1
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Wang Y, Zeng W, Ni C, Kong X, Mu X, Conlin CC, Qi H, Zhang JL. Exercise-induced calf muscle hyperemia quantified with dynamic blood oxygen level-dependent (BOLD) imaging. Magn Reson Imaging 2024; 111:21-27. [PMID: 38582100 DOI: 10.1016/j.mri.2024.04.004] [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: 08/11/2023] [Revised: 04/03/2024] [Accepted: 04/03/2024] [Indexed: 04/08/2024]
Abstract
Muscle hyperemia in exercise is usually the combined result of increased cardiac output and local muscle vasodilation, with the latter reflecting muscle's capacity for increased blood perfusion to support exercise. In this study, we aim to quantify muscle's vasodilation capability with dynamic BOLD imaging. A deoxyhemoglobin-kinetics model is proposed to analyze dynamic BOLD signals acquired during exercise recovery, deriving a hyperemia index (HI) for a muscle group of interest. We demonstrated the method's validity with calf muscles of healthy subjects who performed plantar flexion for muscle stimulation. In a test with exercise load incrementally increasing from 0 to 16 lbs., gastrocnemius HI showed considerable variance among the 4 subjects, but with a consistent trend, i.e. low at light load (e.g. 0-6 lbs) and linearly increasing at heavy load. The high variability among different subjects was confirmed with the other 10 subjects who exercised with a same moderate load of 8 lbs., with coefficient of variance among subjects' medial gastrocnemius 87.8%, lateral gastrocnemius 111.8% and soleus 132.3%. These findings align with the fact that intensive exercise induces high muscle hyperemia, but a comparison among different subjects is hard to make, presumably due to the subjects' different rate of oxygen utilization. For the same 10 subjects who exercised with load of 8 lbs., we also performed dynamic contrast enhanced (DCE) MRI to measure muscle perfusion (F). With a moderate correlation of 0.654, HI and F displayed three distinctive responses of calf muscles: soleus of all the subjects were in the cluster of low F and low HI, and gastrocnemius of most subjects had high F and either low or high HI. This finding suggests that parameter F encapsulates blood flow through vessels of all sizes, but BOLD-derived HI focuses on capillary flow and therefore is a more specific indicator of muscle vasodilation. In conclusion, the proposed hyperemia index has the potential of quantitatively assessing muscle vasodilation induced with exercise.
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Affiliation(s)
- Yujie Wang
- School of Biomedical Engineering, ShanghaiTech University, 393 Middle Huaxia Road, Pudong, Shanghai 201210, China; School of Life Science and Technology, ShanghaiTech University, 393 Middle Huaxia Road, Pudong, Shanghai 201210, China
| | - Wanning Zeng
- School of Biomedical Engineering, ShanghaiTech University, 393 Middle Huaxia Road, Pudong, Shanghai 201210, China
| | - Chang Ni
- School of Biomedical Engineering, ShanghaiTech University, 393 Middle Huaxia Road, Pudong, Shanghai 201210, China
| | - Xiangwei Kong
- School of Biomedical Engineering, ShanghaiTech University, 393 Middle Huaxia Road, Pudong, Shanghai 201210, China; School of Life Science and Technology, ShanghaiTech University, 393 Middle Huaxia Road, Pudong, Shanghai 201210, China
| | - Xin Mu
- School of Biomedical Engineering, ShanghaiTech University, 393 Middle Huaxia Road, Pudong, Shanghai 201210, China
| | - Christopher C Conlin
- Department of Radiology, University of California San Diego, 9500 Gilman Dr. La Jolla, CA 92093, USA
| | - Haikun Qi
- School of Biomedical Engineering, ShanghaiTech University, 393 Middle Huaxia Road, Pudong, Shanghai 201210, China
| | - Jeff L Zhang
- School of Biomedical Engineering, ShanghaiTech University, 393 Middle Huaxia Road, Pudong, Shanghai 201210, China.
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2
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Pigorini A, Avanzini P, Barborica A, Bénar CG, David O, Farisco M, Keller CJ, Manfridi A, Mikulan E, Paulk AC, Roehri N, Subramanian A, Vulliémoz S, Zelmann R. Simultaneous invasive and non-invasive recordings in humans: A novel Rosetta stone for deciphering brain activity. J Neurosci Methods 2024; 408:110160. [PMID: 38734149 DOI: 10.1016/j.jneumeth.2024.110160] [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: 12/18/2023] [Revised: 04/10/2024] [Accepted: 05/01/2024] [Indexed: 05/13/2024]
Abstract
Simultaneous noninvasive and invasive electrophysiological recordings provide a unique opportunity to achieve a comprehensive understanding of human brain activity, much like a Rosetta stone for human neuroscience. In this review we focus on the increasingly-used powerful combination of intracranial electroencephalography (iEEG) with scalp electroencephalography (EEG) or magnetoencephalography (MEG). We first provide practical insight on how to achieve these technically challenging recordings. We then provide examples from clinical research on how simultaneous recordings are advancing our understanding of epilepsy. This is followed by the illustration of how human neuroscience and methodological advances could benefit from these simultaneous recordings. We conclude with a call for open data sharing and collaboration, while ensuring neuroethical approaches and argue that only with a true collaborative approach the promises of simultaneous recordings will be fulfilled.
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Affiliation(s)
- Andrea Pigorini
- Department of Biomedical, Surgical and Dental Sciences, Università degli Studi di Milano, Milan, Italy; UOC Maxillo-facial Surgery and dentistry, Fondazione IRCCS Cà Granda, Ospedale Maggiore Policlinico, Milan, Italy.
| | - Pietro Avanzini
- Institute of Neuroscience, Consiglio Nazionale delle Ricerche, Parma, Italy
| | | | - Christian-G Bénar
- Aix Marseille Univ, Inserm, U1106, INS, Institut de Neurosciences des Systèmes, Marseille, France
| | - Olivier David
- Aix Marseille Univ, Inserm, U1106, INS, Institut de Neurosciences des Systèmes, Marseille, France
| | - Michele Farisco
- Centre for Research Ethics and Bioethics, Department of Public Health and Caring Sciences, Uppsala University, P.O. Box 256, Uppsala, SE 751 05, Sweden; Science and Society Unit Biogem, Biology and Molecular Genetics Institute, Via Camporeale snc, Ariano Irpino, AV 83031, Italy
| | - Corey J Keller
- Department of Psychiatry & Behavioral Sciences, Stanford University Medical Center, Stanford, CA 94305, USA; Wu Tsai Neurosciences Institute, Stanford University Medical Center, Stanford, CA 94305, USA; Veterans Affairs Palo Alto Healthcare System, and the Sierra Pacific Mental Illness, Research, Education, and Clinical Center (MIRECC), Palo Alto, CA 94394, USA
| | - Alfredo Manfridi
- Department of Pathophysiology and Transplantation, Università degli Studi di Milano, Milan, Italy
| | - Ezequiel Mikulan
- Department of Health Sciences, Università degli Studi di Milano, Milan, Italy
| | - Angelique C Paulk
- Department of Neurology and Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Nicolas Roehri
- EEG and Epilepsy Unit, Dpt of Clinical Neurosciences, Geneva University Hospitals and University of Geneva, Switzerland
| | - Ajay Subramanian
- Department of Psychiatry & Behavioral Sciences, Stanford University Medical Center, Stanford, CA 94305, USA; Wu Tsai Neurosciences Institute, Stanford University Medical Center, Stanford, CA 94305, USA; Veterans Affairs Palo Alto Healthcare System, and the Sierra Pacific Mental Illness, Research, Education, and Clinical Center (MIRECC), Palo Alto, CA 94394, USA
| | - Serge Vulliémoz
- EEG and Epilepsy Unit, Dpt of Clinical Neurosciences, Geneva University Hospitals and University of Geneva, Switzerland
| | - Rina Zelmann
- Department of Neurology and Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
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3
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Bonanno M, Papa GA, Ruffoni P, Catalioto E, De Luca R, Maggio MG, Calabrò RS. The Effects of Osteopathic Manipulative Treatment on Brain Activity: A Scoping Review of MRI and EEG Studies. Healthcare (Basel) 2024; 12:1353. [PMID: 38998887 PMCID: PMC11241316 DOI: 10.3390/healthcare12131353] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2024] [Revised: 07/01/2024] [Accepted: 07/04/2024] [Indexed: 07/14/2024] Open
Abstract
Osteopathic manipulative treatment (OMT) is a hands-on therapy aiming to achieve the global homeostasis of the patient. OMT focuses on treating the somatic dysfunctions characterized by tissue modifications, body asymmetry, and range-of-motion restrictions. The benefits related to OMT are thought to be associated with the interconnectedness of the body's systems and the inherent capacity for self-healing. However, whether OMT can influence brain activity, and, consequently, neurophysiological responses is an open research question. Our research investigates the literature to identify the effects of OMT on brain activity. The main purpose of the research question is: can OMT influence brain activity and consequently neurophysiological responses? A scoping review was conducted, searching the following databases: PubMed, Google Scholar, and OSTEOMED.DR (Osteopathic Medical Digital Repository), Scopus, Web of Science (WoS), and Science Direct. The initial search returned 114 articles, and after removing duplicates, 69 were considered eligible to be included in the final sample. In the end, eight studies (six randomized controlled trials, one pilot study, and one cross-over study) were finally included and analyzed in this review. In conclusion, OMT seems to have a role in influencing functional changes in brain activity in healthy individuals and even more in patients with chronic musculoskeletal pain. However, further RCT studies are needed to confirm these findings. Registration protocol: CRD42024525390.
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Affiliation(s)
- Mirjam Bonanno
- IRCCS Centro Neurolesi Bonino-Pulejo, Cda Casazza, SS 113, 98124 Messina, Italy
| | | | - Paola Ruffoni
- International College of Osteopathic Medicine, 20092 Milan, Italy
| | | | - Rosaria De Luca
- IRCCS Centro Neurolesi Bonino-Pulejo, Cda Casazza, SS 113, 98124 Messina, Italy
| | - Maria Grazia Maggio
- IRCCS Centro Neurolesi Bonino-Pulejo, Cda Casazza, SS 113, 98124 Messina, Italy
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4
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Thanaraju A, Marzuki AA, Chan JK, Wong KY, Phon-Amnuaisuk P, Vafa S, Chew J, Chia YC, Jenkins M. Structural and functional brain correlates of socioeconomic status across the life span: A systematic review. Neurosci Biobehav Rev 2024; 162:105716. [PMID: 38729281 DOI: 10.1016/j.neubiorev.2024.105716] [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: 01/28/2024] [Revised: 04/08/2024] [Accepted: 05/06/2024] [Indexed: 05/12/2024]
Abstract
It is well-established that higher socioeconomic status (SES) is associated with improved brain health. However, the effects of SES across different life stages on brain structure and function is still equivocal. In this systematic review, we aimed to synthesise findings from life course neuroimaging studies that investigated the structural and functional brain correlates of SES across the life span. The results indicated that higher SES across different life stages were independently and cumulatively related to neural outcomes typically reflective of greater brain health (e.g., increased cortical thickness, grey matter volume, fractional anisotropy, and network segregation) in adult individuals. The results also demonstrated that the corticolimbic system was most commonly impacted by socioeconomic disadvantages across the life span. This review highlights the importance of taking into account SES across the life span when studying its effects on brain health. It also provides directions for future research including the need for longitudinal and multimodal research that can inform effective policy interventions tailored to specific life stages.
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Affiliation(s)
- Arjun Thanaraju
- Department of Biological Sciences, School of Medical and Life Sciences, Sunway University, Malaysia.
| | - Aleya A Marzuki
- Department for Psychiatry and Psychotherapy, Medical School and University Hospital, Eberhard Karls University of Tübingen, Germany
| | - Jee Kei Chan
- Department of Psychology, Jeffrey Cheah School of Medicine and Health Sciences, Monash University Malaysia, Malaysia
| | - Kean Yung Wong
- Sensory Neuroscience and Nutrition Lab, University of Otago, New Zealand
| | - Paveen Phon-Amnuaisuk
- Department of Psychology, Jeffrey Cheah School of Medicine and Health Sciences, Monash University Malaysia, Malaysia
| | - Samira Vafa
- Department of Psychology, School of Medical and Life Sciences, Sunway University, Malaysia
| | - Jactty Chew
- Department of Biological Sciences, School of Medical and Life Sciences, Sunway University, Malaysia
| | - Yook Chin Chia
- Department of Medical Sciences, School of Medical and Life Sciences, Sunway University, Malaysia
| | - Michael Jenkins
- Department of Psychology, School of Medical and Life Sciences, Sunway University, Malaysia
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5
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Yu P, Dong R, Wang X, Tang Y, Liu Y, Wang C, Zhao L. Neuroimaging of motor recovery after ischemic stroke - functional reorganization of motor network. Neuroimage Clin 2024; 43:103636. [PMID: 38950504 PMCID: PMC11267109 DOI: 10.1016/j.nicl.2024.103636] [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: 03/10/2024] [Revised: 06/01/2024] [Accepted: 06/27/2024] [Indexed: 07/03/2024]
Abstract
The long-term motor outcome of acute stroke patients may be correlated to the reorganization of brain motor network. Abundant neuroimaging studies contribute to understand the pathological changes and recovery of motor networks after stroke. In this review, we summarized how current neuroimaging studies have increased understanding of reorganization and plasticity in post stroke motor recovery. Firstly, we discussed the changes in the motor network over time during the motor-activation and resting states, as well as the overall functional integration trend of the motor network. These studies indicate that the motor network undergoes dynamic bilateral hemispheric functional reorganization, as well as a trend towards network randomization. In the second part, we summarized the current study progress in the application of neuroimaging technology to early predict the post-stroke motor outcome. In the third part, we discuss the neuroimaging techniques commonly used in the post-stroke recovery. These methods provide direct or indirect visualization patterns to understand the neural mechanisms of post-stroke motor recovery, opening up new avenues for studying spontaneous and treatment-induced recovery and plasticity after stroke.
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Affiliation(s)
- Pei Yu
- School of Acupuncture and Massage, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China
| | - Ruoyu Dong
- Dongzhimen Hospital Affiliated to Beijing University of Chinese Medicine, Beijing, China
| | - Xiao Wang
- School of Acupuncture and Massage, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China
| | - Yuqi Tang
- School of Acupuncture and Massage, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China
| | - Yaning Liu
- School of Acupuncture and Massage, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China
| | - Can Wang
- School of Acupuncture and Massage, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China
| | - Ling Zhao
- School of Acupuncture and Massage, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China.
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6
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Coleman C, Van Horn JD. Towards Comprehensive Connectivity Modeling. Neuroinformatics 2024:10.1007/s12021-024-09676-4. [PMID: 38926268 DOI: 10.1007/s12021-024-09676-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/28/2024]
Affiliation(s)
- Campbell Coleman
- Department of Psychology, University of Virginia, Charlottesville, VA, 22903, USA
| | - John Darrell Van Horn
- Department of Psychology, University of Virginia, Charlottesville, VA, 22903, USA.
- School of Data Science, University of Virginia, Charlottesville, VA, 22903, USA.
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7
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Halperin I, Vigotsky AD. An Integrated Perspective of Effort and Perception of Effort. Sports Med 2024:10.1007/s40279-024-02055-8. [PMID: 38909350 DOI: 10.1007/s40279-024-02055-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/22/2024] [Indexed: 06/24/2024]
Abstract
Effort and the perception of effort (PE) have been extensively studied across disciplines, resulting in multiple definitions. These inconsistencies block scientific progress by impeding effective communication between and within fields. Here, we present an integrated perspective of effort and PE that is applicable to both physical and cognitive activities. We define effort as the energy utilized to perform an action. This definition can be applied to biological entities performing various voluntary or involuntary activities, irrespective of whether the effort contributes to goal achievement. Then, we define PE as the instantaneous experience of utilizing energy to perform an action. This definition builds on that of effort without conflating it with other subjective experiences. We explore the nature of effort and PE as constructs and variables and highlight key considerations in their measurement. Our integrated perspective aims to facilitate a deeper understanding of these constructs, refine research methodologies, and promote interdisciplinary collaborations.
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Affiliation(s)
- Israel Halperin
- Department of Health Promotion, School of Public Health, Faculty of Medical & Health Sciences, Tel-Aviv University, Tel-Aviv, Israel.
- Sylvan Adams Sports Institute, Tel Aviv University, Tel-Aviv, Israel.
| | - Andrew D Vigotsky
- Departments of Biomedical Engineering and Statistics, Northwestern University, Evanston, IL, USA
- Department of Neuroscience, Northwestern University, Chicago, IL, USA
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8
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Chen Z, Gezginer I, Zhou Q, Tang L, Deán-Ben XL, Razansky D. Multimodal optoacoustic imaging: methods and contrast materials. Chem Soc Rev 2024; 53:6068-6099. [PMID: 38738633 PMCID: PMC11181994 DOI: 10.1039/d3cs00565h] [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: 12/19/2023] [Indexed: 05/14/2024]
Abstract
Optoacoustic (OA) imaging offers powerful capabilities for interrogating biological tissues with rich optical absorption contrast while maintaining high spatial resolution for deep tissue observations. The spectrally distinct absorption of visible and near-infrared photons by endogenous tissue chromophores facilitates extraction of diverse anatomic, functional, molecular, and metabolic information from living tissues across various scales, from organelles and cells to whole organs and organisms. The primarily blood-related contrast and limited penetration depth of OA imaging have fostered the development of multimodal approaches to fully exploit the unique advantages and complementarity of the method. We review the recent hybridization efforts, including multimodal combinations of OA with ultrasound, fluorescence, optical coherence tomography, Raman scattering microscopy and magnetic resonance imaging as well as ionizing methods, such as X-ray computed tomography, single-photon-emission computed tomography and positron emission tomography. Considering that most molecules absorb light across a broad range of the electromagnetic spectrum, the OA interrogations can be extended to a large number of exogenously administered small molecules, particulate agents, and genetically encoded labels. This unique property further makes contrast moieties used in other imaging modalities amenable for OA sensing.
