scholarly journals Investigation of Spontaneous Brain Activity at Rest in Patients with Chronic Pain by Using Resting-state fMRI

2021 ◽  
Vol 58 (11) ◽  
pp. 1235-1242
Author(s):  
Shigeyuki Kan
Keyword(s):  
Chronic Pain ◽  
Resting State ◽  
Brain Activity ◽  
Resting State Fmri ◽  
Spontaneous Brain Activity

scholarly journals Jumping over baselines with new methods to predict activation maps from resting-state fMRI

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Eric Lacosse ◽  
Klaus Scheffler ◽  
Gabriele Lohmann ◽  
Georg Martius
Keyword(s):  
Resting State ◽  
Brain Activity ◽  
Resting State Fmri ◽  
Behavioral Differences ◽  
Large Variability ◽  
Single Vertex ◽  
Spontaneous Brain Activity ◽  
New Methods ◽  
Group Averaging ◽  
Proposed Modification

AbstractCognitive fMRI research primarily relies on task-averaged responses over many subjects to describe general principles of brain function. Nonetheless, there exists a large variability between subjects that is also reflected in spontaneous brain activity as measured by resting state fMRI (rsfMRI). Leveraging this fact, several recent studies have therefore aimed at predicting task activation from rsfMRI using various machine learning methods within a growing literature on ‘connectome fingerprinting’. In reviewing these results, we found lack of an evaluation against robust baselines that reliably supports a novelty of predictions for this task. On closer examination to reported methods, we found most underperform against trivial baseline model performances based on massive group averaging when whole-cortex prediction is considered. Here we present a modification to published methods that remedies this problem to large extent. Our proposed modification is based on a single-vertex approach that replaces commonly used brain parcellations. We further provide a summary of this model evaluation by characterizing empirical properties of where prediction for this task appears possible, explaining why some predictions largely fail for certain targets. Finally, with these empirical observations we investigate whether individual prediction scores explain individual behavioral differences in a task.

Abnormal spontaneous brain activity in medication-naïve ADHD children: A resting state fMRI study

2011 ◽  
Vol 502 (2) ◽  
pp. 89-93 ◽  
Author(s):  
Hong Yang ◽  
Qi-Zhu Wu ◽  
Lan-Ting Guo ◽  
Qian-Qian Li ◽  
Xiang-Yu Long ◽  
...  
Keyword(s):  
Resting State ◽  
Brain Activity ◽  
Resting State Fmri ◽  
Spontaneous Brain Activity ◽  
Fmri Study ◽  
Adhd Children

scholarly journals Meta-analysis of resting-state fMRI in depression: generating spatial hypotheses for potential clinical applications

2014 ◽  
Author(s):  
Benedikt Sundermann ◽  
Mona Olde lütke Beverborg ◽  
Bettina Pfleiderer
Keyword(s):  
Resting State ◽  
Spatial Information ◽  
Brain Activity ◽  
Meta Analysis ◽  
Likelihood Estimation ◽  
Resting State Fmri ◽  
Brain Regions ◽  
Anterior Cingulate ◽  
Diagnostic Classification Models ◽  
Spontaneous Brain Activity

Information derived from functional magnetic resonance imaging (fMRI) during wakeful rest has been introduced as a candidate diagnostic biomarker in unipolar major depressive disorder (MDD). Multiple reports of resting state fMRI in MDD describe group effects. Such prior knowledge can be adopted to pre-select potentially discriminating features, for example for diagnostic classification models with the aim to improve diagnostic accuracy. Purpose of this analysis was to consolidate spatial information about alterations of spontaneous brain activity in MDD to serve such feature selection and as a secondary aim to improve understanding of disease mechanisms. 32 studies were included in final analyses. Coordinates extracted from the original reports were assigned to two categories based on directionality of findings. Meta-analyses were calculated using the non-additive activation likelihood estimation approach with coordinates organized by subject group to account for non-independent samples. Results were compared with established resting state networks (RSNs) and spatial representations of recently introduced temporally independent functional modes (TFMs) of spontaneous brain activity. Converging evidence revealed a distributed pattern of brain regions with increased or decreased spontaneous activity in MDD. The most distinct finding was hyperactivity/ hyperconnectivity presumably reflecting the interaction of cortical midline structures (posterior default mode network components associated with self-referential processing and the subgenual anterior cingulate cortex) with lateral frontal areas related to externally-directed cognition. One particular TFM seems to better comprehend the findings than classical RSNs. Alterations that can be captured by resting state fMRI show considerable overlap with those identifiable with other neuroimaging modalities though differing in some aspects.

scholarly journals Temporal transitions of spontaneous brain activity

eLife ◽  
2018 ◽  
Vol 7 ◽  
Author(s):  
Zhiwei Ma ◽  
Nanyin Zhang
Keyword(s):  
Graph Theory ◽  
Resting State ◽  
Temporal Relationship ◽  
Brain Activity ◽  
Resting State Fmri ◽  
Temporal Organization ◽  
Mammalian Brain ◽  
Resting State Functional Connectivity ◽  
Spontaneous Brain Activity ◽  
Awake Rats

Spontaneous brain activity, typically investigated using resting-state fMRI (rsfMRI), provides a measure of inter-areal resting-state functional connectivity (RSFC). Although it has been established that RSFC is non-stationary, previous dynamic rsfMRI studies mainly focused on revealing the spatial characteristics of dynamic RSFC patterns, but the temporal relationship between these RSFC patterns remains elusive. Here we investigated the temporal organization of characteristic RSFC patterns in awake rats and humans. We found that transitions between RSFC patterns were not random but followed specific sequential orders. The organization of RSFC pattern transitions was further analyzed using graph theory, and pivotal RSFC patterns in transitions were identified. This study has demonstrated that spontaneous brain activity is not only nonrandom spatially, but also nonrandom temporally, and this feature is well conserved between rodents and humans. These results offer new insights into understanding the spatiotemporal dynamics of spontaneous activity in the mammalian brain.

Spontaneous brain activity in adult patients with moyamoya disease: a resting-state fMRI study

2014 ◽  
Vol 1546 ◽  
pp. 27-33 ◽  
Author(s):  
Yu Lei ◽  
Yanjiang Li ◽  
Wei Ni ◽  
Hanqiang Jiang ◽  
Zhong Yang ◽  
...  
Keyword(s):  
Moyamoya Disease ◽  
Resting State ◽  
Brain Activity ◽  
Resting State Fmri ◽  
Adult Patients ◽  
Spontaneous Brain Activity ◽  
Fmri Study
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