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Panikratova YR, Tomyshev AS, Abdullina EG, Rodionov GI, Arkhipov AY, Tikhonov DV, Bozhko OV, Kaleda VG, Strelets VB, Lebedeva IS. Resting-state functional connectivity correlates of brain structural aging in schizophrenia. Eur Arch Psychiatry Clin Neurosci 2024:10.1007/s00406-024-01837-5. [PMID: 38914851 DOI: 10.1007/s00406-024-01837-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/07/2023] [Accepted: 05/27/2024] [Indexed: 06/26/2024]
Abstract
A large body of research has shown that schizophrenia patients demonstrate increased brain structural aging. Although this process may be coupled with aberrant changes in intrinsic functional architecture of the brain, they remain understudied. We hypothesized that there are brain regions whose whole-brain functional connectivity at rest is differently associated with brain structural aging in schizophrenia patients compared to healthy controls. Eighty-four male schizophrenia patients and eighty-six male healthy controls underwent structural MRI and resting-state fMRI. The brain-predicted age difference (b-PAD) was a measure of brain structural aging. Resting-state fMRI was applied to obtain global correlation (GCOR) maps comprising voxelwise values of the strength and sign of functional connectivity of a given voxel with the rest of the brain. Schizophrenia patients had higher b-PAD compared to controls (mean between-group difference + 2.9 years). Greater b-PAD in schizophrenia patients, compared to controls, was associated with lower whole-brain functional connectivity of a region in frontal orbital cortex, inferior frontal gyrus, Heschl's Gyrus, plana temporale and polare, insula, and opercular cortices of the right hemisphere (rFTI). According to post hoc seed-based correlation analysis, decrease of functional connectivity with the posterior cingulate gyrus, left superior temporal cortices, as well as right angular gyrus/superior lateral occipital cortex has mainly driven the results. Lower functional connectivity of the rFTI was related to worse verbal working memory and language production. Our findings demonstrate that well-established frontotemporal functional abnormalities in schizophrenia are related to increased brain structural aging.
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Affiliation(s)
| | | | | | - Georgiy I Rodionov
- Institute of Higher Nervous Activity and Neurophysiology of Russian Academy of Sciences, Moscow, Russia
| | - Andrey Yu Arkhipov
- Institute of Higher Nervous Activity and Neurophysiology of Russian Academy of Sciences, Moscow, Russia
| | | | | | | | - Valeria B Strelets
- Institute of Higher Nervous Activity and Neurophysiology of Russian Academy of Sciences, Moscow, Russia
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2
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Aghamohammadi-Sereshki A, Pietrasik W, Malykhin NV. Aging, cingulate cortex, and cognition: insights from structural MRI, emotional recognition, and theory of mind. Brain Struct Funct 2024:10.1007/s00429-023-02753-5. [PMID: 38305874 DOI: 10.1007/s00429-023-02753-5] [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: 06/23/2023] [Accepted: 12/12/2023] [Indexed: 02/03/2024]
Abstract
The cingulate cortex is a limbic structure involved in multiple functions, including emotional processing, pain, cognition, memory, and spatial orientation. The main goal of this structural Magnetic Resonance Imaging (MRI) study was to investigate whether age affects the cingulate cortex uniformly across its anteroposterior dimensions and determine if the effects of age differ based on sex, hemisphere, and regional cingulate anatomy, in a large cohort of healthy individuals across the adult lifespan. The second objective aimed to explore whether the decline in emotional recognition accuracy and Theory of Mind (ToM) is linked to the potential age-related reductions in the pregenual anterior cingulate (ACC) and anterior midcingulate (MCC) cortices. We recruited 126 healthy participants (18-85 years) for this study. MRI datasets were acquired on a 4.7 T system. The cingulate cortex was manually segmented into the pregenual ACC, anterior MCC, posterior MCC, and posterior cingulate cortex (PCC). We observed negative relationships between the presence and length of the superior cingulate gyrus and bilateral volumes of pregenual ACC and anterior MCC. Age showed negative effects on the volume of all cingulate cortical subregions bilaterally except for the right anterior MCC. Most of the associations between age and the cingulate subregional volumes were linear. We did not find a significant effect of sex on cingulate cortical volumes. However, stronger effects of age were observed in men compared to women. This study also demonstrated that performance on an emotional recognition task was linked to pregenual ACC volume, whist the ToM capabilities were related to the size of pregenual ACC and anterior MCC. These results suggest that the cingulate cortex contributes to emotional recognition ability and ToM across the adult lifespan.
