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Pindus DM, Paluska S, So J, Wyczesany M, Ligeza TS, Sarol J, Kuang J, Quiroz FB, Shanmugam R, Syed T, Kos M, Khan N, Hillman C, Kramer A. Breaking prolonged sitting with high-intensity interval training to improve cognitive and brain health in middle-aged and older adults: a protocol for the pilot feasibility HIIT2SITLess trial. BMJ Open 2025; 15:e095415. [PMID: 40341152 PMCID: PMC12060886 DOI: 10.1136/bmjopen-2024-095415] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/22/2024] [Accepted: 04/08/2025] [Indexed: 05/10/2025] Open
Abstract
INTRODUCTION Excessive sedentary time (ST) is linked to dementia risk, poorer attentional control and episodic memory. These cognitive decrements have been associated with decreased functional connectivity (FC) in the frontoparietal network (FPN) and default mode networks (DMN) with ageing. Physical activity (PA) interventions can enhance FC in these networks, but these interventions are not designed to decrease ST among older adults. Prolonged sitting (ie, sitting continuously for ≥20 min) can acutely reduce frontoparietal brain function and attentional control, while a single PA bout lasting at least 20 min can enhance them. It has been theorised that stimulation of the cerebral norepinephrine release through peripheral increase in catecholamines may explain this effect. In contrast, the effects of shorter (<10 min) PA bouts used to interrupt prolonged sitting on neurocognitive functions remain poorly understood. This pilot randomised crossover feasibility trial capitalises on PA intensity as the major limiting factor in peripheral catecholamine increase and tests the effects of interrupting prolonged sitting every 30 min with 6 min high-intensity interval training (HIIT) compared with low-intensity interval training (LIIT) bouts. The study will address three aims: (1) to assess feasibility, acceptability, fidelity and safety of HIIT breaks to improve neurocognitive function in middle-aged and older adults; (2) to quantify the differences between conditions in the change in the amplitude and latency of the P3b component of event-related potentials (a marker for frontoparietal function) and (3) to explore the differences between conditions in attentional control, episodic memory and FC of the FPN and DMN in middle-aged and older adults. METHODS AND ANALYSIS 54 healthy adults, aged 40-75 years, will be recruited from the local community and randomly assigned to a condition sequence (HIIT, LIIT vs LIIT and HIIT). Each HIIT bout comprises a 1 min warm-up, 2 min at 90% of the maximum heart rate (HRmax), 1 min passive rest and 2 min at 90% HRmax. During 2 min intervals in LIIT, participants exercise at 57%-60% of HRmax. The primary outcomes include the feasibility (recruitment and retention rates, percentage of valid electroencephalogram data), acceptability of time commitment, HIIT bouts and neurocognitive assessments, fidelity (the intensity of HIIT breaks, percentage of time spent sitting) and the amplitude and the latency of the P3b component of event-related brain potentials measured during the modified Eriksen flanker task at pretests, after the first and the third PA bout and at post-test. General linear mixed-effects models will be used to test the effects of the intervention on the P3b component. ETHICS AND DISSEMINATION The Institutional Review Board at the University of Illinois Urbana-Champaign provided the ethical approval for the study. Findings will be disseminated in peer-reviewed journals and at scientific conferences. TRIAL REGISTRATION NUMBER NCT06243016.
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Affiliation(s)
- Dominika M Pindus
- Department of Health and Kinesiology, University of Illinois at Urbana-Champaign College of Applied Health Sciences, Urbana, Illinois, USA
- Neuroscience Program, University of Illinois Urbana-Champaign, Urbana, Illinois, USA
- Beckman Institute for Advanced Science and Technology, University of Illinois Urbana-Champaign, Urbana, Illinois, USA
| | - Scott Paluska
- Department of Health and Kinesiology, University of Illinois at Urbana-Champaign College of Applied Health Sciences, Urbana, Illinois, USA
- University of Vermont Larner College of Medicine, Burlington, Vermont, USA
- Evergreen Sports Medicine, Williston, Vermont, USA
| | - Joseph So
- Department of Health and Kinesiology, University of Illinois at Urbana-Champaign College of Applied Health Sciences, Urbana, Illinois, USA
- Department and Urgent Care VA, Hospital Medicine, Danville, Illinois, UK
| | - Miroslaw Wyczesany
- Insitute of Psychology, Jagiellonian University, Krakow, Małopolskie, Poland
| | - Tomasz S Ligeza
- Insitute of Psychology, Jagiellonian University, Krakow, Małopolskie, Poland
| | - Jesus Sarol
- Interdisciplinary Health Sciences Institute, University of Illinois Urbana-Champaign, Urbana, Illinois, USA
| | - Jin Kuang
- Department of Health and Kinesiology, University of Illinois at Urbana-Champaign College of Applied Health Sciences, Urbana, Illinois, USA
| | - Flor B Quiroz
- Department of Health and Kinesiology, University of Illinois at Urbana-Champaign College of Applied Health Sciences, Urbana, Illinois, USA
- Department of Psychology, University of Illinois Urbana-Champaign, Urbana, Illinois, USA
| | - Ramiya Shanmugam
- Department of Health and Kinesiology, University of Illinois at Urbana-Champaign College of Applied Health Sciences, Urbana, Illinois, USA
- The School of Cellular and Molecular Biology, University of Illinois Urbana-Champaign, Urbana, Illinois, USA
| | - Talha Syed
- Department of Health and Kinesiology, University of Illinois at Urbana-Champaign College of Applied Health Sciences, Urbana, Illinois, USA
- Department of Psychology, University of Illinois Urbana-Champaign, Urbana, Illinois, USA
| | - Maciej Kos
- Center for Cognitive & Brain Health, Northeastern University, Boston, Massachusetts, USA
| | - Naiman Khan
- Department of Health and Kinesiology, University of Illinois at Urbana-Champaign College of Applied Health Sciences, Urbana, Illinois, USA
- Neuroscience Program, University of Illinois Urbana-Champaign, Urbana, Illinois, USA
- Beckman Institute for Advanced Science and Technology, University of Illinois Urbana-Champaign, Urbana, Illinois, USA
- Division of Nutritional Sciences, University of Illinois Urbana-Champaign, Urbana, Illinois, USA
| | - Charles Hillman
- Center for Cognitive & Brain Health, Northeastern University, Boston, Massachusetts, USA
- Department of Psychology, Northeastern University, Boston, Massachusetts, USA
- Department of Physical Therapy, Movement, & Rehabilitation Sciences, Northeastern University, Boston, Massachusetts, USA
| | - Art Kramer
- Center for Cognitive & Brain Health, Northeastern University, Boston, Massachusetts, USA
- Department of Psychology, Northeastern University, Boston, Massachusetts, USA
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Mandino F, Shen X, Desrosiers-Grégoire G, O'Connor D, Mukherjee B, Owens A, Qu A, Onofrey J, Papademetris X, Chakravarty MM, Strittmatter SM, Lake EMR. Aging-dependent loss of functional connectivity in a mouse model of Alzheimer's disease and reversal by mGluR5 modulator. Mol Psychiatry 2025; 30:1730-1745. [PMID: 39424929 PMCID: PMC12015114 DOI: 10.1038/s41380-024-02779-z] [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: 03/11/2024] [Revised: 09/26/2024] [Accepted: 09/30/2024] [Indexed: 10/21/2024]
Abstract
Amyloid accumulation in Alzheimer's disease (AD) is associated with synaptic damage and altered connectivity in brain networks. While measures of amyloid accumulation and biochemical changes in mouse models have utility for translational studies of certain therapeutics, preclinical analysis of altered brain connectivity using clinically relevant fMRI measures has not been well developed for agents intended to improve neural networks. Here, we conduct a longitudinal study in a double knock-in mouse model for AD (AppNL-G-F/hMapt), monitoring brain connectivity by means of resting-state fMRI. While the 4-month-old AD mice are indistinguishable from wild-type controls (WT), decreased connectivity in the default-mode network is significant for the AD mice relative to WT mice by 6 months of age and is pronounced by 9 months of age. In a second cohort of 20-month-old mice with persistent functional connectivity deficits for AD relative to WT, we assess the impact of two-months of oral treatment with a silent allosteric modulator of mGluR5 (BMS-984923/ALX001) known to rescue synaptic density. Functional connectivity deficits in the aged AD mice are reversed by the mGluR5-directed treatment. The longitudinal application of fMRI has enabled us to define the preclinical time trajectory of AD-related changes in functional connectivity, and to demonstrate a translatable metric for monitoring disease emergence, progression, and response to synapse-rescuing treatment.
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Affiliation(s)
- Francesca Mandino
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, 06520, USA
| | - Xilin Shen
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, 06520, USA
| | - Gabriel Desrosiers-Grégoire
- Computational Brain Anatomy Laboratory, Cerebral Imaging Center, Douglas Mental Health University Institute, Montreal, QC, H4H 1R3, Canada
- Integrated Program in Neuroscience, McGill University, Montreal, QC, H3A 0G4, Canada
| | - David O'Connor
- Department of Biomedical Engineering, Yale University, New Haven, CT, 06511, USA
| | - Bandhan Mukherjee
- Cellular Neuroscience, Neurodegeneration and Repair Program, Yale School of Medicine, New Haven, CT, 06520, USA
| | - Ashley Owens
- Cellular Neuroscience, Neurodegeneration and Repair Program, Yale School of Medicine, New Haven, CT, 06520, USA
| | - An Qu
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, 06520, USA
| | - John Onofrey
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, 06520, USA
- Department of Biomedical Engineering, Yale University, New Haven, CT, 06511, USA
- Department of Urology, Yale School of Medicine, New Haven, CT, 06520, USA
| | - Xenophon Papademetris
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, 06520, USA
- Department of Biomedical Engineering, Yale University, New Haven, CT, 06511, USA
- Department of Biomedical Informatics and Data Science, Yale School of Medicine, New Haven, CT, 06520, USA
- Wu Tsai Institute, Yale University, New Haven, CT, 06510, USA
| | - M Mallar Chakravarty
- Computational Brain Anatomy Laboratory, Cerebral Imaging Center, Douglas Mental Health University Institute, Montreal, QC, H4H 1R3, Canada
- Integrated Program in Neuroscience, McGill University, Montreal, QC, H3A 0G4, Canada
- Department of Psychiatry, McGill University, Montreal, QC, H3A 0G4, Canada
- Department of Biological and Biomedical Engineering, McGill University, Montreal, QC, H3A 0G4, Canada
| | - Stephen M Strittmatter
- Cellular Neuroscience, Neurodegeneration and Repair Program, Yale School of Medicine, New Haven, CT, 06520, USA.
- Wu Tsai Institute, Yale University, New Haven, CT, 06510, USA.
- Department of Neurology, Yale University School of Medicine, New Haven, CT, 06510, USA.
- Kavli Institute of Neuroscience, Yale University School of Medicine, New Haven, CT, 06510, USA.
- Department of Neuroscience, Yale University School of Medicine, New Haven, CT, 06510, USA.
| | - Evelyn M R Lake
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, 06520, USA.
- Department of Biomedical Engineering, Yale University, New Haven, CT, 06511, USA.
- Wu Tsai Institute, Yale University, New Haven, CT, 06510, USA.
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An S, Oh SJ, Noh S, Jun SB, Sung JE. Enhancing cognitive abilities through transcutaneous auricular vagus nerve stimulation: Findings from prefrontal functional connectivity analysis and virtual brain simulation. Neuroimage 2025; 311:121179. [PMID: 40158670 DOI: 10.1016/j.neuroimage.2025.121179] [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: 01/14/2025] [Revised: 03/26/2025] [Accepted: 03/27/2025] [Indexed: 04/02/2025] Open
Abstract
Recent studies have indicated the potential of transcutaneous auricular vagus nerve stimulation (taVNS) as an intervention for cognitive decline. In this study, we systematically analyzed the effects of taVNS on cognitive enhancement from the perspective of brain networks, by combining functional near-infrared spectroscopy (fNIRS) signal analysis with virtual brain simulations. Behavioral experiments with older adults demonstrated that participants with low baseline performance experienced significant improvements in working memory performance following taVNS, while those with high baseline performance tended to decline. This pattern was closely associated with functional connectivity (FC) in the prefrontal cortex (PFC) concurrently measured during the behavioral tasks, i.e., task performance correlated with FC in the PFC, particularly in the medial PFC (mPFC). Moreover, the changes in performance due to taVNS, which varied based on baseline performance, exhibited a notable alignment with the FC changes in the mPFC. These findings were further explored through virtual brain simulations. The simulation results demonstrated that the brain's functional state could vary depending on the network coupling parameter-capable of reflecting loss of structural brain connectivity associated with aging-and that the modulation effects induced by taVNS may also differ based on those functional states. Current results indicate that the efficacy of taVNS interventions for cognitive enhancement may vary according to the pre-intervention structural and functional states of individual brains. Therefore, the development of personalized optimization strategies for taVNS intervention is crucial, and digital brain research holds significant promise in advancing this field.
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Affiliation(s)
- Sora An
- Department of Electronic and Electrical Engineering, Ewha Womans University, Seoul, Republic of Korea
| | - Se Jin Oh
- Department of Communication Disorders, Ewha Womans University, Seoul, Republic of Korea
| | - Shinhee Noh
- Department of Communication Disorders, Ewha Womans University, Seoul, Republic of Korea
| | - Sang Beom Jun
- Department of Electronic and Electrical Engineering, Ewha Womans University, Seoul, Republic of Korea; Graduate Program in Smart Factory, Ewha Womans University, Seoul, Republic of Korea; Department of Brain and Cognitive Sciences, Ewha Womans University, Seoul, Republic of Korea.
| | - Jee Eun Sung
- Department of Communication Disorders, Ewha Womans University, Seoul, Republic of Korea.
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Guo H, Liu YX, Li Y, Guo QL, Hao ZP, Yang YL, Wei J. Self-organizing dynamic research based on phase coherence graph autoencoders: Analysis of brain metastable states across the lifespan. Neuroimage 2025; 310:121119. [PMID: 40049301 DOI: 10.1016/j.neuroimage.2025.121119] [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: 10/11/2024] [Revised: 02/21/2025] [Accepted: 03/04/2025] [Indexed: 03/14/2025] Open
Abstract
The development of the human brain is a complex, lifelong process during which collective behaviors of neurons exhibit self-organizing dynamics. Metastable states play a crucial role in understanding the complex dynamical mechanisms of the brain, and analyzing them helps to reveal the mechanisms of functional changes in the brain throughout development and aging. Specifically, global metastable state provides a overall perspective on the flexibility of brain reorganization, while the evolution trajectories of transient functional patterns capture detailed changes in brain activity. The leading eigenvector dynamics analysis (LEiDA) method significantly reduces the dimensionality of data and is widely used to capture the temporal trajectory characteristics of transient functional patterns, i.e., metastable brain states. However, LEiDA's linear dimensionality reduction of high-dimensional raw brain data may overlook non-linear information and lose some relationships between features. We developed a framework based on Phase Coherence Graph Autoencoder (PCGAE) that employs graph autoencoders (GAE) for non-linear dimensionality reduction of phase coherence matrices. This approach clusters to identify more distinct metastable brain states and is applied to the analysis of resting-state functional magnetic resonance imaging (rs-fMRI) data across the human lifespan. This paper investigates age-related differences and continuity changes from different perspectives: metastable state indicators and state trajectory indicators (occurrence probability, lifetime, and state transition metrics). Global metastable state shows a linear decline with age, while both linear and quadratic effects of age-related changes are observed in detailed state metastable and state trajectory indicators. Finally, the proposed feature extraction scheme demonstrates good classification performance for categorizing brain age groups. These findings can help us understand the self-organizing reorganization characteristics associated with aging and their complex dynamic changes, providing new insights into brain development throughout the entire lifespan.
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Affiliation(s)
- Hao Guo
- College of Computer Science and Technology, Taiyuan University of Technology, Taiyuan 030024, China
| | - Yu-Xuan Liu
- College of Computer Science and Technology, Taiyuan University of Technology, Taiyuan 030024, China
| | - Yao Li
- School of Software, Taiyuan University of Technology, Taiyuan 030024, China
| | - Qi-Li Guo
- College of Computer Science and Technology, Taiyuan University of Technology, Taiyuan 030024, China
| | - Zhi-Peng Hao
- College of Computer Science and Technology, Taiyuan University of Technology, Taiyuan 030024, China
| | - Yan-Li Yang
- College of Computer Science and Technology, Taiyuan University of Technology, Taiyuan 030024, China.
| | - Jing Wei
- School of Information, Shanxi University of Finance and Economics, Taiyuan 030024, China.
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Madden D, Stephens TM, Scott J, O’Neal Swann C, Prather K, Hoffmeister J, Ding L, Dunn IF, Conner AK, Yuan H. Functional connectivity of default mode network in non-hospitalized patients with post-COVID cognitive complaints. Front Neurosci 2025; 19:1576393. [PMID: 40276574 PMCID: PMC12018477 DOI: 10.3389/fnins.2025.1576393] [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: 02/14/2025] [Accepted: 03/26/2025] [Indexed: 04/26/2025] Open
Abstract
Introduction Neurologic impairment is common in patients with acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection. While patients with severe COVID have a higher prevalence of neurologic symptoms, as many as one in five patients with mild COVID may also be affected, exhibiting impaired memory as well as other cognitive dysfunctions. Methods To characterize the effect of COVID on the brain, the current study recruited a group of adults with post-COVID cognitive complaints but with mild, non-hospitalized cases. They were then evaluated through formal neuropsychological testing and underwent functional MRI of the brain. The participants in our study performed nearly as expected for cognitively intact individuals. Additionally, we characterized the functional connectivity of the default mode network (DMN), which is known for cognitive functions including memory as well as the attention functions involved in normal aging and degenerative diseases. Results Along with the retention of functional connectivity in the DMN, our results found the DMN to be associated with neurocognitive performance through region-of-interest and whole-brain analyses. The connectivity between key nodes of the DMN was positively correlated with cognitive scores (r = 0.51, p = 0.02), with higher performers exhibiting higher DMN connectivity. Discussion Our findings provide neuroimaging evidence of the functional connectivity of brain networks among individuals experiencing cognitive deficits beyond the recovery of mild COVID. These imaging outcomes indicate expected functional trends in the brain, furthering understanding and guidance of the DMN and neurocognitive deficits in patients recovering from COVID.
