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Herrera ML, Champarini LG, Basmadjian OM, Bellini MJ, Hereñú CB. IGF-1 gene therapy prevents spatial memory deficits and modulates dopaminergic neurodegeneration and inflammation in a parkinsonism model. Brain Behav Immun 2024; 119:851-866. [PMID: 38750702 DOI: 10.1016/j.bbi.2024.05.013] [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: 08/22/2023] [Revised: 04/14/2024] [Accepted: 05/12/2024] [Indexed: 05/19/2024] Open
Abstract
Cognitive impairment in Parkinson's disease is considered an indicator of the prodromal stages of this condition, occurring prior to the onset of classic and pathognomonic motor symptoms. Among other factors, neuroinflammation is increasingly recognized as a potential mediator of this neurodegenerative process, and glial cells are directly involved. However, the use of neurotrophic factors is associated with neuroprotection and cognitive improvements. Among all those factors, insulin-like growth factor 1 (IGF-1) has attracted considerable attention. In this study, we aimed to investigate the effect of IGF-1 gene therapy in an early animal model of 6-hydroxidopamine (6-OHDA)- induced parkinsonism. For this purpose, we employed male Wistar rats. The animals were first divided into two groups according to the bilateral injection into de Caudate Putamen unit (CPu):(a) VEH group (vehicle solution) and (b) 6-OHDA group (neurotoxic solution). After that, the animals in each group were divided, according to the bilateral injection into the dorsal hippocampus, in a control group (who received a control virus RAd-DSRed) and an experimental group (who received a therapeutic virus (RAd-IGF1). After three weeks of exposure to 6-OHDA, our study showed that IGF-1 gene therapy improved cognitive deficits related to short-term and spatial working memory, it also increased expression levels of tyrosine hydroxylase in the CPu. In addition, the therapy resulted in significant changes in several parameters (area, perimeter, roundness, ramification, and skeleton ́s analyses) related to microglia and astrocyte phenotypes, particularly in the CPu and dorsal hippocampal areas. Our data support the use of IGF-1 as a therapeutic molecule for future gene transfer interventions, that will contribute to a better understanding of the mechanisms correlating cognitive function and inflammatory process.
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Affiliation(s)
- Macarena Lorena Herrera
- Universidad Nacional de Córdoba, Facultad de Ciencias Químicas, Departamento de Farmacología, Instituto de Farmacología Experimental de Córdoba (IFEC-CONICET), Córdoba, Argentina; Instituto de Investigaciones Bioquímicas de La Plata, Facultad de Ciencias Médicas, Universidad Nacional de La Plata (INIBIOLP-CONICET-UNLP), Buenos Aires, Argentina
| | - Leandro Gabriel Champarini
- Universidad Nacional de Córdoba, Facultad de Ciencias Químicas, Departamento de Farmacología, Instituto de Farmacología Experimental de Córdoba (IFEC-CONICET), Córdoba, Argentina
| | - Osvaldo Martín Basmadjian
- Instituto de Investigación Médica Mercedes y Martín Ferreyra (INIMEC), CONICET-UNC, Córdoba, Argentina
| | - María José Bellini
- Instituto de Investigaciones Bioquímicas de La Plata, Facultad de Ciencias Médicas, Universidad Nacional de La Plata (INIBIOLP-CONICET-UNLP), Buenos Aires, Argentina.
| | - Claudia Beatriz Hereñú
- Universidad Nacional de Córdoba, Facultad de Ciencias Químicas, Departamento de Farmacología, Instituto de Farmacología Experimental de Córdoba (IFEC-CONICET), Córdoba, Argentina.
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Wang L, Han K, Huang Q, Hu W, Mo J, Wang J, Deng K, Zhang R, Tan X. Systemic lupus erythematosus-related brain abnormalities in the default mode network and the limbic system: A resting-state fMRI meta-analysis. J Affect Disord 2024; 355:190-199. [PMID: 38548195 DOI: 10.1016/j.jad.2024.03.121] [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: 12/20/2023] [Revised: 02/29/2024] [Accepted: 03/23/2024] [Indexed: 04/04/2024]
Abstract
BACKGROUND Systemic lupus erythematosus (SLE) is an immune-mediated and multi-systemic disease which may affect the nervous system, causing neuropsychiatric SLE (NPSLE). Recent neuroimaging studies have examined brain functional alterations in SLE. However, discrepant findings were reported. This meta-analysis aims to identify consistent resting-state functional abnormalities in SLE. METHODS PubMed and Web of Science were searched to identify candidate resting-state functional MRI studies assessing SLE. A voxel-based meta-analysis was performed using the anisotropic effect-size version of the seed-based d mapping (AES-SDM). The abnormal intrinsic functional patterns extracted from SDM were mapped onto the brain functional network atlas to determine brain abnormalities at a network level. RESULTS Twelve studies evaluating fifteen datasets were included in this meta-analysis, comprising 572 SLE patients and 436 healthy controls (HCs). Compared with HCs, SLE patients showed increased brain activity in the bilateral hippocampus and right superior temporal gyrus, and decreased brain activity in the left superior frontal gyrus, left middle temporal gyrus, bilateral thalamus, left inferior frontal gyrus and right cerebellum. Mapping the abnormal patterns to the network atlas revealed the default mode network and the limbic system as core neural systems commonly affected in SLE. LIMITATIONS The number of included studies is relatively small, with heterogeneous analytic methods and a risk of publication bias. CONCLUSIONS Brain functional alterations in SLE are predominantly found in the default mode network and the limbic system. These findings uncovered a consistent pattern of resting-state functional network abnormalities in SLE which may serve as a potential objective neuroimaging biomarker.
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Affiliation(s)
- Linhui Wang
- Department of Medical Imaging Center, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Kai Han
- Department of Dermatology, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Qin Huang
- Department of Rheumatology, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Wenjun Hu
- Department of Medical Imaging Center, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Jiaying Mo
- Department of Medical Imaging Center, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Jingyi Wang
- Department of Medical Imaging Center, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Kan Deng
- Philips Healthcare, Guangzhou, China
| | - Ruibin Zhang
- Cognitive control and Brain Healthy Laboratory, Department of Psychology, School of Public Health, Southern Medical University, Guangzhou, China; Department of Psychiatry, Zhujiang Hospital, Southern Medical University, Guangzhou, China.
| | - Xiangliang Tan
- Department of Medical Imaging Center, Nanfang Hospital, Southern Medical University, Guangzhou, China.
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Caballero HS, McFall GP, Gee M, MacDonald S, Phillips NA, Fogarty J, Montero-Odasso M, Camicioli R, Dixon RA. Cognitive Speed in Neurodegenerative Disease: Comparing Mean Rate and Inconsistency Within and Across the Alzheimer's and Lewy Body Spectra in the COMPASS-ND Study. J Alzheimers Dis 2024:JAD240210. [PMID: 38875040 DOI: 10.3233/jad-240210] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/16/2024]
Abstract
Background Alzheimer's disease (AD) and Lewy body disease (LBD) are characterized by early and gradual worsening perturbations in speeded cognitive responses. Objective Using simple and choice reaction time tasks, we compared two indicators of cognitive speed within and across the AD and LBD spectra: mean rate (average reaction time across trials) and inconsistency (within person variability). Methods The AD spectrum cohorts included subjective cognitive impairment (SCI, n = 28), mild cognitive impairment (MCI, n = 121), and AD (n = 45) participants. The LBD spectrum included Parkinson's disease (PD, n = 32), mild cognitive impairment in PD (PD-MCI, n = 21), and LBD (n = 18) participants. A cognitively unimpaired (CU, n = 39) cohort served as common benchmark. We conducted multivariate analyses of variance and discrimination analyses. Results Within the AD spectrum, the AD cohort was slower and more inconsistent than the CU, SCI, and MCI cohorts. The MCI cohort was slower than the CU cohort. Within the LBD spectrum, the LBD cohort was slower and more inconsistent than the CU, PD, and PD-MCI cohorts. The PD-MCI cohort was slower than the CU and PD cohorts. In cross-spectra (corresponding cohort) comparisons, the LBD cohort was slower and more inconsistent than the AD cohort. The PD-MCI cohort was slower than the MCI cohort. Discrimination analyses clarified the group difference patterns. Conclusions For both speed tasks, mean rate and inconsistency demonstrated similar sensitivity to spectra-related comparisons. Both dementia cohorts were slower and more inconsistent than each of their respective non-dementia cohorts.
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Affiliation(s)
- H Sebastian Caballero
- Neuroscience and Mental Health Institute, University of Alberta, Edmonton, AB, Canada
| | - G Peggy McFall
- Neuroscience and Mental Health Institute, University of Alberta, Edmonton, AB, Canada
- Department of Psychology, University of Alberta, Edmonton, AB, Canada
| | - Myrlene Gee
- Department of Medicine (Neurology), University of Alberta, Edmonton, AB, Canada
| | - Stuart MacDonald
- Department of Psychology, University of Victoria, Victoria, BC, Canada
| | | | | | | | - Richard Camicioli
- Neuroscience and Mental Health Institute, University of Alberta, Edmonton, AB, Canada
- Department of Medicine (Neurology), University of Alberta, Edmonton, AB, Canada
| | - Roger A Dixon
- Neuroscience and Mental Health Institute, University of Alberta, Edmonton, AB, Canada
- Department of Psychology, University of Alberta, Edmonton, AB, Canada
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Ysbæk-Nielsen AT. Connectome-based predictive modelling estimates individual cognitive status in Parkinson's disease. Parkinsonism Relat Disord 2024; 123:106020. [PMID: 38579439 DOI: 10.1016/j.parkreldis.2024.106020] [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: 12/19/2023] [Revised: 01/30/2024] [Accepted: 01/30/2024] [Indexed: 04/07/2024]
Abstract
INTRODUCTION The progressive nature of Parkinson's disease (PD) affords emphasis on accurate early-stage individual-level assessment of risk and intervention appropriateness. In PD, cognitive impairment (CI) may follow or precede motor symptoms but are generally underdetected. In addition to impeding daily functioning and quality of life, CIs increase the risk for later conversion to dementia, providing a pressing need to develop novel tools to detect and interpret them. Connectome-based predictive modelling (CPM) is an emerging machine-learning approach to individual prediction that holds translational promise due to its noninvasiveness and simple implementation. The aim of this study was to investigate CPM's potential to predict and understand CIs in PD. METHODS Resting-state functional connectivity from 58 patients with PD of varying cognitive status was used to train a CPM-model to predict a global cognitive composite (GCC) score. The model was validated using cross-validation, permutation testing, and internal stability analyses. The combined predictive strength of two brain connectivity networks, positive and negative, directly and inversely correlated with GCC, respectively, was assessed. RESULTS The model significantly predicted individual GCC scores, r = 0.63, pperm < .05. Separately, the positive and negative networks were similar in performance, rs ≥ .58, ps < .05, but varied in anatomical distribution. CONCLUSIONS This study identified a connectome predictive of cognitive scores in PD, with features overlapping with established and emerging evidence on aberrant connectivity in PD-related CIs. Overall, CPM appears promising for clinical translation in this population, but longitudinal studies with out-of-sample validation are needed.
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Du J, Liu Y, Zhu W. The altered functional status in vestibular migraine: A meta-analysis. Brain Behav 2024; 14:e3591. [PMID: 38849984 PMCID: PMC11161393 DOI: 10.1002/brb3.3591] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/03/2023] [Revised: 05/07/2024] [Accepted: 05/16/2024] [Indexed: 06/09/2024] Open
Abstract
PURPOSE Vestibular migraine (VM) is a disorder with prominent vestibular symptoms that are causally correlated with migraine and is the most prevalent neurological cause of episodic vertigo. Nevertheless, the functional underpinnings of VM remain largely unclear. This study aimed to reveal concordant alteration patterns of functional connectivity (FC) in VM patients. METHODS We searched literature measuring resting-state FC abnormalities of VM patients in PubMed, Embase, Cochrane, and Scopus databases before May 2023. Furthermore, we applied the anisotropic effect size-signed differential mapping (AES-SDM) to conduct a whole-brain voxel-wise meta-analysis to identify the convergence of FC alterations in VM patients. RESULTS Nine studies containing 251 VM patients and 257 healthy controls (HCs) were included. Relative to HCs, VM patients showed reduced activity in the left superior temporal gyrus and left midcingulate/paracingulate gyri, and increased activity in the precuneus, right superior parietal gyrus, and right middle frontal gyrus. Jackknife's analysis and subgroup analysis further supported the generalization and robustness of the main results. Furthermore, meta-regression analyses indicated that the Dizziness Handicap Inventory (DHI) ratings were positively correlated with the activity in the precuneus, while higher Headache Impact Test-6 and DHI scores were associated with lower activity within the left midcingulate/paracingulate gyri. CONCLUSIONS The study indicates that VM is associated with specific functional deficits of VM patients in crucial regions involved in the vestibular and pain networks and provides further information on the pathophysiological mechanisms of VM.
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Affiliation(s)
- Junyong Du
- Department of Neurology, Tongji Hospital, Tongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
| | - Yong Liu
- School of Artificial IntelligenceBeijing University of Posts and TelecommunicationsBeijingChina
- School of Artificial IntelligenceUniversity of Chinese Academy of SciencesBeijingChina
| | - Wenhao Zhu
- Department of Neurology, Tongji Hospital, Tongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
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Chen Z, Liu Y, Lin C, Li Z, Shan J, Duan Z, Rong L, Wei X, Xiao L, Liu H. Aberrant cerebral blood flow and functional connectivity in patients with vestibular migraine: a resting-state ASL and fMRI study. J Headache Pain 2024; 25:84. [PMID: 38773396 PMCID: PMC11107056 DOI: 10.1186/s10194-024-01792-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2024] [Accepted: 05/15/2024] [Indexed: 05/23/2024] Open
Abstract
BACKGROUND Prior neuroimaging studies on vestibular migraine (VM) have extensively certified the functional and structural alterations in multiple brain regions and networks. However, few studies have assessed the cerebral blood flow (CBF) in VM patients using arterial spin labeling (ASL). The present study aimed to investigate CBF and functional connectivity (FC) alterations in VM patients during interictal periods. METHODS We evaluated 52 VM patients and 46 healthy controls (HC) who received resting-state pseudo-continuous ASL and functional magnetic resonance imaging (fMRI) scanning. Comparisons of voxel-based CBF and seed-based FC were performed between the two groups. Brain regions showed significant group differences in CBF analyses were chosen as seeds in FC analyses. Additionally, the associations between abnormal imaging results and clinical features were explored. RESULTS Compared with HC, VM patients showed higher normalized CBF in the right precentral gyrus (PreCG), left postcentral gyrus (PostCG), left superior frontal gyrus and bilateral insular (p < 0.05, FDR corrected). Furthermore, VM patients exhibited increased FC between the right PreCG and areas of the left PostCG, left cuneus and right lingual gyrus (p < 0.05, FDR corrected). In addition, we observed decreased FC between the left insular and regions of the left thalamus and right anterior cingulate cortex, as well as increased FC between the left insular and right fusiform gyrus in VM patients (p < 0.05, FDR corrected). Moreover, these variations in brain perfusion and FC were significantly correlated with multiple clinical features including frequency of migraine symptoms, frequency of vestibular symptoms and disease duration of VM (all p < 0.05). CONCLUSIONS Patients with VM during interictal period showed hyperperfusion and abnormal resting-state FC in brain regions potentially contributed to disrupted multi-sensory and autonomic processing, as well as impaired ocular motor control, pain modulation and emotional regulation. Our study provided novel insights into the complex neuropathology of VM from a CBF perspective.
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Affiliation(s)
- Zhengwei Chen
- Department of Neurology, Second Affiliated Hospital of Xuzhou Medical University, No.32, Meijian Road, Xuzhou, Jiangsu, 221006, China
| | - Yueji Liu
- Department of Neurology, Second Affiliated Hospital of Xuzhou Medical University, No.32, Meijian Road, Xuzhou, Jiangsu, 221006, China
| | - Cunxin Lin
- Department of Neurology, Second Affiliated Hospital of Xuzhou Medical University, No.32, Meijian Road, Xuzhou, Jiangsu, 221006, China
| | - Zhining Li
- Department of Neurology, Second Affiliated Hospital of Xuzhou Medical University, No.32, Meijian Road, Xuzhou, Jiangsu, 221006, China
| | - Junjun Shan
- Department of Neurology, Second Affiliated Hospital of Xuzhou Medical University, No.32, Meijian Road, Xuzhou, Jiangsu, 221006, China
| | - Zuowei Duan
- Department of Neurology, Second Affiliated Hospital of Xuzhou Medical University, No.32, Meijian Road, Xuzhou, Jiangsu, 221006, China
| | - Liangqun Rong
- Department of Neurology, Second Affiliated Hospital of Xuzhou Medical University, No.32, Meijian Road, Xuzhou, Jiangsu, 221006, China
| | - Xiue Wei
- Department of Neurology, Second Affiliated Hospital of Xuzhou Medical University, No.32, Meijian Road, Xuzhou, Jiangsu, 221006, China
| | - Lijie Xiao
- Department of Neurology, Second Affiliated Hospital of Xuzhou Medical University, No.32, Meijian Road, Xuzhou, Jiangsu, 221006, China.
| | - Haiyan Liu
- Department of Neurology, Second Affiliated Hospital of Xuzhou Medical University, No.32, Meijian Road, Xuzhou, Jiangsu, 221006, China.
