1
|
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.
Collapse
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
| |
Collapse
|
2
|
Hou J, King TZ, Chen H, Wang Q, Xie Y, Mao H, Wang L, Cheng L. Concurrent brain structural and functional alterations in the thalamus of adult survivors of childhood brain tumors: a multimodal MRI study. Brain Res Bull 2024; 211:110937. [PMID: 38570077 DOI: 10.1016/j.brainresbull.2024.110937] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Revised: 03/20/2024] [Accepted: 03/31/2024] [Indexed: 04/05/2024]
Abstract
Adult survivors of childhood brain tumors often present with cognitive deficits that affect their quality of life. Studying brain structure and function in brain tumor survivors can help understand the underlying mechanisms of their cognitive deficits to improve long-term prognosis of these patients. This study analyzed voxel-based morphometry (VBM) derived from T1-weighted MRI and the amplitude of low-frequency fluctuation (ALFF) from resting-state functional magnetic resonance imaging (rs-fMRI) to examine the structural and functional alterations in 35 brain tumor survivors using 35 matching healthy individuals as controls. Compared with healthy controls, brain tumor survivors had decreased gray matter volumes (GMV) in the thalamus and increased GMV in the superior frontal gyrus. Functionally, brain tumor survivors had lower ALFF values in the inferior temporal gyrus and medial prefrontal area and higher ALFF values in the thalamus. Importantly, we found concurrent but negatively correlated structural and functional alterations in the thalamus based on observed significant differences in GMV and ALFF values. These findings on concurrent brain structural and functional alterations provide new insights towards a better understanding of the cognitive deficits in brain tumor survivors.
Collapse
Affiliation(s)
- Jinfeng Hou
- School of Life and Environmental Sciences, Guilin University of Electronic Technology, Guilin 541004, China; Nanning Research Institute, Guilin University of Electronic Technology, Nanning 530000, China
| | - Tricia Z King
- Department of Psychology and the Neuroscience Institute, Georgia State University, Atlanta, GA, USA
| | - Hongbo Chen
- School of Life and Environmental Sciences, Guilin University of Electronic Technology, Guilin 541004, China; Guangxi Colleges and Universities Key Laboratory of Biomedical Sensors and Intelligent Instruments, Guilin 541004, China; Guangxi Human Physiological Information Non-Invasive Detection Engineering Technology Research Center, Guilin 541004, China; Guangxi Key Laboratory of Metabolic Reprogramming and Intelligent Medical Engineering for Chronic Diseases, Guilin 541004, China
| | - Qian Wang
- School of Life and Environmental Sciences, Guilin University of Electronic Technology, Guilin 541004, China; Nanning Research Institute, Guilin University of Electronic Technology, Nanning 530000, China
| | - You Xie
- Guilin Municipal Hospital of Traditional Chinese Medicine, Guilin 541004, China
| | - Hui Mao
- Department of Radiology and Imaging Science, Emory University, Atlanta, GA, USA
| | - Liya Wang
- Department of Radiology, The Fist Affiliated Hospital of Nanchang University, Shenzhen Hezheng Hospital, Shenzhen, Guangdong 518109, China.
| | - Luqi Cheng
- School of Life and Environmental Sciences, Guilin University of Electronic Technology, Guilin 541004, China; Guangxi Colleges and Universities Key Laboratory of Biomedical Sensors and Intelligent Instruments, Guilin 541004, China; Guangxi Human Physiological Information Non-Invasive Detection Engineering Technology Research Center, Guilin 541004, China; Guangxi Key Laboratory of Metabolic Reprogramming and Intelligent Medical Engineering for Chronic Diseases, Guilin 541004, China; Zhejiang Lab, Hangzhou 311100, China.
| |
Collapse
|
3
|
Long J, Song X, Wang C, Peng L, Niu L, Li Q, Huang R, Zhang R. Global-brain functional connectivity related with trait anxiety and its association with neurotransmitters and gene expression profiles. J Affect Disord 2024; 348:248-258. [PMID: 38159654 DOI: 10.1016/j.jad.2023.12.052] [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: 08/10/2023] [Revised: 11/30/2023] [Accepted: 12/23/2023] [Indexed: 01/03/2024]
Abstract
BACKGROUND Numerous studies have explored the neural correlates of trait anxiety, a predisposing factor for several stress-related disorders. However, the findings from previous studies are inconsistent, which might be due to the limited regions of interest (ROI). A recent approach, named global-brain functional connectivity (GBC), has been demonstrated to address the shortcomings of ROI-based analysis. Furthermore, research on the transcriptome-connectome association has provided an approach to link the microlevel transcriptome profile with the macroscale brain network. In this paper, we aim to explore the neurobiology of trait anxiety with an imaging transcriptomic approach using GBC, biological neurotransmitters, and transcriptome profiles. METHODS Using a sample of resting-state fMRI data, we investigated trait anxiety-related alteration in GBC. We further used behavioral analysis, spatial correlation analysis, and postmortem gene expression to separately assess the cognitive functions, neurotransmitters, and transcriptional profiles related to alteration in GBC in individuals with trait anxiety. RESULTS GBC values in the ventromedial prefrontal cortex and the precuneus were negatively correlated with levels of trait anxiety. This alteration was correlated with behavioral terms including social cognition, emotion, and memory. A strong association was revealed between trait anxiety-related alteration in GBC and neurotransmitters, including dopaminergic, serotonergic, GABAergic, and glutamatergic systems in the ventromedial prefrontal cortex and the precuneus. The transcriptional profiles explained the functional connectivity, with correlated genes enriched in transmembrane signaling. LIMITATIONS Several limitations should be taken into account in this research. For example, future research should consider using some different approaches based on dynamic or task-based functional connectivity analysis, include more neurotransmitter receptors, additional gene expression data from different samples or more genes related to other stress-related disorders. Meanwhile, it is of great significance to include a larger sample size of individuals with a diagnosis of major depression disorder or other disorders for analysis and comparison and apply stricter multiple-comparison correction and threshold settings in future research. CONCLUSIONS Our research employed multimodal data to investigate GBC in the context of trait anxiety and to establish its associations with neurotransmitters and transcriptome profiles. This approach may improve understanding of the neural mechanism, together with the biological and molecular genetic foundations of GBC in trait anxiety.
Collapse
Affiliation(s)
- Jixin Long
- Laboratory of Cognitive Control and Brain Healthy, Department of Psychology, School of Public Health, Southern Medical University, Guangzhou, China
| | - Xiaoqi Song
- Laboratory of Cognitive Control and Brain Healthy, Department of Psychology, School of Public Health, Southern Medical University, Guangzhou, China
| | - Chanyu Wang
- Laboratory of Cognitive Control and Brain Healthy, Department of Psychology, School of Public Health, Southern Medical University, Guangzhou, China; Faculty of Medicine and Health Sciences, Department of Head and Skin, Ghent Experimental Psychiatry (GHEP) lab, Ghent University, Ghent, Belgium
| | - Lanxin Peng
- Laboratory of Cognitive Control and Brain Healthy, Department of Psychology, School of Public Health, Southern Medical University, Guangzhou, China
| | - Lijing Niu
- Laboratory of Cognitive Control and Brain Healthy, Department of Psychology, School of Public Health, Southern Medical University, Guangzhou, China
| | - Qian Li
- Laboratory of Cognitive Control and Brain Healthy, Department of Psychology, School of Public Health, Southern Medical University, Guangzhou, China
| | - Ruiwang Huang
- School of Psychology, South China Normal University, Guangzhou, China
| | - Ruibin Zhang
- Laboratory of Cognitive Control and Brain Healthy, Department of Psychology, School of Public Health, Southern Medical University, Guangzhou, China; Department of Psychiatry, Zhujiang Hospital, Southern Medical University, Guangzhou, China.
| |
Collapse
|
4
|
Golestani AM, Chen JJ. Comparing data-driven physiological denoising approaches for resting-state fMRI: implications for the study of aging. Front Neurosci 2024; 18:1223230. [PMID: 38379761 PMCID: PMC10876882 DOI: 10.3389/fnins.2024.1223230] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Accepted: 01/17/2024] [Indexed: 02/22/2024] Open
Abstract
Introduction Physiological nuisance contributions by cardiac and respiratory signals have a significant impact on resting-state fMRI data quality. As these physiological signals are often not recorded, data-driven denoising methods are commonly used to estimate and remove physiological noise from fMRI data. To investigate the efficacy of these denoising methods, one of the first steps is to accurately capture the cardiac and respiratory signals, which requires acquiring fMRI data with high temporal resolution. Methods In this study, we used such high-temporal resolution fMRI data to evaluate the effectiveness of several data-driven denoising methods, including global-signal regression (GSR), white matter and cerebrospinal fluid regression (WM-CSF), anatomical (aCompCor) and temporal CompCor (tCompCor), ICA-AROMA. Our analysis focused on the consequence of changes in low-frequency, cardiac and respiratory signal power, as well as age-related differences in terms of functional connectivity (fcMRI). Results Our results confirm that the ICA-AROMA and GSR removed the most physiological noise but also more low-frequency signals. These methods are also associated with substantially lower age-related fcMRI differences. On the other hand, aCompCor and tCompCor appear to be better at removing high-frequency physiological signals but not low-frequency signal power. These methods are also associated with relatively higher age-related fcMRI differences, whether driven by neuronal signal or residual artifact. These results were reproduced in data downsampled to represent conventional fMRI sampling frequency. Lastly, methods differ in performance depending on the age group. Discussion While this study cautions direct comparisons of fcMRI results based on different denoising methods in the study of aging, it also enhances the understanding of different denoising methods in broader fcMRI applications.
Collapse
Affiliation(s)
- Ali M. Golestani
- Department of Physics and Astronomy, University of Calgary, Calgary, AB, Canada
- Department of Oncology, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - J. Jean Chen
- Rotman Research Institute at Baycrest, Toronto, ON, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
- Department of Biomedical Engineering, University of Toronto, Toronto, ON, Canada
| |
Collapse
|
5
|
Niu L, Song X, Li Q, Peng L, Dai H, Zhang J, Chen K, Lee TMC, Zhang R. Age-related positive emotional reactivity decline associated with the anterior insula based resting-state functional connectivity. Hum Brain Mapp 2024; 45:e26621. [PMID: 38339823 PMCID: PMC10858337 DOI: 10.1002/hbm.26621] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Revised: 01/17/2024] [Accepted: 01/26/2024] [Indexed: 02/12/2024] Open
Abstract
Recent studies have suggested that emotional reactivity changes with age, but the neural basis is still unclear. The insula may be critical for the emotional reactivity. The current study examined how ageing affects emotional reactivity using the emotional reactivity task data from a human sample (Cambridge Center for Age and Neuroscience, N = 243, age 18-88 years). The resting-state magnetic resonance measurements from the same sample were used to investigate the potential mechanisms of the insula. In the initial analysis, we conducted partial correlation assessments to examine the associations between emotional reactivity and age, as well as between the gray matter volume (GMV) of the insula and age. Our results revealed that emotional reactivity, especially positive emotional reactivity, decreased with age and that the GMV of the insula was negatively correlated with age. Subsequently, the bilateral insula was divided into six subregions to calculate the whole brain resting-state functional connectivity (rsFC). The mediating effect of the rsFC on age and emotional reactivity was then calculated. The results showed that the rsFC of the left anterior insula (AI) with the right hippocampus, and the rsFCs of the right AI with the striatum and the thalamus were mediated the relationship between positive emotional reactivity and age. Our findings suggest that attenuating emotional reactivity with age may be a strategic adaptation fostering emotional stability and diminishing emotional vulnerability. Meanwhile, the findings implicate a key role for the AI in the changes in positive emotional reactivity with age.
Collapse
Affiliation(s)
- Lijing Niu
- Cognitive Control and Brain Healthy Laboratory, Department of Psychology, School of Public HealthSouthern Medical UniversityGuangzhouChina
| | - Xiaoqi Song
- Cognitive Control and Brain Healthy Laboratory, Department of Psychology, School of Public HealthSouthern Medical UniversityGuangzhouChina
- State Key Laboratory of Brain and Cognitive SciencesThe University of Hong KongHong KongSARChina
- Laboratory of Neuropsychology and Human NeuroscienceThe University of Hong KongHong KongSARChina
| | - Qian Li
- Cognitive Control and Brain Healthy Laboratory, Department of Psychology, School of Public HealthSouthern Medical UniversityGuangzhouChina
| | - Lanxin Peng
- Cognitive Control and Brain Healthy Laboratory, Department of Psychology, School of Public HealthSouthern Medical UniversityGuangzhouChina
| | - Haowei Dai
- Cognitive Control and Brain Healthy Laboratory, Department of Psychology, School of Public HealthSouthern Medical UniversityGuangzhouChina
| | - Jiayuan Zhang
- Cognitive Control and Brain Healthy Laboratory, Department of Psychology, School of Public HealthSouthern Medical UniversityGuangzhouChina
| | - Keyin Chen
- Cognitive Control and Brain Healthy Laboratory, Department of Psychology, School of Public HealthSouthern Medical UniversityGuangzhouChina
| | - Tatia M. C. Lee
- State Key Laboratory of Brain and Cognitive SciencesThe University of Hong KongHong KongSARChina
- Laboratory of Neuropsychology and Human NeuroscienceThe University of Hong KongHong KongSARChina
- Center for Brain Science and Brain‐Inspired IntelligenceGuangdong‐Hong Kong‐Macao Greater Bay AreaGuangzhouChina
| | - Ruibin Zhang
- Cognitive Control and Brain Healthy Laboratory, Department of Psychology, School of Public HealthSouthern Medical UniversityGuangzhouChina
- Department of Psychiatry, Zhujiang HospitalSouthern Medical UniversityGuangzhouPR China
| |
Collapse
|
6
|
Kim GW, Farabaugh AH, Vetterman R, Holmes A, Nyer M, Nasiriavanaki Z, Fava M, Holt DJ. Diminished frontal pole size and functional connectivity in young adults with high suicidality. J Affect Disord 2022; 310:484-492. [PMID: 35427718 DOI: 10.1016/j.jad.2022.04.069] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/14/2021] [Revised: 02/06/2022] [Accepted: 04/10/2022] [Indexed: 10/18/2022]
Abstract
BACKGROUND Suicide rates among young people have been increasing in recent years, yet no validated methods are available for identifying those who are at greatest risk for suicide. Abnormalities in the medial prefrontal cortex have been previously observed in suicidal individuals, but confounding factors such as treatment and chronic illness may have contributed to these findings. Thus, in this study we tested whether the size of the medial prefrontal cortex is altered in suicidal young adults who have received no treatment with psychotropic medications. METHODS Suicidality was evaluated using the Suicide Behaviors Questionnaire-Revised (SBQ-R) and surface areas of four regions-of-interest (ROIs) within the medial prefrontal cortex were measured using magnetic resonance imaging (MRI) in a cohort of college students (n = 102). In addition, a secondary seed-based functional connectivity analysis was conducted using resting-state functional MRI data. Areas and functional connectivity of the medial prefrontal cortex of young adults with high suicidality (HS; SBQ-R score > 7; n = 20) were compared to those with low suicidality (LS; SBQ-R score = 3, n = 37). RESULTS Compared to the LS group, the HS group had a significantly lower surface area of the right frontal pole (p < 0.05, Bonferroni-corrected) and significantly lower functional connectivity of the right frontal pole with the bilateral inferior frontal cortex (p < 0.001, Monte-Carlo corrected). LIMITATION These findings require replication in a larger sample and extension in younger (adolescent) populations. CONCLUSION Diminished frontal pole surface area and functional connectivity may be linked to elevated levels of suicidality in young people.