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Affiliation(s)
- Derek Madden
- Stephenson School of Biomedical Engineering, Gallogly College of Engineering, The University of Oklahoma, Norman, OK, United States
| | - Tressie M. Stephens
- Department of Neurosurgery, The University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States
| | - Jim Scott
- Department of Psychiatry and Behavioral Sciences, The University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States
| | - Christen O’Neal Swann
- Department of Neurosurgery, The University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States
| | - Kiana Prather
- Department of Neurosurgery, The University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States
| | - Jordan Hoffmeister
- Department of Psychiatry and Behavioral Sciences, The University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States
| | - Lei Ding
- Stephenson School of Biomedical Engineering, Gallogly College of Engineering, The University of Oklahoma, Norman, OK, United States
- Institute for Biomedical Engineering, Science, and Technology, University of Oklahoma, Norman, OK, United States
| | - Ian F. Dunn
- Department of Neurosurgery, The University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States
| | - Andrew K. Conner
- Department of Neurosurgery, The University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States
| | - Han Yuan
- Stephenson School of Biomedical Engineering, Gallogly College of Engineering, The University of Oklahoma, Norman, OK, United States
- Department of Neurosurgery, The University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States
- Institute for Biomedical Engineering, Science, and Technology, University of Oklahoma, Norman, OK, United States
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Grydeland H, Sneve MH, Roe JM, Raud L, Ness HT, Folvik L, Amlien I, Geier OM, Sørensen Ø, Vidal-Piñeiro D, Walhovd KB, Fjell AM. Network segregation during episodic memory shows age-invariant relations with memory performance from 7 to 82 years. Neurobiol Aging 2025; 148:1-15. [PMID: 39874716 DOI: 10.1016/j.neurobiolaging.2025.01.004] [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: 03/01/2024] [Revised: 01/14/2025] [Accepted: 01/14/2025] [Indexed: 01/30/2025]
Abstract
Lower episodic memory capability, as seen in development and aging compared with younger adulthood, may partly depend on lower brain network segregation. Here, our objective was twofold: (1) test this hypothesis using within- and between-network functional connectivity (FC) during episodic memory encoding and retrieval, in two independent samples (n = 734, age 7-82 years). (2) Assess associations with age and the ability to predict memory comparing task-general FC and memory-modulated FC. In a multiverse-inspired approach, we performed tests across multiple analytic choices. Results showed that relationships differed based on these analytic choices and were mainly present in the largest dataset,. Significant relationships indicated that (i) memory-modulated FC predicted memory performance and associated with memory in an age-invariant manner. (ii) In line with the so-called neural dedifferentiation view, task-general FC showed lower segregation with higher age in adults which was associated with worse memory performance. In development, although there were only weak signs of a neural differentiation, that is, gradually higher segregation with higher age, we observed similar lower segregation-worse memory relationships. This age-invariant relationships between FC and episodic memory suggest that network segregation is pivotal for memory across the healthy lifespan.
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Affiliation(s)
- Håkon Grydeland
- Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Oslo 0317, Norway.
| | - Markus H Sneve
- Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Oslo 0317, Norway
| | - James M Roe
- Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Oslo 0317, Norway
| | - Liisa Raud
- Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Oslo 0317, Norway
| | - Hedda T Ness
- Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Oslo 0317, Norway
| | - Line Folvik
- Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Oslo 0317, Norway
| | - Inge Amlien
- Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Oslo 0317, Norway
| | - Oliver M Geier
- Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Oslo 0317, Norway; Department of Diagnostic Physics, Division of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
| | - Øystein Sørensen
- Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Oslo 0317, Norway
| | - Didac Vidal-Piñeiro
- Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Oslo 0317, Norway
| | - Kristine B Walhovd
- Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Oslo 0317, Norway; Department of Radiology and Nuclear Medicine, University of Oslo, Oslo 0317, Norway
| | - Anders M Fjell
- Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Oslo 0317, Norway; Department of Radiology and Nuclear Medicine, University of Oslo, Oslo 0317, Norway
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Liu Z, Xia H, Chen A. Impaired brain ability of older adults to transit and persist to latent states with well-organized structures at wakeful rest. GeroScience 2025; 47:1761-1776. [PMID: 39361232 PMCID: PMC11979083 DOI: 10.1007/s11357-024-01366-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2024] [Accepted: 09/24/2024] [Indexed: 11/16/2024] Open
Abstract
The intrinsic brain functional network organization continuously changes with aging. By integrating spatial and temporal information, the process of how brain networks temporally reconfigure and remain well-organized spatial structure largely reflects the brain function, thereby holds the potential to capture its age-related declines. In this study, we examined the spatiotemporal brain dynamics from resting-state functional Magnetic Resonance Imaging (fMRI) data of healthy young and older adults using a Hidden Markov Model (HMM). Six brain states were generated by HMM, with the young group showing higher fractional occupancy and mean dwell time in states 1, 3, and 4 (SY1, SY2 and SY3), and the older group in states 2, 5, and 6 (SO1, SO2 and SO3). Importantly, comparisons of transition probabilities revealed that the older group showed a reduced brain ability to transition into states dominated by the younger group, as well as a diminished capacity to persist in them. Moreover, graph analysis revealed that these young-specific states exhibited higher modularity and k-coreness. Collectively, these findings suggested that the older group showed impaired brain ability of both transition into and sustain well spatially organized states. This emphasized that the temporal changes in brain state organization, rather than its static mode, could be a key biomarker for detecting age-related functional decline. These insights may pave the way for targeted interventions aimed at mitigating cognitive decline in the aging population.
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Affiliation(s)
- Zijin Liu
- School of Psychology, Research Center for Exercise and Brain Science, Shanghai University of Sport, Shanghai, 200082, China
| | - Haishuo Xia
- Faculty of Psychology, Southwest University, Chongqing, 400700, China
| | - Antao Chen
- Faculty of Psychology, Southwest University, Chongqing, 400700, China.
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Doucet GE, Goldsmith C, Myers K, Rice DL, Ende G, Pavelka DJ, Joliot M, Calhoun VD, Wilson TW, Uddin LQ. Dev-Atlas: A reference atlas of functional brain networks for typically developing adolescents. Dev Cogn Neurosci 2025; 72:101523. [PMID: 39938145 PMCID: PMC11870229 DOI: 10.1016/j.dcn.2025.101523] [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: 08/20/2024] [Revised: 11/20/2024] [Accepted: 01/21/2025] [Indexed: 02/14/2025] Open
Abstract
It is well accepted that the brain is functionally organized into multiple networks and extensive literature has demonstrated that the organization of these networks shows major changes during adolescence. Yet, there is limited option for a reference functional brain atlas derived from typically-developing adolescents, which is problematic as the reliable identification of functional brain networks crucially depends on the use of such reference functional atlases. In this context, we utilized resting-state functional MRI data from 1391 typically-developing youth aged 8-17 years to create an adolescent-specific reference atlas of functional brain networks. We further investigated the impact of age and sex on these networks. Using a multiscale individual component clustering algorithm, we identified 24 reliable functional brain networks, classified within six domains: Default-Mode (5 networks), Control (4 networks), Salience (3 networks), Attention (4 networks), Somatomotor (5 networks), and Visual (3 networks). We identified reliable and large effects of age on the spatial topography of these majority of networks, as well as on the functional network connectivity. Sex effects were not as widespread. We created a novel brain atlas, named Dev-Atlas, focused on a typically-developing sample, with the hope that this atlas can be used in future developmental neuroscience studies.
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Affiliation(s)
- Gaelle E Doucet
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, USA; Center for Pediatric Brain Health, Boys Town National Research Hospital, Boys Town, NE, USA; Department of Pharmacology and Neuroscience, Creighton University School of Medicine, Omaha, NE, USA.
| | - Callum Goldsmith
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, USA
| | - Katrina Myers
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, USA
| | - Danielle L Rice
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, USA
| | - Grace Ende
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, USA
| | - Derek J Pavelka
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, USA
| | - Marc Joliot
- Groupe d'Imagerie Neurofonctionelle-Institut des maladies neurodégénératives (GIN-IMN) UMR 5293, Bordeaux University, CNRS, CEA, Bordeaux, France
| | - Vince D Calhoun
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA, USA
| | - Tony W Wilson
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, USA; Center for Pediatric Brain Health, Boys Town National Research Hospital, Boys Town, NE, USA; Department of Pharmacology and Neuroscience, Creighton University School of Medicine, Omaha, NE, USA
| | - Lucina Q Uddin
- Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, CA, USA; Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, USA; Department of Psychology, University of California Los Angeles, Los Angeles, CA, USA
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9
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Xu H, Liu Y, Li C, Li X, Shen L, Wang H, Liu F, Zou J, Xia Y, Huang W, Liu Y, Gao Z, Fu Y, Wang F, Huang S, Song Z, Song F, Gao Y, Peng Y, Zou J, Zhu H, Liu S, Li L, Zhu X, Xiong Y, Hu Y, Yang J, Li Y, Gao F, Guo Q, Huang H, Zhang W, Li J, Chen Y, Dong P, Yang J, Lv J, Wang P, Sun Y, Qian B, Yaffe K, Guan J, Yi H, Leng Y, Yin S. Effects of Continuous Positive Airway Pressure on Neuroimaging Biomarkers and Cognition in Adult Obstructive Sleep Apnea: A Randomized Controlled Trial. Am J Respir Crit Care Med 2025; 211:628-636. [PMID: 39998447 DOI: 10.1164/rccm.202406-1170oc] [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: 06/14/2024] [Accepted: 02/25/2025] [Indexed: 02/26/2025] Open
Abstract
Rationale: Obstructive sleep apnea (OSA) is associated with cognitive impairment. The effects of continuous positive airway pressure (CPAP) on neuroimaging biomarkers and cognitive performance among middle-aged patients with OSA and normal cognition remain unclear. Objectives: To investigate the effects of CPAP therapy over 12 months on neuroimaging biomarkers and cognitive performance. Methods: In this multicenter, randomized clinical trial, we randomly assigned 148 participants with normal cognition and an apnea-hypopnea index ⩾15/h into two groups: patients receiving CPAP with best supportive care (BSC); and patients receiving BSC alone. The primary endpoint was Montreal Cognitive Assessment (MoCA) score at 6 months after enrollment. The secondary endpoints were intranetwork functional connectivity (FC) of default mode network (DMN) and cortical thickness assessed by functional and structural magnetic resonance imaging, other neuroimaging biomarkers, and neurobehavioral tests. Measurements and Main Results: Between 2017 and 2021, 148 patients were recruited from five hospitals. Linear mixed models showed that there was no significant difference in MoCA scores at 6 months between the CPAP and BSC groups (difference, -0.04; 95% confidence interval [CI], -0.72 to 0.65; P = 0.91). However, there were significant differences in the FC of DMN (difference, -13.73; 95% CI, -23.40 to -4.06; P = 0.01) and cortical thickness (difference, -0.06 mm; 95% CI, -0.10 to -0.01 mm; P = 0.02) between CPAP and BSC groups at 6 months after treatment. No serious adverse events occurred. Conclusions: CPAP improved cortical thickness and FC of DMN, suggesting that patients with OSA may recover from brain atrophic processes after CPAP treatment. However, no improvement in MoCA was found. Clinical trial registered with www.clinicaltrials.gov (NCT02886156).
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Affiliation(s)
- Huajun Xu
- Department of Otolaryngology-Head and Neck Surgery, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yupu Liu
- Department of Otolaryngology-Head and Neck Surgery, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Chenyang Li
- Department of Otolaryngology-Head and Neck Surgery, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xinyi Li
- Department of Otolaryngology-Head and Neck Surgery, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | | | - Hui Wang
- Department of Otolaryngology-Head and Neck Surgery, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Feng Liu
- Department of Otolaryngology-Head and Neck Surgery, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Juanjuan Zou
- Department of Otolaryngology-Head and Neck Surgery, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Department of Otorhinolaryngology and
- National Health Commission (NHC) Key Laboratory of Otorhinolaryngology, Shandong University Affiliated Qilu Hospital, Jinan, China
| | - Yunyan Xia
- Department of Otolaryngology-Head and Neck Surgery, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Department of Otolaryngology-Head and Neck Surgery, First Affiliated Hospital of Nanchang University, Jiangxi, China
| | - Weijun Huang
- Department of Otolaryngology-Head and Neck Surgery, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yuenan Liu
- Department of Otolaryngology-Head and Neck Surgery, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Zhenfei Gao
- Department of Otolaryngology-Head and Neck Surgery, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yiqun Fu
- Department of Otolaryngology-Head and Neck Surgery, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Fan Wang
- Department of Otolaryngology-Head and Neck Surgery, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Shujian Huang
- Department of Otolaryngology-Head and Neck Surgery, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Zhiyuan Song
- Department of Otolaryngology-Head and Neck Surgery, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Department of Otolaryngology Head and Neck Surgery, Huashan Hospital, Fudan University, Shanghai, China
| | - Fan Song
- Department of Otolaryngology-Head and Neck Surgery, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Department of Otolaryngology, Head and Neck Surgery, Shanghai General Hospital
| | - Yiqing Gao
- Department of Otolaryngology-Head and Neck Surgery, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yu Peng
- Department of Otolaryngology-Head and Neck Surgery, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jianyin Zou
- Department of Otolaryngology-Head and Neck Surgery, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Huaming Zhu
- Department of Otolaryngology-Head and Neck Surgery, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Suru Liu
- Department of Otolaryngology-Head and Neck Surgery, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Linpeng Li
- Department of Otolaryngology-Head and Neck Surgery, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xiaoyue Zhu
- Department of Otolaryngology-Head and Neck Surgery, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yuanping Xiong
- Department of Otolaryngology-Head and Neck Surgery, First Affiliated Hospital of Nanchang University, Jiangxi, China
| | - Yuli Hu
- Nursing Department of Otolaryngology Head and Neck Surgery
- Center of Sleep Medicine
| | - Jiaxin Yang
- Nursing Department of Otolaryngology Head and Neck Surgery
- Center of Sleep Medicine
| | | | - Feng Gao
- Department of Clinical Laboratory, and
| | - Qihao Guo
- Department of Gerontology, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Hengye Huang
- Department of Epidemiology, School of Public Health
| | | | - Jiping Li
- Department of Otorhinolaryngology, Renji Hospital
| | - Yanqing Chen
- Department of Otorhinolaryngology, Renji Hospital
| | - Pin Dong
- Department of Otolaryngology, Head and Neck Surgery, Shanghai General Hospital
| | - Jun Yang
- Department of Otorhinolaryngology-Head and Neck Surgery, Xinhua Hospital, and
| | - Jingrong Lv
- Department of Otorhinolaryngology-Head and Neck Surgery, Xinhua Hospital, and
| | - Peihua Wang
- Department of Otorhinolaryngology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; and
| | - Yiyuan Sun
- Department of Otorhinolaryngology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; and
| | - Biyun Qian
- School of Public Health, Hongqiao International Institute of Medicine, Shanghai Tong Ren Hospital
| | - Kristine Yaffe
- Department of Psychiatry
- Department of Neurology
- Department of Epidemiology, and
| | - Jian Guan
- Department of Otolaryngology-Head and Neck Surgery, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Hongliang Yi
- Department of Otolaryngology-Head and Neck Surgery, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yue Leng
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, California
| | - Shankai Yin
- Department of Otolaryngology-Head and Neck Surgery, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
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10
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Carpenter CM, Mullin HA, Cwiek A, Carter E, Vervoordt S, Lan X, Dennis NA, Rabinowitz A, Venkatesan UM, Hillary FG. Hippocampal network connectivity and episodic memory in individuals aging with traumatic brain injury. Brain Imaging Behav 2025; 19:433-445. [PMID: 39982608 DOI: 10.1007/s11682-025-00979-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/06/2025] [Indexed: 02/22/2025]
Abstract
Aging is associated with marked declines in episodic memory corresponding with decreased volume in studies of morphology and reduced network response in studies of functional connectomics. Furthermore, recent research has demonstrated that reductions in resting state network connectivity are related to declines in episodic memory, specifically in the default mode and frontoparietal cortical networks. Additionally, the interactive effects of aging and traumatic brain injury (TBI) are associated with increased risk for neurodegeneration and episodic memory impairments. However, there is a gap in the literature examining episodic memory and hippocampal-subcortical resting state connectivity differences related to aging with and without TBI. The current work aims to investigate episodic memory differences between older adults with TBI (N = 45) and older adults with no history of TBI (N = 28) and how that relates to hippocampal-subcortical network differences at rest. We demonstrate a positive relationship between default mode and frontoparietal network connectivity and memory performance differentially between those aging with and without moderate-severe TBI (msTBI). Additionally, we demonstrate that reliability in the strength of resting state functional connectivity between parcellations is weakest among connections to the hippocampus compared to other cortical connections but is generally reliable across other connections.
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Affiliation(s)
| | - Hollie A Mullin
- The Pennsylvania State University, State College, University Park, USA
| | - Andrew Cwiek
- The Pennsylvania State University, State College, University Park, USA
| | - Emily Carter
- The Pennsylvania State University, State College, University Park, USA
| | | | - Xinhui Lan
- The Pennsylvania State University, State College, University Park, USA
| | - Nancy A Dennis
- The Pennsylvania State University, State College, University Park, USA
| | - Amanda Rabinowitz
- Moss Rehabilitation Research Institute, Philadelphia, USA
- Sidney Kimmel Medical College at Thomas Jefferson University, Philadelphia, USA
| | - Umesh M Venkatesan
- Moss Rehabilitation Research Institute, Philadelphia, USA
- Sidney Kimmel Medical College at Thomas Jefferson University, Philadelphia, USA
| | - Frank G Hillary
- The Pennsylvania State University, State College, University Park, USA.
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11
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Nolin SA, Faulkner ME, Stewart P, Fleming LL, Merritt S, Rezaei RF, Bharadwaj PK, Franchetti MK, Raichlen DA, Jessup CJ, Edwards L, Hishaw GA, Van Etten EJ, Trouard TP, Geldmacher D, Wadley VG, Alperin N, Porges ES, Woods AJ, Cohen RA, Levin BE, Rundek T, Alexander GE, Visscher KM. Network segregation is associated with processing speed in the cognitively healthy oldest-old. eLife 2025; 14:e78076. [PMID: 40137179 PMCID: PMC12097785 DOI: 10.7554/elife.78076] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Accepted: 01/07/2025] [Indexed: 03/27/2025] Open
Abstract
The brain is organized into systems and networks of interacting components. The functional connections among these components give insight into the brain's organization and may underlie some cognitive effects of aging. Examining the relationship between individual differences in brain organization and cognitive function in older adults who have reached oldest-old ages with healthy cognition can help us understand how these networks support healthy cognitive aging. We investigated functional network segregation in 146 cognitively healthy participants aged 85+ in the McKnight Brain Aging Registry (MBAR). We found that the segregation of the association system and the individual networks within the association system (the fronto-parietal network , cingulo-opercular network, and default mode network), has strong associations with overall cognition and processing speed. We also provide a healthy oldest-old (85+) cortical parcellation that can be used in future work in this age group. This study shows that network segregation of the oldest-old brain is closely linked to cognitive performance. This work adds to the growing body of knowledge about differentiation in the aged brain by demonstrating that cognitive ability is associated with differentiated functional networks in very old individuals representing successful cognitive aging.