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Castelli MB, Alonso-Recio L, Carvajal F, Serrano JM. Does the Montreal Cognitive Assessment (MoCA) identify cognitive impairment profiles in Parkinson's disease? An exploratory study. APPLIED NEUROPSYCHOLOGY. ADULT 2024; 31:238-247. [PMID: 34894908 DOI: 10.1080/23279095.2021.2011727] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
An important proportion of patients with Parkinson's Disease (PD) present signs of cognitive impairment, although this is heterogeneous. In an attempt to classify this, the dual syndrome hypothesis distinguishes between two profiles: one defined by attentional and executive problems with damage in anterior cerebral regions, and another with mnesic and visuospatial alterations, with damage in posterior cerebral regions. The Montreal Cognitive Assessment (MoCA) is one of the recommended screening tools, and one of the most used, to assess cognitive impairment in PD. However, its ability to specifically identify these two profiles of cognitive impairment has not been studied. The aim of this study was, therefore, to analyze the capacity of the MoCA to detect cognitive impairment, and also to identify anterior and posterior profiles defined by the dual syndrome hypothesis. For this purpose, 59 patients with idiopathic PD were studied with the MoCA and a neuropsychological battery of tests covering all cognitive domains. Results of logistic regression analysis with ROC (Receiver Operating Characteristic) curves showed that MoCA detected cognitive impairment and identified patients with a profile of anterior/attentional and executive deficit, with acceptable sensibility and specificity. However, it did not identify patients with a posterior/mnesic-visuospatial impairment. We discuss the reasons for the lack of sensitivity of MoCA in this profile, and other possible implications of these results with regards the usefulness of this tool to assess cognitive impairment in PD.
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Affiliation(s)
- María Belén Castelli
- Departamento de Psicología Biológica y de la Salud, Facultad de Psicología, Universidad Autónoma de Madrid, Madrid, Spain
| | - Laura Alonso-Recio
- Departamento de Psicología y Salud, Facultad de Ciencias de la Salud y la Educación, Universidad a Distancia de Madrid, Madrid, Spain
| | - Fernando Carvajal
- Departamento de Psicología Biológica y de la Salud, Facultad de Psicología, Universidad Autónoma de Madrid, Madrid, Spain
| | - Juan Manuel Serrano
- Departamento de Psicología Biológica y de la Salud, Facultad de Psicología, Universidad Autónoma de Madrid, Madrid, Spain
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Mekbib DB, Cai M, Wu D, Dai W, Liu X, Zhao L. Reproducibility and Sensitivity of Resting-State fMRI in Patients With Parkinson's Disease Using Cross Validation-Based Data Censoring. J Magn Reson Imaging 2024; 59:1630-1642. [PMID: 37584329 DOI: 10.1002/jmri.28958] [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: 04/25/2023] [Revised: 08/02/2023] [Accepted: 08/02/2023] [Indexed: 08/17/2023] Open
Abstract
BACKGROUND Uncontrollable body movements are typical symptoms of Parkinson's disease (PD), which results in inconsistent findings regarding resting-state functional connectivity (rsFC) networks, especially for group difference clusters. Systematically identifying the motion-associated data was highly demanded. PURPOSE To determine data censoring criteria using a quantitative cross validation-based data censoring (CVDC) method and to improve the detection of rsFC deficits in PD. STUDY TYPE Prospective. SUBJECTS Forty-one PD patients (68.63 ± 9.17 years, 44% female) and 20 healthy controls (66.83 ± 12.94 years, 55% female). FIELD STRENGTH/SEQUENCE 3-T, T1-weighted gradient echo and EPI sequences. ASSESSMENT Clusters with significant differences between groups were found in three visual networks, default network, and right sensorimotor network. Five-fold cross-validation tests were performed using multiple motion exclusion criteria, and the selected criteria were determined based on cluster sizes, significance values, and Dice coefficients among the cross-validation tests. As a reference method, whole brain rsFC comparisons between groups were analyzed using a FMRIB Software Library (FSL) pipeline with default settings. STATISTICAL TESTS Group difference clusters were calculated using nonparametric permutation statistics of FSL-randomize. The family-wise error was corrected. Demographic information was evaluated using independent sample t-tests and Pearson's Chi-squared tests. The level of statistical significance was set at P < 0.05. RESULTS With the FSL processing pipeline, the mean Dice coefficient of the network clusters was 0.411, indicating a low reproducibility. With the proposed CVDC method, motion exclusion criteria were determined as frame-wise displacement >0.55 mm. Group-difference clusters showed a mean P-value of 0.01 and a 72% higher mean Dice coefficient compared to the FSL pipeline. Furthermore, the CVDC method was capable of detecting subtle rsFC deficits in the medial sensorimotor network and auditory network that were unobservable using the conventional pipeline. DATA CONCLUSION The CVDC method may provide superior sensitivity and improved reproducibility for detecting rsFC deficits in PD. LEVEL OF EVIDENCE 1 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Destaw Bayabil Mekbib
- Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
- Department of Physics and Statistics, Addis Ababa Science and Technology University, Addis Ababa, Ethiopia
| | - Miao Cai
- Department of Neurology, Affiliated Zhejiang Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Dan Wu
- Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
| | - Weiying Dai
- Department of Computer Science, State University of New York at Binghamton, Binghamton, New York, USA
| | - Xiaoli Liu
- Department of Neurology, Affiliated Zhejiang Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Li Zhao
- Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
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Lu J, Zhang X, Shu Z, Han J, Yu N. A dynamic brain network decomposition method discovers effective brain hemodynamic sub-networks for Parkinson's disease. J Neural Eng 2024; 21:026047. [PMID: 38621377 DOI: 10.1088/1741-2552/ad3eb6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2024] [Accepted: 04/15/2024] [Indexed: 04/17/2024]
Abstract
Objective.Dopaminergic treatment is effective for Parkinson's disease (PD). Nevertheless, the conventional treatment assessment mainly focuses on human-administered behavior examination while the underlying functional improvements have not been well explored. This paper aims to investigate brain functional variations of PD patients after dopaminergic therapy.Approach.This paper proposed a dynamic brain network decomposition method and discovered brain hemodynamic sub-networks that well characterized the efficacy of dopaminergic treatment in PD. Firstly, a clinical walking procedure with functional near-infrared spectroscopy was developed, and brain activations during the procedure from fifty PD patients under the OFF and ON states (without and with dopaminergic medication) were captured. Then, dynamic brain networks were constructed with sliding-window analysis of phase lag index and integrated time-varying functional networks across all patients. Afterwards, an aggregated network decomposition algorithm was formulated based on aggregated effectiveness optimization of functional networks in spanning network topology and cross-validation network variations, and utilized to unveil effective brain hemodynamic sub-networks for PD patients. Further, dynamic sub-network features were constructed to characterize the brain flexibility and dynamics according to the temporal switching and activation variations of discovered sub-networks, and their correlations with differential treatment-induced gait alterations were analyzed.Results.The results demonstrated that PD patients exhibited significantly enhanced flexibility after dopaminergic therapy within a sub-network related to the improvement of motor functions. Other sub-networks were significantly correlated with trunk-related axial symptoms and exhibited no significant treatment-induced dynamic interactions.Significance.The proposed method promises a quantified and objective approach for dopaminergic treatment evaluation. Moreover, the findings suggest that the gait of PD patients comprises distinct motor domains, and the corresponding neural controls are selectively responsive to dopaminergic treatment.
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Affiliation(s)
- Jiewei Lu
- College of Artificial Intelligence, Nankai University, Tianjin, People's Republic of China
| | - Xinyuan Zhang
- College of Artificial Intelligence, Nankai University, Tianjin, People's Republic of China
| | - Zhilin Shu
- College of Artificial Intelligence, Nankai University, Tianjin, People's Republic of China
| | - Jianda Han
- College of Artificial Intelligence, Nankai University, Tianjin, People's Republic of China
- Engineering Research Center of Trusted Behavior Intelligence, Ministry of Education, Nankai University, Tianjin, People's Republic of China
- Institute of Intelligence Technology and Robotic Systems, Shenzhen Research Institute of Nankai University, Shenzhen, People's Republic of China
| | - Ningbo Yu
- College of Artificial Intelligence, Nankai University, Tianjin, People's Republic of China
- Engineering Research Center of Trusted Behavior Intelligence, Ministry of Education, Nankai University, Tianjin, People's Republic of China
- Institute of Intelligence Technology and Robotic Systems, Shenzhen Research Institute of Nankai University, Shenzhen, People's Republic of China
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Novakova L, Gajdos M, Barton M, Brabenec L, Zeleznikova Z, Moravkova I, Rektorova I. Striato-cortical functional connectivity changes in mild cognitive impairment with Lewy bodies. Parkinsonism Relat Disord 2024; 121:106031. [PMID: 38364623 DOI: 10.1016/j.parkreldis.2024.106031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Revised: 02/01/2024] [Accepted: 02/09/2024] [Indexed: 02/18/2024]
Abstract
BACKGROUND Functional connectivity changes in clinically overt neurodegenerative diseases such as dementia with Lewy bodies have been described, but studies on connectivity changes in the pre-dementia phase are scarce. OBJECTIVES We concentrated on evaluating striato-cortical functional connectivity differences between patients with Mild Cognitive Impairment with Lewy bodies and healthy controls and on assessing the relation to cognition. METHODS Altogether, we enrolled 77 participants (47 patients, of which 35 met all the inclusion criteria for the final analysis, and 30 age- and gender-matched healthy controls, of which 28 met all the inclusion criteria for the final analysis) to study the seed-based connectivity of the dorsal, middle, and ventral striatum. We assessed correlations between functional connectivity in the regions of between-group differences and neuropsychological scores of interest (visuospatial and executive domains z-scores). RESULTS Subjects with Mild Cognitive Impairment with Lewy Bodies, as compared to healthy controls, showed increased connectivity from the dorsal part of the striatum particularly to the bilateral anterior part of the temporal cortex with an association with executive functions. CONCLUSIONS We were able to capture early abnormal connectivity within cholinergic and noradrenergic pathways that correlated with cognitive functions known to be linked to cholinergic/noradrenergic deficits. The knowledge of specific alterations may improve our understanding of early neural changes in pre-dementia stages and enhance research of disease modifying therapy.
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Affiliation(s)
- Lubomira Novakova
- Brain and Mind Research Program, CEITEC, Masaryk University, Brno, Czech Republic
| | - Martin Gajdos
- Brain and Mind Research Program, CEITEC, Masaryk University, Brno, Czech Republic
| | - Marek Barton
- Brain and Mind Research Program, CEITEC, Masaryk University, Brno, Czech Republic
| | - Lubos Brabenec
- Brain and Mind Research Program, CEITEC, Masaryk University, Brno, Czech Republic
| | - Zaneta Zeleznikova
- Brain and Mind Research Program, CEITEC, Masaryk University, Brno, Czech Republic; First Department of Neurology, St. Anne's University Hospital and Faculty of Medicine, Masaryk University, Brno, Czech Republic
| | - Ivona Moravkova
- Brain and Mind Research Program, CEITEC, Masaryk University, Brno, Czech Republic; First Department of Neurology, St. Anne's University Hospital and Faculty of Medicine, Masaryk University, Brno, Czech Republic
| | - Irena Rektorova
- Brain and Mind Research Program, CEITEC, Masaryk University, Brno, Czech Republic; First Department of Neurology, St. Anne's University Hospital and Faculty of Medicine, Masaryk University, Brno, Czech Republic.
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11
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Silva NA, Barrios-Martinez J, Yeh FC, Hodaie M, Roque D, Boerwinkle VL, Krishna V. Diffusion and functional MRI in surgical neuromodulation. Neurotherapeutics 2024; 21:e00364. [PMID: 38669936 PMCID: PMC11064589 DOI: 10.1016/j.neurot.2024.e00364] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2023] [Revised: 04/13/2024] [Accepted: 04/15/2024] [Indexed: 04/28/2024] Open
Abstract
Surgical neuromodulation has witnessed significant progress in recent decades. Notably, deep brain stimulation (DBS), delivered precisely within therapeutic targets, has revolutionized the treatment of medication-refractory movement disorders and is now expanding for refractory psychiatric disorders, refractory epilepsy, and post-stroke motor recovery. In parallel, the advent of incisionless treatment with focused ultrasound ablation (FUSA) can offer patients life-changing symptomatic relief. Recent research has underscored the potential to further optimize DBS and FUSA outcomes by conceptualizing the therapeutic targets as critical nodes embedded within specific brain networks instead of strictly anatomical structures. This paradigm shift was facilitated by integrating two imaging modalities used regularly in brain connectomics research: diffusion MRI (dMRI) and functional MRI (fMRI). These advanced imaging techniques have helped optimize the targeting and programming techniques of surgical neuromodulation, all while holding immense promise for investigations into treating other neurological and psychiatric conditions. This review aims to provide a fundamental background of advanced imaging for clinicians and scientists, exploring the synergy between current and future approaches to neuromodulation as they relate to dMRI and fMRI capabilities. Focused research in this area is required to optimize existing, functional neurosurgical treatments while serving to build an investigative infrastructure to unlock novel targets to alleviate the burden of other neurological and psychiatric disorders.
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Affiliation(s)
- Nicole A Silva
- Department of Neurological Surgery, University of North Carolina - Chapel Hill, Chapel Hill, NC, USA
| | | | - Fang-Cheng Yeh
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA, USA
| | - Mojgan Hodaie
- Division of Neurosurgery, University of Toronto, Toronto, Canada
| | - Daniel Roque
- Department of Neurology, University of North Carolina in Chapel Hill, NC, USA
| | - Varina L Boerwinkle
- Department of Neurology, University of North Carolina in Chapel Hill, NC, USA
| | - Vibhor Krishna
- Department of Neurological Surgery, University of North Carolina - Chapel Hill, Chapel Hill, NC, USA.
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12
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Caeyenberghs K, Imms P, Irimia A, Monti MM, Esopenko C, de Souza NL, Dominguez D JF, Newsome MR, Dobryakova E, Cwiek A, Mullin HAC, Kim NJ, Mayer AR, Adamson MM, Bickart K, Breedlove KM, Dennis EL, Disner SG, Haswell C, Hodges CB, Hoskinson KR, Johnson PK, Königs M, Li LM, Liebel SW, Livny A, Morey RA, Muir AM, Olsen A, Razi A, Su M, Tate DF, Velez C, Wilde EA, Zielinski BA, Thompson PM, Hillary FG. ENIGMA's simple seven: Recommendations to enhance the reproducibility of resting-state fMRI in traumatic brain injury. Neuroimage Clin 2024; 42:103585. [PMID: 38531165 PMCID: PMC10982609 DOI: 10.1016/j.nicl.2024.103585] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2023] [Revised: 02/22/2024] [Accepted: 02/25/2024] [Indexed: 03/28/2024]
Abstract
Resting state functional magnetic resonance imaging (rsfMRI) provides researchers and clinicians with a powerful tool to examine functional connectivity across large-scale brain networks, with ever-increasing applications to the study of neurological disorders, such as traumatic brain injury (TBI). While rsfMRI holds unparalleled promise in systems neurosciences, its acquisition and analytical methodology across research groups is variable, resulting in a literature that is challenging to integrate and interpret. The focus of this narrative review is to address the primary methodological issues including investigator decision points in the application of rsfMRI to study the consequences of TBI. As part of the ENIGMA Brain Injury working group, we have collaborated to identify a minimum set of recommendations that are designed to produce results that are reliable, harmonizable, and reproducible for the TBI imaging research community. Part one of this review provides the results of a literature search of current rsfMRI studies of TBI, highlighting key design considerations and data processing pipelines. Part two outlines seven data acquisition, processing, and analysis recommendations with the goal of maximizing study reliability and between-site comparability, while preserving investigator autonomy. Part three summarizes new directions and opportunities for future rsfMRI studies in TBI patients. The goal is to galvanize the TBI community to gain consensus for a set of rigorous and reproducible methods, and to increase analytical transparency and data sharing to address the reproducibility crisis in the field.
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Affiliation(s)
- Karen Caeyenberghs
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, Australia.
| | - Phoebe Imms
- Ethel Percy Andrus Gerontology Center, Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA, USA.
| | - Andrei Irimia
- Ethel Percy Andrus Gerontology Center, Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA, USA; Alfred E. Mann Department of Biomedical Engineering, Andrew & Erna Viterbi School of Engineering, University of Southern California, Los Angeles, CA, USA; Department of Quantitative & Computational Biology, Dana and David Dornsife College of Arts & Sciences, University of Southern California, Los Angeles, CA, USA.
| | - Martin M Monti
- Department of Psychology, UCLA, USA; Brain Injury Research Center (BIRC), Department of Neurosurgery, UCLA, USA.
| | - Carrie Esopenko
- Department of Rehabilitation and Human Performance, Icahn School of Medicine at Mount Sinai, NY, USA.
| | - Nicola L de Souza
- Department of Rehabilitation and Human Performance, Icahn School of Medicine at Mount Sinai, NY, USA.
| | - Juan F Dominguez D
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, Australia.
| | - Mary R Newsome
- Michael E. DeBakey VA Medical Center, Houston, TX, USA; H. Ben Taub Department of Physical Medicine and Rehabilitation, Baylor College of Medicine, Houston, TX, USA; TBI and Concussion Center, Department of Neurology, University of Utah, Salt Lake City, UT, USA.
| | - Ekaterina Dobryakova
- Center for Traumatic Brain Injury, Kessler Foundation, East Hanover, NJ, USA; Rutgers New Jersey Medical School, Newark, NJ, USA.
| | - Andrew Cwiek
- Department of Psychology, Penn State University, State College, PA, USA.
| | - Hollie A C Mullin
- Department of Psychology, Penn State University, State College, PA, USA.
| | - Nicholas J Kim
- Ethel Percy Andrus Gerontology Center, Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA, USA; Alfred E. Mann Department of Biomedical Engineering, Andrew & Erna Viterbi School of Engineering, University of Southern California, Los Angeles, CA, USA.
| | - Andrew R Mayer
- Mind Research Network, Albuquerque, NM, USA; Departments of Neurology and Psychiatry, University of New Mexico School of Medicine, Albuquerque, NM, USA.
| | - Maheen M Adamson
- Women's Operational Military Exposure Network (WOMEN) & Rehabilitation Department, VA Palo Alto, Palo Alto, CA, USA; Rehabilitation Service, VA Palo Alto, Palo Alto, CA, USA; Neurosurgery, Stanford School of Medicine, Stanford, CA, USA.
| | - Kevin Bickart
- UCLA Steve Tisch BrainSPORT Program, USA; Department of Neurology, David Geffen School of Medicine at UCLA, USA.
| | - Katherine M Breedlove
- Center for Clinical Spectroscopy, Brigham and Women's Hospital, Boston, MA, USA; Department of Radiology, Harvard Medical School, Boston, MA, USA.
