1
|
Samantaray T, Saini J, Pal PK, Gupta CN. Brain connectivity for subtypes of parkinson's disease using structural MRI. Biomed Phys Eng Express 2024; 10:025012. [PMID: 38224618 DOI: 10.1088/2057-1976/ad1e77] [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: 09/20/2023] [Accepted: 01/15/2024] [Indexed: 01/17/2024]
Abstract
Objective. Delineating Parkinson's disease (PD) into distinct subtypes is a major challenge. Most studies use clinical symptoms to label PD subtypes while our work uses an imaging-based data-mining approach to subtype PD. Our study comprises two major objectives - firstly, subtyping Parkinson's patients based on grey matter information from structural magnetic resonance imaging scans of human brains; secondly, comparative structural brain connectivity analysis of PD subtypes derived from the former step.Approach. Source-based-morphometry decomposition was performed on 131 Parkinson's patients and 78 healthy controls from PPMI dataset, to derive at components (regions) with significance in disease and high effect size. The loading coefficients of significant components were thresholded for arriving at subtypes. Further, regional grey matter maps of subtype-specific subjects were separately parcellated and employed for construction of subtype-specific association matrices using Pearson correlation. These association matrices were binarized using sparsity threshold and leveraged for structural brain connectivity analysis using network metrics.Main results. Two distinct Parkinson's subtypes (namely A and B) were detected employing loadings of two components satisfying the selection criteria, and a third subtype (AB) was detected, common to these two components. Subtype A subjects were highly weighted in inferior, middle and superior frontal gyri while subtype B subjects in inferior, middle and superior temporal gyri. Network metrics analyses through permutation test revealed significant inter-subtype differences (p < 0.05) in clustering coefficient, local efficiency, participation coefficient and betweenness centrality. Moreover, hubs were obtained using betweenness centrality and mean network degree.Significance. MRI-based data-driven subtypes show frontal and temporal lobes playing a key role in PD. Graph theory-driven brain network analyses could untangle subtype-specific differences in structural brain connections showing differential network architecture. Replication of these initial results in other Parkinson's datasets may be explored in future. Clinical Relevance- Investigating structural brain connections in Parkinson's disease may provide subtype-specific treatment.
Collapse
Affiliation(s)
- Tanmayee Samantaray
- Neural Engineering Lab, Department of Biosciences and Bioengineering, Indian Institute of Technology Guwahati, 781039, India
| | - Jitender Saini
- Department of Neuroimaging and Interventional Radiology, National Institute of Mental Health and Neurosciences, Bengaluru, 560029, India
| | - Pramod Kumar Pal
- Department of Neurology, National Institute of Mental Health & Neuro Sciences, Bengaluru, 560029, India
| | - Cota Navin Gupta
- Neural Engineering Lab, Department of Biosciences and Bioengineering, Indian Institute of Technology Guwahati, 781039, India
| |
Collapse
|
2
|
Li J, Tan C, Zhang L, Cai S, Shen Q, Liu Q, Wang M, Song C, Zhou F, Yuan J, Liu Y, Lan B, Liao H. Neural functional network of early Parkinson's disease based on independent component analysis. Cereb Cortex 2023; 33:11025-11035. [PMID: 37746803 DOI: 10.1093/cercor/bhad342] [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: 07/02/2023] [Revised: 08/08/2023] [Indexed: 09/26/2023] Open
Abstract
This work explored neural network changes in early Parkinson's disease: Resting-state functional magnetic resonance imaging was used to investigate functional alterations in different stages of Parkinson's disease (PD). Ninety-five PD patients (50 early/mild and 45 early/moderate) and 37 healthy controls (HCs) were included. Independent component analysis revealed significant differences in intra-network connectivity, specifically in the default mode network (DMN) and right frontoparietal network (RFPN), in both PD groups compared to HCs. Inter-network connectivity analysis showed reduced connectivity between the executive control network (ECN) and DMN, as well as ECN-left frontoparietal network (LFPN), in early/mild PD. Early/moderate PD exhibited decreased connectivity in ECN-LFPN, ECN-RFPN, ECN-DMN, and DMN-auditory network, along with increased connectivity in LFPN-cerebellar network. Correlations were found between ECN-DMN and ECN-LFPN connections with UPDRS-III scores in early/mild PD. These findings suggest that PD progression involves dysfunction in multiple intra- and inter-networks, particularly implicating the ECN, and a wider range of abnormal functional networks may mark the progression of the disease.
