1
|
Wu X, Zhang Y, Xue M, Li J, Li X, Cui Z, Gao JH, Yang G. Heritability of functional gradients in the human subcortico-cortical connectivity. Commun Biol 2024; 7:854. [PMID: 38997510 PMCID: PMC11245549 DOI: 10.1038/s42003-024-06551-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2023] [Accepted: 07/04/2024] [Indexed: 07/14/2024] Open
Abstract
The human subcortex plays a pivotal role in cognition and is widely implicated in the pathophysiology of many psychiatric disorders. However, the heritability of functional gradients based on subcortico-cortical functional connectivity remains elusive. Here, leveraging twin functional MRI (fMRI) data from both the Human Connectome Project (n = 1023) and the Adolescent Brain Cognitive Development study (n = 936) datasets, we construct large-scale subcortical functional gradients and delineate an increased principal functional gradient pattern from unimodal sensory/motor networks to transmodal association networks. We observed that this principal functional gradient is heritable, and the strength of heritability exhibits a heterogeneous pattern along a hierarchical unimodal-transmodal axis in subcortex for both young adults and children. Furthermore, employing a machine learning framework, we show that this heterogeneous pattern of the principal functional gradient in subcortex can accurately discern the relationship between monozygotic twin pairs and dizygotic twin pairs with an accuracy of 76.2% (P < 0.001). The heritability of functional gradients is associated with the anatomical myelin proxied by MRI-derived T1-weighted/T2-weighted (T1w/T2w) ratio mapping in subcortex. This study provides new insights into the biological basis of subcortical functional hierarchy by revealing the structural and genetic properties of the subcortical functional gradients.
Collapse
Affiliation(s)
- Xinyu Wu
- Advanced Research Institute of Multidisciplinary Sciences, Beijing Institute of Technology, Beijing, China
| | - Yu Zhang
- Advanced Research Institute of Multidisciplinary Sciences, Beijing Institute of Technology, Beijing, China
| | - Mufan Xue
- Advanced Research Institute of Multidisciplinary Sciences, Beijing Institute of Technology, Beijing, China
| | - Jinlong Li
- School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China
| | - Xuesong Li
- School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China
| | - Zaixu Cui
- Chinese Institute for Brain Research, Beijing, China
| | - Jia-Hong Gao
- Beijing City Key Lab for Medical Physics and Engineering, Institution of Heavy Ion Physics, School of Physics, Peking University, Beijing, China.
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China.
- McGovern Institute for Brain Research, Peking University, Beijing, China.
- Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, China.
| | - Guoyuan Yang
- Advanced Research Institute of Multidisciplinary Sciences, Beijing Institute of Technology, Beijing, China.
- School of Medical Technology, Beijing Institute of Technology, Beijing, China.
| |
Collapse
|
2
|
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] [Abstract] [Key Words] [MESH Headings] [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.
Collapse
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.
| |
Collapse
|
3
|
Ilan Y. Free Will as Defined by the Constrained Disorder Principle: a Restricted, Mandatory, Personalized, Regulated Process for Decision-Making. Integr Psychol Behav Sci 2024:10.1007/s12124-024-09853-9. [PMID: 38900370 DOI: 10.1007/s12124-024-09853-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/08/2024] [Indexed: 06/21/2024]
Abstract
The concept of free will has challenged physicists, biologists, philosophers, and other professionals for decades. The constrained disorder principle (CDP) is a fundamental law that defines systems according to their inherent variability. It provides mechanisms for adapting to dynamic environments. This work examines the CDP's perspective of free will concerning various free will theories. Per the CDP, systems lack intentions, and the "freedom" to select and act is built into their design. The "freedom" is embedded within the response range determined by the boundaries of the systems' variability. This built-in and self-generating mechanism enables systems to cope with perturbations. According to the CDP, neither dualism nor an unknown metaphysical apparatus dictates choices. Brain variability facilitates cognitive adaptation to complex, unpredictable situations across various environments. Human behaviors and decisions reflect an underlying physical variability in the brain and other organs for dealing with unpredictable noises. Choices are not predetermined but reflect the ongoing adaptation processes to dynamic prssu½res. Malfunctions and disease states are characterized by inappropriate variability, reflecting an inability to respond adequately to perturbations. Incorporating CDP-based interventions can overcome malfunctions and disease states and improve decision processes. CDP-based second-generation artificial intelligence platforms improve interventions and are being evaluated to augment personal development, wellness, and health.
Collapse
Affiliation(s)
- Yaron Ilan
- Faculty of Medicine, Hebrew University and Department of Medicine, Hadassah Medical Center, Jerusalem, Israel.
| |
Collapse
|
4
|
Grujic N, Polania R, Burdakov D. Neurobehavioral meaning of pupil size. Neuron 2024:S0896-6273(24)00406-9. [PMID: 38925124 DOI: 10.1016/j.neuron.2024.05.029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2023] [Revised: 03/22/2024] [Accepted: 05/31/2024] [Indexed: 06/28/2024]
Abstract
Pupil size is a widely used metric of brain state. It is one of the few signals originating from the brain that can be readily monitored with low-cost devices in basic science, clinical, and home settings. It is, therefore, important to investigate and generate well-defined theories related to specific interpretations of this metric. What exactly does it tell us about the brain? Pupils constrict in response to light and dilate during darkness, but the brain also controls pupil size irrespective of luminosity. Pupil size fluctuations resulting from ongoing "brain states" are used as a metric of arousal, but what is pupil-linked arousal and how should it be interpreted in neural, cognitive, and computational terms? Here, we discuss some recent findings related to these issues. We identify open questions and propose how to answer them through a combination of well-defined tasks, neurocomputational models, and neurophysiological probing of the interconnected loops of causes and consequences of pupil size.
Collapse
Affiliation(s)
- Nikola Grujic
- Neurobehavioural Dynamics Lab, ETH Zürich, Department of Health Sciences and Technology, Schorenstrasse 16, 8603 Schwerzenbach, Switzerland.
| | - Rafael Polania
- Decision Neuroscience Lab, ETH Zürich, Department of Health Sciences and Technology, Winterthurstrasse 190, 8057 Zürich, Switzerland
| | - Denis Burdakov
- Neurobehavioural Dynamics Lab, ETH Zürich, Department of Health Sciences and Technology, Schorenstrasse 16, 8603 Schwerzenbach, Switzerland.
| |
Collapse
|
5
|
Das SK, Sao AK, Biswal BB. Estimation of static and dynamic functional connectivity in resting-state fMRI using zero-frequency resonator. Hum Brain Mapp 2024; 45:e26606. [PMID: 38895977 PMCID: PMC11187872 DOI: 10.1002/hbm.26606] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Revised: 11/28/2023] [Accepted: 12/29/2023] [Indexed: 06/21/2024] Open
Abstract
Resting-state functional magnetic resonance imaging (rs-fMRI) is increasingly being used to infer the functional organization of the brain. Blood oxygen level-dependent (BOLD) features related to spontaneous neuronal activity, are yet to be clearly understood. Prior studies have hypothesized that rs-fMRI is spontaneous event-related and these events convey crucial information about the neuronal activity in estimating resting state functional connectivity (FC). Attempts have been made to extract these temporal events using a predetermined threshold. However, the thresholding methods in addition to being very sensitive to noise, may consider redundant events or exclude the low-valued inflection points. Here, we extract the event-related temporal onsets from the rs-fMRI time courses using a zero-frequency resonator (ZFR). The ZFR reflects the transient behavior of the BOLD events at its output. The conditional rate (CR) of the BOLD events occurring in a time course with respect to a seed time course is used to derive static FC. The temporal activity around the estimated events called high signal-to-noise ratio (SNR) segments are also obtained in the rs-fMRI time course and are then used to compute static and dynamic FCs during rest. Coactivation pattern (CAP) is the dynamic FC obtained using the high SNR segments driven by the ZFR. The static FC demonstrates that the ZFR-based CR distinguishes the coactivation and non-coactivation scores well in the distribution. CAP analysis demonstrated the stable and longer dwell time dominant resting state functional networks with high SNR segments driven by the ZFR. Static and dynamic FC analysis underpins that the ZFR-driven temporal onsets of BOLD events derive reliable and consistent FCs in the resting brain using a subset of the time points.
Collapse
Affiliation(s)
- Sukesh Kumar Das
- School of Computing and Electrical EngineeringIndian Institute of Technology MandiMandiHimachal PradeshIndia
| | - Anil K. Sao
- Department of Computer Science and EngineeringIndian Institute of Technology BhilaiBhilaiChhattisgarhIndia
| | - Bharat B. Biswal
- Department of Biomedical EngineeringNew Jersey Institute of TechnologyNewarkNew JerseyUSA
| |
Collapse
|
6
|
Foster M, Scheinost D. Brain states as wave-like motifs. Trends Cogn Sci 2024; 28:492-503. [PMID: 38582654 DOI: 10.1016/j.tics.2024.03.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2023] [Revised: 02/29/2024] [Accepted: 03/11/2024] [Indexed: 04/08/2024]
Abstract
There is ample evidence of wave-like activity in the brain at multiple scales and levels. This emerging literature supports the broader adoption of a wave perspective of brain activity. Specifically, a brain state can be described as a set of recurring, sequential patterns of propagating brain activity, namely a wave. We examine a collective body of experimental work investigating wave-like properties. Based on these works, we consider brain states as waves using a scale-agnostic framework across time and space. Emphasis is placed on the sequentiality and periodicity associated with brain activity. We conclude by discussing the implications, prospects, and experimental opportunities of this framework.
Collapse
Affiliation(s)
- Maya Foster
- Department of Biomedical Engineering, Yale University, New Haven, CT, USA.
| | - Dustin Scheinost
- Department of Biomedical Engineering, Yale University, New Haven, CT, USA; Department of Radiology and Biomedical Engineering, Yale School of Medicine, New Haven, CT, USA
| |
Collapse
|
7
|
Anumba N, Kelberman MA, Pan W, Marriott A, Zhang X, Xu N, Weinshenker D, Keilholz S. The Effects of Locus Coeruleus Optogenetic Stimulation on Global Spatiotemporal Patterns in Rats. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.23.595327. [PMID: 38826205 PMCID: PMC11142206 DOI: 10.1101/2024.05.23.595327] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2024]
Abstract
Whole-brain intrinsic activity as detected by resting-state fMRI can be summarized by three primary spatiotemporal patterns. These patterns have been shown to change with different brain states, especially arousal. The noradrenergic locus coeruleus (LC) is a key node in arousal circuits and has extensive projections throughout the brain, giving it neuromodulatory influence over the coordinated activity of structurally separated regions. In this study, we used optogenetic-fMRI in rats to investigate the impact of LC stimulation on the global signal and three primary spatiotemporal patterns. We report small, spatially specific changes in global signal distribution as a result of tonic LC stimulation, as well as regional changes in spatiotemporal patterns of activity at 5 Hz tonic and 15 Hz phasic stimulation. We also found that LC stimulation had little to no effect on the spatiotemporal patterns detected by complex principal component analysis. These results show that the effects of LC activity on the BOLD signal in rats may be small and regionally concentrated, as opposed to widespread and globally acting.
Collapse
Affiliation(s)
- Nmachi Anumba
- Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, United States
| | - Michael A Kelberman
- Department of Human Genetics, Emory University, Atlanta, GA, United States
- Molecular Cellular and Developmental Biology Department, University of Colorado Boulder, Boulder, CO, United States
| | - Wenju Pan
- Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, United States
| | - Alexia Marriott
- Department of Human Genetics, Emory University, Atlanta, GA, United States
| | - Xiaodi Zhang
- Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, United States
| | - Nan Xu
- Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, United States
| | - David Weinshenker
- Department of Human Genetics, Emory University, Atlanta, GA, United States
| | - Shella Keilholz
- Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, United States
| |
Collapse
|
8
|
Xie K, Royer J, Larivière S, Rodriguez-Cruces R, Frässle S, Cabalo DG, Ngo A, DeKraker J, Auer H, Tavakol S, Weng Y, Abdallah C, Arafat T, Horwood L, Frauscher B, Caciagli L, Bernasconi A, Bernasconi N, Zhang Z, Concha L, Bernhardt BC. Atypical connectome topography and signal flow in temporal lobe epilepsy. Prog Neurobiol 2024; 236:102604. [PMID: 38604584 DOI: 10.1016/j.pneurobio.2024.102604] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Revised: 12/18/2023] [Accepted: 04/07/2024] [Indexed: 04/13/2024]
Abstract
Temporal lobe epilepsy (TLE) is the most common pharmaco-resistant epilepsy in adults. While primarily associated with mesiotemporal pathology, recent evidence suggests that brain alterations in TLE extend beyond the paralimbic epicenter and impact macroscale function and cognitive functions, particularly memory. Using connectome-wide manifold learning and generative models of effective connectivity, we examined functional topography and directional signal flow patterns between large-scale neural circuits in TLE at rest. Studying a multisite cohort of 95 patients with TLE and 95 healthy controls, we observed atypical functional topographies in the former group, characterized by reduced differentiation between sensory and transmodal association cortices, with most marked effects in bilateral temporo-limbic and ventromedial prefrontal cortices. These findings were consistent across all study sites, present in left and right lateralized patients, and validated in a subgroup of patients with histopathological validation of mesiotemporal sclerosis and post-surgical seizure freedom. Moreover, they were replicated in an independent cohort of 30 TLE patients and 40 healthy controls. Further analyses demonstrated that reduced differentiation related to decreased functional signal flow into and out of temporolimbic cortical systems and other brain networks. Parallel analyses of structural and diffusion-weighted MRI data revealed that topographic alterations were independent of TLE-related cortical thinning but partially mediated by white matter microstructural changes that radiated away from paralimbic circuits. Finally, we found a strong association between the degree of functional alterations and behavioral markers of memory dysfunction. Our work illustrates the complex landscape of macroscale functional imbalances in TLE, which can serve as intermediate markers bridging microstructural changes and cognitive impairment.