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Affiliation(s)
- Zhenyue Chen
- Institute for Biomedical Engineering and Institute of Pharmacology and Toxicology, Faculty of Medicine, University of Zurich, Switzerland.
- Institute for Biomedical Engineering, Department of Information Technology and Electrical Engineering, ETH Zurich, Switzerland
| | - Irmak Gezginer
- Institute for Biomedical Engineering and Institute of Pharmacology and Toxicology, Faculty of Medicine, University of Zurich, Switzerland.
- Institute for Biomedical Engineering, Department of Information Technology and Electrical Engineering, ETH Zurich, Switzerland
| | - Quanyu Zhou
- Institute for Biomedical Engineering and Institute of Pharmacology and Toxicology, Faculty of Medicine, University of Zurich, Switzerland.
- Institute for Biomedical Engineering, Department of Information Technology and Electrical Engineering, ETH Zurich, Switzerland
| | - Lin Tang
- Institute for Biomedical Engineering and Institute of Pharmacology and Toxicology, Faculty of Medicine, University of Zurich, Switzerland.
- Institute for Biomedical Engineering, Department of Information Technology and Electrical Engineering, ETH Zurich, Switzerland
| | - Xosé Luís Deán-Ben
- Institute for Biomedical Engineering and Institute of Pharmacology and Toxicology, Faculty of Medicine, University of Zurich, Switzerland.
- Institute for Biomedical Engineering, Department of Information Technology and Electrical Engineering, ETH Zurich, Switzerland
| | - Daniel Razansky
- Institute for Biomedical Engineering and Institute of Pharmacology and Toxicology, Faculty of Medicine, University of Zurich, Switzerland.
- Institute for Biomedical Engineering, Department of Information Technology and Electrical Engineering, ETH Zurich, Switzerland
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9
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Driscoll N, Antonini MJ, Cannon TM, Maretich P, Olaitan G, Phi Van VD, Nagao K, Sahasrabudhe A, Vargas E, Hunt S, Hummel M, Mupparaju S, Jasanoff A, Venton J, Anikeeva P. Fiber-based Probes for Electrophysiology, Photometry, Optical and Electrical Stimulation, Drug Delivery, and Fast-Scan Cyclic Voltammetry In Vivo. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.07.598004. [PMID: 38895451 PMCID: PMC11185794 DOI: 10.1101/2024.06.07.598004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/21/2024]
Abstract
Recording and modulation of neuronal activity enables the study of brain function in health and disease. While translational neuroscience relies on electrical recording and modulation techniques, mechanistic studies in rodent models leverage genetic precision of optical methods, such as optogenetics and imaging of fluorescent indicators. In addition to electrical signal transduction, neurons produce and receive diverse chemical signals which motivate tools to probe and modulate neurochemistry. Although the past decade has delivered a wealth of technologies for electrophysiology, optogenetics, chemical sensing, and optical recording, combining these modalities within a single platform remains challenging. This work leverages materials selection and convergence fiber drawing to permit neural recording, electrical stimulation, optogenetics, fiber photometry, drug and gene delivery, and voltammetric recording of neurotransmitters within individual fibers. Composed of polymers and non-magnetic carbon-based conductors, these fibers are compatible with magnetic resonance imaging, enabling concurrent stimulation and whole-brain monitoring. Their utility is demonstrated in studies of the mesolimbic reward pathway by simultaneously interfacing with the ventral tegmental area and nucleus accumbens in mice and characterizing the neurophysiological effects of a stimulant drug. This study highlights the potential of these fibers to probe electrical, optical, and chemical signaling across multiple brain regions in both mechanistic and translational studies.
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Affiliation(s)
| | | | | | - Pema Maretich
- Massachusetts Institute of Technology, Cambridge, MA 02139
| | | | | | - Keisuke Nagao
- Massachusetts Institute of Technology, Cambridge, MA 02139
| | | | | | | | - Melissa Hummel
- Massachusetts Institute of Technology, Cambridge, MA 02139
| | | | - Alan Jasanoff
- Massachusetts Institute of Technology, Cambridge, MA 02139
| | - Jill Venton
- The University of Virginia, Charlottesville, VA 22904
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10
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Kalani M, Anjankar A. Revolutionizing Neurology: The Role of Artificial Intelligence in Advancing Diagnosis and Treatment. Cureus 2024; 16:e61706. [PMID: 38975469 PMCID: PMC11224934 DOI: 10.7759/cureus.61706] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Accepted: 06/04/2024] [Indexed: 07/09/2024] Open
Abstract
Artificial intelligence (AI) has emerged as a powerful tool in the field of neurology, significantly impacting the diagnosis and treatment of neurological disorders. Recent technological breakthroughs have given us access to a plethora of information relevant to many aspects of neurology. Neuroscience and AI share a long history of collaboration. Along with great potential, we encounter obstacles relating to data quality, ethics, and inherent difficulty in applying data science in healthcare. Neurological disorders pose intricate challenges due to their complex manifestations and variability. Automating image interpretation tasks, AI algorithms accurately identify brain structures and detect abnormalities. This accelerates diagnosis and reduces the workload on medical professionals. Treatment optimization benefits from AI simulations that model different scenarios and predict outcomes. These AI systems can currently perform many of the sophisticated perceptual and cognitive capacities of biological systems, such as object identification and decision making. Furthermore, AI is rapidly being used as a tool in neuroscience research, altering our understanding of brain functioning. It has the ability to revolutionize healthcare as we know it into a system in which humans and robots collaborate to deliver better care for our patients. Image analysis activities such as recognizing particular brain regions, calculating changes in brain volume over time, and detecting abnormalities in brain scans can be automated by AI systems. This lessens the strain on radiologists and neurologists while improving diagnostic accuracy and efficiency. It is now obvious that cutting-edge artificial intelligence models combined with high-quality clinical data will lead to enhanced prognostic and diagnostic models in neurological illness, permitting expert-level clinical decision aids across healthcare settings. In conclusion, AI's integration into neurology has revolutionized diagnosis, treatment, and research. As AI technologies advance, they promise to unravel the complexities of neurological disorders further, leading to improved patient care and quality of life. The symbiosis of AI and neurology offers a glimpse into a future where innovation and compassion converge to reshape neurological healthcare. This abstract provides a concise overview of the role of AI in neurology and its transformative potential.
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Affiliation(s)
- Meetali Kalani
- Biochemistry, Jawaharlal Nehru Medical College, Datta Meghe Institute of Higher Education and Research, Wardha, IND
| | - Ashish Anjankar
- Biochemistry, Jawaharlal Nehru Medical College, Datta Meghe Institute of Higher Education and Research, Wardha, IND
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11
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Kim J, Lee W, Kang B, Seo H, Park H. A noise robust image reconstruction using slice aware cycle interpolator network for parallel imaging in MRI. Med Phys 2024; 51:4143-4157. [PMID: 38598259 DOI: 10.1002/mp.17066] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2023] [Revised: 03/01/2024] [Accepted: 03/23/2024] [Indexed: 04/11/2024] Open
Abstract
BACKGROUND Reducing Magnetic resonance imaging (MRI) scan time has been an important issue for clinical applications. In order to reduce MRI scan time, imaging acceleration was made possible by undersampling k-space data. This is achieved by leveraging additional spatial information from multiple, independent receiver coils, thereby reducing the number of sampled k-space lines. PURPOSE The aim of this study is to develop a deep-learning method for parallel imaging with a reduced number of auto-calibration signals (ACS) lines in noisy environments. METHODS A cycle interpolator network is developed for robust reconstruction of parallel MRI with a small number of ACS lines in noisy environments. The network estimates missing (unsampled) lines of each coil data, and these estimated missing lines are then utilized to re-estimate the sampled k-space lines. In addition, a slice aware reconstruction technique is developed for noise-robust reconstruction while reducing the number of ACS lines. We conducted an evaluation study using retrospectively subsampled data obtained from three healthy volunteers at 3T MRI, involving three different slice thicknesses (1.5, 3.0, and 4.5 mm) and three different image contrasts (T1w, T2w, and FLAIR). RESULTS Despite the challenges posed by substantial noise in cases with a limited number of ACS lines and thinner slices, the slice aware cycle interpolator network reconstructs the enhanced parallel images. It outperforms RAKI, effectively eliminating aliasing artifacts. Moreover, the proposed network outperforms GRAPPA and demonstrates the ability to successfully reconstruct brain images even under severe noisy conditions. CONCLUSIONS The slice aware cycle interpolator network has the potential to improve reconstruction accuracy for a reduced number of ACS lines in noisy environments.
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Affiliation(s)
- Jeewon Kim
- School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea
- Bionics Research Center, Korea Institute of Science and Technology (KIST), Seoul, Republic of Korea
| | - Wonil Lee
- School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea
| | - Beomgu Kang
- School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea
| | - Hyunseok Seo
- Bionics Research Center, Korea Institute of Science and Technology (KIST), Seoul, Republic of Korea
| | - HyunWook Park
- School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea
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12
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Gilbreath D, Hagood D, Larson-Prior L. A Systematic Review over the Effect of Early Infant Diet on Neurodevelopment: Insights from Neuroimaging. Nutrients 2024; 16:1703. [PMID: 38892636 PMCID: PMC11174660 DOI: 10.3390/nu16111703] [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: 03/20/2024] [Revised: 04/29/2024] [Accepted: 05/23/2024] [Indexed: 06/21/2024] Open
Abstract
The optimization of infant neuronal development through nutrition is an increasingly studied area. While human milk consumption during infancy is thought to give a slight cognitive advantage throughout early childhood in comparison to commercial formula, the biological underpinnings of this process are less well-known and debated in the literature. This systematic review seeks to quantitatively analyze whether early diet affects infant neurodevelopment as measured by various neuroimaging modalities and techniques. Results presented suggest that human milk does have a slight positive impact on the structural development of the infant brain-and that this impact is larger in preterm infants. Other diets with distinct macronutrient compositions were also considered, although these had more conflicting results.
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Affiliation(s)
- Dylan Gilbreath
- Department of Neurobiology and Developmental Sciences, University of Arkansas for Medical Science, Little Rock, AR 72207, USA;
- Arkansas Children’s Nutrition Center, Little Rock, AR 72202, USA;
| | - Darcy Hagood
- Arkansas Children’s Nutrition Center, Little Rock, AR 72202, USA;
| | - Linda Larson-Prior
- Department of Neurobiology and Developmental Sciences, University of Arkansas for Medical Science, Little Rock, AR 72207, USA;
- Arkansas Children’s Nutrition Center, Little Rock, AR 72202, USA;
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13
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Nistri R, Ianniello A, Pozzilli V, Giannì C, Pozzilli C. Advanced MRI Techniques: Diagnosis and Follow-Up of Multiple Sclerosis. Diagnostics (Basel) 2024; 14:1120. [PMID: 38893646 PMCID: PMC11171945 DOI: 10.3390/diagnostics14111120] [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: 04/08/2024] [Revised: 05/08/2024] [Accepted: 05/13/2024] [Indexed: 06/21/2024] Open
Abstract
Brain and spinal cord imaging plays a pivotal role in aiding clinicians with the diagnosis and monitoring of multiple sclerosis. Nevertheless, the significance of magnetic resonance imaging in MS extends beyond its clinical utility. Advanced imaging modalities have facilitated the in vivo detection of various components of MS pathogenesis, and, in recent years, MRI biomarkers have been utilized to assess the response of patients with relapsing-remitting MS to the available treatments. Similarly, MRI indicators of neurodegeneration demonstrate potential as primary and secondary endpoints in clinical trials targeting progressive phenotypes. This review aims to provide an overview of the latest advancements in brain and spinal cord neuroimaging in MS.
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Affiliation(s)
- Riccardo Nistri
- Department of Human Neuroscience, Sapienza University, 00185 Rome, Italy; (A.I.); (C.G.); (C.P.)
| | - Antonio Ianniello
- Department of Human Neuroscience, Sapienza University, 00185 Rome, Italy; (A.I.); (C.G.); (C.P.)
| | - Valeria Pozzilli
- Fondazione Policlinico Universitario Campus Bio-Medico, 00128 Rome, Italy
- Unit of Neurology, Neurophysiology, Neurobiology and Psychiatry, Department of Medicine and Surgery, Università Campus Bio-Medico di Roma, 00128 Rome, Italy
| | - Costanza Giannì
- Department of Human Neuroscience, Sapienza University, 00185 Rome, Italy; (A.I.); (C.G.); (C.P.)
- IRCCS Neuromed, 86077 Pozzilli, Italy
| | - Carlo Pozzilli
- Department of Human Neuroscience, Sapienza University, 00185 Rome, Italy; (A.I.); (C.G.); (C.P.)
- MS Center Sant’Andrea Hospital, 00189 Rome, Italy
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14
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Mallio CA, Buoso A, Stiffi M, Cea L, Vertulli D, Bernetti C, Di Gennaro G, van den Heuvel MP, Beomonte Zobel B. Mapping the Neural Basis of Neuroeconomics with Functional Magnetic Resonance Imaging: A Narrative Literature Review. Brain Sci 2024; 14:511. [PMID: 38790489 PMCID: PMC11120557 DOI: 10.3390/brainsci14050511] [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: 04/17/2024] [Revised: 05/09/2024] [Accepted: 05/17/2024] [Indexed: 05/26/2024] Open
Abstract
Neuroeconomics merges neuroscience, economics, and psychology to investigate the neural basis of decision making. Decision making involves assessing outcomes with subjective value, shaped by emotions and experiences, which are crucial in economic decisions. Functional MRI (fMRI) reveals key areas of the brain, including the ventro-medial prefrontal cortex, that are involved in subjective value representation. Collaborative interdisciplinary efforts are essential for advancing the field of neuroeconomics, with implications for clinical interventions and policy design. This review explores subjective value in neuroeconomics, highlighting brain regions identified through fMRI studies.
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Affiliation(s)
- Carlo A. Mallio
- Fondazione Policlinico Universitario Campus Bio-Medico, 00100 Rome, Italy; (A.B.); (M.S.); (L.C.); (D.V.); (C.B.); (B.B.Z.)
- Research Unit of Radiology, Department of Medicine and Surgery, Università Campus Bio-Medico di Roma, 00100 Rome, Italy
| | - Andrea Buoso
- Fondazione Policlinico Universitario Campus Bio-Medico, 00100 Rome, Italy; (A.B.); (M.S.); (L.C.); (D.V.); (C.B.); (B.B.Z.)
- Research Unit of Radiology, Department of Medicine and Surgery, Università Campus Bio-Medico di Roma, 00100 Rome, Italy
| | - Massimo Stiffi
- Fondazione Policlinico Universitario Campus Bio-Medico, 00100 Rome, Italy; (A.B.); (M.S.); (L.C.); (D.V.); (C.B.); (B.B.Z.)
- Research Unit of Radiology, Department of Medicine and Surgery, Università Campus Bio-Medico di Roma, 00100 Rome, Italy
| | - Laura Cea
- Fondazione Policlinico Universitario Campus Bio-Medico, 00100 Rome, Italy; (A.B.); (M.S.); (L.C.); (D.V.); (C.B.); (B.B.Z.)
- Research Unit of Radiology, Department of Medicine and Surgery, Università Campus Bio-Medico di Roma, 00100 Rome, Italy
| | - Daniele Vertulli
- Fondazione Policlinico Universitario Campus Bio-Medico, 00100 Rome, Italy; (A.B.); (M.S.); (L.C.); (D.V.); (C.B.); (B.B.Z.)
- Research Unit of Radiology, Department of Medicine and Surgery, Università Campus Bio-Medico di Roma, 00100 Rome, Italy
| | - Caterina Bernetti
- Fondazione Policlinico Universitario Campus Bio-Medico, 00100 Rome, Italy; (A.B.); (M.S.); (L.C.); (D.V.); (C.B.); (B.B.Z.)
- Research Unit of Radiology, Department of Medicine and Surgery, Università Campus Bio-Medico di Roma, 00100 Rome, Italy
| | - Gianfranco Di Gennaro
- Department of Health Sciences, Medical Statistics, University of Catanzaro “Magna Græcia”, 88100 Catanzaro, Italy;
| | - Martijn P. van den Heuvel
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, 1081 Amsterdam, The Netherlands;
- Department of Child and Adolescent Psychiatry and Psychology, Amsterdam UMC, Vrije Universiteit Amsterdam, 1081 Amsterdam, The Netherlands
| | - Bruno Beomonte Zobel
- Fondazione Policlinico Universitario Campus Bio-Medico, 00100 Rome, Italy; (A.B.); (M.S.); (L.C.); (D.V.); (C.B.); (B.B.Z.)