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Affiliation(s)
| | - Wojciech Pietrasik
- Department of Psychiatry, Faculty of Medicine & Dentistry, University of Alberta, Edmonton, AB, T6G 2V2, Canada
| | - Nikolai V Malykhin
- Neuroscience and Mental Health Institute, University of Alberta, Edmonton, AB, Canada.
- Department of Psychiatry, Faculty of Medicine & Dentistry, University of Alberta, Edmonton, AB, T6G 2V2, Canada.
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3
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Ruan J, Wang N, Li J, Wang J, Zou Q, Lv Y, Zhang H, Wang J. Single-subject cortical morphological brain networks across the adult lifespan. Hum Brain Mapp 2023; 44:5429-5449. [PMID: 37578334 PMCID: PMC10543107 DOI: 10.1002/hbm.26450] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Revised: 07/07/2023] [Accepted: 07/28/2023] [Indexed: 08/15/2023] Open
Abstract
Age-related changes in focal cortical morphology have been well documented in previous literature; however, how interregional coordination patterns of the focal cortical morphology reorganize with advancing age is not well established. In this study, we performed a comprehensive analysis of the topological changes in single-subject morphological brain networks across the adult lifespan. Specifically, we constructed four types of single-subject morphological brain networks for 650 participants (aged from 18 to 88 years old), and characterized their topological organization using graph-based network measures. Age-related changes in the network measures were examined via linear, quadratic, and cubic models. We found profound age-related changes in global small-world attributes and efficiency, local nodal centralities, and interregional similarities of the single-subject morphological brain networks. The age-related changes were mainly embodied in cortical thickness networks, involved in frontal regions and highly connected hubs, concentrated on short-range connections, characterized by linear changes, and susceptible to connections between limbic, frontoparietal, and ventral attention networks. Intriguingly, nonlinear (i.e., quadratic or cubic) age-related changes were frequently found in the insula and limbic regions, and age-related cubic changes preferred long-range morphological connections. Finally, we demonstrated that the morphological similarity in cortical thickness between two frontal regions mediated the relationship between age and cognition measured by Cattell scores. Taken together, these findings deepen our understanding of adaptive changes of the human brain with advancing age, which may account for interindividual variations in behaviors and cognition.
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Affiliation(s)
- Jingxuan Ruan
- School of Electronics and Information TechnologySouth China Normal UniversityFoshanChina
| | - Ningkai Wang
- Institute for Brain Research and RehabilitationSouth China Normal UniversityGuangzhouChina
| | - Junle Li
- Institute for Brain Research and RehabilitationSouth China Normal UniversityGuangzhouChina
| | - Jing Wang
- Institute for Brain Research and RehabilitationSouth China Normal UniversityGuangzhouChina
| | - Qihong Zou
- Center for MRI Research, Academy for Advanced Interdisciplinary StudiesPeking UniversityBeijingChina
| | - Yating Lv
- Institute of Psychological SciencesHangzhou Normal UniversityZhejiangHangzhouChina
| | - Han Zhang
- School of Electronics and Information TechnologySouth China Normal UniversityFoshanChina
| | - Jinhui Wang
- Institute for Brain Research and RehabilitationSouth China Normal UniversityGuangzhouChina
- Key Laboratory of Brain, Cognition and Education SciencesMinistry of EducationBeijingChina
- Center for Studies of Psychological ApplicationSouth China Normal UniversityGuangzhouChina
- Guangdong Key Laboratory of Mental Health and Cognitive ScienceSouth China Normal UniversityGuangzhouChina
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Hrybouski S, Das SR, Xie L, Wisse LEM, Kelley M, Lane J, Sherin M, DiCalogero M, Nasrallah I, Detre J, Yushkevich PA, Wolk DA. Aging and Alzheimer's disease have dissociable effects on local and regional medial temporal lobe connectivity. Brain Commun 2023; 5:fcad245. [PMID: 37767219 PMCID: PMC10521906 DOI: 10.1093/braincomms/fcad245] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Revised: 08/06/2023] [Accepted: 09/12/2023] [Indexed: 09/29/2023] Open
Abstract