Collapse
Affiliation(s)
- Ke Xie
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Jessica Royer
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada; Analytical Neurophysiology Laboratory, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Sara Larivière
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Raul Rodriguez-Cruces
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Stefan Frässle
- Translational Neuromodeling Unit (TNU), Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - Donna Gift Cabalo
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Alexander Ngo
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Jordan DeKraker
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Hans Auer
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Shahin Tavakol
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Yifei Weng
- Department of Medical Imaging, Jinling Hospital, Nanjing University School of Medicine, Nanjing, China
| | - Chifaou Abdallah
- Analytical Neurophysiology Laboratory, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Thaera Arafat
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Linda Horwood
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada; Analytical Neurophysiology Laboratory, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Birgit Frauscher
- Analytical Neurophysiology Laboratory, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada; Department of Neurology, Duke University School of Medicine and Department of Biomedical Engineering, Duke University Pratt School of Engineering, Durham, NC 27705, USA
| | - Lorenzo Caciagli
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Neurology, Inselspital, Sleep-Wake-Epilepsy-Center, Bern University Hospital, University of Bern, Bern, Switzerland; Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London WC1N 3 BG, United Kingdom
| | - Andrea Bernasconi
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Neda Bernasconi
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Zhiqiang Zhang
- Department of Medical Imaging, Jinling Hospital, Nanjing University School of Medicine, Nanjing, China
| | - Luis Concha
- Institute of Neurobiology, Universidad Nacional Autónoma de Mexico (UNAM), Queretaro, Mexico
| | - Boris C Bernhardt
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada.
| |
Collapse
|
9
|
Vohryzek J, Cabral J, Timmermann C, Atasoy S, Roseman L, Nutt DJ, Carhart-Harris RL, Deco G, Kringelbach ML. The flattening of spacetime hierarchy of the N,N-dimethyltryptamine brain state is characterized by harmonic decomposition of spacetime (HADES) framework. Natl Sci Rev 2024; 11:nwae124. [PMID: 38778818 PMCID: PMC11110867 DOI: 10.1093/nsr/nwae124] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2023] [Revised: 02/15/2024] [Accepted: 03/11/2024] [Indexed: 05/25/2024] Open
Abstract
The human brain is a complex system, whose activity exhibits flexible and continuous reorganization across space and time. The decomposition of whole-brain recordings into harmonic modes has revealed a repertoire of gradient-like activity patterns associated with distinct brain functions. However, the way these activity patterns are expressed over time with their changes in various brain states remains unclear. Here, we investigate healthy participants taking the serotonergic psychedelic N,N-dimethyltryptamine (DMT) with the Harmonic Decomposition of Spacetime (HADES) framework that can characterize how different harmonic modes defined in space are expressed over time. HADES demonstrates significant decreases in contributions across most low-frequency harmonic modes in the DMT-induced brain state. When normalizing the contributions by condition (DMT and non-DMT), we detect a decrease specifically in the second functional harmonic, which represents the uni- to transmodal functional hierarchy of the brain, supporting the leading hypothesis that functional hierarchy is changed in psychedelics. Moreover, HADES' dynamic spacetime measures of fractional occupancy, life time and latent space provide a precise description of the significant changes of the spacetime hierarchical organization of brain activity in the psychedelic state.
Collapse
Affiliation(s)
- Jakub Vohryzek
- Centre for Eudaimonia and Human Flourishing, Linacre College, Department of Psychiatry, University of Oxford, Oxford OX3 9BX, UK
- Department of Psychiatry, University of Oxford, Oxford OX3 7JX, UK
- Center for Music in the Brain, Aarhus University, Aarhus 8000, Denmark
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona 08005, Spain
| | - Joana Cabral
- Centre for Eudaimonia and Human Flourishing, Linacre College, Department of Psychiatry, University of Oxford, Oxford OX3 9BX, UK
- Life and Health Sciences Research Institute, School of Medicine, University of Minho, Braga 4710-057, Portugal
- ICVS/3B's - PT Government Associate Laboratory, Braga/Guimarães 4710-057, Portugal
| | - Christopher Timmermann
- Centre for Psychedelic Research, Department of Brain Sciences, Imperial College London, London SW7 2AZ, UK
| | - Selen Atasoy
- Centre for Eudaimonia and Human Flourishing, Linacre College, Department of Psychiatry, University of Oxford, Oxford OX3 9BX, UK
- Department of Psychiatry, University of Oxford, Oxford OX3 7JX, UK
| | - Leor Roseman
- Centre for Psychedelic Research, Department of Brain Sciences, Imperial College London, London SW7 2AZ, UK
| | - David J Nutt
- Centre for Psychedelic Research, Department of Brain Sciences, Imperial College London, London SW7 2AZ, UK
| | - Robin L Carhart-Harris
- Centre for Psychedelic Research, Department of Brain Sciences, Imperial College London, London SW7 2AZ, UK
- Departments of Neurology and Psychiatry, University of California San Francisco, San Francisco 94143, USA
| | - Gustavo Deco
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona 08005, Spain
- Institució Catalana de la Recerca i Estudis Avançats (ICREA), Barcelona 08010, Spain
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- School of Psychological Sciences, Monash University, Melbourne, Australia
| | - Morten L Kringelbach
- Centre for Eudaimonia and Human Flourishing, Linacre College, Department of Psychiatry, University of Oxford, Oxford OX3 9BX, UK
- Department of Psychiatry, University of Oxford, Oxford OX3 7JX, UK
- Center for Music in the Brain, Aarhus University, Aarhus 8000, Denmark
| |
Collapse
|
10
|
Kozlowska K, Scher S. Recent advances in understanding the neurobiology of pediatric functional neurological disorder. Expert Rev Neurother 2024; 24:497-516. [PMID: 38591353 DOI: 10.1080/14737175.2024.2333390] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2023] [Accepted: 03/18/2024] [Indexed: 04/10/2024]
Abstract
INTRODUCTION Functional neurological disorder (FND) is a neuropsychiatric disorder that manifests in a broad array of functional motor, sensory, or cognitive symptoms, which arise from complex interactions between brain, mind, body, and context. Children with FND make up 10%-20% of presentations to neurology services in children's hospitals and up to 20% of adolescents admitted to hospital for the management of intractable seizures. AREAS COVERED The current review focuses on the neurobiology of pediatric FND. The authors present an overview of the small but growing body of research pertaining to the biological, emotion-processing, cognitive, mental health, physical health, and social system levels. EXPERT OPINION Emerging research suggests that pediatric FND is underpinned by aberrant changes within and between neuron-glial (brain) networks, with a variety of factors - on multiple system levels - contributing to brain network changes. In pediatric practice, adverse childhood experiences (ACEs) are commonly reported, and activation or dysregulation of stress-system components is a frequent finding. Our growing understanding of the neurobiology of pediatric FND has yielded important flow-on effects for assessing and diagnosing FND, for developing targeted treatment interventions, and for improving the treatment outcomes of children and adolescents with FND.
Collapse
Affiliation(s)
- Kasia Kozlowska
- The Children's Hospital at Westmead, Westmead, NSW, Australia
- Brain Dynamics Centre, Westmead Institute of Medical Research, Westmead, NSW, Australia
- University of Sydney Medical School, Camperdown, NSW, Australia
| | - Stephen Scher
- University of Sydney Medical School, Camperdown, NSW, Australia
- Department of Psychiatry, Harvard Medical School, Belmont, MA, USA
- McLean Hospital, Belmont, MA, USA
| |
Collapse
|
11
|
Koller DP, Schirner M, Ritter P. Human connectome topology directs cortical traveling waves and shapes frequency gradients. Nat Commun 2024; 15:3570. [PMID: 38670965 PMCID: PMC11053146 DOI: 10.1038/s41467-024-47860-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2023] [Accepted: 04/09/2024] [Indexed: 04/28/2024] Open
Abstract
Traveling waves and neural oscillation frequency gradients are pervasive in the human cortex. While the direction of traveling waves has been linked to brain function and dysfunction, the factors that determine this direction remain elusive. We hypothesized that structural connectivity instrength gradients - defined as the gradually varying sum of incoming connection strengths across the cortex - could shape both traveling wave direction and frequency gradients. We confirm the presence of instrength gradients in the human connectome across diverse cohorts and parcellations. Using a cortical network model, we demonstrate how these instrength gradients direct traveling waves and shape frequency gradients. Our model fits resting-state MEG functional connectivity best in a regime where instrength-directed traveling waves and frequency gradients emerge. We further show how structural subnetworks of the human connectome generate opposing wave directions and frequency gradients observed in the alpha and beta bands. Our findings suggest that structural connectivity instrength gradients affect both traveling wave direction and frequency gradients.
Collapse
Grants
- P.R. acknowledges funding from the following sources: Digital Europe Grant TEF-Health # 101100700, H2020 Research and Innovation Action Grant Human Brain Project SGA2 785907, H2020 Research and Innovation Action Grant Human Brain Project SGA3 945539, H2020 Research and Innovation Action Grant EOSC VirtualBrainCloud 826421, H2020 Research and Innovation Action Grant AISN 101057655, H2020 Research Infrastructures Grant EBRAINS-PREP 101079717, H2020 European Innovation Council PHRASE 101058240, H2020 Research Infrastructures Grant EBRAIN-Health 101058516, H2020 European Research Council Grant ERC BrainModes 683049, JPND ERA PerMed PatternCog 2522FSB904, Berlin Institute of Health & Foundation Charité, Johanna Quandt Excellence Initiative, German Research Foundation SFB 1436 (project ID 425899996), German Research Foundation SFB 1315 (project ID 327654276), German Research Foundation SFB 936 (project ID 178316478), German Research Foundation SFB-TRR 295 (project ID 424778381) German Research Foundation SPP Computational Connectomics RI 2073/6-1, RI 2073/10-2, RI 2073/9-1.
Collapse
Affiliation(s)
- Dominik P Koller
- Berlin Institute of Health (BIH) at Charité - Universitätsmedizin Berlin, Charitéplatz 1, 10117, Berlin, Germany.
- Department of Neurology with Experimental Neurology, Charité, Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin and Humboldt Universität zu Berlin, Charitéplatz 1, 10117, Berlin, Germany.
| | - Michael Schirner
- Berlin Institute of Health (BIH) at Charité - Universitätsmedizin Berlin, Charitéplatz 1, 10117, Berlin, Germany
- Department of Neurology with Experimental Neurology, Charité, Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin and Humboldt Universität zu Berlin, Charitéplatz 1, 10117, Berlin, Germany
- Bernstein Focus State Dependencies of Learning and Bernstein Center for Computational Neuroscience, 10115, Berlin, Germany
- Einstein Center for Neuroscience Berlin, Charitéplatz 1, 10117, Berlin, Germany
- Einstein Center Digital Future, Wilhelmstraße 67, 10117, Berlin, Germany
| | - Petra Ritter
- Berlin Institute of Health (BIH) at Charité - Universitätsmedizin Berlin, Charitéplatz 1, 10117, Berlin, Germany.
- Department of Neurology with Experimental Neurology, Charité, Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin and Humboldt Universität zu Berlin, Charitéplatz 1, 10117, Berlin, Germany.
- Bernstein Focus State Dependencies of Learning and Bernstein Center for Computational Neuroscience, 10115, Berlin, Germany.
- Einstein Center for Neuroscience Berlin, Charitéplatz 1, 10117, Berlin, Germany.
- Einstein Center Digital Future, Wilhelmstraße 67, 10117, Berlin, Germany.
| |
Collapse
|
12
|
Madsen J, Parra LC. Bidirectional brain-body interactions during natural story listening. Cell Rep 2024; 43:114081. [PMID: 38581682 DOI: 10.1016/j.celrep.2024.114081] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Revised: 11/25/2023] [Accepted: 03/24/2024] [Indexed: 04/08/2024] Open
Abstract
Narratives can synchronize neural and physiological signals between individuals, but the relationship between these signals, and the underlying mechanism, is unclear. We hypothesized a top-down effect of cognition on arousal and predicted that auditory narratives will drive not only brain signals but also peripheral physiological signals. We find that auditory narratives entrained gaze variation, saccade initiation, pupil size, and heart rate. This is consistent with a top-down effect of cognition on autonomic function. We also hypothesized a bottom-up effect, whereby autonomic physiology affects arousal. Controlled breathing affected pupil size, and heart rate was entrained by controlled saccades. Additionally, fluctuations in heart rate preceded fluctuations of pupil size and brain signals. Gaze variation, pupil size, and heart rate were all associated with anterior-central brain signals. Together, these results suggest bidirectional causal effects between peripheral autonomic function and central brain circuits involved in the control of arousal.
Collapse
Affiliation(s)
- Jens Madsen
- Department of Biomedical Engineering, City College of New York, 85 St. Nicholas Terrace, New York, NY 10031, USA.
| | - Lucas C Parra
- Department of Biomedical Engineering, City College of New York, 85 St. Nicholas Terrace, New York, NY 10031, USA
| |
Collapse
|
13
|
Gavenas J, Rutishauser U, Schurger A, Maoz U. Slow ramping emerges from spontaneous fluctuations in spiking neural networks. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.05.27.542589. [PMID: 37398452 PMCID: PMC10312459 DOI: 10.1101/2023.05.27.542589] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/04/2023]
Abstract
1. We reveal a mechanism for slow-ramping signals before spontaneous voluntary movements. 2. Slow synapses stabilize spontaneous fluctuations in spiking neural network. 3. We validate model predictions in human frontal cortical single-neuron recordings. 4. The model recreates the readiness potential in an EEG proxy signal. 5. Neurons that ramp together had correlated activity before ramping onset. The capacity to initiate actions endogenously is critical for goal-directed behavior. Spontaneous voluntary actions are typically preceded by slow-ramping activity in medial frontal cortex that begins around two seconds before movement, which may reflect spontaneous fluctuations that influence action timing. However, the mechanisms by which these slow ramping signals emerge from single-neuron and network dynamics remain poorly understood. Here, we developed a spiking neural-network model that produces spontaneous slow ramping activity in single neurons and population activity with onsets ∼2 seconds before threshold crossings. A key prediction of our model is that neurons that ramp together have correlated firing patterns before ramping onset. We confirmed this model-derived hypothesis in a dataset of human single neuron recordings from medial frontal cortex. Our results suggest that slow ramping signals reflect bounded spontaneous fluctuations that emerge from quasi-winner-take-all dynamics in clustered networks that are temporally stabilized by slow-acting synapses.
Collapse
|
14
|
Sargent KS, Martinez EL, Reed AC, Guha A, Bartholomew ME, Diehl CK, Chang CS, Salama S, Popov T, Thayer JF, Miller GA, Yee CM. Oscillatory Coupling Between Neural and Cardiac Rhythms. Psychol Sci 2024:9567976241235932. [PMID: 38568870 DOI: 10.1177/09567976241235932] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/05/2024] Open
Abstract
Oscillations serve a critical role in organizing biological systems. In the brain, oscillatory coupling is a fundamental mechanism of communication. The possibility that neural oscillations interact directly with slower physiological rhythms (e.g., heart rate, respiration) is largely unexplored and may have important implications for psychological functioning. Oscillations in heart rate, an aspect of heart rate variability (HRV), show remarkably robust associations with psychological health. Mather and Thayer proposed coupling between high-frequency HRV (HF-HRV) and neural oscillations as a mechanism that partially accounts for such relationships. We tested this hypothesis by measuring phase-amplitude coupling between HF-HRV and neural oscillations in 37 healthy adults at rest. Robust coupling was detected in all frequency bands. Granger causality analyses indicated stronger heart-to-brain than brain-to-heart effects in all frequency bands except gamma. These findings suggest that cardiac rhythms play a causal role in modulating neural oscillations, which may have important implications for mental health.