| | - Emily L Dennis
- TBI and Concussion Center, Department of Neurology, University of Utah, Salt Lake City, UT, USA; George E. Wahlen Veterans Affairs Medical Center, Salt Lake City, UT, USA.
| | - Seth G Disner
- Minneapolis VA Health Care System, Minneapolis, MN, USA; Department of Psychiatry and Behavioral Sciences, University of Minnesota Medical School, Minneapolis, MN, USA.
| | - Courtney Haswell
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA.
| | - Cooper B Hodges
- TBI and Concussion Center, Department of Neurology, University of Utah, Salt Lake City, UT, USA; George E. Wahlen Veterans Affairs Medical Center, Salt Lake City, UT, USA; Department of Psychology, Brigham Young University, Provo, UT, USA.
| | - Kristen R Hoskinson
- Center for Biobehavioral Health, The Abigail Wexner Research Institute at Nationwide Children's Hospital, Columbus, OH, USA; Department of Pediatrics, The Ohio State University College of Medicine, OH, USA.
| | - Paula K Johnson
- TBI and Concussion Center, Department of Neurology, University of Utah, Salt Lake City, UT, USA; Neuroscience Center, Brigham Young University, Provo, UT, USA.
| | - Marsh Königs
- Emma Children's Hospital, Amsterdam UMC, University of Amsterdam, Emma Neuroscience Group, The Netherlands; Amsterdam Reproduction and Development, Amsterdam, The Netherlands.
| | - Lucia M Li
- C3NL, Imperial College London, United Kingdom; UK DRI Centre for Health Care and Technology, Imperial College London, United Kingdom.
| | - Spencer W Liebel
- TBI and Concussion Center, Department of Neurology, University of Utah, Salt Lake City, UT, USA; George E. Wahlen Veterans Affairs Medical Center, Salt Lake City, UT, USA.
| | - Abigail Livny
- Division of Diagnostic Imaging, Sheba Medical Center, Tel-Hashomer, Israel; Sagol School of Neuroscience, Tel-Aviv University, Tel-Aviv, Israel; Sackler Faculty of Medicine, Tel-Aviv University, Tel-Aviv, Israel.
| | - Rajendra A Morey
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA; Duke-UNC Brain Imaging and Analysis Center, Duke University, Durham, NC, USA; VA Mid-Atlantic Mental Illness Research Education and Clinical Center, Durham, NC, USA.
| | - Alexandra M Muir
- Department of Psychology, Brigham Young University, Provo, UT, USA.
| | - Alexander Olsen
- Department of Psychology, Norwegian University of Science and Technology, Trondheim, Norway; Clinic of Rehabilitation, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway; NorHEAD - Norwegian Centre for Headache Research, Norwegian University of Science and Technology, Trondheim, Norway.
| | - Adeel Razi
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, VIC 3800, Australia; Wellcome Centre for Human Neuroimaging, University College London, WC1N 3AR London, United Kingdom; CIFAR Azrieli Global Scholars Program, CIFAR, Toronto, ON, Canada.
| | - Matthew Su
- H. Ben Taub Department of Physical Medicine and Rehabilitation, Baylor College of Medicine, Houston, TX, USA.
| | - David F Tate
- TBI and Concussion Center, Department of Neurology, University of Utah, Salt Lake City, UT, USA; George E. Wahlen Veterans Affairs Medical Center, Salt Lake City, UT, USA.
| | - Carmen Velez
- TBI and Concussion Center, Department of Neurology, University of Utah, Salt Lake City, UT, USA; George E. Wahlen Veterans Affairs Medical Center, Salt Lake City, UT, USA.
| | - Elisabeth A Wilde
- H. Ben Taub Department of Physical Medicine and Rehabilitation, Baylor College of Medicine, Houston, TX, USA; TBI and Concussion Center, Department of Neurology, University of Utah, Salt Lake City, UT, USA; George E. Wahlen Veterans Affairs Medical Center, Salt Lake City, UT, USA.
| | - Brandon A Zielinski
- Departments of Pediatrics, Neurology, and Neuroscience, University of Florida, Gainesville, FL, USA; Departments of Pediatrics, Neurology, and Radiology, University of Utah, Salt Lake City, UT, USA.
| | - Paul M Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging & Informatics Institute, University of Southern California, Marina del Rey, CA, USA.
| | - Frank G Hillary
- Department of Psychology, Penn State University, State College, PA, USA; Department of Neurology, Hershey Medical Center, PA, USA.
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13
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Samanci B, Tan S, Michielse S, Kuijf ML, Temel Y. The habenula in Parkinson's disease: Anatomy, function, and implications for mood disorders - A narrative review. J Chem Neuroanat 2024; 136:102392. [PMID: 38237746 DOI: 10.1016/j.jchemneu.2024.102392] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Revised: 01/07/2024] [Accepted: 01/12/2024] [Indexed: 01/31/2024]
Abstract
Parkinson's disease (PD), a widespread neurodegenerative disorder, often coexists with mood disorders. Degeneration of serotonergic neurons in brainstem raphe nuclei have been linked to depression and anxiety. Additionally, the locus coeruleus and its noradrenergic neurons are among the first areas to degenerate in PD and contribute to stress, emotional memory, motor, sensory, and autonomic symptoms. Another brain region of interest is habenula, which is especially related to anti-reward processing, and its function has recently been linked to PD and to mood-related symptoms. There are several neuroimaging studies that investigated role of the habenula in mood disorders. Differences in habenular size and hemispheric symmetry were found in healthy controls compared to individuals with mood disorders. The lateral habenula, as a link between the dopaminergic and serotonergic systems, is thought to contribute to depressive symptoms in PD. However, there is only one imaging study about role of habenula in mood disorders in PD, although the relationship between PD and mood disorders is known. There is little known about habenula pathology in PD but given these observations, the question arises whether habenular dysfunction could play a role in PD and the development of PD-related mood disorders. In this review, we evaluate neuroimaging techniques and studies that investigated the habenula in the context of PD and mood disorders. Future studies are important to understand habenula's role in PD patients with mood disorders. Thus, new potential diagnostic and treatment opportunities would be found for mood disorders in PD.
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Affiliation(s)
- Bedia Samanci
- School for Mental Health and Neurosciences, Maastricht University, Maastricht, the Netherlands; Behavioral Neurology and Movement Disorders Unit, Department of Neurology, Istanbul Faculty of Medicine, Istanbul University, Istanbul, Turkey.
| | - Sonny Tan
- School for Mental Health and Neurosciences, Maastricht University, Maastricht, the Netherlands; Department of Neurosurgery, Antwerp University Hospital, Edegem, Belgium
| | - Stijn Michielse
- School for Mental Health and Neurosciences, Maastricht University, Maastricht, the Netherlands
| | - Mark L Kuijf
- School for Mental Health and Neurosciences, Maastricht University, Maastricht, the Netherlands; Department of Neurology, Maastricht University Medical Centre, Maastricht, the Netherlands
| | - Yasin Temel
- School for Mental Health and Neurosciences, Maastricht University, Maastricht, the Netherlands; Department of Neurosurgery, Maastricht University Medical Centre, Maastricht, the Netherlands
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14
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Galvez V, Romero-Rebollar C, Estudillo-Guerra MA, Fernandez-Ruiz J. Resting-state networks and their relationship with MoCA performance in PD patients. Brain Imaging Behav 2024:10.1007/s11682-024-00860-3. [PMID: 38332386 DOI: 10.1007/s11682-024-00860-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/30/2024] [Indexed: 02/10/2024]
Abstract
Although mild cognitive impairment is a common non-motor symptom experienced by individuals with Parkinson's Disease, the changes in intrinsic resting-state networks associated with its onset in Parkinson's remain underexamined. To address the issue, our study sought to examine resting-state network alterations and their association with total performance in the Montreal Cognitive Assessment and its cognitive domains in Parkinson's by means of functional magnetic resonance imaging of 29 Parkinson's patients with normal cognition, 25 Parkinson's patients with mild cognitive impairment, and 13 healthy controls. To contrast the Parkinson's groups with each other and the controls, the images were used to estimate the Z-score coefficient between the regions of interest from the default mode network, the salience network and the central executive network. Our first finding was that default mode and salience network connectivity decreased significantly in Parkinson's patients regardless of their cognitive status. Additionally, default mode network nodes had a negative and salience network nodes a positive correlation with the global assessment in Parkinson's with normal cognition; this inverse relationship of both networks to total score was not found in the group with cognitive impairment. Finally, a positive correlation was found between executive scores and anterior and posterior cortical network connectivity and, in the group with cognitive impairment, between language scores and salience network connectivity. Our results suggest that specific resting-state networks of Parkinson's patients with cognitive impairment differ from those of Parkinson's patients with normal cognition, supporting the evidence that cognitive impairment in Parkinson's Disease displays a differentiated neurodegenerative pattern.
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Affiliation(s)
- Victor Galvez
- Laboratorio de Neurociencias Cognitivas y Desarrollo, Escuela de Psicología, Universidad Panamericana, Ciudad de México, México.
| | - César Romero-Rebollar
- Escuela de Pedagogía, Universidad Panamericana, Ciudad de México, México
- Universidad Tecnológica de México-UNITEC MÉXICO-Campus en línea, Ciudad de México, México
| | - M Anayali Estudillo-Guerra
- Spaulding Rehabilitation Hospital and Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Juan Fernandez-Ruiz
- Departamento de Fisiología, Facultad de Medicina, Universidad Nacional Autónoma de México, Ciudad de México, México
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15
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Theis H, Pavese N, Rektorová I, van Eimeren T. Imaging Biomarkers in Prodromal and Earliest Phases of Parkinson's Disease. JOURNAL OF PARKINSON'S DISEASE 2024:JPD230385. [PMID: 38339941 DOI: 10.3233/jpd-230385] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/12/2024]
Abstract
Assessing imaging biomarker in the prodromal and early phases of Parkinson's disease (PD) is of great importance to ensure an early and safe diagnosis. In the last decades, imaging modalities advanced and are now able to assess many different aspects of neurodegeneration in PD. MRI sequences can measure iron content or neuromelanin. Apart from SPECT imaging with Ioflupane, more specific PET tracers to assess degeneration of the dopaminergic system are available. Furthermore, metabolic PET patterns can be used to anticipate a phenoconversion from prodromal PD to manifest PD. In this regard, it is worth mentioning that PET imaging of inflammation will gain significance. Molecular imaging of neurotransmitters like serotonin, noradrenaline and acetylcholine shed more light on non-motor symptoms. Outside of the brain, molecular imaging of the heart and gut is used to measure PD-related degeneration of the autonomous nervous system. Moreover, optical coherence tomography can noninvasively detect degeneration of retinal fibers as a potential biomarker in PD. In this review, we describe these state-of-the-art imaging modalities in early and prodromal PD and point out in how far these techniques can and will be used in the future to pave the way towards a biomarker-based staging of PD.
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Affiliation(s)
- Hendrik Theis
- University of Cologne, Faculty of Medicine and University Hospital Cologne, Department of Nuclear Medicine, Multimodal Neuroimaging Group, Cologne, Germany
- University of Cologne, Faculty of Medicine and University Hospital Cologne, Department of Neurology, Cologne, Germany
| | - Nicola Pavese
- Aarhus University, Institute of Clinical Medicine, Department of Nuclear Medicine & PET, Aarhus N, Denmark
- Newcastle University, Translational and Clinical Research Institute, Newcastle upon Tyne, United Kingdom
| | - Irena Rektorová
- Masaryk University, Faculty of Medicine and St. Anne's University Hospital, International Clinical Research Center, ICRC, Brno, Czech Republic
- Masaryk University, Faculty of Medicine and St. Anne's University Hospital, First Department of Neurology, Brno, Czech Republic
- Masaryk University, Applied Neuroscience Research Group, Central European Institute of Technology - CEITEC, Brno, Czech Republic
| | - Thilo van Eimeren
- University of Cologne, Faculty of Medicine and University Hospital Cologne, Department of Nuclear Medicine, Multimodal Neuroimaging Group, Cologne, Germany
- University of Cologne, Faculty of Medicine and University Hospital Cologne, Department of Neurology, Cologne, Germany
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16
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De Micco R, Di Nardo F, Siciliano M, Silvestro M, Russo A, Cirillo M, Tedeschi G, Esposito F, Tessitore A. Intrinsic brain functional connectivity predicts treatment-related motor complications in early Parkinson's disease patients. J Neurol 2024; 271:826-834. [PMID: 37814131 PMCID: PMC10827831 DOI: 10.1007/s00415-023-12020-6] [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: 05/28/2023] [Revised: 09/09/2023] [Accepted: 09/19/2023] [Indexed: 10/11/2023]
Abstract
BACKGROUND Treatment-related motor complications may develop progressively over the course of Parkinson's disease (PD). OBJECTIVE We investigated intrinsic brain networks functional connectivity (FC) at baseline in a cohort of early PD patients which successively developed treatment-related motor complications over 4 years. METHODS Baseline MRI images of 88 drug-naïve PD patients and 20 healthy controls were analyzed. After the baseline assessments, all PD patients were prescribed with dopaminergic treatment and yearly clinically re-assessed. At the 4-year follow-up, 36 patients have developed treatment-related motor complications (PD-Compl) whereas 52 had not (PD-no-Compl). Single-subject and group-level independent component analyses were used to investigate FC changes within the major large-scale resting-state networks at baseline. A multivariate Cox regression model was used to explore baseline predictors of treatment-related motor complications at 4-year follow-up. RESULTS At baseline, an increased FC in the right middle frontal gyrus within the frontoparietal network as well as a decreased connectivity in the left cuneus within the default-mode network were detected in PD-Compl compared with PD-no-Compl. PD-Compl patients showed a preserved sensorimotor FC compared to controls. FC differences were found to be independent predictors of treatment-related motor complications over time. CONCLUSION Our findings demonstrated that specific FC differences may characterize drug-naïve PD patients more prone to develop treatment-related complications. These findings may reflect the presence of an intrinsic vulnerability across frontal and prefrontal circuits, which may be potentially targeted as a future biomarker in clinical trials.
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Affiliation(s)
- Rosa De Micco
- Department of Advanced Medical and Surgical Sciences, University of Campania "Luigi Vanvitelli", Naples, Italy
| | - Federica Di Nardo
- Department of Advanced Medical and Surgical Sciences, University of Campania "Luigi Vanvitelli", Naples, Italy
| | - Mattia Siciliano
- Department of Advanced Medical and Surgical Sciences, University of Campania "Luigi Vanvitelli", Naples, Italy
- Neuropsychology Laboratory, Department of Psychology, University of Campania "Luigi Vanvitelli", Caserta, Italy
| | - Marcello Silvestro
- Department of Advanced Medical and Surgical Sciences, University of Campania "Luigi Vanvitelli", Naples, Italy
| | - Antonio Russo
- Department of Advanced Medical and Surgical Sciences, University of Campania "Luigi Vanvitelli", Naples, Italy
| | - Mario Cirillo
- Department of Advanced Medical and Surgical Sciences, University of Campania "Luigi Vanvitelli", Naples, Italy
| | - Gioacchino Tedeschi
- Department of Advanced Medical and Surgical Sciences, University of Campania "Luigi Vanvitelli", Naples, Italy
| | - Fabrizio Esposito
- Department of Advanced Medical and Surgical Sciences, University of Campania "Luigi Vanvitelli", Naples, Italy
| | - Alessandro Tessitore
- Department of Advanced Medical and Surgical Sciences, University of Campania "Luigi Vanvitelli", Naples, Italy.