- Research Unit of Radiology, Department of Medicine and Surgery, Università Campus Bio-Medico di Roma, 00100 Rome, Italy
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15
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Haris EM, Bryant RA, Korgaonkar MS. Structural covariance, topological organization, and volumetric features of amygdala subnuclei in posttraumatic stress disorder. Neuroimage Clin 2024; 42:103619. [PMID: 38744025 PMCID: PMC11108976 DOI: 10.1016/j.nicl.2024.103619] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2023] [Revised: 04/14/2024] [Accepted: 05/10/2024] [Indexed: 05/16/2024]
Abstract
The amygdala is divided into functional subnuclei which have been challenging to investigate due to functional magnetic resonance imaging (MRI) limitations in mapping small neural structures. Hence their role in the neurobiology of posttraumatic stress disorder (PTSD) remains poorly understood. Examination of covariance of structural MRI measures could be an alternate approach to circumvent this issue. T1-weighted anatomical scans from a 3 T scanner from non-trauma-exposed controls (NEC; n = 71, 75 % female) and PTSD participants (n = 67, 69 % female) were parcellated into 105 brain regions. Pearson's r partial correlations were computed for three and nine bilateral amygdala subnuclei and every other brain region, corrected for age, sex, and total brain volume. Pairwise correlation comparisons were performed to examine subnuclei covariance profiles between-groups. Graph theory was employed to investigate subnuclei network topology. Volumetric measures were compared to investigate structural changes. We found differences between amygdala subnuclei in covariance with the hippocampus for both groups, and additionally with temporal brain regions for the PTSD group. Network topology demonstrated the importance of the right basal nucleus in facilitating network communication only in PTSD. There were no between-group differences for any of the three structural metrics. These findings are in line with previous work that has failed to find structural differences for amygdala subnuclei between PTSD and controls. However, differences between amygdala subnuclei covariance profiles observed in our study highlight the need to investigate amygdala subnuclei functional connectivity in PTSD using higher field strength fMRI for better spatial resolution.
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Affiliation(s)
- Elizabeth M Haris
- Brain Dynamics Centre, Westmead Institute for Medical Research, The University of Sydney, Westmead, NSW, Australia; School of Psychology, University of New South Wales, Sydney, Australia.
| | - Richard A Bryant
- Brain Dynamics Centre, Westmead Institute for Medical Research, The University of Sydney, Westmead, NSW, Australia; School of Psychology, University of New South Wales, Sydney, Australia
| | - Mayuresh S Korgaonkar
- Brain Dynamics Centre, Westmead Institute for Medical Research, The University of Sydney, Westmead, NSW, Australia; Discipline of Psychiatry, Sydney Medical School, Westmead, NSW, Australia; Department of Radiology, Western Sydney Local Health District, Westmead, NSW, Australia.
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16
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Song B, Sommer W, Maurer U. Expectation Modulates Repetition Suppression at Late But Not Early Stages during Visual Word Recognition: Evidence from Event-related Potentials. J Cogn Neurosci 2024; 36:872-887. [PMID: 38261395 DOI: 10.1162/jocn_a_02111] [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] [Indexed: 01/24/2024]
Abstract
Visual word recognition is commonly rapid and efficient, incorporating top-down predictive processing mechanisms. Neuroimaging studies with face stimuli suggest that repetition suppression (RS) reflects predictive processing at the neural level, as this effect is larger when repetitions are more frequent, that is, more expected. It remains unclear, however, at the temporal level whether and how RS and its modulation by expectation occur in visual word recognition. To address this gap, the present study aimed to investigate the presence and time course of these effects during visual word recognition using EEG. Thirty-six native Cantonese speakers were presented with pairs of Chinese written words and performed a nonlinguistic oddball task. The second word of a pair was either a repetition of the first or a different word (alternation). In repetition blocks, 75% of trials were repetitions and 25% were alternations, whereas the reverse was true in alternation blocks. Topographic analysis of variance of EEG at each time point showed robust RS effects in three time windows (141-227 msec, 242-445 msec, and 467-513 msec) reflecting facilitation of visual word recognition. Importantly, the modulation of RS by expectation was observed at the late rather than early intervals (334-387 msec, 465-550 msec, and 559-632 msec) and more than 100 msec after the first RS effects. In the predictive coding view of RS, only late repetition effects are modulated by expectation, whereas early RS effects may be mediated by lower-level predictions. Taken together, our findings provide the first EEG evidence revealing distinct temporal dynamics of RS effects and repetition probability on RS effects in visual processing of Chinese words.
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Affiliation(s)
- Bingbing Song
- Department of Psychology, The Chinese University of Hong Kong, Hong Kong, China
| | - Werner Sommer
- Institut für Psychologie, Humboldt-Universitaet zu Berlin, Berlin, Germany
- Department of Physics, Hong Kong Baptist University, Hong Kong, China
| | - Urs Maurer
- Department of Psychology, The Chinese University of Hong Kong, Hong Kong, China
- Centre for Developmental Psychology, The Chinese University of Hong Kong, Hong Kong, China
- Brain and Mind Institute, The Chinese University of Hong Kong, Hong Kong, China
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17
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Taguchi T, Kitazono J, Sasai S, Oizumi M. Association of bidirectional network cores in the brain with conscious perception and cognition. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.30.591001. [PMID: 38746271 PMCID: PMC11092575 DOI: 10.1101/2024.04.30.591001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/16/2024]
Abstract
The brain comprises a complex network of interacting regions. To understand the roles and mechanisms of this complex network, its structural features related to specific cognitive functions need to be elucidated. Among such relationships, recent developments in neuroscience highlight the link between network bidirectionality and conscious perception. Given the essential roles of both feedforward and feedback signals in conscious perception, it is surmised that subnetworks with bidirectional interactions are critical. However, the link between such subnetworks and conscious perception remains unclear due to the network's complexity. In this study, we propose a framework for extracting subnetworks with strong bidirectional interactions-termed the "cores" of a network-from brain activity. We applied this framework to resting-state and task-based fMRI data to identify regions forming strongly bidirectional cores. We then explored the association of these cores with conscious perception and cognitive functions. The central cores predominantly included cerebral cortical regions, which are crucial for conscious perception, rather than subcortical regions. Furthermore, the cores were composed of previously reported regions in which electrical stimulation altered conscious perception. These results suggest a link between the bidirectional cores and conscious perception. A meta-analysis and comparison of the core structure with a cortical functional connectivity gradient suggested that the central cores were related to lower-order sensorimotor functions. An ablation study emphasized the importance of incorporating bidirectionality, not merely interaction strength for these outcomes. The proposed framework provides novel insight into the roles of network cores with strong bidirectional interactions in conscious perception and lower-order sensorimotor functions.
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Affiliation(s)
- Tomoya Taguchi
- Graduate School of Arts and Sciences, The University of Tokyo, Tokyo, Japan
| | - Jun Kitazono
- Graduate School of Data Science, Yokohama City University, Kanagawa, Japan
| | | | - Masafumi Oizumi
- Graduate School of Arts and Sciences, The University of Tokyo, Tokyo, Japan
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18
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Wang KP, Yu CL, Shen C, Schack T, Hung TM. A longitudinal study of the effect of visuomotor learning on functional brain connectivity. Psychophysiology 2024; 61:e14510. [PMID: 38159049 DOI: 10.1111/psyp.14510] [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: 03/06/2023] [Revised: 10/07/2023] [Accepted: 10/12/2023] [Indexed: 01/03/2024]
Abstract
Neural adaptation in the frontoparietal and motor cortex-sensorimotor circuits is crucial for acquiring visuomotor skills. However, the specific nature of highly dynamic neural connectivity in these circuits during the acquisition of visuomotor skills remains unclear. To achieve a more comprehensive understanding of the relationship between acquisition of visuomotor skills and neural connectivity, we used electroencephalographic coherence to capture highly dynamic nature of neural connectivity. We recruited 60 male novices who were randomly assigned to either the experimental group (EG) or the control group (CG). Participants in EG were asked to engage in repeated putting practice, but CG did not engage in golf practice. In addition, we analyzed the connectivity by using 8-13 Hz imaginary inter-site phase coherence in the frontoparietal networks (Fz-P3 and Fz-P4) and the motor cortex-sensorimotor networks (Cz-C3 and Cz-C4) during a golf putting task. To gain a deeper understanding of the dynamic nature of learning trajectories, we compared data at three time points: baseline (T1), 50% improvement from baseline (T2), and 100% improvement from baseline (T3). The results primarily focused on EG, an inverted U-shaped coherence curve was observed in the connectivity of the left motor cortex-sensorimotor circuit, whereas an increase in the connectivity of the right frontoparietal circuit from T2 to T3 was revealed. These results imply that the dynamics of cortico-cortical communication, particularly involving the left motor cortex-sensorimotor and frontal-left parietal circuits. In addition, our findings partially support Hikosaka et al.'s model and provide additional insight into the specific role of these circuits in visuomotor learning.
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Affiliation(s)
- Kuo-Pin Wang
- Center for Cognitive Interaction Technology, Bielefeld University, Bielefeld, Germany
- Neurocognition and Action, Biomechanics Research Group, Faculty of Psychology and Sports Science, Bielefeld University, Bielefeld, Germany
| | - Chien-Lin Yu
- Department of Physical Education and Sport Sciences, National Taiwan Normal University, Taipei, Taiwan
| | - Cheng Shen
- Department of Physical Education and Sport Sciences, National Taiwan Normal University, Taipei, Taiwan
| | - Thomas Schack
- Center for Cognitive Interaction Technology, Bielefeld University, Bielefeld, Germany
- Neurocognition and Action, Biomechanics Research Group, Faculty of Psychology and Sports Science, Bielefeld University, Bielefeld, Germany
| | - Tsung-Min Hung
- Department of Physical Education and Sport Sciences, National Taiwan Normal University, Taipei, Taiwan
- Institute for Research Excellence in Learning Science, National Taiwan Normal University, Taipei, Taiwan
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19
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Stumpo V, Sayin ES, Bellomo J, Sobczyk O, van Niftrik CHB, Sebök M, Weller M, Regli L, Kulcsár Z, Pangalu A, Bink A, Duffin J, Mikulis DD, Fisher JA, Fierstra J. Transient deoxyhemoglobin formation as a contrast for perfusion MRI studies in patients with brain tumors: a feasibility study. Front Physiol 2024; 15:1238533. [PMID: 38725571 PMCID: PMC11079274 DOI: 10.3389/fphys.2024.1238533] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Accepted: 04/02/2024] [Indexed: 05/12/2024] Open
Abstract
Background: Transient hypoxia-induced deoxyhemoglobin (dOHb) has recently been shown to represent a comparable contrast to gadolinium-based contrast agents for generating resting perfusion measures in healthy subjects. Here, we investigate the feasibility of translating this non-invasive approach to patients with brain tumors. Methods: A computer-controlled gas blender was used to induce transient precise isocapnic lung hypoxia and thereby transient arterial dOHb during echo-planar-imaging acquisition in a cohort of patients with different types of brain tumors (n = 9). We calculated relative cerebral blood volume (rCBV), cerebral blood flow (rCBF), and mean transit time (MTT) using a standard model-based analysis. The transient hypoxia induced-dOHb MRI perfusion maps were compared to available clinical DSC-MRI. Results: Transient hypoxia induced-dOHb based maps of resting perfusion displayed perfusion patterns consistent with underlying tumor histology and showed high spatial coherence to gadolinium-based DSC MR perfusion maps. Conclusion: Non-invasive transient hypoxia induced-dOHb was well-tolerated in patients with different types of brain tumors, and the generated rCBV, rCBF and MTT maps appear in good agreement with perfusion maps generated with gadolinium-based DSC MR perfusion.
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Affiliation(s)
- Vittorio Stumpo
- Department of Neurosurgery, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Ece Su Sayin
- Department of Physiology, University of Toronto, Toronto, ON, Canada
- Joint Department of Medical Imaging and the Functional Neuroimaging Lab, University Health Network, Toronto, ON, Canada
| | - Jacopo Bellomo
- Department of Neurosurgery, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Olivia Sobczyk
- Joint Department of Medical Imaging and the Functional Neuroimaging Lab, University Health Network, Toronto, ON, Canada
- Department of Anesthesia and Pain Management, University Health Network, University of Toronto, Toronto, ON, Canada
| | | | - Martina Sebök
- Department of Neurosurgery, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Michael Weller
- Department of Neurology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Luca Regli
- Department of Neurosurgery, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Zsolt Kulcsár
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Athina Pangalu
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Andrea Bink
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - James Duffin
- Department of Physiology, University of Toronto, Toronto, ON, Canada
- Joint Department of Medical Imaging and the Functional Neuroimaging Lab, University Health Network, Toronto, ON, Canada
| | - David D. Mikulis
- Department of Anesthesia and Pain Management, University Health Network, University of Toronto, Toronto, ON, Canada
| | - Joseph A. Fisher
- Department of Physiology, University of Toronto, Toronto, ON, Canada
- Joint Department of Medical Imaging and the Functional Neuroimaging Lab, University Health Network, Toronto, ON, Canada
| | - Jorn Fierstra
- Department of Neurosurgery, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland
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20
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Zhou Q, Glück C, Tang L, Glandorf L, Droux J, El Amki M, Wegener S, Weber B, Razansky D, Chen Z. Cortex-wide transcranial localization microscopy with fluorescently labeled red blood cells. Nat Commun 2024; 15:3526. [PMID: 38664419 PMCID: PMC11045747 DOI: 10.1038/s41467-024-47892-3] [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: 11/13/2023] [Accepted: 04/15/2024] [Indexed: 04/28/2024] Open
Abstract
Large-scale imaging of brain activity with high spatio-temporal resolution is crucial for advancing our understanding of brain function. The existing neuroimaging techniques are largely limited by restricted field of view, slow imaging speed, or otherwise do not have the adequate spatial resolution to capture brain activities on a capillary and cellular level. To address these limitations, we introduce fluorescence localization microscopy aided with sparsely-labeled red blood cells for cortex-wide morphological and functional cerebral angiography with 4.9 µm spatial resolution and 1 s temporal resolution. When combined with fluorescence calcium imaging, the proposed method enables extended recordings of stimulus-evoked neuro-vascular changes in the murine brain while providing simultaneous multiparametric readings of intracellular neuronal activity, blood flow velocity/direction/volume, and vessel diameter. Owing to its simplicity and versatility, the proposed approach will become an invaluable tool for deciphering the regulation of cortical microcirculation and neurovascular coupling in health and disease.
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Affiliation(s)
- Quanyu Zhou
- Institute of Pharmacology and Toxicology, Faculty of Medicine, University of Zurich, Zurich, Switzerland
- Institute for Biomedical Engineering, Department of Information Technology and Electrical Engineering, ETH Zurich, Zurich, Switzerland
| | - Chaim Glück
- Institute of Pharmacology and Toxicology, Faculty of Medicine, University of Zurich, Zurich, Switzerland
- Zurich Neuroscience Center, Zurich, Switzerland
| | - Lin Tang
- Institute of Pharmacology and Toxicology, Faculty of Medicine, University of Zurich, Zurich, Switzerland
- Institute for Biomedical Engineering, Department of Information Technology and Electrical Engineering, ETH Zurich, Zurich, Switzerland
| | - Lukas Glandorf
- Institute of Pharmacology and Toxicology, Faculty of Medicine, University of Zurich, Zurich, Switzerland
- Institute for Biomedical Engineering, Department of Information Technology and Electrical Engineering, ETH Zurich, Zurich, Switzerland
| | - Jeanne Droux
- Zurich Neuroscience Center, Zurich, Switzerland
- Department of Neurology, University Hospital and University of Zurich, Zurich, Switzerland
| | - Mohamad El Amki
- Zurich Neuroscience Center, Zurich, Switzerland
- Department of Neurology, University Hospital and University of Zurich, Zurich, Switzerland
| | - Susanne Wegener
- Zurich Neuroscience Center, Zurich, Switzerland
- Department of Neurology, University Hospital and University of Zurich, Zurich, Switzerland
| | - Bruno Weber
- Institute of Pharmacology and Toxicology, Faculty of Medicine, University of Zurich, Zurich, Switzerland
- Zurich Neuroscience Center, Zurich, Switzerland
| | - Daniel Razansky
- Institute of Pharmacology and Toxicology, Faculty of Medicine, University of Zurich, Zurich, Switzerland.
- Institute for Biomedical Engineering, Department of Information Technology and Electrical Engineering, ETH Zurich, Zurich, Switzerland.
- Zurich Neuroscience Center, Zurich, Switzerland.
| | - Zhenyue Chen
- Institute of Pharmacology and Toxicology, Faculty of Medicine, University of Zurich, Zurich, Switzerland.
- Institute for Biomedical Engineering, Department of Information Technology and Electrical Engineering, ETH Zurich, Zurich, Switzerland.
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21
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Sasaki D, Imai K, Ikoma Y, Matsui K. Plastic vasomotion entrainment. eLife 2024; 13:RP93721. [PMID: 38629828 PMCID: PMC11023696 DOI: 10.7554/elife.93721] [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] [Indexed: 04/19/2024] Open
Abstract
The presence of global synchronization of vasomotion induced by oscillating visual stimuli was identified in the mouse brain. Endogenous autofluorescence was used and the vessel 'shadow' was quantified to evaluate the magnitude of the frequency-locked vasomotion. This method allows vasomotion to be easily quantified in non-transgenic wild-type mice using either the wide-field macro-zoom microscopy or the deep-brain fiber photometry methods. Vertical stripes horizontally oscillating at a low temporal frequency (0.25 Hz) were presented to the awake mouse, and oscillatory vasomotion locked to the temporal frequency of the visual stimulation was induced not only in the primary visual cortex but across a wide surface area of the cortex and the cerebellum. The visually induced vasomotion adapted to a wide range of stimulation parameters. Repeated trials of the visual stimulus presentations resulted in the plastic entrainment of vasomotion. Horizontally oscillating visual stimulus is known to induce horizontal optokinetic response (HOKR). The amplitude of the eye movement is known to increase with repeated training sessions, and the flocculus region of the cerebellum is known to be essential for this learning to occur. Here, we show a strong correlation between the average HOKR performance gain and the vasomotion entrainment magnitude in the cerebellar flocculus. Therefore, the plasticity of vasomotion and neuronal circuits appeared to occur in parallel. Efficient energy delivery by the entrained vasomotion may contribute to meeting the energy demand for increased coordinated neuronal activity and the subsequent neuronal circuit reorganization.