Collapse
Affiliation(s)
- Gwang-Won Kim
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, United States of America; Advanced Institute of Aging Science, Chonnam National University, Republic of Korea
| | - Amy H Farabaugh
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, United States of America
| | - Richard Vetterman
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, United States of America
| | - Avram Holmes
- Department of Psychology, Yale University, United States of America
| | - Maren Nyer
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, United States of America
| | - Zahra Nasiriavanaki
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, United States of America
| | - Maurizio Fava
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, United States of America
| | - Daphne J Holt
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, United States of America; Athinoula A. Martinos Center for Biomedical Imaging, United States of America.
| |
Collapse
|
7
|
Weiler M, Casseb RF, de Campos BM, Crone JS, Lutkenhoff ES, Vespa PM, Monti MM. Evaluating denoising strategies in resting-state functional magnetic resonance in traumatic brain injury (EpiBioS4Rx). Hum Brain Mapp 2022; 43:4640-4649. [PMID: 35723510 PMCID: PMC9491287 DOI: 10.1002/hbm.25979] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2022] [Revised: 05/17/2022] [Accepted: 05/29/2022] [Indexed: 11/11/2022] Open
Abstract
Resting-state functional MRI is increasingly used in the clinical setting and is now included in some diagnostic guidelines for severe brain injury patients. However, to ensure high-quality data, one should mitigate fMRI-related noise typical of this population. Therefore, we aimed to evaluate the ability of different preprocessing strategies to mitigate noise-related signal (i.e., in-scanner movement and physiological noise) in functional connectivity (FC) of traumatic brain injury (TBI) patients. We applied nine commonly used denoising strategies, combined into 17 pipelines, to 88 TBI patients from the Epilepsy Bioinformatics Study for Anti-epileptogenic Therapy clinical trial. Pipelines were evaluated by three quality control (QC) metrics across three exclusion regimes based on the participant's head movement profile. While no pipeline eliminated noise effects on FC, some pipelines exhibited relatively high effectiveness depending on the exclusion regime. Once high-motion participants were excluded, the choice of denoising pipeline becomes secondary - although this strategy leads to substantial data loss. Pipelines combining spike regression with physiological regressors were the best performers, whereas pipelines that used automated data-driven methods performed comparatively worse. In this study, we report the first large-scale evaluation of denoising pipelines aimed at reducing noise-related FC in a clinical population known to be highly susceptible to in-scanner motion and significant anatomical abnormalities. If resting-state functional magnetic resonance is to be a successful clinical technique, it is crucial that procedures mitigating the effect of noise be systematically evaluated in the most challenging populations, such as TBI datasets.
Collapse
Affiliation(s)
- Marina Weiler
- Department of Psychology, University of California Los Angeles, Los Angeles, California, USA
| | - Raphael F Casseb
- Neuroimaging Laboratory, University of Campinas, Campinas, São Paulo, Brazil
| | - Brunno M de Campos
- Neuroimaging Laboratory, University of Campinas, Campinas, São Paulo, Brazil
| | - Julia S Crone
- Department of Psychology, University of California Los Angeles, Los Angeles, California, USA
| | - Evan S Lutkenhoff
- Department of Psychology, University of California Los Angeles, Los Angeles, California, USA
| | - Paul M Vespa
- David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
| | - Martin M Monti
- Department of Psychology, University of California Los Angeles, Los Angeles, California, USA.,Department of Neurosurgery, Brain Injury Research Center, University of California Los Angeles, Los Angeles, California, USA
| | | |
Collapse
|
8
|
Zhang R, Tam SKTS, Wong NML, Wu J, Tao J, Chen L, Lin K, Lee TMC. Aberrant functional metastability and structural connectivity are associated with rumination in individuals with major depressive disorder. Neuroimage Clin 2022; 33:102916. [PMID: 34923200 PMCID: PMC8693354 DOI: 10.1016/j.nicl.2021.102916] [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: 07/14/2021] [Revised: 11/30/2021] [Accepted: 12/13/2021] [Indexed: 11/23/2022]
Abstract
Higher synchrony and lower metastability in adults with higher levels of rumination. Prefrontal white matter integrity deficits are also associated with rumination. Most prominent aberrations were found in the genu of the corpus callosum. Structural connectivity as the basis between dynamic connectivity and rumination. New outlook on altered structural integrity and metastability subserving rumination.
Rumination is a repetitive and compulsive thinking focusing on oneself, and the nature and consequences of distress. It is a core characteristic in psychiatric disorders characterized by affective dysregulation, and emerging evidence suggests that rumination is associated with aberrant dynamic functional connectivity and structural connectivity. However, the underlying neural mechanisms remain poorly understood. Here, we adopted a multimodal approach and tested the hypothesis that white matter connectivity forms the basis of the implications of temporal dynamics of functional connectivity in the rumination trait. Fifty-three depressed and ruminative individuals and a control group of 47 age- and gender-matched individuals with low levels of rumination underwent resting-state fMRI and diffusion tensor imaging. We found that lower global metastability and higher global synchrony of the dynamic functional connectivity were associated with higher levels of rumination. Specifically, the altered global synchrony and global metastability mediated the association between white matter integrity of the genu of the corpus callosum to rumination. Hence, our findings offered the first line of evidence for the intricate role of (sub)optimal transition of functional brain states in the connection of structural brain connectivity in ruminative thinking.
Collapse
Affiliation(s)
- Ruibin Zhang
- Laboratory of Cognitive Control and Brain Healthy, Department of Psychology, School of Public Health, Southern Medical University, Department of Psychiatry, Zhujiang Hospital, Southern Medical University, Guangzhou, China
| | - Sammi-Kenzie T S Tam
- State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong, China; Laboratory of Neuropsychology and Human Neuroscience, The University of Hong Kong, Hong Kong, China
| | - Nichol M L Wong
- State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong, China; Laboratory of Neuropsychology and Human Neuroscience, The University of Hong Kong, Hong Kong, China.
| | - Jingsong Wu
- Fujian University of Traditional Chinese Medicine, Fuzhou, China
| | - Jing Tao
- Fujian University of Traditional Chinese Medicine, Fuzhou, China
| | - Lidian Chen
- Fujian University of Traditional Chinese Medicine, Fuzhou, China
| | - Kangguang Lin
- Department of Affective Disorders, Guangzhou Huiai Hospital, The Affiliated Brain Hospital of Guangzhou Medical University, China.
| | - Tatia M C Lee
- State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong, China; Laboratory of Neuropsychology and Human Neuroscience, The University of Hong Kong, Hong Kong, China; Institute of Clinical Neuropsychology, The University of Hong Kong, Hong Kong, China.
| |
Collapse
|
9
|
Kelly RE, Hoptman MJ, Lee S, Alexopoulos GS, Gunning FM, McKeown MJ. Seed-based dual regression: An illustration of the impact of dual regression's inherent filtering of global signal. J Neurosci Methods 2022; 366:109410. [PMID: 34798212 PMCID: PMC8720564 DOI: 10.1016/j.jneumeth.2021.109410] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2021] [Revised: 10/05/2021] [Accepted: 11/09/2021] [Indexed: 01/17/2023]
Abstract
BACKGROUND Functional connectivity (FC) maps from brain fMRI data are often derived with seed-based methods that estimate temporal correlations between the time course in a predefined region (seed) and other brain regions (SCA, seed-based correlation analysis). Standard dual regression, which uses a set of spatial regressor maps, can detect FC with entire brain "networks," such as the default mode network, but may not be feasible when detecting FC associated with a single small brain region alone (for example, the amygdala). NEW METHOD We explored seed-based dual regression (SDR) from theoretical and practical points of view. SDR is a modified implementation of dual regression where the set of spatial regressors is replaced by a single binary spatial map of the seed region. RESULTS SDR allowed detection of FC with small brain regions. COMPARISON WITH EXISTING METHOD For both synthetic and natural fMRI data, detection of FC with SDR was identical to that obtained with SCA after removal of global signal from fMRI data with global signal regression (GSR). In the absence of GSR, detection of FC was significantly improved when using SDR compared with SCA. CONCLUSION The improved FC detection achieved with SDR was related to a partial filtering of the global signal that occurred during spatial regression, an integral part of dual regression. This filtering can sometimes lead to spurious negative correlations that result in a widespread negative bias in FC derived with any application of dual regression. We provide guidelines for how to identify and correct this potential problem.
Collapse
Affiliation(s)
- Robert E Kelly
- Department of Psychiatry, Weill Cornell Medical College, 21 Bloomingdale Road, White Plains, NY 10605, USA.
| | - Matthew J Hoptman
- Clinical Research Division, Nathan S. Kline Institute for Psychiatric Research,140 Old Orangeburg Road, Orangeburg, NY 10962, USA; Department of Psychiatry, New York University Grossman School of Medicine, 550 First Avenue, New York, NY 10016, USA.
| | - Soojin Lee
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, UK.
| | - George S Alexopoulos
- Department of Psychiatry, Weill Cornell Medical College, 21 Bloomingdale Road, White Plains, NY 10605, USA.
| | - Faith M Gunning
- Department of Psychiatry, Weill Cornell Medical College, 21 Bloomingdale Road, White Plains, NY 10605, USA.
| | - Martin J McKeown
- Neurology, Pacific Parkinson's Research Center, University of British Columbia, 2221 Wesbrook Mall, Vancouver, British Columbia V6T 2B5 Canada.
| |
Collapse
|
10
|
Lu X, Zhang JF, Gu F, Zhang HX, Zhang M, Zhang HS, Song RZ, Shi YC, Li K, Wang B, Zhang ZJ, Northoff G. Altered task modulation of global signal topography in the default-mode network of unmedicated major depressive disorder. J Affect Disord 2022; 297:53-61. [PMID: 34610369 DOI: 10.1016/j.jad.2021.09.093] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/19/2021] [Revised: 09/07/2021] [Accepted: 09/26/2021] [Indexed: 11/17/2022]
Abstract
BACKGROUND Altered global signal (GS) topography features in the resting-state fMRI of major depressive disorder (MDD), showing abnormally strong global signal representation in the default-mode network (DMN). Whether the abnormal local to global change also shapes activity during task states, and how it relates to psychopathological symptoms, e.g., abnormally slow time speed of motor, cognitive, and affective symptoms, remains unknown. METHODS We investigated fMRI-based GS with its topographical representation during task states in unmedicated 51 MDD subjects and 28 healthy subjects. Task-related global signal correlation (GSCORR) was probed by a novel paradigm testing the processing of negative/neutral emotions during different time speeds, i.e., slow and fast. RESULTS We observed a significant interaction between time speed and emotion of GSCORR in various DMN regions in healthy subjects. Next, we showed that MDD exhibits reduced task-related GSCORR in various DMN regions during specifically the fast processing of negative emotions. Finally, we demonstrated that GSCORR in DMN and other brain regions (motor-related regions, inferior frontal cortex) correlated with the degree of psychomotor retardation especially during the fast emotional stimuli. LIMITATIONS The measurement of interoceptive variables like respiration rate or heart rate were not included in our fMRI acquisition. CONCLUSION Together, we demonstrated the functional relevance of GS topography by showing reduced GSCORR in DMN during specifically the fast processing of negative emotions in MDD, suggesting the abnormal slowness, i.e., reduced time speed, to be a key feature of both brain and symptoms in MDD.
Collapse
Affiliation(s)
- Xiang Lu
- Department of Neurology of Affiliated ZhongDa Hospital, Institute of Neuropsychiatry and Medical School of Southeast University, Nanjing 210009, Jiangsu Province, China; Royal Ottawa Mental Health Centre, University of Ottawa(,) Institute of Mental Health Research(,) Ottawa(,) Ontario K1Z 7K4, Canada; Department of Neurology, Northern Jiangsu People's Hospital, Clinical Medical College, Yangzhou University(,) Yangzhou 225001, Jiangsu Province, China
| | - Jian-Feng Zhang
- Center for Brain Disorders and Cognitive Sciences(,) Shenzhen University, Shenzhen 518055, Guangdong Province, China
| | - Feng Gu
- Royal Ottawa Mental Health Centre, University of Ottawa(,) Institute of Mental Health Research(,) Ottawa(,) Ontario K1Z 7K4, Canada
| | - Hong-Xing Zhang
- Department of Psychology of Xinxiang Medical University, Xinxiang 453003, Henan Province, China; Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, Xinxiang 453002, Henan Province, China
| | - Meng Zhang
- Department of Psychology of Xinxiang Medical University, Xinxiang 453003, Henan Province, China
| | - Hai-San Zhang
- Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, Xinxiang 453002, Henan Province, China
| | - Rui-Ze Song
- Department of Neurology of Affiliated ZhongDa Hospital, Institute of Neuropsychiatry and Medical School of Southeast University, Nanjing 210009, Jiangsu Province, China
| | - Ya-Chen Shi
- Department of Neurology of Affiliated ZhongDa Hospital, Institute of Neuropsychiatry and Medical School of Southeast University, Nanjing 210009, Jiangsu Province, China
| | - Kun Li
- Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, Xinxiang 453002, Henan Province, China
| | - Bi Wang
- Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, Xinxiang 453002, Henan Province, China
| | - Zhi-Jun Zhang
- Department of Neurology of Affiliated ZhongDa Hospital, Institute of Neuropsychiatry and Medical School of Southeast University, Nanjing 210009, Jiangsu Province, China; Department of Psychology of Xinxiang Medical University, Xinxiang 453003, Henan Province, China; Mental Health Center, Zhejiang University School of Medicine, Hangzhou 310013, Zhejiang Province, China; Shenzhen institute of advanced technology, Chinese academy of sciences, Shenzhen 518055, Guangdong Province, China.
| | - Georg Northoff
- Department of Neurology of Affiliated ZhongDa Hospital, Institute of Neuropsychiatry and Medical School of Southeast University, Nanjing 210009, Jiangsu Province, China; Royal Ottawa Mental Health Centre, University of Ottawa(,) Institute of Mental Health Research(,) Ottawa(,) Ontario K1Z 7K4, Canada; Mental Health Center, Zhejiang University School of Medicine, Hangzhou 310013, Zhejiang Province, China; Brain and Mind Research Institute, Centre for Neural Dynamics, Faculty of Medicine, University of Ottawa(,) Ottawa, Ontario K1Z 7K4(,) Canada; Centre for Cognition and Brain Disorders, Hangzhou Normal University, Hangzhou 310013, Zhejiang Province, China.
| |
Collapse
|
11
|
Shi G, Li X, Zhu Y, Shang R, Sun Y, Guo H, Sui J. The divided brain: Functional brain asymmetry underlying self-construal. Neuroimage 2021; 240:118382. [PMID: 34252524 DOI: 10.1016/j.neuroimage.2021.118382] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2021] [Revised: 06/26/2021] [Accepted: 07/08/2021] [Indexed: 12/29/2022] Open
Abstract
Self-construal (orientations of independence and interdependence) is a fundamental concept that guides human behaviour, and it is linked to a large number of brain regions. However, understanding the connectivity of these regions and the critical principles underlying these self-functions are lacking. Because brain activity linked to self-related processes are intrinsic, the resting-state method has received substantial attention. Here, we focused on resting-state functional connectivity matrices based on brain asymmetry as indexed by the differential partition of the connectivity located in mirrored positions of the two hemispheres, hemispheric specialization measured using the intra-hemispheric (left or right) connectivity, brain communication via inter-hemispheric interactions, and global connectivity as the sum of the two intra-hemispheric connectivity. Combining machine learning techniques with hypothesis-driven network mapping approaches, we demonstrated that orientations of independence and interdependence were best predicted by the asymmetric matrix compared to brain communication, hemispheric specialization, and global connectivity matrices. The network results revealed that there were distinct asymmetric connections between the default mode network, the salience network and the executive control network which characterise independence and interdependence. These analyses shed light on the importance of brain asymmetry in understanding how complex self-functions are optimally represented in the brain networks.
Collapse
Affiliation(s)
- Gen Shi
- School of Computer Science and Technology, Beijing Institute of Technology, Beijing, PR China
| | - Xuesong Li
- School of Computer Science and Technology, Beijing Institute of Technology, Beijing, PR China.
| | - Yifan Zhu
- School of Computer Science and Technology, Beijing Institute of Technology, Beijing, PR China
| | - Ruihong Shang
- School of Computer Science and Technology, Beijing Institute of Technology, Beijing, PR China
| | - Yang Sun
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, PR China
| | - Hua Guo
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, PR China
| | - Jie Sui
- School of Psychology, University of Aberdeen, Aberdeen, UK.
| |
Collapse
|
12
|
Attarpour A, Ward J, Chen JJ. Vascular origins of low-frequency oscillations in the cerebrospinal fluid signal in resting-state fMRI: Interpretation using photoplethysmography. Hum Brain Mapp 2021; 42:2606-2622. [PMID: 33638224 PMCID: PMC8090775 DOI: 10.1002/hbm.25392] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2020] [Revised: 02/09/2021] [Accepted: 02/16/2021] [Indexed: 12/12/2022] Open
Abstract
In vivo mapping of cerebrovascular oscillations in the 0.05–0.15 Hz remains difficult. Oscillations in the cerebrospinal fluid (CSF) represent a possible avenue for noninvasively tracking these oscillations using resting‐state functional MRI (rs‐fMRI), and have been used to correct for vascular oscillations in rs‐fMRI functional connectivity. However, the relationship between low‐frequency CSF and vascular oscillations remains unclear. In this study, we investigate this relationship using fast simultaneous rs‐fMRI and photoplethysmogram (PPG), examining the 0.1 Hz PPG signal, heart‐rate variability (HRV), pulse‐intensity ratio (PIR), and the second derivative of the PPG (SDPPG). The main findings of this study are: (a) signals in different CSF regions are not equivalent in their associations with vascular and tissue rs‐fMRI signals; (b) the PPG signal is maximally coherent with the arterial and CSF signals at the cardiac frequency, but coherent with brain tissue at ~0.2 Hz; (c) PIR is maximally coherent with the CSF signal near 0.03 Hz; and (d) PPG‐related vascular oscillations only contribute to ~15% of the CSF (and arterial) signal in rs‐fMRI. These findings caution against averaging all CSF regions when extracting physiological nuisance regressors in rs‐fMRI applications, and indicate the drivers of the CSF signal are more than simply cardiac. Our study is an initial attempt at the refinement and standardization of how the CSF signal in rs‐fMRI can be used and interpreted. It also paves the way for using rs‐fMRI in the CSF as a potential tool for tracking cerebrovascular health through, for instance, the potential relationship between PIR and the CSF signal.