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Affiliation(s)
- Sara A Nolin
- University of Alabama at Birmingham Heersink School of Medicine and Evelyn F. McKnight Brain InstituteBirminghamUnited States
| | - Mary E Faulkner
- University of Alabama at Birmingham Heersink School of Medicine and Evelyn F. McKnight Brain InstituteBirminghamUnited States
| | - Paul Stewart
- University of Alabama at Birmingham Heersink School of Medicine and Evelyn F. McKnight Brain InstituteBirminghamUnited States
| | - Leland L Fleming
- University of Alabama at Birmingham Heersink School of Medicine and Evelyn F. McKnight Brain InstituteBirminghamUnited States
| | - Stacy Merritt
- University of Miami Miller School of Medicine and Evelyn F.McKnight Brain InstituteMiamiUnited States
| | - Roxanne F Rezaei
- University of Florida and Evelyn F. and William L.McKnight Brain InstituteGainesvilleUnited States
| | | | | | | | - Cortney J Jessup
- University of Arizona and Evelyn F. McKnightBrain InstituteTucsonUnited States
| | - Lloyd Edwards
- University of Alabama at Birmingham Heersink School of Medicine and Evelyn F. McKnight Brain InstituteBirminghamUnited States
| | - G Alex Hishaw
- University of Arizona and Evelyn F. McKnightBrain InstituteTucsonUnited States
| | - Emily J Van Etten
- University of Arizona and Evelyn F. McKnightBrain InstituteTucsonUnited States
| | - Theodore P Trouard
- University of Arizona and Evelyn F. McKnightBrain InstituteTucsonUnited States
| | - David Geldmacher
- University of Alabama at Birmingham Heersink School of Medicine and Evelyn F. McKnight Brain InstituteBirminghamUnited States
| | - Virginia G Wadley
- University of Alabama at Birmingham Heersink School of Medicine and Evelyn F. McKnight Brain InstituteBirminghamUnited States
| | - Noam Alperin
- University of Miami Miller School of Medicine and Evelyn F.McKnight Brain InstituteMiamiUnited States
| | - Eric S Porges
- University of Florida and Evelyn F. and William L.McKnight Brain InstituteGainesvilleUnited States
| | - Adam J Woods
- University of Florida and Evelyn F. and William L.McKnight Brain InstituteGainesvilleUnited States
| | - Ron A Cohen
- University of Florida and Evelyn F. and William L.McKnight Brain InstituteGainesvilleUnited States
| | - Bonnie E Levin
- University of Miami Miller School of Medicine and Evelyn F.McKnight Brain InstituteMiamiUnited States
| | - Tatjana Rundek
- University of Miami Miller School of Medicine and Evelyn F.McKnight Brain InstituteMiamiUnited States
| | - Gene E Alexander
- University of Arizona and Evelyn F. McKnightBrain InstituteTucsonUnited States
| | - Kristina M Visscher
- University of Alabama at Birmingham Heersink School of Medicine and Evelyn F. McKnight Brain InstituteBirminghamUnited States
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12
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Lien CH, Vande Casteele T, Laroy M, G A Van Cauwenberge M, Peeters R, Sunaert S, Van Laere K, Dupont P, Bouckaert F, Emsell L, Vandenbulcke M, Van den Stock J. Are resting-state network alterations in late-life depression related to synaptic density? Findings of a combined 11C-UCB-J PET and fMRI study. Cereb Cortex 2025; 35:bhaf028. [PMID: 40072885 DOI: 10.1093/cercor/bhaf028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2024] [Revised: 12/16/2024] [Accepted: 01/07/2025] [Indexed: 03/14/2025] Open
Abstract
This study investigates the relationship between resting-state functional magnetic resonance imaging (rs-fMRI) topological properties and synaptic vesicle glycoprotein 2A (SV2A) positron emission tomography (PET) synaptic density (SD) in late-life depression (LLD). 18 LLD patients and 33 healthy controls underwent rs-fMRI, 3D T1-weighted MRI, and 11C-UCB-J PET scans to assess SD. The rs-fMRI data were utilized to construct weighted networks for calculating four global topological metrics, including clustering coefficient, characteristic path length, global efficiency, and small-worldness, and six nodal metrics, including nodal clustering coefficient, nodal characteristic path length, nodal degree, nodal strength, local efficiency, and betweenness centrality. The 11C-UCB-J PET provided standardized uptake value ratios as SD measures. LLD patients exhibited preserved global topological organization, with reduced nodal properties in regions associated with LLD, such as the medial prefrontal cortex (mPFC), and increased nodal properties in the basal ganglia and cerebellar regions. Notably, a negative correlation was observed between betweenness centrality in the mPFC and depressive symptom severity. No significant alterations in SD or associations between rs-fMRI topological properties and SD were found, challenging the hypothesis that SD alterations are the molecular basis for rs-fMRI topological changes in LLD. Our findings suggest other molecular mechanisms may underlie the observed functional connectivity alterations in these patients.
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Affiliation(s)
- Chih-Hao Lien
- Neuropsychiatry, Department of Neurosciences, Leuven Brain Institute, KU Leuven, Herestraat 49, B-3000 Leuven, Belgium
| | - Thomas Vande Casteele
- Neuropsychiatry, Department of Neurosciences, Leuven Brain Institute, KU Leuven, Herestraat 49, B-3000 Leuven, Belgium
| | - Maarten Laroy
- Neuropsychiatry, Department of Neurosciences, Leuven Brain Institute, KU Leuven, Herestraat 49, B-3000 Leuven, Belgium
| | - Margot G A Van Cauwenberge
- Neuropsychiatry, Department of Neurosciences, Leuven Brain Institute, KU Leuven, Herestraat 49, B-3000 Leuven, Belgium
- Neurology, University Hospitals Leuven, Herestraat 49, B-3000 Leuven, Belgium
| | - Ronald Peeters
- Translational MRI, Department of Imaging and Pathology, Leuven Brain Institute, KU Leuven, Herestraat 49, B-3000 Leuven, Belgium
| | - Stefan Sunaert
- Translational MRI, Department of Imaging and Pathology, Leuven Brain Institute, KU Leuven, Herestraat 49, B-3000 Leuven, Belgium
- Radiology, University Hospitals Leuven, Herestraat 49, B-3000 Leuven, Belgium
| | - Koen Van Laere
- Nuclear Medicine, Department of Imaging and Pathology, Leuven Brain Institute, KU Leuven, Herestraat 49, B-3000 Leuven, Belgium
- Nuclear Medicine, University Hospitals Leuven, Herestraat 49, B-3000 Leuven, Belgium
| | - Patrick Dupont
- Laboratory for Cognitive Neurology, Department of Neurosciences, Leuven Brain Institute, KU Leuven, Herestraat 49, B-3000 Leuven, Belgium
| | - Filip Bouckaert
- Neuropsychiatry, Department of Neurosciences, Leuven Brain Institute, KU Leuven, Herestraat 49, B-3000 Leuven, Belgium
- University Psychiatric Center, Geriatric Psychiatry, Herestraat 49, KU Leuven, B-3000 Leuven, Belgium
| | - Louise Emsell
- Neuropsychiatry, Department of Neurosciences, Leuven Brain Institute, KU Leuven, Herestraat 49, B-3000 Leuven, Belgium
- Translational MRI, Department of Imaging and Pathology, Leuven Brain Institute, KU Leuven, Herestraat 49, B-3000 Leuven, Belgium
- University Psychiatric Center, Geriatric Psychiatry, Herestraat 49, KU Leuven, B-3000 Leuven, Belgium
| | - Mathieu Vandenbulcke
- Neuropsychiatry, Department of Neurosciences, Leuven Brain Institute, KU Leuven, Herestraat 49, B-3000 Leuven, Belgium
- University Psychiatric Center, Geriatric Psychiatry, Herestraat 49, KU Leuven, B-3000 Leuven, Belgium
| | - Jan Van den Stock
- Neuropsychiatry, Department of Neurosciences, Leuven Brain Institute, KU Leuven, Herestraat 49, B-3000 Leuven, Belgium
- University Psychiatric Center, Geriatric Psychiatry, Herestraat 49, KU Leuven, B-3000 Leuven, Belgium
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13
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Perez DC, Hernandez JJ, Wulfekuhle G, Gratton C. Variation in brain aging: A review and perspective on the utility of individualized approaches to the study of functional networks in aging. Neurobiol Aging 2025; 147:68-87. [PMID: 39709668 PMCID: PMC11793866 DOI: 10.1016/j.neurobiolaging.2024.11.010] [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: 02/28/2024] [Revised: 11/15/2024] [Accepted: 11/26/2024] [Indexed: 12/24/2024]
Abstract
Healthy aging is associated with cognitive decline across multiple domains, including executive function, memory, and attention. These cognitive changes can often influence an individual's ability to function and quality of life. However, the degree to which individuals experience cognitive decline, as well as the trajectory of these changes, exhibits wide variability across people. These cognitive abilities are thought to depend on the coordinated activity of large-scale networks. Like behavioral effects, large variation can be seen in brain structure and function with aging, including in large-scale functional networks. However, tracking this variation requires methods that reliably measure individual brain networks and their changes over time. Here, we review the literature on age-related cognitive decline and on age-related differences in brain structure and function. We focus particularly on functional networks and the individual variation that exists in these measures. We propose that novel individual-centered fMRI approaches can shed new light on patterns of inter- and intra-individual variability in aging. These approaches may be instrumental in understanding the neural bases of cognitive decline.
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Affiliation(s)
- Diana C Perez
- Department of Psychology, Northwestern University, Evanston, IL, USA.
| | - Joanna J Hernandez
- Department of Psychology, Northwestern University, Evanston, IL, USA; Department of Psychology, Harvard University, Cambridge, MA, USA
| | - Gretchen Wulfekuhle
- Department of Psychology, Florida State University, Tallahassee, FL, USA; University of North Carolina, Chapel Hill, NC, USA
| | - Caterina Gratton
- Department of Psychology, Northwestern University, Evanston, IL, USA; Department of Psychology, Florida State University, Tallahassee, FL, USA; University of Illinois Urbana-Champaign, Champaign, IL, USA
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14
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Sansare A, Magalhaes TNC, Bernard JA. Relationships of functional connectivity of motor cortex, primary somatosensory cortex, and cerebellum to balance performance in middle-aged and older adults. Neurobiol Aging 2025; 147:1-11. [PMID: 39637518 PMCID: PMC11973825 DOI: 10.1016/j.neurobiolaging.2024.11.009] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2024] [Revised: 11/20/2024] [Accepted: 11/21/2024] [Indexed: 12/07/2024]
Abstract
Connectivity of somatosensory cortex (S1) and cerebellum with the motor cortex (M1) is critical for balance control. While both S1-M1 and cerebellar-M1 connections are affected with aging, the implications of altered connectivity for balance control are not known. We investigated the relationship between S1-M1 and cerebellar-M1 connectivity and standing balance in middle-aged and older adults. Our secondary objective was to investigate how cognition affected the relationship between connectivity and balance. Our results show that greater S1-M1 and cerebellar-M1 connectivity was related to greater postural sway during standing. This may be indicative of an increase in functional recruitment of additional brain networks to maintain upright balance despite differences in network connectivity. Also, cognition moderated the relationship between S1-M1 connectivity and balance, such that those with lower cognition had a stronger relationship between connectivity and balance performance. It may be that individuals with poor cognition need increased recruitment of brain regions (compensation for cognitive declines) and in turn, higher wiring costs, which would be associated with increased functional connectivity.
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Affiliation(s)
- Ashwini Sansare
- Department of Kinesiology and Sports Management, Texas A&M University, USA
| | | | - Jessica A Bernard
- Department of Psychological and Brain Sciences, Texas A&M University, USA; Texas A&M Institute for Neuroscience, Texas A&M University, USA.
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15
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Du J, Elliott ML, Ladopoulou J, Eldaief MC, Buckner RL. Within-Individual Precision Mapping of Brain Networks Exclusively Using Task Data. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2025:2025.02.25.640090. [PMID: 40060474 PMCID: PMC11888310 DOI: 10.1101/2025.02.25.640090] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 03/14/2025]
Abstract
Precision mapping of brain networks within individuals has become a widely used tool that prevailingly relies on functional connectivity analysis of resting-state data. Here we explored whether networks could be precisely estimated solely using data acquired during active task paradigms. The straightforward strategy involved extracting residualized data after application of a task-based general linear model (GLM) and then applying standard functional connectivity analysis. Functional correlation matrices estimated from task data were highly similar to those derived from traditional resting-state fixation data. The largest factor affecting similarity between correlation matrices was the amount of data. Networks estimated within-individual from task data displayed strong spatial overlap with those estimated from resting-state fixation data and predicted the same triple functional dissociation in independent data. The implications of these findings are that (1) existing task data can be reanalyzed to estimate within-individual network organization, (2) resting-state fixation and task data can be pooled to increase statistical power, and (3) future studies can exclusively acquire task data to both estimate networks and extract task responses. Most broadly, the present results suggest that there is an underlying, stable network architecture that is idiosyncratic to the individual and persists across task states.
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Affiliation(s)
- Jingnan Du
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
| | - Maxwell L Elliott
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
| | - Joanna Ladopoulou
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
| | - Mark C Eldaief
- Department of Psychiatry, Massachusetts General Hospital, Charlestown, MA 02129, USA
| | - Randy L Buckner
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
- Department of Psychiatry, Massachusetts General Hospital, Charlestown, MA 02129, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129, USA
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16
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Wenuganen S, Walton KG, Travis FT, Stalder T, Wallace RK, Srivastava M, Fagan J. Possible Anti-Aging and Anti-Stress Effects of Long-Term Transcendental Meditation Practice: Differences in Gene Expression, EEG Correlates of Cognitive Function, and Hair Steroids. Biomolecules 2025; 15:317. [PMID: 40149853 PMCID: PMC11939949 DOI: 10.3390/biom15030317] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2024] [Revised: 02/08/2025] [Accepted: 02/11/2025] [Indexed: 03/29/2025] Open
Abstract
Background: Our previous comparison of peripheral blood mononuclear cells (PBMCs) from long-term Transcendental Meditation® (TM®) practitioners and matched non-practitioner controls found 200 differentially expressed (DE) genes. Bioinformatics analyses of these DE genes suggested a reduced risk of diseases associated with stress and aging in the TM group. Here we assessed additional signs of reduced stress and aging. Methods: A sample of 15 of the 200 DE genes was studied using qPCR in PBMCs from 40-year TM practitioners ("Old TM", n = 23) compared to a "Young Control" group (n = 19) and an "Old Control" group (n = 21) of non-meditators. In these three groups, plus a "Young TM", 12-year practitioner group (n = 26), we also studied EEG-based parameters of cognitive function (the Brain Integration Scale (BIS), and latency of three components of the event-related potential (ERP)). Finally, using LC/MS/MS, we compared persistent levels of cortisol (F) and its inactive congener, cortisone (E), in hair. Results: qPCR analysis showed that 13 of the 15 genes were more highly expressed in Old Controls than in Young Controls. In the Old TM group, 7 of these 13 were lower than in Old Controls. Both TM groups had higher BIS scores than their age-matched controls. The Old TM group had shorter N2, P3a, and P3b latencies than the Old Control group, and latencies in the Old TM group were not longer than in the Young Control group. The Hair F/Hair E ratio was higher in the control subgroups than in their age-matched TM subgroups, and Hair F was higher in the Young Control and combined control groups than in the Young TM and combined TM groups. Conclusions: These results are consistent with reductions in biomarkers of chronic stress and biological age in long-term TM meditators. They are also consistent with results from the previous study suggesting that TM practice lowers energy consumption or leads to more efficient energy metabolism.
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Affiliation(s)
- Supaya Wenuganen
- Center for Brain, Cognition and Consciousness, Maharishi International University, Fairfield, IA 52557, USA;
- Department of Physiology and Health, Maharishi International University, Fairfield, IA 52557, USA; (R.K.W.); (J.F.)
| | - Kenneth G. Walton
- Department of Physiology and Health, Maharishi International University, Fairfield, IA 52557, USA; (R.K.W.); (J.F.)
- Institute for Prevention Research, Maharishi International University, Fairfield, IA 52557, USA
| | - Frederick T. Travis
- Center for Brain, Cognition and Consciousness, Maharishi International University, Fairfield, IA 52557, USA;
| | - Tobias Stalder
- Department of Psychology, University of Siegen, 57076 Siegen, Germany;
| | - R. Keith Wallace
- Department of Physiology and Health, Maharishi International University, Fairfield, IA 52557, USA; (R.K.W.); (J.F.)
| | - Meera Srivastava
- Department of Anatomy, Physiology, and Genetics, Uniformed Services University of the Health Sciences, Bethesda, MD 20814, USA;
| | - John Fagan
- Department of Physiology and Health, Maharishi International University, Fairfield, IA 52557, USA; (R.K.W.); (J.F.)
- Health Research Institute, Fairfield, IA 52556, USA
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17
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Aditya S, Armitage L, Clarke A, Traynor V, Pappas E, Kanchanawong T, Lee WCC. Relationship Between Cognitive Abilities and Lower-Limb Movements: Can Analyzing Gait Parameters and Movements Help Detect Dementia? A Systematic Review. SENSORS (BASEL, SWITZERLAND) 2025; 25:813. [PMID: 39943452 PMCID: PMC11821030 DOI: 10.3390/s25030813] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/15/2024] [Revised: 01/24/2025] [Accepted: 01/27/2025] [Indexed: 02/16/2025]
Abstract
Identifying and diagnosing cognitive impairment remains challenging. Some diagnostic procedures are invasive, expensive, and not always accurate. Meanwhile, evidence suggests that cognitive impairment is associated with changes in gait parameters. Certain gait parameters manifesting differences between people with and without cognitive impairment are more pronounced when adding a secondary task (dual-task scenario). In this systematic review, the capability of gait analysis to identify cognitive impairment is investigated. Twenty-three studies published between 2014 and 2024 met the inclusion criteria. A significantly lower gait speed and cadence as well as higher gait variability were found in people with mild cognitive impairment (MCI) and/or dementia, compared with the group with no cognitive impairment. While dual tasks appeared to amplify the differences between the two populations, the type of secondary tasks (e.g., calculations and recalling phone numbers) had an effect on gait changes. The activity and volume of different brain regions were also different between the two populations during walking. In conclusion, while this systematic review supported the potential of using gait analysis to identify cognitive impairment, there are a number of parameters researchers need to consider such as gait variables to be studied, types of dual tasks, and analysis of brain changes while performing the movement tasks.
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Affiliation(s)
- Swapno Aditya
- School of Mechanical, Material, Mechatronics and Biomedical Engineering, University of Wollongong, Wollongong 2522, Australia; (S.A.); (L.A.)
- Advanced Mechatronics and Biomedical Engineering Research Group, University of Wollongong, Wollongong 2522, Australia
| | - Lucy Armitage
- School of Mechanical, Material, Mechatronics and Biomedical Engineering, University of Wollongong, Wollongong 2522, Australia; (S.A.); (L.A.)
- Advanced Mechatronics and Biomedical Engineering Research Group, University of Wollongong, Wollongong 2522, Australia
| | - Adam Clarke
- School of Psychology, University of Wollongong, Wollongong 2522, Australia;
| | - Victoria Traynor
- University of the Sunshine Coast Sunshine Coast 4560, Australia and Warrigal, Illawarra 2527, Australia;
| | - Evangelos Pappas
- School of Health and Biomedical Sciences, RMIT University, Melbourne 3001, Australia;
| | - Thanaporn Kanchanawong
- School of Computer Science and Information Technology, University of Wollongong, Wollongong 2522, Australia;
| | - Winson Chiu-Chun Lee
- School of Mechanical, Material, Mechatronics and Biomedical Engineering, University of Wollongong, Wollongong 2522, Australia; (S.A.); (L.A.)