Functional disruption of the medial temporal lobe-dependent networks is thought to underlie episodic memory deficits in aging and Alzheimer's disease. Previous studies revealed that the anterior medial temporal lobe is more vulnerable to pathological and neurodegenerative processes in Alzheimer's disease. In contrast, cognitive and structural imaging literature indicates posterior, as opposed to anterior, medial temporal lobe vulnerability in normal aging. However, the extent to which Alzheimer's and aging-related pathological processes relate to functional disruption of the medial temporal lobe-dependent brain networks is poorly understood. To address this knowledge gap, we examined functional connectivity alterations in the medial temporal lobe and its immediate functional neighbourhood-the Anterior-Temporal and Posterior-Medial brain networks-in normal agers, individuals with preclinical Alzheimer's disease and patients with Mild Cognitive Impairment or mild dementia due to Alzheimer's disease. In the Anterior-Temporal network and in the perirhinal cortex, in particular, we observed an inverted 'U-shaped' relationship between functional connectivity and Alzheimer's stage. According to our results, the preclinical phase of Alzheimer's disease is characterized by increased functional connectivity between the perirhinal cortex and other regions of the medial temporal lobe, as well as between the anterior medial temporal lobe and its one-hop neighbours in the Anterior-Temporal system. This effect is no longer present in symptomatic Alzheimer's disease. Instead, patients with symptomatic Alzheimer's disease displayed reduced hippocampal connectivity within the medial temporal lobe as well as hypoconnectivity within the Posterior-Medial system. For normal aging, our results led to three main conclusions: (i) intra-network connectivity of both the Anterior-Temporal and Posterior-Medial networks declines with age; (ii) the anterior and posterior segments of the medial temporal lobe become increasingly decoupled from each other with advancing age; and (iii) the posterior subregions of the medial temporal lobe, especially the parahippocampal cortex, are more vulnerable to age-associated loss of function than their anterior counterparts. Together, the current results highlight evolving medial temporal lobe dysfunction in Alzheimer's disease and indicate different neurobiological mechanisms of the medial temporal lobe network disruption in aging versus Alzheimer's disease.
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Affiliation(s)
- Stanislau Hrybouski
- Penn Image Computing and Science Laboratory (PICSL), University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Sandhitsu R Das
- Penn Image Computing and Science Laboratory (PICSL), University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Neurology, University of Pennsylvania, Philadelphia, PA 19104, USA
- Penn Memory Center, University of Pennsylvania, Philadelphia, PA 19104, USA
- Penn Alzheimer’s Disease Research Center, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Long Xie
- Penn Image Computing and Science Laboratory (PICSL), University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Laura E M Wisse
- Penn Image Computing and Science Laboratory (PICSL), University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Diagnostic Radiology, Lund University, 221 00 Lund, Sweden
| | - Melissa Kelley
- Penn Memory Center, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Jacqueline Lane
- Penn Memory Center, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Monica Sherin
- Penn Memory Center, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Michael DiCalogero
- Penn Memory Center, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Ilya Nasrallah
- Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA
- Penn Alzheimer’s Disease Research Center, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - John Detre
- Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Neurology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Paul A Yushkevich
- Penn Image Computing and Science Laboratory (PICSL), University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA
- Penn Alzheimer’s Disease Research Center, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - David A Wolk
- Department of Neurology, University of Pennsylvania, Philadelphia, PA 19104, USA
- Penn Alzheimer’s Disease Research Center, University of Pennsylvania, Philadelphia, PA 19104, USA
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5
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Hrybouski S, Das SR, Xie L, Wisse LEM, Kelley M, Lane J, Sherin M, DiCalogero M, Nasrallah I, Detre JA, Yushkevich PA, Wolk DA. Aging and Alzheimer's Disease Have Dissociable Effects on Medial Temporal Lobe Connectivity. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.01.18.23284749. [PMID: 36711782 PMCID: PMC9882834 DOI: 10.1101/2023.01.18.23284749] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