Collapse
Affiliation(s)
- Kaia S Sargent
- Department of Psychology, University of California, Los Angeles
| | | | | | - Anika Guha
- Department of Psychology, University of California, Los Angeles
| | | | | | | | - Sarah Salama
- Department of Psychology, University of California, Los Angeles
| | - Tzvetan Popov
- Department of Psychology, University of Konstanz
- Department of Psychology, University of Zurich
| | - Julian F Thayer
- Department of Psychological Science, University of California, Irvine
| | - Gregory A Miller
- Department of Psychology, University of California, Los Angeles
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles
| | - Cindy M Yee
- Department of Psychology, University of California, Los Angeles
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles
| |
Collapse
|
15
|
White BR, Adepoju TE, Fisher HB, Shinohara RT, Vandekar S. Spatial nonstationarity of image noise in widefield optical imaging and its effects on cluster-based inference for resting-state functional connectivity. J Neurosci Methods 2024; 404:110076. [PMID: 38331258 PMCID: PMC10940215 DOI: 10.1016/j.jneumeth.2024.110076] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2024] [Accepted: 02/04/2024] [Indexed: 02/10/2024]
Abstract
BACKGROUND Resting-state functional connectivity (RSFC) analysis with widefield optical imaging (WOI) is a potentially powerful tool to develop imaging biomarkers in mouse models of disease before translating them to human neuroimaging with functional magnetic resonance imaging (fMRI). The delineation of such biomarkers depends on rigorous statistical analysis. However, statistical understanding of WOI data is limited. In particular, cluster-based analysis of neuroimaging data depends on assumptions of spatial stationarity (i.e., that the distribution of cluster sizes under the null is equal at all brain locations). Whether actual data deviate from this assumption has not previously been examined in WOI. NEW METHOD In this manuscript, we characterize the effects of spatial nonstationarity in WOI RSFC data and adapt a "two-pass" technique from fMRI to correct cluster sizes and mitigate spatial bias, both parametrically and nonparametrically. These methods are tested on multi-institutional data. RESULTS AND COMPARISON WITH EXISTING METHODS We find that spatial nonstationarity has a substantial effect on inference in WOI RSFC data with false positives much more likely at some brain regions than others. This pattern of bias varies between imaging systems, contrasts, and mouse ages, all of which could affect experimental reproducibility if not accounted for. CONCLUSIONS Both parametric and nonparametric corrections for nonstationarity result in significant improvements in spatial bias. The proposed methods are simple to implement and will improve the robustness of inference in optical neuroimaging data.
Collapse
Affiliation(s)
- Brian R White
- Children's Hospital of Philadelphia, Perelman School of Medicine at the University of Pennsylvania, Division of Cardiology, Department of Pediatrics, USA.
| | - Temilola E Adepoju
- Children's Hospital of Philadelphia, Perelman School of Medicine at the University of Pennsylvania, Division of Cardiology, Department of Pediatrics, USA
| | - Hayden B Fisher
- Children's Hospital of Philadelphia, Perelman School of Medicine at the University of Pennsylvania, Division of Cardiology, Department of Pediatrics, USA
| | - Russell T Shinohara
- University of Pennsylvania, Perelman School of Medicine, Department of Biostatistics, Epidemiology, and Informatics, USA; University of Pennsylvania, Center for Biomedical Image Computing and Analysis, Department of Radiology, USA; University of Pennsylvania, Penn Statistics in Imaging and Visualization Endeavor, Department of Biostatistics, Epidemiology, and Informatics, USA
| | | |
Collapse
|
16
|
Froese T. Irruption and Absorption: A 'Black-Box' Framework for How Mind and Matter Make a Difference to Each Other. ENTROPY (BASEL, SWITZERLAND) 2024; 26:288. [PMID: 38667841 PMCID: PMC11049376 DOI: 10.3390/e26040288] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/15/2024] [Revised: 03/22/2024] [Accepted: 03/23/2024] [Indexed: 04/28/2024]
Abstract
Cognitive science is confronted by several fundamental anomalies deriving from the mind-body problem. Most prominent is the problem of mental causation and the hard problem of consciousness, which can be generalized into the hard problem of agential efficacy and the hard problem of mental content. Here, it is proposed to accept these explanatory gaps at face value and to take them as positive indications of a complex relation: mind and matter are one, but they are not the same. They are related in an efficacious yet non-reducible, non-observable, and even non-intelligible manner. Natural science is well equipped to handle the effects of non-observables, and so the mind is treated as equivalent to a hidden 'black box' coupled to the body. Two concepts are introduced given that there are two directions of coupling influence: (1) irruption denotes the unobservable mind hiddenly making a difference to observable matter, and (2) absorption denotes observable matter hiddenly making a difference to the unobservable mind. The concepts of irruption and absorption are methodologically compatible with existing information-theoretic approaches to neuroscience, such as measuring cognitive activity and subjective qualia in terms of entropy and compression, respectively. By offering novel responses to otherwise intractable theoretical problems from first principles, and by doing so in a way that is closely connected with empirical advances, irruption theory is poised to set the agenda for the future of the mind sciences.
Collapse
Affiliation(s)
- Tom Froese
- Embodied Cognitive Science Unit, Okinawa Institute of Science and Technology Graduate University (OIST), 1919-1 Tancha, Onna-son, Okinawa 904-0495, Japan
| |
Collapse
|
17
|
Kim B, Ding W, Yang L, Chen Q, Mao J, Feng G, Choi JH, Shen S. Simultaneous two-photon imaging and wireless EEG recording in mice. Heliyon 2024; 10:e25910. [PMID: 38449613 PMCID: PMC10915345 DOI: 10.1016/j.heliyon.2024.e25910] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Revised: 01/05/2024] [Accepted: 02/05/2024] [Indexed: 03/08/2024] Open
Abstract
Background In vivo two-photon imaging is a reliable method with high spatial resolution that allows observation of individual neuron and dendritic activity longitudinally. Neurons in local brain regions can be influenced by global brain states such as levels of arousal and attention that change over relatively short time scales, such as minutes. As such, the scientific rigor of investigating regional neuronal activities could be enhanced by considering the global brain state. New method In order to assess the global brain state during in vivo two-photon imaging, CBRAIN (collective brain research platform aided by illuminating neural activity), a wireless EEG collecting and labeling device, was controlled by the same computer of two-photon microscope. In an experiment to explore neuronal responses to isoflurane anesthesia through two-photon imaging, we investigated whether the response of individual cells correlated with concurrent EEG changes induced by anesthesia. Results In two-photon imaging, calcium activities of the excitatory neurons in the primary somatosensory cortex disappeared in about 30s after to the initiation of isoflurane anesthesia. The simultaneously recorded EEG showed various transitional activity for about 7 min from the initiation of anesthesia and continued with burst and suppression alternating pattern thereafter. As such, there was a dissociation between excitatory neuron activity of the primary somatosensory cortex and the global brain activity under anesthesia. Comparison with existing methods Existing methods to combine two-photon and EEG recording used wired EEG recording. In this study, wireless EEG was used in conjunction with two-photon imaging, facilitated by CBRAIN. More importantly, built-in algorithms of the CBRAIN can automatically detect brain state such as sleep. The codes used for EEG classification are easy to use, with no prior experience required. Conclusion Simultaneous recording of wireless EEG and two-photon imaging provides a practical way to capture individual neuronal activities with respect to global brain state in an experimental set-up.
Collapse
Affiliation(s)
- Bowon Kim
- Center for Translational Pain Research, Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital/Harvard Medical School, Boston, MA, USA
- Center for Neuroscience, Korea Institute of Science and Technology, Seoul, Republic of Korea
| | - Weihua Ding
- Center for Translational Pain Research, Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital/Harvard Medical School, Boston, MA, USA
| | - Liuyue Yang
- Center for Translational Pain Research, Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital/Harvard Medical School, Boston, MA, USA
| | - Qian Chen
- McGovern Institute for Brain Research and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge MA, USA
- Current address: Zhongshan Institute for Drug Discovery, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, China
| | - Jianren Mao
- Center for Translational Pain Research, Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital/Harvard Medical School, Boston, MA, USA
| | - Guoping Feng
- McGovern Institute for Brain Research and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge MA, USA
| | - Jee Hyun Choi
- Center for Neuroscience, Korea Institute of Science and Technology, Seoul, Republic of Korea
| | - Shiqian Shen
- Center for Translational Pain Research, Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital/Harvard Medical School, Boston, MA, USA
| |
Collapse
|
18
|
Yang C, Biswal B, Cui Q, Jing X, Ao Y, Wang Y. Frequency-dependent alterations of global signal topography in patients with major depressive disorder. Psychol Med 2024:1-10. [PMID: 38362834 DOI: 10.1017/s0033291724000254] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/17/2024]
Abstract
BACKGROUND Major depressive disorder (MDD) is associated not only with disorders in multiple brain networks but also with frequency-specific brain activities. The abnormality of spatiotemporal networks in patients with MDD remains largely unclear. METHODS We investigated the alterations of the global spatiotemporal network in MDD patients using a large-sample multicenter resting-state functional magnetic resonance imaging dataset. The spatiotemporal characteristics were measured by the variability of global signal (GS) and its correlation with local signals (GSCORR) at multiple frequency bands. The association between these indicators and clinical scores was further assessed. RESULTS The GS fluctuations were reduced in patients with MDD across the full frequency range (0-0.1852 Hz). The GSCORR was also reduced in the MDD group, especially in the relatively higher frequency range (0.0728-0.1852 Hz). Interestingly, these indicators showed positive correlations with depressive scores in the MDD group and relative negative correlations in the control group. CONCLUSION The GS and its spatiotemporal effects on local signals were weakened in patients with MDD, which may impair inter-regional synchronization and related functions. Patients with severe depression may use the compensatory mechanism to make up for the functional impairments.
Collapse
Affiliation(s)
- Chengxiao Yang
- Institute of Brain and Psychological Sciences, Sichuan Normal University, Chengdu 610066, China
| | - Bharat Biswal
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Qian Cui
- School of Public Affairs and Administration, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Xiujuan Jing
- Institute of Brain and Psychological Sciences, Sichuan Normal University, Chengdu 610066, China
| | - Yujia Ao
- Faculty of Medicine, University of Ottawa, Ottawa, Ontario, Canada
| | - Yifeng Wang
- Institute of Brain and Psychological Sciences, Sichuan Normal University, Chengdu 610066, China
| |
Collapse
|
19
|
Jacob LPL, Bailes SM, Williams SD, Stringer C, Lewis LD. Distributed fMRI dynamics predict distinct EEG rhythms across sleep and wakefulness. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.29.577429. [PMID: 38352426 PMCID: PMC10862763 DOI: 10.1101/2024.01.29.577429] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/22/2024]
Abstract
The brain exhibits rich oscillatory dynamics that vary across tasks and states, such as the EEG oscillations that define sleep. These oscillations play critical roles in cognition and arousal, but the brainwide mechanisms underlying them are not yet described. Using simultaneous EEG and fast fMRI in subjects drifting between sleep and wakefulness, we developed a machine learning approach to investigate which brainwide fMRI dynamics predict alpha (8-12 Hz) and delta (1-4 Hz) rhythms. We predicted moment-by-moment EEG power from fMRI activity in held-out subjects, and found that information about alpha power was represented by a remarkably small set of regions, segregated in two distinct networks linked to arousal and visual systems. Conversely, delta rhythms were diffusely represented on a large spatial scale across the cortex. These results identify distributed networks that predict delta and alpha rhythms, and establish a computational framework for investigating fMRI brainwide dynamics underlying EEG oscillations.
Collapse
Affiliation(s)
- Leandro P L Jacob
- Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Sydney M Bailes
- Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA
- Boston University, Boston, MA, USA
| | - Stephanie D Williams
- Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA
- Boston University, Boston, MA, USA
| | | | - Laura D Lewis
- Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA
- Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston MA USA
| |
Collapse
|
20
|
Seeburger DT, Xu N, Ma M, Larson S, Godwin C, Keilholz SD, Schumacher EH. Time-varying functional connectivity predicts fluctuations in sustained attention in a serial tapping task. COGNITIVE, AFFECTIVE & BEHAVIORAL NEUROSCIENCE 2024; 24:111-125. [PMID: 38253775 PMCID: PMC10979291 DOI: 10.3758/s13415-024-01156-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 01/08/2024] [Indexed: 01/24/2024]
Abstract
The mechanisms for how large-scale brain networks contribute to sustained attention are unknown. Attention fluctuates from moment to moment, and this continuous change is consistent with dynamic changes in functional connectivity between brain networks involved in the internal and external allocation of attention. In this study, we investigated how brain network activity varied across different levels of attentional focus (i.e., "zones"). Participants performed a finger-tapping task, and guided by previous research, in-the-zone performance or state was identified by low reaction time variability and out-of-the-zone as the inverse. In-the-zone sessions tended to occur earlier in the session than out-of-the-zone blocks. This is unsurprising given the way attention fluctuates over time. Employing a novel method of time-varying functional connectivity, called the quasi-periodic pattern analysis (i.e., reliable, network-level low-frequency fluctuations), we found that the activity between the default mode network (DMN) and task positive network (TPN) is significantly more anti-correlated during in-the-zone states versus out-of-the-zone states. Furthermore, it is the frontoparietal control network (FPCN) switch that differentiates the two zone states. Activity in the dorsal attention network (DAN) and DMN were desynchronized across both zone states. During out-of-the-zone periods, FPCN synchronized with DMN, while during in-the-zone periods, FPCN switched to synchronized with DAN. In contrast, the ventral attention network (VAN) synchronized more closely with DMN during in-the-zone periods compared with out-of-the-zone periods. These findings demonstrate that time-varying functional connectivity of low frequency fluctuations across different brain networks varies with fluctuations in sustained attention or other processes that change over time.
Collapse
Affiliation(s)
- Dolly T Seeburger
- School of Psychology, Georgia Institute of Technology, Atlanta, GA, USA.
| | - Nan Xu
- Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, USA
| | - Marcus Ma
- College of Computing, Georgia Institute of Technology, Atlanta, GA, USA
| | - Sam Larson
- Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, USA
| | - Christine Godwin
- School of Psychology, Georgia Institute of Technology, Atlanta, GA, USA
| | - Shella D Keilholz
- Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, USA
| | - Eric H Schumacher
- School of Psychology, Georgia Institute of Technology, Atlanta, GA, USA.
| |
Collapse
|
21
|
Fan C, Xu D, Mei H, Zhong X, Ren J, Ma J, Ruan Z, Lv J, Liu X, Wang H, Gao L, Xu H. Hemispheric coupling between structural and functional asymmetries in clinically asymptomatic carotid stenosis with cognitive impairment. Brain Imaging Behav 2024; 18:192-206. [PMID: 37985612 DOI: 10.1007/s11682-023-00823-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/08/2023] [Indexed: 11/22/2023]
Abstract
Advanced carotid stenosis is a known risk factor for ischemic stroke and vascular dementia, and it is associated with multidomain cognitive impairment as well as asymmetric alterations in hemispheric structure and function. Here we introduced a novel measure-the asymmetry index of amplitude of low-frequency fluctuations (ALFF_AI)-derived from resting-state functional magnetic resonance imaging. This measure captures the hemispheric asymmetry of intrinsic brain activity using high-dimensional registration. We aimed to investigate functional brain asymmetric alterations in patients with severe asymptomatic carotid stenosis (SACS). Furthermore, we extended the analyses of ALFF_AI to different frequencies to detect frequency-specific alterations. Finally, we examined the coupling between hemispheric asymmetric structure and function and the relationship between these results and cognitive tests, as well as the white matter hyperintensity burden. SACS patients presented significantly decreased ALFF_AI in several clusters, including the visual, auditory, parahippocampal, Rolandic, and superior parietal regions. At low frequencies (0.01-0.25 Hz), the ALFF_AI exhibited prominent group differences as frequency increased. Further structure-function coupling analysis indicated that SACS patients had lower coupling in the lateral prefrontal, superior medial frontal, middle temporal, superior parietal, and striatum regions but higher coupling in the lateral occipital regions. These findings suggest that, under potential hemodynamic burden, SACS patients demonstrate asymmetric hemispheric configurations of intrinsic activity patterns and a decoupling between structural and functional asymmetries.