Collapse
Affiliation(s)
- Ahmadreza Attarpour
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
| | - James Ward
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Ontario, Canada
| | - J Jean Chen
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada.,Rotman Research Institute, Baycrest Health Sciences, Toronto, Ontario, Canada
| |
Collapse
|
13
|
Chen Y, Tang J, Chen Y, Farrand J, Craft MA, Carlson BW, Yuan H. Amplitude of fNIRS Resting-State Global Signal Is Related to EEG Vigilance Measures: A Simultaneous fNIRS and EEG Study. Front Neurosci 2020; 14:560878. [PMID: 33343275 PMCID: PMC7744746 DOI: 10.3389/fnins.2020.560878] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2020] [Accepted: 11/11/2020] [Indexed: 12/21/2022] Open
Abstract
Recently, functional near-infrared spectroscopy (fNIRS) has been utilized to image the hemodynamic activities and connectivity in the human brain. With the advantage of economic efficiency, portability, and fewer physical constraints, fNIRS enables studying of the human brain at versatile environment and various body positions, including at bed side and during exercise, which complements the use of functional magnetic resonance imaging (fMRI). However, like fMRI, fNIRS imaging can be influenced by the presence of a strong global component. Yet, the nature of the global signal in fNIRS has not been established. In this study, we investigated the relationship between fNIRS global signal and electroencephalogram (EEG) vigilance using simultaneous recordings in resting healthy subjects in high-density and whole-head montage. In Experiment 1, data were acquired at supine, sitting, and standing positions. Results found that the factor of body positions significantly affected the amplitude of the resting-state fNIRS global signal, prominently in the frequency range of 0.05-0.1 Hz but not in the very low frequency range of less than 0.05 Hz. As a control, the task-induced fNIRS or EEG responses to auditory stimuli did not differ across body positions. However, EEG vigilance plays a modulatory role in the fNIRS signals in the frequency range of less than 0.05 Hz: resting-state sessions of low EEG vigilance measures are associated with high amplitudes of fNIRS global signals. Moreover, in Experiment 2, we further examined the epoch-to-epoch fluctuations in concurrent fNIRS and EEG data acquired from a separate group of subjects and found a negative temporal correlation between EEG vigilance measures and fNIRS global signal amplitudes. Our study for the first time revealed that vigilance as a neurophysiological factor modulates the resting-state dynamics of fNIRS, which have important implications for understanding and processing the noises in fNIRS signals.
Collapse
Affiliation(s)
- Yuxuan Chen
- School of Electrical and Computer Engineering, University of Oklahoma, Norman, OK, United States
| | - Julia Tang
- Stephenson School of Biomedical Engineering, University of Oklahoma, Norman, OK, United States
| | - Yafen Chen
- Stephenson School of Biomedical Engineering, University of Oklahoma, Norman, OK, United States
| | - Jesse Farrand
- Stephenson School of Biomedical Engineering, University of Oklahoma, Norman, OK, United States
| | - Melissa A. Craft
- Fran and Earl Ziegler College of Nursing, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States
| | - Barbara W. Carlson
- Fran and Earl Ziegler College of Nursing, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States
| | - Han Yuan
- Stephenson School of Biomedical Engineering, University of Oklahoma, Norman, OK, United States
- Institute for Biomedical Engineering, Science, and Technology, University of Oklahoma, Norman, OK, United States
| |
Collapse
|
14
|
Madden DJ, Jain S, Monge ZA, Cook AD, Lee A, Huang H, Howard CM, Cohen JR. Influence of structural and functional brain connectivity on age-related differences in fluid cognition. Neurobiol Aging 2020; 96:205-222. [PMID: 33038808 PMCID: PMC7722190 DOI: 10.1016/j.neurobiolaging.2020.09.010] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2020] [Revised: 08/08/2020] [Accepted: 09/05/2020] [Indexed: 01/01/2023]
Abstract
We used graph theoretical measures to investigate the hypothesis that structural brain connectivity constrains the influence of functional connectivity on the relation between age and fluid cognition. Across 143 healthy, community-dwelling adults 19-79 years of age, we estimated structural network properties from diffusion-weighted imaging and functional network properties from resting-state functional magnetic resonance imaging. We confirmed previous reports of age-related decline in the strength and efficiency of structural networks, as well as in the connectivity strength within and between structural network modules. Functional networks, in contrast, exhibited age-related decline only in system segregation, a measure of the distinctiveness among network modules. Aging was associated with decline in a composite measure of fluid cognition, particularly tests of executive function. Functional system segregation was a significant mediator of age-related decline in executive function. Structural network properties did not directly influence the age-related decline in functional system segregation. The raw correlational data underlying the graph theoretical measures indicated that structural connectivity exerts a limited constraint on age-related decline in functional connectivity.
Collapse
Affiliation(s)
- David J Madden
- Brain Imaging and Analysis Center, Duke University Medical Center, Durham, NC, USA; Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC, USA; Center for Cognitive Neuroscience, Duke University, Durham, NC, USA.
| | - Shivangi Jain
- Brain Imaging and Analysis Center, Duke University Medical Center, Durham, NC, USA
| | - Zachary A Monge
- Brain Imaging and Analysis Center, Duke University Medical Center, Durham, NC, USA; Center for Cognitive Neuroscience, Duke University, Durham, NC, USA
| | - Angela D Cook
- Brain Imaging and Analysis Center, Duke University Medical Center, Durham, NC, USA
| | - Alexander Lee
- Brain Imaging and Analysis Center, Duke University Medical Center, Durham, NC, USA
| | - Hua Huang
- Brain Imaging and Analysis Center, Duke University Medical Center, Durham, NC, USA
| | - Cortney M Howard
- Brain Imaging and Analysis Center, Duke University Medical Center, Durham, NC, USA; Center for Cognitive Neuroscience, Duke University, Durham, NC, USA
| | - Jessica R Cohen
- Brain Imaging and Analysis Center, Duke University Medical Center, Durham, NC, USA; Department of Psychology and Neuroscience, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| |
Collapse
|
15
|
Pläschke RN, Patil KR, Cieslik EC, Nostro AD, Varikuti DP, Plachti A, Lösche P, Hoffstaedter F, Kalenscher T, Langner R, Eickhoff SB. Age differences in predicting working memory performance from network-based functional connectivity. Cortex 2020; 132:441-459. [PMID: 33065515 PMCID: PMC7778730 DOI: 10.1016/j.cortex.2020.08.012] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2019] [Revised: 06/27/2020] [Accepted: 08/23/2020] [Indexed: 01/14/2023]
Abstract
Deterioration in working memory capacity (WMC) has been associated with normal aging, but it remains unknown how age affects the relationship between WMC and connectivity within functional brain networks. We therefore examined the predictability of WMC from fMRI-based resting-state functional connectivity (RSFC) within eight meta-analytically defined functional brain networks and the connectome in young and old adults using relevance vector machine in a robust cross-validation scheme. Particular brain networks have been associated with mental functions linked to WMC to a varying degree and are associated with age-related differences in performance. Comparing prediction performance between the young and old sample revealed age-specific effects: In young adults, we found a general unpredictability of WMC from RSFC in networks subserving WM, cognitive action control, vigilant attention, theory-of-mind cognition, and semantic memory, whereas in older adults each network significantly predicted WMC. Moreover, both WM-related and WM-unrelated networks were differently predictive in older adults with low versus high WMC. These results indicate that the within-network functional coupling during task-free states is specifically related to individual task performance in advanced age, suggesting neural-level reorganization. In particular, our findings support the notion of a decreased segregation of functional brain networks, deterioration of network integrity within different networks and/or compensation by reorganization as factors driving associations between individual WMC and within-network RSFC in older adults. Thus, using multivariate pattern regression provided novel insights into age-related brain reorganization by linking cognitive capacity to brain network integrity.
Collapse
Affiliation(s)
- Rachel N Pläschke
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany.
| | - Kaustubh R Patil
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
| | - Edna C Cieslik
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
| | - Alessandra D Nostro
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
| | - Deepthi P Varikuti
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
| | - Anna Plachti
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
| | - Patrick Lösche
- Leibniz Institute for International Educational Research (DIPF), Centre for Research on Human Development and Education, Frankfurt am Main, Germany
| | - Felix Hoffstaedter
- Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
| | - Tobias Kalenscher
- Comparative Psychology, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Robert Langner
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
| | - Simon B Eickhoff
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany.
| |
Collapse
|
16
|
Zhang Y, Ren J, Qin Y, Yang C, Zhang T, Gong Q, Yang T, Zhou D. Altered topological organization of functional brain networks in drug-naive patients with paroxysmal kinesigenic dyskinesia. J Neurol Sci 2020; 411:116702. [DOI: 10.1016/j.jns.2020.116702] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2019] [Revised: 01/06/2020] [Accepted: 01/21/2020] [Indexed: 10/25/2022]
|
17
|
Weiss F, Zamoscik V, Schmidt SN, Halli P, Kirsch P, Gerchen MF. Just a very expensive breathing training? Risk of respiratory artefacts in functional connectivity-based real-time fMRI neurofeedback. Neuroimage 2020; 210:116580. [DOI: 10.1016/j.neuroimage.2020.116580] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2019] [Revised: 01/15/2020] [Accepted: 01/20/2020] [Indexed: 10/25/2022] Open
|
18
|
Disambiguating the role of blood flow and global signal with partial information decomposition. Neuroimage 2020; 213:116699. [PMID: 32179104 DOI: 10.1016/j.neuroimage.2020.116699] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2019] [Revised: 02/24/2020] [Accepted: 02/29/2020] [Indexed: 12/12/2022] Open
Abstract
Global signal (GS) is an ubiquitous construct in resting state functional magnetic resonance imaging (rs-fMRI), associated to nuisance, but containing by definition most of the neuronal signal. Global signal regression (GSR) effectively removes the impact of physiological noise and other artifacts, but at the same time it alters correlational patterns in unpredicted ways. Performing GSR taking into account the underlying physiology (mainly the blood arrival time) has been proven to be beneficial. From these observations we aimed to: 1) characterize the effect of GSR on network-level functional connectivity in a large dataset; 2) assess the complementary role of global signal and vessels; and 3) use the framework of partial information decomposition to further look into the joint dynamics of the global signal and vessels, and their respective influence on the dynamics of cortical areas. We observe that GSR affects intrinsic connectivity networks in the connectome in a non-uniform way. Furthermore, by estimating the predictive information of blood flow and the global signal using partial information decomposition, we observe that both signals are present in different amounts across intrinsic connectivity networks. Simulations showed that differences in blood arrival time can largely explain this phenomenon, while using hemodynamic and calcium mouse recordings we were able to confirm the presence of vascular effects, as calcium recordings lack hemodynamic information. With these results we confirm network-specific effects of GSR and the importance of taking blood flow into account for improving de-noising methods. Additionally, and beyond the mere issue of data denoising, we quantify the diverse and complementary effect of global and vessel BOLD signals on the dynamics of cortical areas.
Collapse
|
19
|
Zhang R, Kranz GS, Zou W, Deng Y, Huang X, Lin K, Lee TMC. Rumination network dysfunction in major depression: A brain connectome study. Prog Neuropsychopharmacol Biol Psychiatry 2020; 98:109819. [PMID: 31734293 DOI: 10.1016/j.pnpbp.2019.109819] [Citation(s) in RCA: 35] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/23/2019] [Revised: 11/12/2019] [Accepted: 11/12/2019] [Indexed: 11/19/2022]
Abstract
BACKGROUND Rumination is a central feature of major depressive disorder (MDD). Knowledge of the neural structures that underpin rumination offers significant insight into depressive pathophysiology and may help to develop potential intervention strategies for MDD, a mental illness that has become the leading cause of disability worldwide. METHODS Using resting-state fMRI and graph theory, this study adopted a connectome approach to examine the functional topological organization of the neural network associated with rumination in MDD. Data from 96 participants were analyzed, including 51 patients with MDD and 45 healthy controls. RESULTS We found altered functional integration and segregation of neural networks associated with depressive rumination as indicated by reduced global and local efficiency in MDD patients compared with controls. Interestingly, these metrics correlated positively with depression severity, as measured by the Hamilton Depression Rating Scale. Moreover, mediation analysis indicated that the association between network metrics and depression severity was mediated by the ruminative tendency of patients. Disrupted nodal centralities were located in regions associated with emotional processing, visual mental imagery, and attentional control. CONCLUSION Our results highlight rumination as a two-edged sword that reflects a disease-specific neuropathology but also points to a functionality of depressive symptoms with evolutionary meaning.
Collapse
Affiliation(s)
- Ruibin Zhang
- The State Key Laboratory of Brain and Cognitive Science, The University of Hong Kong, Hong Kong, China; Laboratory of Social Cognitive and Affective Neuroscience, The University of Hong Kong, Hong Kong, China; Department of Psychology, School of Public Health, Southern Medical University (Guangdong Provincial Key Laboratory of Tropical Disease Research), China; Department of Psychiatry, Zhujiang Hospital, Southern Medical University, Guangzhou 510282, China
| | - Georg S Kranz
- The State Key Laboratory of Brain and Cognitive Science, The University of Hong Kong, Hong Kong, China; Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong, China; Department of Psychiatry and Psychotherapy, Medical University of Vienna, Austria
| | - Wenjin Zou
- Department of Radiology, The Affiliated Hospital of Guangzhou Medical University (Guangzhou Huiai Hospital), China
| | - Yue Deng
- Department of Psychiatry, The Second Affiliated Hospital of Guangzhou Medical University, China
| | - Xuejun Huang
- Department of Psychiatry, The Second Affiliated Hospital of Guangzhou Medical University, China
| | - Kangguang Lin
- Department of Affective Disorders, The Affiliated Hospital of Guangzhou Medical University (Guangzhou Huiai Hospital), China; Laboratory of Emotion and Cognition, The Affiliated Hospital of Guangzhou Medical University, China.
| | - Tatia M C Lee
- Laboratory of Emotion and Cognition, The Affiliated Hospital of Guangzhou Medical University, China; The State Key Laboratory of Brain and Cognitive Science, The University of Hong Kong, Hong Kong, China; Laboratory of Social Cognitive and Affective Neuroscience, The University of Hong Kong, Hong Kong, China; Center for Brain Science and Brain-Inspired Intelligence, Guangdong-Hong Kong-Macao Greater Bay Area, China.
| |
Collapse
|
20
|
Orban C, Kong R, Li J, Chee MWL, Yeo BTT. Time of day is associated with paradoxical reductions in global signal fluctuation and functional connectivity. PLoS Biol 2020; 18:e3000602. [PMID: 32069275 PMCID: PMC7028250 DOI: 10.1371/journal.pbio.3000602] [Citation(s) in RCA: 64] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2019] [Accepted: 01/15/2020] [Indexed: 12/13/2022] Open
Abstract
The brain exhibits substantial diurnal variation in physiology and function, but neuroscience studies rarely report or consider the effects of time of day. Here, we examined variation in resting-state functional MRI (fMRI) in around 900 individuals scanned between 8 AM and 10 PM on two different days. Multiple studies across animals and humans have demonstrated that the brain’s global signal (GS) amplitude (henceforth referred to as “fluctuation”) increases with decreased arousal. Thus, in accord with known circadian variation in arousal, we hypothesised that GS fluctuation would be lowest in the morning, increase in the midafternoon, and dip in the early evening. Instead, we observed a cumulative decrease in GS fluctuation as the day progressed. Although respiratory variation also decreased with time of day, control analyses suggested that this did not account for the reduction in GS fluctuation. Finally, time of day was associated with marked decreases in resting-state functional connectivity across the whole brain. The magnitude of decrease was significantly stronger than associations between functional connectivity and behaviour (e.g., fluid intelligence). These findings reveal time of day effects on global brain activity that are not easily explained by expected arousal state or physiological artefacts. We conclude by discussing potential mechanisms for the observed diurnal variation in resting brain activity and the importance of accounting for time of day in future studies. The brain exhibits substantial diurnal variation in physiology and function. A large-scale fMRI study reveals that the brain’s global signal amplitude, typically elevated during drowsy states, unexpectedly reduces steadily as the day progresses.