Functional disruption of the medial temporal lobe-dependent networks is thought to underlie episodic memory deficits in aging and Alzheimer's disease. Previous studies revealed that the anterior medial temporal lobe is more vulnerable to pathological and neurodegenerative processes in Alzheimer's disease. In contrast, cognitive and structural imaging literature indicates posterior, as opposed to anterior, medial temporal lobe vulnerability in normal aging. However, the extent to which Alzheimer's and aging-related pathological processes relate to functional disruption of the medial temporal lobe-dependent brain networks is poorly understood. To address this knowledge gap, we examined functional connectivity alterations in the medial temporal lobe and its immediate functional neighborhood - the Anterior-Temporal and Posterior-Medial brain networks - in normal agers, individuals with preclinical Alzheimer's disease, and patients with Mild Cognitive Impairment or mild dementia due to Alzheimer's disease. In the Anterior-Temporal network and in the perirhinal cortex, in particular, we observed an inverted 'U-shaped' relationship between functional connectivity and Alzheimer's stage. According to our results, the preclinical phase of Alzheimer's disease is characterized by increased functional connectivity between the perirhinal cortex and other regions of the medial temporal lobe, as well as between the anterior medial temporal lobe and its one-hop neighbors in the Anterior-Temporal system. This effect is no longer present in symptomatic Alzheimer's disease. Instead, patients with symptomatic Alzheimer's disease displayed reduced hippocampal connectivity within the medial temporal lobe as well as hypoconnectivity within the Posterior-Medial system. For normal aging, our results led to three main conclusions: (1) intra-network connectivity of both the Anterior-Temporal and Posterior-Medial networks declines with age; (2) the anterior and posterior segments of the medial temporal lobe become increasingly decoupled from each other with advancing age; and, (3) the posterior subregions of the medial temporal lobe, especially the parahippocampal cortex, are more vulnerable to age-associated loss of function than their anterior counterparts. Together, the current results highlight evolving medial temporal lobe dysfunction in Alzheimer's disease and indicate different neurobiological mechanisms of the medial temporal lobe network disruption in aging vs. Alzheimer's disease.
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6
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Pollok B, Hagedorn A, Krause V, Kotz SA. Age interferes with sensorimotor timing and error correction in the supra-second range. Front Aging Neurosci 2023; 14:1048610. [PMID: 36704500 PMCID: PMC9871492 DOI: 10.3389/fnagi.2022.1048610] [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: 09/19/2022] [Accepted: 12/22/2022] [Indexed: 01/12/2023] Open
Abstract
Introduction Precise motor timing including the ability to adjust movements after changes in the environment is fundamental to many daily activities. Sensorimotor timing in the sub-and supra-second range might rely on at least partially distinct brain networks, with the latter including the basal ganglia (BG) and the prefrontal cortex (PFC). Since both structures are particularly vulnerable to age-related decline, the present study investigated whether age might distinctively affect sensorimotor timing and error correction in the supra-second range. Methods A total of 50 healthy right-handed volunteers with 22 older (age range: 50-60 years) and 28 younger (age range: 20-36 years) participants synchronized the tap-onsets of their right index finger with an isochronous auditory pacing signal. Stimulus onset asynchronies were either 900 or 1,600 ms. Positive or negative step-changes that were perceivable or non-perceivable were occasionally interspersed to the fixed intervals to induce error correction. A simple reaction time task served as control condition. Results and Discussion In line with our hypothesis, synchronization variability in trials with supra-second intervals was larger in the older group. While reaction times were not affected by age, the mean negative asynchrony was significantly smaller in the elderly in trials with positive step-changes, suggesting more pronounced tolerance of positive deviations at older age. The analysis of error correction by means of the phase correction response (PCR) suggests reduced error correction in the older group. This effect emerged in trials with supra-second intervals and large positive step-changes, only. Overall, these results support the hypothesis that sensorimotor synchronization in the sub-second range is maintained but synchronization accuracy and error correction in the supra-second range is reduced in the elderly as early as in the fifth decade of life suggesting that these measures are suitable for the early detection of age-related changes of the motor system.