Collapse
Affiliation(s)
- Chenhong Fan
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuchang District, 430071, Wuhan City, Hubei Province, China
- The Interventional Diagnostic and Therapeutic Center, Zhongnan Hospital of Wuhan University, Wuchang District, 430071, Wuhan City, Hubei Province, China
| | - Dan Xu
- Department of Nuclear Medicine, Zhongnan Hospital of Wuhan University, Wuchang District, 430071, Wuhan City, Hubei Province, China
| | - Hao Mei
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuchang District, 430071, Wuhan City, Hubei Province, China
| | - Xiaoli Zhong
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuchang District, 430071, Wuhan City, Hubei Province, China
| | - Jinxia Ren
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuchang District, 430071, Wuhan City, Hubei Province, China
| | - Jiaojiao Ma
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuchang District, 430071, Wuhan City, Hubei Province, China
| | - Zhao Ruan
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuchang District, 430071, Wuhan City, Hubei Province, China
| | - Jinfeng Lv
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuchang District, 430071, Wuhan City, Hubei Province, China
| | - Xitong Liu
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuchang District, 430071, Wuhan City, Hubei Province, China
| | - Huan Wang
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuchang District, 430071, Wuhan City, Hubei Province, China
| | - Lei Gao
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuchang District, 430071, Wuhan City, Hubei Province, China.
| | - Haibo Xu
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuchang District, 430071, Wuhan City, Hubei Province, China.
| |
Collapse
|
22
|
Lurie DJ, Pappas I, D'Esposito M. Cortical timescales and the modular organization of structural and functional brain networks. Hum Brain Mapp 2024; 45:e26587. [PMID: 38339903 PMCID: PMC10823764 DOI: 10.1002/hbm.26587] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Revised: 12/01/2023] [Accepted: 12/21/2023] [Indexed: 02/12/2024] Open
Abstract
Recent years have seen growing interest in characterizing the properties of regional brain dynamics and their relationship to other features of brain structure and function. In particular, multiple studies have observed regional differences in the "timescale" over which activity fluctuates during periods of quiet rest. In the cerebral cortex, these timescales have been associated with both local circuit properties as well as patterns of inter-regional connectivity, including the extent to which each region exhibits widespread connectivity to other brain areas. In the current study, we build on prior observations of an association between connectivity and dynamics in the cerebral cortex by investigating the relationship between BOLD fMRI timescales and the modular organization of structural and functional brain networks. We characterize network community structure across multiple scales and find that longer timescales are associated with greater within-community functional connectivity and diverse structural connectivity. We also replicate prior observations of a positive correlation between timescales and structural connectivity degree. Finally, we find evidence for preferential functional connectivity between cortical areas with similar timescales. We replicate these findings in an independent dataset. These results contribute to our understanding of functional brain organization and structure-function relationships in the human brain, and support the notion that regional differences in cortical dynamics may in part reflect the topological role of each region within macroscale brain networks.
Collapse
Affiliation(s)
- Daniel J. Lurie
- Department of PsychologyUniversity of CaliforniaBerkeleyCaliforniaUSA
- Department of Biomedical Informatics University of Pittsburgh School of Medicine PittsburghPennsylvaniaUSA
| | - Ioannis Pappas
- Department of Neurology, Keck School of MedicineUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Mark D'Esposito
- Department of Psychology and Helen Wills Neuroscience InstituteUniversity of CaliforniaBerkeleyCaliforniaUSA
| |
Collapse
|
23
|
Lei VLC, Leong TI, Leong CT, Liu L, Choi CU, Sereno MI, Li D, Huang R. Phase-encoded fMRI tracks down brainstorms of natural language processing with subsecond precision. Hum Brain Mapp 2024; 45:e26617. [PMID: 38339788 PMCID: PMC10858339 DOI: 10.1002/hbm.26617] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Revised: 12/04/2023] [Accepted: 01/21/2024] [Indexed: 02/12/2024] Open
Abstract
Natural language processing unfolds information overtime as spatially separated, multimodal, and interconnected neural processes. Existing noninvasive subtraction-based neuroimaging techniques cannot simultaneously achieve the spatial and temporal resolutions required to visualize ongoing information flows across the whole brain. Here we have developed rapid phase-encoded designs to fully exploit the temporal information latent in functional magnetic resonance imaging data, as well as overcoming scanner noise and head-motion challenges during overt language tasks. We captured real-time information flows as coherent hemodynamic waves traveling over the cortical surface during listening, reading aloud, reciting, and oral cross-language interpreting tasks. We were able to observe the timing, location, direction, and surge of traveling waves in all language tasks, which were visualized as "brainstorms" on brain "weather" maps. The paths of hemodynamic traveling waves provide direct evidence for dual-stream models of the visual and auditory systems as well as logistics models for crossmodal and cross-language processing. Specifically, we have tracked down the step-by-step processing of written or spoken sentences first being received and processed by the visual or auditory streams, carried across language and domain-general cognitive regions, and finally delivered as overt speeches monitored through the auditory cortex, which gives a complete picture of information flows across the brain during natural language functioning. PRACTITIONER POINTS: Phase-encoded fMRI enables simultaneous imaging of high spatial and temporal resolution, capturing continuous spatiotemporal dynamics of the entire brain during real-time overt natural language tasks. Spatiotemporal traveling wave patterns provide direct evidence for constructing comprehensive and explicit models of human information processing. This study unlocks the potential of applying rapid phase-encoded fMRI to indirectly track the underlying neural information flows of sequential sensory, motor, and high-order cognitive processes.
Collapse
Affiliation(s)
- Victoria Lai Cheng Lei
- Centre for Cognitive and Brain SciencesUniversity of MacauTaipaChina
- Faculty of Arts and HumanitiesUniversity of MacauTaipaChina
| | - Teng Ieng Leong
- Centre for Cognitive and Brain SciencesUniversity of MacauTaipaChina
- Faculty of Arts and HumanitiesUniversity of MacauTaipaChina
| | - Cheok Teng Leong
- Centre for Cognitive and Brain SciencesUniversity of MacauTaipaChina
- Faculty of Science and TechnologyUniversity of MacauTaipaChina
| | - Lili Liu
- Centre for Cognitive and Brain SciencesUniversity of MacauTaipaChina
- Faculty of Science and TechnologyUniversity of MacauTaipaChina
| | - Chi Un Choi
- Centre for Cognitive and Brain SciencesUniversity of MacauTaipaChina
| | - Martin I. Sereno
- Department of PsychologySan Diego State UniversitySan DiegoCaliforniaUSA
| | - Defeng Li
- Centre for Cognitive and Brain SciencesUniversity of MacauTaipaChina
- Faculty of Arts and HumanitiesUniversity of MacauTaipaChina
| | - Ruey‐Song Huang
- Centre for Cognitive and Brain SciencesUniversity of MacauTaipaChina
- Faculty of Science and TechnologyUniversity of MacauTaipaChina
| |
Collapse
|
24
|
Huang Z, Mashour GA, Hudetz AG. Propofol Disrupts the Functional Core-Matrix Architecture of the Thalamus in Humans. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.23.576934. [PMID: 38328136 PMCID: PMC10849566 DOI: 10.1101/2024.01.23.576934] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/09/2024]
Abstract
Research into the role of thalamocortical circuits in anesthesia-induced unconsciousness is difficult due to anatomical and functional complexity. Prior neuroimaging studies have examined either the thalamus as a whole or focused on specific subregions, overlooking the distinct neuronal subtypes like core and matrix cells. We conducted a study of heathy volunteers and functional magnetic resonance imaging during conscious baseline, deep sedation, and recovery. We advanced the functional gradient mapping technique to delineate the functional geometry of thalamocortical circuits, within a framework of the unimodal-transmodal functional axis of the cortex. We observed a significant shift in this geometry during unconsciousness, marked by the dominance of unimodal over transmodal geometry. This alteration was closely linked to the spatial variations in the density of matrix cells within the thalamus. This research bridges cellular and systems-level understanding, highlighting the crucial role of thalamic core-matrix functional architecture in understanding the neural mechanisms of states of consciousness.
Collapse
Affiliation(s)
- Zirui Huang
- Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, MI 48109, USA
- Center for Consciousness Science, University of Michigan Medical School, Ann Arbor, MI 48109, USA
- Michigan Psychedelic Center, University of Michigan Medical School, Ann Arbor, MI, 48109, USA
- Neuroscience Graduate Program, University of Michigan, Ann Arbor, MI 48109, USA
| | - George A Mashour
- Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, MI 48109, USA
- Center for Consciousness Science, University of Michigan Medical School, Ann Arbor, MI 48109, USA
- Michigan Psychedelic Center, University of Michigan Medical School, Ann Arbor, MI, 48109, USA
- Neuroscience Graduate Program, University of Michigan, Ann Arbor, MI 48109, USA
- Department of Pharmacology, University of Michigan Medical School, Ann Arbor, MI, 48109, USA
| | - Anthony G Hudetz
- Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, MI 48109, USA
- Center for Consciousness Science, University of Michigan Medical School, Ann Arbor, MI 48109, USA
- Michigan Psychedelic Center, University of Michigan Medical School, Ann Arbor, MI, 48109, USA
- Neuroscience Graduate Program, University of Michigan, Ann Arbor, MI 48109, USA
| |
Collapse
|
25
|
Yang C, Coalson TS, Smith SM, Elam JS, Van Essen DC, Glasser MF. Automating the Human Connectome Project's Temporal ICA Pipeline. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.15.574667. [PMID: 38293188 PMCID: PMC10827070 DOI: 10.1101/2024.01.15.574667] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/01/2024]
Abstract
Functional magnetic resonance imaging (fMRI) data are dominated by noise and artifacts, with only a small fraction of the variance relating to neural activity. Temporal independent component analysis (tICA) is a recently developed method that enables selective denoising of fMRI artifacts related to physiology such as respiration. However, an automated and easy to use pipeline for tICA has not previously been available; instead, two manual steps have been necessary: 1) setting the group spatial ICA dimensionality after MELODIC's Incremental Group-PCA (MIGP) and 2) labeling tICA components as artifacts versus signals. Moreover, guidance has been lacking as to how many subjects and timepoints are needed to adequately re-estimate the temporal ICA decomposition and what alternatives are available for smaller groups or even individual subjects. Here, we introduce a nine-step fully automated tICA pipeline which removes global artifacts from fMRI dense timeseries after sICA+FIX cleaning and MSMAll alignment driven by functionally relevant areal features. Additionally, we have developed an automated "reclean" Pipeline for improved spatial ICA (sICA) artifact removal. Two major automated components of the pipeline are 1) an automatic group spatial ICA (sICA) dimensionality selection for MIGP data enabled by fitting multiple Wishart distributions; 2) a hierarchical classifier to distinguish group tICA signal components from artifactual components, equipped with a combination of handcrafted features from domain expert knowledge and latent features obtained via self-supervised learning on spatial maps. We demonstrate that the dimensionality estimated for the MIGP data from HCP Young Adult 3T and 7T datasets is comparable to previous manual tICA estimates, and that the group sICA decomposition is highly reproducible. We also show that the tICA classifier achieved over 0.98 Precision-Recall Area Under Curve (PR-AUC) and that the correctly classified components account for over 95% of the tICA-represented variance on multiple held-out evaluation datasets including the HCP-Young Adult, HCP-Aging and HCP-Development datasets under various settings. Our automated tICA pipeline is now available as part of the HCP pipelines, providing a powerful and user-friendly tool for the neuroimaging community.
Collapse
|
26
|
Davis ZW, Busch A, Stewerd C, Muller L, Reynolds J. Horizontal cortical connections shape intrinsic traveling waves into feature-selective motifs that regulate perceptual sensitivity. RESEARCH SQUARE 2024:rs.3.rs-3830199. [PMID: 38260448 PMCID: PMC10802692 DOI: 10.21203/rs.3.rs-3830199/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
Intrinsic, ongoing fluctuations of cortical activity form traveling waves that modulate the gain of sensory-evoked responses and perceptual sensitivity. Several lines of evidence suggest that intrinsic traveling waves (iTWs) may arise, in part, from the coordination of synaptic activity through the recurrent horizontal connectivity within cortical areas, which include long range patchy connections that link neurons with shared feature preferences. In a spiking network model with anatomical topology that incorporates feature-selective patchy connections, which we call the Balanced Patchy Network (BPN), we observe repeated iTWs, which we refer to as motifs. In the model, motifs stem from fluctuations in the excitability of like-tuned neurons that result from shifts in E/I balance as action potentials traverse these patchy connections. To test if feature-selective motifs occur in vivo, we examined data previously recorded using multielectrode arrays in Area MT of marmosets trained to perform a threshold visual detection task. Using a newly developed method for comparing the similarity of wave patterns we found that some iTWs can be grouped into motifs. As predicted by the BPN, many of these motifs are feature selective, exhibiting direction-selective modulations in ongoing spiking activity. Further, motifs modulate the gain of the response evoked by a target and perceptual sensitivity to the target if the target matches the preference of the motif. These results provide evidence that iTWs are shaped by the patterns of horizontal fiber projections in the cortex and that patchy connections enable iTWs to regulate neural and perceptual sensitivity in a feature selective manner.
Collapse
Affiliation(s)
- Zachary W Davis
- The Salk Institute for Biological Studies, La Jolla, CA, USA. 92037
- Department of Ophthalmology and Visual Science, University of Utah, SLC, UT, USA 84112
| | - Alexandria Busch
- Department of Applied Mathematics, Western University, London, ON, Canada. N6A 3K7
- Brain and Mind Institute, Western University, London, ON, Canada. N6A 3K7
| | - Christopher Stewerd
- Department of Applied Mathematics, Western University, London, ON, Canada. N6A 3K7
- Brain and Mind Institute, Western University, London, ON, Canada. N6A 3K7
| | - Lyle Muller
- Department of Applied Mathematics, Western University, London, ON, Canada. N6A 3K7
- Brain and Mind Institute, Western University, London, ON, Canada. N6A 3K7
| | - John Reynolds
- The Salk Institute for Biological Studies, La Jolla, CA, USA. 92037
| |
Collapse
|
27
|
Krimmel SR, Laumann TO, Chauvin RJ, Hershey T, Roland JL, Shimony JS, Willie JT, Norris SA, Marek S, Van AN, Monk J, Scheidter KM, Whiting F, Ramirez-Perez N, Metoki A, Wang A, Kay BP, Nahman-Averbuch H, Fair DA, Lynch CJ, Raichle ME, Gordon EM, Dosenbach NUF. The brainstem's red nucleus was evolutionarily upgraded to support goal-directed action. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.12.30.573730. [PMID: 38260662 PMCID: PMC10802246 DOI: 10.1101/2023.12.30.573730] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
The red nucleus is a large brainstem structure that coordinates limb movement for locomotion in quadrupedal animals (Basile et al., 2021). The humans red nucleus has a different pattern of anatomical connectivity compared to quadrupeds, suggesting a unique purpose (Hatschek, 1907). Previously the function of the human red nucleus remained unclear at least partly due to methodological limitations with brainstem functional neuroimaging (Sclocco et al., 2018). Here, we used our most advanced resting-state functional connectivity (RSFC) based precision functional mapping (PFM) in highly sampled individuals (n = 5) and large group-averaged datasets (combined N ~ 45,000), to precisely examine red nucleus functional connectivity. Notably, red nucleus functional connectivity to motor-effector networks (somatomotor hand, foot, and mouth) was minimal. Instead, red nucleus functional connectivity along the central sulcus was specific to regions of the recently discovered somato-cognitive action network (SCAN; (Gordon et al., 2023)). Outside of primary motor cortex, red nucleus connectivity was strongest to the cingulo-opercular (CON) and salience networks, involved in action/cognitive control (Dosenbach et al., 2007; Newbold et al., 2021) and reward/motivated behavior (Seeley, 2019), respectively. Functional connectivity to these two networks was organized into discrete dorsal-medial and ventral-lateral zones. Red nucleus functional connectivity to the thalamus recapitulated known structural connectivity of the dento-rubral thalamic tract (DRTT) and could prove clinically useful in functionally targeting the ventral intermediate (VIM) nucleus. In total, our results indicate that far from being a 'motor' structure, the red nucleus is better understood as a brainstem nucleus for implementing goal-directed behavior, integrating behavioral valence and action plans.
