scholarly journals Effects of bariatric surgery on functional connectivity of the reward and default mode network: A pre‐registered analysis

2021 ◽  
Author(s):  
Hannah S. Heinrichs ◽  
Frauke Beyer ◽  
Evelyn Medawar ◽  
Kristin Prehn ◽  
Jürgen Ordemann ◽  
...  
Keyword(s):  
Bariatric Surgery ◽  
Functional Connectivity ◽  
Default Mode Network ◽  
Default Mode

scholarly journals Effects of bariatric surgery on functional connectivity of the reward and default mode network: a pre-registered analysis

2021 ◽  
Author(s):  
Hannah S. Heinrichs ◽  
Frauke Beyer ◽  
Evelyn Medawar ◽  
Kristin Prehn ◽  
Juergen Ordemann ◽  
...  
Keyword(s):  
Bariatric Surgery ◽  
Functional Connectivity ◽  
Default Mode Network ◽  
Resting State ◽  
Interaction Analysis ◽  
Brain Networks ◽  
Group Interaction ◽  
Head Motion ◽  
Whole Brain ◽  
Default Mode

Obesity imposes serious health risks and involves alterations in resting-state functional connectivity of brain networks involved in eating behavior. Bariatric surgery is an effective treatment, but its effects on functional connectivity are still under debate. In this pre-registered study, we aimed to determine the effects of bariatric surgery on major resting-state brain networks (reward and default mode network) in a longitudinal controlled design. 33 bariatric surgery patients and 15 obese waiting-list control patients (37 females; aged 44.15 ± 11.86 SD years (range 21-68)) underwent magnetic resonance imaging at baseline, after 6 and 12 months. We conducted a pre-registered whole-brain time-by-group interaction analysis, and a time-by-group interaction analysis on within-network connectivity (https://osf.io/f8tpn/, https://osf.io/59bh7/). In exploratory analyses, we investigated the effects of weight loss and head motion. Bariatric surgery compared to waiting did not significantly affect functional connectivity (FWE-corrected p > 0.05), neither whole-brain nor within-network. In exploratory analyses, surgery-related BMI decrease (FWE-corrected p = 0.041) and higher average head motion (FWE-corrected p = 0.021) resulted in significantly stronger connectivity of the reward network with medial posterior frontal regions. This pre-registered well-controlled study did not support a strong effect of bariatric surgery, compared to waiting, on major resting-state brain networks after 6 months. Exploratory analyses indicated that head motion might have confounded the effects. Data pooling and more rigorous control of within-scanner head motion during data acquisition are needed to substantiate effects of bariatric surgery on brain organization.

scholarly journals Functional Connectivity of Paired Default Mode Network Subregions in Retinal Detachment

2018 ◽  
Vol 7 (6) ◽  
pp. 15
Author(s):  
Ting Su ◽  
Yong-Qiang Shu ◽  
Kang-Cheng Liu ◽  
Lei Ye ◽  
Ling-Long Chen ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Retinal Detachment ◽  
Default Mode Network ◽  
Default Mode

scholarly journals Aberrant Dynamic Functional Connectivity of Default Mode Network in Schizophrenia and Links to Symptom Severity

2021 ◽  
Vol 15 ◽  
Author(s):  
Mohammad S. E. Sendi ◽  
Elaheh Zendehrouh ◽  
Charles A. Ellis ◽  
Zhijia Liang ◽  
Zening Fu ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Default Mode Network ◽  
Resting State ◽  
Symptom Severity ◽  
Transition Probability ◽  
Feature Selection Method ◽  
Cingulate Cortex ◽  
Anterior Cingulate ◽  
Dynamic Functional Connectivity ◽  
Default Mode

