above the infarct. We visually analyzed all raw EEG data in epochs of 1 h. Inspection was directed at detection of the typical combination of CSD characteristics, i.e., (i) a large slow potential change (SPC) accompanied by a simultaneous amplitude depression of >1Hz activity, (ii) focal presentation, and (iii) spread reflected as appearance on neighboring electrodes with a delay. Results In 3,035 one-hour EEG epochs, infraslow activity (ISA) was present in half to three quarters of the registration time. Typically, activity was intermittent with amplitudes of 40–220 µV, approximately half was oscillatory. There was no specific spatial distribution. Relevant changes of ISA were always visible in multiple electrodes, and not focal, as expected in CSD. ISA appearing as “SPC” was mostly associated with an amplitude increase of faster activities, and never with suppression. In all patients, depressions of spontaneous brain activity occurred. However, these were not accompanied by simultaneous SPC, occurred simultaneously on all channels, and were not focal, let alone spread, as expected in CSD. Conclusion With full band scalp EEG in patients with cortical ischemic stroke or traumatic brain injury, we observed various ISA, probably modulating cortical excitability. However, we were unable to identify unambiguous characteristics of CSD.
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Affiliation(s)
- Jeannette Hofmeijer
- Department of Clinical Neurophysiology, MIRA Institute for Biomedical Technology and Technical Medicine, University of Twente, Enschede, Netherlands.,Department of Neurology, Rijnstate Hospital, Arnhem, Netherlands
| | - C R van Kaam
- Department of Clinical Neurophysiology, MIRA Institute for Biomedical Technology and Technical Medicine, University of Twente, Enschede, Netherlands.,Department of Neurology, Rijnstate Hospital, Arnhem, Netherlands
| | - Babette van de Werff
- Department of Clinical Neurophysiology, MIRA Institute for Biomedical Technology and Technical Medicine, University of Twente, Enschede, Netherlands.,Department of Neurology, Rijnstate Hospital, Arnhem, Netherlands
| | - Sarah E Vermeer
- Department of Neurology, Rijnstate Hospital, Arnhem, Netherlands
| | | | - Michel J A M van Putten
- Department of Clinical Neurophysiology, MIRA Institute for Biomedical Technology and Technical Medicine, University of Twente, Enschede, Netherlands.,Department of Clinical Neurophysiology, Medisch Spectrum Twente, Enschede, Netherlands
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Dash MB, Ajayi S, Folsom L, Gold PE, Korol DL. Spontaneous Infraslow Fluctuations Modulate Hippocampal EPSP-PS Coupling. eNeuro 2018; 5:ENEURO. [PMID: 29349291 DOI: 10.1523/ENEURO.0403-17.2017] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2017] [Accepted: 12/15/2017] [Indexed: 11/26/2022] Open
Abstract
Extensive trial-to-trial variability is a hallmark of most behavioral, cognitive, and physiological processes. Spontaneous brain activity (SBA), a ubiquitous phenomenon that coordinates levels and patterns of neuronal activity throughout the brain, may contribute to this variability by dynamically altering neuronal excitability. In freely-behaving male rats, we observed extensive variability of the hippocampal evoked response across 28-min recording periods despite maintaining constant stimulation parameters of the medial perforant path. This variability was related to antecedent SBA: increases in low-frequency (0.5–9 Hz) and high-frequency (40.25–100 Hz) band-limited power (BLP) in the 4-s preceding stimulation were associated with decreased slope of the field EPSP (fEPSP) and increased population spike (PS) amplitude. These fluctuations in SBA and evoked response magnitude did not appear stochastic but rather exhibited coordinated activity across infraslow timescales (0.005–0.02 Hz). Specifically, infraslow fluctuations in high- and low-frequency BLP were antiphase with changes in fEPSP slope and in phase with changes in PS amplitude. With these divergent effects on the fEPSP and PS, infraslow SBA ultimately modulates EPSP-PS coupling and thereby enables hippocampal circuitry to generate heterogeneous outputs from identical inputs. Consequently, infraslow SBA appears well suited to dynamically alter sensory selection and information processing and highlights the fundamental role of endogenous neuronal activity for shaping the brain’s response to incoming stimuli.
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Lu FM, Wang YF, Zhang J, Chen HF, Yuan Z. Optical mapping of the dominant frequency of brain signal oscillations in motor systems. Sci Rep 2017; 7:14703. [PMID: 29116158 PMCID: PMC5677051 DOI: 10.1038/s41598-017-15046-9] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2017] [Accepted: 10/17/2017] [Indexed: 12/17/2022] Open
Abstract
Recent neuroimaging studies revealed that the dominant frequency of neural oscillations is brain-region-specific and can vary with frequency-specific reorganization of brain networks during cognition. In this study, we examined the dominant frequency in low-frequency neural oscillations represented by oxygenated hemoglobin measurements after the hemodynamic response function (HRF) deconvolution. Twenty-nine healthy college subjects were recruited to perform a serial finger tapping task at the frequency of 0.2 Hz. Functional near-infrared spectroscopy (fNIRS) was applied to record the hemodynamic signals over the primary motor cortex, supplementary motor area (SMA), premotor cortex, and prefrontal area. We then explored the low frequency steady-state brain response (lfSSBR), which was evoked in the motor systems at the fundamental frequency (0.2 Hz) and its harmonics (0.4, 0.6, and 0.8 Hz). In particular, after HRF deconvolution, the lfSSBR at the frequency of 0.4 Hz in the SMA was identified as the dominant frequency. Interestingly, the domain frequency exhibited the correlation with behavior data such as reaction time, indicating that the physiological implication of lfSSBR is related to the brain anatomy, stimulus frequency and cognition. More importantly, the HRF deconvolution showed its capability for recovering signals probably reflecting neural-level events and revealing the physiological meaning of lfSSBR.
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Affiliation(s)
- Feng-Mei Lu
- Bioimaging Core, Faculty of Health Sciences, University of Macau, Macau, SAR, China
| | - Yi-Feng Wang
- Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054, China
| | - Juan Zhang
- Faculty of Education, University of Macau, Macau, SAR, China
| | - Hua-Fu Chen
- Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054, China
| | - Zhen Yuan
- Bioimaging Core, Faculty of Health Sciences, University of Macau, Macau, SAR, China.
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