Collapse
Affiliation(s)
- Junli Li
- Department of Medical Imaging, Huizhou Central People's Hospital, Eling North Road, Huicheng District, Huizhou, Guangdong 516001, China
| | - Changlian Tan
- Department of Radiology, The Second Xiangya Hospital, Central South University, Renmin Middle Road, Furong District, Changsha, Hunan 410011, China
| | - Lin Zhang
- Department of Radiology, Chengdu Fifth People's Hospital, Mashi Street, Wenjiang District, Chengdu, Sichuan 611130, China
| | - Sainan Cai
- Department of Radiology, The Second Xiangya Hospital, Central South University, Renmin Middle Road, Furong District, Changsha, Hunan 410011, China
| | - Qin Shen
- Department of Radiology, The Second Xiangya Hospital, Central South University, Renmin Middle Road, Furong District, Changsha, Hunan 410011, China
| | - Qinru Liu
- Department of Radiology, The Second Xiangya Hospital, Central South University, Renmin Middle Road, Furong District, Changsha, Hunan 410011, China
| | - Min Wang
- Department of Radiology, The Second Xiangya Hospital, Central South University, Renmin Middle Road, Furong District, Changsha, Hunan 410011, China
| | - ChenDie Song
- Department of Radiology, The Second Xiangya Hospital, Central South University, Renmin Middle Road, Furong District, Changsha, Hunan 410011, China
| | - Fan Zhou
- Department of Radiology, The Second Xiangya Hospital, Central South University, Renmin Middle Road, Furong District, Changsha, Hunan 410011, China
| | - Jiaying Yuan
- Department of Radiology, The Second Xiangya Hospital, Central South University, Renmin Middle Road, Furong District, Changsha, Hunan 410011, China
| | - Yujing Liu
- Department of Radiology, The Second Xiangya Hospital, Central South University, Renmin Middle Road, Furong District, Changsha, Hunan 410011, China
| | - Bowen Lan
- Department of Medical Imaging, Huizhou Central People's Hospital, Eling North Road, Huicheng District, Huizhou, Guangdong 516001, China
| | - Haiyan Liao
- Department of Radiology, The Second Xiangya Hospital, Central South University, Renmin Middle Road, Furong District, Changsha, Hunan 410011, China
| |
Collapse
|
3
|
Thams F, Külzow N, Flöel A, Antonenko D. Modulation of network centrality and gray matter microstructure using multi-session brain stimulation and memory training. Hum Brain Mapp 2022; 43:3416-3426. [PMID: 35373873 PMCID: PMC9248322 DOI: 10.1002/hbm.25857] [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: 11/08/2021] [Revised: 02/15/2022] [Accepted: 03/24/2022] [Indexed: 11/07/2022] Open
Abstract
Neural mechanisms of behavioral improvement induced by repeated transcranial direct current stimulation (tDCS) combined with cognitive training are yet unclear. Previously, we reported behavioral effects of a 3-day visuospatial memory training with concurrent anodal tDCS over the right temporoparietal cortex in older adults. To investigate intervention-induced neural alterations we here used functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) datasets available from 35 participants of this previous study, acquired before and after the intervention. To delineate changes in whole-brain functional network architecture, we employed eigenvector centrality mapping. Gray matter alterations were analyzed using DTI-derived mean diffusivity (MD). Network centrality in the bilateral posterior temporooccipital cortex was reduced after anodal compared to sham stimulation. This focal effect is indicative of decreased functional connectivity of the brain region underneath the anodal electrode and its left-hemispheric homolog with other "relevant" (i.e., highly connected) brain regions, thereby providing evidence for reorganizational processes within the brain's network architecture. Examining local MD changes in these clusters, an interaction between stimulation condition and training success indicated a decrease of MD in the right (stimulated) temporooccipital cluster in individuals who showed superior behavioral training benefits. Using a data-driven whole-brain network approach, we provide evidence for targeted neuromodulatory effects of a combined tDCS-and-training intervention. We show for the first time that gray matter alterations of microstructure (assessed by DTI-derived MD) may be involved in tDCS-enhanced cognitive training. Increased knowledge on how combined interventions modulate neural networks in older adults, will help the development of specific therapeutic interventions against age-associated cognitive decline.
Collapse
Affiliation(s)
- Friederike Thams
- Department of Neurology, Universitätsmedizin Greifswald, Greifswald, Germany
| | - Nadine Külzow
- Charité - Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Neurocure Cluster of Excellence, Berlin, Germany.,Neurological Rehabilitation Clinic, Kliniken Beelitz GmbH, Beelitz, Germany
| | - Agnes Flöel
- Department of Neurology, Universitätsmedizin Greifswald, Greifswald, Germany.,German Centre for Neurodegenerative Diseases (DZNE) Standort Greifswald, Greifswald, Germany
| | - Daria Antonenko
- Department of Neurology, Universitätsmedizin Greifswald, Greifswald, Germany
| |
Collapse
|