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Fiorenzato E, Moaveninejad S, Weis L, Biundo R, Antonini A, Porcaro C. Brain Dynamics Complexity as a Signature of Cognitive Decline in Parkinson's Disease. Mov Disord 2024; 39:305-317. [PMID: 38054573 DOI: 10.1002/mds.29678] [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: 07/26/2023] [Revised: 11/13/2023] [Accepted: 11/17/2023] [Indexed: 12/07/2023] Open
Abstract
BACKGROUND Higuchi's fractal dimension (FD) captures brain dynamics complexity and may be a promising method to analyze resting-state functional magnetic resonance imaging (fMRI) data and detect the neuronal interaction complexity underlying Parkinson's disease (PD) cognitive decline. OBJECTIVES The aim was to compare FD with a more established index of spontaneous neural activity, the fractional amplitude of low-frequency fluctuations (fALFF), and identify through machine learning (ML) models which method could best distinguish across PD-cognitive states, ranging from normal cognition (PD-NC), mild cognitive impairment (PD-MCI) to dementia (PDD). Finally, the aim was to explore correlations between fALFF and FD with clinical and cognitive PD features. METHODS Among 118 PD patients age-, sex-, and education matched with 35 healthy controls, 52 were classified with PD-NC, 46 with PD-MCI, and 20 with PDD based on an extensive cognitive and clinical evaluation. fALFF and FD metrics were computed on rs-fMRI data and used to train ML models. RESULTS FD outperformed fALFF metrics in differentiating between PD-cognitive states, reaching an overall accuracy of 78% (vs. 62%). PD showed increased neuronal dynamics complexity within the sensorimotor network, central executive network (CEN), and default mode network (DMN), paralleled by a reduction in spontaneous neuronal activity within the CEN and DMN, whose increased complexity was strongly linked to the presence of dementia. Further, we found that some DMN critical hubs correlated with worse cognitive performance and disease severity. CONCLUSIONS Our study indicates that PD-cognitive decline is characterized by an altered spontaneous neuronal activity and increased temporal complexity, involving the CEN and DMN, possibly reflecting an increased segregation of these networks. Therefore, we propose FD as a prognostic biomarker of PD-cognitive decline. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Eleonora Fiorenzato
- Parkinson's Disease and Movement Disorders Unit, Department of Neuroscience, Centre for Rare Neurological Diseases (ERN-RND), University of Padova, Padova, Italy
| | - Sadaf Moaveninejad
- Department of Neuroscience and Padova Neuroscience Center, University of Padua, Padua, Italy
| | - Luca Weis
- Parkinson's Disease and Movement Disorders Unit, Department of Neuroscience, Centre for Rare Neurological Diseases (ERN-RND), University of Padova, Padova, Italy
- IRCCS, San Camillo Hospital, Venice, Italy
| | - Roberta Biundo
- Parkinson's Disease and Movement Disorders Unit, Department of Neuroscience, Centre for Rare Neurological Diseases (ERN-RND), University of Padova, Padova, Italy
- Department of Neuroscience, Center for Neurodegenerative Disease Research (CESNE), University of Padova, Padova, Italy
- Department of General Psychology, University of Padua, Padua, Italy
| | - Angelo Antonini
- Parkinson's Disease and Movement Disorders Unit, Department of Neuroscience, Centre for Rare Neurological Diseases (ERN-RND), University of Padova, Padova, Italy
- Department of Neuroscience and Padova Neuroscience Center, University of Padua, Padua, Italy
- Department of Neuroscience, Center for Neurodegenerative Disease Research (CESNE), University of Padova, Padova, Italy
| | - Camillo Porcaro
- Department of Neuroscience and Padova Neuroscience Center, University of Padua, Padua, Italy
- Institute of Cognitive Sciences and Technologies-National Research Council, Rome, Italy
- Centre for Human Brain Health and School of Psychology, University of Birmingham, Birmingham, United Kingdom
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18
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Zeng Y, Ye Z, Zheng W, Wang J. Efficacy of Cerebellar Transcranial Magnetic Stimulation for Post-stroke Balance and Limb Motor Function Impairments: Meta-analyses of Random Controlled Trials and Resting-State fMRI Studies. CEREBELLUM (LONDON, ENGLAND) 2024:10.1007/s12311-024-01660-7. [PMID: 38280142 DOI: 10.1007/s12311-024-01660-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 01/16/2024] [Indexed: 01/29/2024]
Abstract
This study aimed to investigate the potential therapeutic effects of cerebellar transcranial magnetic stimulation (TMS) on balance and limb motor impairments in stroke patients. A meta-analysis of randomized controlled trials was conducted to assess the effects of cerebellar TMS on balance and motor impairments in stroke patients. Additionally, an activation likelihood estimation (ALE) meta-analysis was performed on resting-state functional magnetic resonance imaging (fMRI) studies to compare spontaneous neural activity differences between stroke patients and healthy controls using measures including the amplitude of low frequency fluctuation (ALFF), fractional ALFF (fALFF), and regional homogeneity (ReHo). The analysis included 10 cerebellar TMS studies and 18 fMRI studies. Cerebellar TMS treatment demonstrated significant improvements in the Berg Balance Scale score (p < 0.0001) and the Fugl-Meyer Assessment lower extremity score (p < 0.0001) compared to the control group in stroke patients. Additionally, spontaneous neural activity alterations were identified in motor-related regions after stroke, including the precentral gyrus, putamen, thalamus, and paracentral lobule. Cerebellar TMS shows promise as a therapeutic intervention to enhance balance and lower limb motor function in stroke patients. It is easy for clinical application and addresses the limitations of insufficient direct stimulation depth on the leg area of the cortex. However, further research combining neuroimaging outcomes with clinical measurements is necessary to validate these findings.
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Affiliation(s)
- Yuheng Zeng
- Institute of Sports Medicine and Health, Chengdu Sport University, Chengdu, 610041, China.
| | - Zujuan Ye
- Institute of Sports Medicine and Health, Chengdu Sport University, Chengdu, 610041, China
| | - Wanxin Zheng
- Department of Genome Medicine, Tokyo Metropolitan Institute of Medical Science, Tokyo, 156-8506, Japan
| | - Jue Wang
- Institute of Sports Medicine and Health, Chengdu Sport University, Chengdu, 610041, China
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Hajebrahimi F, Budak M, Saricaoglu M, Temel Z, Demir TK, Hanoglu L, Yildirim S, Bayraktaroglu Z. Functional neural networks stratify Parkinson's disease patients across the spectrum of cognitive impairment. Brain Behav 2024; 14:e3395. [PMID: 38376051 PMCID: PMC10808882 DOI: 10.1002/brb3.3395] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/28/2023] [Revised: 11/23/2023] [Accepted: 12/26/2023] [Indexed: 02/21/2024] Open
Abstract
INTRODUCTION Cognitive impairment (CI) is a significant non-motor symptoms in Parkinson's disease (PD) that often precedes the emergence of motor symptoms by several years. Patients with PD hypothetically progress from stages without CI (PD-normal cognition [NC]) to stages with Mild CI (PD-MCI) and PD dementia (PDD). CI symptoms in PD are linked to different brain regions and neural pathways, in addition to being the result of dysfunctional subcortical regions. However, it is still unknown how functional dysregulation correlates to progression during the CI. Neuroimaging techniques hold promise in discriminating CI stages of PD and further contribute to the biomarker formation of CI in PD. In this study, we explore disparities in the clinical assessments and resting-state functional connectivity (FC) among three CI stages of PD. METHODS We enrolled 88 patients with PD and 26 healthy controls (HC) for a cross sectional clinical study and performed intra- and inter-network FC analysis in conjunction with comprehensive clinical cognitive assessment. RESULTS Our findings underscore the significance of several neural networks, namely, the default mode network (DMN), frontoparietal network (FPN), dorsal attention network, and visual network (VN) and their inter-intra-network FC in differentiating between PD-MCI and PDD. Additionally, our results showed the importance of sensory motor network, VN, DMN, and salience network (SN) in the discriminating PD-NC from PDD. Finally, in comparison to HC, we found DMN, FPN, VN, and SN as pivotal networks for further differential diagnosis of CI stages of PD. CONCLUSION We propose that resting-state networks (RSN) can be a discriminating factor in distinguishing the CI stages of PD and progressing from PD-NC to MCI or PDD. The integration of clinical and neuroimaging data may enhance the early detection of PD in clinical settings and potentially prevent the disease from advancing to more severe stages.
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Affiliation(s)
- Farzin Hajebrahimi
- Functional Imaging and Cognitive‐Affective Neuroscience Lab (fINCAN), Research Institute for Health Sciences and Technologies (SABITA)Istanbul Medipol UniversityIstanbulTurkey
- Department of Physical Therapy and Rehabilitation, School of Health SciencesIstanbul Medipol UniversityIstanbulTurkey
- Department of Health Informatics, Rutgers University, School of Health ProfessionsRutgers Biomedical and Health SciencesNewarkNew JerseyUSA
| | - Miray Budak
- Functional Imaging and Cognitive‐Affective Neuroscience Lab (fINCAN), Research Institute for Health Sciences and Technologies (SABITA)Istanbul Medipol UniversityIstanbulTurkey
- Department of Ergotherapy, School of Health SciencesIstanbul Medipol UniversityIstanbulTurkey
- Center for Molecular and Behavioral NeuroscienceRutgers University‐NewarkNewarkNew JerseyUSA
| | - Mevhibe Saricaoglu
- Functional Imaging and Cognitive‐Affective Neuroscience Lab (fINCAN), Research Institute for Health Sciences and Technologies (SABITA)Istanbul Medipol UniversityIstanbulTurkey
- Program of Electroneurophysiology, Vocational SchoolIstanbul Medipol UniversityIstanbulTurkey
| | - Zeynep Temel
- Department of PsychologyFatih Sultan Mehmet Vakif UniversityIstanbulTurkey
| | - Tugce Kahraman Demir
- Program of Electroneurophysiology, Vocational SchoolBiruni UniversityIstanbulTurkey
| | - Lutfu Hanoglu
- Department of Neurology, School of MedicineIstanbul Medipol UniversityIstanbulTurkey
- Regenerative and Restorative Medicine Research Center (REMER), Research Institute for Health Sciences and Technologies (SABITA)Istanbul Medipol UniversityIstanbulTurkey
| | - Suleyman Yildirim
- Regenerative and Restorative Medicine Research Center (REMER), Research Institute for Health Sciences and Technologies (SABITA)Istanbul Medipol UniversityIstanbulTurkey
- Department of Medical Microbiology, International School of MedicineIstanbul Medipol UniversityIstanbulTurkey
| | - Zubeyir Bayraktaroglu
- Functional Imaging and Cognitive‐Affective Neuroscience Lab (fINCAN), Research Institute for Health Sciences and Technologies (SABITA)Istanbul Medipol UniversityIstanbulTurkey
- Regenerative and Restorative Medicine Research Center (REMER), Research Institute for Health Sciences and Technologies (SABITA)Istanbul Medipol UniversityIstanbulTurkey
- Department of Physiology, International School of MedicineIstanbul Medipol UniversityIstanbulTurkey
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20
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Güllüoğlu H, Hünerli D, Çakmur R, Çolakoğlu BD, Ada E, Yener G. Structural and Functional Changes in Mild Cognitive Impairment in Parkinson's Disease. MEDICINA (KAUNAS, LITHUANIA) 2023; 60:33. [PMID: 38256295 PMCID: PMC10817693 DOI: 10.3390/medicina60010033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/22/2023] [Revised: 12/20/2023] [Accepted: 12/22/2023] [Indexed: 01/24/2024]
Abstract
Background and Objectives: The pathophysiology of mild cognitive impairment in Parkinson's disease (PD-MCI) is still not fully elucidated. It has been shown in a few studies in the literature that volume loss in the occipital, parietal and frontal cortices and atrophy in the hippocampus of PD-MCI patients can occur in the early stages of PD. The aim of this study was to evaluate the relationship between gray and white matter volumes and different neuropsychological tests and volumetric magnetic resonance imaging parameters in patients with mild cognitive impairment in Parkinson's disease (PD-MCI). Materials and Methods: Twenty-six PD-MCI and twenty-six healthy elderly (HC) were included in this study. Results: We found that Mini Mental State Examination, Trail Making Test Part A, Clock Drawing Test, Benton Line Judgment Orientation Test and pentagon figure-copying scores were impaired in PD-MCI patients due to the decrease in brain volumes. Conclusions: Our study revealed that among PD-MCI patients, there was a more noticeable decline in White matter volume (WMV) based on volumetric Magnetic Resonance Imaging (MRI) compared to the localized loss of GMV. We think that these abnormal neuropsychological tests in PD-MCI patients can be used as pretests in the evaluation of the stage of transition to dementia.
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Affiliation(s)
- Halil Güllüoğlu
- Department of Neurology, Izmir Ekonomi University Medical Point Hospital, Izmir 35080, Turkey
| | - Duygu Hünerli
- Department of Neuroscience, Dokuz Eylul University Institute Health Sciences, Izmir 35210, Turkey;
| | - Raif Çakmur
- Department of Neurology, Dokuz Eylul University School of Medicine, Izmir 35210, Turkey; (R.Ç.); (B.D.Ç.)
| | - Berril Dönmez Çolakoğlu
- Department of Neurology, Dokuz Eylul University School of Medicine, Izmir 35210, Turkey; (R.Ç.); (B.D.Ç.)
| | - Emel Ada
- Department of Radiology, Dokuz Eylul University School of Medicine, Izmir 35210, Turkey;
| | - Görsev Yener
- Izmir Biomedicine and Genome Center, Izmir 35340, Turkey;
- Department of Neurolohy, Faculty of Medicine, Izmir University of Economics, Izmir 35330, Turkey
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21
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Conti M, Guerra A, Pierantozzi M, Bovenzi R, D'Onofrio V, Simonetta C, Cerroni R, Liguori C, Placidi F, Mercuri NB, Di Giuliano F, Schirinzi T, Stefani A. Band-Specific Altered Cortical Connectivity in Early Parkinson's Disease and its Clinical Correlates. Mov Disord 2023; 38:2197-2208. [PMID: 37860930 DOI: 10.1002/mds.29615] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2023] [Revised: 08/25/2023] [Accepted: 09/11/2023] [Indexed: 10/21/2023] Open
Abstract
BACKGROUND Functional connectivity (FC) has shown promising results in assessing the pathophysiology and identifying early biomarkers of neurodegenerative disorders, such as Parkinson's disease (PD). OBJECTIVES In this study, we aimed to assess possible resting-state FC abnormalities in early-stage PD patients using high-density electroencephalography (EEG) and to detect their clinical relationship with motor and non-motor PD symptoms. METHODS We enrolled 26 early-stage levodopa naïve PD patients and a group of 20 healthy controls (HC). Data were recorded with 64-channels EEG system and a source-reconstruction method was used to identify brain-region activity. FC was calculated using the weighted phase-lag index in θ, α, and β bands. Additionally, we quantified the unbalancing between β and lower frequencies through a novel index (β-functional ratio [FR]). Statistical analysis was conducted using a network-based statistical approach. RESULTS PD patients showed hypoconnected networks in θ and α band, involving prefrontal-limbic-temporal and frontoparietal areas, respectively, and a hyperconnected network in the β frequency band, involving sensorimotor-frontal areas. The θ FC network was negatively related to Non-Motor Symptoms Scale scores and α FC to the Movement Disorder Society-Sponsored Revision of the Unified Parkinson's Disease Rating Scale part III gait subscore, whereas β FC and β-FR network were positively linked to the bradykinesia subscore. Changes in θ FC and β-FR showed substantial reliability and high accuracy, precision, sensitivity, and specificity in discriminating PD and HC. CONCLUSIONS Frequency-specific FC changes in PD likely reflect the dysfunction of distinct cortical networks, which occur from the early stage of the disease. These abnormalities are involved in the pathophysiology of specific motor and non-motor PD symptoms, including gait, bradykinesia, mood, and cognition. © 2023 International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Matteo Conti
- Parkinson Centre, Department of Systems Medicine, University of Rome "Tor Vergata", Rome, Italy
| | - Andrea Guerra
- Parkinson and Movement Disorders Unit, Study Centre on Neurodegeneration (CESNE), Department of Neuroscience, University of Padova, Padua, Italy
| | - Mariangela Pierantozzi
- Parkinson Centre, Department of Systems Medicine, University of Rome "Tor Vergata", Rome, Italy
- Neurology Unit, Department of Systems Medicine, University of Rome "Tor Vergata", Rome, Italy
| | - Roberta Bovenzi
- Parkinson Centre, Department of Systems Medicine, University of Rome "Tor Vergata", Rome, Italy
| | - Valentina D'Onofrio
- Parkinson and Movement Disorders Unit, Study Centre on Neurodegeneration (CESNE), Department of Neuroscience, University of Padova, Padua, Italy
| | - Clara Simonetta
- Neurology Unit, Department of Systems Medicine, University of Rome "Tor Vergata", Rome, Italy
| | - Rocco Cerroni
- Parkinson Centre, Department of Systems Medicine, University of Rome "Tor Vergata", Rome, Italy
| | - Claudio Liguori
- Neurology Unit, Department of Systems Medicine, University of Rome "Tor Vergata", Rome, Italy
| | - Fabio Placidi
- Neurology Unit, Department of Systems Medicine, University of Rome "Tor Vergata", Rome, Italy
| | - Nicola Biagio Mercuri
- Neurology Unit, Department of Systems Medicine, University of Rome "Tor Vergata", Rome, Italy
| | - Francesca Di Giuliano
- Neuroradiology Unit, Department of Biomedicine and Prevention, University of Rome "Tor Vergata", Rome, Italy
| | - Tommaso Schirinzi
- Neurology Unit, Department of Systems Medicine, University of Rome "Tor Vergata", Rome, Italy
| | - Alessandro Stefani
- Parkinson Centre, Department of Systems Medicine, University of Rome "Tor Vergata", Rome, Italy
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22
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Bachrata B, Bollmann S, Jin J, Tourell M, Dal-Bianco A, Trattnig S, Barth M, Ropele S, Enzinger C, Robinson SD. Super-resolution QSM in little or no additional time for imaging (NATIve) using 2D EPI imaging in 3 orthogonal planes. Neuroimage 2023; 283:120419. [PMID: 37871759 DOI: 10.1016/j.neuroimage.2023.120419] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Revised: 09/22/2023] [Accepted: 10/20/2023] [Indexed: 10/25/2023] Open
Abstract
Quantitative Susceptibility Mapping has the potential to provide additional insights into neurological diseases but is typically based on a quite long (5-10 min) 3D gradient-echo scan which is highly sensitive to motion. We propose an ultra-fast acquisition based on three orthogonal (sagittal, coronal and axial) 2D simultaneous multi-slice EPI scans with 1 mm in-plane resolution and 3 mm thick slices. Images in each orientation are corrected for susceptibility-related distortions and co-registered with an iterative non-linear Minimum Deformation Averaging (Volgenmodel) approach to generate a high SNR, super-resolution data set with an isotropic resolution of close to 1 mm. The net acquisition time is 3 times the volume acquisition time of EPI or about 12 s, but the three volumes could also replace "dummy scans" in fMRI, making it feasible to acquire QSM in little or No Additional Time for Imaging (NATIve). NATIve QSM values agreed well with reference 3D GRE QSM in the basal ganglia in healthy subjects. In patients with multiple sclerosis, there was also a good agreement between the susceptibility values within lesions and control ROIs and all lesions which could be seen on 3D GRE QSMs could also be visualized on NATIve QSMs. The approach is faster than conventional 3D GRE by a factor of 25-50 and faster than 3D EPI by a factor of 3-5. As a 2D technique, NATIve QSM was shown to be much more robust to motion than the 3D GRE and 3D EPI, opening up the possibility of studying neurological diseases involving iron accumulation and demyelination in patients who find it difficult to lie still for long enough to acquire QSM data with conventional methods.