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Affiliation(s)
- Daichi Sasaki
- Super-network Brain Physiology, Graduate School of Life Sciences, Tohoku UniversitySendaiJapan
| | - Ken Imai
- Super-network Brain Physiology, Graduate School of Life Sciences, Tohoku UniversitySendaiJapan
| | - Yoko Ikoma
- Super-network Brain Physiology, Graduate School of Life Sciences, Tohoku UniversitySendaiJapan
| | - Ko Matsui
- Super-network Brain Physiology, Graduate School of Life Sciences, Tohoku UniversitySendaiJapan
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22
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Moschopoulos CD, Stanitsa E, Protopapas K, Kavatha D, Papageorgiou SG, Antoniadou A, Papadopoulos A. Multimodal Approach to Neurocognitive Function in People Living with HIV in the cART Era: A Comprehensive Review. Life (Basel) 2024; 14:508. [PMID: 38672778 PMCID: PMC11050956 DOI: 10.3390/life14040508] [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: 03/07/2024] [Revised: 04/02/2024] [Accepted: 04/13/2024] [Indexed: 04/28/2024] Open
Abstract
Combination antiretroviral treatment (cART) has revolutionized the management of human immunodeficiency virus (HIV) and has markedly improved the disease burden and life expectancy of people living with HIV. HIV enters the central nervous system (CNS) early in the course of infection, establishes latency, and produces a pro-inflammatory milieu that may affect cognitive functions, even in the cART era. Whereas severe forms of neurocognitive impairment (NCI) such as HIV-associated dementia have declined over the last decades, milder forms have become more prevalent, are commonly multifactorial, and are associated with comorbidity burdens, mental health, cART neurotoxicity, and ageing. Since 2007, the Frascati criteria have been used to characterize and classify HIV-associated neurocognitive disorders (HAND) into three stages, namely asymptomatic neurocognitive impairment (ANI), mild neurocognitive disorder (MND), and HIV-associated dementia (HAD). These criteria are based on a comprehensive neuropsychological assessment that presupposes the availability of validated, demographically adjusted, and normative population data. Novel neuroimaging modalities and biomarkers have been proposed in order to complement NCI assessments, elucidate neuropathogenic mechanisms, and support HIV-associated NCI diagnosis, monitoring, and prognosis. By integrating neuropsychological assessments with biomarkers and neuroimaging into a holistic care approach, clinicians can enhance diagnostic accuracy, prognosis, and patient outcomes. This review interrogates the value of these modes of assessment and proposes a unified approach to NCI diagnosis.
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Affiliation(s)
- Charalampos D. Moschopoulos
- 4th Department of Internal Medicine, Medical School of Athens, National and Kapodistrian University of Athens, Attikon University Hospital, 12462 Athens, Greece; (K.P.); (D.K.); (A.A.); (A.P.)
| | - Evangelia Stanitsa
- 1st Department of Neurology, Medical School of Athens, National and Kapodistrian University of Athens, Eginition Hospital, 11528 Athens, Greece; (E.S.); (S.G.P.)
| | - Konstantinos Protopapas
- 4th Department of Internal Medicine, Medical School of Athens, National and Kapodistrian University of Athens, Attikon University Hospital, 12462 Athens, Greece; (K.P.); (D.K.); (A.A.); (A.P.)
| | - Dimitra Kavatha
- 4th Department of Internal Medicine, Medical School of Athens, National and Kapodistrian University of Athens, Attikon University Hospital, 12462 Athens, Greece; (K.P.); (D.K.); (A.A.); (A.P.)
| | - Sokratis G. Papageorgiou
- 1st Department of Neurology, Medical School of Athens, National and Kapodistrian University of Athens, Eginition Hospital, 11528 Athens, Greece; (E.S.); (S.G.P.)
| | - Anastasia Antoniadou
- 4th Department of Internal Medicine, Medical School of Athens, National and Kapodistrian University of Athens, Attikon University Hospital, 12462 Athens, Greece; (K.P.); (D.K.); (A.A.); (A.P.)
| | - Antonios Papadopoulos
- 4th Department of Internal Medicine, Medical School of Athens, National and Kapodistrian University of Athens, Attikon University Hospital, 12462 Athens, Greece; (K.P.); (D.K.); (A.A.); (A.P.)
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Hughes NC, Qian H, Zargari M, Zhao Z, Singh B, Wang Z, Fulton JN, Johnson GW, Li R, Dawant BM, Englot DJ, Constantinidis C, Roberson SW, Bick SK. Reward Circuit Local Field Potential Modulations Precede Risk Taking. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.10.588629. [PMID: 38645237 PMCID: PMC11030333 DOI: 10.1101/2024.04.10.588629] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/23/2024]
Abstract
Risk taking behavior is a symptom of multiple neuropsychiatric disorders and often lacks effective treatments. Reward circuitry regions including the amygdala, orbitofrontal cortex, insula, and anterior cingulate have been implicated in risk-taking by neuroimaging studies. Electrophysiological activity associated with risk taking in these regions is not well understood in humans. Further characterizing the neural signalling that underlies risk-taking may provide therapeutic insight into disorders associated with risk-taking. Eleven patients with pharmacoresistant epilepsy who underwent stereotactic electroencephalography with electrodes in the amygdala, orbitofrontal cortex, insula, and/or anterior cingulate participated. Patients participated in a gambling task where they wagered on a visible playing card being higher than a hidden card, betting $5 or $20 on this outcome, while local field potentials were recorded from implanted electrodes. We used cluster-based permutation testing to identify reward prediction error signals by comparing oscillatory power following unexpected and expected rewards. We also used cluster-based permutation testing to compare power preceding high and low bets in high-risk (<50% chance of winning) trials and two-way ANOVA with bet and risk level to identify signals associated with risky, risk averse, and optimized decisions. We used linear mixed effects models to evaluate the relationship between reward prediction error and risky decision signals across trials, and a linear regression model for associations between risky decision signal power and Barratt Impulsiveness Scale scores for each patient. Reward prediction error signals were identified in the amygdala (p=0.0066), anterior cingulate (p=0.0092), and orbitofrontal cortex (p=6.0E-4, p=4.0E-4). Risky decisions were predicted by increased oscillatory power in high-gamma frequency range during card presentation in the orbitofrontal cortex (p=0.0022), and by increased power following bet cue presentation across the theta-to-beta range in the orbitofrontal cortex ( p =0.0022), high-gamma in the anterior cingulate ( p =0.0004), and high-gamma in the insula ( p =0.0014). Risk averse decisions were predicted by decreased orbitofrontal cortex gamma power ( p =2.0E-4). Optimized decisions that maximized earnings were preceded by decreases within the theta to beta range in orbitofrontal cortex ( p =2.0E-4), broad frequencies in amygdala ( p =2.0E-4), and theta to low-gamma in insula ( p =4.0E-4). Insula risky decision power was associated with orbitofrontal cortex high-gamma reward prediction error signal ( p =0.0048) and with patient impulsivity ( p =0.00478). Our findings identify and help characterize reward circuitry activity predictive of risk-taking in humans. These findings may serve as potential biomarkers to inform the development of novel treatment strategies such as closed loop neuromodulation for disorders of risk taking.
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24
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Morgado F, Vandewouw MM, Hammill C, Kelley E, Crosbie J, Schachar R, Ayub M, Nicolson R, Georgiades S, Arnold P, Iaboni A, Kushki A, Taylor MJ, Anagnostou E, Lerch JP. Behaviour-correlated profiles of cerebellar-cerebral functional connectivity observed in independent neurodevelopmental disorder cohorts. Transl Psychiatry 2024; 14:173. [PMID: 38570480 PMCID: PMC10991387 DOI: 10.1038/s41398-024-02857-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Revised: 02/27/2024] [Accepted: 02/29/2024] [Indexed: 04/05/2024] Open
Abstract
The cerebellum, through its connectivity with the cerebral cortex, plays an integral role in regulating cognitive and affective processes, and its dysregulation can result in neurodevelopmental disorder (NDD)-related behavioural deficits. Identifying cerebellar-cerebral functional connectivity (FC) profiles in children with NDDs can provide insight into common connectivity profiles and their correlation to NDD-related behaviours. 479 participants from the Province of Ontario Neurodevelopmental Disorders (POND) network (typically developing = 93, Autism Spectrum Disorder = 172, Attention Deficit/Hyperactivity Disorder = 161, Obsessive-Compulsive Disorder = 53, mean age = 12.2) underwent resting-state functional magnetic resonance imaging and behaviour testing (Social Communication Questionnaire, Toronto Obsessive-Compulsive Scale, and Child Behaviour Checklist - Attentional Problems Subscale). FC components maximally correlated to behaviour were identified using canonical correlation analysis. Results were then validated by repeating the investigation in 556 participants from an independent NDD cohort provided from a separate consortium (Healthy Brain Network (HBN)). Replication of canonical components was quantified by correlating the feature vectors between the two cohorts. The two cerebellar-cerebral FC components that replicated to the greatest extent were correlated to, respectively, obsessive-compulsive behaviour (behaviour feature vectors, rPOND-HBN = -0.97; FC feature vectors, rPOND-HBN = -0.68) and social communication deficit contrasted against attention deficit behaviour (behaviour feature vectors, rPOND-HBN = -0.99; FC feature vectors, rPOND-HBN = -0.78). The statistically stable (|z| > 1.96) features of the FC feature vectors, measured via bootstrap re-sampling, predominantly comprised of correlations between cerebellar attentional and control network regions and cerebral attentional, default mode, and control network regions. In both cohorts, spectral clustering on FC loading values resulted in subject clusters mixed across diagnostic categories, but no cluster was significantly enriched for any given diagnosis as measured via chi-squared test (p > 0.05). Overall, two behaviour-correlated components of cerebellar-cerebral functional connectivity were observed in two independent cohorts. This suggests the existence of generalizable cerebellar network differences that span across NDD diagnostic boundaries.
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Affiliation(s)
- Felipe Morgado
- Dept. Medical Biophysics, University of Toronto, Toronto, Canada.
- Neurosciences & Mental Health, Hospital for Sick Children, Toronto, Canada.
| | - Marlee M Vandewouw
- Institute of Biomedical Engineering, University of Toronto, Toronto, Canada
- Autism Research Centre, Holland Bloorview Kids Rehabilitation Hospital, Toronto, Canada
| | - Christopher Hammill
- Data Science & Advanced Analytics, St. Michael's Hospital, University of Toronto, Toronto, Canada
| | | | - Jennifer Crosbie
- Neurosciences & Mental Health, Hospital for Sick Children, Toronto, Canada
- Department of Psychiatry, University of Toronto, Toronto, Canada
| | - Russell Schachar
- Neurosciences & Mental Health, Hospital for Sick Children, Toronto, Canada
- Department of Psychiatry, University of Toronto, Toronto, Canada
| | - Muhammad Ayub
- Department of Psychiatry, University College London, London, UK
| | - Robert Nicolson
- Department of Psychiatry, University of Western Ontario, London, Canada
- Lawson Research Institute, London, Canada
| | - Stelios Georgiades
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, Canada
- Offord Centre for Child Studies, McMaster University, Hamilton, Canada
| | - Paul Arnold
- The Mathison Centre for Mental Health Research & Education, Hotchkiss Brain Institute, University of Calgary, Calgary, Canada
- Department of Psychiatry, University of Calgary, Calgary, Canada
| | - Alana Iaboni
- Autism Research Centre, Holland Bloorview Kids Rehabilitation Hospital, Toronto, Canada
| | - Azadeh Kushki
- Institute of Biomedical Engineering, University of Toronto, Toronto, Canada
- Autism Research Centre, Holland Bloorview Kids Rehabilitation Hospital, Toronto, Canada
| | - Margot J Taylor
- Neurosciences & Mental Health, Hospital for Sick Children, Toronto, Canada
- Diagnostic Imaging, Hospital for Sick Children, Toronto, Canada
- Department of Medical Imaging, University of Toronto, Toronto, Canada
| | - Evdokia Anagnostou
- Autism Research Centre, Holland Bloorview Kids Rehabilitation Hospital, Toronto, Canada
- Institute of Medical Science, University of Toronto, Toronto, Canada
| | - Jason P Lerch
- Nuffield Department of Clinical Neurosciences, Oxford University, Oxford, UK
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Salehi MA, Zafari R, Mohammadi S, Shahrabi Farahani M, Dolatshahi M, Harandi H, Poopak A, Dager SR. Brain-based sex differences in schizophrenia: A systematic review of fMRI studies. Hum Brain Mapp 2024; 45:e26664. [PMID: 38520370 PMCID: PMC10960555 DOI: 10.1002/hbm.26664] [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: 12/08/2023] [Revised: 02/29/2024] [Accepted: 03/08/2024] [Indexed: 03/25/2024] Open
Abstract
Schizophrenia is a chronic psychiatric disorder with characteristic symptoms of delusions, hallucinations, lack of motivation, and paucity of thought. Recent evidence suggests that the symptoms of schizophrenia, negative symptoms in particular, vary widely between the sexes and that symptom onset is earlier in males. A better understanding of sex-based differences in functional magnetic resonance imaging (fMRI) studies of schizophrenia may provide a key to understanding sex-based symptom differences. This study aimed to summarize sex-based functional magnetic resonance imaging (fMRI) differences in brain activity of patients with schizophrenia. We searched PubMed and Scopus to find fMRI studies that assessed sex-based differences in the brain activity of patients with schizophrenia. We excluded studies that did not evaluate brain activity using fMRI, did not evaluate sex differences, and were nonhuman or in vitro studies. We found 12 studies that met the inclusion criteria for the current systematic review. Compared to females with schizophrenia, males with schizophrenia showed more blood oxygen level-dependent (BOLD) activation in the cerebellum, the temporal gyrus, and the right precuneus cortex. Male patients also had greater occurrence of low-frequency fluctuations in cerebral blood flow in frontal and parietal lobes and the insular cortex, while female patients had greater occurrence of low-frequency fluctuations in the hippocampus, parahippocampus, and lentiform nucleus. The current study summarizes fMRI studies that evaluated sex-based fMRI brain differences in schizophrenia that may help to shed light on the underlying pathophysiology and further understanding of sex-based differences in the clinical presentation and course of the disorder.
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Affiliation(s)
| | - Rasa Zafari
- School of MedicineTehran University of Medical SciencesTehranIran
| | - Soheil Mohammadi
- School of MedicineTehran University of Medical SciencesTehranIran
| | | | - Mahsa Dolatshahi
- Mallinckrodt Institute of Radiology, Division of NeuroradiologyWashington University in St. LouisSt. LouisMissouriUSA
| | - Hamid Harandi
- School of MedicineTehran University of Medical SciencesTehranIran
| | | | - Stephen R. Dager
- Department of RadiologyUniversity of WashingtonSeattleWashingtonUSA
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Xue Y, Dong HY, Feng JY, Bai MS, Li D, Yang H, Jia FY. Parent-child interaction related to brain functional alterations and development outcomes in autism spectrum disorder: A study based on resting state-fMRI. RESEARCH IN DEVELOPMENTAL DISABILITIES 2024; 147:104701. [PMID: 38402713 DOI: 10.1016/j.ridd.2024.104701] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Revised: 01/30/2024] [Accepted: 02/15/2024] [Indexed: 02/27/2024]
Abstract
BACKGROUND Limited study has investigated the influence of parent-child interaction on brain functional alterations and development outcomes of autism spectrum disorder (ASD) children. This pilot study aimed to explore the relationship between parent-child interaction, brain functional activities and development outcomes of ASD children. METHODS and Procedures: 653 ASD with an average age of 41.06 ± 10.88 months and 102 typically developmental (TD) children with an average age of 44.35 ± 18.39 months were enrolled in this study, of whom 155 ASD completed brain rs-fMRI scans. The amplitude of low-frequency fluctuations (ALFF) and regional homogeneity (ReHo) measured using resting-state functional magnetic resonance imaging (rs-fMRI) data reflect local brain function. The parent-child interaction was assessed by the Chinese Parent-child Interaction Scale (CPCIS). Childhood Autism Rating Scale (CARS) and developmental quotient (DQ) indicated development outcomes. OUTCOMES AND RESULTS Total CPCIS score was negatively correlated with CARS total score, and positively correlated with DQ. The frequency of parent-child interaction was negatively correlated with ALFF values in the left median cingulate and paracingulate gyri (DCG.L) and ReHo values in the right superior frontal gyrus, medial (SFGmed.R)(P < 0.05, FDR correction). ALFF values in the DCG.L and ReHo values in the SFGmed.R play complete mediating roles in the relationship between parent-child interaction and performance DQ. CONCLUSION AND IMPLICATIONS This study suggest that parent-child interaction has an impact on autistic characteristics and DQ of ASD children. Local brain regions with functional abnormalities in the DCG.L and SFGmed.R may be a crucial factors affecting the performance development of ASD children with reduced parent-child interaction.
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Affiliation(s)
- Yang Xue
- Department of Developmental and Behavioral Pediatrics, Children's Hospital of the First Hospital of Jilin University, The First Hospital of Jilin University, Jilin University, Changchun, China; The Child Health Clinical Research Center of Jilin Province, Changchun, China
| | - Han-Yu Dong
- Department of Developmental and Behavioral Pediatrics, Children's Hospital of the First Hospital of Jilin University, The First Hospital of Jilin University, Jilin University, Changchun, China; The Child Health Clinical Research Center of Jilin Province, Changchun, China
| | - Jun-Yan Feng
- Department of Developmental and Behavioral Pediatrics, Children's Hospital of the First Hospital of Jilin University, The First Hospital of Jilin University, Jilin University, Changchun, China; The Child Health Clinical Research Center of Jilin Province, Changchun, China
| | - Miao-Shui Bai
- Department of Developmental and Behavioral Pediatrics, Children's Hospital of the First Hospital of Jilin University, The First Hospital of Jilin University, Jilin University, Changchun, China; The Child Health Clinical Research Center of Jilin Province, Changchun, China
| | - Dan Li
- Department of Radiology, The First Hospital of Jilin University, Jilin University, Changchun, China
| | - Hong Yang
- Department of Pediatrics, Affiliated Hospital of Beihua University, Beihua University, Jilin, China
| | - Fei-Yong Jia
- Department of Developmental and Behavioral Pediatrics, Children's Hospital of the First Hospital of Jilin University, The First Hospital of Jilin University, Jilin University, Changchun, China; The Child Health Clinical Research Center of Jilin Province, Changchun, China.
