Intrinsic functional brain connectivity patterns underlying enhanced interoceptive sensibility

2020 ◽  
Vol 276 ◽  
pp. 804-814 ◽  
Author(s):  
Xiaoqin Wang ◽  
Yafei Tan ◽  
Omer Van den Bergh ◽  
Andreas von Leupoldt ◽  
Jiang Qiu
Keyword(s):  
Brain Connectivity ◽  
Functional Brain ◽  
Connectivity Patterns

Imaging functional brain connectivity patterns from high-resolution EEG and fMRI via graph theory

2007 ◽  
Vol 44 (6) ◽  
pp. 880-893 ◽  
Author(s):  
L. Astolfi ◽  
F. De Vico Fallani ◽  
F. Cincotti ◽  
D. Mattia ◽  
M. G. Marciani ◽  
...  
Keyword(s):  
Graph Theory ◽  
High Resolution ◽  
Brain Connectivity ◽  
Functional Brain ◽  
Connectivity Patterns ◽  
High Resolution Eeg

scholarly journals Data-driven clustering reveals a link between symptoms and functional brain connectivity in depression

2018 ◽  
Author(s):  
Luigi A. Maglanoc ◽  
Nils Inge Landrø ◽  
Rune Jonassen ◽  
Tobias Kaufmann ◽  
Aldo Cordova-Palomera ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Brain Connectivity ◽  
Total Sample ◽  
Individual Variability ◽  
Functional Brain Imaging ◽  
Depression Symptoms ◽  
Imaging Data ◽  
Functional Brain ◽  
Symptom Profiles ◽  
Connectivity Patterns

AbstractBackgroundDepression is a complex disorder with large inter-individual variability in symptom profiles that often occur alongside symptoms of other psychiatric domains such as anxiety. A dimensional and symptom-based approach may help refine the characterization and classification of depressive and anxiety disorders and thus aid in establishing robust biomarkers. We assess the brain functional connectivity correlates of a symptom-based clustering of individuals using functional brain imaging data.MethodsWe assessed symptoms of depression and anxiety using Beck’s Depression and Beck’s Anxiety inventories in individuals with or without a history of depression, and high dimensional data clustering to form subgroups based on symptom profiles. To assess the biological relevance of this subtyping, we compared functional magnetic resonance imaging-based dynamic and static functional connectivity between subgroups in a subset of the total sample.ResultsWe identified five subgroups with distinct symptom profiles, cutting across diagnostic boundaries and differing in terms of total severity, symptom patterns and centrality. For instance, inability to relax, fear of the worst, and feelings of guilt were among the most severe symptoms in subgroup 1, 2 and 3, respectively. These subgroups showed evidence of differential static brain connectivity patterns, in particular comprising a fronto-temporal network. In contrast, we found no significant associations with clinical sum scores, dynamic functional connectivity or global connectivity measures.ConclusionAdding to the ongoing pursuit of individual-based treatment, the results show subtyping based on a dimensional conceptualization and unique constellations of anxiety and depression symptoms is supported by distinct brain static functional connectivity patterns.

scholarly journals Neuroplasticity Within and between Functional Brain Networks in Mental Training Based on Long-Term Meditation

2021 ◽  
Vol 11 (8) ◽  
pp. 1086
Author(s):  
Roberto Guidotti ◽  
Cosimo Del Gratta ◽  
Mauro Gianni Perrucci ◽  
Gian Luca Romani ◽  
Antonino Raffone
Keyword(s):  
Large Scale ◽  
Brain Connectivity ◽  
Brain Networks ◽  
Connectivity Pattern ◽  
Mental Training ◽  
Functional Brain ◽  
Connectivity Patterns ◽  
Open Monitoring ◽  
The Impact

(1) The effects of intensive mental training based on meditation on the functional and structural organization of the human brain have been addressed by several neuroscientific studies. However, how large-scale connectivity patterns are affected by long-term practice of the main forms of meditation, Focused Attention (FA) and Open Monitoring (OM), as well as by aging, has not yet been elucidated. (2) Using functional Magnetic Resonance Imaging (fMRI) and multivariate pattern analysis, we investigated the impact of meditation expertise and age on functional connectivity patterns in large-scale brain networks during different meditation styles in long-term meditators. (3) The results show that fMRI connectivity patterns in multiple key brain networks can differentially predict the meditation expertise and age of long-term meditators. Expertise-predictive patterns are differently affected by FA and OM, while age-predictive patterns are not influenced by the meditation form. The FA meditation connectivity pattern modulated by expertise included nodes and connections implicated in focusing, sustaining and monitoring attention, while OM patterns included nodes associated with cognitive control and emotion regulation. (4) The study highlights a long-term effect of meditation practice on multivariate patterns of functional brain connectivity and suggests that meditation expertise is associated with specific neuroplastic changes in connectivity patterns within and between multiple brain networks.

Association between metabolic syndrome and resting-state functional brain connectivity

2021 ◽  
Author(s):  
Barnaly Rashid ◽  
Victoria N. Poole ◽  
Francesca C. Fortenbaugh ◽  
Michael Esterman ◽  
William P. Milberg ◽  
...  
Keyword(s):  
Metabolic Syndrome ◽  
Resting State ◽  
Brain Connectivity ◽  
Functional Brain
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