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Affiliation(s)
- Beata Bachrata
- High Field MR Centre, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Austria; Karl Landsteiner Institute for Clinical Molecular MR in Musculoskeletal Imaging, Vienna, Austria; Department of Medical Engineering, Carinthia University of Applied Sciences, Klagenfurt, Austria
| | - Steffen Bollmann
- Centre of Advanced Imaging, University of Queensland, Brisbane, Australia; ARC Training Centre for Innovation in Biomedical Imaging Technology, University of Queensland, Brisbane, Australia; School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane, Australia
| | - Jin Jin
- Centre of Advanced Imaging, University of Queensland, Brisbane, Australia; Siemens Healthcare Pty Ltd, Australia
| | - Monique Tourell
- Centre of Advanced Imaging, University of Queensland, Brisbane, Australia; ARC Training Centre for Innovation in Biomedical Imaging Technology, University of Queensland, Brisbane, Australia
| | - Assunta Dal-Bianco
- Department of Neurology, Medical University of Vienna, Austria; Comprehensive Center for Clinical Neurosciences and Mental Health, Medical University of Vienna, Austria
| | - Siegfried Trattnig
- High Field MR Centre, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Austria; Karl Landsteiner Institute for Clinical Molecular MR in Musculoskeletal Imaging, Vienna, Austria
| | - Markus Barth
- Centre of Advanced Imaging, University of Queensland, Brisbane, Australia; ARC Training Centre for Innovation in Biomedical Imaging Technology, University of Queensland, Brisbane, Australia; School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane, Australia
| | - Stefan Ropele
- Department of Neurology, Medical University of Graz, Austria
| | | | - Simon Daniel Robinson
- High Field MR Centre, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Austria; Centre of Advanced Imaging, University of Queensland, Brisbane, Australia; Department of Neurology, Medical University of Graz, Austria.
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23
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Sousa NMF, Diniz JDFG, Galvão AP, Brucki SMD. Cognitive profile of patients with and without speech impairment in Parkinson's disease. Dement Neuropsychol 2023; 17:e20220093. [PMID: 38028381 PMCID: PMC10666554 DOI: 10.1590/1980-5764-dn-2022-0093] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2022] [Revised: 08/28/2023] [Accepted: 09/04/2023] [Indexed: 12/01/2023] Open
Abstract
Cognitive functions have been the subject of studies evaluating the pathophysiological mechanism of speech control. Objective To compare the groups of patients with and without speech disorders with cognitive assessment, demographic, and clinical data (disease duration, functionality, and motor symptoms). Methods Retrospective, cross-sectional study. Patients were evaluated using the Addenbrooke's Cognitive Examination III and neuropsychological tests. The following speech subsystems were analyzed: articulation, phonation, resonance, and prosody, through auditory-perceptual evaluation (based on the Protocol for the Evaluation of Acquired Speech Disorders in Individuals with Parkinson's Disease - PADAF Protocol tests), observing aspects of speech programming and execution. The patients were distributed into three subgroups (normal cognition, mild cognitive impairment, and dementia). After speech evaluation, they were divided into two subgroups (with and without speech disorders). Results A total of 150 patients participated in this study, 104 men and 46 women, 63.58 (8.81) years of age, 11.03 (4.00) years of schooling, 6.61 (4.69) years of disease progression, and with the highest proportion of individuals in stage I-II of the Hoehn & Yarh (H&Y) scale (86, or 57.33%). Statistically significant differences were observed between subgroups with and without speech alteration. Worse performance was verified in the Trail Making Test (TMT) TMT-Δ and a tendency of difference in the TMT-B of the subgroup with speech disorders, in addition to worse severity of motor symptoms (H&Y) and cognitive complaints. Conclusion Individuals with speech disorders brought more frequent cognitive complaints and impairment below expected in tests assessing executive functions. Future studies, with stratification by type of speech disorder, are necessary to contribute to and validate these results.
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Affiliation(s)
| | | | | | - Sonia Maria Dozzi Brucki
- Universidade de São Paulo, Faculdade de Medicina, Departamento de Neurologia, São Paulo SP, Brazil
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24
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Novikov NI, Brazhnik ES, Kitchigina VF. Pathological Correlates of Cognitive Decline in Parkinson's Disease: From Molecules to Neural Networks. BIOCHEMISTRY. BIOKHIMIIA 2023; 88:1890-1904. [PMID: 38105206 DOI: 10.1134/s0006297923110172] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Revised: 09/22/2023] [Accepted: 09/22/2023] [Indexed: 12/19/2023]
Abstract
Parkinson's disease (PD) is a progressive neurodegenerative disorder caused by the death of dopaminergic neurons in the substantia nigra and appearance of protein aggregates (Lewy bodies) consisting predominantly of α-synuclein in neurons. PD is currently recognized as a multisystem disorder characterized by severe motor impairments and various non-motor symptoms. Cognitive decline is one of the most common and worrisome non-motor symptoms. Moderate cognitive impairments (CI) are diagnosed already at the early stages of PD, usually transform into dementia. The main types of CI in PD include executive dysfunction, attention and memory decline, visuospatial impairments, and verbal deficits. According to the published data, the following mechanisms play an essential role demonstrates a crucial importance in the decline of the motor and cognitive functions in PD: (1) changes in the conformational structure of transsynaptic proteins and protein aggregation in presynapses; (2) synaptic transmission impairment; (3) neuroinflammation (pathological activation of the neuroglia); (4) mitochondrial dysfunction and oxidative stress; (5) metabolic disorders (hypometabolism of glucose, dysfunction of glycolipid metabolism; and (6) functional rearrangement of neuronal networks. These changes can lead to the death of dopaminergic cells in the substantia nigra and affect the functioning of other neurotransmitter systems, thus disturbing neuronal networks involved in the transmission of information related to the regulation of motor activity and cognitive functions. Identification of factors causing detrimental changes in PD and methods for their elimination will help in the development of new approaches to the therapy of PD. The goal of this review was to analyze pathological processes that take place in the brain and underlie the onset of cognitive disorders in PD, as well as to describe the impairments of cognitive functions in this disease.
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Affiliation(s)
- Nikolai I Novikov
- Institute of Theoretical and Experimental Biophysics, Russian Academy of Sciences, Pushchino, Moscow Region, 142290, Russia
| | - Elena S Brazhnik
- Institute of Theoretical and Experimental Biophysics, Russian Academy of Sciences, Pushchino, Moscow Region, 142290, Russia
| | - Valentina F Kitchigina
- Institute of Theoretical and Experimental Biophysics, Russian Academy of Sciences, Pushchino, Moscow Region, 142290, Russia.
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25
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Li H, Shi H, Jiang S, Hou C, Wu H, Yao G, Yao D, Luo C. Atypical Hierarchical Connectivity Revealed by Stepwise Functional Connectivity in Aging. Bioengineering (Basel) 2023; 10:1166. [PMID: 37892896 PMCID: PMC10604600 DOI: 10.3390/bioengineering10101166] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Revised: 09/18/2023] [Accepted: 09/30/2023] [Indexed: 10/29/2023] Open
Abstract
Hierarchical functional structure plays a crucial role in brain function. We aimed to investigate how aging affects hierarchical functional structure and to evaluate the relationship between such effects and molecular, microvascular, and cognitive features. We used resting-state functional magnetic resonance imaging (fMRI) data from 95 older adults (66.94 ± 7.23 years) and 44 younger adults (21.8 ± 2.53 years) and employed an innovative graph-theory-based analysis (stepwise functional connectivity (SFC)) to reveal the effects of aging on hierarchical functional structure in the brain. In the older group, an SFC pattern converged on the primary sensory-motor network (PSN) rather than the default mode network (DMN). Moreover, SFC decreased in the DMN and increased in the PSN at longer link-steps in aging, indicating a reconfiguration of brain hub systems during aging. Subsequent correlation analyses were performed between SFC values and molecular, microvascular features, and behavioral performance. Altered SFC patterns were associated with dopamine and serotonin, suggesting that altered hierarchical functional structure in aging is linked to the molecular fundament with dopamine and serotonin. Furthermore, increased SFC in the PSN, decreased SFC in the DMN, and accelerated convergence rate were all linked to poorer microvascular features and lower executive function. Finally, a mediation analysis among SFC features, microvascular features, and behavioral performance indicated that the microvascular state may influence executive function through SFC features, highlighting the interactive effects of SFC features and microvascular state on cognition.
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Affiliation(s)
- Hechun Li
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China; (H.L.); (H.S.); (S.J.); (C.H.); (H.W.); (D.Y.)
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China
| | - Hongru Shi
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China; (H.L.); (H.S.); (S.J.); (C.H.); (H.W.); (D.Y.)
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China
| | - Sisi Jiang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China; (H.L.); (H.S.); (S.J.); (C.H.); (H.W.); (D.Y.)
- Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, 2019RU035, Chengdu 610054, China
| | - Changyue Hou
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China; (H.L.); (H.S.); (S.J.); (C.H.); (H.W.); (D.Y.)
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China
| | - Hanxi Wu
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China; (H.L.); (H.S.); (S.J.); (C.H.); (H.W.); (D.Y.)
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China
| | - Gang Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China; (H.L.); (H.S.); (S.J.); (C.H.); (H.W.); (D.Y.)
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China; (H.L.); (H.S.); (S.J.); (C.H.); (H.W.); (D.Y.)
- Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, 2019RU035, Chengdu 610054, China
| | - Cheng Luo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China; (H.L.); (H.S.); (S.J.); (C.H.); (H.W.); (D.Y.)
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China
- Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, 2019RU035, Chengdu 610054, China
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26
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Barbero JA, Unadkat P, Choi YY, Eidelberg D. Functional Brain Networks to Evaluate Treatment Responses in Parkinson's Disease. Neurotherapeutics 2023; 20:1653-1668. [PMID: 37684533 PMCID: PMC10684458 DOI: 10.1007/s13311-023-01433-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/24/2023] [Indexed: 09/10/2023] Open
Abstract
Network analysis of functional brain scans acquired with [18F]-fluorodeoxyglucose positron emission tomography (FDG PET, to map cerebral glucose metabolism), or resting-state functional magnetic resonance imaging (rs-fMRI, to map blood oxygen level-dependent brain activity) has increasingly been used to identify and validate reproducible circuit abnormalities associated with neurodegenerative disorders such as Parkinson's disease (PD). In addition to serving as imaging markers of the underlying disease process, these networks can be used singly or in combination as an adjunct to clinical diagnosis and as a screening tool for therapeutics trials. Disease networks can also be used to measure rates of progression in natural history studies and to assess treatment responses in individual subjects. Recent imaging studies in PD subjects scanned before and after treatment have revealed therapeutic effects beyond the modulation of established disease networks. Rather, other mechanisms of action may be at play, such as the induction of novel functional brain networks directly by treatment. To date, specific treatment-induced networks have been described in association with novel interventions for PD such as subthalamic adeno-associated virus glutamic acid decarboxylase (AAV2-GAD) gene therapy, as well as sham surgery or oral placebo under blinded conditions. Indeed, changes in the expression of these networks with treatment have been found to correlate consistently with clinical outcome. In aggregate, these attributes suggest a role for functional brain networks as biomarkers in future clinical trials.
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Affiliation(s)
- János A Barbero
- Center for Neurosciences, The Feinstein Institutes for Medical Research, 350 Community Drive, Manhasset, NY, 11030, USA
- Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, 11549, USA
| | - Prashin Unadkat
- Center for Neurosciences, The Feinstein Institutes for Medical Research, 350 Community Drive, Manhasset, NY, 11030, USA
- Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, 11549, USA
- Elmezzi Graduate School of Molecular Medicine, Manhasset, NY, 11030, USA
| | - Yoon Young Choi
- Center for Neurosciences, The Feinstein Institutes for Medical Research, 350 Community Drive, Manhasset, NY, 11030, USA
| | - David Eidelberg
- Center for Neurosciences, The Feinstein Institutes for Medical Research, 350 Community Drive, Manhasset, NY, 11030, USA.
- Molecular Medicine and Neurology, Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, 11549, USA.
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27
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Cao Z, Wu C, Hong H, Huang P, Zhou C, Guan X, Wu H, Duanmu X, Xu X, Zhang M. Predictability of inter-regional cerebral perfusion similarity on dopamine responsiveness and the moderation role of cognition in PD patients. Neuroimage 2023; 279:120305. [PMID: 37562719 DOI: 10.1016/j.neuroimage.2023.120305] [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: 06/09/2023] [Revised: 07/09/2023] [Accepted: 07/31/2023] [Indexed: 08/12/2023] Open
Abstract
BACKGROUND Large heterogeneity can be found in dopamine responsiveness of patients with Parkinson's disease (PD). Instantly and objectively understanding dopamine responsiveness of patients may help clinical practice. PURPOSE This PD study explored the predictability of off-state inter-regional cerebral blood flow (CBF) perfusion similarity on patient's dopamine responsiveness and tested whether the predictive power could be moderated by patient's cognitive status. MATERIALS AND METHOD The PD cohort with 192 patients (containing off state and on state (PD-off and PD-on)) and the normal control (NC) cohort with 92 subjects were included. The intra-individual CBF relative variation networks were constructed and compared between PD-off and PD-on, PD-off and NC to identify the alterations caused by dopamine depletion. Based on that, regression analysis of off-state inter-regional CBF perfusion similarity on patient's dopamine responsiveness was performed. Finally, moderation analysis was conducted to test the moderation role of cognition on the regression model. RESULTS In the PD-off cohort, a total of 82 edges in the network were identified that affected by dopamine depletion. Off-state inter-regional CBF perfusion similarity was found that had a significant influence on patient's dopamine responsiveness. Cognitive status was validated that positively moderated the relationship between off-state inter-regional CBF perfusion similarity and dopamine responsiveness. CONCLUSION Dopamine responsiveness of PD patient could be predicted by off-state inter-regional CBF perfusion similarity. Patient's cognitive status might have a positive moderation effect on his/her dopamine responsiveness.
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Affiliation(s)
- Zhengye Cao
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang 310009, China
| | - Chenqing Wu
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang 310009, China
| | - Hui Hong
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang 310009, China
| | - Peiyu Huang
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang 310009, China
| | - Cheng Zhou
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang 310009, China
| | - Xiaojun Guan
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang 310009, China
| | - Haoting Wu
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang 310009, China
| | - Xiaojie Duanmu
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang 310009, China
| | - Xiaojun Xu
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang 310009, China
| | - Minming Zhang
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang 310009, China.
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Alahmadi AA, Alotaibi NO, Hakami NY, Almutairi RS, Darwesh AM, Abdeen R, Alghamdi J, Abdulaal OM, Alsharif W, Sultan SR, Kanbayti IH. Gender and cytoarchitecture differences: Functional connectivity of the hippocampal sub-regions. Heliyon 2023; 9:e20389. [PMID: 37780771 PMCID: PMC10539667 DOI: 10.1016/j.heliyon.2023.e20389] [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: 12/10/2022] [Revised: 07/27/2023] [Accepted: 09/20/2023] [Indexed: 10/03/2023] Open
Abstract
Introduction The hippocampus plays a significant role in learning, memory encoding, and spatial navigation. Typically, the hippocampus is investigated as a whole region of interest. However, recent work has developed fully detailed atlases based on cytoarchitecture properties of brain regions, and the hippocampus has been sub-divided into seven sub-areas that have structural differences in terms of distinct numbers of cells, neurons, and other structural and chemical properties. Moreover, gender differences are of increasing concern in neuroscience research. Several neuroscience studies have found structural and functional variations between the brain regions of females and males, and the hippocampus is one of these regions. Aim The aim of this study to explore whether the cytoarchitecturally distinct sub-regions of the hippocampus have varying patterns of functional connectivity with different networks of the brain and how these functional connections differ in terms of gender differences. Method This study investigated 200 healthy participants using seed-based resting-state functional magnetic resonance imaging (rsfMRI). The primary aim of this study was to explore the resting connectivity and gender distinctions associated with specific sub-regions of the hippocampus and their relationship with major functional brain networks. Results The findings revealed that the majority of the seven hippocampal sub-regions displayed functional connections with key brain networks, and distinct patterns of functional connectivity were observed between the hippocampal sub-regions and various functional networks within the brain. Notably, the default and visual networks exhibited the most consistent functional connections. Additionally, gender-based analysis highlighted evident functional resemblances and disparities, particularly concerning the anterior section of the hippocampus. Conclusion This study highlighted the functional connectivity patterns and involvement of the hippocampal sub-regions in major brain functional networks, indicating that the hippocampus should be investigated as a region of multiple distinct functions and should always be examined as sub-regions of interest. The results also revealed clear gender differences in functional connectivity.
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Affiliation(s)
- Adnan A.S. Alahmadi
- Radiologic Sciences, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah, Saudi Arabia
- NMR Research Unit, Department of Neuroinflammation, Queen Square MS Centre, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Nada O. Alotaibi
- Radiologic Sciences, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Norah Y. Hakami
- Radiologic Sciences, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Raghad S. Almutairi
- Radiologic Sciences, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Afnan M.F. Darwesh
- Radiologic Sciences, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Rawan Abdeen
- Radiologic Sciences, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Jamaan Alghamdi
- Radiologic Sciences, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Osamah M. Abdulaal
- Diagnostic Radiology Technology, College of Applied Medical Sciences, Taibah University, Madina, Saudi Arabia
| | - Walaa Alsharif
- Diagnostic Radiology Technology, College of Applied Medical Sciences, Taibah University, Madina, Saudi Arabia
| | - Salahaden R. Sultan
- Radiologic Sciences, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Ibrahem H. Kanbayti
- Radiologic Sciences, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah, Saudi Arabia
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Di Tella S, De Marco M, Baglio F, Silveri MC, Venneri A. Resting-state functional connectivity is modulated by cognitive reserve in early Parkinson's disease. Front Psychol 2023; 14:1207988. [PMID: 37691780 PMCID: PMC10485267 DOI: 10.3389/fpsyg.2023.1207988] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2023] [Accepted: 07/28/2023] [Indexed: 09/12/2023] Open
Abstract
Background Fronto-striatal disconnection is thought to be at the basis of dysexecutive symptoms in patients with Parkinson's disease (PD). Multiple reserve-related processes may offer resilience against functional decline. Among these, cognitive reserve (CR) refers to the adaptability of cognitive processes. Objective To test the hypothesis that functional connectivity of pathways associated with executive dysfunction in PD is modulated by CR. Methods Twenty-six PD patients and 24 controls underwent resting-state functional magnetic resonance imaging. Functional connectivity was explored with independent component analysis and seed-based approaches. The following networks were selected from the outcome of the independent component analysis: default-mode (DMN), left and right fronto-parietal (l/rFPN), salience (SalN), sensorimotor (SMN), and occipital visual (OVN). Seed regions were selected in the substantia nigra and in the dorsolateral and ventromedial prefrontal cortex for the assessment of seed-based functional connectivity maps. Educational and occupational attainments were used as CR proxies. Results Compared with their counterparts with high CR, PD individuals with low CR had reduced posterior DMN functional connectivity in the anterior cingulate and basal ganglia, and bilaterally reduced connectivity in fronto-parietal regions within the networks defined by the dorsolateral and ventrolateral prefrontal seeds. Hyper-connectivity was detected within medial prefrontal regions when comparing low-CR PD with low-CR controls. Conclusion CR may exert a modulatory effect on functional connectivity in basal ganglia and executive-attentional fronto-parietal networks. In PD patients with low CR, attentional control networks seem to be downregulated, whereas higher recruitment of medial frontal regions suggests compensation via an upregulation mechanism. This upregulation might contribute to maintaining efficient cognitive functioning when posterior cortical function is progressively reduced.
