1
|
Zhao Z, Shuai Y, Wu Y, Xu X, Li M, Wu D. Age-dependent functional development pattern in neonatal brain: An fMRI-based brain entropy study. Neuroimage 2024; 297:120669. [PMID: 38852805 DOI: 10.1016/j.neuroimage.2024.120669] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2023] [Revised: 04/01/2024] [Accepted: 06/05/2024] [Indexed: 06/11/2024] Open
Abstract
The relationship between brain entropy (BEN) and early brain development has been established through animal studies. However, it remains unclear whether the BEN can be used to identify age-dependent functional changes in human neonatal brains and the genetic underpinning of the new neuroimaging marker remains to be elucidated. In this study, we analyzed resting-state fMRI data from the Developing Human Connectome Project, including 280 infants who were scanned at 37.5-43.5 weeks postmenstrual age. The BEN maps were calculated for each subject, and a voxel-wise analysis was conducted using a general linear model to examine the effects of age, sex, and preterm birth on BEN. Additionally, we evaluated the correlation between regional BEN and gene expression levels. Our results demonstrated that the BEN in the sensorimotor-auditory and association cortices, along the 'S-A' axis, was significantly positively correlated with postnatal age (PNA), and negatively correlated with gestational age (GA), respectively. Meanwhile, the BEN in the right rolandic operculum correlated significantly with both GA and PNA. Preterm-born infants exhibited increased BEN values in widespread cortical areas, particularly in the visual-motor cortex, when compared to term-born infants. Moreover, we identified five BEN-related genes (DNAJC12, FIG4, STX12, CETN2, and IRF2BP2), which were involved in protein folding, synaptic vesicle transportation and cell division. These findings suggest that the fMRI-based BEN can serve as an indicator of age-dependent brain functional development in human neonates, which may be influenced by specific genes.
Collapse
Affiliation(s)
- Zhiyong Zhao
- Department of Radiology, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, China
| | - Yifan Shuai
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China
| | - Yihan Wu
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Xinyi Xu
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China
| | - Mingyang Li
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China
| | - Dan Wu
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China.
| |
Collapse
|
2
|
Del Mauro G, Sevel LS, Boissoneault J, Wang Z. Divergent association between pain intensity and resting-state fMRI-based brain entropy in different age groups. J Neurosci Res 2024; 102:e25341. [PMID: 38751218 PMCID: PMC11154588 DOI: 10.1002/jnr.25341] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2024] [Revised: 04/24/2024] [Accepted: 04/27/2024] [Indexed: 06/11/2024]
Abstract
Pain is a multidimensional subjective experience sustained by multiple brain regions involved in different aspects of pain experience. We used brain entropy (BEN) estimated from resting-state fMRI (rsfMRI) data to investigate the neural correlates of pain experience. BEN was estimated from rs-fMRI data provided by two datasets with different age range: the Human Connectome Project-Young Adult (HCP-YA) and the Human Connectome project-Aging (HCP-A) datasets. Retrospective assessment of experienced pain intensity was retrieved from both datasets. No main effect of pain intensity was observed. The interaction between pain and age, however, was related to increased BEN in several pain-related brain regions, reflecting greater variability of spontaneous brain activity. Dividing the sample into a young adult group (YG) and a middle age-aging group (MAG) resulted in two divergent patterns of pain-BEN association: In the YG, pain intensity was related to reduced BEN in brain regions involved in the sensory processing of pain; in the MAG, pain was associated with increased BEN in areas related to both sensory and cognitive aspects of pain experience.
Collapse
Affiliation(s)
- Gianpaolo Del Mauro
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Landrew Samuel Sevel
- Department of Anesthesiology, University of Minnesota, Minneapolis, Minnesota, USA
| | - Jeff Boissoneault
- Department of Anesthesiology, University of Minnesota, Minneapolis, Minnesota, USA
| | - Ze Wang
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, Maryland, USA
| |
Collapse
|
3
|
Del Mauro G, Wang Z. Associations of Brain Entropy Estimated by Resting State fMRI With Physiological Indices, Body Mass Index, and Cognition. J Magn Reson Imaging 2024; 59:1697-1707. [PMID: 37578314 PMCID: PMC10864678 DOI: 10.1002/jmri.28948] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2023] [Revised: 07/27/2023] [Accepted: 07/28/2023] [Indexed: 08/15/2023] Open
Abstract
BACKGROUND In recent years, resting-state fMRI (rsfMRI)-based brain entropy (BEN) has gained increasing interest as a tool to characterize brain activity. While previous studies indicate that BEN is correlated with cognition, it remains unclear whether BEN is influenced by other factors that typically affect brain activity measured by fMRI. PURPOSE To investigate the relationship between BEN and physiological indices, including respiratory rate (RR), heart rate (HR), systolic blood pressure (s-BP), and body mass index (BMI), and to investigate whether and to what extent the relationship between BEN and cognition is influenced by physiological variables. STUDY TYPE Retrospective. SUBJECTS One thousand two hundred six healthy subjects (mean age: 28.83 ± 3.69 years; 550 male) with rsfMRI datasets selected from the Human Connectome Project (HCP). FIELD STRENGTH/SEQUENCE Multiband echo planar imaging (EPI) sequence at 3.0 Tesla. ASSESSMENT Neurocognitive, physical health (RR, HR, s-BP, BMI), and rsfMRI data were retrieved from the HCP datasets. Neurocognition was measured through the total cognition composite (TCC) score provided by HCP. BEN maps were calculated from rsfMRI data. STATISTICAL TESTS Multiple regression models, pheight-family wise error (FWE) < 0.05 and pcluster-FWE < 0.05 were considered statistically significant. RESULTS BEN was negatively associated with RR (T-thresholds ranging from 4.75 to 4.8; r-threshold = |0.15|) and positively associated with s-BP and BMI (T-thresholds ranging from 4.75 to 4.8; r-threshold = |0.15|) in areas overlapping with the default mode network. After controlling the physiological effects, BEN still showed regional associations with TCC, including negative associations (T-thresholds = 3.09; r-threshold = |0.1|) in the fronto-parietal cortex and positive associations (T-thresholds = 3.09; r-threshold = |0.1|) in the sensorimotor system (motor network and the limbic system). DATA CONCLUSIONS RR negatively affects rsfMRI-derived BEN, while s-BP and BMI positively affect BEN. The positive associations between BEN and cognition in the motor network and the limbic system might indicate a facilitation of information processing in the sensorimotor system. EVIDENCE LEVEL 3 TECHNICAL EFFICACY: Stage 3.
Collapse
Affiliation(s)
- Gianpaolo Del Mauro
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Ze Wang
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, Maryland, USA
| |
Collapse
|
4
|
Xin X, Yu J, Gao X. The brain entropy dynamics in resting state. Front Neurosci 2024; 18:1352409. [PMID: 38595975 PMCID: PMC11002175 DOI: 10.3389/fnins.2024.1352409] [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: 12/08/2023] [Accepted: 03/08/2024] [Indexed: 04/11/2024] Open
Abstract
As a novel measure for irregularity and complexity of the spontaneous fluctuations of brain activities, brain entropy (BEN) has attracted much attention in resting-state functional magnetic resonance imaging (rs-fMRI) studies during the last decade. Previous studies have shown its associations with cognitive and mental functions. While most previous research assumes BEN is approximately stationary during scan sessions, the brain, even at its resting state, is a highly dynamic system. Such dynamics could be characterized by a series of reoccurring whole-brain patterns related to cognitive and mental processes. The present study aims to explore the time-varying feature of BEN and its potential links with general cognitive ability. We adopted a sliding window approach to derive the dynamical brain entropy (dBEN) of the whole-brain functional networks from the HCP (Human Connectome Project) rs-fMRI dataset that includes 812 young healthy adults. The dBEN was further clustered into 4 reoccurring BEN states by the k-means clustering method. The fraction window (FW) and mean dwell time (MDT) of one BEN state, characterized by the extremely low overall BEN, were found to be negatively correlated with general cognitive abilities (i.e., cognitive flexibility, inhibitory control, and processing speed). Another BEN state, characterized by intermediate overall BEN and low within-state BEN located in DMN, ECN, and part of SAN, its FW, and MDT were positively correlated with the above cognitive abilities. The results of our study advance our understanding of the underlying mechanism of BEN dynamics and provide a potential framework for future investigations in clinical populations.