- Advanced Mechatronics and Biomedical Engineering Research Group, University of Wollongong, Wollongong 2522, Australia
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18
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Yang G, Fan C, Li H, Tong Y, Lin S, Feng Y, Liu F, Bao C, Xie H, Wu Y. Resting-State Brain Network Characteristics Related to Mild Cognitive Impairment: A Preliminary fNIRS Proof-of-Concept Study. J Integr Neurosci 2025; 24:26406. [PMID: 40018781 DOI: 10.31083/jin26406] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2024] [Revised: 11/25/2024] [Accepted: 12/04/2024] [Indexed: 03/01/2025] Open
Abstract
BACKGROUND This study investigates the reliability of functional near-infrared spectroscopy (fNIRS) in detecting resting-state brain network characteristics in patients with mild cognitive impairment (MCI), focusing on static resting-state functional connectivity (sRSFC) and dynamic resting-state functional connectivity (dRSFC) patterns in MCI patients and healthy controls (HCs) without cognitive impairment. METHODS A total of 89 MCI patients and 83 HCs were characterized using neuropsychological scales. Subject sRSFC strength and dRSFC variability coefficients were evaluated via fNIRS. The study evaluated the feasibility of using fNIRS to measure these connectivity metrics and compared resting-state brain network characteristics between the two groups. Correlations with Montreal Cognitive Assessment (MoCA) scores were also explored. RESULTS sRSFC strength in homologous brain networks was significantly lower than in heterologous networks (p < 0.05). A significant negative correlation was also observed between sRSFC strength and dRSFC variability at both the group and individual levels (p < 0.001). While sRSFC strength did not differentiate between MCI patients and HCs, the dRSFC variability between the dorsal attention network (DAN) and default mode network (DMN), and between the ventral attention network (VAN) and visual network (VIS), emerged as sensitive biomarkers after false discovery rate correction (p < 0.05). No significant correlation was found between MoCA scores and connectivity measures. CONCLUSIONS fNIRS can be used to study resting-state brain networks, with dRSFC variability being more sensitive than sRSFC strength for discriminating between MCI patients and HCs. The DAN-DMN and VAN-VIS regions were found to be particularly useful for the identification of dRSFC differences between the two groups. CLINICAL TRIAL REGISTRATION ChiCTR2200057281, registered on 6 March, 2022; https://www.chictr.org.cn/showproj.html?proj=133808.
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Affiliation(s)
- Guohui Yang
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, 200040 Shanghai, China
- National Center for Neurological Disorders, Huashan Hospital, Fudan University, 200040 Shanghai, China
| | - Chenyu Fan
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, 200040 Shanghai, China
- National Center for Neurological Disorders, Huashan Hospital, Fudan University, 200040 Shanghai, China
| | - Haozheng Li
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, 200040 Shanghai, China
- National Center for Neurological Disorders, Huashan Hospital, Fudan University, 200040 Shanghai, China
| | - Yu Tong
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, 200040 Shanghai, China
- National Center for Neurological Disorders, Huashan Hospital, Fudan University, 200040 Shanghai, China
| | - Shuang Lin
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, 200040 Shanghai, China
- National Center for Neurological Disorders, Huashan Hospital, Fudan University, 200040 Shanghai, China
| | - Yashuo Feng
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, 200040 Shanghai, China
- National Center for Neurological Disorders, Huashan Hospital, Fudan University, 200040 Shanghai, China
- School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, 201203 Shanghai, China
| | - Fengzhi Liu
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, 200040 Shanghai, China
- National Center for Neurological Disorders, Huashan Hospital, Fudan University, 200040 Shanghai, China
| | - Chunrong Bao
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, 200030 Shanghai, China
| | - Hongyu Xie
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, 200040 Shanghai, China
- National Center for Neurological Disorders, Huashan Hospital, Fudan University, 200040 Shanghai, China
| | - Yi Wu
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, 200040 Shanghai, China
- National Center for Neurological Disorders, Huashan Hospital, Fudan University, 200040 Shanghai, China
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19
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Ishikawa H, Hoshino T, Hamanaka G, Mandeville ET, Guo S, Kimura S, Fukuda N, Li W, Shindo A, Sakadzic S, Harrington ME, Lo EH, Arai K. Effects of aging on diurnal transcriptome change in the mouse corpus callosum. iScience 2025; 28:111556. [PMID: 39845418 PMCID: PMC11750567 DOI: 10.1016/j.isci.2024.111556] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2024] [Revised: 06/06/2024] [Accepted: 12/05/2024] [Indexed: 01/24/2025] Open
Abstract
The corpus callosum, a major white matter region central to cognitive function, is vulnerable to aging. Using zeitgeber time (ZT) aligned with environmental light/dark cycles, we investigated temporal gene expression patterns in the corpus callosum of young (5-month-old) and aged (24-month-old) mice using RNA-seq. Comparative analysis revealed more differentially expressed genes across ZT pairs in young mice than aged mice. In addition, complement pathway genes, including C4b, C3, C1qa, C1qb, and C1qc, were consistently upregulated in aged mice regardless of ZT. Furthermore, genes such as Etnppl, Tinagl1, Hspa12b, Ppp1r3c, Thbd, Pla2g3, and Tsc22d3 exhibited ZT-dependent rhythmicity in young mice, but their rhythmic patterns were altered with age. This study provides an important dataset of the interplay between aging, diurnal rhythms, and gene expression in the corpus callosum, highlighting potential molecular mechanisms mediating white matter aging. Further investigation is warranted to dissect these gene's specific roles in neurological health during aging.
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Affiliation(s)
- Hidehiro Ishikawa
- Neuroprotection Research Laboratories, Departments of Radiology and Neurology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA 02129, USA
- Department of Neurology, Mie University Graduate School of Medicine, 2-174 Edobashi, Tsu, Mie 514-8507, Japan
| | - Tomonori Hoshino
- Neuroprotection Research Laboratories, Departments of Radiology and Neurology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA 02129, USA
| | - Gen Hamanaka
- Neuroprotection Research Laboratories, Departments of Radiology and Neurology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA 02129, USA
| | - Emiri T. Mandeville
- Neuroprotection Research Laboratories, Departments of Radiology and Neurology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA 02129, USA
| | - Shuzhen Guo
- Neuroprotection Research Laboratories, Departments of Radiology and Neurology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA 02129, USA
| | - Shintaro Kimura
- Neuroprotection Research Laboratories, Departments of Radiology and Neurology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA 02129, USA
| | - Norito Fukuda
- Neuroprotection Research Laboratories, Departments of Radiology and Neurology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA 02129, USA
| | - Wenlu Li
- Neuroprotection Research Laboratories, Departments of Radiology and Neurology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA 02129, USA
| | - Akihiro Shindo
- Department of Neurology, Mie University Graduate School of Medicine, 2-174 Edobashi, Tsu, Mie 514-8507, Japan
| | - Sava Sakadzic
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA 02129, USA
| | | | - Eng H. Lo
- Neuroprotection Research Laboratories, Departments of Radiology and Neurology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA 02129, USA
| | - Ken Arai
- Neuroprotection Research Laboratories, Departments of Radiology and Neurology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA 02129, USA
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20
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Ranjbar-Slamloo Y, Chong HR, Kamigaki T. Aging disrupts the link between network centrality and functional properties of prefrontal neurons during memory-guided behavior. Commun Biol 2025; 8:62. [PMID: 39820515 PMCID: PMC11739477 DOI: 10.1038/s42003-025-07498-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2024] [Accepted: 01/08/2025] [Indexed: 01/19/2025] Open
Abstract
The prefrontal cortex (PFC) is vital for higher cognitive functions and displays neuronal heterogeneity, with neuronal activity varying significantly across individual neurons. Using calcium imaging in the medial PFC (mPFC) of mice, we investigate whether differences in degree centrality-a measure of connectivity strength within local circuits-could explain this neuronal diversity and its functional implications. In young adults, neurons with high degree centrality, inferred from resting-state activity, exhibit reliable and stable action-plan selectivity during memory-guided tasks, suggesting that connectivity strength is closely linked to functional heterogeneity. This relationship, however, deteriorates in middle-aged and older mice. A computational model simulating age-related declines in synaptic plasticity reproduces these results. In young adults, degree centrality also predicts cross-modal action-plan selectivity, but this predictive power diminishes with age. Furthermore, neurons with high action-plan selectivity are spatially clustered, a pattern that fades with aging. These findings reveal the significant aging impact on the network properties in parallel with the functional and spatial organization of the mPFC.
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Affiliation(s)
- Yadollah Ranjbar-Slamloo
- Neuroscience & Mental Health, Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, 308232, Singapore
| | - Huee Ru Chong
- Neuroscience & Mental Health, Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, 308232, Singapore
| | - Tsukasa Kamigaki
- Neuroscience & Mental Health, Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, 308232, Singapore.
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21
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Thovinakere N, Ghosh SS, Itturia-Medina Y, Geddes MR. Social Determinants of Health and Functional Brain Connectivity Predict Long-Term Physical Activity in Older Adults with a New Cardiovascular Diagnosis. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2025:2024.09.30.24314678. [PMID: 39830285 PMCID: PMC11741470 DOI: 10.1101/2024.09.30.24314678] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 01/22/2025]
Abstract
Background Physical activity is essential for preventing cognitive decline, stroke and dementia in older adults. A new cardiovascular diagnosis offers a critical window for positive lifestyle changes. However, sustaining physical activity behavior change remains challenging and the underlying mechanisms are poorly understood. Methods To identify the neural, behavioral and contextual predictors of successful longer-term behavior change after a new cardiovascular diagnosis, we used support vector machine learning to predict changes in moderate-to-vigorous physical activity over four years in 295 cognitively unimpaired older adults from the UK Biobank, testing three models that incorporated baseline: (i) demographic, cognitive, and contextual factors, (ii) baseline resting-state functional connectivity alone, and (iii) combined multimodal features across all predictors. Results The combined multi-modal model had the highest predictive power (r=0.28, p=0.001). Key predictors included greenspace access, social support, retirement status, executive function, and between-network functional connectivity within the default mode, frontoparietal control and salience/ventral attention networks. Conclusions These findings underscore the importance of social and structural determinants of health and uncover neural mechanisms that may support lifestyle modifications. In addition to furthering our understanding of the mechanisms underlying successful physical activity behavior change, these findings help to guide the design of interventions and health policy with the ultimate goal of preventing cardiovascular disease burden and late-life cognitive decline.
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Affiliation(s)
- Nagashree Thovinakere
- The Neuro, Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, QC, Canada
- Rotman Research Institute, University of Toronto, Toronto, Canada
| | - Satrajit S. Ghosh
- Program in Speech and Hearing Bioscience and Technology, Harvard Medical School, Boston, MA, USA
- Department of Otolaryngology-Head and Neck Surgery, Harvard Medical School, Boston, MA, USA
- McGovern Institute for Brain Research, MIT, Cambridge, MA, USA
| | - Yasser Itturia-Medina
- The Neuro, Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, QC, Canada
- McConnell Brain Imaging Centre (BIC), MNI, Faculty of Medicine, McGill University, Montreal, QC, Canada
- Ludmer Centre for Neuroinformatics & Mental Health, Montreal, Canada
| | - Maiya R. Geddes
- The Neuro, Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, QC, Canada
- Rotman Research Institute, University of Toronto, Toronto, Canada
- McGovern Institute for Brain Research, MIT, Cambridge, MA, USA
- McConnell Brain Imaging Centre (BIC), MNI, Faculty of Medicine, McGill University, Montreal, QC, Canada
- Centre for Studies in the Prevention of Alzheimer’s Disease, Douglas Mental Health Institute, McGill University, Montreal, QC, Canada
- McGill University Research Centre for Studies in Aging, McGill University, Montreal, QC, Canada
- Department of Psychology, Northeastern University, Boston, MA, USA
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22
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Mooraj Z, Salami A, Campbell KL, Dahl MJ, Kosciessa JQ, Nassar MR, Werkle-Bergner M, Craik FIM, Lindenberger U, Mayr U, Rajah MN, Raz N, Nyberg L, Garrett DD. Toward a functional future for the cognitive neuroscience of human aging. Neuron 2025; 113:154-183. [PMID: 39788085 DOI: 10.1016/j.neuron.2024.12.008] [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: 10/02/2024] [Revised: 12/08/2024] [Accepted: 12/10/2024] [Indexed: 01/12/2025]
Abstract
The cognitive neuroscience of human aging seeks to identify neural mechanisms behind the commonalities and individual differences in age-related behavioral changes. This goal has been pursued predominantly through structural or "task-free" resting-state functional neuroimaging. The former has elucidated the material foundations of behavioral decline, and the latter has provided key insight into how functional brain networks change with age. Crucially, however, neither is able to capture brain activity representing specific cognitive processes as they occur. In contrast, task-based functional imaging allows a direct probe into how aging affects real-time brain-behavior associations in any cognitive domain, from perception to higher-order cognition. Here, we outline why task-based functional neuroimaging must move center stage to better understand the neural bases of cognitive aging. In turn, we sketch a multi-modal, behavior-first research framework that is built upon cognitive experimentation and emphasizes the importance of theory and longitudinal design.
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Affiliation(s)
- Zoya Mooraj
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Lentzeallee 94, 14195 Berlin, Germany; Max Planck UCL Centre for Computational Psychiatry and Ageing Research, Lentzeallee 94, 14195 Berlin, Germany and Max Planck UCL Centre for Computational Psychiatry and Ageing Research, 10-12 Russell Square, London, WC1B 5Eh, UK.
| | - Alireza Salami
- Aging Research Center, Karolinska Institutet & Stockholm University, 17165 Stockholm, Sweden; Umeå Center for Functional Brain Imaging (UFBI), Umeå University, 90187 Umeå, Sweden; Department of Medical and Translational Biology, Umeå University, 90187 Umeå, Sweden; Wallenberg Center for Molecular Medicine, Umeå University, 90187 Umeå, Sweden
| | - Karen L Campbell
- Department of Psychology, Brock University, 1812 Sir Isaac Brock Way, St. Catharines, ON L2S 3A1, Canada
| | - Martin J Dahl
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Lentzeallee 94, 14195 Berlin, Germany; Max Planck UCL Centre for Computational Psychiatry and Ageing Research, Lentzeallee 94, 14195 Berlin, Germany and Max Planck UCL Centre for Computational Psychiatry and Ageing Research, 10-12 Russell Square, London, WC1B 5Eh, UK; Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA 90089, USA
| | - Julian Q Kosciessa
- Radboud University, Donders Institute for Brain, Cognition and Behaviour, 6525 GD Nijmegen, the Netherlands
| | - Matthew R Nassar
- Robert J. & Nancy D. Carney Institute for Brain Science, Brown University, Providence, RI 02912, USA; Department of Neuroscience, Brown University, 185 Meeting Street, Providence, RI 02912, USA
| | - Markus Werkle-Bergner
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Lentzeallee 94, 14195 Berlin, Germany
| | - Fergus I M Craik
- Rotman Research Institute at Baycrest, Toronto, ON M6A 2E1, Canada
| | - Ulman Lindenberger
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Lentzeallee 94, 14195 Berlin, Germany; Max Planck UCL Centre for Computational Psychiatry and Ageing Research, Lentzeallee 94, 14195 Berlin, Germany and Max Planck UCL Centre for Computational Psychiatry and Ageing Research, 10-12 Russell Square, London, WC1B 5Eh, UK
| | - Ulrich Mayr
- Department of Psychology, University of Oregon, Eugene, OR 97403, USA
| | - M Natasha Rajah
- Department of Psychiatry, McGill University Montreal, Montreal, QC H3A 1A1, Canada; Department of Psychology, Toronto Metropolitan University, Toronto, ON, M5B 2K3, Canada
| | - Naftali Raz
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Lentzeallee 94, 14195 Berlin, Germany; Department of Psychology, Stony Brook University, Stony Brook, NY 11794, USA
| | - Lars Nyberg
- Umeå Center for Functional Brain Imaging (UFBI), Umeå University, 90187 Umeå, Sweden; Department of Medical and Translational Biology, Umeå University, 90187 Umeå, Sweden; Department of Diagnostics and Intervention, Diagnostic Radiology, Umeå University, 90187 Umeå, Sweden
| | - Douglas D Garrett
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Lentzeallee 94, 14195 Berlin, Germany; Max Planck UCL Centre for Computational Psychiatry and Ageing Research, Lentzeallee 94, 14195 Berlin, Germany and Max Planck UCL Centre for Computational Psychiatry and Ageing Research, 10-12 Russell Square, London, WC1B 5Eh, UK.
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23
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Khan AF, Saleh N, Smith ZA. The Brain's Aging Resting State Functional Connectivity. J Integr Neurosci 2025; 24:25041. [PMID: 39862002 DOI: 10.31083/jin25041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2024] [Revised: 07/29/2024] [Accepted: 08/09/2024] [Indexed: 01/27/2025] Open
Abstract
Resting state networks (RSNs) of the brain are characterized as correlated spontaneous time-varying fluctuations in the absence of goal-directed tasks. These networks can be local or large-scale spanning the brain. The study of the spatiotemporal properties of such networks has helped understand the brain's fundamental functional organization under healthy and diseased states. As we age, these spatiotemporal properties change. Moreover, RSNs exhibit neural plasticity to compensate for the loss of cognitive functions. This narrative review aims to summarize current knowledge from functional magnetic resonance imaging (fMRI) studies on age-related alterations in RSNs. Underlying mechanisms influencing such changes are discussed. Methodological challenges and future directions are also addressed. By providing an overview of the current state of knowledge in this field, this review aims to guide future research endeavors aimed at promoting healthy brain aging and developing effective interventions for age-related cognitive impairment and neurodegenerative diseases.
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Affiliation(s)
- Ali F Khan
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA
| | - Nada Saleh
- Graduate College, University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA
| | - Zachary A Smith
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA
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24
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Thompson JL, Woods SP, Webber TA, Medina LD, Podell K, Yoshida H, Evans D, Ridgely NC, Babicz MA, Gomez EM, Mustafa A. Development of the Telephone-based Daily Instrumental Activities of Living (T-DIAL) to assess financial management remotely in older adults. NEUROPSYCHOLOGY, DEVELOPMENT, AND COGNITION. SECTION B, AGING, NEUROPSYCHOLOGY AND COGNITION 2025; 32:69-92. [PMID: 38727240 DOI: 10.1080/13825585.2024.2352900] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Accepted: 05/02/2024] [Indexed: 12/25/2024]
Abstract
The current study evaluated the reliability and validity of a novel, performance-based banking task in 60 younger (18-34 years) and 60 older (50-85 years) adults. All participants completed the Telephone-based Daily Instrumental Activities of Living (T-DIAL) using interactive voice response technology to complete a series of mock actions with a financial institution via telephone. The T-DIAL showed strong inter-rater reliability and internal consistency. T-DIAL accuracy was significantly and independently related to better self-reported instrumental activities of daily living and executive functions at a large effect size. Findings from this study provided preliminary supportive evidence for the reliability and validity of the T-DIAL, which had robust associations with manifest everyday functioning and higher-order cognitive ability. Future work is needed on the psychometrics (e.g. test-retest reliability, normative standards), and construct validity (e.g. diagnostic accuracy) of the T-DIAL in neurocognitive disorders and under-served communities for whom remote evaluations might be particularly relevant.