Collapse
Affiliation(s)
- Csaba Orban
- Department of Electrical and Computer Engineering, N.1 Institute for Health and Memory Networks Program, National University of Singapore, Singapore
- Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Clinical Imaging and Research Centre, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Neuropsychopharmacology Unit, Centre for Psychiatry, Imperial College London, London, United Kingdom
- * E-mail: (CO); (BTTY)
| | - Ru Kong
- Department of Electrical and Computer Engineering, N.1 Institute for Health and Memory Networks Program, National University of Singapore, Singapore
- Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Clinical Imaging and Research Centre, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Jingwei Li
- Department of Electrical and Computer Engineering, N.1 Institute for Health and Memory Networks Program, National University of Singapore, Singapore
- Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Clinical Imaging and Research Centre, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Michael W. L. Chee
- Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Clinical Imaging and Research Centre, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Centre for Cognitive Neuroscience, Duke-NUS Medical School, Singapore
- NUS Graduate School for Integrative Sciences and Engineering, National University of Singapore, Singapore
| | - B. T. Thomas Yeo
- Department of Electrical and Computer Engineering, N.1 Institute for Health and Memory Networks Program, National University of Singapore, Singapore
- Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Clinical Imaging and Research Centre, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Centre for Cognitive Neuroscience, Duke-NUS Medical School, Singapore
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, United States of America
- NUS Graduate School for Integrative Sciences and Engineering, National University of Singapore, Singapore
- * E-mail: (CO); (BTTY)
| |
Collapse
|
21
|
Kelly RE, Hoptman MJ, Alexopoulos GS, Gunning FM, McKeown MJ. Omission of temporal nuisance regressors from dual regression can improve accuracy of fMRI functional connectivity maps. Hum Brain Mapp 2019; 40:4005-4025. [PMID: 31187917 PMCID: PMC6865788 DOI: 10.1002/hbm.24692] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2018] [Revised: 05/26/2019] [Accepted: 05/29/2019] [Indexed: 01/08/2023] Open
Abstract
Functional connectivity (FC) maps from brain fMRI data can be derived with dual regression, a proposed alternative to traditional seed-based FC (SFC) methods that detect temporal correlation between a predefined region (seed) and other regions in the brain. As with SFC, incorporating nuisance regressors (NR) into the dual regression must be done carefully, to prevent potential bias and insensitivity of FC estimates. Here, we explore the potentially untoward effects on dual regression that may occur when NR correlate highly with the signal of interest, using both synthetic and real fMRI data to elucidate mechanisms responsible for loss of accuracy in FC maps. Our tests suggest significantly improved accuracy in FC maps derived with dual regression when highly correlated temporal NR were omitted. Single-map dual regression, a simplified form of dual regression that uses neither spatial nor temporal NR, offers a viable alternative whose FC maps may be more easily interpreted, and in some cases be more accurate than those derived with standard dual regression.
Collapse
Affiliation(s)
- Robert E. Kelly
- Department of PsychiatryWeill Cornell Medical CollegeWhite PlainsNew York
| | - Matthew J. Hoptman
- Schizophrenia Research DivisionNathan S. Kline Institute for Psychiatric ResearchOrangeburgNew York
- Department of PsychiatryNew York University School of MedicineNew YorkNew York
| | | | - Faith M. Gunning
- Department of PsychiatryWeill Cornell Medical CollegeWhite PlainsNew York
| | - Martin J. McKeown
- Neurology, Pacific Parkinson's Research CenterUniversity of British ColumbiaVancouverBritish ColumbiaCanada
| |
Collapse
|
22
|
Maknojia S, Churchill NW, Schweizer TA, Graham SJ. Resting State fMRI: Going Through the Motions. Front Neurosci 2019; 13:825. [PMID: 31456656 PMCID: PMC6700228 DOI: 10.3389/fnins.2019.00825] [Citation(s) in RCA: 40] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2019] [Accepted: 07/23/2019] [Indexed: 11/19/2022] Open
Abstract
Resting state functional magnetic resonance imaging (rs-fMRI) has become an indispensable tool in neuroscience research. Despite this, rs-fMRI signals are easily contaminated by artifacts arising from movement of the head during data collection. The artifacts can be problematic even for motions on the millimeter scale, with complex spatiotemporal properties that can lead to substantial errors in functional connectivity estimates. Effective correction methods must be employed, therefore, to distinguish true functional networks from motion-related noise. Research over the last three decades has produced numerous correction methods, many of which must be applied in combination to achieve satisfactory data quality. Subject instruction, training, and mild restraints are helpful at the outset, but usually insufficient. Improvements come from applying multiple motion correction algorithms retrospectively after rs-fMRI data are collected, although residual artifacts can still remain in cases of elevated motion, which are especially prevalent in patient populations. Although not commonly adopted at present, “real-time” correction methods are emerging that can be combined with retrospective methods and that promise better correction and increased rs-fMRI signal sensitivity. While the search for the ideal motion correction protocol continues, rs-fMRI research will benefit from good disclosure practices, such as: (1) reporting motion-related quality control metrics to provide better comparison between studies; and (2) including motion covariates in group-level analyses to limit the extent of motion-related confounds when studying group differences.
Collapse
Affiliation(s)
- Sanam Maknojia
- Physical Sciences Platform, Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
| | - Nathan W Churchill
- Keenan Research Centre for Biomedical Science, St. Michael's Hospital, Toronto, ON, Canada
| | - Tom A Schweizer
- Keenan Research Centre for Biomedical Science, St. Michael's Hospital, Toronto, ON, Canada.,Division of Neurosurgery, Faculty of Medicine, University of Toronto, Toronto, ON, Canada.,Institute of Biomaterials and Biomedical Engineering, Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - S J Graham
- Physical Sciences Platform, Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, ON, Canada.,Department of Medical Biophysics, Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| |
Collapse
|
23
|
Yu Y, Yan LF, Sun Q, Hu B, Zhang J, Yang Y, Dai YJ, Cui WX, Xiu SJ, Hu YC, Heng CN, Liu QQ, Hou JF, Pan YY, Zhai LH, Han TH, Cui GB, Wang W. Neurovascular decoupling in type 2 diabetes mellitus without mild cognitive impairment: Potential biomarker for early cognitive impairment. Neuroimage 2019; 200:644-658. [PMID: 31252056 DOI: 10.1016/j.neuroimage.2019.06.058] [Citation(s) in RCA: 36] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2019] [Revised: 06/22/2019] [Accepted: 06/24/2019] [Indexed: 12/15/2022] Open
Abstract
Type 2 diabetes mellitus (T2DM) is a significant risk factor for mild cognitive impairment (MCI) and the acceleration of MCI to dementia. The high glucose level induce disturbance of neurovascular (NV) coupling is suggested to be one potential mechanism, however, the neuroimaging evidence is still lacking. To assess the NV decoupling pattern in early diabetic status, 33 T2DM without MCI patients and 33 healthy control subjects were prospectively enrolled. Then, they underwent resting state functional MRI and arterial spin labeling imaging to explore the hub-based networks and to estimate the coupling of voxel-wise cerebral blood flow (CBF)-degree centrality (DC), CBF-mean amplitude of low-frequency fluctuation (mALFF) and CBF- mean regional homogeneity (mReHo). We further evaluated the relationship between NV coupling pattern and cognitive performance (false discovery rate corrected). T2DM without MCI patients displayed significant decrease in the absolute CBF-mALFF, CBF-mReHo coupling of CBFnetwork and in the CBF-DC coupling of DCnetwork. Besides, networks which involved CBF and DC hubs mainly located in the default mode network (DMN). Furthermore, less severe disease and better cognitive performance in T2DM patients were significantly correlated with higher coupling of CBF-DC, CBF-mALFF or CBF-mReHo, especially for the cognitive dimensions of general function and executive function. Thus, coupling of CBF-DC, CBF-mALFF and CBF-mReHo may serve as promising indicators to reflect NV coupling state and to explain the T2DM related early cognitive impairment.
Collapse
Affiliation(s)
- Ying Yu
- Department of Radiology & Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University (Air Force Medical University), 569 Xinsi Road, Xi'an, 710038, Shaanxi, China.
| | - Lin-Feng Yan
- Department of Radiology & Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University (Air Force Medical University), 569 Xinsi Road, Xi'an, 710038, Shaanxi, China.
| | - Qian Sun
- Department of Radiology & Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University (Air Force Medical University), 569 Xinsi Road, Xi'an, 710038, Shaanxi, China.
| | - Bo Hu
- Department of Radiology & Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University (Air Force Medical University), 569 Xinsi Road, Xi'an, 710038, Shaanxi, China.
| | - Jin Zhang
- Department of Radiology & Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University (Air Force Medical University), 569 Xinsi Road, Xi'an, 710038, Shaanxi, China.
| | - Yang Yang
- Department of Radiology & Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University (Air Force Medical University), 569 Xinsi Road, Xi'an, 710038, Shaanxi, China.
| | - Yu-Jie Dai
- Department of Clinical Nutrition, Xijing Hospital, Fourth Military Medical University (Air Force Medical University), 15 West Changle Road, Xi'an, 710032, Shaanxi, China.
| | - Wu-Xun Cui
- Department of Radiology & Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University (Air Force Medical University), 569 Xinsi Road, Xi'an, 710038, Shaanxi, China.
| | - Si-Jie Xiu
- Department of Radiology & Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University (Air Force Medical University), 569 Xinsi Road, Xi'an, 710038, Shaanxi, China.
| | - Yu-Chuan Hu
- Department of Radiology & Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University (Air Force Medical University), 569 Xinsi Road, Xi'an, 710038, Shaanxi, China.
| | - Chun-Ni Heng
- Department of Endocrinology, Tangdu Hospital, Fourth Military Medical University (Air Force Medical University), 569 Xinsi Road, Xi'an, 710038, Shaanxi, China.
| | - Qing-Quan Liu
- Department of Endocrinology, Tangdu Hospital, Fourth Military Medical University (Air Force Medical University), 569 Xinsi Road, Xi'an, 710038, Shaanxi, China.
| | - Jun-Feng Hou
- Department of Endocrinology, Tangdu Hospital, Fourth Military Medical University (Air Force Medical University), 569 Xinsi Road, Xi'an, 710038, Shaanxi, China.
| | - Yu-Yun Pan
- Student Brigade, Fourth Military Medical University (Air Force Medical University), 169 Changle Road, Xi'an, 710032, Shaanxi, China.
| | - Liang-Hao Zhai
- Student Brigade, Fourth Military Medical University (Air Force Medical University), 169 Changle Road, Xi'an, 710032, Shaanxi, China.
| | - Teng-Hui Han
- Student Brigade, Fourth Military Medical University (Air Force Medical University), 169 Changle Road, Xi'an, 710032, Shaanxi, China.
| | - Guang-Bin Cui
- Department of Radiology & Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University (Air Force Medical University), 569 Xinsi Road, Xi'an, 710038, Shaanxi, China.
| | - Wen Wang
- Department of Radiology & Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University (Air Force Medical University), 569 Xinsi Road, Xi'an, 710038, Shaanxi, China.
| |
Collapse
|
24
|
Shu H, Shi Y, Chen G, Wang Z, Liu D, Yue C, Ward BD, Li W, Xu Z, Chen G, Guo QH, Xu J, Li SJ, Zhang Z. Distinct neural correlates of episodic memory among apolipoprotein E alleles in cognitively normal elderly. Brain Imaging Behav 2019; 13:255-269. [PMID: 29396739 DOI: 10.1007/s11682-017-9818-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
The apolipoprotein E (APOE) ε4 and ε2 alleles are acknowledged genetic factors modulating Alzheimer's disease (AD) risk and episodic memory (EM) deterioration in an opposite manner. Mounting neuroimaging studies describe EM-related brain activity differences among APOE alleles but remain limited in elucidating the underlying mechanism. Here, we hypothesized that the APOE ε2, ε3, and ε4 alleles have distinct EM neural substrates, as a manifestation of degeneracy, underlying their modulations on EM-related brain activity and AD susceptibility. To test the hypothesis, we identified neural correlates of EM function by correlating intrinsic hippocampal functional connectivity networks with neuropsychological EM performances in a voxelwise manner, with 129 cognitively normal elderly subjects (36 ε2 carriers, 44 ε3 homozygotes, and 49 ε4 carriers). We demonstrated significantly different EM neural correlates among the three APOE allele groups. Specifically, in the ε3 homozygotes, positive EM neural correlates were characterized in the Papez circuit regions; in the ε4 carriers, positive EM neural correlates involved the lateral temporal cortex, premotor cortex/sensorimotor cortex/superior parietal lobule, and cuneus; and in the ε2 carriers, negative EM neural correlates appeared in the bilateral frontopolar, posteromedial, and sensorimotor cortex. Further, in the ε4 carriers, the interaction between age and EM function occurred in the temporoparietal junction and prefrontal cortex. Our findings suggest that the underlying mechanism of APOE polymorphism modulations on EM function and AD susceptibility is genetically related to the neural degeneracy of EM function across APOE alleles.
Collapse
Affiliation(s)
- Hao Shu
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, 87 Dingjiaqiao Road, Nanjing, Jiangsu, 210009, China
- Department of Biophysics, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI, 53226, USA
| | - Yongmei Shi
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, 87 Dingjiaqiao Road, Nanjing, Jiangsu, 210009, China
| | - Gang Chen
- Department of Biophysics, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI, 53226, USA
| | - Zan Wang
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, 87 Dingjiaqiao Road, Nanjing, Jiangsu, 210009, China
| | - Duan Liu
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, 87 Dingjiaqiao Road, Nanjing, Jiangsu, 210009, China
| | - Chunxian Yue
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, 87 Dingjiaqiao Road, Nanjing, Jiangsu, 210009, China
| | - B Douglas Ward
- Department of Biophysics, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI, 53226, USA
| | - Wenjun Li
- Department of Biophysics, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI, 53226, USA
| | - Zhan Xu
- Department of Biophysics, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI, 53226, USA
| | - Guangyu Chen
- Department of Biophysics, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI, 53226, USA
| | - Qi-Hao Guo
- Department of Neurology, Huashan Hospital, Fudan University, Shanghai, 200040, China
| | - Jun Xu
- Department of Neurology, Jiangsu Province Geriatric Institute, Nanjing, Jiangsu, 210024, China
| | - Shi-Jiang Li
- Department of Biophysics, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI, 53226, USA.
| | - Zhijun Zhang
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, 87 Dingjiaqiao Road, Nanjing, Jiangsu, 210009, China.
| |
Collapse
|
25
|
O'Connor E, Zeffiro T. Is treated HIV infection still toxic to the brain? PROGRESS IN MOLECULAR BIOLOGY AND TRANSLATIONAL SCIENCE 2019; 165:259-284. [PMID: 31481166 DOI: 10.1016/bs.pmbts.2019.04.001] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Clinically apparent HIV infection, accompanied by CNS opportunistic infections and HIV encephalopathy, was often associated with profound structural and functional brain effects prior to the introduction of anti-retroviral therapy (ART). With treatment, HIV structural and functional brain effects are smaller and have not been as easily detected. With near complete elimination of CNS opportunistic infections, the HIV neuroimaging research community now grapples with the problem of detecting subtler structural and functional changes against a background of persisting confounds, such as comorbidities and clinical features common in the HIV infected population. This situation also raises the question of whether imaging measure changes that are reported as HIV brain effects are purely related to viral infection, rather than originating from confounding effects that might include age, substance use, hepatitis C coinfection, cerebrovascular risk factors, ART, premorbid cognitive skills and illness duration. In addition to cohort characteristics, variation in image acquisition and analysis techniques may also contribute to study outcome heterogeneity. We review the potential effects of these confounds on detection of HIV infection effects and discuss strategies to avoid or mitigate the effects of these confounds. We then present a systematic approach to measurement, design and analysis in HIV neuroimaging studies, combining both experimental and statistical control techniques to determine if HIV infection effects persist, fluctuate or worsen in groups achieving viral suppression from ART.