Collapse
Affiliation(s)
- Xiaoyang Xin
- Center for Psychological Sciences, Zhejiang University, Hangzhou, China
- Preschool College, Luoyang Normal University, Luoyang, China
| | - Jiaqian Yu
- Center for Psychological Sciences, Zhejiang University, Hangzhou, China
| | - Xiaoqing Gao
- Center for Psychological Sciences, Zhejiang University, Hangzhou, China
| |
Collapse
|
5
|
Yu X, Chen K, Ma Y, Bai T, Zhu S, Cai D, Zhang X, Wang K, Tian Y, Wang J. Molecular basis underlying changes of brain entropy and functional connectivity in major depressive disorders after electroconvulsive therapy. CNS Neurosci Ther 2024; 30:e14690. [PMID: 38529527 PMCID: PMC10964037 DOI: 10.1111/cns.14690] [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: 10/27/2023] [Revised: 02/03/2024] [Accepted: 02/23/2024] [Indexed: 03/27/2024] Open
Abstract
INTRODUCTION Electroconvulsive therapy (ECT) is widely used for treatment-resistant depression. However, it is unclear whether/how ECT can be targeted to affect brain regions and circuits in the brain to dynamically regulate mood and cognition. METHODS This study used brain entropy (BEN) to measure the irregular levels of brain systems in 46 major depressive disorder (MDD) patients before and after ECT treatment. Functional connectivity (FC) was further adopted to reveal changes of functional couplings. Moreover, transcriptomic and neurotransmitter receptor data were used to reveal genetic and molecular basis of the changes of BEN and functional connectivities. RESULTS Compared to pretreatment, the BEN in the posterior cerebellar lobe (PCL) significantly decreased and FC between the PCL and the right temporal pole (TP) significantly increased in MDD patients after treatment. Moreover, we found that these changes of BEN and FC were closely associated with genes' expression profiles involved in MAPK signaling pathway, GABAergic synapse, and dopaminergic synapse and were significantly correlated with the receptor/transporter density of 5-HT, norepinephrine, glutamate, etc. CONCLUSION: These findings suggest that loops in the cerebellum and TP are crucial for ECT regulation of mood and cognition, which provides new evidence for the antidepressant effects of ECT and the potential molecular mechanism leading to cognitive impairment.
Collapse
Affiliation(s)
- Xiaohui Yu
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational MedicineKunming University of Science and TechnologyKunmingChina
- Yunnan Key Laboratory of Primate Biomedical ResearchKunmingChina
| | - Kexuan Chen
- Medical SchoolKunming University of Science and TechnologyKunmingChina
| | - Yingzi Ma
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational MedicineKunming University of Science and TechnologyKunmingChina
- Yunnan Key Laboratory of Primate Biomedical ResearchKunmingChina
| | - Tongjian Bai
- Department of NeurologyThe First Hospital of Anhui Medical UniversityHefeiChina
| | - Shunli Zhu
- School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduChina
| | - Defang Cai
- The Second People's Hospital of YuxiThe Affiliated Hospital of Kunming University of Science and TechnologyYuxiChina
| | - Xing Zhang
- The Second People's Hospital of YuxiThe Affiliated Hospital of Kunming University of Science and TechnologyYuxiChina
| | - Kai Wang
- Department of NeurologyThe First Hospital of Anhui Medical UniversityHefeiChina
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric DisordersHefeiChina
- School of Mental Health and Psychological SciencesAnhui Medical UniversityHefeiChina
- Collaborative Innovation Center of Neuropsychiatric Disorders and Mental HealthHefeiChina
- Anhui Province Clinical Research Center for Neurological DiseaseHefeiChina
| | - Yanghua Tian
- Department of NeurologyThe First Hospital of Anhui Medical UniversityHefeiChina
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric DisordersHefeiChina
- School of Mental Health and Psychological SciencesAnhui Medical UniversityHefeiChina
- Collaborative Innovation Center of Neuropsychiatric Disorders and Mental HealthHefeiChina
- Anhui Province Clinical Research Center for Neurological DiseaseHefeiChina
- Institute of Artificial IntelligenceHefei Comprehensive National Science CenterHefeiChina
| | - Jiaojian Wang
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational MedicineKunming University of Science and TechnologyKunmingChina
- Yunnan Key Laboratory of Primate Biomedical ResearchKunmingChina
| |
Collapse
|
6
|
Camargo A, Del Mauro G, Wang Z. Task-induced changes in brain entropy. J Neurosci Res 2024; 102:e25310. [PMID: 38400553 PMCID: PMC10947426 DOI: 10.1002/jnr.25310] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2023] [Revised: 12/21/2023] [Accepted: 02/09/2024] [Indexed: 02/25/2024]
Abstract
Entropy indicates irregularity of a dynamic system, with higher entropy indicating higher irregularity and more transit states. In the human brain, regional brain entropy (BEN) has been increasingly assessed using resting state fMRI (rs-fMRI), while changes of regional BEN during task-based fMRI have been scarcely studied. The purpose of this study is to characterize task-induced regional BEN alterations using the large Human Connectome Project (HCP) data. To control the potential modulation by the block design, BEN of task-fMRI was calculated from the fMRI images acquired during the task conditions only (task BEN) and then compared to BEN of rs-fMRI (resting BEN). Moreover, BEN was separately calculated from the control blocks of the task-fMRI runs (control BEN) and compared to task BEN. Finally, control BEN was compared to resting BEN to test for residual task effects in the control condition. With respect to resting state, task performance unanimously induced BEN reduction in the peripheral cortical area and BEN increase in the centric part of the sensorimotor and perception networks. Control compared to resting BEN showed similar entropy alterations, suggesting large residual task effects. Task compared to control BEN was characterized by reduced entropy in occipital, orbitofrontal, and parietal regions.
Collapse
Affiliation(s)
- Aldo Camargo
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine
| | - Gianpaolo Del Mauro
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine
| | - Ze Wang
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine
| |
Collapse
|
7
|
Jordan T, Apostol MR, Nomi J, Petersen N. Unraveling Neural Complexity: Exploring Brain Entropy to Yield Mechanistic Insight in Neuromodulation Therapies for Tobacco Use Disorder. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.12.557465. [PMID: 37745351 PMCID: PMC10515846 DOI: 10.1101/2023.09.12.557465] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/26/2023]
Abstract
Neuromodulation therapies, such as repetitive transcranial magnetic stimulation (rTMS), have shown promise as treatments for tobacco use disorder (TUD). However, the underlying mechanisms of these therapies remain unclear, which may hamper optimization and personalization efforts. In this study, we investigated alteration of brain entropy as a potential mechanism underlying the neural effects of noninvasive brain stimulation by rTMS in people with TUD. We employed sample entropy (SampEn) to quantify the complexity and predictability of brain activity measured using resting-state fMRI data. Our study design included a randomized single-blind study with 42 participants who underwent 2 data collection sessions. During each session, participants received high-frequency (10Hz) stimulation to the dorsolateral prefrontal cortex (dlPFC) or a control region (visual cortex), and resting-state fMRI scans were acquired before and after rTMS. Our findings revealed that individuals who smoke exhibited higher baseline SampEn throughout the brain as compared to previously-published SampEn measurements in control participants. Furthermore, high-frequency rTMS to the dlPFC but not the control region reduced SampEn in the insula and dlPFC, regions implicated in TUD, and also reduced self-reported cigarette craving. These results suggest that brain entropy may serve as a potential biomarker for effects of rTMS, and provide insight into the neural mechanisms underlying rTMS effects on smoking cessation. Our study contributes to the growing understanding of brain-based interventions for TUD by highlighting the relevance of brain entropy in characterizing neural activity patterns associated with smoking. The observed reductions in entropy following dlPFC-targeted rTMS suggest a potential mechanism for the therapeutic effects of this intervention. These findings support the use of neuroimaging techniques to investigate the use of neuromodulation therapies for TUD.
Collapse
Affiliation(s)
- Timothy Jordan
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, UCLA, Los Angeles CA
| | - Michael R. Apostol
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, UCLA, Los Angeles CA
| | - Jason Nomi
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, UCLA, Los Angeles CA
| | - Nicole Petersen
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, UCLA, Los Angeles CA
| |
Collapse
|
8
|
Liu H, Gao W, Cao W, Meng Q, Xu L, Kuang L, Guo Y, Cui D, Qiu J, Jiao Q, Su L, Lu G. Immediate visual reproduction negatively correlates with brain entropy of parahippocampal gyrus and inferior occipital gyrus in bipolar II disorder adolescents. BMC Psychiatry 2023; 23:515. [PMID: 37464363 DOI: 10.1186/s12888-023-05012-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/04/2023] [Accepted: 07/07/2023] [Indexed: 07/20/2023] Open
Abstract
BACKGROUND Brain entropy reveals complexity and irregularity of brain, and it has been proven to reflect brain complexity alteration in disease states. Previous studies found that bipolar disorder adolescents showed cognitive impairment. The relationship between complexity of brain neural activity and cognition of bipolar II disorder (BD-II) adolescents remains unclear. METHODS Nineteen BD-II patients (14.63 ±1.57 years old) and seventeen age-gender matched healthy controls (HCs) (14.18 ± 1.51 years old) were enlisted. Entropy values of all voxels of the brain in resting-state functional MRI data were calculated and differences of them between BD-II and HC groups were evaluated. After that, correlation analyses were performed between entropy values of brain regions showing significant entropy differences and clinical indices in BD-II adolescents. RESULTS Significant differences were found in scores of immediate visual reproduction subtest (VR-I, p = 0.003) and Stroop color-word test (SCWT-1, p = 0.015; SCWT-2, p = 0.004; SCWT-3, p = 0.003) between the two groups. Compared with HCs, BD-II adolescents showed significant increased brain entropy in right parahippocampal gyrus and right inferior occipital gyrus. Besides, significant negative correlations between brain entropy values of right parahippocampal gyrus, right inferior occipital gyrus and immediate visual reproduction subtest scores were observed in BD-II adolescents. CONCLUSIONS The findings of the present study suggested that the disrupted function of corticolimbic system is related with cognitive abnormality of BD-II adolescents. And from the perspective temporal dynamics of brain system, the current study, brain entropy may provide available evidences for understanding the underlying neural mechanism in BD-II adolescents.