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Affiliation(s)
- Jennifer L Thompson
- Department of Psychology, University of Houston, Houston, TX, USA
- Psychology Department, West Los Angeles VA Medical Center, Los Angeles, CA, USA
| | | | - Troy A Webber
- Mental Health Care Line, Michael E. DeBakey VA Medical Center, Houston, TX, USA
- Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, USA
| | - Luis D Medina
- Department of Psychology, University of Houston, Houston, TX, USA
| | - Kenneth Podell
- Department of Neurology, Methodist Hospital, Houston, TX, USA
| | - Hanako Yoshida
- Department of Psychology, University of Houston, Houston, TX, USA
| | - Darrian Evans
- Health, University of Louisville Health, Louisville, KY, USA
| | | | - Michelle A Babicz
- Mental Health and Behavioral Science Service, James A. Haley Veterans' Hospital, Tampa, FL, USA
| | - Elliott M Gomez
- Department of Psychology, University of Houston, Houston, TX, USA
| | - Andrea Mustafa
- Department of Psychology, University of Houston, Houston, TX, USA
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25
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Tong Z, Xing C, Xu X, Xu J, Wu Y, Salvi R, Yin X, Zhao F, Chen Y, Cai Y. Impaired network organization in mild age-related hearing loss. MedComm (Beijing) 2025; 6:e70002. [PMID: 39760112 PMCID: PMC11695200 DOI: 10.1002/mco2.70002] [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: 01/25/2024] [Revised: 08/30/2024] [Accepted: 09/24/2024] [Indexed: 01/07/2025] Open
Abstract
Age-related hearing loss (ARHL) is considered one of the most common neurodegenerative disorders in the elderly; however, how it contributes to cognitive decline is poorly understood. With resting-state functional magnetic resonance imaging from 66 individuals with ARHL and 54 healthy controls, group spatial independent component analyses, sliding window analyses, graph-theory methods, multilayer networks, and correlation analyses were used to identify ARHL-induced disturbances in static and dynamic functional network connectivity (sFNC/dFNC), alterations in global network switching and their links to cognitive performances. ARHL was associated with decreased sFNC/dFNC within the default mode network (DMN) and increased sFNC/dFNC between the DMN and central executive, salience (SN), and visual networks. The variability in dFNC between the DMN and auditory network (AUN) and between the SN and AUN was decreased in ARHL. The individuals with ARHL had lower network switching rates than controls among global network nodes, especially in the DMN. Some disturbances within DMN were associated with disrupted executive and memory performance. The prolonged loss of sensory information associated with ARHL-induced compensatory within-network segregations and between-network integrations in the DMN might reduce network information processing and accelerate brain aging and cognitive decline.
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Affiliation(s)
- Zhaopeng Tong
- Department of OtolaryngologySun Yat‐sen Memorial HospitalSun Yat‐sen UniversityGuangzhouChina
- Institute of Hearing and Speech‐Language ScienceSun Yat‐sen UniversityGuangzhouChina
| | - Chunhua Xing
- Department of RadiologyNanjing First HospitalNanjing Medical UniversityNanjingChina
| | - Xiaomin Xu
- Department of RadiologyNanjing First HospitalNanjing Medical UniversityNanjingChina
| | - Jin‐Jing Xu
- Department of OtolaryngologyNanjing First HospitalNanjing Medical UniversityNanjingChina
| | - Yuanqing Wu
- Department of OtolaryngologyNanjing First HospitalNanjing Medical UniversityNanjingChina
| | - Richard Salvi
- Center for Hearing and DeafnessState University of New York at BuffaloBuffaloNew YorkUSA
| | - Xindao Yin
- Department of RadiologyNanjing First HospitalNanjing Medical UniversityNanjingChina
| | - Fei Zhao
- Department of Speech and Language Therapy and Hearing ScienceCardiff Metropolitan UniversityCardiffUK
| | - Yu‐Chen Chen
- Department of RadiologyNanjing First HospitalNanjing Medical UniversityNanjingChina
| | - Yuexin Cai
- Department of OtolaryngologySun Yat‐sen Memorial HospitalSun Yat‐sen UniversityGuangzhouChina
- Institute of Hearing and Speech‐Language ScienceSun Yat‐sen UniversityGuangzhouChina
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26
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Sintini I, Ali F, Stephens Y, Clark HM, Stierwalt JA, Machulda MM, Satoh R, Josephs KA, Whitwell JL. Functional connectivity abnormalities in clinical variants of progressive supranuclear palsy. Neuroimage Clin 2024; 45:103727. [PMID: 39719808 PMCID: PMC11728076 DOI: 10.1016/j.nicl.2024.103727] [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: 08/23/2024] [Revised: 11/07/2024] [Accepted: 12/16/2024] [Indexed: 12/26/2024]
Abstract
Progressive supranuclear palsy (PSP) can present with different clinical variants which show distinct, but partially overlapping, patterns of neurodegeneration and tau deposition in a network of regions including cerebellar dentate, superior cerebellar peduncle, midbrain, thalamus, basal ganglia, and frontal lobe. We sought to determine whether disruptions in functional connectivity within this PSP network measured using resting-state functional MRI (rs-fMRI) differed between PSP-Richardson's syndrome (PSP-RS) and the cortical and subcortical clinical variants of PSP. Structural MRI and rs-fMRI scans were collected for 36 PSP-RS, 25 PSP-cortical and 34 PSP-subcortical participants who met the Movement Disorder Society PSP clinical criteria. Ninety participants underwent flortaucipir-PET scans. MRIs were processed using CONN Toolbox. Functional connectivity between regions of the PSP network was compared between each PSP group and 83 healthy controls, and between the PSP groups, covarying for age. The effect of flortaucipir uptake and clinical scores on connectivity was assessed. Connectivity was reduced in PSP-RS compared to controls throughout the network, involving cerebellar dentate, midbrain, basal ganglia, thalamus, and frontal regions. Frontal regions showed reduced connectivity to other regions in the network in PSP-cortical, particularly the thalamus, caudate and substantia nigra. Disruptions in connectivity in PSP-subcortical were less pronounced, with the strongest disruption between the pallidum and striatum. There was moderate evidence that elevated subcortical flortaucipir uptake correlated with both increased and reduced connectivity between regions of the PSP network. Lower connectivity within the PSP network correlated with worse performance on clinical tests, including PSP rating scale. Patterns of disrupted functional connectivity revealed both variant-specific and shared disease pathways within the PSP network among PSP clinical variants, providing insight into disease heterogeneity.
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Affiliation(s)
- Irene Sintini
- Department of Radiology, Mayo Clinic, Rochester, MN, USA.
| | - Farwa Ali
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | | | | | | | - Mary M Machulda
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, USA
| | - Ryota Satoh
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
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27
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Li K, Zhang R, Feng T. Functional connectivity in procrastination and emotion regulation. Brain Cogn 2024; 182:106240. [PMID: 39515273 DOI: 10.1016/j.bandc.2024.106240] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2024] [Revised: 11/04/2024] [Accepted: 11/04/2024] [Indexed: 11/16/2024]
Abstract
Procrastination, an irrational delay of intended action, leads to numerous adverse effects in many life domains, such as low academic performance, poor mental health, and financial distress. Previous studies have revealed a substantial negative correlation between emotional regulation and procrastination. However, the neural basis for the association between emotion regulation and procrastination remains unclear. Therefore, we employed the voxel-based morphometry (VBM) and resting-state functional connectivity (RSFC) methods to explore the neural substrates underlying how emotion regulation is responsible for procrastination (N = 243). In line with our hypothesis, the results showed a significant negative correlation between emotion regulation ability and procrastination. Additionally, the VBM analysis showed that emotion regulation ability was positively correlated with gray matter (GM) volumes in the right dorsal-lateral prefrontal cortex (dlPFC). The mediation analysis revealed that emotion regulation ability mediated the relationship between the GM volumes of the right dlPFC and procrastination. Furthermore, the RSFC results indicated that right dlPFC-left insula functional connectivity was positively associated with emotion regulation ability. Emotion regulation ability further mediated the relationship between the right dlPFC-left insula functional connectivity and procrastination. The current findings suggest that the neural pathway related to cognitive control over aversive emotion may be responsible for the close relationship between emotion regulation and procrastination, which provides a novel perspective for explaining the tight association between emotion regulation and procrastination.
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Affiliation(s)
- Keli Li
- Faculty of Psychology, Southwest University, Chongqing, China.
| | - Rong Zhang
- Faculty of Psychology, Southwest University, Chongqing, China.
| | - Tingyong Feng
- Faculty of Psychology, Southwest University, Chongqing, China; Key Laboratory of Cognition and Personality, Ministry of Education, Chongqing, China.
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28
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Fleming LL, Defenderfer MK, Demirayak P, Stewart P, Decarlo DK, Visscher KM. Impact of Deprivation and Preferential Usage on Functional Connectivity Between Early Visual Cortex and Category-Selective Visual Regions. Hum Brain Mapp 2024; 45:e70064. [PMID: 39575904 PMCID: PMC11583081 DOI: 10.1002/hbm.70064] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2024] [Revised: 10/01/2024] [Accepted: 10/17/2024] [Indexed: 11/25/2024] Open
Abstract
Human behavior can be remarkably shaped by experience, such as the removal of sensory input. Many studies of conditions such as stroke, limb amputation, and vision loss have examined how removal of input changes brain function. However, an important question yet to be answered is: when input is lost, does the brain change its connectivity to preferentially use some remaining inputs over others? In individuals with healthy vision, the central portion of the retina is preferentially used for everyday visual tasks, due to its ability to discriminate fine details. When central vision is lost in conditions like macular degeneration, peripheral vision must be relied upon for those everyday tasks, with some portions receiving "preferential" usage over others. Using resting-state fMRI collected during total darkness, we examined how deprivation and preferential usage influence the intrinsic functional connectivity of sensory cortex by studying individuals with selective vision loss due to late stages of macular degeneration. Specifically, we examined functional connectivity between category-selective visual areas and the cortical representation of three areas of the retina: the lesioned area, a preferentially used region of the intact retina, and a non-preferentially used region. We found that cortical regions representing spared portions of the peripheral retina, regardless of whether they are preferentially used, exhibit plasticity of intrinsic functional connectivity in macular degeneration. Cortical representations of spared peripheral retinal locations showed stronger connectivity to MT, a region involved in processing motion. These results suggest that the long-term loss of central vision can produce widespread effects throughout spared representations in early visual cortex, regardless of whether those representations are preferentially used. These findings support the idea that connections to visual cortex maintain the capacity for change well after critical periods of visual development.
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Affiliation(s)
- Leland L. Fleming
- Department of NeurobiologyUniversity of Alabama at Birmingham School of MedicineBirminghamAlabamaUSA
| | - Matthew K. Defenderfer
- Department of NeurobiologyUniversity of Alabama at Birmingham School of MedicineBirminghamAlabamaUSA
| | - Pinar Demirayak
- Department of NeurobiologyUniversity of Alabama at Birmingham School of MedicineBirminghamAlabamaUSA
| | - Paul Stewart
- Department of NeurobiologyUniversity of Alabama at Birmingham School of MedicineBirminghamAlabamaUSA
| | - Dawn K. Decarlo
- Department of OphthalmologyUniversity of Alabama at Birmingham School of MedicineBirminghamAlabamaUSA
| | - Kristina M. Visscher
- Department of NeurobiologyUniversity of Alabama at Birmingham School of MedicineBirminghamAlabamaUSA
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29
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Pruitt PJ, Tang L, Hayes JM, Ofen N, Damoiseaux JS. Lifespan differences in background functional connectivity of core cognitive large-scale brain networks. Neurosci Res 2024; 209:1-8. [PMID: 36122815 PMCID: PMC10088545 DOI: 10.1016/j.neures.2022.09.005] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Revised: 08/31/2022] [Accepted: 09/13/2022] [Indexed: 10/14/2022]
Abstract
Large-scale brain networks undergo functional reorganization over the course of the lifespan, with concurrent implications for cognition. Characterizing network connectivity during a task may provide complementary insight into cognitive development and aging, to that provided by resting-state. We assessed network background connectivity, which refers to connectivity that remains after task effects have been regressed out, during a visual memory-encoding task in a lifespan sample. More specifically we assessed the within- and between-network background connectivity of the default mode, salience, and frontoparietal networks. Within-network background connectivity of salience and frontoparietal networks differed between age groups, with late-life adults showing lower connectivity. We did not find an effect of age group in default mode network background connectivity, contrary to previous findings using resting-state. However, default mode between-network background connectivity with salience and frontoparietal networks was greater in mid-life and late-life adults than in younger age groups. Overall, our findings in a lifespan sample are in line with previous observations of age-related network de-differentiation. However, the lack of age effect in default mode network background connectivity suggests that background connectivity indeed represents a complementary measure to resting-state connectivity, providing a differential glance of network connectivity during a particular state.
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Affiliation(s)
- Patrick J Pruitt
- Institute of Gerontology, Wayne State University, 87 E. Ferry St., Detroit, MI 48202, United States.
| | - Lingfei Tang
- Institute of Gerontology, Wayne State University, 87 E. Ferry St., Detroit, MI 48202, United States; Department of Psychology, Wayne State University, 5057 Woodward Ave. 7th Floor Suite 7908, Detroit, MI 48201, United States.
| | - Jessica M Hayes
- Institute of Gerontology, Wayne State University, 87 E. Ferry St., Detroit, MI 48202, United States; Department of Psychology, Wayne State University, 5057 Woodward Ave. 7th Floor Suite 7908, Detroit, MI 48201, United States.
| | - Noa Ofen
- Institute of Gerontology, Wayne State University, 87 E. Ferry St., Detroit, MI 48202, United States; Department of Psychology, Wayne State University, 5057 Woodward Ave. 7th Floor Suite 7908, Detroit, MI 48201, United States.
| | - Jessica S Damoiseaux
- Institute of Gerontology, Wayne State University, 87 E. Ferry St., Detroit, MI 48202, United States; Department of Psychology, Wayne State University, 5057 Woodward Ave. 7th Floor Suite 7908, Detroit, MI 48201, United States.
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30
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Alrouji M, Anwar S, Venkatesan K, Shahwan M, Hassan MI, Islam A, Shamsi A. Iron homeostasis and neurodegeneration in the ageing brain: Insight into ferroptosis pathways. Ageing Res Rev 2024; 102:102575. [PMID: 39515619 DOI: 10.1016/j.arr.2024.102575] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2024] [Revised: 10/25/2024] [Accepted: 11/03/2024] [Indexed: 11/16/2024]
Abstract
Ageing is a major risk factor for various chronic diseases and offers a potential target for developing novel and broadly effective preventatives or therapeutics for age-related conditions, including those affecting the brain. Mechanisms contributing to ageing have been summarized as the hallmarks of ageing, with iron imbalance being one of the major factors. Ferroptosis, an iron-mediated lipid peroxidation-induced programmed cell death, has recently been implicated in neurodegenerative diseases such as Alzheimer's disease (AD), Parkinson's disease (PD) and Huntington's disease (HD). Addressing ferroptosis offers both opportunities and challenges for treating neurodegenerative diseases, though the specific mechanisms remain unclear. This research explores the key processes behind how ferroptosis contributes to brain ageing, with a focus on the complex signaling networks that are involved. The current article aims to uncover that how ferroptosis, a specific type of cell death, may drive age-related changes in the brain. Additionally, the article also unveils its role in neurodegenerative diseases, discussing how understanding these mechanisms could open up new therapeutic avenues.
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Affiliation(s)
- Mohammed Alrouji
- Department of Medical Laboratories, College of Applied Medical Sciences, Shaqra University, Shaqra 11961, Saudi Arabia.
| | - Saleha Anwar
- Center for Global Health Research, Saveetha medical college, Saveetha institute of Medical and Technical Sciences, Chennai, India.
| | - Kumar Venkatesan
- Department of Pharmaceutical Chemistry, College of Pharmacy, King Khalid University, Abha 62529, Saudi Arabia.
| | - Moyad Shahwan
- Centre of Medical and Bio-allied Health Sciences Research, Ajman University, United Arab Emirates.
| | - Md Imtaiyaz Hassan
- Center for Interdsicplinary Research in Basic Sciences, Jamia Millia Islamia, New Delhi, India.
| | - Asimul Islam
- Center for Interdsicplinary Research in Basic Sciences, Jamia Millia Islamia, New Delhi, India.
| | - Anas Shamsi
- Centre of Medical and Bio-allied Health Sciences Research, Ajman University, United Arab Emirates.
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31
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Knoff AA, Nowak MK, Van Etten EJ, Andreu-Arasa VC, Esterman M, Leritz EC, Fortenbaugh FC, Milberg WP, Fortier CB, Salat DH. Metabolic syndrome is associated with reduced default mode network functional connectivity in young post-9/11 Veterans. Brain Imaging Behav 2024; 18:1499-1508. [PMID: 39347938 DOI: 10.1007/s11682-024-00927-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/05/2024] [Indexed: 10/01/2024]
Abstract
Metabolic syndrome is a collection of health factors that increases risk for cardiovascular disease. A condition of aging, metabolic syndrome is associated with reduced brain network integrity, including functional connectivity alterations among the default mode, regions vulnerable to neurodegeneration. Prevalence of metabolic syndrome is elevated in younger populations including post-9/11 Veterans and individuals with posttraumatic stress disorder, but it is unclear whether metabolic syndrome affects brain function in earlier adulthood. Identifying early effects of metabolic syndrome on brain network integrity is critical, as these impacts could contribute to increased risk for cognitive disorders later in life for Veterans. The current study examined whether metabolic syndrome and its individual components were associated with default mode functional connectivity. We also explored the contribution of posttraumatic stress disorder and traumatic brain injury on these metabolic syndrome-brain relationships. Post-9/11 Veterans with combat deployment history (95 with and 325 without metabolic syndrome) underwent functional magnetic resonance imaging to capture seed-based resting-state functional connectivity within the default mode. The metabolic syndrome group demonstrated reduced positive functional connectivity between the posterior cingulate cortex seed and the bilateral superior frontal gyrus. Data-driven analyses demonstrated that metabolic syndrome components, particularly cholesterol and central adiposity, were associated with widespread reductions in default mode network connectivity. Functional connectivity was also reduced in participants with metabolic syndrome but without current posttraumatic stress disorder diagnosis and with traumatic brain injury history. These results suggest that metabolic syndrome disrupts resting-state functional connectivity decades earlier than prior work has shown.
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Affiliation(s)
- Aubrey A Knoff
- Translational Research Center for TBI and Stress Disorders (TRACTS 182-JP), VA Boston Healthcare System, 150 S. Huntington Avenue, Boston, MA, 02130, USA.
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA.