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Affiliation(s)
- Bettina Pollok
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany,*Correspondence: Bettina Pollok,
| | - Amelie Hagedorn
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany,Department of Neuropsychology and Psychopharmacology, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands
| | - Vanessa Krause
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany,Department of Neuropsychology, Mauritius Hospital and Neurorehabilitation Center Meerbusch, Meerbusch, Germany
| | - Sonja A. Kotz
- Department of Neuropsychology and Psychopharmacology, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands
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7
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Du Y, Kong Y, He X. IABC: A Toolbox for Intelligent Analysis of Brain Connectivity. Neuroinformatics 2023; 21:303-321. [PMID: 36609668 DOI: 10.1007/s12021-022-09617-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/30/2022] [Indexed: 01/09/2023]
Abstract
Brain functional networks and connectivity have played an important role in exploring brain function for understanding the brain and disclosing the mechanisms of brain disorders. Independent component analysis (ICA) is one of the most widely applied data-driven methods to extract brain functional networks/connectivity. However, it is hard to guarantee the reliability of networks/connectivity due to the randomness of component order and the difficulty in selecting an optimal component number in ICA. To facilitate the analysis of brain functional networks and connectivity using ICA, we developed a MATLAB toolbox called Intelligent Analysis of Brain Connectivity (IABC). IABC incorporates our previously proposed group information guided independent component analysis (GIG-ICA), NeuroMark, and splitting-merging assisted reliable ICA (SMART ICA) methods, which can estimate reliable individual-subject neuroimaging measures for further analysis. After user inputs functional magnetic resonance imaging (fMRI) data of multiple subjects that are regularly organized (e.g., in Brain Imaging Data Structure (BIDS)) and clicks a few buttons to set parameters, IABC automatically outputs brain functional networks, their related time courses, and functional network connectivity of each subject. All these neuroimaging measures are promising for providing clues in understanding brain function and differentiating brain disorders.
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Affiliation(s)
- Yuhui Du
- School of Computer and Information Technology, Shanxi University, Taiyuan, China.
| | - Yanshu Kong
- School of Computer and Information Technology, Shanxi University, Taiyuan, China
| | - Xingyu He
- School of Computer and Information Technology, Shanxi University, Taiyuan, China
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8
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Strain JF, Brier MR, Tanenbaum A, Gordon BA, McCarthy JE, Dincer A, Marcus DS, Chhatwal JP, Graff-Radford NR, Day GS, la Fougère C, Perrin RJ, Salloway S, Schofield PR, Yakushev I, Ikeuchi T, Vöglein J, Morris JC, Benzinger TLS, Bateman RJ, Ances BM, Snyder AZ. Covariance-based vs. correlation-based functional connectivity dissociates healthy aging from Alzheimer disease. Neuroimage 2022; 261:119511. [PMID: 35914670 PMCID: PMC9750733 DOI: 10.1016/j.neuroimage.2022.119511] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2022] [Revised: 07/04/2022] [Accepted: 07/22/2022] [Indexed: 01/05/2023] Open
Abstract
Prior studies of aging and Alzheimer disease have evaluated resting state functional connectivity (FC) using either seed-based correlation (SBC) or independent component analysis (ICA), with a focus on particular functional systems. SBC and ICA both are insensitive to differences in signal amplitude. At the same time, accumulating evidence indicates that the amplitude of spontaneous BOLD signal fluctuations is physiologically meaningful. We systematically compared covariance-based FC, which is sensitive to amplitude, vs. correlation-based FC, which is not, in affected individuals and controls drawn from two cohorts of participants including autosomal dominant Alzheimer disease (ADAD), late onset Alzheimer disease (LOAD), and age-matched controls. Functional connectivity was computed over 222 regions of interest and group differences were evaluated in terms of components projected onto a space of lower dimension. Our principal observations are: (1) Aging is associated with global loss of resting state fMRI signal amplitude that is approximately uniform across resting state networks. (2) Thus, covariance FC measures decrease with age whereas correlation FC is relatively preserved in healthy aging. (3) In contrast, symptomatic ADAD and LOAD both lead to loss of spontaneous activity amplitude as well as severely degraded correlation structure. These results demonstrate a double dissociation between age vs. Alzheimer disease and the amplitude vs. correlation structure of resting state BOLD signals. Modeling results suggest that the AD-associated loss of correlation structure is attributable to a relative increase in the fraction of locally restricted as opposed to widely shared variance.