Collapse
Affiliation(s)
- Haiqin Liu
- Department of Radiology, The Second Affiliated Hospital of Shandong First Medical University, Tai'an, China
- School of Radiology, Shandong First Medical University & Shandong Academy of Medical Sciences, Tai'an, China
| | - Weijia Gao
- Department of Child Psychology, The Children' s Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Weifang Cao
- School of Radiology, Shandong First Medical University & Shandong Academy of Medical Sciences, Tai'an, China
| | - Qingmin Meng
- Department of interventional radiology, Taian Central Hospital, Tai'an, China
| | - Longchun Xu
- Department of Radiology, The Second Affiliated Hospital of Shandong First Medical University, Tai'an, China
| | - Liangfeng Kuang
- School of Radiology, Shandong First Medical University & Shandong Academy of Medical Sciences, Tai'an, China
| | - Yongxin Guo
- School of Radiology, Shandong First Medical University & Shandong Academy of Medical Sciences, Tai'an, China
| | - Dong Cui
- School of Radiology, Shandong First Medical University & Shandong Academy of Medical Sciences, Tai'an, China
| | - Jianfeng Qiu
- School of Radiology, Shandong First Medical University & Shandong Academy of Medical Sciences, Tai'an, China
| | - Qing Jiao
- Department of Radiology, The Second Affiliated Hospital of Shandong First Medical University, Tai'an, China.
- School of Radiology, Shandong First Medical University & Shandong Academy of Medical Sciences, Tai'an, China.
| | - Linyan Su
- Key Laboratory of Psychiatry and Mental Health of Hunan Province, Mental Health Institute of the Second Xiangya Hospital, Central South University, Changsha, China
| | - Guangming Lu
- Department of Medical Imaging, Jinling Hospital, Clinical School of Medical College, Nanjing University, Nanjing, China
| |
Collapse
|
9
|
Fu S, Liang S, Lin C, Wu Y, Xie S, Li M, Lei Q, Li J, Yu K, Yin Y, Hua K, Li W, Wu C, Ma X, Jiang G. Aberrant brain entropy in posttraumatic stress disorder comorbid with major depressive disorder during the coronavirus disease 2019 pandemic. Front Psychiatry 2023; 14:1143780. [PMID: 37333934 PMCID: PMC10272369 DOI: 10.3389/fpsyt.2023.1143780] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Accepted: 05/09/2023] [Indexed: 06/20/2023] Open
Abstract
Aim Previously, neuroimaging studies on comorbid Posttraumatic-Major depression disorder (PTSD-MDD) comorbidity found abnormalities in multiple brain regions among patients. Recent neuroimaging studies have revealed dynamic nature on human brain activity during resting state, and entropy as an indicator of dynamic regularity may provide a new perspective for studying abnormalities of brain function among PTSD-MDD patients. During the COVID-19 pandemic, there has been a significant increase in the number of patients with PTSD-MDD. We have decided to conduct research on resting-state brain functional activity of patients who developed PTSD-MDD during this period using entropy. Methods Thirty three patients with PTSD-MDD and 36 matched TCs were recruited. PTSD and depression symptoms were assessed using multiple clinical scales. All subjects underwent functional magnetic resonance imaging (fMRI) scans. And the brain entropy (BEN) maps were calculated using the BEN mapping toolbox. A two-sample t-test was used to compare the differences in the brain entropy between the PTSD-MDD comorbidity group and TC group. Furthermore, correlation analysis was conducted between the BEN changes in patients with PTSD-MDD and clinical scales. Results Compared to the TCs, PTSD-MDD patients had a reduced BEN in the right middle frontal orbital gyrus (R_MFOG), left putamen, and right inferior frontal gyrus, opercular part (R_IFOG). Furthermore, a higher BEN in the R_MFOG was related to higher CAPS and HAMD-24 scores in the patients with PTSD-MDD. Conclusion The results showed that the R_MFOG is a potential marker for showing the symptom severity of PTSD-MDD comorbidity. Consequently, PTSD-MDD may have reduced BEN in frontal and basal ganglia regions which are related to emotional dysregulation and cognitive deficits.
Collapse
Affiliation(s)
- Shishun Fu
- The Department of Medical Imaging Guangdong Second Provincial General Hospital, Guangzhou, China
| | - Sipei Liang
- The Second School of Clinical Medicine, Southern Medical University, Guangzhou, China
| | - Chulan Lin
- The Department of Medical Imaging Guangdong Second Provincial General Hospital, Guangzhou, China
| | - Yunfan Wu
- The Department of Medical Imaging Guangdong Second Provincial General Hospital, Guangzhou, China
| | - Shuangcong Xie
- The Department of Medical Imaging Guangdong Second Provincial General Hospital, Guangzhou, China
| | - Meng Li
- The Department of Medical Imaging Guangdong Second Provincial General Hospital, Guangzhou, China
| | - Qiang Lei
- The Department of Medical Imaging Guangdong Second Provincial General Hospital, Guangzhou, China
| | - Jianneng Li
- The Department of Medical Imaging Guangdong Second Provincial General Hospital, Guangzhou, China
| | - Kanghui Yu
- The Department of Medical Imaging Guangdong Second Provincial General Hospital, Guangzhou, China
| | - Yi Yin
- The Department of Medical Imaging Guangdong Second Provincial General Hospital, Guangzhou, China
| | - Kelei Hua
- The Department of Medical Imaging Guangdong Second Provincial General Hospital, Guangzhou, China
| | - Wuming Li
- The Department of Medical Imaging Guangdong Second Provincial General Hospital, Guangzhou, China
| | - Caojun Wu
- The Second School of Clinical Medicine, Southern Medical University, Guangzhou, China
| | - Xiaofen Ma
- The Department of Nuclear Medicine, Guangdong Second Provincial General Hospital, Guangzhou, China
| | - Guihua Jiang
- The Department of Medical Imaging Guangdong Second Provincial General Hospital, Guangzhou, China
| |
Collapse
|
10
|
Cao X, Wang Z, Chen X, Liu Y, Abdoulaye IA, Ju S, Zhang S, Wu S, Wang Y, Guo Y. Changes in Resting-State Neural Activity and Nerve Fibres in Ischaemic Stroke Patients with Hemiplegia. Brain Topogr 2023; 36:255-268. [PMID: 36604349 DOI: 10.1007/s10548-022-00937-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2022] [Accepted: 12/30/2022] [Indexed: 01/07/2023]
Abstract
Many neuroimaging studies have reported that stroke induces abnormal brain activity. However, little is known about resting-state networks (RSNs) and the corresponding white matter changes in stroke patients with hemiplegia. Here, we utilized functional magnetic resonance imaging (fMRI) to measure neural activity and related fibre tracts in 14 ischaemic stroke patients with hemiplegia and 12 healthy controls. Fractional amplitude of low-frequency fluctuations (fALFF) calculation and correlation analyses were used to assess the relationship between regional neural activity and movement scores. Tractography was performed using diffusion tensor imaging (DTI) data to analyse the fibres passing through the regions of interest. Compared with controls, stroke patients showed abnormal functional connectivity (FC) between some brain regions in the RSNs. The fALFF was increased in the contralesional parietal lobe, with the regional fALFF being correlated with behavioural scores in stroke patients. Additionally, the passage of fibres across regions with reduced FC in the RSNs was increased in stroke patients. This study suggests that structural remodelling of functionally relevant white matter tracts is probably an adaptive response that compensates for injury to the brain.