Collapse
Affiliation(s)
- Samuel R Krimmel
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Timothy O Laumann
- Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Roselyne J Chauvin
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Tamara Hershey
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA
- Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri, USA
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri, USA
- Department of Psychological & Brain Sciences, Washington University, St. Louis, Missouri, USA
| | - Jarod L Roland
- Department of Neurosurgery, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Joshua S Shimony
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Jon T Willie
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA
- Department of Psychiatry, Weill Cornell Medicine, New York, New York, USA
- Department of Neuroscience, Washington University School of Medicine, St. Louis, Missouri
| | - Scott A Norris
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Scott Marek
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Andrew N Van
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA
- Department of Biomedical Engineering, Washington University, St. Louis, Missouri
| | - Julia Monk
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Kristen M Scheidter
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Forrest Whiting
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Nadeshka Ramirez-Perez
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA
- Department of Neurosurgery, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Athanasia Metoki
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Anxu Wang
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri, USA
- Division of Computation and Data Science, Washington University, St. Louis, Missouri, USA
| | - Benjamin P Kay
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Hadas Nahman-Averbuch
- Washington University Pain Center, Department of Anesthesiology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Damien A Fair
- Department of Pediatrics, University of Minnesota, Minneapolis, Minnesota, USA
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, Minnesota, USA
- Institute of Child Development, University of Minnesota, Minneapolis, Minnesota, USA
| | - Charles J Lynch
- Department of Psychiatry, Weill Cornell Medicine, New York, New York, USA
| | - Marcus E Raichle
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri, USA
- Department of Psychological & Brain Sciences, Washington University, St. Louis, Missouri, USA
- Department of Neuroscience, Washington University School of Medicine, St. Louis, Missouri
- Department of Biomedical Engineering, Washington University, St. Louis, Missouri
| | - Evan M Gordon
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Nico U F Dosenbach
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri, USA
- Department of Psychological & Brain Sciences, Washington University, St. Louis, Missouri, USA
- Department of Biomedical Engineering, Washington University, St. Louis, Missouri
- Program in Occupational Therapy, Washington University, St. Louis, Missouri, USA
- Department of Pediatrics, Washington University School of Medicine, St. Louis, Missouri, USA
| |
Collapse
|
28
|
Liu X, Wang Z, Liu S, Gong L, Sosa PAV, Becker B, Jung TP, Dai XJ, Wan F. Activation network improves spatiotemporal modelling of human brain communication processes. Neuroimage 2024; 285:120472. [PMID: 38007187 DOI: 10.1016/j.neuroimage.2023.120472] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Revised: 11/08/2023] [Accepted: 11/22/2023] [Indexed: 11/27/2023] Open
Abstract
Dynamic functional networks (DFN) have considerably advanced modelling of the brain communication processes. The prevailing implementation capitalizes on the system and network-level correlations between time series. However, this approach does not account for the continuous impact of non-dynamic dependencies within the statistical correlation, resulting in relatively stable connectivity patterns of DFN over time with limited sensitivity for communication dynamic between brain regions. Here, we propose an activation network framework based on the activity of functional connectivity (AFC) to extract new types of connectivity patterns during brain communication process. The AFC captures potential time-specific fluctuations associated with the brain communication processes by eliminating the non-dynamic dependency of the statistical correlation. In a simulation study, the positive correlation (r=0.966,p<0.001) between the extracted dynamic dependencies and the simulated "ground truth" validates the method's dynamic detection capability. Applying to autism spectrum disorders (ASD) and COVID-19 datasets, the proposed activation network extracts richer topological reorganization information, which is largely invisible to the DFN. Detailed, the activation network exhibits significant inter-regional connections between function-specific subnetworks and reconfigures more efficiently in the temporal dimension. Furthermore, the DFN fails to distinguish between patients and healthy controls. However, the proposed method reveals a significant decrease (p<0.05) in brain information processing abilities in patients. Finally, combining two types of networks successfully classifies ASD (83.636 % ± 11.969 %,mean±std) and COVID-19 (67.333 % ± 5.398 %). These findings suggest the proposed method could be a potential analytic framework for elucidating the neural mechanism of brain dynamics.
Collapse
Affiliation(s)
- Xucheng Liu
- Department of Electrical and Computer Engineering, Faculty of Science and Technology, University of Macau, Macau 999078, China; Centre for Cognitive and Brain Sciences, Institute of Collaborative Innovation, University of Macau, Macau, 999078, China
| | - Ze Wang
- Macao Centre for Mathematical Sciences, and the Respiratory Disease AI Laboratory on Epidemic Intelligence and Medical Big Data Instrument Applications, Faculty of Innovation Engineering, Macau University of Science and Technology, Macau, 999078, China
| | - Shun Liu
- Department of Electrical and Computer Engineering, Faculty of Science and Technology, University of Macau, Macau 999078, China; Centre for Cognitive and Brain Sciences, Institute of Collaborative Innovation, University of Macau, Macau, 999078, China
| | - Lianggeng Gong
- Department of Radiology, The Second Affiliated Hospital of Nanchang University, Nanchang, 330006, China
| | - Pedro A Valdes Sosa
- The Clinical Hospital of Chengdu Brain Sciences Institute. University of Electronic Sciences and Technology of China, Chengdu, 611731, China; Cuban Neuroscience Center, La Habana 10200, Cuba
| | - Benjamin Becker
- State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong 999077, China; Department of Psychology, The University of Hong Kong, Hong Kong 999077, China
| | - Tzyy-Ping Jung
- Department of Bioengineering, University of California at San Diego, La Jolla 92092, United States; Swartz Center for Computational Neuroscience, Institute for Neural Computation, University of California at San Diego, La Jolla 92093, United States
| | - Xi-Jian Dai
- Department of Electrical and Computer Engineering, Faculty of Science and Technology, University of Macau, Macau 999078, China; Centre for Cognitive and Brain Sciences, Institute of Collaborative Innovation, University of Macau, Macau, 999078, China; Department of Radiology, The Second Affiliated Hospital of Nanchang University, Nanchang, 330006, China.
| | - Feng Wan
- Department of Electrical and Computer Engineering, Faculty of Science and Technology, University of Macau, Macau 999078, China; Centre for Cognitive and Brain Sciences, Institute of Collaborative Innovation, University of Macau, Macau, 999078, China.
| |
Collapse
|
29
|
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] [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.
Collapse
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.
| |
Collapse
|
30
|
Raut RV, Rosenthal ZP, Wang X, Miao H, Zhang Z, Lee JM, Raichle ME, Bauer AQ, Brunton SL, Brunton BW, Kutz JN. Arousal as a universal embedding for spatiotemporal brain dynamics. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.06.565918. [PMID: 38187528 PMCID: PMC10769245 DOI: 10.1101/2023.11.06.565918] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/09/2024]
Abstract
Neural activity in awake organisms shows widespread and spatiotemporally diverse correlations with behavioral and physiological measurements. We propose that this covariation reflects in part the dynamics of a unified, arousal-related process that regulates brain-wide physiology on the timescale of seconds. Taken together with theoretical foundations in dynamical systems, this interpretation leads us to a surprising prediction: that a single, scalar measurement of arousal (e.g., pupil diameter) should suffice to reconstruct the continuous evolution of multimodal, spatiotemporal measurements of large-scale brain physiology. To test this hypothesis, we perform multimodal, cortex-wide optical imaging and behavioral monitoring in awake mice. We demonstrate that spatiotemporal measurements of neuronal calcium, metabolism, and blood-oxygen can be accurately and parsimoniously modeled from a low-dimensional state-space reconstructed from the time history of pupil diameter. Extending this framework to behavioral and electrophysiological measurements from the Allen Brain Observatory, we demonstrate the ability to integrate diverse experimental data into a unified generative model via mappings from an intrinsic arousal manifold. Our results support the hypothesis that spontaneous, spatially structured fluctuations in brain-wide physiology-widely interpreted to reflect regionally-specific neural communication-are in large part reflections of an arousal-related process. This enriched view of arousal dynamics has broad implications for interpreting observations of brain, body, and behavior as measured across modalities, contexts, and scales.
Collapse
Affiliation(s)
- Ryan V. Raut
- Allen Institute, Seattle, WA, USA
- Department of Physiology & Biophysics, University of Washington, Seattle, WA, USA
| | - Zachary P. Rosenthal
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Xiaodan Wang
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, MO, USA
| | - Hanyang Miao
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
| | - Zhanqi Zhang
- Department of Computer Science & Engineering, University of California San Diego, La Jolla, CA, USA
| | - Jin-Moo Lee
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
| | - Marcus E. Raichle
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, MO, USA
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
| | - Adam Q. Bauer
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, MO, USA
| | - Steven L. Brunton
- Department of Mechanical Engineering, University of Washington, Seattle, WA, USA
| | | | - J. Nathan Kutz
- Department of Applied Mathematics, University of Washington, Seattle, WA, USA
| |
Collapse
|
31
|
Dai R, Huang Z, Larkin TE, Tarnal V, Picton P, Vlisides PE, Janke E, McKinney A, Hudetz AG, Harris RE, Mashour GA. Psychedelic concentrations of nitrous oxide reduce functional differentiation in frontoparietal and somatomotor cortical networks. Commun Biol 2023; 6:1284. [PMID: 38114805 PMCID: PMC10730842 DOI: 10.1038/s42003-023-05678-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Accepted: 12/05/2023] [Indexed: 12/21/2023] Open
Abstract
Despite the longstanding use of nitrous oxide and descriptions of its psychological effects more than a century ago, there is a paucity of neurobiological investigation of associated psychedelic experiences. We measure the brain's functional geometry (through analysis of cortical gradients) and temporal dynamics (through analysis of co-activation patterns) using human resting-state functional magnetic resonance imaging data acquired before and during administration of 35% nitrous oxide. Both analyses demonstrate that nitrous oxide reduces functional differentiation in frontoparietal and somatomotor networks. Importantly, the subjective psychedelic experience induced by nitrous oxide is inversely correlated with the degree of functional differentiation. Thus, like classical psychedelics acting on serotonin receptors, nitrous oxide flattens the functional geometry of the cortex and disrupts temporal dynamics in association with psychoactive effects.
Collapse
Affiliation(s)
- Rui Dai
- Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, MI, 48109, USA
- Center for Consciousness Science, University of Michigan Medical School, Ann Arbor, MI, 48109, USA
- Michigan Psychedelic Center, University of Michigan Medical School, Ann Arbor, MI, 48109, USA
| | - Zirui Huang
- Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, MI, 48109, USA.
- Center for Consciousness Science, University of Michigan Medical School, Ann Arbor, MI, 48109, USA.
- Michigan Psychedelic Center, University of Michigan Medical School, Ann Arbor, MI, 48109, USA.
- Neuroscience Graduate Program, University of Michigan, Ann Arbor, MI, 48109, USA.
| | - Tony E Larkin
- Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, MI, 48109, USA
- Chronic Pain and Fatigue Research Center, University of Michigan Medical School, Ann Arbor, MI, 48109, USA
| | - Vijay Tarnal
- Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, MI, 48109, USA
- Center for Consciousness Science, University of Michigan Medical School, Ann Arbor, MI, 48109, USA
- Michigan Psychedelic Center, University of Michigan Medical School, Ann Arbor, MI, 48109, USA
| | - Paul Picton
- Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, MI, 48109, USA
- Center for Consciousness Science, University of Michigan Medical School, Ann Arbor, MI, 48109, USA
- Michigan Psychedelic Center, University of Michigan Medical School, Ann Arbor, MI, 48109, USA
| | - Phillip E Vlisides
- Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, MI, 48109, USA
- Center for Consciousness Science, University of Michigan Medical School, Ann Arbor, MI, 48109, USA
- Michigan Psychedelic Center, University of Michigan Medical School, Ann Arbor, MI, 48109, USA
| | - Ellen Janke
- Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, MI, 48109, USA
- Center for Consciousness Science, University of Michigan Medical School, Ann Arbor, MI, 48109, USA
- Michigan Psychedelic Center, University of Michigan Medical School, Ann Arbor, MI, 48109, USA
| | - Amy McKinney
- Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, MI, 48109, USA
| | - Anthony G Hudetz
- Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, MI, 48109, USA
- Center for Consciousness Science, University of Michigan Medical School, Ann Arbor, MI, 48109, USA
- Michigan Psychedelic Center, University of Michigan Medical School, Ann Arbor, MI, 48109, USA
- Neuroscience Graduate Program, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Richard E Harris
- Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, MI, 48109, USA
- Michigan Psychedelic Center, University of Michigan Medical School, Ann Arbor, MI, 48109, USA
- Neuroscience Graduate Program, University of Michigan, Ann Arbor, MI, 48109, USA
- Chronic Pain and Fatigue Research Center, University of Michigan Medical School, Ann Arbor, MI, 48109, USA
| | - George A Mashour
- Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, MI, 48109, USA
- Center for Consciousness Science, University of Michigan Medical School, Ann Arbor, MI, 48109, USA
- Michigan Psychedelic Center, University of Michigan Medical School, Ann Arbor, MI, 48109, USA
- Neuroscience Graduate Program, University of Michigan, Ann Arbor, MI, 48109, USA
- Department of Pharmacology, University of Michigan Medical School, Ann Arbor, MI, 48109, USA
| |
Collapse
|
32
|
Pagani M, Gutierrez-Barragan D, de Guzman AE, Xu T, Gozzi A. Mapping and comparing fMRI connectivity networks across species. Commun Biol 2023; 6:1238. [PMID: 38062107 PMCID: PMC10703935 DOI: 10.1038/s42003-023-05629-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2023] [Accepted: 11/22/2023] [Indexed: 12/18/2023] Open
Abstract
Technical advances in neuroimaging, notably in fMRI, have allowed distributed patterns of functional connectivity to be mapped in the human brain with increasing spatiotemporal resolution. Recent years have seen a growing interest in extending this approach to rodents and non-human primates to understand the mechanism of fMRI connectivity and complement human investigations of the functional connectome. Here, we discuss current challenges and opportunities of fMRI connectivity mapping across species. We underscore the critical importance of physiologically decoding neuroimaging measures of brain (dys)connectivity via multiscale mechanistic investigations in animals. We next highlight a set of general principles governing the organization of mammalian connectivity networks across species. These include the presence of evolutionarily conserved network systems, a dominant cortical axis of functional connectivity, and a common repertoire of topographically conserved fMRI spatiotemporal modes. We finally describe emerging approaches allowing comparisons and extrapolations of fMRI connectivity findings across species. As neuroscientists gain access to increasingly sophisticated perturbational, computational and recording tools, cross-species fMRI offers novel opportunities to investigate the large-scale organization of the mammalian brain in health and disease.