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Affiliation(s)
- Jeremy F Strain
- Department of Neurology, Washington University in Saint Louis, St. Louis, MO 63110, USA
| | - Matthew R Brier
- Department of Neurology, Washington University in Saint Louis, St. Louis, MO 63110, USA
| | - Aaron Tanenbaum
- Department of Neurology, Washington University in Saint Louis, St. Louis, MO 63110, USA
| | - Brian A Gordon
- Department of Radiology, Washington University in Saint Louis, Box 8225, 660 South Euclid Ave, St. Louis, MO 63110, USA; Knight Alzheimer Disease Research Center, Washington University in St. Louis, St. Louis, MO 63110, USA; Department of Psychological & Brain Sciences, Washington University, St. Louis, MO, USA
| | - John E McCarthy
- Department of Mathematics and Statistics, Washington University, St. Louis, MO 63130, USA
| | - Aylin Dincer
- Department of Radiology, Washington University in Saint Louis, Box 8225, 660 South Euclid Ave, St. Louis, MO 63110, USA
| | - Daniel S Marcus
- Department of Radiology, Washington University in Saint Louis, Box 8225, 660 South Euclid Ave, St. Louis, MO 63110, USA; Knight Alzheimer Disease Research Center, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Jasmeer P Chhatwal
- Martinos Center, Massachusetts General Hospital, 149 13th St Room 2662, Charlestown, MA 02129, USA
| | - Neill R Graff-Radford
- Department of Neurology, Mayo Clinic Florida, 4500 San Pablo Road, Jacksonville, Fl 32224, USA
| | - Gregory S Day
- Department of Neurology, Mayo Clinic Florida, 4500 San Pablo Road, Jacksonville, Fl 32224, USA
| | - Christian la Fougère
- Department of Nuclear Medicine and Clinical Molecular Imaging, Universityhospital Tübingen, Tübingen, Germany; German Center for Neurodegenerative Diseases (DZNE) Tübingen, Germany
| | - Richard J Perrin
- Department of Neurology, Washington University in Saint Louis, St. Louis, MO 63110, USA; Knight Alzheimer Disease Research Center, Washington University in St. Louis, St. Louis, MO 63110, USA; Hope Center for Neurological Disorders, Washington University in St. Louis, St. Louis, MO 63110, USA; Department of Pathology and Immunology, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Stephen Salloway
- Alpert Medical School of Brown University, 345 Blackstone Boulevard, Providence, RI 02906, USA
| | - Peter R Schofield
- Neuroscience Research Australia, Sydney, NSW 2131, Australia; School of Medical Sciences, University of New South Wales, Sydney, NSW 2052, Australia
| | - Igor Yakushev
- Department of Nuclear Medicine, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Ismaninger Str. 22, Munich 81675, Germany
| | - Takeshi Ikeuchi
- Department of Molecular Genetics, Brain Research Institute, Niigata University, Japan
| | - Jonathan Vöglein
- Department of Neurology, Ludwig-Maximilians-Universität Munich, Germany
| | - John C Morris
- Department of Neurology, Washington University in Saint Louis, St. Louis, MO 63110, USA; Knight Alzheimer Disease Research Center, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Tammie L S Benzinger
- Department of Radiology, Washington University in Saint Louis, Box 8225, 660 South Euclid Ave, St. Louis, MO 63110, USA; Knight Alzheimer Disease Research Center, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Randall J Bateman
- Department of Neurology, Washington University in Saint Louis, St. Louis, MO 63110, USA; Knight Alzheimer Disease Research Center, Washington University in St. Louis, St. Louis, MO 63110, USA; Hope Center for Neurological Disorders, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Beau M Ances
- Department of Neurology, Washington University in Saint Louis, St. Louis, MO 63110, USA; Department of Radiology, Washington University in Saint Louis, Box 8225, 660 South Euclid Ave, St. Louis, MO 63110, USA; Hope Center for Neurological Disorders, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Abraham Z Snyder
- Department of Neurology, Washington University in Saint Louis, St. Louis, MO 63110, USA; Department of Radiology, Washington University in Saint Louis, Box 8225, 660 South Euclid Ave, St. Louis, MO 63110, USA.