- Department of Psychiatry, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, USA.
| | - Madeleine K Nowak
- Translational Research Center for TBI and Stress Disorders (TRACTS 182-JP), VA Boston Healthcare System, 150 S. Huntington Avenue, Boston, MA, 02130, USA
- Department of Psychiatry, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, USA
- National Center for PTSD at VA Boston Healthcare System, Boston, MA, USA
| | - Emily J Van Etten
- Translational Research Center for TBI and Stress Disorders (TRACTS 182-JP), VA Boston Healthcare System, 150 S. Huntington Avenue, Boston, MA, 02130, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, USA
| | - V Carlota Andreu-Arasa
- Department of Radiology, VA Boston Healthcare System, Boston, MA, USA
- Department of Radiology, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, USA
| | - Michael Esterman
- Translational Research Center for TBI and Stress Disorders (TRACTS 182-JP), VA Boston Healthcare System, 150 S. Huntington Avenue, Boston, MA, 02130, USA
- Department of Psychiatry, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, USA
- National Center for PTSD at VA Boston Healthcare System, Boston, MA, USA
- Neuroimaging Research for Veterans Center, VA Boston Healthcare System, Boston, MA, USA
| | - Elizabeth C Leritz
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
- Geriatric Research, Educational and Clinical Center (GRECC), VA Boston Healthcare System, Boston, MA, USA
| | - Francesca C Fortenbaugh
- Translational Research Center for TBI and Stress Disorders (TRACTS 182-JP), VA Boston Healthcare System, 150 S. Huntington Avenue, Boston, MA, 02130, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - William P Milberg
- Translational Research Center for TBI and Stress Disorders (TRACTS 182-JP), VA Boston Healthcare System, 150 S. Huntington Avenue, Boston, MA, 02130, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
- Geriatric Research, Educational and Clinical Center (GRECC), VA Boston Healthcare System, Boston, MA, USA
| | - Catherine B Fortier
- Translational Research Center for TBI and Stress Disorders (TRACTS 182-JP), VA Boston Healthcare System, 150 S. Huntington Avenue, Boston, MA, 02130, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
- Geriatric Research, Educational and Clinical Center (GRECC), VA Boston Healthcare System, Boston, MA, USA
| | - David H Salat
- Translational Research Center for TBI and Stress Disorders (TRACTS 182-JP), VA Boston Healthcare System, 150 S. Huntington Avenue, Boston, MA, 02130, USA
- Geriatric Research, Educational and Clinical Center (GRECC), VA Boston Healthcare System, Boston, MA, USA
- Neuroimaging Research for Veterans Center, VA Boston Healthcare System, Boston, MA, USA
- Anthinoula A. Martinos Center for Biomedical Imaging, Boston, MA, USA
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32
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Gu Y, Guo L, Cai X, Yang Q, Sun J, Li Y, Zhu J, Zhang W, Huang P, Jiang Y, Bo B, Li Y, Zhang Y, Zhang M, Wu J, Shi H, Liu S, He Q, Yao X, Zhang Q, Wei H, Zhang X, Zhang H. Connectome-based predictive modelling of ageing, overall cognitive functioning and memory performance. Eur J Neurosci 2024. [PMID: 39523689 DOI: 10.1111/ejn.16559] [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: 12/27/2023] [Revised: 09/16/2024] [Accepted: 09/18/2024] [Indexed: 11/16/2024]
Abstract
Resting-state functional magnetic resonance imaging (rs-fMRI) and brain functional connectome (we use 'brain connectome' hereafter for simplicity) have advanced our understanding of the ageing brain and age-related changes in cognitive function. Previous studies have investigated the association among brain connectome and age, global cognition, and memory function separately. However, very few have predicted age, overall cognitive functioning and memory performance in a single study to better understand their complex relationship. In this cross-sectional study, we applied an exploratory, data-driven method to investigate the brain connectome markers that could predict ageing, overall cognitive functioning assessed as intelligence quotient (IQ, measured by Wechsler Memory Scale) and memory performance assessed as memory quotient (MQ, measured by Wechsler Memory Scale) in a carefully designed, multicentre, normal ageing cohort (n = 313). Our results showed that brain connectome could predict ageing and IQ, but the association with MQ was weak. We found that the connectivity with orbital frontal cortex was associated with both ageing and IQ. Mediation analysis further showed that the brain connectome mediated the relationship between age and overall cognitive functioning, suggesting a protective brain connectomic mechanism for maintaining normal cognitive functions during healthy ageing. This work may shed light on the potential neural correlates of healthy ageing, overall cognitive functioning and memory performance.
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Affiliation(s)
- Yi Gu
- School of Biomedical Engineering, ShanghaiTech University, Shanghai, China
| | - Lianghu Guo
- School of Biomedical Engineering, ShanghaiTech University, Shanghai, China
| | - Xinyi Cai
- School of Biomedical Engineering, ShanghaiTech University, Shanghai, China
| | - Qing Yang
- School of Biomedical Engineering, ShanghaiTech University, Shanghai, China
- Shanghai Brain-Intelligence Project, Shanghai, China
- Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai, China
| | - Jian Sun
- School of Biomedical Engineering, ShanghaiTech University, Shanghai, China
| | - Yufei Li
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
- School of Mathematics and Computer Science, Chifeng University, Chifeng, China
| | - Jiayu Zhu
- Shanghai United Imaging Healthcare Co., Ltd., Shanghai, China
- Paul C. Lauterbur Research Centre for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Science, Shenzhen, China
| | - Weijun Zhang
- Shanghai United Imaging Healthcare Co., Ltd., Shanghai, China
| | - Peiyu Huang
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Yi Jiang
- Research Unit of Pain Medicine, Chinese Academy of Medical Sciences, Guangdong Institute of Intelligence Science and Technology, Hengqin, Zhuhai, Guangdong, China
| | - Bin Bo
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Yao Li
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Yaoyu Zhang
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Minming Zhang
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Jinsong Wu
- Glioma Surgery Division, Neurologic Surgery Department, Huashan Hospital, Shanghai, China
- Medical College, Fudan University, Shanghai, China
| | - Hongcheng Shi
- Department of Nuclear Medicine, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Siwei Liu
- Department of Nuclear Medicine, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Qiang He
- Shanghai United Imaging Healthcare Co., Ltd., Shanghai, China
- United Imaging Research Institute of Innovative Medical Equipment, Shenzhen, China
| | - Xing Yao
- Shanghai United Imaging Healthcare Co., Ltd., Shanghai, China
| | - Qiang Zhang
- Shanghai United Imaging Healthcare Co., Ltd., Shanghai, China
| | - Hongjiang Wei
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Xu Zhang
- Shanghai Brain-Intelligence Project, Shanghai, China
- Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai, China
- Research Unit of Pain Medicine, Chinese Academy of Medical Sciences, Guangdong Institute of Intelligence Science and Technology, Hengqin, Zhuhai, Guangdong, China
- School of Life Science and Technology, ShanghaiTech University, Shanghai, China
| | - Han Zhang
- School of Biomedical Engineering, ShanghaiTech University, Shanghai, China
- Shanghai Brain-Intelligence Project, Shanghai, China
- State Key Laboratory of Advanced Medical Materials and Devices, ShanghaiTech University, Shanghai, China
- Shanghai Clinical Research and Trail Center, Shanghai, China
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33
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Marti E, Coll SY, Doganci N, Ptak R. Cortical and subcortical substrates of working memory in the right hemisphere: A connectome-based lesion-symptom mapping study. Neuropsychologia 2024; 204:108998. [PMID: 39251106 DOI: 10.1016/j.neuropsychologia.2024.108998] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2024] [Revised: 07/19/2024] [Accepted: 09/06/2024] [Indexed: 09/11/2024]
Abstract
Working Memory (WM) is a cognitive system whose crucial role is to temporarily hold and manipulate information. Early studies suggest that verbal WM is typically associated with left hemisphere (LH) brain regions, while the processing of visuospatial information in WM more specifically depends on the right hemisphere (RH). However, recent evidence suggests a more complex network involving both hemispheres' prefrontal and posterior parietal cortices in these processes. Unfortunately, previous lesion studies often examined only one modality (either verbal, or visuospatial) or one hemisphere, which limits the possible conclusions regarding non-lateralized hemispheric involvement. Using connectome-based lesion-symptom mapping on a large sample of patients with left (LBD) and right (RBD) focal brain damage, we examined whether gray matter damage and white matter disconnections predict deficits of WM updating in an N-back task. Patients were examined with two WM tasks that differed regarding modality (verbal, spatial) and cognitive load (1-back, 2-back). Behavioral outcomes indicated that RBD patients showed significant deficits in WM updating, regardless of task modality or load. This observation was supported by whole-brain voxel-based analysis, revealing associations between WM deficits and gray matter clusters in the RH. Specifically, damage to the right lateral frontal cortex including the brain region homologous to Broca's area was associated with verbal WM deficits, while damage to the right inferior parietal lobe and posterior temporal cortex predicted spatial WM deficits. Additionally, white matter analyses identified severely impacted tracts in the RH, predicting deficits in both verbal and spatial WM. Our findings suggest that the mental manipulation of both verbal and visuospatial information in WM updating relies on the integrity of the RH, irrespective of the specific type of information held in mind.
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Affiliation(s)
- Emilie Marti
- Laboratory of Cognitive Neurorehabilitation, Faculty of Medicine, University of Geneva, Geneva, Switzerland.
| | - Sélim Yahia Coll
- Laboratory of Cognitive Neurorehabilitation, Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Naz Doganci
- Laboratory of Cognitive Neurorehabilitation, Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Radek Ptak
- Laboratory of Cognitive Neurorehabilitation, Faculty of Medicine, University of Geneva, Geneva, Switzerland; Division of Neurorehabilitation, Department of Clinical Neurosciences, Geneva University Hospitals, Geneva, Switzerland.
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Perry RN, Ethier-Gagnon MA, Helmick C, Spinella TC, Tibbo PG, Stewart SH, Barrett SP. The impact of cannabidiol placebo on amygdala-based neural responses to an acute stressor. J Psychopharmacol 2024; 38:935-948. [PMID: 39400103 PMCID: PMC11528970 DOI: 10.1177/02698811241287557] [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] [Indexed: 10/15/2024]
Abstract
BACKGROUND Cannabidiol (CBD) impacts brain regions implicated in anxiety reactivity and stress reactivity (e.g., amygdala, anterior cingulate cortex (ACC), anterior insula (AI)); however, placebo-controlled studies are mixed regarding CBD's anxiolytic effects. We previously reported that CBD expectancy alone can alter subjective, physiological, and endocrine markers of stress/anxiety; however, it is unclear whether these findings reflect altered brain reactivity. This study evaluated whether CBD expectancy independently alters amygdala resting-state functional connectivity (rsFC) with the ACC and AI following acute stress. METHOD Thirty-eight (20 females) healthy adults were randomly assigned to receive accurate or inaccurate information regarding the CBD content of a CBD-free oil administered during a single experimental session. Following a baseline resting state MRI scan, participants administered their assigned oil sublingually, engaged in a stress task (serial subtraction with negative feedback) inside the scanner, and underwent another resting state MRI scan. Amygdala rsFC with the ACC and AI was measured during each scan, and the subjective state was assessed at six time points. Outcomes were analyzed using ANCOVA. RESULTS CBD expectancy (vs CBD-free expectancy) was associated with significantly weaker rsFC between the left amygdala and right ACC (p = 0.042), but did not systematically alter amygdala-AI rsFC (p-values > 0.05). We also replicated our previously reported CBD expectancy effects on subjective stress/anxiety in the scanner context. CONCLUSION CBD placebo effects may be sufficient to alter neural responses relevant to its purported anxiolytic and stress-relieving properties. Future work is needed to replicate these results and determine whether CBD expectancy and pharmacology interact to alter neural anxiety reactivity and stress reactivity.
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Affiliation(s)
- Robin N Perry
- Department of Psychology and Neuroscience, Dalhousie University, Halifax, NS, Canada
| | | | - Carl Helmick
- Department of Psychiatry, Dalhousie University, Halifax, NS, Canada
| | - Toni C Spinella
- Department of Psychology and Neuroscience, Dalhousie University, Halifax, NS, Canada
| | - Philip G Tibbo
- Department of Psychology and Neuroscience, Dalhousie University, Halifax, NS, Canada
- Department of Psychiatry, Dalhousie University, Halifax, NS, Canada
| | - Sherry H Stewart
- Department of Psychology and Neuroscience, Dalhousie University, Halifax, NS, Canada
- Department of Psychiatry, Dalhousie University, Halifax, NS, Canada
| | - Sean P Barrett
- Department of Psychology and Neuroscience, Dalhousie University, Halifax, NS, Canada
- Department of Psychiatry, Dalhousie University, Halifax, NS, Canada
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Billot A, Jhingan N, Varkanitsa M, Blank I, Ryskin R, Kiran S, Fedorenko E. The language network ages well: Preserved selectivity, lateralization, and within-network functional synchronization in older brains. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.10.23.619954. [PMID: 39484368 PMCID: PMC11527140 DOI: 10.1101/2024.10.23.619954] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 11/03/2024]
Abstract
Healthy aging is associated with structural and functional brain changes. However, cognitive abilities differ from one another in how they change with age: whereas executive functions, like working memory, show age-related decline, aspects of linguistic processing remain relatively preserved (Hartshorne et al., 2015). This heterogeneity of the cognitive-behavioral landscape in aging predicts differences among brain networks in whether and how they should change with age. To evaluate this prediction, we used individual-subject fMRI analyses ('precision fMRI') to examine the language-selective network (Fedorenko et al., 2024) and the Multiple Demand (MD) network, which supports executive functions (Duncan et al., 2020), in older adults (n=77) relative to young controls (n=470). In line with past claims, relative to young adults, the MD network of older adults shows weaker and less spatially extensive activations during an executive function task and reduced within-network functional synchronization. However, in stark contrast to the MD network, we find remarkable preservation of the language network in older adults. Their language network responds to language as strongly and selectively as in younger adults, and is similarly lateralized and internally synchronized. In other words, the language network of older adults looks indistinguishable from that of younger adults. Our findings align with behavioral preservation of language skills in aging and suggest that some networks remain young-like, at least on standard measures of function and connectivity.
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Affiliation(s)
- Anne Billot
- Department of Neurology, Massachusetts General Hospital & Harvard Medical School; Boston, MA 02114
- Center for Brain Science, Harvard University, Cambridge, MA 02138
| | - Niharika Jhingan
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139
| | - Maria Varkanitsa
- Department of Speech, Language, and Hearing Sciences, Boston University, Boston, MA 02215
| | - Idan Blank
- Department of Psychology and Department of Linguistics, University of California Los Angeles, Los Angeles, CA 90095
| | - Rachel Ryskin
- Department of Cognitive & Information Sciences, University of California Merced, Merced, CA 95343
| | - Swathi Kiran
- Department of Speech, Language, and Hearing Sciences, Boston University, Boston, MA 02215
| | - Evelina Fedorenko
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139
- Program in Speech and Hearing Bioscience and Technology, Harvard University, Boston, MA 02114
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Wing D, Roelands B, Wetherell JL, Nichols JF, Meeusen R, Godino JG, Shimony JS, Snyder AZ, Nishino T, Nicol GE, Nagels G, Eyler LT, Lenze EJ. Cardiorespiratory Fitness and Sleep, but not Physical Activity, are Associated with Functional Connectivity in Older Adults. SPORTS MEDICINE - OPEN 2024; 10:113. [PMID: 39425826 PMCID: PMC11490599 DOI: 10.1186/s40798-024-00778-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/03/2024] [Accepted: 09/29/2024] [Indexed: 10/21/2024]
Abstract
BACKGROUND Aging results in changes in resting state functional connectivity within key networks associated with cognition. Cardiovascular function, physical activity, sleep, and body composition may influence these age-related changes in the brain. Better understanding these associations may help clarify mechanisms related to brain aging and guide interventional strategies to reduce these changes. METHODS In a large (n = 398) sample of healthy community dwelling older adults that were part of a larger interventional trial, we conducted cross sectional analyses of baseline data to examine the relationships between several modifiable behaviors and resting state functional connectivity within networks associated with cognition and emotional regulation. Additionally, maximal aerobic capacity, physical activity, quality of sleep, and body composition were assessed. Associations were explored both through correlation and best vs. worst group comparisons. RESULTS Greater cardiovascular fitness, but not larger quantity of daily physical activity, was associated with greater functional connectivity within the Default Mode (p = 0.008 r = 0.142) and Salience Networks (p = 0.005, r = 0.152). Better sleep (greater efficiency and fewer nighttime awakenings) was also associated with greater functional connectivity within multiple networks including the Default Mode, Executive Control, and Salience Networks. When the population was split into quartiles, the highest body fat group displayed higher functional connectivity in the Dorsal Attentional Network compared to the lowest body fat percentage (p = 0.011; 95% CI - 0.0172 to - 0.0023). CONCLUSION These findings confirm and expand on previous work indicating that, in older adults, higher levels of cardiovascular fitness and better sleep quality, but not greater quantity of physical activity, total sleep time, or lower body fat percentage are associated with increased functional connectivity within key resting state networks.
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Affiliation(s)
- David Wing
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California, San Diego, USA.
- Exercise and Physical Activity Resource Center (EPARC), University of California, San Diego, USA.
| | - Bart Roelands
- Human Physiology & Sports Physiotherapy Research Group, Faculty of Physical Education and Physiotherapy, Vrije Universiteit Brussel, Brussels, Belgium
- Vrije Universiteit Brussel, Brussels, Belgium
| | - Julie Loebach Wetherell
- Mental Health Service, VA San Diego Healthcare System, San Diego, USA
- Department of Psychiatry, University of California, San Diego, USA
| | - Jeanne F Nichols
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California, San Diego, USA
- Exercise and Physical Activity Resource Center (EPARC), University of California, San Diego, USA
| | - Romain Meeusen
- Human Physiology & Sports Physiotherapy Research Group, Faculty of Physical Education and Physiotherapy, Vrije Universiteit Brussel, Brussels, Belgium
- Vrije Universiteit Brussel, Brussels, Belgium
- Department of Sports, Recreation, Exercise and Sciences, Community and Health Sciences, University of the Western Cape, Cape Town, South Africa
| | - Job G Godino
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California, San Diego, USA
- Exercise and Physical Activity Resource Center (EPARC), University of California, San Diego, USA
| | - Joshua S Shimony
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | - Abraham Z Snyder
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | - Tomoyuki Nishino
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
| | - Ginger E Nicol
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
| | - Guy Nagels
- Department of Neurology, Brussels, Belgium/Center for Neurosciences (C4N), UZ Brussel, Vrije Universiteit Brussel (VUB), Brussels, Belgium
| | - Lisa T Eyler
- Department of Psychiatry, University of California, San Diego, USA
- Education, and Clinical Center, Desert-Pacific Mental Illness Research, San Diego Veterans Administration Healthcare System, San Diego, USA
| | - Eric J Lenze
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
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Pauley C, Zeithamova D, Sander MC. Age differences in functional connectivity track dedifferentiation of category representations. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.04.574135. [PMID: 38260463 PMCID: PMC10802339 DOI: 10.1101/2024.01.04.574135] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
With advancing age, the distinctiveness of neural representations of information declines. While the finding of this so-called 'age-related neural dedifferentiation' in category-selective neural regions is well-described, the contribution of age-related changes in network organization to dedifferentiation is unknown. Here, we asked whether age differences in a) whole-brain network segregation (i.e., network dedifferentiation) and b) functional connectivity to category-selective neural regions are related to regional dedifferentiation of categorical representations. Younger and older adults viewed blocks of face and house stimuli in the fMRI scanner. We found an age-related decline in neural distinctiveness for faces in the fusiform gyrus (FG) and for houses in the parahippocampal gyrus (PHG). Functional connectivity analyses revealed age-related dedifferentiation of global network structure as well as age differences in connectivity between the FG and early visual cortices. Interindividual correlations demonstrated that regional distinctiveness was related to network segregation. Together, our findings suggest that dedifferentiation of categorical representations may be linked to age-related reorganization of functional networks.