Collapse
Affiliation(s)
- Erin O'Connor
- University of Maryland School of Medicine, Baltimore, MD, United States.
| | - Thomas Zeffiro
- University of Maryland School of Medicine, Baltimore, MD, United States.
| |
Collapse
|
26
|
van Duijvenvoorde ACK, Westhoff B, de Vos F, Wierenga LM, Crone EA. A three-wave longitudinal study of subcortical-cortical resting-state connectivity in adolescence: Testing age- and puberty-related changes. Hum Brain Mapp 2019; 40:3769-3783. [PMID: 31099959 PMCID: PMC6767490 DOI: 10.1002/hbm.24630] [Citation(s) in RCA: 41] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2018] [Revised: 04/22/2019] [Accepted: 05/02/2019] [Indexed: 12/20/2022] Open
Abstract
Adolescence is the transitional period between childhood and adulthood, characterized by substantial changes in reward‐driven behavior. Although reward‐driven behavior is supported by subcortical‐medial prefrontal cortex (PFC) connectivity, the development of these circuits is not well understood. Particularly, while puberty has been hypothesized to accelerate organization and activation of functional neural circuits, the relationship between age, sex, pubertal change, and functional connectivity has hardly been studied. Here, we present an analysis of resting‐state functional connectivity between subcortical structures and the medial PFC, in 661 scans of 273 participants between 8 and 29 years, using a three‐wave longitudinal design. Generalized additive mixed model procedures were used to assess the effects of age, sex, and self‐reported pubertal status on connectivity between subcortical structures (nucleus accumbens, caudate, putamen, hippocampus, and amygdala) and cortical medial structures (dorsal anterior cingulate, ventral anterior cingulate, subcallosal cortex, frontal medial cortex). We observed an age‐related strengthening of subcortico‐subcortical and cortico‐cortical connectivity. Subcortical–cortical connectivity, such as, between the nucleus accumbens—frontal medial cortex, and the caudate—dorsal anterior cingulate cortex, however, weakened across age. Model‐based comparisons revealed that for specific connections pubertal development described developmental change better than chronological age. This was particularly the case for changes in subcortical–cortical connectivity and distinctively for boys and girls. Together, these findings indicate changes in functional network strengthening with pubertal development. These changes in functional connectivity may maximize the neural efficiency of interregional communication and set the stage for further inquiry of biological factors driving adolescent functional connectivity changes.
Collapse
Affiliation(s)
- Anna C K van Duijvenvoorde
- Institute of Psychology, Leiden University, Leiden, The Netherlands.,Leiden Institute for Brain and Cognition, Leiden University, Leiden, The Netherlands
| | - Bianca Westhoff
- Institute of Psychology, Leiden University, Leiden, The Netherlands.,Leiden Institute for Brain and Cognition, Leiden University, Leiden, The Netherlands
| | - Frank de Vos
- Institute of Psychology, Leiden University, Leiden, The Netherlands.,Leiden Institute for Brain and Cognition, Leiden University, Leiden, The Netherlands
| | - Lara M Wierenga
- Institute of Psychology, Leiden University, Leiden, The Netherlands.,Leiden Institute for Brain and Cognition, Leiden University, Leiden, The Netherlands
| | - Eveline A Crone
- Institute of Psychology, Leiden University, Leiden, The Netherlands.,Leiden Institute for Brain and Cognition, Leiden University, Leiden, The Netherlands
| |
Collapse
|
27
|
O'Connor EE, Zeffiro TA. Why is Clinical fMRI in a Resting State? Front Neurol 2019; 10:420. [PMID: 31068901 PMCID: PMC6491723 DOI: 10.3389/fneur.2019.00420] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2019] [Accepted: 04/05/2019] [Indexed: 12/28/2022] Open
Abstract
While resting state fMRI (rs-fMRI) has gained widespread application in neuroimaging clinical research, its penetration into clinical medicine has been more limited. We surveyed a neuroradiology professional group to ascertain their experience with rs-fMRI, identify perceived barriers to using rs-fMRI clinically and elicit suggestions about ways to facilitate its use in clinical practice. The electronic survey also collected information about demographics and work environment using Likert scales. We found that 90% of the respondents had adequate equipment to conduct rs-fMRI and 82% found rs-fMRI data easy to collect. Fifty-nine percent have used rs-fMRI in their past research and 72% reported plans to use rs-fMRI for research in the next year. Nevertheless, only 40% plan to use rs-fMRI in clinical practice in the next year and 82% agreed that their clinical fMRI use is largely confined to pre-surgical planning applications. To explore the reasons for the persistent low utilization of rs-fMRI in clinical applications, we identified barriers to clinical rs-fMRI use related to the availability of robust denoising procedures, single-subject analysis techniques, demonstration of functional connectivity map reliability, regulatory clearance, reimbursement, and neuroradiologist training opportunities. In conclusion, while rs-fMRI use in clinical neuroradiology practice is limited, enthusiasm appears to be quite high and there are several possible avenues in which further research and development may facilitate its penetration into clinical practice.
Collapse
Affiliation(s)
- Erin E O'Connor
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland Medical Center, Baltimore, MD, United States
| | - Thomas A Zeffiro
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland Medical Center, Baltimore, MD, United States
| |
Collapse
|
28
|
Li X, Wang A, Xu J, Sun Z, Xia J, Wang P, Wang B, Zhang M, Tian J. Reduced Dynamic Interactions Within Intrinsic Functional Brain Networks in Early Blind Patients. Front Neurosci 2019; 13:268. [PMID: 30983956 PMCID: PMC6448007 DOI: 10.3389/fnins.2019.00268] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2018] [Accepted: 03/07/2019] [Indexed: 11/16/2022] Open
Abstract
Neuroimaging studies in early blind (EB) patients have shown altered connections or brain networks. However, it remains unclear how the causal relationships are disrupted within intrinsic brain networks. In our study, we used spectral dynamic causal modeling (DCM) to estimate the causal interactions using resting-state data in a group of 20 EB patients and 20 healthy controls (HC). Coupling parameters in specific regions were estimated, including the medial prefrontal cortex (mPFC), posterior cingulate cortex (PCC), and inferior parietal lobule (IPC) in the default mode network (DMN); dorsal anterior cingulate cortex (dACC) and bilateral anterior insulae (AI) in the salience network (SN), and bilateral frontal eye fields (FEF) and superior parietal lobes (SPL) within the dorsal attention network (DAN). Statistical analyses found that all endogenous connections and the connections from the mPFC to bilateral IPCs in EB patients were significantly reduced within the DMN, and the effective connectivity from the PCC and lIPC to the mPFC, and from the mPFC to the PCC were enhanced. For the SN, all significant connections in EB patients were significantly decreased, except the intrinsic right AI connections. Within the DAN, more significant effective connections were observed to be reduced between the EB and HC groups, while only the connections from the right SPL to the left SPL and the intrinsic connection in the left SPL were significantly enhanced. Furthermore, discovery of more decreased effective connections in the EB subjects suggested that the disrupted causal interactions between specific regions are responsive to the compensatory brain plasticity in early deprivation.
Collapse
Affiliation(s)
- Xianglin Li
- Department of Medical Imaging, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.,Medical Imaging Research Institute, Binzhou Medical University, Yantai, China
| | - Ailing Wang
- Department of Clinical Laboratory, Yantai Affiliated Hospital of Binzhou Medical University, Yantai, China
| | - Junhai Xu
- Tianjin Key Laboratory of Cognitive Computing and Application, School of Artificial Intelligence, College of Intelligence and Computing, Tianjin University, Tianjin, China
| | - Zhenbo Sun
- Medical Imaging Research Institute, Binzhou Medical University, Yantai, China
| | - Jikai Xia
- Department of Radiology, Yantai Affiliated Hospital of Binzhou Medical University, Yantai, China
| | - Peiyuan Wang
- Department of Radiology, Yantai Affiliated Hospital of Binzhou Medical University, Yantai, China
| | - Bin Wang
- Medical Imaging Research Institute, Binzhou Medical University, Yantai, China
| | - Ming Zhang
- Department of Medical Imaging, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Jie Tian
- Department of Medical Imaging, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.,School of Life Sciences and Technology, Xidian University, Xi'an, China
| |
Collapse
|
29
|
Pan WJ, Billings J, Nezafati M, Abbas A, Keilholz S. Resting State fMRI in Rodents. ACTA ACUST UNITED AC 2019; 83:e45. [PMID: 30040200 DOI: 10.1002/cpns.45] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Resting state functional MRI (fMRI) and functional connectivity are widely applied in humans to examine the role of brain networks in normal function and dysfunction. A similar approach can be taken in rodents, either to obtain translational measures in models of brain disorders or to more carefully examine the neurophysiological underpinnings of the networks. A protocol for resting state functional connectivity in the anesthetized rat, from animal setup to data acquisition to possible pipelines for data analysis, is described. © 2018 by John Wiley & Sons, Inc.
Collapse
Affiliation(s)
- Wen-Ju Pan
- Biomedical Engineering, Emory University/Georgia Institute of Technology, Atlanta, Georgia
| | - Jacob Billings
- Neuroscience Program, Emory University, Atlanta, Georgia
| | - Maysam Nezafati
- Biomedical Engineering, Emory University/Georgia Institute of Technology, Atlanta, Georgia
| | - Anzar Abbas
- Neuroscience Program, Emory University, Atlanta, Georgia
| | - Shella Keilholz
- Biomedical Engineering, Emory University/Georgia Institute of Technology, Atlanta, Georgia
| |
Collapse
|
30
|
Yang Y, Liu S, Jiang X, Yu H, Ding S, Lu Y, Li W, Zhang H, Liu B, Cui Y, Fan L, Jiang T, Lv L. Common and Specific Functional Activity Features in Schizophrenia, Major Depressive Disorder, and Bipolar Disorder. Front Psychiatry 2019; 10:52. [PMID: 30837901 PMCID: PMC6389674 DOI: 10.3389/fpsyt.2019.00052] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/02/2018] [Accepted: 01/24/2019] [Indexed: 12/12/2022] Open
Abstract
Objectives: Schizophrenia (SZ), major depressive disorder (MDD), and bipolar disorder (BD) are serious mental disorders with distinct diagnostic criteria. They share common clinical and biological features. However, there are still only few studies on the common and specific brain imaging changes associated with the three mental disorders. Therefore, the aim of this study was to identify the common and specific functional activity and connectivity changes in SZ, MDD, and BD. Methods: A total of 271 individuals underwent functional magnetic resonance imaging: SZ (n = 64), MDD (n = 73), BD (n = 41), and healthy controls (n = 93). The symptoms of SZ patients were evaluated by the Positive and Negative Syndrome Scale. The Beck Depression Inventory (BDI), and Beck Anxiety Inventory (BAI) were used to evaluate the symptoms of MDD patients. The BDI, BAI, and Young Mania Rating Scale were used to evaluate the symptoms of MDD and BD patients. In addition, we compared the fALFF and functional connectivity between the three mental disorders and healthy controls using two sample t-tests. Results: Significantly decreased functional activity was found in the right superior frontal gyrus, middle cingulate gyrus, left middle frontal gyrus, and decreased functional connectivity (FC) of the insula was found in SZ, MDD, and BD. Specific fALFF changes, mainly in the ventral lateral pre-frontal cortex, striatum, and thalamus were found for SZ, in the left motor cortex and parietal lobe for MDD, and the dorsal lateral pre-frontal cortex, orbitofrontal cortex, and posterior cingulate cortex in BD. Conclusion: Our findings of common abnormalities in SZ, MDD, and BD provide evidence that salience network abnormality may play a critical role in the pathogenesis of these three mental disorders. Meanwhile, our findings also indicate that specific alterations in SZ, MDD, and BD provide neuroimaging evidence for the differential diagnosis of the three mental disorders.
Collapse
Affiliation(s)
- Yongfeng Yang
- Key Laboratory for Neuroinformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China.,Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China.,Henan Key Laboratory of Biological Psychiatry, Xinxiang Medical University, Xinxiang, China
| | - Shu Liu
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, China.,National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Xiaoyan Jiang
- Key Laboratory for Neuroinformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Hongyan Yu
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China
| | - Shuang Ding
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China.,Henan Key Laboratory of Biological Psychiatry, Xinxiang Medical University, Xinxiang, China
| | - Yanli Lu
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China.,Henan Key Laboratory of Biological Psychiatry, Xinxiang Medical University, Xinxiang, China
| | - Wenqiang Li
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China.,Henan Key Laboratory of Biological Psychiatry, Xinxiang Medical University, Xinxiang, China
| | - Hongxing Zhang
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China.,Henan Key Laboratory of Biological Psychiatry, Xinxiang Medical University, Xinxiang, China
| | - Bing Liu
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, China.,National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China.,University of Chinese Academy of Sciences, Beijing, China
| | - Yue Cui
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, China.,National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China.,University of Chinese Academy of Sciences, Beijing, China
| | - Lingzhong Fan
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, China.,National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China.,University of Chinese Academy of Sciences, Beijing, China
| | - Tianzi Jiang
- Key Laboratory for Neuroinformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China.,Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, China.,National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China.,University of Chinese Academy of Sciences, Beijing, China.,The Queensland Brain Institute, University of Queensland, Brisbane, QLD, Australia
| | - Luxian Lv
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China.,Henan Key Laboratory of Biological Psychiatry, Xinxiang Medical University, Xinxiang, China
| |
Collapse
|
31
|
Zhu J, Cai H, Yuan Y, Yue Y, Jiang D, Chen C, Zhang W, Zhuo C, Yu Y. Variance of the global signal as a pretreatment predictor of antidepressant treatment response in drug-naïve major depressive disorder. Brain Imaging Behav 2018; 12:1768-1774. [PMID: 29473140 PMCID: PMC6302054 DOI: 10.1007/s11682-018-9845-9] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
Several behavioral and neuroimaging markers could be used to predict eventual antidepressant medication (ADM) outcomes in patients with major depressive disorder (MDD). However, these predictors are either subjective or complex, which has limited their clinical use. Thus, we aimed to identify an objective and easy-to-get marker to predict early therapeutic efficacy. Forty-seven drug-naïve patients with MDD and 47 age-, gender- and education-matched healthy controls underwent resting-state functional magnetic resonance imaging (fMRI) scans. We calculated the variable coefficient (VC) of the global signal for each subject. Baseline Hamilton Rating Scale for Depression (HRSD) score and that after 2 weeks of ADM were assessed for patients. Although there was no difference in VC between patients with MDD and healthy controls, we found a significant positive correlation between the VC and the decline rate of HRSD scores in the patients. Compared with the non-responding depression (NRD) group, the treatment-responsive depression (TRD) group had a higher VC. Receiver operator characteristic curve analysis revealed that the VC exhibited a good ability to differentiate TRD from NRD. In addition, the linear and logistic regression analyses showed that the VC was a significant predictor of the decline rate of HRSD scores and the antidepressant treatment response. These findings suggest that variance of the global signal may serve as a useful marker to help clinicians find an appropriate drug for individuals with MDD at the earliest opportunity and then further to facilitate personalized therapy.
Collapse
Affiliation(s)
- Jiajia Zhu
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Huanhuan Cai
- Medical Imaging Center, The First Affiliated Hospital of Anhui University of Chinese Medicine, Hefei, China
| | - Yonggui Yuan
- Department of Psychosomatics & Psychiatry, Institute of Psychosomatics, Zhongda Hospital, Medical School of Southeast University, Nanjing, China
| | - Yingying Yue
- Department of Psychosomatics & Psychiatry, Institute of Psychosomatics, Zhongda Hospital, Medical School of Southeast University, Nanjing, China
| | - Deguo Jiang
- Department of Psychiatry, Wenzhou Seventh People's Hospital, Wenzhou, China
| | - Ce Chen
- Department of Psychiatry, Wenzhou Seventh People's Hospital, Wenzhou, China
| | - Wei Zhang
- Department of Psychiatry, Wenzhou Seventh People's Hospital, Wenzhou, China
| | - Chuanjun Zhuo
- Department of Psychiatry, Wenzhou Seventh People's Hospital, Wenzhou, China.