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27
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Duque L, Ghafouri M, Nunez NA, Ospina JP, Philbrick KL, Port JD, Savica R, Prokop LJ, Rummans TA, Singh B. Functional neuroimaging in patients with catatonia: A systematic review. J Psychosom Res 2024; 179:111640. [PMID: 38484496 PMCID: PMC11006573 DOI: 10.1016/j.jpsychores.2024.111640] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/25/2023] [Revised: 03/02/2024] [Accepted: 03/05/2024] [Indexed: 04/12/2024]
Abstract
BACKGROUND Catatonia is a challenging and heterogeneous neuropsychiatric syndrome of motor, affective and behavioral dysregulation which has been associated with multiple disorders such as structural brain lesions, systemic diseases, and psychiatric disorders. This systematic review summarized and compared functional neuroimaging abnormalities in catatonia associated with psychiatric and medical conditions. METHODS Using PRISMA methods, we completed a systematic review of 6 databases from inception to February 7th, 2024 of patients with catatonia that had functional neuroimaging performed. RESULTS A total of 309 studies were identified through the systematic search and 62 met the criteria for full-text review. A total of 15 studies reported patients with catatonia associated with a psychiatric disorder (n = 241) and one study reported catatonia associated with another medical condition, involving patients with N-methyl-d-aspartate receptor antibody encephalitis (n = 23). Findings varied across disorders, with hyperactivity observed in areas like the prefrontal cortex (PFC), the supplementary motor area (SMA) and the ventral pre-motor cortex in acute catatonia associated to a psychiatric disorder, hypoactivity in PFC, the parietal cortex, and the SMA in catatonia associated to a medical condition, and mixed metabolic activity in the study on catatonia linked to a medical condition. CONCLUSION Findings support the theory of dysfunction in cortico-striatal-thalamic, cortico-cerebellar, anterior cingulate-medial orbitofrontal, and lateral orbitofrontal networks in catatonia. However, the majority of the literature focuses on schizophrenia spectrum disorders, leaving the pathophysiologic characteristics of catatonia in other disorders less understood. This review highlights the need for further research to elucidate the pathophysiology of catatonia across various disorders.
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Affiliation(s)
- Laura Duque
- Department of Psychiatry & Psychology, Mayo Clinic, Rochester, MN, USA; Department of Psychiatry, Brigham and Women's Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA.
| | - Mohammad Ghafouri
- Department of Psychiatry & Psychology, Mayo Clinic, Rochester, MN, USA
| | - Nicolas A Nunez
- Department of Psychiatry & Psychology, Mayo Clinic, Rochester, MN, USA; Department of Psychiatry, University of Utah, Salt Lake City, UT, USA
| | - Juan Pablo Ospina
- Harvard Medical School, Boston, MA, USA; Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | | | - John D Port
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | - Rodolfo Savica
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | | | - Teresa A Rummans
- Department of Psychiatry & Psychology, Mayo Clinic, Rochester, MN, USA; Department of Psychiatry, Mayo Clinic, Jacksonville, Florida
| | - Balwinder Singh
- Department of Psychiatry & Psychology, Mayo Clinic, Rochester, MN, USA
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Zou L, Herold F, Cheval B, Wheeler MJ, Pindus DM, Erickson KI, Raichlen DA, Alexander GE, Müller NG, Dunstan DW, Kramer AF, Hillman CH, Hallgren M, Ekelund U, Maltagliati S, Owen N. Sedentary behavior and lifespan brain health. Trends Cogn Sci 2024; 28:369-382. [PMID: 38431428 DOI: 10.1016/j.tics.2024.02.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Revised: 02/02/2024] [Accepted: 02/06/2024] [Indexed: 03/05/2024]
Abstract
Higher levels of physical activity are known to benefit aspects of brain health across the lifespan. However, the role of sedentary behavior (SB) is less well understood. In this review we summarize and discuss evidence on the role of SB on brain health (including cognitive performance, structural or functional brain measures, and dementia risk) for different age groups, critically compare assessment approaches to capture SB, and offer insights into emerging opportunities to assess SB via digital technologies. Across the lifespan, specific characteristics of SB (particularly whether they are cognitively active or cognitively passive) potentially act as moderators influencing the associations between SB and specific brain health outcomes. We outline challenges and opportunities for future research aiming to provide more robust empirical evidence on these observations.
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Affiliation(s)
- Liye Zou
- Body-Brain-Mind Laboratory, School of Psychology, Shenzhen University, Shenzhen, China.
| | - Fabian Herold
- Body-Brain-Mind Laboratory, School of Psychology, Shenzhen University, Shenzhen, China; Research Group Degenerative and Chronic Diseases, Movement, Faculty of Health Sciences Brandenburg, University of Potsdam, 14476 Potsdam, Germany
| | - Boris Cheval
- Department of Sport Sciences and Physical Education, Ecole Normale Supérieure Rennes, Bruz, France; Laboratory VIPS2, University of Rennes, Rennes, France
| | - Michael J Wheeler
- Physical Activity Laboratory, Baker Heart & Diabetes Institute, Melbourne, Victoria, Australia; Institute for Physical Activity and Nutrition (IPAN), School of Exercise and Nutrition Sciences, Deakin University, Geelong, Australia
| | - Dominika M Pindus
- Kinesiology and Community Health, University of Illinois at Chicago, Chicago, IL, USA; Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, USA; Neuroscience Program, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Kirk I Erickson
- AdventHealth Research Institute, Department of Neuroscience, AdventHealth, Orlando, FL, USA; Department of Psychology, University of Pittsburgh, Pittsburgh, PA, USA; Center for the Neural Basis of Cognition, University of Pittsburgh, Pittsburgh, PA, USA
| | - David A Raichlen
- Human and Evolutionary Biology Section, Department of Biological Sciences, University of Southern California, Los Angeles, CA 90089, USA; Department of Anthropology, University of Southern California, Los Angeles, CA 90089, USA
| | - Gene E Alexander
- BIO5 Institute, University of Arizona, Tucson, AZ 85721, USA; Department of Psychology, University of Arizona, Tucson, AZ 85721, USA; Evelyn F. McKnight Brain Institute, University of Arizona, Tucson, AZ 85721, USA; Department of Psychiatry, University of Arizona, Tucson, AZ 85721, USA; Neuroscience Graduate Interdisciplinary Program, University of Arizona, Tucson, AZ 85721, USA; Physiological Sciences Graduate Interdisciplinary Program, University of Arizona, Tucson, AZ85721, USA
| | - Notger G Müller
- Research Group Degenerative and Chronic Diseases, Movement, Faculty of Health Sciences Brandenburg, University of Potsdam, 14476 Potsdam, Germany
| | - David W Dunstan
- Physical Activity Laboratory, Baker Heart & Diabetes Institute, Melbourne, Victoria, Australia; Institute for Physical Activity and Nutrition (IPAN), School of Exercise and Nutrition Sciences, Deakin University, Geelong, Australia
| | - Arthur F Kramer
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, USA; Center for Cognitive and Brain Health, Northeastern University, Boston, MA, USA; Department of Psychology, Northeastern University, Boston, MA, 02115, USA
| | - Charles H Hillman
- Center for Cognitive and Brain Health, Northeastern University, Boston, MA, USA; Department of Psychology, Northeastern University, Boston, MA, 02115, USA; Department of Physical Therapy, Movement, & Rehabilitation Sciences, Northeastern University, Boston, MA, 02115, USA
| | - Mats Hallgren
- Epidemiology of Psychiatric Conditions, Substance Use and Social Environment (EPiCSS), Department of Public Health Sciences, Karolinska Institutet, Solna, Sweden
| | - Ulf Ekelund
- Department of Sports Medicine, Norwegian School of Sport Sciences, Oslo, Norway; Department of Chronic Diseases and Ageing, The Norwegian Institute for Public Health, Oslo, Norway
| | - Silvio Maltagliati
- Human and Evolutionary Biology Section, Department of Biological Sciences, University of Southern California, Los Angeles, CA 90089, USA
| | - Neville Owen
- Physical Activity Laboratory, Baker Heart & Diabetes Institute, Melbourne, Victoria, Australia; Centre for Urban Transitions, Swinburne University of Technology, Melbourne, Victoria, Australia
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Panagopoulos VN, Bailey A, Kostopoulos GK, Ioannides AA. Changes in distinct brain systems identified with fMRI during smoking cessation treatment with varenicline: a review. Psychopharmacology (Berl) 2024; 241:653-685. [PMID: 38430396 DOI: 10.1007/s00213-024-06556-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/23/2023] [Accepted: 02/15/2024] [Indexed: 03/03/2024]
Abstract
BACKGROUND Varenicline is considered one of the most effective treatment options for smoking cessation. Nonetheless, it is only modestly effective. A deeper comprehension of the effects of varenicline by means of the in-depth review of relevant fMRI studies may assist in paving the development of more targeted and effective treatments. METHODOLOGY A search of PubMed and Google Scholar databases was conducted with the keywords "functional magnetic resonance imaging" or "fMRI", and "varenicline". All peer-reviewed articles regarding the assessment of smokers with fMRI while undergoing treatment with varenicline and meeting the predefined criteria were included. RESULTS Several studies utilizing different methodologies and targeting different aspects of brain function were identified. During nicotine withdrawal, decreased mesocorticolimbic activity and increased amygdala activity, as well as elevated amygdala-insula and insula-default-mode-network functional connectivity are alleviated by varenicline under specific testing conditions. However, other nicotine withdrawal-induced changes, including the decreased reward responsivity of the ventral striatum, the bilateral dorsal striatum and the anterior cingulate cortex are not influenced by varenicline suggesting a task-dependent divergence in neurocircuitry activation. Under satiety, varenicline treatment is associated with diminished cue-induced activation of the ventral striatum and medial orbitofrontal cortex concomitant with reduced cravings; during the resting state, varenicline induces activation of the lateral orbitofrontal cortex and suppression of the right amygdala. CONCLUSIONS The current review provides important clues with regard to the neurobiological mechanism of action of varenicline and highlights promising research opportunities regarding the development of more selective and effective treatments and predictive biomarkers for treatment efficacy.
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Affiliation(s)
- Vassilis N Panagopoulos
- Laboratory for Human Brain Dynamics, AAI Scientific Cultural Services Ltd., Nicosia, Cyprus.
- Department of Physiology, Medical School, University of Patras, Patras, Greece.
| | - Alexis Bailey
- Pharmacology Section, St. George's University of London, London, UK
| | | | - Andreas A Ioannides
- Laboratory for Human Brain Dynamics, AAI Scientific Cultural Services Ltd., Nicosia, Cyprus
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Pilmeyer J, Lamerichs R, Ramsaransing F, Jansen JFA, Breeuwer M, Zinger S. Improved clinical outcome prediction in depression using neurodynamics in an emotional face-matching functional MRI task. Front Psychiatry 2024; 15:1255370. [PMID: 38585483 PMCID: PMC10996064 DOI: 10.3389/fpsyt.2024.1255370] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/08/2023] [Accepted: 03/06/2024] [Indexed: 04/09/2024] Open
Abstract
Introduction Approximately one in six people will experience an episode of major depressive disorder (MDD) in their lifetime. Effective treatment is hindered by subjective clinical decision-making and a lack of objective prognostic biomarkers. Functional MRI (fMRI) could provide such an objective measure but the majority of MDD studies has focused on static approaches, disregarding the rapidly changing nature of the brain. In this study, we aim to predict depression severity changes at 3 and 6 months using dynamic fMRI features. Methods For our research, we acquired a longitudinal dataset of 32 MDD patients with fMRI scans acquired at baseline and clinical follow-ups 3 and 6 months later. Several measures were derived from an emotion face-matching fMRI dataset: activity in brain regions, static and dynamic functional connectivity between functional brain networks (FBNs) and two measures from a wavelet coherence analysis approach. All fMRI features were evaluated independently, with and without demographic and clinical parameters. Patients were divided into two classes based on changes in depression severity at both follow-ups. Results The number of coherence clusters (nCC) between FBNs, reflecting the total number of interactions (either synchronous, anti-synchronous or causal), resulted in the highest predictive performance. The nCC-based classifier achieved 87.5% and 77.4% accuracy for the 3- and 6-months change in severity, respectively. Furthermore, regression analyses supported the potential of nCC for predicting depression severity on a continuous scale. The posterior default mode network (DMN), dorsal attention network (DAN) and two visual networks were the most important networks in the optimal nCC models. Reduced nCC was associated with a poorer depression course, suggesting deficits in sustained attention to and coping with emotion-related faces. An ensemble of classifiers with demographic, clinical and lead coherence features, a measure of dynamic causality, resulted in a 3-months clinical outcome prediction accuracy of 81.2%. Discussion The dynamic wavelet features demonstrated high accuracy in predicting individual depression severity change. Features describing brain dynamics could enhance understanding of depression and support clinical decision-making. Further studies are required to evaluate their robustness and replicability in larger cohorts.
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Affiliation(s)
- Jesper Pilmeyer
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, Netherlands
- Department of Research and Development, Epilepsy Centre Kempenhaeghe, Heeze, Netherlands
| | - Rolf Lamerichs
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, Netherlands
- Department of Research and Development, Epilepsy Centre Kempenhaeghe, Heeze, Netherlands
- Department of Medical Image Acquisitions, Philips Research, Eindhoven, Netherlands
| | - Faroeq Ramsaransing
- Department of Research and Development, Epilepsy Centre Kempenhaeghe, Heeze, Netherlands
- Department of Psychiatry, Amsterdam University Medical Center, Amsterdam, Netherlands
| | - Jacobus F. A. Jansen
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, Netherlands
- Department of Radiology and Nuclear Medicine, Maastricht University, Maastricht, Netherlands
- Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, Netherlands
| | - Marcel Breeuwer
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, Netherlands
- Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, Netherlands
- Department of Magnetic Resonance Research & Development - Clinical Science, Philips Healthcare, Best, Netherlands
| | - Svitlana Zinger
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, Netherlands
- Department of Research and Development, Epilepsy Centre Kempenhaeghe, Heeze, Netherlands
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Li X, Meng F, Huang W, Cui Y, Meng F, Wu S, Xu H. The Alterations in the Brain Corresponding to Low Back Pain: Recent Insights and Advances. Neural Plast 2024; 2024:5599046. [PMID: 38529366 PMCID: PMC10963108 DOI: 10.1155/2024/5599046] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Revised: 01/11/2024] [Accepted: 01/19/2024] [Indexed: 03/27/2024] Open
Abstract
Low back pain (LBP) is a leading cause of global disabilities. Numerous molecular, cellular, and anatomical factors are implicated in LBP. Current issues regarding neurologic alterations in LBP have focused on the reorganization of peripheral nerve and spinal cord, but neural mechanisms of exactly what LBP impacts on the brain required further researches. Based on existing clinical studies that chronic pain problems were accompanying alterations in brain structures and functions, researchers proposed logical conjectures that similar alterations occur in LBP patients as well. With recent extensive studies carried out using noninvasive neuroimaging technique, increasing number of abnormalities and alterations has been identified. Here, we reviewed brain alterations including white matters, grey matters, and neural circuits between brain areas, which are involved in chronic LBP. Moreover, brain structural and functional connectivity abnormalities are correlated to the happening and transition of LBP. The negative emotions related to back pain indicate possible alterations in emotional brain regions. Thus, the aim of this review is to summarize current findings on the alterations corresponding to LBP in the brain. It will not only further our understanding of etiology of LBP and understanding of negative emotions accompanying with back pain but also provide ideas and basis for new accesses to the diagnosis, treatment, and rehabilitation afterward based on integral medicine.
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Affiliation(s)
- Xuyang Li
- Department of Neurobiology and Collaborative Innovation Center for Brain Science, School of Basic Medicine, The Fourth Military Medical University, Xi'an, China
| | - Fancheng Meng
- Department of Neurobiology and Collaborative Innovation Center for Brain Science, School of Basic Medicine, The Fourth Military Medical University, Xi'an, China
| | - Wenye Huang
- Department of Neurobiology and Collaborative Innovation Center for Brain Science, School of Basic Medicine, The Fourth Military Medical University, Xi'an, China
- College of Life Sciences, Northwest University, Xi'an, China
| | - Yue Cui
- Department of Neurobiology and Collaborative Innovation Center for Brain Science, School of Basic Medicine, The Fourth Military Medical University, Xi'an, China
| | - Fanbo Meng
- Department of Neurobiology and Collaborative Innovation Center for Brain Science, School of Basic Medicine, The Fourth Military Medical University, Xi'an, China
| | - Shengxi Wu
- Department of Neurobiology and Collaborative Innovation Center for Brain Science, School of Basic Medicine, The Fourth Military Medical University, Xi'an, China
| | - Hui Xu
- Department of Neurobiology and Collaborative Innovation Center for Brain Science, School of Basic Medicine, The Fourth Military Medical University, Xi'an, China
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Tang QY, Zhong YL, Wang XM, Huang BL, Qin WG, Huang X. Machine Learning Analysis Classifies Patients with Primary Angle-Closure Glaucoma Using Abnormal Brain White Matter Function. Clin Ophthalmol 2024; 18:659-670. [PMID: 38468914 PMCID: PMC10926922 DOI: 10.2147/opth.s451872] [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: 11/26/2023] [Accepted: 02/05/2024] [Indexed: 03/13/2024] Open
Abstract
Objective Primary angle-closure glaucoma (PACG) is a globally prevalent, irreversible eye disease leading to blindness. Previous neuroimaging studies demonstrated that PACG patients were associated with gray matter function changes. However, whether the white matter(WM) function changes in PACG patients remains unknown. The purpose of the study is to investigate WM function changes in the PACG patients. Methods In total, 40 PACG patients and 40 well-matched HCs participated in our study and underwent resting-state functional magnetic resonance imaging (rs-fMRI) scans. We compared between-group differences between PACG patients and HC in the WM function using amplitude of low-frequency fluctuations (ALFF). In addition, the SVM method was applied to the construction of the PACG classification model. Results Compared with the HC group, ALFF was attenuated in right posterior thalamic radiation (include optic radiation), splenium of corpus callosum, and left tapetum in the PACG group, the results are statistically significant (GRF correction, voxel-level P < 0.001, cluster-level P < 0.05). Furthermore, the SVM classification had an accuracy of 80.0% and an area under the curve (AUC) of 0.86 for distinguishing patients with PACG from HC. Conclusion The findings of our study uncover abnormal WM functional alterations in PACG patients and mainly involves vision-related regions. These findings provide new insights into widespread brain damage in PACG from an alternative WM functional perspective.
