scholarly journals Resting-state functional reorganization in Parkinson's disease: An activation likelihood estimation meta-analysis

Cortex ◽  
2017 ◽  
Vol 92 ◽  
pp. 119-138 ◽  
Author(s):  
Masoud Tahmasian ◽  
Simon B. Eickhoff ◽  
Kathrin Giehl ◽  
Frank Schwartz ◽  
Damian M. Herz ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Resting State ◽  
Meta Analysis ◽  
Likelihood Estimation ◽  
Activation Likelihood Estimation ◽  
Functional Reorganization

scholarly journals Neuroimaging in Parkinson’s disease dementia: connecting the dots

2019 ◽  
Vol 1 (1) ◽  
Author(s):  
Rimona S Weil ◽  
Joey K Hsu ◽  
Ryan R Darby ◽  
Louis Soussand ◽  
Michael D Fox
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Meta Analysis ◽  
Likelihood Estimation ◽  
Brain Network ◽  
Activation Likelihood Estimation ◽  
Stage Specificity ◽  
Network Mapping

Abstract Dementia is a common and devastating symptom of Parkinson’s disease but the anatomical substrate remains unclear. Some evidence points towards hippocampal involvement but neuroimaging abnormalities have been reported throughout the brain and are largely inconsistent across studies. Here, we test whether these disparate neuroimaging findings for Parkinson’s disease dementia localize to a common brain network. We used a literature search to identify studies reporting neuroimaging correlates of Parkinson’s dementia (11 studies, 385 patients). We restricted our search to studies of brain atrophy and hypometabolism that compared Parkinson’s patients with dementia to those without cognitive involvement. We used a standard coordinate-based activation likelihood estimation meta-analysis to assess for consistency in the neuroimaging findings. We then used a new approach, coordinate-based network mapping, to test whether neuroimaging findings localized to a common brain network. This approach uses resting-state functional connectivity from a large cohort of normative subjects (n = 1000) to identify the network of regions connected to a reported neuroimaging coordinate. Activation likelihood estimation meta-analysis failed to identify any brain regions consistently associated with Parkinson’s dementia, showing major heterogeneity across studies. In contrast, coordinate-based network mapping found that these heterogeneous neuroimaging findings localized to a specific brain network centred on the hippocampus. Next, we tested whether this network showed symptom specificity and stage specificity by performing two further analyses. We tested symptom specificity by examining studies of Parkinson’s hallucinations (9 studies, 402 patients) that are frequently co-morbid with Parkinson’s dementia. We tested for stage specificity by using studies of mild cognitive impairment in Parkinson’s disease (15 studies, 844 patients). Coordinate-based network mapping revealed that correlates of visual hallucinations fell within a network centred on bilateral lateral geniculate nucleus and correlates of mild cognitive impairment in Parkinson’s disease fell within a network centred on posterior default mode network. In both cases, the identified networks were distinct from the hippocampal network of Parkinson’s dementia. Our results link heterogeneous neuroimaging findings in Parkinson’s dementia to a common network centred on the hippocampus. This finding was symptom and stage-specific, with implications for understanding Parkinson’s dementia and heterogeneity of neuroimaging findings in general.

scholarly journals “Resting-state fMRI in Parkinson's disease patients with cognitive impairment: A meta-analysis”: Answer to Wang and colleagues

2019 ◽  
Vol 66 ◽  
pp. 253-254
Author(s):  
Amée F. Wolters ◽  
Sjors C.F. van de Weijer ◽  
Albert F.G. Leentjens ◽  
Annelien A. Duits ◽  
Heidi I.L. Jacobs ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Cognitive Impairment ◽  
Resting State ◽  
Meta Analysis ◽  
Resting State Fmri

scholarly journals Resting-state fMRI in Parkinson's disease patients with cognitive impairment: A meta-analysis

2019 ◽  
Vol 62 ◽  
pp. 16-27 ◽  
Author(s):  
Amée F. Wolters ◽  
Sjors C.F. van de Weijer ◽  
Albert F.G. Leentjens ◽  
Annelien A. Duits ◽  
Heidi I.L. Jacobs ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Cognitive Impairment ◽  
Resting State ◽  
Meta Analysis ◽  
Resting State Fmri

scholarly journals Resting State Functional Connectivity of Brain With Electroconvulsive Therapy in Depression: Meta-Analysis to Understand Its Mechanisms

2021 ◽  
Vol 14 ◽  
Author(s):  
Preeti Sinha ◽  
Himanshu Joshi ◽  
Dhruva Ithal
Keyword(s):  
Systematic Review ◽  
Functional Connectivity ◽  
Electroconvulsive Therapy ◽  
Resting State ◽  
Meta Analysis ◽  
Likelihood Estimation ◽  
Cingulate Cortex ◽  
Activation Likelihood Estimation ◽  
Resting State Functional Connectivity ◽  
The Right

Introduction: Electroconvulsive therapy (ECT) is a commonly used brain stimulation treatment for treatment-resistant or severe depression. This study was planned to find the effects of ECT on brain connectivity by conducting a systematic review and coordinate-based meta-analysis of the studies performing resting state fMRI (rsfMRI) in patients with depression receiving ECT.Methods: We systematically searched the databases published up to July 31, 2020, for studies in patients having depression that compared resting-state functional connectivity (rsFC) before and after a course of pulse wave ECT. Meta-analysis was performed using the activation likelihood estimation method after extracting details about coordinates, voxel size, and method for correction of multiple comparisons corresponding to the significant clusters and the respective rsFC analysis measure with its method of extraction.Results: Among 41 articles selected for full-text review, 31 articles were included in the systematic review. Among them, 13 articles were included in the meta-analysis, and a total of 73 foci of 21 experiments were examined using activation likelihood estimation in 10 sets. Using the cluster-level interference method, one voxel-wise analysis with the measure of amplitude of low frequency fluctuations and one seed-voxel analysis with the right hippocampus showed a significant reduction (p < 0.0001) in the left cingulate gyrus (dorsal anterior cingulate cortex) and a significant increase (p < 0.0001) in the right hippocampus with the right parahippocampal gyrus, respectively. Another analysis with the studies implementing network-wise (posterior default mode network: dorsomedial prefrontal cortex) resting state functional connectivity showed a significant increase (p < 0.001) in bilateral posterior cingulate cortex. There was considerable variability as well as a few key deficits in the preprocessing and analysis of the neuroimages and the reporting of results in the included studies. Due to lesser studies, we could not do further analysis to address the neuroimaging variability and subject-related differences.Conclusion: The brain regions noted in this meta-analysis are reasonably specific and distinguished, and they had significant changes in resting state functional connectivity after a course of ECT for depression. More studies with better neuroimaging standards should be conducted in the future to confirm these results in different subgroups of depression and with varied aspects of ECT.

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