Collapse
Affiliation(s)
- Xuejin Cao
- Department of Neurology, Affiliated ZhongDa Hospital of Southeast University, Medical School of Southeast University, Nanjing, China
| | - Zan Wang
- Department of Neurology, Affiliated ZhongDa Hospital of Southeast University, Medical School of Southeast University, Nanjing, China
| | - Xiaohui Chen
- Department of Radiology, Affiliated ZhongDa Hospital of Southeast University, Jiangsu Key Laboratory of Molecular and Functional Imaging, Medical School of Southeast University, Nanjing, China
| | - Yanli Liu
- Department of Rehabilitation, Affiliated ZhongDa Hospital of Southeast University, Nanjing, China
| | - Idriss Ali Abdoulaye
- Department of Neurology, Affiliated ZhongDa Hospital of Southeast University, Medical School of Southeast University, Nanjing, China
| | - Shenghong Ju
- Department of Radiology, Affiliated ZhongDa Hospital of Southeast University, Jiangsu Key Laboratory of Molecular and Functional Imaging, Medical School of Southeast University, Nanjing, China
| | - Shiyao Zhang
- Department of Neurology, Affiliated ZhongDa Hospital of Southeast University, Medical School of Southeast University, Nanjing, China
| | - Shanshan Wu
- Department of Neurology, Affiliated ZhongDa Hospital of Southeast University, Medical School of Southeast University, Nanjing, China
| | - Yuancheng Wang
- Department of Radiology, Affiliated ZhongDa Hospital of Southeast University, Jiangsu Key Laboratory of Molecular and Functional Imaging, Medical School of Southeast University, Nanjing, China
| | - Yijing Guo
- Department of Neurology, Affiliated ZhongDa Hospital of Southeast University, Medical School of Southeast University, Nanjing, China. .,Department of Neurology, Affiliated ZhongDa Hospital of Southeast University, Medical School of Southeast University, Nanjing, 210009, Jiangsu Province, China.
| |
Collapse
|
11
|
Déli É, Peters JF, Kisvárday Z. How the Brain Becomes the Mind: Can Thermodynamics Explain the Emergence and Nature of Emotions? ENTROPY (BASEL, SWITZERLAND) 2022; 24:1498. [PMID: 37420518 DOI: 10.3390/e24101498] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/27/2022] [Revised: 10/07/2022] [Accepted: 10/11/2022] [Indexed: 07/09/2023]
Abstract
The neural systems' electric activities are fundamental for the phenomenology of consciousness. Sensory perception triggers an information/energy exchange with the environment, but the brain's recurrent activations maintain a resting state with constant parameters. Therefore, perception forms a closed thermodynamic cycle. In physics, the Carnot engine is an ideal thermodynamic cycle that converts heat from a hot reservoir into work, or inversely, requires work to transfer heat from a low- to a high-temperature reservoir (the reversed Carnot cycle). We analyze the high entropy brain by the endothermic reversed Carnot cycle. Its irreversible activations provide temporal directionality for future orientation. A flexible transfer between neural states inspires openness and creativity. In contrast, the low entropy resting state parallels reversible activations, which impose past focus via repetitive thinking, remorse, and regret. The exothermic Carnot cycle degrades mental energy. Therefore, the brain's energy/information balance formulates motivation, sensed as position or negative emotions. Our work provides an analytical perspective of positive and negative emotions and spontaneous behavior from the free energy principle. Furthermore, electrical activities, thoughts, and beliefs lend themselves to a temporal organization, an orthogonal condition to physical systems. Here, we suggest that an experimental validation of the thermodynamic origin of emotions might inspire better treatment options for mental diseases.
Collapse
Affiliation(s)
- Éva Déli
- Department of Anatomy, Histology, and Embryology, University of Debrecen, 4032 Debrecen, Hungary
| | - James F Peters
- Department of Electrical & Computer Engineering, University of Manitoba, Winnipeg, MB R3T 2N2, Canada
- Department of Mathematics, Adiyaman University, Adiyaman 02040, Turkey
| | - Zoltán Kisvárday
- Department of Anatomy, Histology, and Embryology, University of Debrecen, 4032 Debrecen, Hungary
- ELKH Neuroscience Research Group, University of Debrecen, 4032 Debrecen, Hungary
| |
Collapse
|
12
|
Li T, Pei Z, Zhu Z, Wu X, Feng C. Intrinsic brain activity patterns across large-scale networks predict reciprocity propensity. Hum Brain Mapp 2022; 43:5616-5629. [PMID: 36054523 PMCID: PMC9704792 DOI: 10.1002/hbm.26038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Revised: 06/06/2022] [Accepted: 07/25/2022] [Indexed: 01/15/2023] Open
Abstract
Reciprocity is prevalent across human societies, but individuals are heterogeneous regarding their reciprocity propensity. Although a large body of task-based brain imaging measures has shed light on the neural underpinnings of reciprocity at group level, the neural basis underlying the individual differences in reciprocity propensity remains largely unclear. Here, we combined brain imaging and machine learning techniques to individually predict reciprocity propensity from resting-state brain activity measured by fractional amplitude of low-frequency fluctuation. The brain regions contributing to the prediction were then analyzed for functional connectivity and decoding analyses, allowing for a data-driven quantitative inference on psychophysiological functions. Our results indicated that patterns of resting-state brain activity across multiple brain systems were capable of predicting individual reciprocity propensity, with the contributing regions distributed across the salience (e.g., ventrolateral prefrontal cortex), fronto-parietal (e.g., dorsolateral prefrontal cortex), default mode (e.g., ventromedial prefrontal cortex), and sensorimotor (e.g., supplementary motor area) networks. Those contributing brain networks are implicated in emotion and cognitive control, mentalizing, and motor-based processes, respectively. Collectively, these findings provide novel evidence on the neural signatures underlying the individual differences in reciprocity, and lend support the assertion that reciprocity emerges from interactions among regions embodied in multiple large-scale brain networks.
Collapse
Affiliation(s)
- Ting Li
- Key Laboratory of Brain, Cognition and Education Sciences (South China Normal University)Ministry of EducationGuangzhouChina,School of Psychology, Institute of Brain Research and Rehabilitation (IBRR), Center for Studies of Psychological Application, and Guangdong Key Laboratory of Mental Health and Cognitive ScienceSouth China Normal UniversityGuangzhouChina,Institute of Brain and Psychological SciencesSichuan Normal UniversityChengduChina
| | - Zhaodi Pei
- School of Artificial IntelligenceBeijing Normal UniversityBeijingChina,Engineering Research Center of Intelligent Technology and Educational Application of Ministry of EducationBeijing Normal UniversityBeijingChina
| | - Zhiyuan Zhu
- School of Artificial IntelligenceBeijing Normal UniversityBeijingChina,Engineering Research Center of Intelligent Technology and Educational Application of Ministry of EducationBeijing Normal UniversityBeijingChina
| | - Xia Wu
- School of Artificial IntelligenceBeijing Normal UniversityBeijingChina,Engineering Research Center of Intelligent Technology and Educational Application of Ministry of EducationBeijing Normal UniversityBeijingChina
| | - Chunliang Feng
- Key Laboratory of Brain, Cognition and Education Sciences (South China Normal University)Ministry of EducationGuangzhouChina,School of Psychology, Institute of Brain Research and Rehabilitation (IBRR), Center for Studies of Psychological Application, and Guangdong Key Laboratory of Mental Health and Cognitive ScienceSouth China Normal UniversityGuangzhouChina
| |
Collapse
|
13
|
Bansal IR, Ashourvan A, Bertolero M, Bassett DS, Pequito S. Model-based stationarity filtering of long-term memory data applied to resting-state blood-oxygen-level-dependent signal. PLoS One 2022; 17:e0268752. [PMID: 35895686 PMCID: PMC9328502 DOI: 10.1371/journal.pone.0268752] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2021] [Accepted: 05/05/2022] [Indexed: 11/18/2022] Open
Abstract
Resting-state blood-oxygen-level-dependent (BOLD) signal acquired through functional magnetic resonance imaging is a proxy of neural activity and a key mechanism for assessing neurological conditions. Therefore, practical tools to filter out artefacts that can compromise the assessment are required. On the one hand, a variety of tailored methods to preprocess the data to deal with identified sources of noise (e.g., head motion, heart beating, and breathing, just to mention a few) are in place. But, on the other hand, there might be unknown sources of unstructured noise present in the data. Therefore, to mitigate the effects of such unstructured noises, we propose a model-based filter that explores the statistical properties of the underlying signal (i.e., long-term memory). Specifically, we consider autoregressive fractional integrative process filters. Remarkably, we provide evidence that such processes can model the signals at different regions of interest to attain stationarity. Furthermore, we use a principled analysis where a ground-truth signal with statistical properties similar to the BOLD signal under the injection of noise is retrieved using the proposed filters. Next, we considered preprocessed (i.e., the identified sources of noise removed) resting-state BOLD data of 98 subjects from the Human Connectome Project. Our results demonstrate that the proposed filters decrease the power in the higher frequencies. However, unlike the low-pass filters, the proposed filters do not remove all high-frequency information, instead they preserve process-related higher frequency information. Additionally, we considered four different metrics (power spectrum, functional connectivity using the Pearson’s correlation, coherence, and eigenbrains) to infer the impact of such filter. We provided evidence that whereas the first three keep most of the features of interest from a neuroscience perspective unchanged, the latter exhibits some variations that could be due to the sporadic activity filtered out.