- Department of Psychiatry, Tianjin Mental Health Center, Tianjin, China.
| | - Yongqiang Yu
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, China.
| |
Collapse
|
32
|
Xie C, Ma L, Jiang N, Huang R, Li L, Gong L, He C, Xiao C, Liu W, Xu S, Zhang Z. Imbalanced functional link between reward circuits and the cognitive control system in patients with obsessive-compulsive disorder. Brain Imaging Behav 2018; 11:1099-1109. [PMID: 27553440 DOI: 10.1007/s11682-016-9585-7] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
Altered reward processing and cognitive deficits are often observed in patients with obsessive-compulsive disorder (OCD); however, whether the imbalance in activity between reward circuits and the cognitive control (CC) system is associated with compulsive behavior remains unknown. Sixty-eight OCD patients and 33 cognitively normal (CN) healthy subjects participated in this resting-state functional magnetic resonance imaging study. Alterations in the functional connectivity between reward circuits and the CC system were quantitatively assessed and compared between the groups. A Granger causality analysis was used to determine the causal informational influence between and within reward circuits and the CC system across all subjects. OCD patients showed a dichotomous pattern of enhanced functional coupling in their reward circuits and a weakened functional coupling in their CC system when compared to CN subjects. Neural correlates of compulsive behavior were primarily located in the reward circuits and CC system in OCD patients. Importantly, the CC system exerted a reduced interregional causal influence over the reward system in OCD patients relative to its effect in CN subjects. The limitations of this study are that it was a cross-sectional study and the potential effects of environmental and genetic factors were not explored. OCD patients showed an imbalance in the functional link between reward circuits and the CC system at rest. This bias toward a loss of control may define a pathological state in which subjects are more vulnerable to engaging in compulsive behaviors.
Collapse
Affiliation(s)
- Chunming Xie
- Department of Neurology, Affiliated ZhongDa Hospital, Neuropsychiatric Institute, Medical School, Southeast University, No. 87 DingJiaQiao Road, Nanjing, People's Republic of China, 210009.
| | - Lisha Ma
- Department of Psychology, Affiliated Nanjing Brain Hospital, Nanjing Medical University, No. 264 Guangzhou Road, Nanjing, People's Republic of China, 210029
| | - Nan Jiang
- Department of Pharmacy, PLA Army General Hospital, Beijing, People's Republic of China
| | - Ruyan Huang
- Department of Psychology, Affiliated Nanjing Brain Hospital, Nanjing Medical University, No. 264 Guangzhou Road, Nanjing, People's Republic of China, 210029
| | - Li Li
- Advanced Health Center, Affiliated Zhangda Hospital, Medical School, Southeast University, Nanjing, People's Republic of China
| | - Liang Gong
- Department of Neurology, Affiliated ZhongDa Hospital, Neuropsychiatric Institute, Medical School, Southeast University, No. 87 DingJiaQiao Road, Nanjing, People's Republic of China, 210009
| | - Cancan He
- Department of Neurology, Affiliated ZhongDa Hospital, Neuropsychiatric Institute, Medical School, Southeast University, No. 87 DingJiaQiao Road, Nanjing, People's Republic of China, 210009
| | - Chaoyong Xiao
- Department of Psychology, Affiliated Nanjing Brain Hospital, Nanjing Medical University, No. 264 Guangzhou Road, Nanjing, People's Republic of China, 210029
| | - Wen Liu
- Department of Radiology, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, People's Republic of China
| | - Shu Xu
- Department of Psychology, Affiliated Nanjing Brain Hospital, Nanjing Medical University, No. 264 Guangzhou Road, Nanjing, People's Republic of China, 210029.
| | - Zhijun Zhang
- Department of Neurology, Affiliated ZhongDa Hospital, Neuropsychiatric Institute, Medical School, Southeast University, No. 87 DingJiaQiao Road, Nanjing, People's Republic of China, 210009
| |
Collapse
|
33
|
Qian X, Loo BRY, Castellanos FX, Liu S, Koh HL, Poh XWW, Krishnan R, Fung D, Chee MW, Guan C, Lee TS, Lim CG, Zhou J. Brain-computer-interface-based intervention re-normalizes brain functional network topology in children with attention deficit/hyperactivity disorder. Transl Psychiatry 2018; 8:149. [PMID: 30097579 PMCID: PMC6086861 DOI: 10.1038/s41398-018-0213-8] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/18/2018] [Revised: 05/28/2018] [Accepted: 06/20/2018] [Indexed: 01/16/2023] Open
Abstract
A brain-computer-interface (BCI)-based attention training game system has shown promise for treating attention deficit/hyperactivity disorder (ADHD) children with inattentive symptoms. However, little is known about brain network organizational changes underlying behavior improvement following BCI-based training. To cover this gap, we aimed to examine the topological alterations of large-scale brain functional networks induced by the 8-week BCI-based attention intervention in ADHD boys using resting-state functional magnetic resonance imaging method. Compared to the non-intervention (ADHD-NI) group, the intervention group (ADHD-I) showed greater reduction of inattention symptoms accompanied with differential brain network reorganizations after training. Specifically, the ADHD-NI group had increased functional connectivity (FC) within the salience/ventral attention network (SVN) and increased FC between task-positive networks (including the SVN, dorsal attention (DAN), somatomotor, and executive control network) and subcortical regions; in contrast ADHD-I group did not have this pattern. In parallel, ADHD-I group had reduced degree centrality and clustering coefficient as well as increased closeness in task-positive and the default mode networks (prefrontal regions) after the training. More importantly, these reduced local functional processing mainly in the SVN were associated with less inattentive/internalizing problems after 8-week BCI-based intervention across ADHD patients. Our findings suggest that the BCI-based attention training facilitates behavioral improvement in ADHD children by reorganizing brain functional network from more regular to more random configurations, particularly renormalizing salience network processing. Future long-term longitudinal neuroimaging studies are needed to develop the BCI-based intervention approach to promote brain maturation in ADHD.
Collapse
Affiliation(s)
- Xing Qian
- Center for Cognitive Neuroscience, Neuroscience & Behavioral Disorders Program, Duke-National University of Singapore Medical School, Singapore, Singapore
| | - Beatrice Rui Yi Loo
- Center for Cognitive Neuroscience, Neuroscience & Behavioral Disorders Program, Duke-National University of Singapore Medical School, Singapore, Singapore
| | | | - Siwei Liu
- Center for Cognitive Neuroscience, Neuroscience & Behavioral Disorders Program, Duke-National University of Singapore Medical School, Singapore, Singapore
| | - Hui Li Koh
- Center for Cognitive Neuroscience, Neuroscience & Behavioral Disorders Program, Duke-National University of Singapore Medical School, Singapore, Singapore
| | - Xue Wei Wendy Poh
- Department of Child and Adolescent Psychiatry, Institute of Mental Health, Singapore, Singapore
| | - Ranga Krishnan
- Center for Cognitive Neuroscience, Neuroscience & Behavioral Disorders Program, Duke-National University of Singapore Medical School, Singapore, Singapore
| | - Daniel Fung
- Department of Child and Adolescent Psychiatry, Institute of Mental Health, Singapore, Singapore
| | - Michael Wl Chee
- Center for Cognitive Neuroscience, Neuroscience & Behavioral Disorders Program, Duke-National University of Singapore Medical School, Singapore, Singapore
| | - Cuntai Guan
- School of Computer Science and Engineering, Nanyang Technological University, Singapore, Singapore
| | - Tih-Shih Lee
- Center for Cognitive Neuroscience, Neuroscience & Behavioral Disorders Program, Duke-National University of Singapore Medical School, Singapore, Singapore
| | - Choon Guan Lim
- School of Computer Science and Engineering, Nanyang Technological University, Singapore, Singapore
| | - Juan Zhou
- Center for Cognitive Neuroscience, Neuroscience & Behavioral Disorders Program, Duke-National University of Singapore Medical School, Singapore, Singapore.
- Clinical Imaging Research Centre, the Agency for Science, Technology and Research, National University of Singapore, Singapore, Singapore.
| |
Collapse
|
34
|
Gong L, He C, Zhang H, Zhang H, Zhang Z, Xie C. Disrupted reward and cognitive control networks contribute to anhedonia in depression. J Psychiatr Res 2018; 103:61-68. [PMID: 29783076 DOI: 10.1016/j.jpsychires.2018.05.010] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/08/2017] [Revised: 05/07/2018] [Accepted: 05/12/2018] [Indexed: 11/25/2022]
Abstract
Neuroimaging studies have identified that anhedonia, a core feature of major depressive disorder (MDD), is associated with dysfunction in reward and cognitive control processing. However, it is still not clear how the reward network (β-network) and the cognitive control network (δ-network) are linked to biased anhedonia in MDD patients. Sixty-eight MDD patients and 64 cognitively normal (CN) subjects underwent a resting-state functional magnetic resonance imaging scan. A 2*2 ANCOVA analysis was used to explore the differences in the nucleus accumbens-based, voxelwise functional connectivity (FC) between the groups. Then, the β- and δ-networks were constructed, and the FC intensities were compared within and between theβ- and δ-networks across all subjects. Multiple linear regression analyses were also employed to investigate the relationships between the neural features of the β- and δ-networks and anhedonia in MDD patients. Compared to the CN subjects, the MDD patients showed synergistic functional decoupling in both the β- and δ-networks, as well as decreased FC intensities in the intra- and inter- β- and δ-networks. In addition, the FC in both the β- and δ-networks was significantly correlated with anhedonia severity in the MDD patients. Importantly, the integrated neural features of the β- and δ-networks could more precisely predict anhedonic symptoms. These findings initially demonstrated that the imbalance between β- and δ-network activity successfully predicted anhedonia severity and suggested that the neural features of both the β- and δ-networks could represent a fundamental mechanism that underlies anhedonia in MDD patients.
Collapse
Affiliation(s)
- Liang Gong
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, Jiangsu, 210009, China
| | - Cancan He
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, Jiangsu, 210009, China
| | - Haisan Zhang
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, Henan, 453002, China
| | - Hongxing Zhang
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, Henan, 453002, China.
| | - Zhijun Zhang
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, Jiangsu, 210009, China; Neuropsychiatric Institute, Affiliated ZhongDa Hospital, Southeast University, Nanjing, Jiangsu, 210009, China
| | - Chunming Xie
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, Jiangsu, 210009, China; Neuropsychiatric Institute, Affiliated ZhongDa Hospital, Southeast University, Nanjing, Jiangsu, 210009, China.
| |
Collapse
|
35
|
Li W, Zhang J, Zhou C, Hou W, Hu J, Feng H, Zheng X. Abnormal Functional Connectivity Density in Amyotrophic Lateral Sclerosis. Front Aging Neurosci 2018; 10:215. [PMID: 30065647 PMCID: PMC6056617 DOI: 10.3389/fnagi.2018.00215] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2017] [Accepted: 06/25/2018] [Indexed: 01/13/2023] Open
Abstract
Purpose: Amyotrophic lateral sclerosis (ALS) is a motor neuro-degenerative disorder that also damages extra-motor neural pathways. A significant proportion of existing evidence describe alterations in the strengths of functional connectivity, whereas the changes in the density of these functional connections have not been explored. Therefore, our study seeks to identify ALS-induced alternations in the resting-state functional connectivity density (FCD). Methods: Two groups comprising of 38 ALS patients and 35 healthy participants (age and gender matched) were subjected to the resting-state functional magnetic resonance imaging (MRI) scanning. An ultra-fast graph theory method known as FCD mapping was utilized to calculate the voxel-wise short- and long-range FCD values of the brain for each participant. FCD values of patients and controls were compared based on voxels in order to discern cerebral regions that possessed significant FCD alterations. For areas demonstrating a group effect of atypical FCD in ALS, seed-based functional connectivity analysis was then investigated. Partial correlation analyses were carried out between aberrant FCDs and several clinical variables, controlling for age, gender, and total intracranial volume. Results: Patients with ALS were found to have decreased short-range FCD in the primary motor cortex and increased long-range FCD in the premotor cortex. Extra-motor areas that also displayed extensive FCD alterations encompassed the temporal cortex, insula, cingulate gyrus, occipital cortex, and inferior parietal lobule. Seed-based correlation analysis further demonstrated that these regions also possessed disrupted functional connectivity. However, no significant correlations were identified between aberrant FCDs and clinical variables. Conclusion: FCD changes in the regions identified represent communication deficits and impaired functional brain dynamics, which might underlie the motor, motor control, language, visuoperceptual and high-order cognitive deficits in ALS. These findings support the fact that ALS is a disorder affecting multiple systems. We gain a deeper insight of the neural mechanisms underlying ALS.
Collapse
Affiliation(s)
- Weina Li
- Key Laboratory of Biorheological Science and Technology, Ministry of Education, Bioengineering College, Chongqing University, Chongqing, China.,Department of Neurosurgery, Southwest Hospital, Third Military Medical University, Army Medical University, Chongqing, China.,Chongqing Collaborative Innovation Center for Brain Science, Chongqing, China
| | - Jiuquan Zhang
- Department of Radiology, Chongqing University Cancer Hospital, Chongqing, China
| | - Chaoyang Zhou
- Chongqing Collaborative Innovation Center for Brain Science, Chongqing, China.,Department of Radiology, Chongqing University Cancer Hospital, Chongqing, China
| | - Wensheng Hou
- Key Laboratory of Biorheological Science and Technology, Ministry of Education, Bioengineering College, Chongqing University, Chongqing, China.,Chongqing Collaborative Innovation Center for Brain Science, Chongqing, China
| | - Jun Hu
- Chongqing Collaborative Innovation Center for Brain Science, Chongqing, China.,Department of Neurology, Southwest Hospital, Third Military Medical University, Army Medical University, Chongqing, China
| | - Hua Feng
- Department of Neurosurgery, Southwest Hospital, Third Military Medical University, Army Medical University, Chongqing, China.,Chongqing Collaborative Innovation Center for Brain Science, Chongqing, China
| | - Xiaolin Zheng
- Key Laboratory of Biorheological Science and Technology, Ministry of Education, Bioengineering College, Chongqing University, Chongqing, China.,Chongqing Collaborative Innovation Center for Brain Science, Chongqing, China
| |
Collapse
|
36
|
An evaluation of the efficacy, reliability, and sensitivity of motion correction strategies for resting-state functional MRI. Neuroimage 2018; 171:415-436. [DOI: 10.1016/j.neuroimage.2017.12.073] [Citation(s) in RCA: 445] [Impact Index Per Article: 74.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2017] [Revised: 12/21/2017] [Accepted: 12/21/2017] [Indexed: 12/19/2022] Open
|
37
|
Ng KK, Qiu Y, Lo JCY, Koay ESC, Koh WP, Chee MWL, Zhou J. Functional segregation loss over time is moderated by APOE genotype in healthy elderly. Hum Brain Mapp 2018. [PMID: 29520911 DOI: 10.1002/hbm.24036] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
We investigated the influence of the apolipoprotein E-ɛ4 allele (APOE-ɛ4) on longitudinal age-related changes in brain functional connectivity (FC) and cognition, in view of mixed cross-sectional findings. One hundred and twenty-two healthy older adults (aged 58-79; 25 APOE-ɛ4 carriers) underwent task-free fMRI scans at baseline. Seventy-eight (16 carriers) had at least one follow-up (every 2 years). Changes in intra- and internetwork FCs among the default mode (DMN), executive control (ECN), and salience (SN) networks, as well as cognition, were quantified using linear mixed models. Cross-sectionally, APOE-ɛ4 carriers had lower functional connectivity between the ECN and SN than noncarriers. Carriers also showed a stronger age-dependent decrease in visuospatial memory performance. Longitudinally, carriers had steeper increase in inter-ECN-DMN FC, indicating loss of functional segregation. The longitudinal change in processing speed performance was not moderated by APOE-ɛ4 genotype, but the brain-cognition association was. In younger elderly, faster loss of segregation was correlated with greater decline in processing speed regardless of genotype. In older elderly, such relation remained for noncarriers but reversed for carriers. APOE-ɛ4 may alter aging by accelerating the change in segregation between high-level cognitive systems. Its modulation on the longitudinal brain-cognition relationship was age-dependent.