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9
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Xiong X, Cribben I. Beyond linear dynamic functional connectivity: a vine copula change point model. J Comput Graph Stat 2022. [DOI: 10.1080/10618600.2022.2127738] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/14/2022]
Affiliation(s)
- Xin Xiong
- 1Department of Biostatistics, Harvard T. H. Chan School of Public Health
| | - Ivor Cribben
- Department of Accounting and Business Analytics, Alberta School of Business
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10
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Weiss C, Bertolino N, Procissi D, Disterhoft JF. Brain activity studied with magnetic resonance imaging in awake rabbits. FRONTIERS IN NEUROIMAGING 2022; 1:965529. [PMID: 37555136 PMCID: PMC10406271 DOI: 10.3389/fnimg.2022.965529] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/09/2022] [Accepted: 08/08/2022] [Indexed: 08/10/2023]
Abstract
We reviewed fMRI experiments from our previous work in conscious rabbits, an experimental preparation that is advantageous for measuring brain activation that is free of anesthetic modulation and which can address questions in a variety of areas in sensory, cognitive, and pharmacological neuroscience research. Rabbits do not struggle or move for several hours while sitting with their heads restrained inside the horizontal bore of a magnet. This greatly reduces movement artifacts in magnetic resonance (MR) images in comparison to other experimental animals such as rodents, cats, and monkeys. We have been able to acquire high-resolution anatomic as well as functional images that are free of movement artifacts during several hours of restraint. Results from conscious rabbit fMRI studies with whisker stimulation are provided to illustrate the feasibility of this conscious animal model for functional MRI and the reproducibility of data gained with it.
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Affiliation(s)
- Craig Weiss
- Feinberg School of Medicine, Northwestern University, Chicago, IL, United States
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11
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Perinelli A, Assecondi S, Tagliabue CF, Mazza V. Power shift and connectivity changes in healthy aging during resting-state EEG. Neuroimage 2022; 256:119247. [PMID: 35477019 DOI: 10.1016/j.neuroimage.2022.119247] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2021] [Revised: 04/20/2022] [Accepted: 04/23/2022] [Indexed: 12/15/2022] Open
Abstract
The neural activity of human brain changes in healthy individuals during aging. The most frequent variation in patterns of neural activity are a shift from posterior to anterior areas and a reduced asymmetry between hemispheres. These patterns are typically observed during task execution and by using functional magnetic resonance imaging data. In the present study we investigated whether analogous effects can also be detected during rest and by means of source-space time series reconstructed from electroencephalographic recordings. By analyzing oscillatory power distribution across the brain we indeed found a shift from posterior to anterior areas in older adults. We additionally examined this shift by evaluating connectivity and its changes with age. The findings indicated that inter-area connections among frontal, parietal and temporal areas were strengthened in older individuals. A more complex pattern was shown in intra-area connections, where age-related activity was enhanced in parietal and temporal areas, and reduced in frontal areas. Finally, the resulting network exhibits a loss of modularity with age. Overall, the results extend to resting-state condition the evidence of an age-related shift of brain activity from posterior to anterior areas, thus suggesting that this shift is a general feature of the aging brain rather than being task-specific. In addition, the connectivity results provide new information on the reorganization of resting-state brain activity in aging.