Collapse
Affiliation(s)
- Ishita Rai Bansal
- Delft Centre for Systems and Control, Delft University of Technology, Delft, Netherlands
| | - Arian Ashourvan
- Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA, United States of America
- Penn Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, PA, United States of America
| | - Maxwell Bertolero
- Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA, United States of America
| | - Danielle S. Bassett
- Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA, United States of America
- Penn Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, PA, United States of America
- Department of Neurology, Hospital of the University of Pennsylvania, Pennsylvania, United States of America
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States of America
- Department of Electrical & Systems Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA, United States of America
- Department of Physics & Astronomy, College of Arts and Sciences, University of Pennsylvania, Philadelphia, PA, United States of America
| | - Sérgio Pequito
- Delft Centre for Systems and Control, Delft University of Technology, Delft, Netherlands
- * E-mail:
| |
Collapse
|
14
|
Tian N, Liang L, Luo X, Hu R, Long W, Song R. More than just statics: Altered complexity of dynamic amplitude of low-frequency fluctuations in the resting brain after stroke. J Neural Eng 2022; 19. [PMID: 35594839 DOI: 10.1088/1741-2552/ac71ce] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2022] [Accepted: 05/20/2022] [Indexed: 11/12/2022]
Abstract
OBJECTIVE Previous neuroimaging studies mainly focused on static characteristics of brain activity, and little is known about its characteristics over time, especially in post-stroke (PS) patients. In this study, we aimed to investigate the static and dynamic characteristics of brain activity after stroke using functional magnetic resonance imaging (fMRI). APPROACH Twenty ischemic PS patients and nineteen healthy controls (HCs) were recruited to receive a resting-state fMRI scanning. The static amplitude of low-frequency fluctuations (sALFF) and fuzzy entropy of dynamic ALFF (FE-dALFF) were applied to identify the stroke-induced alterations. MAIN RESULTS Compared with the HCs, PS patients showed significantly increased FE-dALFF values in the right angular gyrus (ANG), bilateral precuneus (PCUN), and right inferior parietal lobule (IPL) as well as significantly decreased FE-dALFF values in the right postcentral gyrus (PoCG), right dorsolateral superior frontal gyrus (SFGdor), and right precentral gyrus (PreCG). The ROC analyses demonstrated that FE-dALFF and sALFF possess comparable sensitivity in distinguishing PS patients from the HCs. Moreover, a significantly positive correlation was observed between the FE-dALFF values and the Fugl-Meyer Assessment (FMA) scores in the right SFGdor (r =0.547), right IPL (r =0.522), and right PCUN (r =0.486). SIGNIFICANCE This study provided insight into the stroke-induced alterations in static and dynamic characteristics of local brain activity, highlighting the potential of FE-dALFF in understanding neurophysiological mechanisms and evaluating pathological changes.
Collapse
Affiliation(s)
- Na Tian
- Sun Yat-Sen University, Higher Mega Education Center, Guangzhou, Guangdong, 510006, CHINA
| | - Liuke Liang
- School of Biomedical Engineering, Sun Yat-Sen University, Higher Mega Education Center, Guangzhou, Guangdong, 510006, CHINA
| | - Xuemao Luo
- Department of Radiology, Jiangmen Central Hospital, Jiangmen, Guangdong, CN, Jiangmen, Guangdong, 529030, CHINA
| | - Rongliang Hu
- Department of Rehabilitation Medicine, Jiangmen Central Hospital, Jiangmen, Guangdong, CN, Jiangmen, Guangdong, 529030, CHINA
| | - Wansheng Long
- Department of Radiology, Jiangmen Central Hospital, Jiangmen, Guangdong, CN, Jiangmen, Guangdong, 529030, CHINA
| | - Rong Song
- Biomedical Engineering, National Sun Yat-sen University, Higher Mega Education Center, Guangzhou, 510006, CHINA
| |
Collapse
|
15
|
Lower resting brain entropy is associated with stronger task activation and deactivation. Neuroimage 2022; 249:118875. [PMID: 34998971 DOI: 10.1016/j.neuroimage.2022.118875] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2021] [Revised: 12/15/2021] [Accepted: 01/04/2022] [Indexed: 01/21/2023] Open
Abstract
Brain entropy (BEN) calculated from resting state fMRI has been the subject of increasing research interest in recent years. Previous studies have shown the correlations between rest BEN and neurocognition and task performance, but how this relates to task-evoked brain activations and deactivations remains unknown. The purpose of this study is to address this open question using large data (n = 862). Voxel wise correlations were calculated between rest BEN and task activations/deactivations of five different tasks. For most of the assessed tasks, lower rest BEN was found to be associated with stronger activations (negative correlations) and stronger deactivations (positive correlations) only in brain regions activated or deactivated by the tasks. Higher workload evoked spatially more extended negative correlations between rest BEN and task activations. These results not only confirm that resting brain activity can predict brain activity during task performance but also for the first time show that resting brain activity may facilitate both task activations and deactivations. In addition, the results provide a clue to understanding the individual differences of task performance and brain activations.
Collapse
|
16
|
Kuang L, Gao W, Wang L, Guo Y, Cao W, Cui D, Jiao Q, Qiu J, Su L, Lu G. Increased resting-state brain entropy of parahippocampal gyrus and dorsolateral prefrontal cortex in manic and euthymic adolescent bipolar disorder. J Psychiatr Res 2021; 143:106-112. [PMID: 34479001 DOI: 10.1016/j.jpsychires.2021.08.025] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/22/2021] [Revised: 06/01/2021] [Accepted: 08/17/2021] [Indexed: 11/26/2022]
Abstract
BACKGROUND Alterations of brain signal complexity may reflect brain functional abnormalities. In adolescent bipolar disorder (ABD) distribution of brain regions showing abnormal complexity in different mood states remains unclear. We aimed to analyze brain entropy (BEN) alteration of functional magnetic resonance imaging (fMRI) signal to observe spatial distribution of complexity in ABD patients, as well as the relationship between this variation and clinical variables. METHODS Resting-state fMRI data were acquired from adolescents with bipolar disorder (BD) who were in manic (n = 19) and euthymic (n = 20) states, and from healthy controls (HCs, n = 17). The differences in BEN among the three groups, and their associations with clinical variables, were examined. RESULTS Compared to HCs, manic and euthymic ABD patients showed increased BEN in right parahippocampal gyrus (PHG) and left dorsolateral prefrontal cortex (DLPFC). There was no significant difference of BEN between the manic and the euthymic ABD groups. In manic ABD patients, right PHG BEN exhibited significantly positive relationship with episode times. CONCLUSIONS Increased BEN in right PHG and left DLPFC in ABD patients may cause dysfunction of corticolimbic circuitry which is important to emotional processing and cognitive control. The positive correlation between PHG BEN and episode times of manic ABD patients further expressed a close association between brain complexity and clinical symptoms. From the perspective of brain temporal dynamics, the present study complements previous findings that have reported corticolimbic dysfunction as an important contributor to the pathophysiology of BD. BEN may provide valuable evidences for understanding the underlying mechanism of ABD.
Collapse
Affiliation(s)
- Liangfeng Kuang
- Department of Radiology, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, China
| | - Weijia Gao
- Department of Child Psychology, The Children's Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Luoyu Wang
- Institute of Psychological Sciences, Hangzhou Normal University, Hangzhou, China; Department of Radiology, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Yongxin Guo
- Department of Radiology, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, China
| | - Weifang Cao
- Department of Radiology, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, China
| | - Dong Cui
- Department of Radiology, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, China
| | - Qing Jiao
- Department of Radiology, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, China.
| | - Jianfeng Qiu
- Department of Radiology, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, China
| | - Linyan Su
- Mental Health Institute of the Second Xiangya Hospital, Key Laboratory of Psychiatry and Mental Health of Hunan Province, Central South University, Changsha, China
| | - Guangming Lu
- Department of Medical Imaging, Jinling Hospital, Clinical School of Medical College, Nanjing University, Nanjing, China
| |
Collapse
|
17
|
Xin X, Long S, Sun M, Gao X. The Application of Complexity Analysis in Brain Blood-Oxygen Signal. Brain Sci 2021; 11:brainsci11111415. [PMID: 34827414 PMCID: PMC8615802 DOI: 10.3390/brainsci11111415] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2021] [Revised: 10/22/2021] [Accepted: 10/25/2021] [Indexed: 11/17/2022] Open
Abstract
One of the daunting features of the brain is its physiology complexity, which arises from the interaction of numerous neuronal circuits that operate over a wide range of temporal and spatial scales, enabling the brain to adapt to the constantly changing environment and to perform various cognitive functions. As a reflection of the complexity of brain physiology, the complexity of brain blood-oxygen signal has been frequently studied in recent years. This paper reviews previous literature regarding the following three aspects: (1) whether the complexity of the brain blood-oxygen signal can serve as a reliable biomarker for distinguishing different patient populations; (2) which is the best algorithm for complexity measure? And (3) how to select the optimal parameters for complexity measures. We then discuss future directions for blood-oxygen signal complexity analysis, including improving complexity measurement based on the characteristics of both spatial patterns of brain blood-oxygen signal and latency of complexity itself. In conclusion, the current review helps to better understand complexity analysis in brain blood-oxygen signal analysis and provide useful information for future studies.