Collapse
Affiliation(s)
- Marco Pagani
- Functional Neuroimaging Laboratory, Center for Neuroscience and Cognitive Systems, Istituto Italiano di Tecnologia, Rovereto, Italy
- Autism Center, Child Mind Institute, New York, NY, USA
- IMT School for Advanced Studies, Lucca, Italy
| | - Daniel Gutierrez-Barragan
- Functional Neuroimaging Laboratory, Center for Neuroscience and Cognitive Systems, Istituto Italiano di Tecnologia, Rovereto, Italy
| | - A Elizabeth de Guzman
- Functional Neuroimaging Laboratory, Center for Neuroscience and Cognitive Systems, Istituto Italiano di Tecnologia, Rovereto, Italy
| | - Ting Xu
- Center for the Integrative Developmental Neuroscience, Child Mind Institute, New York, NY, USA
| | - Alessandro Gozzi
- Functional Neuroimaging Laboratory, Center for Neuroscience and Cognitive Systems, Istituto Italiano di Tecnologia, Rovereto, Italy.
| |
Collapse
|
33
|
Han F, Liu X, Mailman RB, Huang X, Liu X. Resting-state global brain activity affects early β-amyloid accumulation in default mode network. Nat Commun 2023; 14:7788. [PMID: 38012153 PMCID: PMC10682457 DOI: 10.1038/s41467-023-43627-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Accepted: 11/14/2023] [Indexed: 11/29/2023] Open
Abstract
It remains unclear why β-amyloid (Aβ) plaque, a hallmark pathology of Alzheimer's disease (AD), first accumulates cortically in the default mode network (DMN), years before AD diagnosis. Resting-state low-frequency ( < 0.1 Hz) global brain activity recently was linked to AD, presumably due to its role in glymphatic clearance. Here we show that the preferential Aβ accumulation in the DMN at the early stage of Aβ pathology was associated with the preferential reduction of global brain activity in the same regions. This can be partly explained by its failure to reach these regions as propagating waves. Together, these findings highlight the important role of resting-state global brain activity in early preferential Aβ deposition in the DMN.
Collapse
Affiliation(s)
- Feng Han
- Department of Biomedical Engineering, The Pennsylvania State University, State College, PA, USA
| | - Xufu Liu
- Department of Biomedical Engineering, The Pennsylvania State University, State College, PA, USA
| | - Richard B Mailman
- Departments of Neurology and Pharmacology, Translational Brain Research Center, Pennsylvania State University College of Medicine and Milton S. Hershey Medical Center, Hershey, PA, USA
| | - Xuemei Huang
- Departments of Neurology and Pharmacology, Translational Brain Research Center, Pennsylvania State University College of Medicine and Milton S. Hershey Medical Center, Hershey, PA, USA
- Departments of Radiology, Neurosurgery, and Kinesiology, Translational Brain Research Center, Pennsylvania State University and Milton S. Hershey Medical Center, Hershey, PA, USA
- Institute for Computational and Data Sciences, The Pennsylvania State University, State College, PA, USA
| | - Xiao Liu
- Department of Biomedical Engineering, The Pennsylvania State University, State College, PA, USA.
- Institute for Computational and Data Sciences, The Pennsylvania State University, State College, PA, USA.
| |
Collapse
|
34
|
Scalabrini A, De Amicis M, Brugnera A, Cavicchioli M, Çatal Y, Keskin K, Pilar JG, Zhang J, Osipova B, Compare A, Greco A, Benedetti F, Mucci C, Northoff G. The self and our perception of its synchrony - Beyond internal and external cognition. Conscious Cogn 2023; 116:103600. [PMID: 37976779 DOI: 10.1016/j.concog.2023.103600] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Revised: 10/23/2023] [Accepted: 11/02/2023] [Indexed: 11/19/2023]
Abstract
The self is the core of our mental life which connects one's inner mental life with the external perception. Since synchrony is a key feature of the biological world and its various species, what role does it play for humans? We conducted a large-scale psychological study (n = 1072) combining newly developed visual analogue scales (VAS) for the perception of synchrony and internal and external cognition complemented by several psychological questionnaires. Overall, our findings showed close connection of the perception of synchrony of the self with both internal (i.e., body and cognition) and external (i.e., others, environment/nature) synchrony being associated positively with adaptive and negatively with maladaptive traits of self. Moreover, we have demonstrated how external (i.e., life events like the COVID-19 pandemic) variables modulate the perception of the self's internal-external synchrony. These findings suggest how synchrony with self plays a central role during times of uncertainty.
Collapse
Affiliation(s)
- Andrea Scalabrini
- Department of Human and Social Sciences, University of Bergamo, Bergamo, Italy.
| | | | - Agostino Brugnera
- Department of Human and Social Sciences, University of Bergamo, Bergamo, Italy
| | | | - Yasir Çatal
- The Royal's Institute of Mental Health Research & University of Ottawa. Brain and Mind Research Institute, Centre for Neural Dynamics, Faculty of Medicine, University of Ottawa, Ottawa, 145 Carling Avenue, Rm. 6435, Ottawa, Ontario K1Z 7K4, Canada; Department of Cellular and Molecular Medicine University of Ottawa, Ottawa, Canada
| | - Kaan Keskin
- Ege University Faculty of Medicine, Department of Psychiatry, 35100 Bornova-İzmir, Turkey
| | - Javier Gomez Pilar
- Biomedical Engineering Group, University of Valladolid, Valladolid, Spain; Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER‑BBN), Valladolid, Spain
| | - Jianfeng Zhang
- Center for Brain Disorders and Cognitive Sciences, Shenzhen University, Shenzhen 518055, Guangdong Province, China
| | - Bella Osipova
- Moscow State University of Psychology and Education (MSUPE)
| | - Angelo Compare
- Department of Human and Social Sciences, University of Bergamo, Bergamo, Italy
| | - Andrea Greco
- Department of Human and Social Sciences, University of Bergamo, Bergamo, Italy
| | - Francesco Benedetti
- University Vita- Salute San Raffaele, Milan, Italy; Psychiatry & Clinical Psychobiology Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Clara Mucci
- Department of Human and Social Sciences, University of Bergamo, Bergamo, Italy
| | - Georg Northoff
- University Vita- Salute San Raffaele, Milan, Italy; The Royal's Institute of Mental Health Research & University of Ottawa. Brain and Mind Research Institute, Centre for Neural Dynamics, Faculty of Medicine, University of Ottawa, Ottawa, 145 Carling Avenue, Rm. 6435, Ottawa, Ontario K1Z 7K4, Canada; Mental Health Centre, Zhejiang University School of Medicine, Tianmu Road 305, Hangzhou, Zhejiang Province 310013, China; Centre for Cognition and Brain Disorders, Hangzhou Normal University, Tianmu Road 305, Hangzhou, Zhejiang Province 310013, China.
| |
Collapse
|
35
|
Chiou R, Margulies D, Soltanlou M, Jefferies E, Kadosh RC. Semantic cognition versus numerical cognition: a topographical perspective. Trends Cogn Sci 2023; 27:993-995. [PMID: 37634952 DOI: 10.1016/j.tics.2023.08.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Revised: 07/12/2023] [Accepted: 08/06/2023] [Indexed: 08/29/2023]
Abstract
Semantic cognition and numerical cognition are dissociable faculties with separable neural mechanisms. However, recent advances in the cortical topography of the temporal and parietal lobes have revealed a common organisational principle for the neural representations of semantics and numbers. We discuss their convergence and divergence through the prism of topography.
Collapse
Affiliation(s)
- Rocco Chiou
- School of Psychology, University of Surrey, Guildford, UK; Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK.
| | - Daniel Margulies
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK; The Integrative Neuroscience and Cognition Center, University of Paris, Paris, France
| | | | | | | |
Collapse
|
36
|
Yang Y, Leopold DA, Duyn JH, Sipe GO, Liu X. Intrinsic forebrain arousal dynamics governs sensory stimulus encoding. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.04.560900. [PMID: 37986990 PMCID: PMC10659438 DOI: 10.1101/2023.10.04.560900] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2023]
Abstract
The neural encoding of sensory stimuli is subject to the brain's internal circuit dynamics. Recent work has demonstrated that the resting brain exhibits widespread, coordinated activity that plays out over multisecond timescales in the form of quasi-periodic spiking cascades. Here we demonstrate that these intrinsic dynamics persist during the presentation of visual stimuli and markedly influence the efficacy of feature encoding in the visual cortex. During periods of passive viewing, the sensory encoding of visual stimuli was determined by quasi-periodic cascade cycle evolving over several seconds. During this cycle, high efficiency encoding occurred during peak arousal states, alternating in time with hippocampal ripples, which were most frequent in low arousal states. However, during bouts of active locomotion, these arousal dynamics were abolished: the brain remained in a state in which visual coding efficiency remained high and ripples were absent. We hypothesize that the brain's observed dynamics during awake, passive viewing reflect an adaptive cycle of alternating exteroceptive sensory sampling and internal mnemonic function.
Collapse
Affiliation(s)
- Yifan Yang
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA, 16802, USA
| | - David A. Leopold
- Neurophysiology Imaging Facility, National Institute of Mental Health, National Institute of Neurological. Disorders and Stroke, and National Eye Institute, National Institutes of Health, Bethesda, MD, 20892, USA
- Section on Cognitive Neurophysiology and Imaging, Laboratory of Neuropsychology, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Jeff H. Duyn
- Advanced MRI Section, Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA
| | - Grayson O. Sipe
- Department of Biology, The Pennsylvania State University, University Park, PA, 16802, USA
| | - Xiao Liu
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA, 16802, USA
- Institute for Computational and Data Sciences, The Pennsylvania State University, University Park, PA, 16802, USA
| |
Collapse
|
37
|
Han Z, Liu T, Shi Z, Zhang J, Suo D, Wang L, Chen D, Wu J, Yan T. Investigating the heterogeneity within the somatosensory-motor network and its relationship with the attention and default systems. PNAS NEXUS 2023; 2:pgad276. [PMID: 37693210 PMCID: PMC10485902 DOI: 10.1093/pnasnexus/pgad276] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/19/2023] [Revised: 06/23/2023] [Accepted: 08/14/2023] [Indexed: 09/12/2023]
Abstract
The somatosensory-motor network (SMN) not only plays an important role in primary somatosensory and motor processing but is also central to many disorders. However, the SMN heterogeneity related to higher-order systems still remains unclear. Here, we investigated SMN heterogeneity from multiple perspectives. To characterize the SMN substructures in more detail, we used ultra-high-field functional MRI to delineate a finer-grained cortical parcellation containing 430 parcels that is more homogenous than the state-of-the-art parcellation. We personalized the new parcellation to account for individual differences and identified multiscale individual-specific brain structures. We found that the SMN subnetworks showed distinct resting-state functional connectivity (RSFC) patterns. The Hand subnetwork was central within the SMN and exhibited stronger RSFC with the attention systems than the other subnetworks, whereas the Tongue subnetwork exhibited stronger RSFC with the default systems. This two-fold differentiation was observed in the temporal ordering patterns within the SMN. Furthermore, we characterized how the distinct attention and default streams were carried forward into the functions of the SMN using dynamic causal modeling and identified two behavioral domains associated with this SMN fractionation using meta-analytic tools. Overall, our findings provided important insights into the heterogeneous SMN organization at the system level and suggested that the Hand subnetwork may be preferentially involved in exogenous processes, whereas the Tongue subnetwork may be more important in endogenous processes.
Collapse
Affiliation(s)
- Ziteng Han
- School of Medical Technology, Beijing Institute of Technology, No. 5 South Zhongguancun Street, Haidian District, Beijing 100081, China
| | - Tiantian Liu
- School of Medical Technology, Beijing Institute of Technology, No. 5 South Zhongguancun Street, Haidian District, Beijing 100081, China
| | - Zhongyan Shi
- School of Medical Technology, Beijing Institute of Technology, No. 5 South Zhongguancun Street, Haidian District, Beijing 100081, China
| | - Jian Zhang
- School of Mechatronical Engineering, Beijing Institute of Technology, No. 5 South Zhongguancun Street, Haidian District, Beijing 100081, China
| | - Dingjie Suo
- School of Medical Technology, Beijing Institute of Technology, No. 5 South Zhongguancun Street, Haidian District, Beijing 100081, China
| | - Li Wang
- School of Medical Technology, Beijing Institute of Technology, No. 5 South Zhongguancun Street, Haidian District, Beijing 100081, China
| | - Duanduan Chen
- School of Medical Technology, Beijing Institute of Technology, No. 5 South Zhongguancun Street, Haidian District, Beijing 100081, China
| | - Jinglong Wu
- School of Medical Technology, Beijing Institute of Technology, No. 5 South Zhongguancun Street, Haidian District, Beijing 100081, China
| | - Tianyi Yan
- School of Medical Technology, Beijing Institute of Technology, No. 5 South Zhongguancun Street, Haidian District, Beijing 100081, China
| |
Collapse
|
38
|
Bailes SM, Gomez DEP, Setzer B, Lewis LD. Resting-state fMRI signals contain spectral signatures of local hemodynamic response timing. eLife 2023; 12:e86453. [PMID: 37565644 PMCID: PMC10506795 DOI: 10.7554/elife.86453] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2023] [Accepted: 08/10/2023] [Indexed: 08/12/2023] Open
Abstract
Functional magnetic resonance imaging (fMRI) has proven to be a powerful tool for noninvasively measuring human brain activity; yet, thus far, fMRI has been relatively limited in its temporal resolution. A key challenge is understanding the relationship between neural activity and the blood-oxygenation-level-dependent (BOLD) signal obtained from fMRI, generally modeled by the hemodynamic response function (HRF). The timing of the HRF varies across the brain and individuals, confounding our ability to make inferences about the timing of the underlying neural processes. Here, we show that resting-state fMRI signals contain information about HRF temporal dynamics that can be leveraged to understand and characterize variations in HRF timing across both cortical and subcortical regions. We found that the frequency spectrum of resting-state fMRI signals significantly differs between voxels with fast versus slow HRFs in human visual cortex. These spectral differences extended to subcortex as well, revealing significantly faster hemodynamic timing in the lateral geniculate nucleus of the thalamus. Ultimately, our results demonstrate that the temporal properties of the HRF impact the spectral content of resting-state fMRI signals and enable voxel-wise characterization of relative hemodynamic response timing. Furthermore, our results show that caution should be used in studies of resting-state fMRI spectral properties, because differences in fMRI frequency content can arise from purely vascular origins. This finding provides new insight into the temporal properties of fMRI signals across voxels, which is crucial for accurate fMRI analyses, and enhances the ability of fast fMRI to identify and track fast neural dynamics.