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Affiliation(s)
- Sonia Di Tella
- Department of Psychology, Università Cattolica del Sacro Cuore, Milan, Italy
- IRCCS, Fondazione Don Carlo Gnocchi Onlus, Milan, Italy
| | - Matteo De Marco
- Department of Life Sciences, Brunel University London, Uxbridge, United Kingdom
| | | | | | - Annalena Venneri
- Department of Life Sciences, Brunel University London, Uxbridge, United Kingdom
- Department of Medicine and Surgery, University of Parma, Parma, Italy
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Zhu X, Dai G, Wang M, Tan M, Li Y, Xu Z, Lei D, Chen L, Chen X, Liu H. Continuous theta burst stimulation over right cerebellum for speech impairment in Parkinson's disease: study protocol for a randomized, sham-controlled, clinical trial. Front Aging Neurosci 2023; 15:1215330. [PMID: 37655339 PMCID: PMC10465698 DOI: 10.3389/fnagi.2023.1215330] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2023] [Accepted: 08/03/2023] [Indexed: 09/02/2023] Open
Abstract
Background Speech impairment is a common symptom of Parkinson's disease (PD) that worsens with disease progression and affects communication and quality of life. Current pharmacological and surgical treatments for PD have inconsistent effects on speech impairment. The cerebellum is an essential part of sensorimotor network that regulates speech production and becomes dysfunctional in PD. Continuous theta-burst stimulation (cTBS) is a non-invasive brain stimulation technique that can modulate the cerebellum and its connections with other brain regions. Objective To investigate whether cTBS over the right cerebellum coupled with speech-language therapy (SLT) can improve speech impairment in PD. Methods In this randomized controlled trial (RCT), 40 patients with PD will be recruited and assigned to either an experimental group (EG) or a control group (CG). Both groups will receive 10 sessions of standard SLT. The EG will receive real cTBS over the right cerebellum, while the CG will receive sham stimulation. Blinded assessors will evaluate the treatment outcome at three time points: pre-intervention, post-intervention, and at a 12-week follow-up. The primary outcome measures are voice/speech quality and neurobehavioral parameters of auditory-vocal integration. The secondary outcome measures are cognitive function, quality of life, and functional connectivity determined by resting-state functional magnetic resonance imaging (fMRI). Significance This trial will provide evidence for the efficacy and safety of cerebellar cTBS for the treatment of speech impairment in PD and shed light on the neural mechanism of this intervention. It will also have implications for other speech impairment attributed to cerebellar dysfunctions. Clinical trial registration www.chictr.org.cn, identifier ChiCTR2100050543.
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Affiliation(s)
- Xiaoxia Zhu
- Department of Rehabilitation Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Guangyan Dai
- Department of Rehabilitation Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Meng Wang
- Department of Radiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Mingdan Tan
- Department of Rehabilitation Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Yongxue Li
- Department of Rehabilitation Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Zhiqin Xu
- Department of Rehabilitation Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Di Lei
- Department of Rehabilitation Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Ling Chen
- Department of Neurology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Xi Chen
- Department of Rehabilitation Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Hanjun Liu
- Department of Rehabilitation Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Brain Function and Disease, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
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Yassine S, Gschwandtner U, Auffret M, Duprez J, Verin M, Fuhr P, Hassan M. Identification of Parkinson's Disease Subtypes from Resting-State Electroencephalography. Mov Disord 2023; 38:1451-1460. [PMID: 37310340 DOI: 10.1002/mds.29451] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Revised: 04/11/2023] [Accepted: 05/05/2023] [Indexed: 06/14/2023] Open
Abstract
BACKGROUND Parkinson's disease (PD) patients present with a heterogeneous clinical phenotype, including motor, cognitive, sleep, and affective disruptions. However, this heterogeneity is often either ignored or assessed using only clinical assessments. OBJECTIVES We aimed to identify different PD sub-phenotypes in a longitudinal follow-up analysis and their electrophysiological profile based on resting-state electroencephalography (RS-EEG) and to assess their clinical significance over the course of the disease. METHODS Using electrophysiological features obtained from RS-EEG recordings and data-driven methods (similarity network fusion and source-space spectral analysis), we have performed a clustering analysis to identify disease sub-phenotypes and we examined whether their different patterns of disruption are predictive of disease outcome. RESULTS We showed that PD patients (n = 44) can be sub-grouped into three phenotypes with distinct electrophysiological profiles. These clusters are characterized by different levels of disruptions in the somatomotor network (Δ and β band), the frontotemporal network (α2 band) and the default mode network (α1 band), which consistently correlate with clinical profiles and disease courses. These clusters are classified into either moderate (only-motor) or mild-to-severe (diffuse) disease. We showed that EEG features can predict cognitive evolution of PD patients from baseline, when the cognitive clinical scores were overlapped. CONCLUSIONS The identification of novel PD subtypes based on electrical brain activity signatures may provide a more accurate prognosis in individual patients in clinical practice and help to stratify subgroups in clinical trials. Innovative profiling in PD can also support new therapeutic strategies that are brain-based and designed to modulate brain activity disruption. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Sahar Yassine
- LTSI - INSERM U1099, University of Rennes, Rennes, France
- NeuroKyma, Rennes, France
- Behavior and Basal Ganglia, CIC1414, CIC-IT, CHU Rennes, Rennes, France
| | - Ute Gschwandtner
- Department of Neurology, Hospitals of the University of Basel, Basel, Switzerland
| | - Manon Auffret
- LTSI - INSERM U1099, University of Rennes, Rennes, France
- Behavior and Basal Ganglia, CIC1414, CIC-IT, CHU Rennes, Rennes, France
- Institut des Neurosciences Cliniques de Rennes (INCR), Rennes, France
- France Développement Electronique, Monswiller, France
| | - Joan Duprez
- LTSI - INSERM U1099, University of Rennes, Rennes, France
| | - Marc Verin
- LTSI - INSERM U1099, University of Rennes, Rennes, France
- Behavior and Basal Ganglia, CIC1414, CIC-IT, CHU Rennes, Rennes, France
- Institut des Neurosciences Cliniques de Rennes (INCR), Rennes, France
- Movement Disorders Unit, Neurology Department, Pontchaillou University Hospital, Rennes, France
| | - Peter Fuhr
- Department of Neurology, Hospitals of the University of Basel, Basel, Switzerland
| | - Mahmoud Hassan
- Behavior and Basal Ganglia, CIC1414, CIC-IT, CHU Rennes, Rennes, France
- School of Science and Engineering, Reykjavik University, Reykjavik, Iceland
- MINDIG, Rennes, France
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Sharma R, Dillon K, Williams SEE, McIntosh R. Does emotion regulation network mediate the effect of social network on psychological distress among older adults? Soc Neurosci 2023; 18:142-154. [PMID: 37267049 DOI: 10.1080/17470919.2023.2218619] [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: 07/14/2022] [Revised: 05/12/2023] [Indexed: 06/04/2023]
Abstract
Socio-emotional interactions are integral for regulating emotions and buffering psychological distress. Social neuroscience perspectives on aging suggest that empathetic interpersonal interactions are supported by the activation of brain regions involved in regulating negative affect. The current study tested whether resting state functional connectivity of a network of brain regions activated during cognitive emotion regulation, i.e., emotion regulation network (ERN), statistically mediates the frequency of social contact with friends or family on psychological distress. Here, a 10-min resting-state functional MRI scan was collected along with self-reported anxiety/depressive, somatic, and thought problems and social networking from 90 community-dwelling older adults (aged 65-85 years). The frequency of social interactions with family, but not friends and neighbors, was associated with lower psychological distress. The magnitude of this effect was reduced by 33.34% to non-significant upon adding resting state ERN connectivity as a mediator. Follow-up whole-brain graph network analyses revealed that efficiency and centrality of the left inferior frontal gyrus and the right middle temporal gyrus relate to greater family interactions and lower distress. These hubs may help to buffer psychological problems in older adults through interactions involving empathetic and cognitive emotion regulation with close family.
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Affiliation(s)
| | - Kaitlyn Dillon
- Department of Psychology, University of Miami, Miami, Florida, USA
| | | | - Roger McIntosh
- Department of Psychology, University of Miami, Miami, Florida, USA
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Luo Y, Chen H, Gui M. Radiomics and Hybrid Models Based on Machine Learning to Predict Levodopa-Induced Dyskinesia of Parkinson's Disease in the First 6 Years of Levodopa Treatment. Diagnostics (Basel) 2023; 13:2511. [PMID: 37568874 PMCID: PMC10417024 DOI: 10.3390/diagnostics13152511] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2023] [Revised: 07/23/2023] [Accepted: 07/26/2023] [Indexed: 08/13/2023] Open
Abstract
BACKGROUND Current research on the prediction of movement complications associated with levodopa therapy in Parkinson's disease (PD) is limited. levodopa-induced dyskinesia (LID) is a movement complication that seriously affects the life quality of PD patients. One-third of PD patients develop LID within 1 to 6 years of levodopa treatment. This study aimed to construct models based on radiomics and machine learning to predict early LID in PD. METHODS We extracted radiomics features from the T1-weighted MRI obtained in the baseline of 49 PD control and 54 PD with LID in the first 6 years of levodopa therapy. Six brain regions related to the onset of PD were segmented as regions of interest (ROIs). The least absolute shrinkage and selection operator (LASSO) was used for feature selection. Using the machine learning methods of support vector machine (SVM), random forest (RF), and AdaBoost, we constructed radiomics models and hybrid models. The hybrid models combined the radiomics features and the Unified Parkinson's Disease Rating Scale part III (UPDRS III) total score. The five-fold cross-validation was performed and repeated 20 times to validate the stability of the classifiers. We used sensitivity, specificity, accuracy, receiver operating characteristic (ROC) curves, and area under the ROC curve (AUC) for model validation. RESULTS We selected 33 out of 6138 radiomics features. In the testing set of the radiomics model, the AUC values of the SVM, RF, and AdaBoost classifiers were 0.905, 0.808, and 0.778, respectively, and the accuracies were 0.839, 0.742, and 0.710. The hybrid models had better prediction performance. In the testing set, the AUC values of SVM, RF, and AdaBoost classifiers were 0.958, 0.861, and 0.832, respectively, and the accuracies were 0.903, 0.806, and 0.774. CONCLUSIONS Our results indicate that T1-weighted MRI is valuable in predicting early LID in PD. This work demonstrates that the combination of radiomics features and clinical features has good potential and value for identifying early LID in PD.
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Affiliation(s)
- Yang Luo
- Department of Neurology, Xiangya Hospital, Central South University, Changsha 410083, China;
| | - Huiqin Chen
- Department of Radiology, Xiangya Hospital, Central South University, Changsha 410083, China;
| | - Mingzhen Gui
- School of Automation, Central South University, Changsha 410083, China
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Gao J, Zhao L, Zhong T, Li C, He Z, Wei Y, Zhang S, Guo L, Liu T, Han J, Jiang X, Zhang T. Prediction of cognitive scores by joint use of movie-watching fMRI connectivity and eye tracking via Attention-CensNet. PSYCHORADIOLOGY 2023; 3:kkad011. [PMID: 38666131 PMCID: PMC10939348 DOI: 10.1093/psyrad/kkad011] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Revised: 06/14/2023] [Accepted: 07/06/2023] [Indexed: 04/28/2024]
Abstract
Background Brain functional connectivity under the naturalistic paradigm has been shown to be better at predicting individual behaviors than other brain states, such as rest and doing tasks. Nevertheless, the state-of-the-art methods have found it difficult to achieve desirable results from movie-watching paradigm functional magnetic resonance imaging (mfMRI) -induced brain functional connectivity, especially when there are fewer datasets. Incorporating other physical measurements into the prediction method may enhance accuracy. Eye tracking, becoming popular due to its portability and lower expense, can provide abundant behavioral features related to the output of human's cognition, and thus might supplement the mfMRI in observing participants' subconscious behaviors. However, there are very few studies on how to effectively integrate the multimodal information to strengthen the performance by a unified framework. Objective A fusion approach with mfMRI and eye tracking, based on convolution with edge-node switching in graph neural networks (CensNet), is proposed in this article. Methods In this graph model, participants are designated as nodes, mfMRI derived functional connectivity as node features, and different eye-tracking features are used to compute similarity between participants to construct heterogeneous graph edges. By taking multiple graphs as different channels, we introduce squeeze-and-excitation attention module to CensNet (A-CensNet) to integrate graph embeddings from multiple channels into one. Results The proposed model outperforms those using a single modality and single channel, and state-of-the-art methods. Conclusions The results indicate that brain functional activities and eye behaviors might complement each other in interpreting trait-like phenotypes.
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Affiliation(s)
- Jiaxing Gao
- School of Automation, Northwestern Polytechnical University, Xi'an 710072, China
| | - Lin Zhao
- Cortical Architecture Imaging and Discovery Laboratory, Department of Computer Science and Bioimaging Research Center, The University of Georgia, Athens, GA 30602, USA
| | - Tianyang Zhong
- School of Automation, Northwestern Polytechnical University, Xi'an 710072, China
| | - Changhe Li
- School of Automation, Northwestern Polytechnical University, Xi'an 710072, China
| | - Zhibin He
- School of Automation, Northwestern Polytechnical University, Xi'an 710072, China
| | - Yaonei Wei
- School of Automation, Northwestern Polytechnical University, Xi'an 710072, China
| | - Shu Zhang
- School of Computer Science, Northwestern Polytechnical University, Xi'an 710072, China
| | - Lei Guo
- School of Automation, Northwestern Polytechnical University, Xi'an 710072, China
| | - Tianming Liu
- Cortical Architecture Imaging and Discovery Laboratory, Department of Computer Science and Bioimaging Research Center, The University of Georgia, Athens, GA 30602, USA
| | - Junwei Han
- School of Automation, Northwestern Polytechnical University, Xi'an 710072, China
| | - Xi Jiang
- School of Life Science and Technology, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Tuo Zhang
- School of Automation, Northwestern Polytechnical University, Xi'an 710072, China
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Legaz A, Prado P, Moguilner S, Báez S, Santamaría-García H, Birba A, Barttfeld P, García AM, Fittipaldi S, Ibañez A. Social and non-social working memory in neurodegeneration. Neurobiol Dis 2023; 183:106171. [PMID: 37257663 PMCID: PMC11177282 DOI: 10.1016/j.nbd.2023.106171] [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: 04/05/2023] [Revised: 05/08/2023] [Accepted: 05/24/2023] [Indexed: 06/02/2023] Open
Abstract
Although social functioning relies on working memory, whether a social-specific mechanism exists remains unclear. This undermines the characterization of neurodegenerative conditions with both working memory and social deficits. We assessed working memory domain-specificity across behavioral, electrophysiological, and neuroimaging dimensions in 245 participants. A novel working memory task involving social and non-social stimuli with three load levels was assessed across controls and different neurodegenerative conditions with recognized impairments in: working memory and social cognition (behavioral-variant frontotemporal dementia); general cognition (Alzheimer's disease); and unspecific patterns (Parkinson's disease). We also examined resting-state theta oscillations and functional connectivity correlates of working memory domain-specificity. Results in controls and all groups together evidenced increased working memory demands for social stimuli associated with frontocinguloparietal theta oscillations and salience network connectivity. Canonical frontal theta oscillations and executive-default mode network anticorrelation indexed non-social stimuli. Behavioral-variant frontotemporal dementia presented generalized working memory deficits related to posterior theta oscillations, with social stimuli linked to salience network connectivity. In Alzheimer's disease, generalized working memory impairments were related to temporoparietal theta oscillations, with non-social stimuli linked to the executive network. Parkinson's disease showed spared working memory performance and canonical brain correlates. Findings support a social-specific working memory and related disease-selective pathophysiological mechanisms.
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Affiliation(s)
- Agustina Legaz
- Cognitive Neuroscience Center (CNC), Universidad de San Andres, Buenos Aires, Argentina; National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina; Universidad Nacional de Córdoba, Facultad de Psicología, Córdoba, Argentina
| | - Pavel Prado
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibañez, Santiago, Chile; Escuela de Fonoaudiología, Facultad de Odontología y Ciencias de la Rehabilitación, Universidad San Sebastián, Santiago, Chile
| | - Sebastián Moguilner
- Cognitive Neuroscience Center (CNC), Universidad de San Andres, Buenos Aires, Argentina; Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibañez, Santiago, Chile; Global Brain Health Institute (GBHI), University of California San Francisco (UCSF), San Francisco, United States; Trinity College Dublin (TCD), Dublin, Ireland
| | | | - Hernando Santamaría-García
- Pontificia Universidad Javeriana, Medical School, Physiology and Psychiatry Departments, Memory and Cognition Center Intellectus, Hospital Universitario San Ignacio, Bogotá, Colombia
| | - Agustina Birba
- Cognitive Neuroscience Center (CNC), Universidad de San Andres, Buenos Aires, Argentina; Facultad de Psicología, Universidad de La Laguna, Tenerife, Spain; Instituto Universitario de Neurociencia, Universidad de La Laguna, Tenerife, Spain
| | - Pablo Barttfeld
- Cognitive Science Group. Instituto de Investigaciones Psicológicas (IIPsi), CONICET UNC, Facultad de Psicología, Universidad Nacional de Córdoba, Boulevard de la Reforma esquina Enfermera Gordillo, CP 5000. Córdoba, Argentina
| | - Adolfo M García
- Cognitive Neuroscience Center (CNC), Universidad de San Andres, Buenos Aires, Argentina; Global Brain Health Institute (GBHI), University of California San Francisco (UCSF), San Francisco, United States; Departamento de Lingüística y Literatura, Facultad de Humanidades, Universidad de Santiago de Chile, Santiago, Chile; Trinity College Dublin (TCD), Dublin, Ireland
| | - Sol Fittipaldi
- Cognitive Neuroscience Center (CNC), Universidad de San Andres, Buenos Aires, Argentina; Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibañez, Santiago, Chile; Global Brain Health Institute (GBHI), University of California San Francisco (UCSF), San Francisco, United States; Trinity College Dublin (TCD), Dublin, Ireland.
| | - Agustín Ibañez
- Cognitive Neuroscience Center (CNC), Universidad de San Andres, Buenos Aires, Argentina; National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina; Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibañez, Santiago, Chile; Global Brain Health Institute (GBHI), University of California San Francisco (UCSF), San Francisco, United States; Trinity College Dublin (TCD), Dublin, Ireland.