Collapse
|
18
|
Zhang S, Spoletini LJ, Gold BP, Morgan VL, Rogers BP, Chang C. Interindividual Signatures of fMRI Temporal Fluctuations. Cereb Cortex 2021; 31:4450-4463. [PMID: 33903915 PMCID: PMC8408464 DOI: 10.1093/cercor/bhab099] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2020] [Revised: 02/28/2021] [Accepted: 03/26/2021] [Indexed: 11/13/2022] Open
Abstract
The complexity and variability of human brain activity, such as quantified from Functional Magnetic Resonance Imaging (fMRI) time series, have been widely studied as potential markers of healthy and pathological states. However, the extent to which fMRI temporal features exhibit stable markers of inter-individual differences in brain function across healthy young adults is currently an open question. In this study, we draw upon two widely used time-series measures-a nonlinear complexity measure (sample entropy; SampEn) and a spectral measure of low-frequency content (fALFF)-to capture dynamic properties of resting-state fMRI in a large sample of young adults from the Human Connectome Project. We observe that these two measures are closely related, and that both generate reproducible patterns across brain regions over four different fMRI runs, with intra-class correlations of up to 0.8. Moreover, we find that both metrics can uniquely differentiate subjects with high identification rates (ca. 89%). Canonical correlation analysis revealed a significant relationship between multivariate brain temporal features and behavioral measures. Overall, these findings suggest that regional profiles of fMRI temporal characteristics may provide stable markers of individual differences, and motivate future studies to further probe relationships between fMRI time series metrics and behavior.
Collapse
Affiliation(s)
- Shengchao Zhang
- Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN 37212, USA
| | - Liam J Spoletini
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37212, USA
| | - Benjamin P Gold
- Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN 37212, USA
- Vanderbilt University, Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN 37212, USA
| | - Victoria L Morgan
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37212, USA
- Vanderbilt University, Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN 37212, USA
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN 37212, USA
| | - Baxter P Rogers
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37212, USA
- Vanderbilt University, Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN 37212, USA
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN 37212, USA
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN 37212, USA
| | - Catie Chang
- Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN 37212, USA
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37212, USA
- Vanderbilt University, Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN 37212, USA
| |
Collapse
|
19
|
Wang Z. The neurocognitive correlates of brain entropy estimated by resting state fMRI. Neuroimage 2021; 232:117893. [PMID: 33621695 PMCID: PMC8138544 DOI: 10.1016/j.neuroimage.2021.117893] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2020] [Revised: 02/02/2021] [Accepted: 02/16/2021] [Indexed: 11/17/2022] Open
Abstract
Resting state brain activity consumes most of brain energy, likely creating and maintaining a reserve of general brain functionality. The latent reserve if it exists may be reflected by the profound long-range fluctuations of resting brain activity. The long-range temporal coherence (LRTC) can be characterized by resting state fMRI (rsfMRI)-based brain entropy (BEN) mapping. While BEN mapping results have shown sensitivity to neuromodulations or disease conditions, the underlying neuromechanisms especially the associations of BEN or LRTC to neurocognition still remain unclear. To address this standing question and to test a novel hypothesis that resting BEN reflects a latent functional reserve through the link to general functionality, we mapped resting BEN of 862 young adults and comprehensively examined its associations to neurocognitions using data from the Human Connectome Project (HCP). Our results unanimously highlighted two brain circuits: the default mode network (DMN) and executive control network (ECN) through their negative associations of BEN to general functionality, which is independent of age and sex. While BEN in DMN/ECN increases with age, it decreases with education years. These results demonstrated the neurocognitive correlates of resting BEN in DMN/ECN and suggest resting BEN in DMN/ECN as a potential proxy of the latent functional reserve that facilitates general brain functionality and may be enhanced by education.
Collapse
Affiliation(s)
- Ze Wang
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, 670W. Baltimore St, Baltimore, MD 20201, United States.
| |
Collapse
|
20
|
Deli E, Peters J, Kisvárday Z. The thermodynamics of cognition: A mathematical treatment. Comput Struct Biotechnol J 2021; 19:784-793. [PMID: 33552449 PMCID: PMC7843413 DOI: 10.1016/j.csbj.2021.01.008] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2020] [Revised: 01/07/2021] [Accepted: 01/07/2021] [Indexed: 10/26/2022] Open
Abstract
There is a general expectation that the laws of classical physics must apply to biology, particularly the neural system. The evoked cycle represents the brain's energy/information exchange with the physical environment through stimulus. Therefore, the thermodynamics of emotions might elucidate the neurological origin of intellectual evolution, and explain the psychological and health consequences of positive and negative emotional states based on their energy profiles. We utilized the Carnot cycle and Landauer's principle to analyze the energetic consequences of the brain's resting and evoked states during and after various cognitive states. Namely, positive emotional states can be represented by the reversed Carnot cycle, whereas negative emotional reactions trigger the Carnot cycle. The two conditions have contrasting energetic and entropic aftereffects with consequences for mental energy. The mathematics of the Carnot and reversed Carnot cycles, which can explain recent findings in human psychology, might be constructive in the scientific endeavor in turning psychology into hard science.
Collapse
Affiliation(s)
- Eva Deli
- Institute for Consciousness Studies (ICS), Benczur ter 9, Nyiregyhaza 4400, Hungary
| | - James Peters
- Department of Electrical and Computer Engineering, University of Manitoba, 75A Chancellor's Circle, Winnipeg, MB R3T 5V6, Canada
- Department of Mathematics Faculty of Arts and Sciences, Adiyaman University, Adiyaman, Turkey
| | - Zoltán Kisvárday
- MTA-Debreceni Egyetem, Neuroscience Research Group, 4032 Debrecen, Nagyerdei krt.98., Hungary
| |
Collapse
|
21
|
Keilholz S, Maltbie E, Zhang X, Yousefi B, Pan WJ, Xu N, Nezafati M, LaGrow TJ, Guo Y. Relationship Between Basic Properties of BOLD Fluctuations and Calculated Metrics of Complexity in the Human Connectome Project. Front Neurosci 2020; 14:550923. [PMID: 33041756 PMCID: PMC7522447 DOI: 10.3389/fnins.2020.550923] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2020] [Accepted: 08/13/2020] [Indexed: 12/14/2022] Open
Abstract
Resting state functional MRI (rs-fMRI) creates a rich four-dimensional data set that can be analyzed in a variety of ways. As more researchers come to view the brain as a complex dynamical system, tools are increasingly being drawn from other fields to characterize the complexity of the brain's activity. However, given that the signal measured with rs-fMRI arises from the hemodynamic response to neural activity, the extent to which complexity metrics reflect neural complexity as compared to signal properties related to image quality remains unknown. To provide some insight into this question, correlation dimension, approximate entropy and Lyapunov exponent were calculated for different rs-fMRI scans from the same subject to examine their reliability. The metrics of complexity were then compared to several properties of the rs-fMRI signal from each brain area to determine if basic signal features could explain differences in the complexity metrics. Differences in complexity across brain areas were highly reliable and were closely linked to differences in the frequency profiles of the rs-fMRI signal. The spatial distributions of the complexity and frequency metrics suggest that they are both influenced by location-dependent signal properties that can obscure changes related to neural activity.