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Affiliation(s)
- Qiu-Yu Tang
- College of Clinical Medicine, Jiangxi University of Chinese Medicine, Nanchang City, Jiangxi, 330004, People’s Republic of China
| | - Yu-Lin Zhong
- Department of Ophthalmology, Jiangxi Provincial People’s Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, Jiangxi, 330006, People’s Republic of China
| | - Xin-Miao Wang
- School of Ophthalmology and Optometry, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi, 330000, People’s Republic of China
| | - Bing-Lin Huang
- College of Clinical Medicine, Jiangxi University of Chinese Medicine, Nanchang City, Jiangxi, 330004, People’s Republic of China
| | - Wei-Guo Qin
- Department of Cardiothoracic Surgery, The 908th Hospital of Chinese People’s Liberation Army Joint Logistic Support Force’, Nanchang, People’s Republic of China
| | - Xin Huang
- Department of Ophthalmology, Jiangxi Provincial People’s Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, Jiangxi, 330006, People’s Republic of China
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Mohammadi S, Ghaderi S. Advanced magnetic resonance neuroimaging techniques: feasibility and applications in long or post-COVID-19 syndrome - a review. Ann Med Surg (Lond) 2024; 86:1584-1589. [PMID: 38463042 PMCID: PMC10923379 DOI: 10.1097/ms9.0000000000001808] [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: 11/16/2023] [Accepted: 01/29/2024] [Indexed: 03/12/2024] Open
Abstract
Long-term or post-COVID-19 syndrome (PCS) is a condition that affects people infected with SARS‑CoV‑2, the virus that causes COVID-19. PCS is characterized by a wide range of persistent or new symptoms that last months after the initial infection, such as fatigue, shortness of breath, cognitive dysfunction, and pain. Advanced magnetic resonance (MR) neuroimaging techniques can provide valuable information on the structural and functional changes in the brain associated with PCS as well as potential biomarkers for diagnosis and prognosis. In this review, we discuss the feasibility and applications of various advanced MR neuroimaging techniques in PCS, including perfusion-weighted imaging (PWI), diffusion-weighted imaging (DWI), susceptibility-weighted imaging (SWI), functional MR imaging (fMRI), diffusion tensor imaging (DTI), and tractography. We summarize the current evidence on neuroimaging findings in PCS, the challenges and limitations of these techniques, and the future directions for research and clinical practice. Although still uncertain, advanced MRI techniques show promise for gaining insight into the pathophysiology and guiding the management of COVID-19 syndrome, pending larger validation studies.
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Affiliation(s)
- Sana Mohammadi
- Department of Medical Sciences, School of Medicine, Iran University of Medical Sciences
| | - Sadegh Ghaderi
- Department of Neuroscience and Addiction Studies, School of Advanced Technologies in Medicine, Tehran University of Medical Sciences, Tehran, Iran
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Tamehisa T, Sato S, Sakai T, Maekawa R, Tanabe M, Ito K, Sugino N. Establishment of Noninvasive Prediction Models for the Diagnosis of Uterine Leiomyoma Subtypes. Obstet Gynecol 2024; 143:358-365. [PMID: 38061038 DOI: 10.1097/aog.0000000000005475] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2023] [Accepted: 10/31/2023] [Indexed: 02/17/2024]
Abstract
OBJECTIVE To establish prediction models for the diagnosis of the subtypes of uterine leiomyomas by machine learning using magnetic resonance imaging (MRI) data. METHODS This is a prospective observational study. Ninety uterine leiomyoma samples were obtained from 51 patients who underwent surgery for uterine leiomyomas. Seventy-one samples (49 mediator complex subunit 12 [ MED12 ] mutation-positive and 22 MED12 mutation-negative leiomyomas) were assigned to the primary data set to establish prediction models. Nineteen samples (13 MED12 mutation-positive and 6 MED12 mutation-negative leiomyomas) were assigned to the unknown testing data set to validate the prediction model utility. The tumor signal intensity was quantified by seven MRI sequences (T2-weighted imaging, apparent diffusion coefficient, magnetic resonance elastography, T1 mapping, magnetization transfer contrast, T2* blood oxygenation level dependent, and arterial spin labeling) that can estimate the collagen and water contents of uterine leiomyomas. After surgery, the MED12 mutations were genotyped. These results were used to establish prediction models based on machine learning by applying support vector classification and logistic regression for the diagnosis of uterine leiomyoma subtypes. The performance of the prediction models was evaluated by cross-validation within the primary data set and then finally evaluated by external validation using the unknown testing data set. RESULTS The signal intensities of five MRI sequences (T2-weighted imaging, apparent diffusion coefficient, T1 mapping, magnetization transfer contrast, and T2* blood oxygenation level dependent) differed significantly between the subtypes. In cross-validation within the primary data set, both machine learning models (support vector classification and logistic regression) based on the five MRI sequences were highly predictive of the subtypes (area under the curve [AUC] 0.974 and 0.988, respectively). External validation with the unknown testing data set confirmed that both models were able to predict the subtypes for all samples (AUC 1.000, 100.0% accuracy). Our prediction models with T2-weighted imaging alone also showed high accuracy to discriminate the uterine leiomyoma subtypes. CONCLUSION We established noninvasive prediction models for the diagnosis of the subtypes of uterine leiomyomas by machine learning using MRI data.
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Affiliation(s)
- Tetsuro Tamehisa
- Department of Obstetrics and Gynecology and the Department of Radiology, Yamaguchi University Graduate School of Medicine, Ube, Japan
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Ahmadi B, Duarte FCK, Srbely J, Bartlewski PM. Ultrasound-based assessment of the expression of inflammatory markers in the rectus femoris muscle of rats. Exp Biol Med (Maywood) 2024; 249:10064. [PMID: 38463389 PMCID: PMC10911122 DOI: 10.3389/ebm.2024.10064] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2023] [Accepted: 01/30/2024] [Indexed: 03/12/2024] Open
Abstract
Ultrasonographic characteristics of skeletal muscles are related to their health status and functional capacity, but they still provide limited information on muscle composition during the inflammatory process. It has been demonstrated that an alteration in muscle composition or structure can have disparate effects on different ranges of ultrasonogram pixel intensities. Therefore, monitoring specific clusters or bands of pixel intensity values could help detect echotextural changes in skeletal muscles associated with neurogenic inflammation. Here we compare two methods of ultrasonographic image analysis, namely, the echointensity (EI) segmentation approach (EI banding method) and detection of selective pixel intensity ranges correlated with the expression of inflammatory regulators using an in-house developed computer algorithm (r-Algo). This study utilized an experimental model of neurogenic inflammation in segmentally linked myotomes (i.e., rectus femoris (RF) muscle) of rats subjected to lumbar facet injury. Our results show that there were no significant differences in RF echotextural variables for different EI bands (with 50- or 25-pixel intervals) between surgery and sham-operated rats, and no significant correlations among individual EI band pixel characteristics and protein expression of inflammatory regulators studied. However, mean numerical pixel values for the pixel intensity ranges identified with the proprietary r-Algo computer program correlated with protein expression of ERK1/2 and substance P (both 86-101-pixel ranges) and CaMKII (86-103-pixel range) in RF, and were greater (p < 0.05) in surgery rats compared with their sham-operated counterparts. Our findings indicate that computer-aided identification of specific pixel intensity ranges was critical for ultrasonographic detection of changes in the expression of inflammatory mediators in neurosegmentally-linked skeletal muscles of rats after facet injury.
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Affiliation(s)
- Bahareh Ahmadi
- Department of Biomedical Sciences, Ontario Veterinary College, University of Guelph, Guelph, ON, Canada
| | - Felipe C. K. Duarte
- School of Health, Medical and Applied Sciences, Central Queensland University, Brisbane, QLD, Australia
| | - John Srbely
- Department of Human Health and Nutritional Sciences, College of Biological Sciences, University of Guelph, Guelph, ON, Canada
| | - Pawel M. Bartlewski
- Department of Biomedical Sciences, Ontario Veterinary College, University of Guelph, Guelph, ON, Canada
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Hung TH, Chen VCH, Chuang YC, Hsu YH, Wu WC, Tsai YH, McIntyre RS, Weng JC. Investigating the effect of hypertension on vascular cognitive impairment by using the resting-state functional connectome. Sci Rep 2024; 14:4580. [PMID: 38403657 PMCID: PMC10894879 DOI: 10.1038/s41598-024-54996-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2023] [Accepted: 02/19/2024] [Indexed: 02/27/2024] Open
Abstract
Hypertension (HTN) affects over 1.2 billion individuals worldwide and is defined as systolic blood pressure (BP) ≥ 140 mmHg and diastolic BP ≥ 90 mmHg. Hypertension is also considered a high risk factor for cerebrovascular diseases, which may lead to vascular cognitive impairment (VCI). VCI is associated with executive dysfunction and is also a transitional stage between hypertension and vascular dementia. Hence, it is essential to establish a reliable approach to diagnosing the severity of VCI. In 28 HTN (51-83 yrs; 18 males, 10 females) and 28 healthy controls (HC) (51-75 yrs; 7 males, 21 females), we investigated which regions demonstrate alterations in the resting-state functional connectome due to vascular cognitive impairment in HTN by using the amplitude of the low-frequency fluctuations (ALFF), regional homogeneity (ReHo), graph theoretical analysis (GTA), and network-based statistic (NBS) methods. In the group comparison between ALFF/ReHo, HTN showed reduced spontaneous activity in the regions corresponding to vascular or metabolic dysfunction and enhanced brain activity, mainly in the primary somatosensory cortex and prefrontal areas. We also observed cognitive dysfunction in HTN, such as executive function, processing speed, and memory. Both the GTA and NBS analyses indicated that the HTN demonstrated complex local segregation, worse global integration, and weak functional connectivity. Our findings show that resting-state functional connectivity was altered, particularly in the frontal and parietal regions, by hypertensive individuals with potential vascular cognitive impairment.
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Affiliation(s)
- Tai-Hsin Hung
- School of Medicine, Chang Gung University, Taoyuan, Taiwan
- Department of Psychiatry, Chang Gung Memorial Hospital, Chiayi, Taiwan
| | - Vincent Chin-Hung Chen
- School of Medicine, Chang Gung University, Taoyuan, Taiwan
- Department of Psychiatry, Chang Gung Memorial Hospital, Chiayi, Taiwan
| | - Yu-Chen Chuang
- Institute of Medical Device and Imaging, Graduate Institute of Clinical Medicine, National Taiwan University, Taipei, Taiwan
- Department of Medical Imaging, National Taiwan University Hospital, Taipei, Taiwan
| | - Yen-Hsuan Hsu
- Department of Psychology, National Chung Cheng University, Chiayi, Taiwan
| | - Wen-Chau Wu
- Institute of Medical Device and Imaging, Graduate Institute of Clinical Medicine, National Taiwan University, Taipei, Taiwan
- Department of Medical Imaging, National Taiwan University Hospital, Taipei, Taiwan
| | - Yuan-Hsiung Tsai
- School of Medicine, Chang Gung University, Taoyuan, Taiwan
- Department of Diagnostic Radiology, Chang Gung Memorial Hospital, Chiayi, Taiwan
| | - Roger S McIntyre
- Mood Disorder Psychopharmacology Unit, Department of Psychiatry, University Health Network, University of Toronto, Toronto, ON, Canada
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada
- Departments of Psychiatry and Pharmacology, University of Toronto, Toronto, ON, Canada
| | - Jun-Cheng Weng
- Department of Psychiatry, Chang Gung Memorial Hospital, Chiayi, Taiwan.
- Department of Medical Imaging and Radiological Sciences, Chang Gung University, No. 259, Wenhua 1st Rd., Guishan Dist., Taoyuan, 33302, Taiwan.
- Department of Artificial Intelligence, Chang Gung University, Taoyuan, Taiwan.
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Rai S, Graff K, Tansey R, Bray S. How do tasks impact the reliability of fMRI functional connectivity? Hum Brain Mapp 2024; 45:e26535. [PMID: 38348730 PMCID: PMC10884875 DOI: 10.1002/hbm.26535] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2023] [Revised: 10/13/2023] [Accepted: 11/01/2023] [Indexed: 02/24/2024] Open
Abstract
While there is growing interest in the use of functional magnetic resonance imaging-functional connectivity (fMRI-FC) for biomarker research, low measurement reliability of conventional acquisitions may limit applications. Factors known to impact FC reliability include scan length, head motion, signal properties, such as temporal signal-to-noise ratio (tSNR), and the acquisition state or task. As tasks impact signal in a region-wise fashion, they likely impact FC reliability differently across the brain, making task an important decision in study design. Here, we use the densely sampled Midnight Scan Club (MSC) dataset, comprising 5 h of rest and 6 h of task fMRI data in 10 healthy adults, to investigate regional effects of tasks on FC reliability. We further considered how BOLD signal properties contributing to tSNR, that is, temporal mean signal (tMean) and temporal standard deviation (tSD), vary across the brain, associate with FC reliability, and are modulated by tasks. We found that, relative to rest, tasks enhanced FC reliability and increased tSD for specific task-engaged regions. However, FC signal variability and reliability is broadly dampened during tasks outside task-engaged regions. From our analyses, we observed signal variability was the strongest driver of FC reliability. Overall, our findings suggest that the choice of task can have an important impact on reliability and should be considered in relation to maximizing reliability in networks of interest as part of study design.
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Affiliation(s)
- Shefali Rai
- Child and Adolescent Imaging Research ProgramUniversity of CalgaryCalgaryAlbertaCanada
- Alberta Children's Hospital Research InstituteUniversity of CalgaryCalgaryAlbertaCanada
- Hotchkiss Brain InstituteUniversity of CalgaryCalgaryAlbertaCanada
- Department of NeuroscienceUniversity of CalgaryCalgaryAlbertaCanada
| | - Kirk Graff
- Child and Adolescent Imaging Research ProgramUniversity of CalgaryCalgaryAlbertaCanada
- Alberta Children's Hospital Research InstituteUniversity of CalgaryCalgaryAlbertaCanada
- Hotchkiss Brain InstituteUniversity of CalgaryCalgaryAlbertaCanada
- Department of NeuroscienceUniversity of CalgaryCalgaryAlbertaCanada
| | - Ryann Tansey
- Child and Adolescent Imaging Research ProgramUniversity of CalgaryCalgaryAlbertaCanada
- Alberta Children's Hospital Research InstituteUniversity of CalgaryCalgaryAlbertaCanada
- Hotchkiss Brain InstituteUniversity of CalgaryCalgaryAlbertaCanada
- Department of NeuroscienceUniversity of CalgaryCalgaryAlbertaCanada
| | - Signe Bray
- Child and Adolescent Imaging Research ProgramUniversity of CalgaryCalgaryAlbertaCanada
- Alberta Children's Hospital Research InstituteUniversity of CalgaryCalgaryAlbertaCanada
- Hotchkiss Brain InstituteUniversity of CalgaryCalgaryAlbertaCanada
- Department of RadiologyUniversity of CalgaryCalgaryAlbertaCanada
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Wu YL, Christodoulou AG, Beumer JH, Rigatti LH, Fisher R, Ross M, Watkins S, Cortes DRE, Ruck C, Manzoor S, Wyman SK, Stapleton MC, Goetzman E, Bharathi S, Wipf P, Tan T, Eiseman JL, Christner SM, Guo J, Lo CWY, Epperly MW, Greenberger JS. Mitigation of Fetal Irradiation Injury from Mid-Gestation Total Body Radiation with Mitochondrial-Targeted GS-Nitroxide JP4-039. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.13.580105. [PMID: 38405696 PMCID: PMC10888932 DOI: 10.1101/2024.02.13.580105] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/27/2024]
Abstract
Victims of a radiation terrorist event will include pregnant women and unborn fetuses. Mitochondrial dysfunction and oxidative stress are key pathogenic factors of fetal irradiation injury. The goal of this preclinical study is to investigate the efficacy of mitigating fetal irradiation injury by maternal administration of the mitochondrial-targeted gramicidin S (GS)- nitroxide radiation mitigator, JP4-039. Pregnant female C57BL/6NTac mice received 3 Gy total body ionizing irradiation (TBI) at mid-gestation embryonic day 13.5 (E13.5). Using novel time- and-motion-resolved 4D in utero magnetic resonance imaging (4D-uMRI), we found TBI caused extensive injury to the fetal brain that included cerebral hemorrhage, loss of cerebral tissue, and hydrocephalus with excessive accumulation of cerebrospinal fluid (CSF). Histopathology of the fetal mouse brain showed broken cerebral vessels and elevated apoptosis. Further use of novel 4D Oxy-wavelet MRI capable of probing in vivo mitochondrial function in intact brain revealed significant reduction of mitochondrial function in the fetal brain after 3Gy TBI. This was validated by ex vivo Oroboros mitochondrial respirometry. Maternal administration JP4-039 one day after TBI (E14.5), which can pass through the placental barrier, significantly reduced fetal brain radiation injury and improved fetal brain mitochondrial respiration. This also preserved cerebral brain tissue integrity and reduced cerebral hemorrhage and cell death. As JP4-039 administration did not change litter sizes or fetus viability, together these findings indicate JP4-039 can be deployed as a safe and effective mitigator of fetal radiation injury from mid-gestational in utero ionizing radiation exposure. One Sentence Summary Mitochondrial-targeted gramicidin S (GS)-nitroxide JP4-039 is safe and effective radiation mitigator for mid-gestational fetal irradiation injury.