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Chelladurai A, Narayan DL, Divakarachari PB, Loganathan U. fMRI-Based Alzheimer's Disease Detection Using the SAS Method with Multi-Layer Perceptron Network. Brain Sci 2023; 13:893. [PMID: 37371371 DOI: 10.3390/brainsci13060893] [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: 05/04/2023] [Revised: 05/24/2023] [Accepted: 05/30/2023] [Indexed: 06/29/2023] Open
Abstract
In the present scenario, Alzheimer's Disease (AD) is one of the incurable neuro-degenerative disorders, which accounts for nearly 60% to 70% of dementia cases. Currently, several machine-learning approaches and neuroimaging modalities are utilized for diagnosing AD. Among the available neuroimaging modalities, functional Magnetic Resonance Imaging (fMRI) is extensively utilized for studying brain activities related to AD. However, analyzing complex brain structures in fMRI is a time-consuming and complex task; so, a novel automated model was proposed in this manuscript for early diagnosis of AD using fMRI images. Initially, the fMRI images are acquired from an online dataset: Alzheimer's Disease Neuroimaging Initiative (ADNI). Further, the quality of the acquired fMRI images was improved by implementing a normalization technique. Then, the Segmentation by Aggregating Superpixels (SAS) method was implemented for segmenting the brain regions (AD, Normal Controls (NC), Mild Cognitive Impairment (MCI), Early Mild Cognitive Impairment (EMCI), Late Mild Cognitive Impairment (LMCI), and Significant Memory Concern (SMC)) from the denoised fMRI images. From the segmented brain regions, feature vectors were extracted by employing Gabor and Gray Level Co-Occurrence Matrix (GLCM) techniques. The obtained feature vectors were dimensionally reduced by implementing Honey Badger Optimization Algorithm (HBOA) and fed to the Multi-Layer Perceptron (MLP) model for classifying the fMRI images as AD, NC, MCI, EMCI, LMCI, and SMC. The extensive investigation indicated that the presented model attained 99.44% of classification accuracy, 88.90% of Dice Similarity Coefficient (DSC), 90.82% of Jaccard Coefficient (JC), and 88.43% of Hausdorff Distance (HD). The attained results are better compared with the conventional segmentation and classification models.
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Affiliation(s)
- Aarthi Chelladurai
- Department of Electronics and Communication Engineering, Sengunthar Engineering College, Tiruchengode 637205, Tamil Nadu, India
| | - Dayanand Lal Narayan
- Department of Computer Science Engineering, GITAM School of Technology, GITAM University, Bengaluru 561203, Karnataka, India
| | | | - Umasankar Loganathan
- Department of Electrical and Electronics Engineering, S.A. Engineering College, Chennai 600077, Tamilnadu, India
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Sun J, Ma J, Gao L, Wang J, Zhang D, Chen L, Fang J, Feng T, Wu T. Disruption of locus coeruleus-related functional networks in Parkinson's disease. NPJ Parkinsons Dis 2023; 9:81. [PMID: 37253752 DOI: 10.1038/s41531-023-00532-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2022] [Accepted: 05/22/2023] [Indexed: 06/01/2023] Open
Abstract
Locus coeruleus (LC) is severely affected in Parkinson's Disease (PD). However, alterations in LC-related resting-state networks (RSNs) in PD remain unclear. We used resting-state functional MRI to investigate the alterations in functional connectivity (FC) of LC-related RSNs and the associations between RSNs changes and clinical features in idiopathic rapid eye movement sleep behavior disorder (iRBD) and PD patients with (PDRBD+) and without RBD (PDRBD-). There was a similarly disrupted FC pattern of LC-related RSNs in iRBD and PDRBD+ patients, whereas LC-related RSNs were less damaged in PDRBD- patients than that in patients with iRBD and PDRBD+. The FC of LC-related RSNs correlated with cognition and duration in iRBD, depression in PDRBD-, and cognition and severity of RBD in patients with PDRBD+. Our findings demonstrate that LC-related RSNs are significantly disrupted in the prodromal stage of α-synucleinopathies and proposed body-first PD (PDRBD+), but are less affected in brain-first PD (PDRBD-).
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Affiliation(s)
- Junyan Sun
- Center for Movement Disorders, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Jinghong Ma
- Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing, China
| | - Linlin Gao
- Department of General Medicine, Tianjin Union Medical Center, Tianjin, China
| | - Junling Wang
- Center for Movement Disorders, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Dongling Zhang
- Center for Movement Disorders, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Lili Chen
- Center for Movement Disorders, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Jiliang Fang
- Department of Radiology, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Tao Feng
- Center for Movement Disorders, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
| | - Tao Wu
- Center for Movement Disorders, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
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Ruan X, Huang X, Li Y, Kuang Z, Li M, Wei X. Dysfunction of human brain network hierarchy in Parkinson's disease patients with freezing of gait. Parkinsonism Relat Disord 2023; 112:105446. [PMID: 37245278 DOI: 10.1016/j.parkreldis.2023.105446] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Revised: 05/10/2023] [Accepted: 05/18/2023] [Indexed: 05/30/2023]
Abstract
INTRODUCTION Hierarchy has been identified as a principle underlying the organization of human brain networks. In Parkinson's disease with freezing of gait (PD-FOG), it remains unclear whether and how the network hierarchy is disrupted. Additionally, the associations between changes in the brain network hierarchy of PD patients with FOG and clinical scales remain unclear. The aim of this study was to explore alterations in the network hierarchy of PD-FOG and their clinical relevance. METHODS In this study, the brain network hierarchy of each group was described through a connectome gradient analysis among 31 PD-FOG, 50 PD patients without FOG (PD-NFOG), and 38 healthy controls (HC). Changes in the network hierarchy were assessed by comparing different gradient values of each network between the PD-FOG, PD-NFOG and HC groups. We further examined the relationship between dynamically changing network gradient values and clinical scales. RESULTS For the second gradient, Salience/ventral attention network-A (SalVentAttnA) network gradient of PD-FOG group was significantly lower than that of PD-NFOG, while both PD subgroups had a Default mode network-C gradient that was significantly lower than that of the HC group. In the third gradient, somatomotor network-A gradient of PD-FOG patients was significantly lower than the PD-NFOG group. Moreover, reduced SalVentAttnA network gradient values were associated with more severe gaits, fall risk, and frozen gait in PD-FOG patients. CONCLUSIONS The brain network hierarchy in PD-FOG is disturbed, this dysfunction is related to the severity of frozen gait. This study provides novel evidence for the neural mechanisms of FOG.
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Affiliation(s)
- Xiuhang Ruan
- Department of Radiology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong, China
| | - Xiaofei Huang
- Department of Radiology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong, China
| | - Yuting Li
- Department of Radiology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong, China
| | - Zhanyu Kuang
- Department of Radiology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong, China
| | - Mengyan Li
- Department of Neurology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong, China.
| | - Xinhua Wei
- Department of Radiology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong, China.
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Wen J, Gao Y, Li M, Hu S, Zhao M, Su C, Wang Q, Xi H, Zhan L, Lv Y, Antwi CO, Ren J, Jia X. Regional abnormalities of spontaneous brain activity in migraine: A coordinate‐based meta‐analysis. J Neurosci Res 2023. [DOI: 10.1002/jnr.25191] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Revised: 02/17/2023] [Accepted: 03/13/2023] [Indexed: 04/03/2023]
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Cao Y, Si Q, Tong R, Zhang X, Li C, Mao S. Abnormal dynamic functional connectivity changes correlated with non-motor symptoms of Parkinson’s disease. Front Neurosci 2023; 17:1116111. [PMID: 37008221 PMCID: PMC10062480 DOI: 10.3389/fnins.2023.1116111] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Accepted: 02/28/2023] [Indexed: 03/17/2023] Open
Abstract
BackgroundNon-motor symptoms are common in Parkinson’s disease (PD) patients, decreasing quality of life and having no specific treatments. This research investigates dynamic functional connectivity (FC) changes during PD duration and its correlations with non-motor symptoms.MethodsTwenty PD patients and 19 healthy controls (HC) from PPMI dataset were collected and used in this study. Independent component analysis (ICA) was performed to select significant components from the entire brain. Components were grouped into seven resting-state intrinsic networks. Static and dynamic FC changes during resting-state functional magnetic resonance imaging (fMRI) were calculated based on selected components and resting state networks (RSN).ResultsStatic FC analysis results showed that there was no difference between PD-baseline (PD-BL) and HC group. Network averaged connection between frontoparietal network and sensorimotor network (SMN) of PD-follow up (PD-FU) was lower than PD-BL. Dynamic FC analysis results suggested four distinct states, and each state’s temporal characteristics, such as fractional windows and mean dwell time, were calculated. The state 2 of our study showed positive coupling within and between SMN and visual network, while the state 3 showed hypo-coupling through all RSN. The fractional windows and mean dwell time of PD-FU state 2 (positive coupling state) were statistically lower than PD-BL. Fractional windows and mean dwell time of PD-FU state 3 (hypo-coupling state) were statistically higher than PD-BL. Outcome scales in Parkinson’s disease–autonomic dysfunction scores of PD-FU positively correlated with mean dwell time of state 3 of PD-FU.ConclusionOverall, our finding indicated that PD-FU patients spent more time in hypo-coupling state than PD-BL. The increase of hypo-coupling state and decrease of positive coupling state might correlate with the worsening of non-motor symptoms in PD patients. Dynamic FC analysis of resting-state fMRI can be used as monitoring tool for PD progression.
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Affiliation(s)
- Yuanyan Cao
- School of Biomedical Engineering, Capital Medical University, Beijing, China
- Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, Beijing, China
- Beijing Key Laboratory of Fundamental Research on Biomechanics in Clinical Application, Capital Medical University, Beijing, China
| | - Qian Si
- School of Cyber Science and Technology, Beihang University, Beijing, China
| | - Renjie Tong
- School of Biomedical Engineering, Capital Medical University, Beijing, China
- Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, Beijing, China
- Beijing Key Laboratory of Fundamental Research on Biomechanics in Clinical Application, Capital Medical University, Beijing, China
| | - Xu Zhang
- School of Biomedical Engineering, Capital Medical University, Beijing, China
- Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, Beijing, China
- Beijing Key Laboratory of Fundamental Research on Biomechanics in Clinical Application, Capital Medical University, Beijing, China
| | - Chunlin Li
- School of Biomedical Engineering, Capital Medical University, Beijing, China
- Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, Beijing, China
- Beijing Key Laboratory of Fundamental Research on Biomechanics in Clinical Application, Capital Medical University, Beijing, China
- Chunlin Li,
| | - Shanhong Mao
- School of Biomedical Engineering, Capital Medical University, Beijing, China
- Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, Beijing, China
- Beijing Key Laboratory of Fundamental Research on Biomechanics in Clinical Application, Capital Medical University, Beijing, China
- *Correspondence: Shanhong Mao,
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Neural Correlates of Impaired Self-awareness of Deficits after Acquired Brain Injury: A Systematic Review. Neuropsychol Rev 2023; 33:222-237. [PMID: 35112305 PMCID: PMC9998557 DOI: 10.1007/s11065-022-09535-6] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2021] [Accepted: 11/29/2021] [Indexed: 10/19/2022]
Abstract
Self-awareness is essential for the process and outcome of rehabilitation but is often affected by acquired brain injury (ABI). While many studies investigated the psychological aspects of self-awareness deficits, the biological underpinnings are not well understood. The aim of this systematic review was to identify the neural correlates of self-awareness after ABI. Results indicate that anticipation of future problems is associated with lesions and decreased neural functioning in the right frontal lobe, as well as increased diffusivity throughout the white matter of the brain. Poor behavioral adjustment on implicit awareness tasks is associated with less functional connectivity of anterior cingulate cortex and right or middle inferior frontal gyri to the fronto-parietal control network, as well as more activation in the left insula and left parietal operculum during error processing. Recognition of mistakes is associated with internetwork connectivity of anterior or posterior default mode network to salience network. In conclusion, after ABI, different results in brain activation and connectivity are found depending on level of awareness measured. Future studies are necessary to confirm these findings.
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Fang XT, Volpi T, Holmes SE, Esterlis I, Carson RE, Worhunsky PD. Linking resting-state network fluctuations with systems of coherent synaptic density: A multimodal fMRI and 11C-UCB-J PET study. Front Hum Neurosci 2023; 17:1124254. [PMID: 36908710 PMCID: PMC9995441 DOI: 10.3389/fnhum.2023.1124254] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Accepted: 01/31/2023] [Indexed: 02/25/2023] Open
Abstract
Introduction: Resting-state network (RSN) connectivity is a widely used measure of the brain's functional organization in health and disease; however, little is known regarding the underlying neurophysiology of RSNs. The aim of the current study was to investigate associations between RSN connectivity and synaptic density assessed using the synaptic vesicle glycoprotein 2A radioligand 11C-UCB-J PET. Methods: Independent component analyses (ICA) were performed on resting-state fMRI and PET data from 34 healthy adult participants (16F, mean age: 46 ± 15 years) to identify a priori RSNs of interest (default-mode, right frontoparietal executive-control, salience, and sensorimotor networks) and select sources of 11C-UCB-J variability (medial prefrontal, striatal, and medial parietal). Pairwise correlations were performed to examine potential intermodal associations between the fractional amplitude of low-frequency fluctuations (fALFF) of RSNs and subject loadings of 11C-UCB-J source networks both locally and along known anatomical and functional pathways. Results: Greater medial prefrontal synaptic density was associated with greater fALFF of the anterior default-mode, posterior default-mode, and executive-control networks. Greater striatal synaptic density was associated with greater fALFF of the anterior default-mode and salience networks. Post-hoc mediation analyses exploring relationships between aging, synaptic density, and RSN activity revealed a significant indirect effect of greater age on fALFF of the anterior default-mode network mediated by the medial prefrontal 11C-UCB-J source. Discussion: RSN functional connectivity may be linked to synaptic architecture through multiple local and circuit-based associations. Findings regarding healthy aging, lower prefrontal synaptic density, and lower default-mode activity provide initial evidence of a neurophysiological link between RSN activity and local synaptic density, which may have relevance in neurodegenerative and psychiatric disorders.
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Affiliation(s)
- Xiaotian T. Fang
- Department of Radiology & Biomedical Imaging, Yale School of Medicine, New Haven, CT, United States
| | - Tommaso Volpi
- Department of Radiology & Biomedical Imaging, Yale School of Medicine, New Haven, CT, United States
| | - Sophie E. Holmes
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, United States
| | - Irina Esterlis
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, United States
- Department of Psychology, Yale University, New Haven, CT, United States
| | - Richard E. Carson
- Department of Radiology & Biomedical Imaging, Yale School of Medicine, New Haven, CT, United States
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Perovnik M, Rus T, Schindlbeck KA, Eidelberg D. Functional brain networks in the evaluation of patients with neurodegenerative disorders. Nat Rev Neurol 2023; 19:73-90. [PMID: 36539533 DOI: 10.1038/s41582-022-00753-3] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/21/2022] [Indexed: 12/24/2022]
Abstract
Network analytical tools are increasingly being applied to brain imaging maps of resting metabolic activity (PET) or blood oxygenation-dependent signals (functional MRI) to characterize the abnormal neural circuitry that underlies brain diseases. This approach is particularly valuable for the study of neurodegenerative disorders, which are characterized by stereotyped spread of pathology along discrete neural pathways. Identification and validation of disease-specific brain networks facilitate the quantitative assessment of pathway changes over time and during the course of treatment. Network abnormalities can often be identified before symptom onset and can be used to track disease progression even in the preclinical period. Likewise, network activity can be modulated by treatment and might therefore be used as a marker of efficacy in clinical trials. Finally, early differential diagnosis can be achieved by simultaneously measuring the activity levels of multiple disease networks in an individual patient's scans. Although these techniques were originally developed for PET, over the past several years analogous methods have been introduced for functional MRI, a more accessible non-invasive imaging modality. This advance is expected to broaden the application of network tools to large and diverse patient populations.
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Affiliation(s)
- Matej Perovnik
- Department of Neurology, University Medical Center Ljubljana, Ljubljana, Slovenia.,Medical Faculty, University of Ljubljana, Ljubljana, Slovenia
| | - Tomaž Rus
- Department of Neurology, University Medical Center Ljubljana, Ljubljana, Slovenia.,Medical Faculty, University of Ljubljana, Ljubljana, Slovenia
| | | | - David Eidelberg
- Center for Neurosciences, The Feinstein Institutes for Medical Research, Manhasset, NY, USA.