Collapse
Affiliation(s)
- Shella Keilholz
- Department of Biomedical Engineering, Georgia Institute of Technology, Emory University, Atlanta, GA, United States
| | - Eric Maltbie
- Department of Biomedical Engineering, Georgia Institute of Technology, Emory University, Atlanta, GA, United States
| | - Xiaodi Zhang
- Department of Biomedical Engineering, Georgia Institute of Technology, Emory University, Atlanta, GA, United States
| | - Behnaz Yousefi
- Department of Biomedical Engineering, Georgia Institute of Technology, Emory University, Atlanta, GA, United States
| | - Wen-Ju Pan
- Department of Biomedical Engineering, Georgia Institute of Technology, Emory University, Atlanta, GA, United States
| | - Nan Xu
- Department of Biomedical Engineering, Georgia Institute of Technology, Emory University, Atlanta, GA, United States
| | - Maysam Nezafati
- Department of Biomedical Engineering, Georgia Institute of Technology, Emory University, Atlanta, GA, United States
| | - Theodore J LaGrow
- Department of Biomedical Engineering, Georgia Institute of Technology, Emory University, Atlanta, GA, United States
| | - Ying Guo
- Department of Biostatistics and Bioinformatics, Emory University, Atlanta, GA, United States
| |
Collapse
|
22
|
Dhamala E, Jamison KW, Sabuncu MR, Kuceyeski A. Sex classification using long-range temporal dependence of resting-state functional MRI time series. Hum Brain Mapp 2020; 41:3567-3579. [PMID: 32627300 PMCID: PMC7416025 DOI: 10.1002/hbm.25030] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2020] [Accepted: 04/27/2020] [Indexed: 12/13/2022] Open
Abstract
A thorough understanding of sex differences that exist in the brains of healthy individuals is crucial for the study of neurological illnesses that exhibit phenotypic differences between males and females. Here we evaluate sex differences in regional temporal dependence of resting-state brain activity in 195 adult male-female pairs strictly matched for total grey matter volume from the Human Connectome Project. We find that males have more persistent temporal dependence in regions within temporal, parietal, and occipital cortices. Machine learning algorithms trained on regional temporal dependence measures achieve sex classification accuracies up to 81%. Regions with the strongest feature importance in the sex classification task included cerebellum, amygdala, and frontal and occipital cortices. Secondarily, we show that even after strict matching of total gray matter volume, significant volumetric sex differences persist; males have larger absolute cerebella, hippocampi, parahippocampi, thalami, caudates, and amygdalae while females have larger absolute cingulates, precunei, and frontal and parietal cortices. Sex classification based on regional volume achieves accuracies up to 85%, highlighting the importance of strict volume-matching when studying brain-based sex differences. Differential patterns in regional temporal dependence between the sexes identifies a potential neurobiological substrate or environmental effect underlying sex differences in functional brain activation patterns.
Collapse
Affiliation(s)
- Elvisha Dhamala
- Department of RadiologyWeill Cornell MedicineNew YorkNew YorkUSA
- Brain and Mind Research InstituteWeill Cornell MedicineNew YorkNew YorkUSA
| | - Keith W. Jamison
- Department of RadiologyWeill Cornell MedicineNew YorkNew YorkUSA
| | - Mert R. Sabuncu
- School of Electrical and Computer EngineeringCornell UniversityIthacaNew YorkUSA
- Meinig School of Biomedical EngineeringCornell UniversityIthacaNew YorkUSA
| | - Amy Kuceyeski
- Department of RadiologyWeill Cornell MedicineNew YorkNew YorkUSA
- Brain and Mind Research InstituteWeill Cornell MedicineNew YorkNew YorkUSA
| |
Collapse
|
23
|
Liang L, Hu R, Luo X, Feng B, Long W, Song R. Reduced Complexity in Stroke with Motor Deficits: A Resting-State fMRI Study. Neuroscience 2020; 434:35-43. [PMID: 32194224 DOI: 10.1016/j.neuroscience.2020.03.020] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2019] [Revised: 03/09/2020] [Accepted: 03/10/2020] [Indexed: 01/02/2023]
Abstract
Recently, alterations of complexity due to brain disorders have been demonstrated using brain entropy (BEN), while the changes of brain complexity in stroke, a common cerebrovascular disease, remain unclear. In this research, resting-state functional magnetic resonance imaging (fMRI) was performed to explore the alterations of brain complexity using BEN in twenty stroke patients with motor deficits and nineteen matched healthy controls. The sample entropy (SampEn) was applied to build the BEN mapping for each participant. Compared with healthy controls, stroke patients exhibited lower BEN values in the contralesional precentral gyrus (preCG), bilateral dorsolateral frontal gyrus (SFGdor) and bilateral supplementary motor area (SMA). Moreover, significantly positive correlations between BEN values and Fugl-Meyer Assessment scores were detected in the ipsilesional SFGdor and ipsilesional SMA. Mutual information independence was observed between BEN and regional homogeneity (ReHo), amplitude of low-frequency fluctuations (ALFF), respectively, in the stroke patients. Our findings implied that brain complexity had been impacted after stroke, and also suggested that BEN could be a complementary tool for evaluating the motor impairment after stroke.
Collapse
Affiliation(s)
- Liuke Liang
- Key Laboratory of Sensing Technology and Biomedical Instrument of Guangdong Province, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou 510006, China
| | - Rongliang Hu
- Department of Rehabilitation Medicine, Jiangmen Central Hospital, Jiangmen, Guangdong, China
| | - Xuemao Luo
- Department of Radiology, Jiangmen Central Hospital, Jiangmen, Guangdong, China
| | - Bao Feng
- Department of Radiology, Jiangmen Central Hospital, Jiangmen, Guangdong, China
| | - Wansheng Long
- Department of Radiology, Jiangmen Central Hospital, Jiangmen, Guangdong, China
| | - Rong Song
- Key Laboratory of Sensing Technology and Biomedical Instrument of Guangdong Province, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou 510006, China; Shenzhen Research Institute of Sun Yat-sen University, Shenzhen, Guangdong, China.
| |
Collapse
|
24
|
Liu X, Song D, Yin Y, Xie C, Zhang H, Zhang H, Zhang Z, Wang Z, Yuan Y. Altered Brain Entropy as a predictor of antidepressant response in major depressive disorder. J Affect Disord 2020; 260:716-721. [PMID: 31563070 DOI: 10.1016/j.jad.2019.09.067] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/23/2019] [Revised: 09/17/2019] [Accepted: 09/18/2019] [Indexed: 12/16/2022]
Abstract
OBJECTIVE To explore the alterations and value of brain entropy (BEN) in major depressive disorder (MDD). METHODS 85 MDD patients and 45 matched normal controls were recruited. MDD was diagnosed based on Diagnostic and Statistical Manual of Mental Disorders, 4th ed (DSM-IV). Symptoms of depression were assessed using the Hamilton depression scale-24 (HAMD-24) at baseline and follow-up (after 8-week treatment). All subjects underwent functional magnetic resonance imaging (fMRI) scans at baseline, and 30 MDD patients completed scans at 8th week. Whole brain BEN maps at each session was calculated using the BEN mapping toolbox. RESULTS The 8-week antidepressant treatment improved symptoms for all MDD patients. As compared to normal controls, MDD showed reduced BEN in medial orbitofrontal cortex (MOFC)/subgenual cingulate cortex (sgACC), but increased BEN in motor cortex (MC). In MDD patients, higher baseline BEN in MOFC/sgACC and lower baseline BEN in temporal cortex (TC) were associated with higher baseline HAMD scores; higher baseline BEN in MOFC/sgACC and hippocampus were associated with greater reduction of HAMD scores after 8-week medication; greater reduction of HAMD scores after 8-week medication was correlated with greater BEN reduction in MOFC/sgACC but were correlated with less BEN reduction in MC, TC, fusiform gyrus (FG) and visual cortex (VC). CONCLUSION The results highlighted MOFC/sgACC BEN as a potential marker for the prediction of MDD diagnosis and treatment effect. MDD might have increased MOFC/sgACC BEN but reduced BEN in visual and sensory-motor circuits corresponding to the imbalanced emotional and sensory-motor information processing. Reversing this unbalanced BEN would improve disease conditions in MDD.
Collapse
Affiliation(s)
- Xiaoyun Liu
- Department of Psychosomatics and Psychiatry, Zhongda Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Donghui Song
- Center for Cognition and Brain Disorders, Department of Psychology, Hangzhou Normal University, Hangzhou, China
| | - Yingying Yin
- Department of Psychosomatics and Psychiatry, Zhongda Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Chunming Xie
- Department of Neurology, ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Haisan Zhang
- Departments of Clinical Magnetic Resonance Imaging, the Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, Henan, China
| | - Hongxing Zhang
- Departments of Psychiatry, the Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, Henan, China
| | - Zhijun Zhang
- Department of Neurology, ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Ze Wang
- Department of Radiology, University of Maryland School of Medicine, USA.
| | - Yonggui Yuan
- Department of Psychosomatics and Psychiatry, Zhongda Hospital, School of Medicine, Southeast University, Nanjing, China.
| |
Collapse
|
25
|
Kim CM, Alvarado RL, Stephens K, Wey HY, Wang DJJ, Leritz EC, Salat DH. Associations between cerebral blood flow and structural and functional brain imaging measures in individuals with neuropsychologically defined mild cognitive impairment. Neurobiol Aging 2019; 86:64-74. [PMID: 31813626 DOI: 10.1016/j.neurobiolaging.2019.10.023] [Citation(s) in RCA: 33] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2018] [Revised: 10/05/2019] [Accepted: 10/08/2019] [Indexed: 01/18/2023]
Abstract
Reduced cerebral blood flow (CBF), an indicator of neurovascular processes and metabolic demands, is a common finding in Alzheimer's disease. However, little is known about what contributes to CBF deficits in individuals with mild cognitive impairment (MCI). We examine regional CBF differences in 17 MCI compared with 21 age-matched cognitively healthy older adults. Next, we examined associations between CBF, white matter lesion (WML) volume, amplitude of low-frequency fluctuations, and cortical thickness to better understand whether altered CBF was detectable before other markers and the potential mechanistic underpinnings of CBF deficits in MCI. MCI had significantly reduced CBF, whereas cortical thickness and amplitude of low-frequency fluctuation were not affected. Reduced CBF was associated with the WML volume but not associated with other measures. Given the presumed vascular etiology of WML and relative worsening of vascular health in MCI, it may suggest CBF deficits result from early vascular as opposed to metabolic deficits in MCI. These findings may support vascular mechanisms as an underlying component of cognitive impairment.