Collapse
Affiliation(s)
- Sydney M Bailes
- Department of Biomedical Engineering, Boston UniversityBostonUnited States
| | - Daniel EP Gomez
- Department of Biomedical Engineering, Boston UniversityBostonUnited States
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General HospitalCharlestownUnited States
- Department of Radiology, Harvard Medical SchoolBostonUnited States
| | - Beverly Setzer
- Department of Biomedical Engineering, Boston UniversityBostonUnited States
- Graduate Program for Neuroscience, Boston UniversityBostonUnited States
| | - Laura D Lewis
- Department of Biomedical Engineering, Boston UniversityBostonUnited States
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General HospitalCharlestownUnited States
- Institute for Medical Engineering and Science, Massachusetts Institute of TechnologyCambridgeUnited States
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of TechnologyCambridgeUnited States
| |
Collapse
|
39
|
Xu N, Smith DM, Jeno G, Seeburger DT, Schumacher EH, Keilholz SD. The interaction between random and systematic visual stimulation and infraslow quasiperiodic spatiotemporal patterns of whole brain activity. IMAGING NEUROSCIENCE (CAMBRIDGE, MASS.) 2023; 1:1-19. [PMID: 37701786 PMCID: PMC10494556 DOI: 10.1162/imag_a_00002] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/14/2023] [Accepted: 05/14/2023] [Indexed: 09/14/2023]
Abstract
One prominent feature of the infraslow BOLD signal during rest or task is quasi-periodic spatiotemporal pattern (QPP) of signal changes that involves an alternation of activity in key functional networks and propagation of activity across brain areas, and that is known to tie to the infraslow neural activity involved in attention and arousal fluctuations. This ongoing whole-brain pattern of activity might potentially modify the response to incoming stimuli or be modified itself by the induced neural activity. To investigate this, we presented checkerboard sequences flashing at 6Hz to subjects. This is a salient visual stimulus that is known to produce a strong response in visual processing regions. Two different visual stimulation sequences were employed, a systematic stimulation sequence in which the visual stimulus appeared every 20.3 secs and a random stimulation sequence in which the visual stimulus occurred randomly every 14~62.3 secs. Three central observations emerged. First, the two different stimulation conditions affect the QPP waveform in different aspects, i.e., systematic stimulation has greater effects on its phase and random stimulation has greater effects on its magnitude. Second, the QPP was more frequent in the systematic condition with significantly shorter intervals between consecutive QPPs compared to the random condition. Third, the BOLD signal response to the visual stimulus across both conditions was swamped by the QPP at the stimulus onset. These results provide novel insights into the relationship between intrinsic patterns and stimulated brain activity.
Collapse
Affiliation(s)
- Nan Xu
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, United States
| | - Derek M. Smith
- School of Psychology, Georgia Institute of Technology, Atlanta, GA, United States
- Department of Neurology, Division of Cognitive Neurology/Neuropsychology, The Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - George Jeno
- School of Computer Science, Georgia Institute of Technology, Atlanta, GA, United States
| | - Dolly T. Seeburger
- School of Psychology, Georgia Institute of Technology, Atlanta, GA, United States
| | - Eric H. Schumacher
- School of Psychology, Georgia Institute of Technology, Atlanta, GA, United States
| | - Shella D. Keilholz
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, United States
| |
Collapse
|
40
|
Rashid B, Glasser MF, Nichols T, Van Essen D, Juttukonda MR, Schwab NA, Greve DN, Yacoub E, Lovely A, Terpstra M, Harms MP, Bookheimer SY, Ances BM, Salat DH, Arnold SE. Cardiovascular and metabolic health is associated with functional brain connectivity in middle-aged and older adults: Results from the Human Connectome Project-Aging study. Neuroimage 2023; 276:120192. [PMID: 37247763 PMCID: PMC10330931 DOI: 10.1016/j.neuroimage.2023.120192] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Revised: 05/15/2023] [Accepted: 05/24/2023] [Indexed: 05/31/2023] Open
Abstract
Several cardiovascular and metabolic indicators, such as cholesterol and blood pressure have been associated with altered neural and cognitive health as well as increased risk of dementia and Alzheimer's disease in later life. In this cross-sectional study, we examined how an aggregate index of cardiovascular and metabolic risk factor measures was associated with correlation-based estimates of resting-state functional connectivity (FC) across a broad adult age-span (36-90+ years) from 930 volunteers in the Human Connectome Project Aging (HCP-A). Increased (i.e., worse) aggregate cardiometabolic scores were associated with reduced FC globally, with especially strong effects in insular, medial frontal, medial parietal, and superior temporal regions. Additionally, at the network-level, FC between core brain networks, such as default-mode and cingulo-opercular, as well as dorsal attention networks, showed strong effects of cardiometabolic risk. These findings highlight the lifespan impact of cardiovascular and metabolic health on whole-brain functional integrity and how these conditions may disrupt higher-order network integrity.
Collapse
Affiliation(s)
- Barnaly Rashid
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, 149 13th St., Charlestown, MA 02129, United States; Harvard Medical School, Boston, MA, United States.
| | - Matthew F Glasser
- Washington University School of Medicine, St. Louis, MO, United States
| | | | - David Van Essen
- Washington University School of Medicine, St. Louis, MO, United States
| | - Meher R Juttukonda
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, 149 13th St., Charlestown, MA 02129, United States; Harvard Medical School, Boston, MA, United States
| | - Nadine A Schwab
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, 149 13th St., Charlestown, MA 02129, United States; Harvard Medical School, Boston, MA, United States
| | - Douglas N Greve
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, 149 13th St., Charlestown, MA 02129, United States; Harvard Medical School, Boston, MA, United States
| | - Essa Yacoub
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, United States
| | - Allison Lovely
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, 149 13th St., Charlestown, MA 02129, United States; Harvard Medical School, Boston, MA, United States
| | | | - Michael P Harms
- Washington University in St. Louis, St. Louis, MO, United States
| | | | - Beau M Ances
- Washington University School of Medicine, St. Louis, MO, United States; Washington University in St. Louis, St. Louis, MO, United States
| | - David H Salat
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, 149 13th St., Charlestown, MA 02129, United States; Harvard Medical School, Boston, MA, United States.
| | - Steven E Arnold
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, 149 13th St., Charlestown, MA 02129, United States; Harvard Medical School, Boston, MA, United States.
| |
Collapse
|
41
|
Huang Z. Temporospatial Nestedness in Consciousness: An Updated Perspective on the Temporospatial Theory of Consciousness. ENTROPY (BASEL, SWITZERLAND) 2023; 25:1074. [PMID: 37510023 PMCID: PMC10378228 DOI: 10.3390/e25071074] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/24/2023] [Revised: 06/20/2023] [Accepted: 06/27/2023] [Indexed: 07/30/2023]
Abstract
Time and space are fundamental elements that permeate the fabric of nature, and their significance in relation to neural activity and consciousness remains a compelling yet unexplored area of research. The Temporospatial Theory of Consciousness (TTC) provides a framework that links time, space, neural activity, and consciousness, shedding light on the intricate relationships among these dimensions. In this review, I revisit the fundamental concepts and mechanisms proposed by the TTC, with a particular focus on the central concept of temporospatial nestedness. I propose an extension of temporospatial nestedness by incorporating the nested relationship between the temporal circuit and functional geometry of the brain. To further unravel the complexities of temporospatial nestedness, future research directions should emphasize the characterization of functional geometry and the temporal circuit across multiple spatial and temporal scales. Investigating the links between these scales will yield a more comprehensive understanding of how spatial organization and temporal dynamics contribute to conscious states. This integrative approach holds the potential to uncover novel insights into the neural basis of consciousness and reshape our understanding of the world-brain dynamic.
Collapse
Affiliation(s)
- Zirui Huang
- Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, MI 48109, USA;
- Center for Consciousness Science, University of Michigan Medical School, Ann Arbor, MI 48109, USA
| |
Collapse
|
42
|
Nanda A, Rubinov M. Unbiased and efficient sampling of timeseries reveals redundancy of brain network and gradient structure. Neuroimage 2023; 274:120110. [PMID: 37150102 DOI: 10.1016/j.neuroimage.2023.120110] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2023] [Revised: 04/05/2023] [Accepted: 04/12/2023] [Indexed: 05/09/2023] Open
Abstract
Many studies in human neuroscience seek to understand the structure of brain networks and gradients. Few studies, however, have tested the redundancy between these outwardly distinct features. Here, we developed methods to directly enable such tests. We built on insights from linear algebra to develop methods for unbiased and efficient sampling of timeseries with network or gradient constraints. We used these methods to show considerable redundancy between popular definitions of network and gradient structure in functional MRI data. On the one hand, we found that network constraints largely accounted for the structure of three major gradients. On the other hand, we found that gradient constraints largely accounted for the structure of seven major networks. Our results imply that some networks and gradients may denote discrete and continuous representations of the same aspects of functional MRI data. We suggest that integrated explanations can reduce redundancy by avoiding the attribution of independent existence or function to these features.
Collapse
Affiliation(s)
- Aditya Nanda
- Department of Biomedical Engineering, Vanderbilt University, USA.
| | - Mikail Rubinov
- Department of Biomedical Engineering, Vanderbilt University, USA; Department of Computer Science, Vanderbilt University, USA; Janelia Research Campus, Howard Hughes Medical Institute, USA.
| |
Collapse
|
43
|
Greene AS, Horien C, Barson D, Scheinost D, Constable RT. Why is everyone talking about brain state? Trends Neurosci 2023; 46:508-524. [PMID: 37164869 PMCID: PMC10330476 DOI: 10.1016/j.tins.2023.04.001] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Revised: 03/17/2023] [Accepted: 04/07/2023] [Indexed: 05/12/2023]
Abstract
The rapid and coordinated propagation of neural activity across the brain provides the foundation for complex behavior and cognition. Technical advances across neuroscience subfields have advanced understanding of these dynamics, but points of convergence are often obscured by semantic differences, creating silos of subfield-specific findings. In this review we describe how a parsimonious conceptualization of brain state as the fundamental building block of whole-brain activity offers a common framework to relate findings across scales and species. We present examples of the diverse techniques commonly used to study brain states associated with physiology and higher-order cognitive processes, and discuss how integration across them will enable a more comprehensive and mechanistic characterization of the neural dynamics that are crucial to survival but are disrupted in disease.
Collapse
Affiliation(s)
- Abigail S Greene
- Interdepartmental Neuroscience Program, Yale School of Medicine, New Haven, CT 06520, USA; MD/PhD program, Yale School of Medicine, New Haven, CT 06520, USA.
| | - Corey Horien
- Interdepartmental Neuroscience Program, Yale School of Medicine, New Haven, CT 06520, USA; MD/PhD program, Yale School of Medicine, New Haven, CT 06520, USA.
| | - Daniel Barson
- Interdepartmental Neuroscience Program, Yale School of Medicine, New Haven, CT 06520, USA; MD/PhD program, Yale School of Medicine, New Haven, CT 06520, USA; Department of Neuroscience, Yale School of Medicine, New Haven, CT 06520, USA.
| | - Dustin Scheinost
- Interdepartmental Neuroscience Program, Yale School of Medicine, New Haven, CT 06520, USA; Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT 06520, USA; Department of Biomedical Engineering, Yale School of Engineering and Applied Science, New Haven, CT 06520, USA; Department of Statistics and Data Science, Yale University, New Haven, CT 06511, USA; Child Study Center, Yale School of Medicine, New Haven, CT 06520, USA
| | - R Todd Constable
- Interdepartmental Neuroscience Program, Yale School of Medicine, New Haven, CT 06520, USA; Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT 06520, USA; Department of Biomedical Engineering, Yale School of Engineering and Applied Science, New Haven, CT 06520, USA; Department of Neurosurgery, Yale School of Medicine, New Haven, CT 06520, USA
| |
Collapse
|
44
|
Yu Y, Gratton C, Smith DM. From correlation to communication: Disentangling hidden factors from functional connectivity changes. Netw Neurosci 2023; 7:411-430. [PMID: 37397894 PMCID: PMC10312287 DOI: 10.1162/netn_a_00290] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Accepted: 11/02/2022] [Indexed: 01/11/2024] Open
Abstract
While correlations in the BOLD fMRI signal are widely used to capture functional connectivity (FC) and its changes across contexts, its interpretation is often ambiguous. The entanglement of multiple factors including local coupling of two neighbors and nonlocal inputs from the rest of the network (affecting one or both regions) limits the scope of the conclusions that can be drawn from correlation measures alone. Here we present a method of estimating the contribution of nonlocal network input to FC changes across different contexts. To disentangle the effect of task-induced coupling change from the network input change, we propose a new metric, "communication change," utilizing BOLD signal correlation and variance. With a combination of simulation and empirical analysis, we demonstrate that (1) input from the rest of the network accounts for a moderate but significant amount of task-induced FC change and (2) the proposed "communication change" is a promising candidate for tracking the local coupling in task context-induced change. Additionally, when compared to FC change across three different tasks, communication change can better discriminate specific task types. Taken together, this novel index of local coupling may have many applications in improving our understanding of local and widespread interactions across large-scale functional networks.
Collapse
Affiliation(s)
- Yuhua Yu
- Department of Psychology, Northwestern University, Evanston, IL, USA
| | - Caterina Gratton
- Department of Psychology, Northwestern University, Evanston, IL, USA
- Department of Neurology, Northwestern University, Evanston, IL, USA
- Department of Psychology, Florida State University, Tallahassee, FL, USA
| | - Derek M. Smith
- Department of Psychology, Northwestern University, Evanston, IL, USA
- Department of Neurology, Division of Cognitive Neurology/Neuropsychology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| |
Collapse
|
45
|
Kim J, Andrews-Hanna JR, Eisenbarth H, Lux BK, Kim HJ, Lee E, Lindquist MA, Losin EAR, Wager TD, Woo CW. A dorsomedial prefrontal cortex-based dynamic functional connectivity model of rumination. Nat Commun 2023; 14:3540. [PMID: 37321986 PMCID: PMC10272121 DOI: 10.1038/s41467-023-39142-9] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Accepted: 06/01/2023] [Indexed: 06/17/2023] Open
Abstract
Rumination is a cognitive style characterized by repetitive thoughts about one's negative internal states and is a common symptom of depression. Previous studies have linked trait rumination to alterations in the default mode network, but predictive brain markers of rumination are lacking. Here, we adopt a predictive modeling approach to develop a neuroimaging marker of rumination based on the variance of dynamic resting-state functional connectivity and test it across 5 diverse subclinical and clinical samples (total n = 288). A whole-brain marker based on dynamic connectivity with the dorsomedial prefrontal cortex (dmPFC) emerges as generalizable across the subclinical datasets. A refined marker consisting of the most important features from a virtual lesion analysis further predicts depression scores of adults with major depressive disorder (n = 35). This study highlights the role of the dmPFC in trait rumination and provides a dynamic functional connectivity marker for rumination.