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Valaei A, Bamdad S, Golfam A, Golmohammadi G, Ameri H, Raoufy MR. Examining resting state functional connectivity and frequency power analysis in adults who stutter compared to adults who do not stutter. Front Hum Neurosci 2024; 18:1338966. [PMID: 38375364 PMCID: PMC10875099 DOI: 10.3389/fnhum.2024.1338966] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2023] [Accepted: 01/18/2024] [Indexed: 02/21/2024] Open
Abstract
Introduction Stuttering is a speech disorder characterized by impaired connections between brain regions involved in speech production. This study aimed to investigate functional connectivity and frequency power during rest in adults who stutter (AWS) compared to fluent adults (AWNS) in the dorsolateral prefrontal cortex (DLPFC), dorsolateral frontal cortex (DLFC), supplementary motor area (SMA), motor speech, angular gyrus (AG), and inferior temporal gyrus (ITG). Materials and methods Fifteen AWS (3 females, 12 males) and fifteen age- and sex-matched AWNS (3 females, 12 males) participated in this study. All participants were native Persian speakers. Stuttering severity in the AWS group was assessed using the Persian version of the Stuttering Severity Instrument Fourth Edition (SSI-4). Resting-state electroencephalography (EEG) was recorded for 5 min while participants sat comfortably with their eyes open. We analyzed frequency band power across various frequency bands and investigated functional connectivity within the specified speech region. Results Significant between-group differences were found in band powers including alpha, beta, delta, theta, and gamma, specifically in the premotor, SMA, motor speech, and frontal regions. AWS also showed increased coherence between the right motor speech region compared to controls. We demonstrate that the proposed hierarchical false discovery rate (FDR) method is the most effective for both simulations and experimental data. In the expected regions, this method revealed significant synchrony effects at an acceptable error rate of 5%. Conclusion The results highlight disrupted functional connectivity in AWS at resting state, particularly in speech-related and associated areas. Given the complex neurological basis of developmental stuttering, robust neural markers are closely linked to this phenomenon. These markers include imbalanced activity within brain regions associated with speech and motor functions, coupled with impaired functional connectivity between these regions. The cortico-basal ganglia-thalamo-cortical system governs the dynamic interplay between cortical regions, with SMA as a key cortical site. It is hypothesized that the aberrant resting state functional connectivity will impact the language planning and motor execution necessary for fluent speech. Examining resting-state metrics as biomarkers could further elucidate the neural underpinnings of stuttering and guide intervention.
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Affiliation(s)
- Atefeh Valaei
- Department of Linguistics, Tarbiat Modares University, Tehran, Iran
| | - Sobhan Bamdad
- Department of Biomedical Engineering, Faculty of Engineering, Shahed University, Tehran, Iran
| | - Arsalan Golfam
- Department of Linguistics, Tarbiat Modares University, Tehran, Iran
| | - Golnoosh Golmohammadi
- Department of Speech Therapy, School of Rehabilitation Sciences, Semnan University of Medical Sciences, Semnan, Iran
| | - Hayat Ameri
- Department of Linguistics, Tarbiat Modares University, Tehran, Iran
| | - Mohammad Reza Raoufy
- Department of Physiology, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran
- Institute for Brain Science and Cognition, Faculty of Medical Science, Tarbiat Modares University, Tehran, Iran
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Hu H, Lin X, Ye Z, Fang L, Gao H, Zhang Q. Application of functional near-infrared spectroscopy (fNIRS) in tinnitus research: contemporary insights and perspectives. Front Psychol 2024; 15:1334660. [PMID: 38371699 PMCID: PMC10870148 DOI: 10.3389/fpsyg.2024.1334660] [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: 11/07/2023] [Accepted: 01/22/2024] [Indexed: 02/20/2024] Open
Abstract
Tinnitus, characterized by phantom sound perception, is a highly disruptive condition lacking clearly effective treatments. Its complex neural mechanisms are not fully elucidated. Functional near-infrared spectroscopy (fNIRS) is a promising neuroimaging tool well-suited for assessing tinnitus due to its quietness, portability, and ability to directly measure cortical hemodynamic responses. This study timely summarizes the recent applications of fNIRS in investigating tinnitus pathology, correlating neuroimaging biomarkers with symptom severity, and evaluating treatment efficacy. Further studies with larger samples are warranted to reproduce existing findings. Thus, fNIRS appears to be a promising tool in tinnitus research. Addressing technical limitations, optimizing control groups, advancing data analysis, integrating standardized, and individualized experimental protocols can facilitate the extended and robust utilization of fNIRS in tinnitus research.
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Affiliation(s)
- Hantong Hu
- Department of Acupuncture and Moxibustion, The Third Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, China
- Department of Neurobiology and Acupuncture Research, Key Laboratory of Acupuncture and Neurology of Zhejiang Province, Zhejiang Chinese Medical University, Hangzhou, China
| | - Xiaoqi Lin
- The Third Clinical Medical College, Zhejiang Chinese Medical University, Hangzhou, China
| | - Ziyu Ye
- Clinical Medical College of Acupuncture, Moxibustion and Rehabilitation, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Lianqiang Fang
- Department of Acupuncture and Moxibustion, The Third Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, China
| | - Hong Gao
- Department of Acupuncture and Moxibustion, The Third Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, China
| | - Quanai Zhang
- Department of Acupuncture and Moxibustion, The Third Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, China
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Ashtiyani M, Moradi Birgani P, Soleimani M, Jameie SB, Shahrokhi A, Mirbagheri MM, Deevband MR. Corpus Callosum Functional Activities in Children with Cerebral Palsy. J Biomed Phys Eng 2024; 14:21-30. [PMID: 38357606 PMCID: PMC10862116 DOI: 10.31661/jbpe.v0i0.2106-1354] [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: 06/14/2021] [Accepted: 08/02/2021] [Indexed: 02/16/2024]
Abstract
Background Since cerebral palsy (CP) is a corollary to brain damage, persistent treatment should accompany an alteration in brain functional activity in line with clinical improvements. In this regard, the corpus callosum (CC), as a connecting bridge between the two hemispheres, plays an essential role. Objective This study aimed to investigate the therapeutic effects of occupational therapy (OT) on CC functional activity and walking capacity in children with cerebral palsy. Material and Methods In this clinical trial study, 4 children with CP (8.25±1.71 years) received 45 min OT sessions 3 times weekly for 8 weeks. Functional magnetic resonance imaging (fMRI) was acquired while conducting passive motor tasks to quantify CC activation. The pre-post activation changes in CC following therapy were quantified in terms of activated voxels. Walking capacity was evaluated using the timed-up-and-go (TUG), 6-minute walk test (6 MWT), and 10-meter walk test (10 MWT) in pre-and post-treatment. Results The number of activated voxels in CC indicated significant improvement in participants. Post-treatment activated voxels substantially exceeded pre-treatment active voxels. Clinical measures, including TUG, 6 MWT, and 10 MWT are improved by 11.9%, 12.6%, and 25.4%, respectively. Conclusion Passive task-based fMRI can detect the effects of OT on CC functional activity in children with CP. According to the results, OT improves CC functional activity in addition to gait and balance performance.
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Affiliation(s)
- Meghdad Ashtiyani
- Department of Biomedical Engineering and Medical Physics, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Parmida Moradi Birgani
- Department of Medical Physics and Biomedical Engineering, Faculty of Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - Maryam Soleimani
- Department of Basic Science, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran
| | | | - Amin Shahrokhi
- Department of Basic Science, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran
| | | | - Mohammad Reza Deevband
- Department of Biomedical Engineering and Medical Physics, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
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Ebersberger L, Kratzer FJ, Franke VL, Nagel AM, Niesporek SC, Korzowski A, Ladd ME, Schlemmer HP, Paech D, Platt T. First implementation of dynamic oxygen-17 ( 17O) magnetic resonance imaging at 7 Tesla during neuronal stimulation in the human brain. MAGMA (NEW YORK, N.Y.) 2024; 37:27-38. [PMID: 37737942 PMCID: PMC10876824 DOI: 10.1007/s10334-023-01119-6] [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] [Received: 03/28/2023] [Revised: 08/27/2023] [Accepted: 08/31/2023] [Indexed: 09/23/2023]
Abstract
OBJECTIVE First implementation of dynamic oxygen-17 (17O) MRI at 7 Tesla (T) during neuronal stimulation in the human brain. METHODS Five healthy volunteers underwent a three-phase 17O gas (17O2) inhalation experiment. Combined right-side visual stimulus and right-hand finger tapping were used to achieve neuronal stimulation in the left cerebral hemisphere. Data analysis included the evaluation of the relative partial volume (PV)-corrected time evolution of absolute 17O water (H217O) concentration and of the relative signal evolution without PV correction. Statistical analysis was performed using a one-tailed paired t test. Blood oxygen level-dependent (BOLD) experiments were performed to validate the stimulation paradigm. RESULTS The BOLD maps showed significant activity in the stimulated left visual and sensorimotor cortex compared to the non-stimulated right side. PV correction of 17O MR data resulted in high signal fluctuations with a noise level of 10% due to small regions of interest (ROI), impeding further quantitative analysis. Statistical evaluation of the relative H217O signal with PV correction (p = 0.168) and without (p = 0.382) did not show significant difference between the stimulated left and non-stimulated right sensorimotor ROI. DISCUSSION The change of cerebral oxygen metabolism induced by sensorimotor and visual stimulation is not large enough to be reliably detected with the current setup and methodology of dynamic 17O MRI at 7 T.
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Affiliation(s)
- Louise Ebersberger
- German Cancer Research Center (DKFZ) Heidelberg, Division of Radiology, Heidelberg, Germany
- Faculty of Medicine, Ruprecht-Karls University Heidelberg, Heidelberg, Germany
- Department of Pediatrics, Bern University Hospital, Bern, Switzerland
| | - Fabian J Kratzer
- German Cancer Research Center (DKFZ) Heidelberg, Division of Medical Physics in Radiology, Heidelberg, Germany
| | - Vanessa L Franke
- German Cancer Research Center (DKFZ) Heidelberg, Division of Medical Physics in Radiology, Heidelberg, Germany
- Faculty of Physics and Astronomy, Ruprecht-Karls University Heidelberg, Heidelberg, Germany
| | - Armin M Nagel
- German Cancer Research Center (DKFZ) Heidelberg, Division of Medical Physics in Radiology, Heidelberg, Germany
- Institute of Radiology, Friedrich-Alexander University Hospital Erlangen-Nürnberg (FAU), University Hospital Erlangen, Erlangen, Germany
| | - Sebastian C Niesporek
- German Cancer Research Center (DKFZ) Heidelberg, Division of Medical Physics in Radiology, Heidelberg, Germany
| | - Andreas Korzowski
- German Cancer Research Center (DKFZ) Heidelberg, Division of Medical Physics in Radiology, Heidelberg, Germany
| | - Mark E Ladd
- Faculty of Medicine, Ruprecht-Karls University Heidelberg, Heidelberg, Germany
- German Cancer Research Center (DKFZ) Heidelberg, Division of Medical Physics in Radiology, Heidelberg, Germany
- Faculty of Physics and Astronomy, Ruprecht-Karls University Heidelberg, Heidelberg, Germany
| | - Heinz-Peter Schlemmer
- German Cancer Research Center (DKFZ) Heidelberg, Division of Radiology, Heidelberg, Germany
| | - Daniel Paech
- German Cancer Research Center (DKFZ) Heidelberg, Division of Radiology, Heidelberg, Germany
- Department of Neuroradiology, University Hospital Bonn, Bonn, Germany
| | - Tanja Platt
- German Cancer Research Center (DKFZ) Heidelberg, Division of Medical Physics in Radiology, Heidelberg, Germany.
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Foster SL, Breukelaar IA, Ekanayake K, Lewis S, Korgaonkar MS. Functional Magnetic Resonance Imaging of the Amygdala and Subregions at 3 Tesla: A Scoping Review. J Magn Reson Imaging 2024; 59:361-375. [PMID: 37352130 DOI: 10.1002/jmri.28836] [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: 03/05/2023] [Revised: 05/18/2023] [Accepted: 05/18/2023] [Indexed: 06/25/2023] Open
Abstract
The amygdalae are a pair of small brain structures, each of which is composed of three main subregions and whose function is implicated in neuropsychiatric conditions. Functional Magnetic Resonance Imaging (fMRI) has been utilized extensively in investigation of amygdala activation and functional connectivity (FC) with most clinical research sites now utilizing 3 Tesla (3T) MR systems. However, accurate imaging and analysis remains challenging not just due to the small size of the amygdala, but also its location deep in the temporal lobe. Selection of imaging parameters can significantly impact data quality with implications for the accuracy of study results and validity of conclusions. Wide variation exists in acquisition protocols with spatial resolution of some protocols suboptimal for accurate assessment of the amygdala as a whole, and for measuring activation and FC of the three main subregions, each of which contains multiple nuclei with specialized roles. The primary objective of this scoping review is to provide a broad overview of 3T fMRI protocols in use to image the activation and FC of the amygdala with particular reference to spatial resolution. The secondary objective is to provide context for a discussion culminating in recommendations for a standardized protocol for imaging activation of the amygdala and its subregions. As the advantages of big data and protocol harmonization in imaging become more apparent so, too, do the disadvantages of data heterogeneity. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Sheryl L Foster
- Sydney School of Health Sciences, Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia
- Department of Radiology, Westmead Hospital, Westmead, New South Wales, Australia
| | - Isabella A Breukelaar
- Brain Dynamics Centre, The Westmead Institute for Medical Research, Westmead, New South Wales, Australia
| | - Kanchana Ekanayake
- University Library, The University of Sydney, Sydney, New South Wales, Australia
| | - Sarah Lewis
- Sydney School of Health Sciences, Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia
| | - Mayuresh S Korgaonkar
- Brain Dynamics Centre, The Westmead Institute for Medical Research, Westmead, New South Wales, Australia
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Ruch F, Gnörich J, Wind K, Köhler M, Zatcepin A, Wiedemann T, Gildehaus FJ, Lindner S, Boening G, von Ungern-Sternberg B, Beyer L, Herms J, Bartenstein P, Brendel M, Eckenweber F. Validity and value of metabolic connectivity in mouse models of β-amyloid and tauopathy. Neuroimage 2024; 286:120513. [PMID: 38191101 DOI: 10.1016/j.neuroimage.2024.120513] [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: 04/14/2023] [Revised: 08/25/2023] [Accepted: 01/05/2024] [Indexed: 01/10/2024] Open
Abstract
Among functional imaging methods, metabolic connectivity (MC) is increasingly used for investigation of regional network changes to examine the pathophysiology of neurodegenerative diseases such as Alzheimer's disease (AD) or movement disorders. Hitherto, MC was mostly used in clinical studies, but only a few studies demonstrated the usefulness of MC in the rodent brain. The goal of the current work was to analyze and validate metabolic regional network alterations in three different mouse models of neurodegenerative diseases (β-amyloid and tau) by use of 2-deoxy-2-[18F]fluoro-d-glucose positron emission tomography (FDG-PET) imaging. We compared the results of FDG-µPET MC with conventional VOI-based analysis and behavioral assessment in the Morris water maze (MWM). The impact of awake versus anesthesia conditions on MC read-outs was studied and the robustness of MC data deriving from different scanners was tested. MC proved to be an accurate and robust indicator of functional connectivity loss when sample sizes ≥12 were considered. MC readouts were robust across scanners and in awake/ anesthesia conditions. MC loss was observed throughout all brain regions in tauopathy mice, whereas β-amyloid indicated MC loss mainly in spatial learning areas and subcortical networks. This study established a methodological basis for the utilization of MC in different β-amyloid and tau mouse models. MC has the potential to serve as a read-out of pathological changes within neuronal networks in these models.