Collapse
Affiliation(s)
- Chan-Mi Kim
- Brain Aging and Dementia (BAnD) Laboratory, MGH/MIT/HMS Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA.
| | - Rachel L Alvarado
- Brain Aging and Dementia (BAnD) Laboratory, MGH/MIT/HMS Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA
| | - Kimberly Stephens
- Brain Aging and Dementia (BAnD) Laboratory, MGH/MIT/HMS Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA
| | - Hsiao-Ying Wey
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
| | - Dany J J Wang
- Laboratory of FMRI Technology (LOFT), Mark & Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, CA, USA; Department of Neurology, University of Southern California, Los Angeles, CA, USA
| | - Elizabeth C Leritz
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA; Geriatric Research, Education & Clinical Center & Translational Research Center for TBI and Stress Disorders, VA Boston Healthcare System, Boston, MA, USA
| | - David H Salat
- Brain Aging and Dementia (BAnD) Laboratory, MGH/MIT/HMS Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA; Neuroimaging Research for Veterans (NeRVe) Center, VA Boston Healthcare System, Boston, MA, USA
| |
Collapse
|
26
|
Lin C, Lee SH, Huang CM, Chen GY, Ho PS, Liu HL, Chen YL, Lee TMC, Wu SC. Increased brain entropy of resting-state fMRI mediates the relationship between depression severity and mental health-related quality of life in late-life depressed elderly. J Affect Disord 2019; 250:270-277. [PMID: 30870777 DOI: 10.1016/j.jad.2019.03.012] [Citation(s) in RCA: 33] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/11/2018] [Revised: 01/30/2019] [Accepted: 03/03/2019] [Indexed: 01/20/2023]
Abstract
BACKGROUND Entropy analysis is a computational method used to quantify the complexity in a system, and loss of brain complexity is hypothesized to be related to mental disorders. Here, we applied entropy analysis to the resting-state functional magnetic resonance imaging (rs-fMRI) signal in subjects with late-life depression (LLD), an illness combined with emotion dysregulation and aging effect. METHODS A total of 35 unremitted depressed elderly and 22 control subjects were recruited. Multiscale entropy (MSE) analysis was performed in the entire brain, 90 automated anatomical labeling-parcellated ROIs, and five resting networks in each study participant. LIMITATIONS Due to ethical concerns, all the participants were under medication during the study. RESULTS Regionally, subjects with LLD showed decreased entropy only in the right posterior cingulate gyrus but had universally increased entropy in affective processing (putamen and thalamus), sensory, motor, and temporal nodes across different time scales. We also found higher entropy in the left frontoparietal network (FPN), which partially mediated the negative correlation between depression severity and mental components of the quality of life, reflecting the possible neural compensation during depression treatment. CONCLUSION MSE provides a novel and complementary approach in rs-fMRI analysis. The temporal-spatial complexity in the resting brain may provide the adaptive variability beneficial for the elderly with depression.
Collapse
Affiliation(s)
- Chemin Lin
- Department of Psychiatry, Keelung Chang Gung Memorial Hospital, Keelung City, Taiwan; College of Medicine, Chang Gung University, Taoyuan County, Taiwan; Community Medicine Research Center, Chang Gung Memorial Hospital, Keelung, Keelung, Taiwan
| | - Shwu-Hua Lee
- College of Medicine, Chang Gung University, Taoyuan County, Taiwan; Department of Psychiatry, Linkou Chang Gung Memorial Hospital, Taoyuan County, Taiwan
| | - Chih-Mao Huang
- Department of Biological Science and Technology, National Chiao Tung University, Hsinchu, Taiwan
| | - Guan-Yen Chen
- Department of Engineering and System Science, National Tsing Hua University, Hsinchu, Taiwan
| | - Pei-Shan Ho
- Department of Engineering and System Science, National Tsing Hua University, Hsinchu, Taiwan
| | - Ho-Ling Liu
- Department of Imaging Physics, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Yao-Liang Chen
- Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital, Keelung, Taiwan
| | - Tatia Mei-Chun Lee
- Laboratory of Neuropsychology, The University of Hong Kong, Hong Kong; Laboratory of Cognitive Affective Neuroscience, The University of Hong Kong, Hong Kong; State Key Laboratory of Brain and Cognitive Science, The University of Hong Kong, Hong Kong; Institute of Clinical Neuropsychology, The University of Hong Kong, Hong Kong.
| | - Shun-Chi Wu
- Department of Engineering and System Science, National Tsing Hua University, Hsinchu, Taiwan.
| |
Collapse
|
27
|
Chang D, Zhang J, Peng W, Shen Z, Gao X, Du Y, Ge Q, Song D, Shang Y, Wang Z. Smoking Cessation With 20 Hz Repetitive Transcranial Magnetic Stimulation (rTMS) Applied to Two Brain Regions: A Pilot Study. Front Hum Neurosci 2018; 12:344. [PMID: 30319373 PMCID: PMC6166007 DOI: 10.3389/fnhum.2018.00344] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2018] [Accepted: 08/13/2018] [Indexed: 12/20/2022] Open
Abstract
Chronic smoking impairs brain functions in the prefrontal cortex and the projecting meso-cortical limbic system. The purpose of this pilot study is to examine whether modulating the frontal brain activity using high-frequency repetitive transcranial magnetic stimulation (rTMS) can improve smoking cessation and to explore the changing pattern of the brain activity after treatment. Fourteen treatment-seeking smokers were offered a program involving 10 days of rTMS treatment with a follow-up for another 25 days. A frequency of 20 Hz rTMS was sequentially applied on the left dorso-lateral prefrontal cortex (DLPFC) and the superior medial frontal cortex (SMFC). The carbon monoxide (CO) level, withdrawal, craving scales, and neuroimaging data were collected. Ten smokers completed the entire treatment program, and 90% of them did not smoke during the 25-day follow-up time. A significant smoking craving reduction and resting brain activity reduction measured by the cerebral blood flow (CBF) and brain entropy (BEN) were observed after 10 days of 20 Hz rTMS treatments compared to the baseline. Although limited by sample size, these pilot findings definitely showed a high potential of multiple-target high-frequency rTMS in smoking cessation and the utility of fMRI for objectively assessing the treatment effects.
Collapse
Affiliation(s)
- Da Chang
- Department of Psychology, Center for Cognition and Brain Disorders, Hangzhou Normal University, Hangzhou, China
| | - Jian Zhang
- Department of Psychology, Center for Cognition and Brain Disorders, Hangzhou Normal University, Hangzhou, China
| | - Wei Peng
- Department of Psychology, Center for Cognition and Brain Disorders, Hangzhou Normal University, Hangzhou, China
| | - Zhuowen Shen
- Department of Psychology, Center for Cognition and Brain Disorders, Hangzhou Normal University, Hangzhou, China
| | - Xin Gao
- Department of Psychology, Center for Cognition and Brain Disorders, Hangzhou Normal University, Hangzhou, China
| | - Youhong Du
- Department of Psychology, Center for Cognition and Brain Disorders, Hangzhou Normal University, Hangzhou, China
| | - Qiu Ge
- Department of Psychology, Center for Cognition and Brain Disorders, Hangzhou Normal University, Hangzhou, China
| | - Donghui Song
- Department of Psychology, Center for Cognition and Brain Disorders, Hangzhou Normal University, Hangzhou, China
| | - Yuanqi Shang
- Department of Psychology, Center for Cognition and Brain Disorders, Hangzhou Normal University, Hangzhou, China
| | - Ze Wang
- Department of Psychology, Center for Cognition and Brain Disorders, Hangzhou Normal University, Hangzhou, China
- Department of Radiology, Lewis Katz School of Medicine, Temple University, Philadelphia, PA, United States
| |
Collapse
|