Collapse
Affiliation(s)
- Jungwoo Kim
- Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, South Korea
- Department of Biomedical Engineering, Sungkyunkwan University, Suwon, South Korea
- Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University, Suwon, South Korea
| | - Jessica R Andrews-Hanna
- Department of Psychology, University of Arizona, Tucson, AZ, USA
- Cognitive Science, University of Arizona, Tucson, AZ, USA
| | - Hedwig Eisenbarth
- School of Psychology, Victoria University of Wellington, Wellington, New Zealand
| | - Byeol Kim Lux
- Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, South Korea
- Department of Biomedical Engineering, Sungkyunkwan University, Suwon, South Korea
- Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH, USA
| | - Hong Ji Kim
- Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, South Korea
- Department of Biomedical Engineering, Sungkyunkwan University, Suwon, South Korea
- Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University, Suwon, South Korea
| | - Eunjin Lee
- Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, South Korea
- Department of Biomedical Engineering, Sungkyunkwan University, Suwon, South Korea
- Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University, Suwon, South Korea
| | - Martin A Lindquist
- Department of Biostatistics, Johns Hopkins University, Baltimore, MD, USA
| | - Elizabeth A Reynolds Losin
- Department of Psychology, University of Miami, Miami, FL, USA
- Department of Biobehavioral Health, Penn State University, State College, PA, USA
| | - Tor D Wager
- Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH, USA.
| | - Choong-Wan Woo
- Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, South Korea.
- Department of Biomedical Engineering, Sungkyunkwan University, Suwon, South Korea.
- Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University, Suwon, South Korea.
- Life-inspired Neural Network for Prediction and Optimization Research Group, Suwon, South Korea.
| |
Collapse
|
46
|
Xu Y, Long X, Feng J, Gong P. Interacting spiral wave patterns underlie complex brain dynamics and are related to cognitive processing. Nat Hum Behav 2023:10.1038/s41562-023-01626-5. [PMID: 37322235 DOI: 10.1038/s41562-023-01626-5] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Accepted: 05/12/2023] [Indexed: 06/17/2023]
Abstract
The large-scale activity of the human brain exhibits rich and complex patterns, but the spatiotemporal dynamics of these patterns and their functional roles in cognition remain unclear. Here by characterizing moment-by-moment fluctuations of human cortical functional magnetic resonance imaging signals, we show that spiral-like, rotational wave patterns (brain spirals) are widespread during both resting and cognitive task states. These brain spirals propagate across the cortex while rotating around their phase singularity centres, giving rise to spatiotemporal activity dynamics with non-stationary features. The properties of these brain spirals, such as their rotational directions and locations, are task relevant and can be used to classify different cognitive tasks. We also demonstrate that multiple, interacting brain spirals are involved in coordinating the correlated activations and de-activations of distributed functional regions; this mechanism enables flexible reconfiguration of task-driven activity flow between bottom-up and top-down directions during cognitive processing. Our findings suggest that brain spirals organize complex spatiotemporal dynamics of the human brain and have functional correlates to cognitive processing.
Collapse
Affiliation(s)
- Yiben Xu
- School of Physics, University of Sydney, Sydney, New South Wales, Australia
- ARC Centre of Excellence for Integrative Brain Function, University of Sydney, Sydney, New South Wales, Australia
| | - Xian Long
- School of Physics, University of Sydney, Sydney, New South Wales, Australia
- ARC Centre of Excellence for Integrative Brain Function, University of Sydney, Sydney, New South Wales, Australia
| | - Jianfeng Feng
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Pulin Gong
- School of Physics, University of Sydney, Sydney, New South Wales, Australia.
- ARC Centre of Excellence for Integrative Brain Function, University of Sydney, Sydney, New South Wales, Australia.
| |
Collapse
|
47
|
Li A, Liu H, Lei X, He Y, Wu Q, Yan Y, Zhou X, Tian X, Peng Y, Huang S, Li K, Wang M, Sun Y, Yan H, Zhang C, He S, Han R, Wang X, Liu B. Hierarchical fluctuation shapes a dynamic flow linked to states of consciousness. Nat Commun 2023; 14:3238. [PMID: 37277338 DOI: 10.1038/s41467-023-38972-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Accepted: 05/23/2023] [Indexed: 06/07/2023] Open
Abstract
Consciousness arises from the spatiotemporal neural dynamics, however, its relationship with neural flexibility and regional specialization remains elusive. We identified a consciousness-related signature marked by shifting spontaneous fluctuations along a unimodal-transmodal cortical axis. This simple signature is sensitive to altered states of consciousness in single individuals, exhibiting abnormal elevation under psychedelics and in psychosis. The hierarchical dynamic reflects brain state changes in global integration and connectome diversity under task-free conditions. Quasi-periodic pattern detection revealed that hierarchical heterogeneity as spatiotemporally propagating waves linking to arousal. A similar pattern can be observed in macaque electrocorticography. Furthermore, the spatial distribution of principal cortical gradient preferentially recapitulated the genetic transcription levels of the histaminergic system and that of the functional connectome mapping of the tuberomammillary nucleus, which promotes wakefulness. Combining behavioral, neuroimaging, electrophysiological, and transcriptomic evidence, we propose that global consciousness is supported by efficient hierarchical processing constrained along a low-dimensional macroscale gradient.
Collapse
Affiliation(s)
- Ang Li
- State Key Lab of Brain and Cognitive Science, Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Haiyang Liu
- Department of Anesthesiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100101, China
- Department of Anesthesiology, Qinghai Provincial Traffic Hospital, Xining, 810001, China
| | - Xu Lei
- Sleep and Neuroimaging Center, Faculty of Psychology, Southwest University, Chongqing, 400715, China
- Key Laboratory of Cognition and Personality (Southwest University), Ministry of Education, Chongqing, 400715, China
| | - Yini He
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
| | - Qian Wu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China
| | - Yan Yan
- Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, 518055, China
| | - Xin Zhou
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
| | - Xiaohan Tian
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
| | - Yingjie Peng
- State Key Lab of Brain and Cognitive Science, Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China
| | - Shangzheng Huang
- State Key Lab of Brain and Cognitive Science, Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China
| | - Kaixin Li
- State Key Lab of Brain and Cognitive Science, Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China
| | - Meng Wang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
| | - Yuqing Sun
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
| | - Hao Yan
- Peking University Sixth Hospital/Institute of Mental Health, Beijing, 100191, China
- NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, China
| | - Cheng Zhang
- The Department of Respiratory and Critical Care Medicine, Peking University First Hospital, Beijing, 100034, China
| | - Sheng He
- State Key Lab of Brain and Cognitive Science, Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China
| | - Ruquan Han
- Department of Anesthesiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100101, China.
| | - Xiaoqun Wang
- State Key Lab of Brain and Cognitive Science, Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China.
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China.
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China.
- New Cornerstone Science Laboratory, Beijing Normal University, Beijing, 100875, China.
| | - Bing Liu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China.
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China.
- Chinese Institute for Brain Research, Beijing, 102206, China.
| |
Collapse
|
48
|
Pang JC, Aquino KM, Oldehinkel M, Robinson PA, Fulcher BD, Breakspear M, Fornito A. Geometric constraints on human brain function. Nature 2023; 618:566-574. [PMID: 37258669 PMCID: PMC10266981 DOI: 10.1038/s41586-023-06098-1] [Citation(s) in RCA: 68] [Impact Index Per Article: 68.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Accepted: 04/18/2023] [Indexed: 06/02/2023]
Abstract
The anatomy of the brain necessarily constrains its function, but precisely how remains unclear. The classical and dominant paradigm in neuroscience is that neuronal dynamics are driven by interactions between discrete, functionally specialized cell populations connected by a complex array of axonal fibres1-3. However, predictions from neural field theory, an established mathematical framework for modelling large-scale brain activity4-6, suggest that the geometry of the brain may represent a more fundamental constraint on dynamics than complex interregional connectivity7,8. Here, we confirm these theoretical predictions by analysing human magnetic resonance imaging data acquired under spontaneous and diverse task-evoked conditions. Specifically, we show that cortical and subcortical activity can be parsimoniously understood as resulting from excitations of fundamental, resonant modes of the brain's geometry (that is, its shape) rather than from modes of complex interregional connectivity, as classically assumed. We then use these geometric modes to show that task-evoked activations across over 10,000 brain maps are not confined to focal areas, as widely believed, but instead excite brain-wide modes with wavelengths spanning over 60 mm. Finally, we confirm predictions that the close link between geometry and function is explained by a dominant role for wave-like activity, showing that wave dynamics can reproduce numerous canonical spatiotemporal properties of spontaneous and evoked recordings. Our findings challenge prevailing views and identify a previously underappreciated role of geometry in shaping function, as predicted by a unifying and physically principled model of brain-wide dynamics.
Collapse
Affiliation(s)
- James C Pang
- The Turner Institute for Brain and Mental Health, School of Psychological Sciences and Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia.
| | - Kevin M Aquino
- School of Physics, University of Sydney, Camperdown, New South Wales, Australia
- BrainKey Inc., San Francisco, CA, USA
| | - Marianne Oldehinkel
- Donders Institute for Brain, Cognition, and Behaviour, Radboud University Medical Centre, Nijmegen, the Netherlands
| | - Peter A Robinson
- School of Physics, University of Sydney, Camperdown, New South Wales, Australia
| | - Ben D Fulcher
- School of Physics, University of Sydney, Camperdown, New South Wales, Australia
| | - Michael Breakspear
- School of Psychological Sciences, College of Engineering, Science and the Environment, University of Newcastle, Callaghan, New South Wales, Australia
- School of Medicine and Public Health, College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, New South Wales, Australia
| | - Alex Fornito
- The Turner Institute for Brain and Mental Health, School of Psychological Sciences and Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia
| |
Collapse
|
49
|
Xie K, Royer J, Larivière S, Rodriguez-Cruces R, Frässle S, Cabalo DG, Ngo A, DeKraker J, Auer H, Tavakol S, Weng Y, Abdallah C, Horwood L, Frauscher B, Caciagli L, Bernasconi A, Bernasconi N, Zhang Z, Concha L, Bernhardt BC. Atypical connectome topography and signal flow in temporal lobe epilepsy. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.23.541934. [PMID: 37292996 PMCID: PMC10245853 DOI: 10.1101/2023.05.23.541934] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Temporal lobe epilepsy (TLE) is one of the most common pharmaco-resistant epilepsies in adults. While hippocampal pathology is the hallmark of this condition, emerging evidence indicates that brain alterations extend beyond the mesiotemporal epicenter and affect macroscale brain function and cognition. We studied macroscale functional reorganization in TLE, explored structural substrates, and examined cognitive associations. We investigated a multisite cohort of 95 patients with pharmaco-resistant TLE and 95 healthy controls using state-of-the-art multimodal 3T magnetic resonance imaging (MRI). We quantified macroscale functional topographic organization using connectome dimensionality reduction techniques and estimated directional functional flow using generative models of effective connectivity. We observed atypical functional topographies in patients with TLE relative to controls, manifesting as reduced functional differentiation between sensory/motor networks and transmodal systems such as the default mode network, with peak alterations in bilateral temporal and ventromedial prefrontal cortices. TLE-related topographic changes were consistent in all three included sites and reflected reductions in hierarchical flow patterns between cortical systems. Integration of parallel multimodal MRI data indicated that these findings were independent of TLE-related cortical grey matter atrophy, but mediated by microstructural alterations in the superficial white matter immediately beneath the cortex. The magnitude of functional perturbations was robustly associated with behavioral markers of memory function. Overall, this work provides converging evidence for macroscale functional imbalances, contributing microstructural alterations, and their associations with cognitive dysfunction in TLE.
Collapse
Affiliation(s)
- Ke Xie
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Jessica Royer
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
- Analytical Neurophysiology Laboratory, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Sara Larivière
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Raul Rodriguez-Cruces
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Stefan Frässle
- Translational Neuromodeling Unit (TNU), Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - Donna Gift Cabalo
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Alexander Ngo
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Jordan DeKraker
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Hans Auer
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Shahin Tavakol
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Yifei Weng
- Department of Medical Imaging, Jinling Hospital, Nanjing University School of Medicine, Nanjing, China
| | - Chifaou Abdallah
- Analytical Neurophysiology Laboratory, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Linda Horwood
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
- Analytical Neurophysiology Laboratory, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Birgit Frauscher
- Analytical Neurophysiology Laboratory, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Lorenzo Caciagli
- Department of Biomedical Engineering, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA
| | - Andrea Bernasconi
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Neda Bernasconi
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Zhiqiang Zhang
- Department of Medical Imaging, Jinling Hospital, Nanjing University School of Medicine, Nanjing, China
| | - Luis Concha
- Brain Connectivity Laboratory, Institute of Neurobiology, Universidad Nacional Autónoma de Mexico (UNAM), Mexico
| | - Boris C Bernhardt
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| |
Collapse
|
50
|
Xu N, Smith DM, Jeno G, Seeburger DT, Schumacher EH, Keilholz SD. The interaction between random and systematic visual stimulation and infraslow quasiperiodic spatiotemporal patterns of whole brain activity. Neuroimage 2023:120165. [PMID: 37172663 DOI: 10.1016/j.neuroimage.2023.120165] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2023] [Revised: 04/25/2023] [Accepted: 05/09/2023] [Indexed: 05/15/2023] Open
Abstract
One prominent feature of the infraslow BOLD signal during rest or task is quasi-periodic spatiotemporal pattern (QPP) of signal changes that involves an alternation of activity in key functional networks and propagation of activity across brain areas, and that is known to tie to the infraslow neural activity involved in attention and arousal fluctuations. This ongoing whole-brain pattern of activity might potentially modify the response to incoming stimuli or be modified itself by the induced neural activity. To investigate this, we presented checkerboard sequences flashing at 6Hz to subjects. This is a salient visual stimulus that is known to produce a strong response in visual processing regions. Two different visual stimulation sequences were employed, a systematic stimulation sequence in which the visual stimulus appeared every 20.3 secs and a random stimulation sequence in which the visual stimulus occurred randomly every 14∼62.3 secs. Three central observations emerged. First, the two different stimulation conditions affect the QPP waveform in different aspects, i.e., systematic stimulation has greater effects on its phase and random stimulation has greater effects on its magnitude. Second, the QPP was more frequent in the systematic condition with significantly shorter intervals between consecutive QPPs compared to the random condition. Third, the BOLD signal response to the visual stimulus across both conditions was swamped by the QPP at the stimulus onset. These results provide novel insights into the relationship between intrinsic patterns and stimulated brain activity.
Collapse
Affiliation(s)
- Nan Xu
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, United States
| | - Derek M Smith
- School of Psychology, Georgia Institute of Technology, Atlanta, GA, United States; Department of Neurology, Division of Cognitive Neurology/Neuropsychology, The Johns Hopkins University School of Medicine, Baltimore, Maryland, United States
| | - George Jeno
- School of Computer Science, Georgia Institute of Technology, Atlanta, GA, United States
| | - Dolly T Seeburger
- School of Psychology, Georgia Institute of Technology, Atlanta, GA, United States
| | - Eric H Schumacher
- School of Psychology, Georgia Institute of Technology, Atlanta, GA, United States
| | - Shella D Keilholz
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, United States
| |
Collapse
|