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Affiliation(s)
- Claire Pauley
- Center for Lifespan Psychology, Max Planck Institute for Human Development, 14195 Berlin, Germany
- Faculty of Life Sciences, Humboldt-Universität zu Berlin, 10115 Berlin, German
| | - Dagmar Zeithamova
- Department of Psychology, University of Oregon, 97403 Eugene, Oregon, USA
| | - Myriam C. Sander
- Center for Lifespan Psychology, Max Planck Institute for Human Development, 14195 Berlin, Germany
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Fenerci C, Setton R, Baracchini G, Snytte J, Spreng RN, Sheldon S. Lifespan differences in hippocampal subregion connectivity patterns during movie watching. Neurobiol Aging 2024; 141:182-193. [PMID: 38968875 DOI: 10.1016/j.neurobiolaging.2024.06.006] [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: 12/10/2023] [Revised: 05/17/2024] [Accepted: 06/22/2024] [Indexed: 07/07/2024]
Abstract
Age-related episodic memory decline is attributed to functional alternations in the hippocampus. Less clear is how aging affects the functional connections of the hippocampus to the rest of the brain during episodic memory processing. We examined fMRI data from the CamCAN dataset, in which a large cohort of participants watched a movie (N = 643; 18-88 years), a proxy for naturalistic episodic memory encoding. We examined connectivity profiles across the lifespan both within the hippocampus (anterior, posterior), and between the hippocampal subregions and cortical networks. Aging was associated with reductions in contralateral (left, right) but not ipsilateral (anterior, posterior) hippocampal subregion connectivity. Aging was primarily associated with increased coupling between the anterior hippocampus and regions affiliated with Control, Dorsal Attention and Default Mode networks, yet decreased coupling between the posterior hippocampus and a selection of these regions. Differences in age-related hippocampal-cortical, but not within-hippocampus circuitry selectively predicted worse memory performance. Our findings comprehensively characterize hippocampal functional topography in relation to cognition in older age, suggesting that shifts in cortico-hippocampal connectivity may be sensitive markers of age-related episodic memory decline.
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Affiliation(s)
- Can Fenerci
- Department of Psychology, McGill University, Montreal, QC, Canada.
| | - Roni Setton
- Department of Psychology, Harvard University, Cambridge, MA, USA
| | - Giulia Baracchini
- Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
| | - Jamie Snytte
- Department of Psychology, McGill University, Montreal, QC, Canada
| | - R Nathan Spreng
- Department of Psychology, McGill University, Montreal, QC, Canada; Department of Psychology, Harvard University, Cambridge, MA, USA; Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
| | - Signy Sheldon
- Department of Psychology, McGill University, Montreal, QC, Canada.
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Sultana OF, Bandaru M, Islam MA, Reddy PH. Unraveling the complexity of human brain: Structure, function in healthy and disease states. Ageing Res Rev 2024; 100:102414. [PMID: 39002647 PMCID: PMC11384519 DOI: 10.1016/j.arr.2024.102414] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2024] [Revised: 06/29/2024] [Accepted: 07/05/2024] [Indexed: 07/15/2024]
Abstract
The human brain stands as an intricate organ, embodying a nexus of structure, function, development, and diversity. This review delves into the multifaceted landscape of the brain, spanning its anatomical intricacies, diverse functional capacities, dynamic developmental trajectories, and inherent variability across individuals. The dynamic process of brain development, from early embryonic stages to adulthood, highlights the nuanced changes that occur throughout the lifespan. The brain, a remarkably complex organ, is composed of various anatomical regions, each contributing uniquely to its overall functionality. Through an exploration of neuroanatomy, neurophysiology, and electrophysiology, this review elucidates how different brain structures interact to support a wide array of cognitive processes, sensory perception, motor control, and emotional regulation. Moreover, it addresses the impact of age, sex, and ethnic background on brain structure and function, and gender differences profoundly influence the onset, progression, and manifestation of brain disorders shaped by genetic, hormonal, environmental, and social factors. Delving into the complexities of the human brain, it investigates how variations in anatomical configuration correspond to diverse functional capacities across individuals. Furthermore, it examines the impact of neurodegenerative diseases on the structural and functional integrity of the brain. Specifically, our article explores the pathological processes underlying neurodegenerative diseases, such as Alzheimer's, Parkinson's, and Huntington's diseases, shedding light on the structural alterations and functional impairments that accompany these conditions. We will also explore the current research trends in neurodegenerative diseases and identify the existing gaps in the literature. Overall, this article deepens our understanding of the fundamental principles governing brain structure and function and paves the way for a deeper understanding of individual differences and tailored approaches in neuroscience and clinical practice-additionally, a comprehensive understanding of structural and functional changes that manifest in neurodegenerative diseases.
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Affiliation(s)
- Omme Fatema Sultana
- Department of Internal Medicine, Texas Tech University Health Sciences Center, Lubbock, TX 79430, USA
| | - Madhuri Bandaru
- Department of Internal Medicine, Texas Tech University Health Sciences Center, Lubbock, TX 79430, USA
| | - Md Ariful Islam
- Department of Internal Medicine, Texas Tech University Health Sciences Center, Lubbock, TX 79430, USA
| | - P Hemachandra Reddy
- Department of Internal Medicine, Texas Tech University Health Sciences Center, Lubbock, TX 79430, USA; Nutritional Sciences Department, College of Human Sciences, Texas Tech University, Lubbock, TX 79409, USA; Department of Pharmacology and Neuroscience, Texas Tech University Health Sciences Center, Lubbock, TX 79430, USA; Department of Neurology, Texas Tech University Health Sciences Center, Lubbock, TX 79430, USA 5. Department of Public Health, Graduate School of Biomedical Sciences, Texas Tech University Health Sciences Center, Lubbock, TX 79430, USA; Department of Speech, Language, and Hearing Sciences, Texas Tech University Health Sciences Center, Lubbock, TX 79430, USA.
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Madden DJ, Merenstein JL, Mullin HA, Jain S, Rudolph MD, Cohen JR. Age-related differences in resting-state, task-related, and structural brain connectivity: graph theoretical analyses and visual search performance. Brain Struct Funct 2024; 229:1533-1559. [PMID: 38856933 PMCID: PMC11374505 DOI: 10.1007/s00429-024-02807-2] [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: 12/29/2023] [Accepted: 05/13/2024] [Indexed: 06/11/2024]
Abstract
Previous magnetic resonance imaging (MRI) research suggests that aging is associated with a decrease in the functional interconnections within and between groups of locally organized brain regions (modules). Further, this age-related decrease in the segregation of modules appears to be more pronounced for a task, relative to a resting state, reflecting the integration of functional modules and attentional allocation necessary to support task performance. Here, using graph-theoretical analyses, we investigated age-related differences in a whole-brain measure of module connectivity, system segregation, for 68 healthy, community-dwelling individuals 18-78 years of age. We obtained resting-state, task-related (visual search), and structural (diffusion-weighted) MRI data. Using a parcellation of modules derived from the participants' resting-state functional MRI data, we demonstrated that the decrease in system segregation from rest to task (i.e., reconfiguration) increased with age, suggesting an age-related increase in the integration of modules required by the attentional demands of visual search. Structural system segregation increased with age, reflecting weaker connectivity both within and between modules. Functional and structural system segregation had qualitatively different influences on age-related decline in visual search performance. Functional system segregation (and reconfiguration) influenced age-related decline in the rate of visual evidence accumulation (drift rate), whereas structural system segregation contributed to age-related slowing of encoding and response processes (nondecision time). The age-related differences in the functional system segregation measures, however, were relatively independent of those associated with structural connectivity.
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Affiliation(s)
- David J Madden
- Brain Imaging and Analysis Center, Duke University Medical Center, Box 3918, Durham, NC, 27710, USA.
- Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC, 27710, USA.
- Center for Cognitive Neuroscience, Duke University, Durham, NC, 27708, USA.
| | - Jenna L Merenstein
- Brain Imaging and Analysis Center, Duke University Medical Center, Box 3918, Durham, NC, 27710, USA
| | - Hollie A Mullin
- Brain Imaging and Analysis Center, Duke University Medical Center, Box 3918, Durham, NC, 27710, USA
- Department of Psychology, Pennsylvania State University, University Park, PA, 16802, USA
| | - Shivangi Jain
- Brain Imaging and Analysis Center, Duke University Medical Center, Box 3918, Durham, NC, 27710, USA
- AdventHealth Research Institute, Neuroscience Institute, Orlando, FL, 32804, USA
| | - Marc D Rudolph
- Department of Psychology and Neuroscience, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27514, USA
- Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, 27101, USA
| | - Jessica R Cohen
- Department of Psychology and Neuroscience, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27514, USA
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Bai Y, Zhang B, Feng T. Neural basis responsible for effect of grit on procrastination: The interaction between the self-regulation and motivation neural pathways. Prog Neuropsychopharmacol Biol Psychiatry 2024; 134:111037. [PMID: 38795822 DOI: 10.1016/j.pnpbp.2024.111037] [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: 11/18/2023] [Revised: 05/07/2024] [Accepted: 05/22/2024] [Indexed: 05/28/2024]
Abstract
Procrastination has a detrimental impact on academic performance, health, and subjective well-being. Previous studies indicated that grit was negatively related to procrastination. However, the underlying neural basis of this relationship remains unclear. To address this issue, we utilized voxel-based morphometry (VBM) and resting-state functional connectivity (RSFC) analysis to identify the neural substrates of how is grit linked to procrastination. Behavioral results showed that procrastination was negatively associated with grit. VBM analysis revealed that gray matter volume (GMV) in the left precuneus was positively associated with the consistency of interest (CI), a subcomponent of grit, while the right medial orbital frontal cortex (mOFC) was positively correlated with the perseverance of effort (PE), another subcomponent of grit. Moreover, the RSFC analysis indicated that both precuneus-medial superior frontal gyrus (mSFG) and precuneus-insula connectivity were positively related to CI, while the functional coupling of right mOFC with left anterior cingulate cortex (ACC) was positively related to PE. Importantly, the structural equation modeling (SEM) results were well suited for the influence of grit on procrastination via both self-regulation (mOFC-ACC) and motivation pathways (precuneus-mSFG, precuneus-insula). Together, these findings imply that self-regulation and motivation could be two neural circuits underlying the impact of grit on procrastination.
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Affiliation(s)
- Youling Bai
- Faculty of Psychology, Southwest University, Chongqing 400715, China
| | - Biying Zhang
- Faculty of Psychology, Southwest University, Chongqing 400715, China
| | - Tingyong Feng
- Faculty of Psychology, Southwest University, Chongqing 400715, China; Key Laboratory of Cognition and Personality, Ministry of Education, 400715, China.
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Yue WL, Ng KK, Liu S, Qian X, Chong JSX, Koh AJ, Ong MQW, Ting SKS, Ng ASL, Kandiah N, Yeo BTT, Zhou JH. Differential spatial working memory-related functional network reconfiguration in young and older adults. Netw Neurosci 2024; 8:395-417. [PMID: 38952809 PMCID: PMC11142455 DOI: 10.1162/netn_a_00358] [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: 09/21/2023] [Accepted: 01/05/2024] [Indexed: 07/03/2024] Open
Abstract
Functional brain networks have preserved architectures in rest and task; nevertheless, previous work consistently demonstrated task-related brain functional reorganization. Efficient rest-to-task functional network reconfiguration is associated with better cognition in young adults. However, aging and cognitive load effects, as well as contributions of intra- and internetwork reconfiguration, remain unclear. We assessed age-related and load-dependent effects on global and network-specific functional reconfiguration between rest and a spatial working memory (SWM) task in young and older adults, then investigated associations between functional reconfiguration and SWM across loads and age groups. Overall, global and network-level functional reconfiguration between rest and task increased with age and load. Importantly, more efficient functional reconfiguration associated with better performance across age groups. However, older adults relied more on internetwork reconfiguration of higher cognitive and task-relevant networks. These reflect the consistent importance of efficient network updating despite recruitment of additional functional networks to offset reduction in neural resources and a change in brain functional topology in older adults. Our findings generalize the association between efficient functional reconfiguration and cognition to aging and demonstrate distinct brain functional reconfiguration patterns associated with SWM in aging, highlighting the importance of combining rest and task measures to study aging cognition.
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Affiliation(s)
- Wan Lin Yue
- Centre for Sleep and Cognition & Centre for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, National University of Singapore
- Integrative Sciences and Engineering Programme, NUS Graduate School, National University of Singapore
| | - Kwun Kei Ng
- Centre for Sleep and Cognition & Centre for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, National University of Singapore
| | - Siwei Liu
- Centre for Sleep and Cognition & Centre for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, National University of Singapore
| | - Xing Qian
- Centre for Sleep and Cognition & Centre for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, National University of Singapore
| | - Joanna Su Xian Chong
- Centre for Sleep and Cognition & Centre for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, National University of Singapore
| | - Amelia Jialing Koh
- Centre for Sleep and Cognition & Centre for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, National University of Singapore
| | - Marcus Qin Wen Ong
- Centre for Sleep and Cognition & Centre for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, National University of Singapore
| | | | | | - Nagaendran Kandiah
- National Neuroscience Institute, Singapore
- Neuroscience and Behavioural Disorders Programme, Duke-NUS Medical School, Singapore
| | - B. T. Thomas Yeo
- Centre for Sleep and Cognition & Centre for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, National University of Singapore
- Integrative Sciences and Engineering Programme, NUS Graduate School, National University of Singapore
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital
- Department of Electrical and Computer Engineering, N.1 Institute for Health and Memory Networks Program, National University of Singapore
| | - Juan Helen Zhou
- Centre for Sleep and Cognition & Centre for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, National University of Singapore
- Integrative Sciences and Engineering Programme, NUS Graduate School, National University of Singapore
- Neuroscience and Behavioural Disorders Programme, Duke-NUS Medical School, Singapore
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Fehr T, Mehrens S, Haag MC, Amelung A, Gloy K. Changes in Spatiotemporal Dynamics of Default Network Oscillations between 19 and 29 Years of Age. Brain Sci 2024; 14:671. [PMID: 39061412 PMCID: PMC11274777 DOI: 10.3390/brainsci14070671] [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: 04/24/2024] [Revised: 06/15/2024] [Accepted: 06/20/2024] [Indexed: 07/28/2024] Open
Abstract
The exploration of functional resting-state brain developmental parameters and measures can help to improve scientific, psychological, and medical applications. The present work focussed on both traditional approaches, such as topographical power analyses at the signal space level, and advanced approaches, such as the exploration of age-related dynamics of source space data. The results confirmed the expectation that the third life decade would show a kind of stability in oscillatory signal and source-space-related parameters. However, from a source dynamics perspective, different frequency ranges appear to develop quite differently, as reflected in age-related sequential network communication profiles. Among other discoveries, the left anterior cingulate source location could be shown to reduce bi-directional network communication in the lower alpha band, whereas it differentiated its uni- and bidirectional communication dynamics to sub-cortical and posterior brain locations. Higher alpha oscillations enhanced communication dynamics between the thalamus and particularly frontal areas. In conclusion, resting-state data appear to be, at least in part, functionally reorganized in the default mode network, while quantitative measures, such as topographical power and regional source activity, did not correlate with age in the third life decade. In line with other authors, we suggest the further development of a multi-perspective approach in biosignal analyses.
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Affiliation(s)
- Thorsten Fehr
- Institute for Psychology, University of Bremen, 28357 Bremen, Germany (K.G.)
- Center for Advanced Imaging, University of Bremen, 28357 Bremen, Germany
| | - Sophia Mehrens
- Institute for Psychology, University of Bremen, 28357 Bremen, Germany (K.G.)
| | | | - Anneke Amelung
- Institute for Psychology, University of Bremen, 28357 Bremen, Germany (K.G.)
| | - Kilian Gloy
- Institute for Psychology, University of Bremen, 28357 Bremen, Germany (K.G.)
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Diamond BR, Sridhar J, Maier J, Martersteck AC, Rogalski EJ. SuperAging functional connectomics from resting-state functional MRI. Brain Commun 2024; 6:fcae205. [PMID: 38978723 PMCID: PMC11228547 DOI: 10.1093/braincomms/fcae205] [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: 12/17/2023] [Revised: 04/12/2024] [Accepted: 06/17/2024] [Indexed: 07/10/2024] Open
Abstract
Understanding the relationship between functional connectivity (FC) of higher-order neurocognitive networks and age-related cognitive decline is a complex and evolving field of research. Decreases in FC have been associated with cognitive decline in persons with Alzheimer's disease and related dementias (ADRD). However, the contributions of FC have been less straightforward in typical cognitive aging. Some investigations suggest relatively robust FC within neurocognitive networks differentiates unusually successful cognitive aging from average aging, while others do not. Methodologic limitations in data processing and varying definitions of 'successful aging' may have contributed to the inconsistent results to date. The current study seeks to address previous limitations by optimized MRI methods to examine FC in the well-established SuperAging phenotype, defined by age and cognitive performance as individuals 80 and older with episodic memory performance equal to or better than 50-to-60-year-olds. Within- and between-network FC of large-scale neurocognitive networks were compared between 24 SuperAgers and 16 cognitively average older-aged control (OACs) with stable cognitive profiles using resting-state functional MRI (rs-fMRI) from a single visit. Group classification was determined based on measures of episodic memory, executive functioning, verbal fluency and picture naming. Inclusion criteria required stable cognitive status across two visits. First, we investigated the FC within and between seven resting-state networks from a common atlas parcellation. A separate index of network segregation was also compared between groups. Second, we investigated the FC between six subcomponents of the default mode network (DMN), the neurocognitive network commonly associated with memory performance and disrupted in persons with ADRD. For each analysis, FCs were compared across groups using two-sample independent t-tests and corrected for multiple comparisons. There were no significant between-group differences in demographic characteristics including age, sex and education. At the group-level, within-network FC, between-network FC, and segregation measurements of seven large-scale networks, including subcomponents of the DMN, were not a primary differentiator between cognitively average aging and SuperAging phenotypes. Thus, FC within or between large-scale networks does not appear to be a primary driver of the exceptional memory performance observed in SuperAgers. These results have relevance for differentiating the role of FC changes associated with cognitive aging from those associated with ADRD.