Collapse
Affiliation(s)
- Kwun Kei Ng
- Centre for Cognitive Neuroscience, Neuroscience and Behavioural Disorders Programme, Duke-National University of Singapore Medical School, Singapore, 169857, Singapore
| | - Yingwei Qiu
- Centre for Cognitive Neuroscience, Neuroscience and Behavioural Disorders Programme, Duke-National University of Singapore Medical School, Singapore, 169857, Singapore.,Department of Radiology, Third Affiliated Hospital of Guangzhou Medical University, Guangzhou Shi, Guangdong Sheng, 510000, China
| | - June Chi-Yan Lo
- Centre for Cognitive Neuroscience, Neuroscience and Behavioural Disorders Programme, Duke-National University of Singapore Medical School, Singapore, 169857, Singapore
| | - Evelyn Siew-Chuan Koay
- Department of Pathology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 117549, Singapore.,Molecular Diagnosis Centre, Department of Laboratory Medicine, National University Hospital, Singapore, 119074, Singapore
| | - Woon-Puay Koh
- Office of Clinical Sciences, Duke-National University of Singapore Medical School, Singapore, 169857, Singapore.,Saw Swee Hock School of Public Health, National University of Singapore, Singapore, 117549, Singapore
| | - Michael Wei-Liang Chee
- Centre for Cognitive Neuroscience, Neuroscience and Behavioural Disorders Programme, Duke-National University of Singapore Medical School, Singapore, 169857, Singapore
| | - Juan Zhou
- Centre for Cognitive Neuroscience, Neuroscience and Behavioural Disorders Programme, Duke-National University of Singapore Medical School, Singapore, 169857, Singapore.,Clinical Imaging Research Centre, the Agency for Science, Technology and Research and National University of Singapore, Singapore, 117599, Singapore
| |
Collapse
|
38
|
Chen G, Shu H, Chen G, Ward BD, Antuono PG, Zhang Z, Li SJ. Staging Alzheimer's Disease Risk by Sequencing Brain Function and Structure, Cerebrospinal Fluid, and Cognition Biomarkers. J Alzheimers Dis 2018; 54:983-993. [PMID: 27567874 PMCID: PMC5055443 DOI: 10.3233/jad-160537] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
This study aims to develop a composite biomarker that can accurately measure the sequential biological stages of Alzheimer’s disease (AD) on an individual level. We selected 144 subjects from the Alzheimer’s Disease Neuroimaging Initiative 2 datasets. Ten biomarkers, from brain function and structure, cerebrospinal fluid, and cognitive performance, were integrated using the event-based probabilistic model to estimate their optimal temporal sequence (Soptimal). We identified the numerical order of the Soptimal as the characterizing Alzheimer’s disease risk events (CARE) index to measure disease stage. The results show that, in the Soptimal, hippocampal and posterior cingulate cortex network biomarkers occur first, followed by aberrant cerebrospinal fluid amyloid-β and p-tau levels, then cognitive deficit, and finally regional gray matter loss and fusiform network abnormality. The CARE index significantly correlates with disease severity and exhibits high reliability. Our findings demonstrate that use of the CARE index would advance AD stage measurement across the whole AD continuum and facilitate personalized treatment of AD.
Collapse
Affiliation(s)
- Guangyu Chen
- Department of Biophysics, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Hao Shu
- Department of Biophysics, Medical College of Wisconsin, Milwaukee, WI, USA.,Department of Neurology, Affiliated ZhongDa Hospital, Neuropsychiatric Institute and Medical School of Southeast University, Nanjing, Jiangsu, China
| | - Gang Chen
- Department of Biophysics, Medical College of Wisconsin, Milwaukee, WI, USA
| | - B Douglas Ward
- Department of Biophysics, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Piero G Antuono
- Department of Neurology, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Zhijun Zhang
- Department of Neurology, Affiliated ZhongDa Hospital, Neuropsychiatric Institute and Medical School of Southeast University, Nanjing, Jiangsu, China
| | - Shi-Jiang Li
- Department of Biophysics, Medical College of Wisconsin, Milwaukee, WI, USA
| | | |
Collapse
|
39
|
Fareri DS, Gabard-Durnam L, Goff B, Flannery J, Gee DG, Lumian DS, Caldera C, Tottenham N. Altered ventral striatal-medial prefrontal cortex resting-state connectivity mediates adolescent social problems after early institutional care. Dev Psychopathol 2017; 29:1865-1876. [PMID: 29162189 PMCID: PMC5957481 DOI: 10.1017/s0954579417001456] [Citation(s) in RCA: 39] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Early caregiving adversity is associated with increased risk for social difficulties. The ventral striatum and associated corticostriatal circuitry, which have demonstrated vulnerability to early exposures to adversity, are implicated in many aspects of social behavior, including social play, aggression, and valuation of social stimuli across development. Here, we used resting-state functional magnetic resonance imaging to assess the degree to which early caregiving adversity was associated with altered coritocostriatal resting connectivity in previously institutionalized youth (n = 41) relative to youth who were raised with their biological families from birth (n = 47), and the degree to which this connectivity was associated with parent-reported social problems. Using a seed-based approach, we observed increased positive coupling between the ventral striatum and anterior regions of medial prefrontal cortex (mPFC) in previously institutionalized youth. Stronger ventral striatum-mPFC coupling was associated with parent reports of social problems. A moderated-mediation analysis showed that ventral striatal-mPFC connectivity mediated group differences in social problems, and more so with increasing age. These findings show that early institutional care is associated with differences in resting-state connectivity between the ventral striatum and the mPFC, and this connectivity seems to play an increasingly important role in social behaviors as youth enter adolescence.
Collapse
Affiliation(s)
- Dominic S. Fareri
- Gordon F. Derner School of Psychology, Adelphi University, Garden City, NY 11530
| | | | - Bonnie Goff
- Department of Psychology, University of California-Los Angeles, Los Angeles, CA 90095
| | - Jessica Flannery
- Department of Psychology, University of Oregon, Eugene, OR 97403
| | - Dylan G. Gee
- Department of Psychology, Yale University, New Haven, CT 06511
| | - Daniel S. Lumian
- Department of Psychology, University of Denver, Denver, CO 80208
| | - Christina Caldera
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California-Los Angeles, Los Angeles, CA 90095
| | - Nim Tottenham
- Department of Psychology, Columbia University, New York, NY 10027
| |
Collapse
|
40
|
Chong JSX, Liu S, Loke YM, Hilal S, Ikram MK, Xu X, Tan BY, Venketasubramanian N, Chen CLH, Zhou J. Influence of cerebrovascular disease on brain networks in prodromal and clinical Alzheimer's disease. Brain 2017; 140:3012-3022. [PMID: 29053778 PMCID: PMC5841199 DOI: 10.1093/brain/awx224] [Citation(s) in RCA: 44] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2017] [Accepted: 07/12/2017] [Indexed: 01/16/2023] Open
Abstract
Network-sensitive neuroimaging methods have been used to characterize large-scale brain network degeneration in Alzheimer’s disease and its prodrome. However, few studies have investigated the combined effect of Alzheimer’s disease and cerebrovascular disease on brain network degeneration. Our study sought to examine the intrinsic functional connectivity and structural covariance network changes in 235 prodromal and clinical Alzheimer’s disease patients with and without cerebrovascular disease. We focused particularly on two higher-order cognitive networks—the default mode network and the executive control network. We found divergent functional connectivity and structural covariance patterns in Alzheimer’s disease patients with and without cerebrovascular disease. Alzheimer’s disease patients without cerebrovascular disease, but not Alzheimer’s disease patients with cerebrovascular disease, showed reductions in posterior default mode network functional connectivity. By comparison, while both groups exhibited parietal reductions in executive control network functional connectivity, only Alzheimer’s disease patients with cerebrovascular disease showed increases in frontal executive control network connectivity. Importantly, these distinct executive control network changes were recapitulated in prodromal Alzheimer’s disease patients with and without cerebrovascular disease. Across Alzheimer’s disease patients with and without cerebrovascular disease, higher default mode network functional connectivity z-scores correlated with greater hippocampal volumes while higher executive control network functional connectivity z-scores correlated with greater white matter changes. In parallel, only Alzheimer’s disease patients without cerebrovascular disease showed increased default mode network structural covariance, while only Alzheimer’s disease patients with cerebrovascular disease showed increased executive control network structural covariance compared to controls. Our findings demonstrate the differential neural network structural and functional changes in Alzheimer’s disease with and without cerebrovascular disease, suggesting that the underlying pathology of Alzheimer’s disease patients with cerebrovascular disease might differ from those without cerebrovascular disease and reflect a combination of more severe cerebrovascular disease and less severe Alzheimer’s disease network degeneration phenotype.
Collapse
Affiliation(s)
- Joanna Su Xian Chong
- Centre for Cognitive Neuroscience, Neuroscience and Behavioural Disorders Programme, Duke-National University of Singapore Medical School, Singapore
| | - Siwei Liu
- Centre for Cognitive Neuroscience, Neuroscience and Behavioural Disorders Programme, Duke-National University of Singapore Medical School, Singapore
| | - Yng Miin Loke
- Centre for Cognitive Neuroscience, Neuroscience and Behavioural Disorders Programme, Duke-National University of Singapore Medical School, Singapore
| | - Saima Hilal
- Department of Pharmacology, Clinical Research Centre, National University Health System, National University of Singapore, Singapore.,Memory Ageing and Cognition Centre, National University Health System, Singapore
| | - Mohammad Kamran Ikram
- Memory Ageing and Cognition Centre, National University Health System, Singapore.,Duke-National University of Singapore Medical School, Singapore
| | - Xin Xu
- Department of Pharmacology, Clinical Research Centre, National University Health System, National University of Singapore, Singapore.,Memory Ageing and Cognition Centre, National University Health System, Singapore
| | | | | | - Christopher Li-Hsian Chen
- Department of Pharmacology, Clinical Research Centre, National University Health System, National University of Singapore, Singapore.,Memory Ageing and Cognition Centre, National University Health System, Singapore
| | - Juan Zhou
- Centre for Cognitive Neuroscience, Neuroscience and Behavioural Disorders Programme, Duke-National University of Singapore Medical School, Singapore.,Clinical Imaging Research Centre, The Agency for Science, Technology and Research and National University of Singapore, Singapore
| |
Collapse
|
41
|
Distinctive pretreatment features of bilateral nucleus accumbens networks predict early response to antidepressants in major depressive disorder. Brain Imaging Behav 2017; 12:1042-1052. [DOI: 10.1007/s11682-017-9773-0] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
|
42
|
Gong L, He C, Yin Y, Wang H, Ye Q, Bai F, Yuan Y, Zhang H, Lv L, Zhang H, Zhang Z, Xie C. Mediating Role of the Reward Network in the Relationship between the Dopamine Multilocus Genetic Profile and Depression. Front Mol Neurosci 2017; 10:292. [PMID: 28959185 PMCID: PMC5603675 DOI: 10.3389/fnmol.2017.00292] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2017] [Accepted: 08/31/2017] [Indexed: 12/24/2022] Open
Abstract
Multiple genetic loci in the dopamine (DA) pathway have been associated with depression symptoms in patients with major depressive disorder (MDD). However, the neural mechanisms underlying the polygenic effects of the DA pathway on depression remain unclear. We used an imaging genetic approach to investigate the polygenic effects of the DA pathway on the reward network in MDD. Fifty-three patients and 37 cognitively normal (CN) subjects were recruited and underwent resting-state functional magnetic resonance imaging (R-fMRI) scans. Multivariate linear regression analysis was employed to measure the effects of disease and multilocus genetic profile scores (MGPS) on the reward network, which was constructed using the nucleus accumbens (NAc) functional connectivity (NAFC) network. DA-MGPS was widely associated within the NAFC network, mainly in the inferior frontal cortex, insula, hypothalamus, superior temporal gyrus, and occipital cortex. The pattern of DA-MGPS effects on the fronto-striatal pathway differed in MDD patients compared with CN subjects. More importantly, NAc-putamen connectivity mediates the association between DA MGPS and anxious depression traits in MDD patients. Our findings suggest that the DA multilocus genetic profile makes a considerable contribution to the reward network and anxious depression in MDD patients. These results expand our understanding of the pathophysiology of polygenic effects underlying brain network abnormalities in MDD.
Collapse
Affiliation(s)
- Liang Gong
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast UniversityNanjing, China
| | - Cancan He
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast UniversityNanjing, China
| | - Yingying Yin
- Department of Psychology, Affiliated ZhongDa Hospital, School of Medicine, Southeast UniversityNanjing, China
| | - Hui Wang
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast UniversityNanjing, China
| | - Qing Ye
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast UniversityNanjing, China
| | - Feng Bai
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast UniversityNanjing, China.,Neuropsychaitric institute, Affiliated ZhongDa Hospital, Southeast UniversityNanjing, China
| | - Yonggui Yuan
- Department of Psychology, Affiliated ZhongDa Hospital, School of Medicine, Southeast UniversityNanjing, China.,Neuropsychaitric institute, Affiliated ZhongDa Hospital, Southeast UniversityNanjing, China
| | - Haisan Zhang
- Department of Psychiatry, Henan Mental Hospital, the Second Hospital of Xinxiang Medical UniversityXinxiang, China
| | - Luxian Lv
- Department of Psychiatry, Henan Mental Hospital, the Second Hospital of Xinxiang Medical UniversityXinxiang, China
| | - Hongxing Zhang
- Department of Psychiatry, Henan Mental Hospital, the Second Hospital of Xinxiang Medical UniversityXinxiang, China
| | - Zhijun Zhang
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast UniversityNanjing, China.,Neuropsychaitric institute, Affiliated ZhongDa Hospital, Southeast UniversityNanjing, China
| | - Chunming Xie
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast UniversityNanjing, China.,Neuropsychaitric institute, Affiliated ZhongDa Hospital, Southeast UniversityNanjing, China
| |
Collapse
|
43
|
Salinas FS, Szabó CÁ. Resting-state functional connectivity changes due to acute and short-term valproic acid administration in the baboon model of GGE. NEUROIMAGE-CLINICAL 2017; 16:132-141. [PMID: 28794974 PMCID: PMC5537408 DOI: 10.1016/j.nicl.2017.07.013] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/07/2017] [Revised: 07/14/2017] [Accepted: 07/15/2017] [Indexed: 12/14/2022]
Abstract
Resting-state functional connectivity (FC) is altered in baboons with genetic generalized epilepsy (GGE) compared to healthy controls (CTL). We compared FC changes between GGE and CTL groups after intravenous injection of valproic acid (VPA) and following one-week of orally administered VPA. Seven epileptic (2 females) and six CTL (3 females) baboons underwent resting-state fMRI (rs-fMRI) at 1) baseline, 2) after intravenous acute VPA administration (20 mg/kg), and 3) following seven-day oral, subacute VPA therapy (20–80 mg/kg/day). FC was evaluated using a data-driven approach, while regressing out the group-wise effects of age, gender and VPA levels. Sixteen networks were identified by independent component analysis (ICA). Each network mask was thresholded (z > 4.00; p < 0.001), and used to compare group-wise FC differences between baseline, intravenous and oral VPA treatment states between GGE and CTL groups. At baseline, FC was increased in most cortical networks of the GGE group but decreased in the thalamic network. After intravenous acute VPA, FC increased in the basal ganglia network and decreased in the parietal network of epileptic baboons to presumed nodes associated with the epileptic network. After oral VPA therapy, FC was decreased in GGE baboons only the orbitofrontal networks connections to the primary somatosensory cortices, reflecting a reversal from baseline comparisons. VPA therapy affects FC in the baboon model of GGE after a single intravenous dose—possibly by facilitating subcortical modulation of the epileptic network and suppressing seizure generation—and after short-term oral VPA treatment, reversing the abnormal baseline increases in FC in the orbitofrontal network. While there is a need to correlate these FC changes with simultaneous EEG recording and seizure outcomes, this study demonstrates the feasibility of evaluating rs-fMRI effects of antiepileptic medications even after short-term exposure. This resting-state fMRI study evaluates treatment-related functional connectivity (FC) changes in the baboon model of GGE. Pre-treatment FC is mostly increased in cortical networks, but decreased for the thalamic network in epileptic baboons. Treatment-related FC changes were noted both after single intravenous dose of VPA and short-term oral VPA treatment. FC studies may provide a novel approach to evaluate antiepileptic medication effects.