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Affiliation(s)
- François Ruch
- Department of Nuclear Medicine, University Hospital of Munich, LMU Munich, Munich, Germany
| | - Johannes Gnörich
- Department of Nuclear Medicine, University Hospital of Munich, LMU Munich, Munich, Germany; German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
| | - Karin Wind
- Department of Nuclear Medicine, University Hospital of Munich, LMU Munich, Munich, Germany; German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
| | - Mara Köhler
- Department of Nuclear Medicine, University Hospital of Munich, LMU Munich, Munich, Germany
| | - Artem Zatcepin
- Department of Nuclear Medicine, University Hospital of Munich, LMU Munich, Munich, Germany; German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
| | - Thomas Wiedemann
- Department of Nuclear Medicine, University Hospital of Munich, LMU Munich, Munich, Germany
| | - Franz-Joseph Gildehaus
- Department of Nuclear Medicine, University Hospital of Munich, LMU Munich, Munich, Germany
| | - Simon Lindner
- Department of Nuclear Medicine, University Hospital of Munich, LMU Munich, Munich, Germany
| | - Guido Boening
- Department of Nuclear Medicine, University Hospital of Munich, LMU Munich, Munich, Germany
| | | | - Leonie Beyer
- Department of Nuclear Medicine, University Hospital of Munich, LMU Munich, Munich, Germany
| | - Jochen Herms
- German Center for Neurodegenerative Diseases (DZNE), Munich, Germany; Munich Cluster for Systems Neurology (SyNergy), Munich, Germany; Center of Neuropathology and Prion Research, University of Munich, Munich, Germany
| | - Peter Bartenstein
- Department of Nuclear Medicine, University Hospital of Munich, LMU Munich, Munich, Germany; German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
| | - Matthias Brendel
- Department of Nuclear Medicine, University Hospital of Munich, LMU Munich, Munich, Germany; German Center for Neurodegenerative Diseases (DZNE), Munich, Germany; Munich Cluster for Systems Neurology (SyNergy), Munich, Germany.
| | - Florian Eckenweber
- Department of Nuclear Medicine, University Hospital of Munich, LMU Munich, Munich, Germany
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Rykov YG, Patterson MD, Gangwar BA, Jabar SB, Leonardo J, Ng KP, Kandiah N. Predicting cognitive scores from wearable-based digital physiological features using machine learning: data from a clinical trial in mild cognitive impairment. BMC Med 2024; 22:36. [PMID: 38273340 PMCID: PMC10809621 DOI: 10.1186/s12916-024-03252-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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Accepted: 01/09/2024] [Indexed: 01/27/2024] Open
Abstract
BACKGROUND Continuous assessment and remote monitoring of cognitive function in individuals with mild cognitive impairment (MCI) enables tracking therapeutic effects and modifying treatment to achieve better clinical outcomes. While standardized neuropsychological tests are inconvenient for this purpose, wearable sensor technology collecting physiological and behavioral data looks promising to provide proxy measures of cognitive function. The objective of this study was to evaluate the predictive ability of digital physiological features, based on sensor data from wrist-worn wearables, in determining neuropsychological test scores in individuals with MCI. METHODS We used the dataset collected from a 10-week single-arm clinical trial in older adults (50-70 years old) diagnosed with amnestic MCI (N = 30) who received a digitally delivered multidomain therapeutic intervention. Cognitive performance was assessed before and after the intervention using the Neuropsychological Test Battery (NTB) from which composite scores were calculated (executive function, processing speed, immediate memory, delayed memory and global cognition). The Empatica E4, a wrist-wearable medical-grade device, was used to collect physiological data including blood volume pulse, electrodermal activity, and skin temperature. We processed sensors' data and extracted a range of physiological features. We used interpolated NTB scores for 10-day intervals to test predictability of scores over short periods and to leverage the maximum of wearable data available. In addition, we used individually centered data which represents deviations from personal baselines. Supervised machine learning was used to train models predicting NTB scores from digital physiological features and demographics. Performance was evaluated using "leave-one-subject-out" and "leave-one-interval-out" cross-validation. RESULTS The final sample included 96 aggregated data intervals from 17 individuals. In total, 106 digital physiological features were extracted. We found that physiological features, especially measures of heart rate variability, correlated most strongly to the executive function compared to other cognitive composites. The model predicted the actual executive function scores with correlation r = 0.69 and intra-individual changes in executive function scores with r = 0.61. CONCLUSIONS Our findings demonstrated that wearable-based physiological measures, primarily HRV, have potential to be used for the continuous assessments of cognitive function in individuals with MCI.
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Affiliation(s)
| | | | | | | | - Jacklyn Leonardo
- Dementia Research Centre, Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
| | - Kok Pin Ng
- Department of Neurology, National Neuroscience Institute, Singapore, Singapore
- Duke-NUS Medical School, Singapore, Singapore
| | - Nagaendran Kandiah
- Dementia Research Centre, Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
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Yang L, He P, Zhang L, Li K. Altered resting-state brain functional activities and networks in Crohn's disease: a systematic review. Front Neurosci 2024; 18:1319359. [PMID: 38332859 PMCID: PMC10851432 DOI: 10.3389/fnins.2024.1319359] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2023] [Accepted: 01/10/2024] [Indexed: 02/10/2024] Open
Abstract
Background Crohn's disease (CD) is a non-specific chronic inflammatory disease of the gastrointestinal tract and is a phenotype of inflammatory bowel disease (IBD). The current study sought to compile the resting-state functional differences in the brain between CD patients and healthy controls. Methods The online databases PubMed, Web of Science Core, and EMBASE were used to find the published neuroimage studies. The search period was from the beginning through December 15, 2023. The predetermined inclusion and exclusion criteria allowed for the identification of the studies. The studies were assembled by two impartial reviewers, who also assessed their quality and bias. Results This review comprised 16 resting-state fMRI studies in total. The included studies generally had modest levels of bias. According to the research, emotional processing and pain processing were largely linked to increased or decreased brain activity in patients with CD. The DMN, CEN, and limbic systems may have abnormalities in patients with CD, according to research on brain networks. Several brain regions showed functional changes in the active CD group compared to the inactive CD group and the healthy control group, respectively. The abnormalities in brain areas were linked to changes in mood fluctuations (anxiety, melancholy) in patients with CD. Conclusion Functional neuroimaging helps provide a better understanding of the underlying neuropathological processes in patients with CD. In this review, we summarize as follows: First, these findings indicate alterations in brain function in patients with CD, specifically affecting brain regions associated with pain, emotion, cognition, and visceral sensation; second, disease activity may have an impact on brain functions in patients with CD; and third, psychological factors may be associated with altered brain functions in patients with CD.
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Affiliation(s)
- Ling Yang
- Radiology Department, Chongqing General Hospital, Chongqing, China
- Department of Radiology Children’s Hospital of Chongqing Medical University, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing, China
| | - Peipei He
- Radiology Department, Chongqing General Hospital, Chongqing, China
| | - Lingqin Zhang
- Radiology Department, Chongqing General Hospital, Chongqing, China
| | - Kang Li
- Radiology Department, Chongqing General Hospital, Chongqing, China
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Schulz MA, Bzdok D, Haufe S, Haynes JD, Ritter K. Performance reserves in brain-imaging-based phenotype prediction. Cell Rep 2024; 43:113597. [PMID: 38159275 PMCID: PMC11215805 DOI: 10.1016/j.celrep.2023.113597] [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: 11/24/2022] [Revised: 07/03/2023] [Accepted: 12/04/2023] [Indexed: 01/03/2024] Open
Abstract
This study examines the impact of sample size on predicting cognitive and mental health phenotypes from brain imaging via machine learning. Our analysis shows a 3- to 9-fold improvement in prediction performance when sample size increases from 1,000 to 1 M participants. However, despite this increase, the data suggest that prediction accuracy remains worryingly low and far from fully exploiting the predictive potential of brain imaging data. Additionally, we find that integrating multiple imaging modalities boosts prediction accuracy, often equivalent to doubling the sample size. Interestingly, the most informative imaging modality often varied with increasing sample size, emphasizing the need to consider multiple modalities. Despite significant performance reserves for phenotype prediction, achieving substantial improvements may necessitate prohibitively large sample sizes, thus casting doubt on the practical or clinical utility of machine learning in some areas of neuroimaging.
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Affiliation(s)
- Marc-Andre Schulz
- Charité - Universitätsmedizin Berlin (corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health), Department of Psychiatry and Psychotherapy, Berlin, Germany; Bernstein Center for Computational Neuroscience, Berlin, Germany.
| | - Danilo Bzdok
- McConnell Brain Imaging Centre (BIC), Montreal Neurological Institute (MNI), Faculty of Medicine, McGill University, Montreal, QC, Canada; Department of Biomedical Engineering, Faculty of Medicine, McGill University, Montreal, QC, Canada; Mila - Quebec Artificial Intelligence Institute, Montreal, QC, Canada
| | - Stefan Haufe
- Bernstein Center for Computational Neuroscience, Berlin, Germany; Technische Universität Berlin, Berlin, Germany; Physikalisch-Technische Bundesanstalt, Berlin, Germany; Charité - Universitätsmedizin Berlin (corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health), Department of Neurology, Berlin Center for Advanced Neuroimaging, Berlin, Germany
| | - John-Dylan Haynes
- Bernstein Center for Computational Neuroscience, Berlin, Germany; Charité - Universitätsmedizin Berlin (corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health), Department of Neurology, Berlin Center for Advanced Neuroimaging, Berlin, Germany
| | - Kerstin Ritter
- Charité - Universitätsmedizin Berlin (corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health), Department of Psychiatry and Psychotherapy, Berlin, Germany; Bernstein Center for Computational Neuroscience, Berlin, Germany
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Singh RK, Nayak NP, Behl T, Arora R, Anwer MK, Gulati M, Bungau SG, Brisc MC. Exploring the Intersection of Geophysics and Diagnostic Imaging in the Health Sciences. Diagnostics (Basel) 2024; 14:139. [PMID: 38248016 PMCID: PMC11154438 DOI: 10.3390/diagnostics14020139] [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: 11/10/2023] [Revised: 01/03/2024] [Accepted: 01/05/2024] [Indexed: 01/23/2024] Open
Abstract
To develop diagnostic imaging approaches, this paper emphasizes the transformational potential of merging geophysics with health sciences. Diagnostic imaging technology improvements have transformed the health sciences by enabling earlier and more precise disease identification, individualized therapy, and improved patient care. This review article examines the connection between geophysics and diagnostic imaging in the field of health sciences. Geophysics, which is typically used to explore Earth's subsurface, has provided new uses of its methodology in the medical field, providing innovative solutions to pressing medical problems. The article examines the different geophysical techniques like electrical imaging, seismic imaging, and geophysics and their corresponding imaging techniques used in health sciences like tomography, magnetic resonance imaging, ultrasound imaging, etc. The examination includes the description, similarities, differences, and challenges associated with these techniques and how modified geophysical techniques can be used in imaging methods in health sciences. Examining the progression of each method from geophysics to medical imaging and its contributions to illness diagnosis, treatment planning, and monitoring are highlighted. Also, the utilization of geophysical data analysis techniques like signal processing and inversion techniques in image processing in health sciences has been briefly explained, along with different mathematical and computational tools in geophysics and how they can be implemented for image processing in health sciences. The key findings include the development of machine learning and artificial intelligence in geophysics-driven medical imaging, demonstrating the revolutionary effects of data-driven methods on precision, speed, and predictive modeling.
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Affiliation(s)
- Rahul Kumar Singh
- Energy Cluster, University of Petroleum and Energy Studies, Dehradun 248007, Uttarakhand, India; (R.K.S.); (N.P.N.)
| | - Nirlipta Priyadarshini Nayak
- Energy Cluster, University of Petroleum and Energy Studies, Dehradun 248007, Uttarakhand, India; (R.K.S.); (N.P.N.)
| | - Tapan Behl
- Amity School of Pharmaceutical Sciences, Amity University, Mohali 140306, Punjab, India
| | - Rashmi Arora
- Chitkara College of Pharmacy, Chitkara University, Rajpura 140401, Punjab, India;
| | - Md. Khalid Anwer
- Department of Pharmaceutics, College of Pharmacy, Prince Sattam Bin Abdulaziz University, Alkharj 11942, Saudi Arabia;
| | - Monica Gulati
- School of Pharmaceutical Sciences, Lovely Professional University, Phagwara 1444411, Punjab, India;
- Australian Research Centre in Complementary and Integrative Medicine, Faculty of Health, University of Technology Sydney, Ultimo, NSW 20227, Australia
| | - Simona Gabriela Bungau
- Department of Pharmacy, Faculty of Medicine and Pharmacy, University of Oradea, 410028 Oradea, Romania
- Doctoral School of Biological and Biomedical Sciences, University of Oradea, 410087 Oradea, Romania
| | - Mihaela Cristina Brisc
- Department of Medical Disciplines, Faculty of Medicine and Pharmacy, University of Oradea, 410073 Oradea, Romania;
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Li X, Naveed Iqbal Qureshi M, Laplante DP, Elgbeili G, Paquin V, Lee Jones S, King S, Rosa-Neto P. Decreased amygdala-sensorimotor connectivity mediates the association between prenatal stress and broad autism phenotype in young adults: Project Ice Storm. Stress 2024; 27:2293698. [PMID: 38131654 DOI: 10.1080/10253890.2023.2293698] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Accepted: 12/04/2023] [Indexed: 12/23/2023] Open
Abstract
Studies show that prenatal maternal stress (PNMS) is related to risk for child autism, and to atypical amygdala functional connectivity in the autistic child. Yet, it remains unclear whether amygdala functional connectivity mediates the association between PNMS and autistic traits, particularly in young adult offspring. We recruited women who were pregnant during, or within 3 months of, the 1998 Quebec ice storm crisis, and assessed three aspects of PNMS: objective hardship (events experienced during the ice storm), subjective distress (post-traumatic stress symptoms experienced as a result of the ice storm) and cognitive appraisal. At age 19, 32 young adults (21 females) self-reported their autistic-like traits (i.e., aloof personality, pragmatic language impairment and rigid personality), and underwent structural MRI and resting-state functional MRI scans. Seed-to-voxel analyses were conducted to map the amygdala functional connectivity network. Mediation analyses were implemented with bootstrapping of 20,000 resamplings. We found that greater maternal objective hardship was associated with weaker functional connectivity between the left amygdala and the right postcentral gyrus, which was then associated with more pragmatic language impairment. Greater maternal subjective distress was associated with weaker functional connectivity between the right amygdala and the left precentral gyrus, which was then associated with more aloof personality. Our results demonstrate that the long-lasting effect of PNMS on offspring autistic-like traits may be mediated by decreased amygdala-sensorimotor circuits. The differences between amygdala-sensory and amygdala-motor pathways mediating different aspects of PNMS on different autism phenotypes need to be studied further.
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Affiliation(s)
- Xinyuan Li
- Integrated Program in Neuroscience, McGill University, Montreal, Canada
- Douglas Mental Health University Institute, Montreal, Canada
- Montreal Neurological Institute, Montreal, Canada
| | - Muhammad Naveed Iqbal Qureshi
- Douglas Mental Health University Institute, Montreal, Canada
- Montreal Neurological Institute, Montreal, Canada
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Montreal, Canada
| | - David P Laplante
- Centre for Child Development and Mental Health, Lady Davis Institute-Jewish General Hospital, Montreal, Canada
| | | | - Vincent Paquin
- Douglas Mental Health University Institute, Montreal, Canada
- Department of Psychiatry, McGill University, Montreal, Canada
| | - Sherri Lee Jones
- Douglas Mental Health University Institute, Montreal, Canada
- Department of Psychiatry, McGill University, Montreal, Canada
| | - Suzanne King
- Integrated Program in Neuroscience, McGill University, Montreal, Canada
- Douglas Mental Health University Institute, Montreal, Canada
- Department of Psychiatry, McGill University, Montreal, Canada
| | - Pedro Rosa-Neto
- Integrated Program in Neuroscience, McGill University, Montreal, Canada
- Douglas Mental Health University Institute, Montreal, Canada
- Montreal Neurological Institute, Montreal, Canada
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Montreal, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal, Canada
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Etekochay MO, Amaravadhi AR, González GV, Atanasov AG, Matin M, Mofatteh M, Steinbusch HW, Tesfaye T, Praticò D. Unveiling New Strategies Facilitating the Implementation of Artificial Intelligence in Neuroimaging for the Early Detection of Alzheimer's Disease. J Alzheimers Dis 2024; 99:1-20. [PMID: 38640152 DOI: 10.3233/jad-231135] [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] [Indexed: 04/21/2024]
Abstract
Alzheimer's disease (AD) is a chronic neurodegenerative disorder with a global impact. The past few decades have witnessed significant strides in comprehending the underlying pathophysiological mechanisms and developing diagnostic methodologies for AD, such as neuroimaging approaches. Neuroimaging techniques, including positron emission tomography and magnetic resonance imaging, have revolutionized the field by providing valuable insights into the structural and functional alterations in the brains of individuals with AD. These imaging modalities enable the detection of early biomarkers such as amyloid-β plaques and tau protein tangles, facilitating early and precise diagnosis. Furthermore, the emerging technologies encompassing blood-based biomarkers and neurochemical profiling exhibit promising results in the identification of specific molecular signatures for AD. The integration of machine learning algorithms and artificial intelligence has enhanced the predictive capacity of these diagnostic tools when analyzing complex datasets. In this review article, we will highlight not only some of the most used diagnostic imaging approaches in neurodegeneration research but focus much more on new tools like artificial intelligence, emphasizing their application in the realm of AD. These advancements hold immense potential for early detection and intervention, thereby paving the way for personalized therapeutic strategies and ultimately augmenting the quality of life for individuals affected by AD.
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Affiliation(s)
| | - Amoolya Rao Amaravadhi
- Internal Medicine, Malla Reddy Institute of Medical Sciences, Jeedimetla, Hyderabad, India
| | - Gabriel Villarrubia González
- Expert Systems and Applications Laboratory (ESALAB), Faculty of Science, University of Salamanca, Salamanca, Spain
| | - Atanas G Atanasov
- Department of Biotechnology and Nutrigenomics, Institute of Genetics and Animal Biotechnology of the Polish Academy of Sciences, Jastrzebiec, Poland
- Ludwig Boltzmann Institute Digital Health and Patient Safety, Medical University of Vienna, Vienna, Austria
| | - Maima Matin
- Ludwig Boltzmann Institute Digital Health and Patient Safety, Medical University of Vienna, Vienna, Austria
| | - Mohammad Mofatteh
- School of Medicine, Dentistry, and Biomedical Sciences, Queen's University Belfast, Belfast, UK
| | - Harry Wilhelm Steinbusch
- Department of Cellular and Translational Neuroscience, School for Mental Health and Neuroscience, Faculty of Health Medicine and Life Sciences, Maastricht University, Netherlands
| | - Tadele Tesfaye
- CareHealth Medical Practice, Jimma Road, Addis Ababa, Ethiopia
| | - Domenico Praticò
- Alzheimer's Center at Temple, Lewis Katz School of Medicine, Temple University, Philadelphia, PA, USA
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