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Affiliation(s)
- Bram R Diamond
- Mesulam Center for Cognitive Neurology and Alzheimer’s Disease, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
- Department of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
- Healthy Aging & Alzheimer’s Research Care (HAARC) Center, Department of Neurology, The University of Chicago, Chicago, IL 60637, USA
| | - Jaiashre Sridhar
- Mesulam Center for Cognitive Neurology and Alzheimer’s Disease, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Jessica Maier
- Department of Psychology, Florida State University, 1107 W Call St, Tallahassee, FL 32304, USA
| | - Adam C Martersteck
- Healthy Aging & Alzheimer’s Research Care (HAARC) Center, Department of Neurology, The University of Chicago, Chicago, IL 60637, USA
| | - Emily J Rogalski
- Healthy Aging & Alzheimer’s Research Care (HAARC) Center, Department of Neurology, The University of Chicago, Chicago, IL 60637, USA
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Islam MA, Sehar U, Sultana OF, Mukherjee U, Brownell M, Kshirsagar S, Reddy PH. SuperAgers and centenarians, dynamics of healthy ageing with cognitive resilience. Mech Ageing Dev 2024; 219:111936. [PMID: 38657874 DOI: 10.1016/j.mad.2024.111936] [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: 03/08/2024] [Revised: 04/08/2024] [Accepted: 04/16/2024] [Indexed: 04/26/2024]
Abstract
Graceful healthy ageing and extended longevity is the most desired goal for human race. The process of ageing is inevitable and has a profound impact on the gradual deterioration of our physiology and health since it triggers the onset of many chronic conditions like dementia, osteoporosis, diabetes, arthritis, cancer, and cardiovascular disease. However, some people who lived/live more than 100 years called 'Centenarians" and how do they achieve their extended lifespans are not completely understood. Studying these unknown factors of longevity is important not only to establish a longer human lifespan but also to manage and treat people with shortened lifespans suffering from age-related morbidities. Furthermore, older adults who maintain strong cognitive function are referred to as "SuperAgers" and may be resistant to risk factors linked to cognitive decline. Investigating the mechanisms underlying their cognitive resilience may contribute to the development of therapeutic strategies that support the preservation of cognitive function as people age. The key to a long, physically, and cognitively healthy life has been a mystery to scientists for ages. Developments in the medical sciences helps us to a better understanding of human physiological function and greater access to medical care has led us to an increase in life expectancy. Moreover, inheriting favorable genetic traits and adopting a healthy lifestyle play pivotal roles in promoting longer and healthier lives. Engaging in regular physical activity, maintaining a balanced diet, and avoiding harmful habits such as smoking contribute to overall well-being. The synergy between positive lifestyle choices, access to education, socio-economic factors, environmental determinants and genetic supremacy enhances the potential for a longer and healthier life. Our article aims to examine the factors associated with healthy ageing, particularly focusing on cognitive health in centenarians. We will also be discussing different aspects of ageing including genomic instability, metabolic burden, oxidative stress and inflammation, mitochondrial dysfunction, cellular senescence, immunosenescence, and sarcopenia.
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Affiliation(s)
- Md Ariful Islam
- Department of Internal Medicine, Texas Tech University Health Sciences Center, Lubbock, TX, USA
| | - Ujala Sehar
- Department of Internal Medicine, Texas Tech University Health Sciences Center, Lubbock, TX, USA
| | - Omme Fatema Sultana
- Department of Internal Medicine, Texas Tech University Health Sciences Center, Lubbock, TX, USA
| | - Upasana Mukherjee
- Department of Internal Medicine, Texas Tech University Health Sciences Center, Lubbock, TX, USA
| | - Malcolm Brownell
- Department of Internal Medicine, Texas Tech University Health Sciences Center, Lubbock, TX, USA
| | - Sudhir Kshirsagar
- Department of Internal Medicine, Texas Tech University Health Sciences Center, Lubbock, TX, USA
| | - P Hemachandra Reddy
- Department of Internal Medicine, Texas Tech University Health Sciences Center, Lubbock, TX, USA; Public Health Department of Graduate School of Biomedical Sciences, Texas Tech University Health Sciences Center, Lubbock, TX 79430, USA; Department of Speech, Language and Hearing Sciences, School Health Professions, Texas Tech University Health Sciences Center, Lubbock, TX 79430, USA; Neurology, Departments of School of Medicine, Texas Tech University Health Sciences Center, Lubbock, TX 79430, USA; Department of Pharmacology and Neuroscience, Texas Tech University Health Sciences Center, Lubbock, TX 79430, USA; Nutritional Sciences Department, College of Human Sciences, Texas Tech University, 1301 Akron Ave, Lubbock, TX 79409, USA.
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Sansare A, Magalhaes TNC, Bernard JA. Relationships between balance performance and connectivity of motor cortex with primary somatosensory cortex and cerebellum in middle aged and older adults. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.29.587335. [PMID: 38853847 PMCID: PMC11160571 DOI: 10.1101/2024.03.29.587335] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2024]
Abstract
Connectivity of somatosensory cortex (S1) and cerebellum with the motor cortex (M1) is critical for balance control. While both S1-M1 and cerebellar-M1 connections are affected with aging, the implications of altered connectivity for balance control are not known. We investigated the relationship between S1-M1 and cerebellar-M1 connectivity and standing balance in middle-aged and older adults. Our secondary objective was to investigate how cognition affected the relationship between connectivity and balance. Our results show that greater S1-M1 and cerebellar-M1 connectivity was related to greater postural sway during standing. This may be indicative of an increase in functional recruitment of additional brain networks to maintain upright balance despite differences in network connectivity. Also, cognition moderated the relationship between S1-M1 connectivity and balance, such that those with lower cognition had a stronger relationship between connectivity and balance performance. It may be that individuals with poor cognition need increased recruitment of brain regions (compensation for cognitive declines) and in turn, higher wiring costs, which would be associated with increased functional connectivity.
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McMorris T, Hale BJ, Pine BS, Williams TB. Creatine supplementation research fails to support the theoretical basis for an effect on cognition: Evidence from a systematic review. Behav Brain Res 2024; 466:114982. [PMID: 38582412 DOI: 10.1016/j.bbr.2024.114982] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2023] [Revised: 02/15/2024] [Accepted: 04/02/2024] [Indexed: 04/08/2024]
Abstract
Creatine supplementation has been put forward as a possible aid to cognition, particularly for vegans, vegetarians, the elderly, sleep deprived and hypoxic individuals. However, previous narrative reviews have only provided limited support for these claims. This is despite the fact that research has shown that creatine supplementation can induce increased brain concentrations of creatine, albeit to a limited extent. We carried out a systematic review to examine the current state of affairs. The review supported claims that creatine supplementation can increases brain creatine content but also demonstrated somewhat equivocal results for effects on cognition. It does, however, provide evidence to suggest that more research is required with stressed populations, as supplementation does appear to significantly affect brain content. Issues with research design, especially supplementation regimens, need to be addressed. Future research must include measurements of creatine brain content.
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Affiliation(s)
- Terry McMorris
- Institue of Sport, Nursing and Allied Health, University of Chichester, College Lane, Chichester PO19 6PE, United Kingdom; Department of Sport and Exercise Science, University of Portsmouth, Spinnaker Building, Cambridge Road, Portsmouth PO12ER, United Kingdom.
| | - Beverley J Hale
- Institue of Sport, Nursing and Allied Health, University of Chichester, College Lane, Chichester PO19 6PE, United Kingdom
| | - Beatrice S Pine
- Institue of Sport, Nursing and Allied Health, University of Chichester, College Lane, Chichester PO19 6PE, United Kingdom
| | - Thomas B Williams
- Department of Sport and Exercise Science, University of Portsmouth, Spinnaker Building, Cambridge Road, Portsmouth PO12ER, United Kingdom
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Fleming LL, Defenderfer M, Demirayak P, Stewart P, Decarlo DK, Visscher KM. Impact of deprivation and preferential usage on functional connectivity between early visual cortex and category selective visual regions. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.17.593020. [PMID: 38798355 PMCID: PMC11118586 DOI: 10.1101/2024.05.17.593020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/29/2024]
Abstract
Human behavior can be remarkably shaped by experience, such as the removal of sensory input. Many studies of conditions such as stroke, limb amputation, and vision loss have examined how the removal of input changes brain function. However, an important question has yet to be answered: when input is lost, does the brain change its connectivity to preferentially use some remaining inputs over others? In individuals with healthy vision, the central portion of the retina is preferentially used for everyday visual tasks, due to its ability to discriminate fine details. However, when central vision is lost in conditions like macular degeneration, peripheral vision must be relied upon for those everyday tasks, with certain portions receiving "preferential" usage over others. Using resting-state fMRI collected during total darkness, we examined how deprivation and preferential usage influence the intrinsic functional connectivity of sensory cortex by studying individuals with selective vision loss due to late stages of macular degeneration. We found that cortical regions representing spared portions of the peripheral retina, regardless of whether they are preferentially used, exhibit plasticity of intrinsic functional connectivity in macular degeneration. Cortical representations of spared peripheral retinal locations showed stronger connectivity to MT, a region involved in processing motion. These results suggest that long-term loss of central vision can produce widespread effects throughout spared representations in early visual cortex, regardless of whether those representations are preferentially used. These findings support the idea that connections to visual cortex maintain the capacity for change well after critical periods of visual development. Highlights Portions of early visual cortex representing central vs. peripheral vision exhibit different patterns of connectivity to category-selective visual regions.When central vision is lost, cortical representations of peripheral vision display stronger functional connections to MT than central representations.When central vision is lost, connectivity to regions selective for tasks that involve central vision (FFA and PHA) are not significantly altered.These effects do not depend on which locations of peripheral vision are used more.
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Pan Y, Bi C, Kochunov P, Shardell M, Smith JC, McCoy RG, Ye Z, Yu J, Lu T, Yang Y, Lee H, Liu S, Gao S, Ma Y, Li Y, Chen C, Ma T, Wang Z, Nichols T, Hong LE, Chen S. Brain-wide functional connectome analysis of 40,000 individuals reveals brain networks that show aging effects in older adults. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.17.594743. [PMID: 38798606 PMCID: PMC11118564 DOI: 10.1101/2024.05.17.594743] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/29/2024]
Abstract
The functional connectome changes with aging. We systematically evaluated aging related alterations in the functional connectome using a whole-brain connectome network analysis in 39,675 participants in UK Biobank project. We used adaptive dense network discovery tools to identify networks directly associated with aging from resting-state fMRI data. We replicated our findings in 499 participants from the Lifespan Human Connectome Project in Aging study. The results consistently revealed two motor-related subnetworks (both permutation test p-values <0.001) that showed a decline in resting-state functional connectivity (rsFC) with increasing age. The first network primarily comprises sensorimotor and dorsal/ventral attention regions from precentral gyrus, postcentral gyrus, superior temporal gyrus, and insular gyrus, while the second network is exclusively composed of basal ganglia regions, namely the caudate, putamen, and globus pallidus. Path analysis indicates that white matter fractional anisotropy mediates 19.6% (p<0.001, 95% CI [7.6% 36.0%]) and 11.5% (p<0.001, 95% CI [6.3% 17.0%]) of the age-related decrease in both networks, respectively. The total volume of white matter hyperintensity mediates 32.1% (p<0.001, 95% CI [16.8% 53.0%]) of the aging-related effect on rsFC in the first subnetwork.
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Affiliation(s)
- Yezhi Pan
- Maryland Psychiatric Research Center, Department of Psychiatry, School of Medicine, University of Maryland, Baltimore, Maryland, United States of America
| | - Chuan Bi
- Maryland Psychiatric Research Center, Department of Psychiatry, School of Medicine, University of Maryland, Baltimore, Maryland, United States of America
| | - Peter Kochunov
- Department of Psychiatry and Behavioral Science, University of Texas Health Science Center Houston, Houston, United States of America
| | - Michelle Shardell
- Department of Epidemiology and Public Health and Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, Maryland, United States of America
| | - J. Carson Smith
- Department of Kinesiology, University of Maryland, College Park, Maryland, United States of America
| | - Rozalina G. McCoy
- Division of Endocrinology, Diabetes, & Nutrition, Department of Medicine, School of Medicine, University of Maryland, Baltimore, Maryland, United States of America
| | - Zhenyao Ye
- Maryland Psychiatric Research Center, Department of Psychiatry, School of Medicine, University of Maryland, Baltimore, Maryland, United States of America
- Division of Biostatistics and Bioinformatics, Department of Epidemiology and Public Health, School of Medicine, University of Maryland, Baltimore, Maryland, United States of America
| | - Jiaao Yu
- Department of Mathematics, University of Maryland, College Park, Maryland, United States of America
| | - Tong Lu
- Department of Mathematics, University of Maryland, College Park, Maryland, United States of America
| | - Yifan Yang
- Department of Mathematics, University of Maryland, College Park, Maryland, United States of America
| | - Hwiyoung Lee
- Maryland Psychiatric Research Center, Department of Psychiatry, School of Medicine, University of Maryland, Baltimore, Maryland, United States of America
| | - Song Liu
- School of Computer Science and Technology, Qilu University of Technology (Shandong Academy of Sciences), Jinan, Shandong, China
| | - Si Gao
- Maryland Psychiatric Research Center, Department of Psychiatry, School of Medicine, University of Maryland, Baltimore, Maryland, United States of America
| | - Yizhou Ma
- Maryland Psychiatric Research Center, Department of Psychiatry, School of Medicine, University of Maryland, Baltimore, Maryland, United States of America
| | - Yiran Li
- Department of Diagnostic Radiology & Nuclear Medicine, University of Maryland School of Medicine, Baltimore, Maryland, United States of America
| | - Chixiang Chen
- Division of Biostatistics and Bioinformatics, Department of Epidemiology and Public Health, School of Medicine, University of Maryland, Baltimore, Maryland, United States of America
| | - Tianzhou Ma
- Department of Epidemiology and Biostatistics, School of Public Health, University of Maryland, College Park, Maryland, United States of America
| | - Ze Wang
- Department of Diagnostic Radiology & Nuclear Medicine, University of Maryland School of Medicine, Baltimore, Maryland, United States of America
| | - Thomas Nichols
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - L. Elliot Hong
- Department of Psychiatry and Behavioral Science, University of Texas Health Science Center Houston, Houston, United States of America
| | - Shuo Chen
- Maryland Psychiatric Research Center, Department of Psychiatry, School of Medicine, University of Maryland, Baltimore, Maryland, United States of America
- Division of Biostatistics and Bioinformatics, Department of Epidemiology and Public Health, School of Medicine, University of Maryland, Baltimore, Maryland, United States of America
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James C, Müller D, Müller C, Van De Looij Y, Altenmüller E, Kliegel M, Van De Ville D, Marie D. Randomized controlled trials of non-pharmacological interventions for healthy seniors: Effects on cognitive decline, brain plasticity and activities of daily living-A 23-year scoping review. Heliyon 2024; 10:e26674. [PMID: 38707392 PMCID: PMC11066598 DOI: 10.1016/j.heliyon.2024.e26674] [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: 10/19/2022] [Revised: 01/28/2024] [Accepted: 02/16/2024] [Indexed: 05/07/2024] Open
Abstract
Little is known about the simultaneous effects of non-pharmacological interventions (NPI) on healthy older adults' behavior and brain plasticity, as measured by psychometric instruments and magnetic resonance imaging (MRI). The purpose of this scoping review was to compile an extensive list of randomized controlled trials published from January 1, 2000, to August 31, 2023, of NPI for mitigating and countervailing age-related physical and cognitive decline and associated cerebral degeneration in healthy elderly populations with a mean age of 55 and over. After inventorying the NPI that met our criteria, we divided them into six classes: single-domain cognitive, multi-domain cognitive, physical aerobic, physical non-aerobic, combined cognitive and physical aerobic, and combined cognitive and physical non-aerobic. The ultimate purpose of these NPI was to enhance individual autonomy and well-being by bolstering functional capacity that might transfer to activities of daily living. The insights from this study can be a starting point for new research and inform social, public health, and economic policies. The PRISMA extension for scoping reviews (PRISMA-ScR) checklist served as the framework for this scoping review, which includes 70 studies. Results indicate that medium- and long-term interventions combining non-aerobic physical exercise and multi-domain cognitive interventions best stimulate neuroplasticity and protect against age-related decline and that outcomes may transfer to activities of daily living.
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Affiliation(s)
- C.E. James
- Geneva Musical Minds Lab (GEMMI Lab), Geneva School of Health Sciences, University of Applied Sciences and Arts Western Switzerland HES-SO, Avenue de Champel 47, 1206, Geneva, Switzerland
- Faculty of Psychology and Educational Sciences, University of Geneva, Boulevard Carl-Vogt 101, 1205, Geneva, Switzerland
| | - D.M. Müller
- Geneva Musical Minds Lab (GEMMI Lab), Geneva School of Health Sciences, University of Applied Sciences and Arts Western Switzerland HES-SO, Avenue de Champel 47, 1206, Geneva, Switzerland
| | - C.A.H. Müller
- Geneva Musical Minds Lab (GEMMI Lab), Geneva School of Health Sciences, University of Applied Sciences and Arts Western Switzerland HES-SO, Avenue de Champel 47, 1206, Geneva, Switzerland
| | - Y. Van De Looij
- Geneva Musical Minds Lab (GEMMI Lab), Geneva School of Health Sciences, University of Applied Sciences and Arts Western Switzerland HES-SO, Avenue de Champel 47, 1206, Geneva, Switzerland
- Division of Child Development and Growth, Department of Pediatrics, School of Medicine, University of Geneva, 6 Rue Willy Donzé, 1205 Geneva, Switzerland
- Center for Biomedical Imaging (CIBM), Animal Imaging and Technology Section, Ecole Polytechnique Fédérale de Lausanne (EPFL), CH F1 - Station 6, 1015, Lausanne, Switzerland
| | - E. Altenmüller
- Hannover University of Music, Drama and Media, Institute for Music Physiology and Musicians' Medicine, Neues Haus 1, 30175, Hannover, Germany
- Center for Systems Neuroscience, Bünteweg 2, 30559, Hannover, Germany
| | - M. Kliegel
- Faculty of Psychology and Educational Sciences, University of Geneva, Boulevard Carl-Vogt 101, 1205, Geneva, Switzerland
- Center for the Interdisciplinary Study of Gerontology and Vulnerability, University of Geneva, Switzerland, Chemin de Pinchat 22, 1207, Carouge, Switzerland
| | - D. Van De Ville
- Ecole polytechnique fédérale de Lausanne (EPFL), Neuro-X Institute, Campus Biotech, 1211 Geneva, Switzerland
- University of Geneva, Department of Radiology and Medical Informatics, Faculty of Medecine, Campus Biotech, 1211 Geneva, Switzerland
| | - D. Marie
- Geneva Musical Minds Lab (GEMMI Lab), Geneva School of Health Sciences, University of Applied Sciences and Arts Western Switzerland HES-SO, Avenue de Champel 47, 1206, Geneva, Switzerland
- CIBM Center for Biomedical Imaging, Cognitive and Affective Neuroimaging Section, University of Geneva, 1211, Geneva, Switzerland
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