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Affiliation(s)
- Alessio Perinelli
- Center for Mind/Brain Sciences (CIMeC), University of Trento, Corso Bettini 31, 38068 Rovereto, TN, Italy.
| | - Sara Assecondi
- Center for Mind/Brain Sciences (CIMeC), University of Trento, Corso Bettini 31, 38068 Rovereto, TN, Italy
| | - Chiara F Tagliabue
- Center for Mind/Brain Sciences (CIMeC), University of Trento, Corso Bettini 31, 38068 Rovereto, TN, Italy
| | - Veronica Mazza
- Center for Mind/Brain Sciences (CIMeC), University of Trento, Corso Bettini 31, 38068 Rovereto, TN, Italy
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12
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The Influence of Virus Infection on Microglia and Accelerated Brain Aging. Cells 2021; 10:cells10071836. [PMID: 34360004 PMCID: PMC8303900 DOI: 10.3390/cells10071836] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2021] [Revised: 07/15/2021] [Accepted: 07/16/2021] [Indexed: 12/12/2022] Open
Abstract
Microglia are the resident immune cells of the central nervous system contributing substantially to health and disease. There is increasing evidence that inflammatory microglia may induce or accelerate brain aging, by interfering with physiological repair and remodeling processes. Many viral infections affect the brain and interfere with microglia functions, including human immune deficiency virus, flaviviruses, SARS-CoV-2, influenza, and human herpes viruses. Especially chronic viral infections causing low-grade neuroinflammation may contribute to brain aging. This review elucidates the potential role of various neurotropic viruses in microglia-driven neurocognitive deficiencies and possibly accelerated brain aging.
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Jin Z, Huyang S, Jiang L, Yan Y, Xu M, Wang J, Li Q, Wu D. Increased Resting-State Interhemispheric Functional Connectivity of Posterior Superior Temporal Gyrus and Posterior Cingulate Cortex in Congenital Amusia. Front Neurosci 2021; 15:653325. [PMID: 33994929 PMCID: PMC8120159 DOI: 10.3389/fnins.2021.653325] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2021] [Accepted: 04/06/2021] [Indexed: 11/26/2022] Open
Abstract
Interhemispheric connectivity of the two cerebral hemispheres is crucial for a broad repertoire of cognitive functions including music and language. Congenital amusia has been reported as a neurodevelopment disorder characterized by impaired music perception and production. However, little is known about the characteristics of the interhemispheric functional connectivity (FC) in amusia. In the present study, we used a newly developed voxel-mirrored homotopic connectivity (VMHC) method to investigate the interhemispheric FC of the whole brain in amusia at resting-state. Thirty amusics and 29 matched participants underwent a resting-state functional magnetic resonance imaging (fMRI) scanning. An automated VMHC approach was used to analyze the fMRI data. Compared to the control group, amusics showed increased VMHC within the posterior part of the default mode network (DMN) mainly in the posterior superior temporal gyrus (pSTG) and posterior cingulate cortex (PCC). Correlation analyses revealed negative correlations between the VMHC value in pSTG/PCC and the music perception ability among amusics. Further ROC analyses showed that the VMHC value of pSTG/PCC showed a good sensibility/specificity to differentiate the amusics from the controls. These findings provide a new perspective for understanding the neural basis of congenital amusia and imply the immature state of DMN may be a credible neural marker of amusia.
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Affiliation(s)
- Zhishuai Jin
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Sizhu Huyang
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Lichen Jiang
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Yajun Yan
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Ming Xu
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Jinyu Wang
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Qixiong Li
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Daxing Wu
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha, China.,Medical Psychological Institute, Central South University, Changsha, China.,National Clinical Research Center for Mental Disorders, Changsha, China
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