Collapse
Affiliation(s)
- Felipe S Salinas
- Research Imaging Institute, UT Health, San Antonio, United States.,South Texas Veterans Health Care System, San Antonio, TX, United States
| | - Charles Ákos Szabó
- Department of Neurology, UT Health, San Antonio, United States.,South Texas Comprehensive Epilepsy Center, UT Health, San Antonio, United States
| |
Collapse
|
44
|
Stimulus-Elicited Connectivity Influences Resting-State Connectivity Years Later in Human Development: A Prospective Study. J Neurosci 2017; 36:4771-84. [PMID: 27122035 DOI: 10.1523/jneurosci.0598-16.2016] [Citation(s) in RCA: 51] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2016] [Accepted: 03/18/2016] [Indexed: 01/25/2023] Open
Abstract
UNLABELLED Although the functional architecture of the brain is indexed by resting-state connectivity networks, little is currently known about the mechanisms through which these networks assemble into stable mature patterns. The current study posits and tests the long-term phasic molding hypothesis that resting-state networks are gradually shaped by recurring stimulus-elicited connectivity across development by examining how both stimulus-elicited and resting-state functional connections of the human brain emerge over development at the systems level. Using a sequential design following 4- to 18-year-olds over a 2 year period, we examined the predictive associations between stimulus-elicited and resting-state connectivity in amygdala-cortical circuitry as an exemplar case (given this network's protracted development across these ages). Age-related changes in amygdala functional connectivity converged on the same regions of medial prefrontal cortex (mPFC) and inferior frontal gyrus when elicited by emotional stimuli and when measured at rest. Consistent with the long-term phasic molding hypothesis, prospective analyses for both connections showed that the magnitude of an individual's stimulus-elicited connectivity unidirectionally predicted resting-state functional connectivity 2 years later. For the amygdala-mPFC connection, only stimulus-elicited connectivity during childhood and the transition to adolescence shaped future resting-state connectivity, consistent with a sensitive period ending with adolescence for the amygdala-mPFC circuit. Together, these findings suggest that resting-state functional architecture may arise from phasic patterns of functional connectivity elicited by environmental stimuli over the course of development on the order of years. SIGNIFICANCE STATEMENT A fundamental issue in understanding the ontogeny of brain function is how resting-state (intrinsic) functional networks emerge and relate to stimulus-elicited functional connectivity. Here, we posit and test the long-term phasic molding hypothesis that resting-state network development is influenced by recurring stimulus-elicited connectivity through prospective examination of the developing human amygdala-cortical functional connections. Our results provide critical insight into how early environmental events sculpt functional network architecture across development and highlight childhood as a potential developmental period of heightened malleability for the amygdala-medial prefrontal cortex circuit. These findings have implications for how both positive and adverse experiences influence the developing brain and motivate future investigations of whether this molding mechanism reflects a general phenomenon of brain development.
Collapse
|
45
|
Geerligs L, Tsvetanov KA, Cam-Can, Henson RN. Challenges in measuring individual differences in functional connectivity using fMRI: The case of healthy aging. Hum Brain Mapp 2017; 38:4125-4156. [PMID: 28544076 PMCID: PMC5518296 DOI: 10.1002/hbm.23653] [Citation(s) in RCA: 114] [Impact Index Per Article: 16.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2016] [Revised: 05/08/2017] [Accepted: 05/08/2017] [Indexed: 12/11/2022] Open
Abstract
Many studies report individual differences in functional connectivity, such as those related to age. However, estimates of connectivity from fMRI are confounded by other factors, such as vascular health, head motion and changes in the location of functional regions. Here, we investigate the impact of these confounds, and pre‐processing strategies that can mitigate them, using data from the Cambridge Centre for Ageing & Neuroscience (http://www.cam-can.com). This dataset contained two sessions of resting‐state fMRI from 214 adults aged 18–88. Functional connectivity between all regions was strongly related to vascular health, most likely reflecting respiratory and cardiac signals. These variations in mean connectivity limit the validity of between‐participant comparisons of connectivity estimates, and were best mitigated by regression of mean connectivity over participants. We also showed that high‐pass filtering, instead of band‐pass filtering, produced stronger and more reliable age‐effects. Head motion was correlated with gray‐matter volume in selected brain regions, and with various cognitive measures, suggesting that it has a biological (trait) component, and warning against regressing out motion over participants. Finally, we showed that the location of functional regions was more variable in older adults, which was alleviated by smoothing the data, or using a multivariate measure of connectivity. These results demonstrate that analysis choices have a dramatic impact on connectivity differences between individuals, ultimately affecting the associations found between connectivity and cognition. It is important that fMRI connectivity studies address these issues, and we suggest a number of ways to optimize analysis choices. Hum Brain Mapp 38:4125–4156, 2017. © 2017 Wiley Periodicals, Inc.
Collapse
Affiliation(s)
- Linda Geerligs
- MRC Cognition and Brain Sciences Unit, Cambridge, United Kingdom.,Cambridge Centre for Ageing and Neuroscience (Cam-CAN), University of Cambridge and MRC Cognition and Brain Sciences Unit, Cambridge, United Kingdom.,Donders Institute for Brain, Cognition and Behaviour, Radboud University, the Netherlands
| | - Kamen A Tsvetanov
- Cambridge Centre for Ageing and Neuroscience (Cam-CAN), University of Cambridge and MRC Cognition and Brain Sciences Unit, Cambridge, United Kingdom.,Centre for Speech, Language and the Brain, Department of Psychology, University of Cambridge, Cambridge, United Kingdom.,Department of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom
| | - Cam-Can
- Cambridge Centre for Ageing and Neuroscience (Cam-CAN), University of Cambridge and MRC Cognition and Brain Sciences Unit, Cambridge, United Kingdom
| | - Richard N Henson
- MRC Cognition and Brain Sciences Unit, Cambridge, United Kingdom.,Cambridge Centre for Ageing and Neuroscience (Cam-CAN), University of Cambridge and MRC Cognition and Brain Sciences Unit, Cambridge, United Kingdom
| |
Collapse
|
46
|
A longitudinal study of the effect of short-term meditation training on functional network organization of the aging brain. Sci Rep 2017; 7:598. [PMID: 28377606 PMCID: PMC5428857 DOI: 10.1038/s41598-017-00678-8] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2016] [Accepted: 03/08/2017] [Indexed: 12/27/2022] Open
Abstract
The beneficial effects of meditation on preserving age-related changes in cognitive functioning are well established. Yet, the neural underpinnings of these positive effects have not been fully unveiled. This study employed a prospective longitudinal design, and graph-based analysis, to study how an eight-week meditation training vs. relaxation training shaped network configuration at global, intermediate, and local levels using graph theory in the elderly. At the intermediate level, meditation training lead to decreased intra-connectivity in the default mode network (DMN), salience network (SAN) and somatomotor network (SMN) modules post training. Also, there was decreased connectivity strength between the DMN and other modules. At a local level, meditation training lowered nodal strength in the left posterior cingulate gryus, bilateral paracentral lobule, and middle cingulate gyrus. According to previous literature, the direction of these changes is consistent with a movement towards a more self-detached viewpoint, as well as more efficient processing. Furthermore, our findings highlight the importance of considering brain network changes across organizational levels, as well as the pace at which these changes may occur. Overall, this study provides further support for short-term meditation as a potentially beneficial method of mental training for the elderly that warrants further investigation.
Collapse
|
47
|
Madden DJ, Parks EL, Tallman CW, Boylan MA, Hoagey DA, Cocjin SB, Packard LE, Johnson MA, Chou YH, Potter GG, Chen NK, Siciliano RE, Monge ZA, Honig JA, Diaz MT. Sources of disconnection in neurocognitive aging: cerebral white-matter integrity, resting-state functional connectivity, and white-matter hyperintensity volume. Neurobiol Aging 2017; 54:199-213. [PMID: 28389085 DOI: 10.1016/j.neurobiolaging.2017.01.027] [Citation(s) in RCA: 43] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2015] [Revised: 01/05/2017] [Accepted: 01/06/2017] [Indexed: 01/12/2023]
Abstract
Age-related decline in fluid cognition can be characterized as a disconnection among specific brain structures, leading to a decline in functional efficiency. The potential sources of disconnection, however, are unclear. We investigated imaging measures of cerebral white-matter integrity, resting-state functional connectivity, and white-matter hyperintensity volume as mediators of the relation between age and fluid cognition, in 145 healthy, community-dwelling adults 19-79 years of age. At a general level of analysis, with a single composite measure of fluid cognition and single measures of each of the 3 imaging modalities, age exhibited an independent influence on the cognitive and imaging measures, and the imaging variables did not mediate the age-cognition relation. At a more specific level of analysis, resting-state functional connectivity of sensorimotor networks was a significant mediator of the age-related decline in executive function. These findings suggest that different levels of analysis lead to different models of neurocognitive disconnection, and that resting-state functional connectivity, in particular, may contribute to age-related decline in executive function.
Collapse
Affiliation(s)
- David J Madden
- Brain Imaging and Analysis Center, Duke University Medical Center, Durham, NC, USA; Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC, USA.
| | - Emily L Parks
- Brain Imaging and Analysis Center, Duke University Medical Center, Durham, NC, USA; Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC, USA
| | - Catherine W Tallman
- Brain Imaging and Analysis Center, Duke University Medical Center, Durham, NC, USA
| | - Maria A Boylan
- Brain Imaging and Analysis Center, Duke University Medical Center, Durham, NC, USA
| | - David A Hoagey
- Brain Imaging and Analysis Center, Duke University Medical Center, Durham, NC, USA
| | - Sally B Cocjin
- Brain Imaging and Analysis Center, Duke University Medical Center, Durham, NC, USA
| | - Lauren E Packard
- Brain Imaging and Analysis Center, Duke University Medical Center, Durham, NC, USA
| | - Micah A Johnson
- Brain Imaging and Analysis Center, Duke University Medical Center, Durham, NC, USA
| | - Ying-Hui Chou
- Brain Imaging and Analysis Center, Duke University Medical Center, Durham, NC, USA; Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC, USA
| | - Guy G Potter
- Brain Imaging and Analysis Center, Duke University Medical Center, Durham, NC, USA; Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC, USA
| | - Nan-Kuei Chen
- Brain Imaging and Analysis Center, Duke University Medical Center, Durham, NC, USA; Department of Radiology, Duke University Medical Center, Durham, NC, USA
| | - Rachel E Siciliano
- Brain Imaging and Analysis Center, Duke University Medical Center, Durham, NC, USA
| | - Zachary A Monge
- Center for Cognitive Neuroscience, Duke University, Durham, NC, USA
| | - Jesse A Honig
- Brain Imaging and Analysis Center, Duke University Medical Center, Durham, NC, USA
| | - Michele T Diaz
- Department of Psychology, Pennsylvania State University, University Park, PA, USA
| |
Collapse
|
48
|
Liu TT, Nalci A, Falahpour M. The global signal in fMRI: Nuisance or Information? Neuroimage 2017; 150:213-229. [PMID: 28213118 DOI: 10.1016/j.neuroimage.2017.02.036] [Citation(s) in RCA: 256] [Impact Index Per Article: 36.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2016] [Revised: 02/05/2017] [Accepted: 02/13/2017] [Indexed: 01/17/2023] Open
Abstract
The global signal is widely used as a regressor or normalization factor for removing the effects of global variations in the analysis of functional magnetic resonance imaging (fMRI) studies. However, there is considerable controversy over its use because of the potential bias that can be introduced when it is applied to the analysis of both task-related and resting-state fMRI studies. In this paper we take a closer look at the global signal, examining in detail the various sources that can contribute to the signal. For the most part, the global signal has been treated as a nuisance term, but there is growing evidence that it may also contain valuable information. We also examine the various ways that the global signal has been used in the analysis of fMRI data, including global signal regression, global signal subtraction, and global signal normalization. Furthermore, we describe new ways for understanding the effects of global signal regression and its relation to the other approaches.
Collapse
Affiliation(s)
- Thomas T Liu
- Center for Functional MRI, University of California San Diego, 9500 Gilman Drive MC 0677, La Jolla, CA 92093, United States; Departments of Radiology, Psychiatry, and Bioengineering, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093, United States.
| | - Alican Nalci
- Center for Functional MRI, University of California San Diego, 9500 Gilman Drive MC 0677, La Jolla, CA 92093, United States; Department of Electrical and Computer Engineering, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093, United States.
| | - Maryam Falahpour
- Center for Functional MRI, University of California San Diego, 9500 Gilman Drive MC 0677, La Jolla, CA 92093, United States.
| |
Collapse
|
49
|
Su F, Shu H, Ye Q, Xie C, Yuan B, Zhang Z, Bai F. Integration of Multilocus Genetic Risk into the Default Mode Network Longitudinal Trajectory during the Alzheimer’s Disease Process. J Alzheimers Dis 2017; 56:491-507. [PMID: 28035927 DOI: 10.3233/jad-160787] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Affiliation(s)
- Fan Su
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, Jiangsu, China
| | - Hao Shu
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, Jiangsu, China
- Department of Biophysics, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Qing Ye
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, Jiangsu, China
| | - Chunming Xie
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, Jiangsu, China
| | - Baoyu Yuan
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, Jiangsu, China
| | - Zhijun Zhang
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, Jiangsu, China
| | - Feng Bai
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, Jiangsu, China
| |
Collapse
|
50
|
Gong L, Yin Y, He C, Ye Q, Bai F, Yuan Y, Zhang H, Lv L, Zhang H, Xie C, Zhang Z. Disrupted reward circuits is associated with cognitive deficits and depression severity in major depressive disorder. J Psychiatr Res 2017; 84:9-17. [PMID: 27673704 DOI: 10.1016/j.jpsychires.2016.09.016] [Citation(s) in RCA: 60] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/17/2016] [Revised: 08/14/2016] [Accepted: 09/16/2016] [Indexed: 01/15/2023]
Abstract
Neuroimaging studies have demonstrated that major depressive disorder (MDD) patients show blunted activity responses to reward-related tasks. However, whether abnormal reward circuits affect cognition and depression in MDD patients remains unclear. Seventy-five drug-naive MDD patients and 42 cognitively normal (CN) subjects underwent a resting-state functional magnetic resonance imaging scan. The bilateral nucleus accumbens (NAc) were selected as seeds to construct reward circuits across all subjects. A multivariate linear regression analysis was employed to investigate the neural substrates of cognitive function and depression severity on the reward circuits in MDD patients. The common pathway underlying cognitive deficits and depression was identified with conjunction analysis. Compared with CN subjects, MDD patients showed decreased reward network connectivity that was primarily located in the prefrontal-striatal regions. Importantly, distinct and common neural pathways underlying cognition and depression were identified, implying the independent and synergistic effects of cognitive deficits and depression severity on reward circuits. This study demonstrated that disrupted topological organization within reward circuits was significantly associated with cognitive deficits and depression severity in MDD patients. These findings suggest that in addition to antidepressant treatment, normalized reward circuits should be a focus and a target for improving depression and cognitive deficits in MDD patients.
Collapse
Affiliation(s)
- Liang Gong
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, Jiangsu 210009, China
| | - Yingying Yin
- Department of Psychology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, Jiangsu 210009, China; Neuropsychiatric Institute, Affiliated ZhongDa Hospital, Southeast University, Nanjing, Jiangsu 210009, China
| | - Cancan He
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, Jiangsu 210009, China
| | - Qing Ye
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, Jiangsu 210009, China
| | - Feng Bai
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, Jiangsu 210009, China; Neuropsychiatric Institute, Affiliated ZhongDa Hospital, Southeast University, Nanjing, Jiangsu 210009, China
| | - Yonggui Yuan
- Department of Psychology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, Jiangsu 210009, China; Neuropsychiatric Institute, Affiliated ZhongDa Hospital, Southeast University, Nanjing, Jiangsu 210009, China
| | - Haisan Zhang
- Department of Psychiatry, Henan Provincial Mental Hospital, Xinxiang Medical University, Xinxiang, Henan 453002, China
| | - Luxian Lv
- Department of Psychiatry, Henan Provincial Mental Hospital, Xinxiang Medical University, Xinxiang, Henan 453002, China
| | - Hongxing Zhang
- Department of Psychiatry, Henan Provincial Mental Hospital, Xinxiang Medical University, Xinxiang, Henan 453002, China; Department of Psychology of Xinxiang Medical University, Xinxiang, Henan 453003, China.
| | - Chunming Xie
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, Jiangsu 210009, China; Neuropsychiatric Institute, Affiliated ZhongDa Hospital, Southeast University, Nanjing, Jiangsu 210009, China.
| | - Zhijun Zhang
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, Jiangsu 210009, China; Neuropsychiatric Institute, Affiliated ZhongDa Hospital, Southeast University, Nanjing, Jiangsu 210009, China
| |
Collapse
|