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Disrupted topological organization of resting-state functional brain networks in Parkinson's disease patients with glucocerebrosidase gene mutations. Neuroradiology 2023; 65:361-370. [PMID: 36269334 DOI: 10.1007/s00234-022-03067-9] [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: 06/29/2022] [Accepted: 10/11/2022] [Indexed: 01/25/2023]
Abstract
PURPOSE The mutations of the glucocerebrosidase (GBA) gene are the greatest genetic risk factor for Parkinson's disease (PD). The mechanism underlying the association between GBA mutations and PD has not been fully elucidated. METHODS Using resting-state functional magnetic resonance imaging and graph theory analysis to investigate the disrupted topological organization in PD patients with GBA mutation (GBA-PD). Eleven GBA-PD patients, 11 noncarriers with PD, and 18 healthy controls (HCs) with a similar age and sex distribution were recruited. Individual whole-brain functional connectome was constructed, and the global and nodal topological disruptions were calculated among groups. Partial correlation analyses between the clinical features of patients with PD and topological alterations were performed. RESULTS The GBA-PD group showed prominently decreased characteristic path length (Lp) and increased global efficiency (Eg) compared to HCs at the global level; a significantly increased nodal betweenness centrality in the medial prefrontal cortex (mPFC) and precuneus within the default mode network, and precentral gyrus within the sensorimotor network, while a significantly decreased betweenness centrality in nodes within the cingulo-opercular network compared to the noncarrier group at the regional level. The altered nodal betweenness centrality of mPFC was positively correlated with fatigue severity scale scores in all patients with PD. CONCLUSION The preliminary pilot study found that GBA-PD patients had a higher functional integration at the global level. The nodal result of the mPFC is congruent with the potential fatigue pathology in PD and is suggestive of a profound effect of GBA mutations on the clinical fatigue in patients with PD.
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Zang Z, Song T, Li J, Nie B, Mei S, Zhang Y, Lu J. Severity-dependent functional connectome and the association with glucose metabolism in the sensorimotor cortex of Parkinson's disease. Front Neurosci 2023; 17:1104886. [PMID: 36793540 PMCID: PMC9922997 DOI: 10.3389/fnins.2023.1104886] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Accepted: 01/16/2023] [Indexed: 01/31/2023] Open
Abstract
Functional MRI studies have achieved promising outcomes in revealing abnormal functional connectivity in Parkinson's disease (PD). The primary sensorimotor area (PSMA) received a large amount of attention because it closely correlates with motor deficits. While functional connectivity represents signaling between PSMA and other brain regions, the metabolic mechanism behind PSMA connectivity has rarely been well established. By introducing hybrid PET/MRI scanning, the current study enrolled 33 advanced PD patients during medication-off condition and 25 age-and-sex-matched healthy controls (HCs), aiming to not only identify the abnormal functional connectome pattern of the PSMA, but also to simultaneously investigate how PSMA functional connectome correlates with glucose metabolism. We calculated degree centrality (DC) and the ratio of standard uptake value (SUVr) using resting state fMRI and 18F-FDG-PET data. A two-sample t-test revealed significantly decreased PSMA DC (PFWE < 0.014) in PD patients. The PSMA DC also correlated negatively with H-Y stage (P = 0.031). We found a widespread reduction of H-Y stage associated (P-values < 0.041) functional connectivity between PSMA and the visual network, attention network, somatomotor network, limbic network, frontoparietal network as well as the default mode network. The PSMA DC correlated positively with FDG-uptake in the HCs (P = 0.039) but not in the PD patients (P > 0.44). In summary, we identified disease severity-dependent PSMA functional connectome which in addition uncoupled with glucose metabolism in PD patients. The current study highlighted the critical role of simultaneous PET/fMRI in revealing the functional-metabolic mechanism in the PSMA of PD patients.
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Affiliation(s)
- Zhenxiang Zang
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China,Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China
| | - Tianbin Song
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China,Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China
| | - Jiping Li
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Binbin Nie
- Beijing Engineering Research Center of Radiographic Techniques and Equipment, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing, China
| | - Shanshan Mei
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Yuqing Zhang
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Jie Lu
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China,Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China,*Correspondence: Jie Lu ✉
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Altered Fractional Amplitude of Low-Frequency Fluctuation in Anxious Parkinson's Disease. Brain Sci 2023; 13:brainsci13010087. [PMID: 36672068 PMCID: PMC9857220 DOI: 10.3390/brainsci13010087] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2022] [Revised: 12/17/2022] [Accepted: 12/27/2022] [Indexed: 01/03/2023] Open
Abstract
OBJECTIVE Anxiety symptoms are persistent in Parkinson's disease (PD), but the underlying neural substrates are still unclear. In the current study, we aimed to explore the underlying neural mechanisms in PD patients with anxiety symptoms. METHODS 42 PD-A patients, 41 PD patients without anxiety symptoms (PD-NA), and 40 healthy controls (HCs) were recruited in the present study. All the subjects performed 3.0T fMRI scans. The fractional amplitude of low-frequency fluctuation (fALFF) analysis was used to investigate the alterations in neural activity among the three groups. A Pearson correlation analysis was performed between the altered fALFF value of the PD-A group and anxiety scores. RESULTS Compared with HCs, PD-A patients had higher fALFF values in the left cerebellum, cerebellum posterior lobe, bilateral temporal cortex, and brainstem and lower fALFF values in the bilateral inferior gyrus, bilateral basal ganglia areas, and left inferior parietal lobule. Moreover, between the two PD groups, PD-A patients showed higher fALFF values in the right precuneus and lower fALFF values in the bilateral inferior gyrus, bilateral basal ganglia areas, left inferior parietal lobule, and left occipital lobe. Furthermore, Pearson's correlation analysis demonstrated that the right precuneus and left caudate were correlated with the Hamilton Anxiety Rating Scale scores. CONCLUSION Our study found that anxiety symptoms in PD patients may be related to alterations of neurological activities in multiple brain regions. Furthermore, these may be critical radiological biomarkers for PD-A patients. Therefore, these findings can improve our understanding of the pathophysiological mechanisms underlying PD-A.
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Cera N, Monteiro J, Esposito R, Di Francesco G, Cordes D, Caldwell JZK, Cieri F. Neural correlates of psychodynamic and non-psychodynamic therapies in different clinical populations through fMRI: A meta-analysis and systematic review. Front Hum Neurosci 2022; 16:1029256. [PMID: 36644207 PMCID: PMC9832372 DOI: 10.3389/fnhum.2022.1029256] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2022] [Accepted: 11/25/2022] [Indexed: 12/24/2022] Open
Abstract
Background The COVID-19 pandemic has exacerbated the ongoing crisis in psychiatric and psychological care, contributing to what we have identified as a new psychological and psychiatric pandemic. Psychotherapy is an effective method for easing the psychological suffering experienced also by the various impacts of COVID-19. This treatment can be examined from a neurological perspective, through the application of brain imaging techniques. Specifically, the meta-analysis of imaging studies can aid in expanding researchers' understanding of the many beneficial applications of psychotherapy. Objectives We examined the functional brain changes accompanying different mental disorders with functional Magnetic Resonance Imaging (fMRI), through a meta-analysis, and systematic review in order to better understand the general neural mechanism involved in psychotherapy and the potential neural difference between psychodynamic and non-psychodynamic approaches. Data sources The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were employed for our systematic review and meta-analysis. We conducted a computer-based literature search, following the Population, Intervention, Comparison and Outcomes (PICO) approach, to retrieve all published articles in English regarding the above-described topics from PubMed (MEDLINE), Scopus, and Web of Science. Study eligibility criteria participants and interventions We combined terms related to psychotherapy and fMRI: ("psychotherapy" [All Fields] OR "psychotherapy" [MeSH Terms] OR "psychotherapy" [All Fields] OR "psychotherapies" [All Fields] OR "psychotherapy s" [All Fields]) AND ("magnetic resonance imaging" [MeSH Terms]) OR ("magnetic"[All Fields] AND "resonance"[All Fields] AND "imaging"[All Fields]) OR ("magnetic resonance imaging"[All Fields] OR "fmri"[All Fields]). We considered (1) whole brain fMRI studies; (2) studies in which participants have been involved in a clinical trial with psychotherapy sessions, with pre/post fMRI; (3) fMRI results presented in coordinate-based (x, y, and z) in MNI or Talairach space; (4) presence of neuropsychiatric patients. The exclusion criteria were: (1) systematic review or meta-analysis; (2) behavioral study; (3) single-case MRI or fMRI study; and (4) other imaging techniques (i.e., PET, SPECT) or EEG. Results After duplicates removal and assessment of the content of each published study, we included 38 sources. The map including all studies that assessed longitudinal differences in brain activity showed two homogeneous clusters in the left inferior frontal gyrus, and caudally involving the anterior insular cortex (p < 0.0001, corr.). Similarly, studies that assessed psychotherapy-related longitudinal changes using emotional or cognitive tasks (TASK map) showed a left-sided homogeneity in the anterior insula (p < 0.000) extending to Broca's area of the inferior frontal gyrus (p < 0.0001) and the superior frontal gyrus (p < 0.0001). Studies that applied psychodynamic psychotherapy showed Family-Wise Error (FWE) cluster-corrected (p < 0.05) homogeneity values in the right superior and inferior frontal gyri, with a small cluster in the putamen. No FWE-corrected homogeneity foci were observed for Mindful- based and cognitive behavioral therapy psychotherapy. In both pre- and post-therapy results, studies showed two bilateral clusters in the dorsal anterior insulae (p = 0.00001 and p = 0.00003, respectively) and involvement of the medial superior frontal gyrus (p = 0.0002). Limitations Subjective experiences, such as an individual's response to therapy, are intrinsically challenging to quantify as objective, factual realities. Brain changes observed both pre- and post-therapy could be related to other factors, not necessary to the specific treatment received. Therapeutic modalities and study designs are generally heterogeneous. Differences exist in sample characteristics, such as the specificity of the disorder and number and duration of sessions. Moreover, the sample size is relatively small, particularly due to the paucity of studies in this field and the little contribution of PDT. Conclusions and implications of key findings All psychological interventions seem to influence the brain from a functional point of view, showing their efficacy from a neurological perspective. Frontal, prefrontal regions, insular cortex, superior and inferior frontal gyrus, and putamen seem involved in these neural changes, with the psychodynamic more linked to the latter three regions.
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Affiliation(s)
- Nicoletta Cera
- Faculty of Psychology and Education Sciences, University of Porto, Porto, Portugal
- CIBIT-Coimbra Institute for Biomedical Imaging and Translational Research, Coimbra, Portugal
| | - Jessica Monteiro
- Faculty of Psychology and Education Sciences, University of Porto, Porto, Portugal
| | - Roberto Esposito
- Department of Radiology, Area Vasta 1/ASUR Marche, Pesaro, Italy
| | | | - Dietmar Cordes
- Department of Neurology, Cleveland Clinic Lou Ruvo Center for Brain Health, Las Vegas, NV, United States
- Department of Brain Health, University of Nevada, Las Vegas, NV, United States
- Department of Psychology and Neuroscience, University of Colorado, Boulder, CO, United States
| | - Jessica Z. K. Caldwell
- Department of Neurology, Cleveland Clinic Lou Ruvo Center for Brain Health, Las Vegas, NV, United States
| | - Filippo Cieri
- Department of Neurology, Cleveland Clinic Lou Ruvo Center for Brain Health, Las Vegas, NV, United States
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Zhang P, Zhang Y, Luo Y, Wang L, Wang K. Regional activity alterations in Parkinson's disease patients with anxiety disorders: A resting-state functional magnetic resonance imaging study. Front Aging Neurosci 2022; 14:1055160. [PMID: 36589538 PMCID: PMC9800784 DOI: 10.3389/fnagi.2022.1055160] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2022] [Accepted: 11/28/2022] [Indexed: 12/23/2022] Open
Abstract
Background Previous studies have revealed alteration of functional connectivity (FC) in Parkinson's disease patients with anxiety (PD-A), but local brain activities associated with anxiety in Parkinson's disease (PD) patients remain to be elucidated. Regional homogeneity (ReHo) analysis was employed to investigate alterations of regional brain activities in PD-A patients. Methods Resting-state functional magnetic resonance imaging (rs-fMRI) data were acquired from 42 PD-A patients, 41 PD patients without anxiety (PD-NA), and 40 age-and gender-matched healthy control (HC) subjects. ReHo analysis was used to investigate the synchronization of neuronal activities in brain regions in the three groups. The relationship between ReHo value and anxiety score in the PD-A group was also investigated. Results Parkinson's disease patients with anxiety showed increased ReHo values in the bilateral frontal lobes, caudate nucleus, and anterior cingulate gyrus [Gaussian random field (GRF) correction, voxel size p < 0.01, cluster size p < 0.05], compared with PD-NA patients and HC subjects, but the ReHo values of the right cerebellar hemisphere and posterior cerebellar lobe decreased (GRF correction, voxel size p < 0.01, cluster size p < 0.05). The increased ReHo values of the right superior frontal gyrus (r = 0.633, p = 0.001) and anterior cingulate gyrus (r = 0.45, p = 0.01) were positively correlated with anxiety scores in PD-A patients. Conclusion The development of PD-A may be associated with dysfunctional local activities in multiple brain regions, including the frontal cortex, cerebella, basal ganglia, and limbic system. Abnormal ReHo values in these brain regions may serve as neuroimaging markers for the early diagnosis of PD-A. The results suggest that using ReHo analysis to identify functional changes in core regions may advance our understanding of the pathophysiological mechanisms underlying PD-A.
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Affiliation(s)
- Peiyao Zhang
- Department of Radiology, China-Japan Friendship Hospital, Beijing, China
| | - Yanling Zhang
- Department of Radiology, China-Japan Friendship Hospital, Beijing, China
| | - Yuan Luo
- Department of Radiology, China-Japan Friendship Hospital, Beijing, China
| | - Lu Wang
- Department of Neurology, China-Japan Friendship Hospital, Beijing, China
| | - Kang Wang
- Department of Neurology, China-Japan Friendship Hospital, Beijing, China,*Correspondence: Kang Wang,
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Cai W, Young CB, Yuan R, Lee B, Ryman S, Kim J, Yang L, Henderson VW, Poston KL, Menon V. Dopaminergic medication normalizes aberrant cognitive control circuit signalling in Parkinson's disease. Brain 2022; 145:4042-4055. [PMID: 35357463 PMCID: PMC10200291 DOI: 10.1093/brain/awac007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2021] [Revised: 12/03/2021] [Accepted: 12/10/2021] [Indexed: 08/21/2023] Open
Abstract
Dopaminergic medication is widely used to alleviate motor symptoms of Parkinson's disease, but these medications also impact cognition with significant variability across patients. It is hypothesized that dopaminergic medication impacts cognition and working memory in Parkinson's disease by modulating frontoparietal-basal ganglia cognitive control circuits, but little is known about the underlying causal signalling mechanisms and their relation to individual differences in response to dopaminergic medication. Here we use a novel state-space computational model with ultra-fast (490 ms resolution) functional MRI to investigate dynamic causal signalling in frontoparietal-basal ganglia circuits associated with working memory in 44 Parkinson's disease patients ON and OFF dopaminergic medication, as well as matched 36 healthy controls. Our analysis revealed aberrant causal signalling in frontoparietal-basal ganglia circuits in Parkinson's disease patients OFF medication. Importantly, aberrant signalling was normalized by dopaminergic medication and a novel quantitative distance measure predicted individual differences in cognitive change associated with medication in Parkinson's disease patients. These findings were specific to causal signalling measures, as no such effects were detected with conventional non-causal connectivity measures. Our analysis also identified a specific frontoparietal causal signalling pathway from right middle frontal gyrus to right posterior parietal cortex that is impaired in Parkinson's disease. Unlike in healthy controls, the strength of causal interactions in this pathway did not increase with working memory load and the strength of load-dependent causal weights was not related to individual differences in working memory task performance in Parkinson's disease patients OFF medication. However, dopaminergic medication in Parkinson's disease patients reinstated the relation with working memory performance. Our findings provide new insights into aberrant causal brain circuit dynamics during working memory and identify mechanisms by which dopaminergic medication normalizes cognitive control circuits.
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Affiliation(s)
- Weidong Cai
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94305, USA
- Wu Tsai Neurosciences Institute, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Christina B Young
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Rui Yuan
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Byeongwook Lee
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Sephira Ryman
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Jeehyun Kim
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Laurice Yang
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Victor W Henderson
- Wu Tsai Neurosciences Institute, Stanford University School of Medicine, Stanford, CA 94305, USA
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA 94305, USA
- Department of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Kathleen L Poston
- Wu Tsai Neurosciences Institute, Stanford University School of Medicine, Stanford, CA 94305, USA
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA 94305, USA
- Department of Neurosurgery, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Vinod Menon
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94305, USA
- Wu Tsai Neurosciences Institute, Stanford University School of Medicine, Stanford, CA 94305, USA
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA 94305, USA
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50
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Yu RL, Wu RM. Mild cognitive impairment in patients with Parkinson’s disease: An updated mini-review and future outlook. Front Aging Neurosci 2022; 14:943438. [PMID: 36147702 PMCID: PMC9485585 DOI: 10.3389/fnagi.2022.943438] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2022] [Accepted: 08/15/2022] [Indexed: 12/04/2022] Open
Abstract
Mild cognitive impairment (MCI) is one of the common non-motor symptoms in patients with Parkinson’s disease (PD). MCI is the transition stage between normal aging and full-blown dementia and is also a powerful predictor of dementia. Although the concept of MCI has been used to describe some of the PD symptoms for many years, there is a lack of consistent diagnostic criteria. Moreover, because of the diverse patterns of the cognitive functions, each cognitive impairment will have a different progression. In this review, we overviewed the diagnostic criteria for PD-MCI, primarily focused on the heterogeneity of PD-MCI patients’ cognitive function, including various types of cognitive functions and their progression rates. A review of this topic is expected to be beneficial for clinical diagnosis, early intervention, and treatment. In addition, we also discussed the unmet needs and future vision in this field.
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Affiliation(s)
- Rwei-Ling Yu
- College of Medicine, Institute of Behavioral Medicine, National Cheng Kung University, Tainan, Taiwan
| | - Ruey-Meei Wu
- Department of Neurology, College of Medicine, National Taiwan University Hospital, National Taiwan University, Taipei, Taiwan
- *Correspondence: Ruey-Meei Wu,
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