Background: Schizophrenia affects around 1% of the global population. Functional connectivity extracted from resting-state functional magnetic resonance imaging (rs-fMRI) has previously been used to study schizophrenia and has great potential to provide novel insights into the disorder. Some studies have shown abnormal functional connectivity in the default mode network (DMN) of individuals with schizophrenia, and more recent studies have shown abnormal dynamic functional connectivity (dFC) in individuals with schizophrenia. However, DMN dFC and the link between abnormal DMN dFC and symptom severity have not been well-characterized.Method: Resting-state fMRI data from subjects with schizophrenia (SZ) and healthy controls (HC) across two datasets were analyzed independently. We captured seven maximally independent subnodes in the DMN by applying group independent component analysis and estimated dFC between subnode time courses using a sliding window approach. A clustering method separated the dFCs into five reoccurring brain states. A feature selection method modeled the difference between SZs and HCs using the state-specific FC features. Finally, we used the transition probability of a hidden Markov model to characterize the link between symptom severity and dFC in SZ subjects.Results: We found decreases in the connectivity of the anterior cingulate cortex (ACC) and increases in the connectivity between the precuneus (PCu) and the posterior cingulate cortex (PCC) (i.e., PCu/PCC) of SZ subjects. In SZ, the transition probability from a state with weaker PCu/PCC and stronger ACC connectivity to a state with stronger PCu/PCC and weaker ACC connectivity increased with symptom severity.Conclusions: To our knowledge, this was the first study to investigate DMN dFC and its link to schizophrenia symptom severity. We identified reproducible neural states in a data-driven manner and demonstrated that the strength of connectivity within those states differed between SZs and HCs. Additionally, we identified a relationship between SZ symptom severity and the dynamics of DMN functional connectivity. We validated our results across two datasets. These results support the potential of dFC for use as a biomarker of schizophrenia and shed new light upon the relationship between schizophrenia and DMN dynamics.

scholarly journals Cognitive Improvement is Correlated with Increased Dynamic Functional Connectivity of Default Mode Network by Personalized rTMS in Alzheimer's Disease

2021 ◽  
Author(s):  
Lili Wei ◽  
Jintao Wang ◽  
Yingchun Zhang ◽  
Luoyi Xu ◽  
Kehua Yang ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Functional Connectivity ◽  
Default Mode Network ◽  
Present Report ◽  
Verbal Learning ◽  
Dynamic Functional Connectivity ◽  
Default Mode ◽  
Cognitive Improvement ◽  
Promising Therapeutic Approach

Abstract Background Repetitive transcranial magnetic stimulation (rTMS) is thought to be a promising therapeutic approach for Alzheimer's disease patients. Methods In the present report, a double-blind, randomized, sham-controlled rTMS trial was conducted in mild-to-moderate Alzheimer's disease patients. High-frequency rTMS was delivered to a subject-specific left lateral parietal region that demonstrated highest functional connectivity with the hippocampus using resting-state fMRI. The Mini Mental State Examination (MMSE) and Philadelphia Verbal Learning Test (PVLT) were used to evaluate patients’ cognitive functions. Results Patients receiving active rTMS treatment (n = 31) showed a significant increase in the MMSE, PVLT-Immediate recall, and PVLT-Short Delay recall scores after two weeks of rTMS treatment, whereas patients who received sham rTMS (n = 27) did not show significant changes in these measures. Dynamic functional connectivity (dFC) magnitude of the default mode network (DMN) in the active-rTMS group showed a significant increase after two weeks of rTMS treatment, and no significant changes were found in the sham-rTMS group. There was a significantly positive correlation between changes of the MMSE and changes of the dFC magnitude of DMN in the active-rTMS group, but not the sham-rTMS group. Conclusions Our findings are novel in demonstrating the feasibility and effectiveness of the fMRI-guided rTMS treatment in Alzheimer's disease patients, and DMN might play a vital role in therapeutic effectiveness of rTMS in Alzheimer’s disease. Trial registration: China National Medical Research Platform (http://114.255.48.20/login, No:MR-33-20-004217), retrospectively registered 2020-12-23.

scholarly journals I know that I don’t know: Structural and functional connectivity underlying meta-ignorance in pre-schoolers

2018 ◽  
Author(s):  
Elisa Filevich ◽  
Caroline Garcia Forlim ◽  
Carmen Fehrman ◽  
Carina Forster ◽  
Markus Paulus ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Default Mode Network ◽  
Orbitofrontal Cortex ◽  
Cingulate Gyrus ◽  
Partial Knowledge ◽  
Metacognitive Monitoring ◽  
Default Mode ◽  
Posterior Cingulate Gyrus ◽  
Knowledge Condition ◽  
The Brain

Research Highlights[1] Children develop the ability to report that they do not know something at around five years of age.[2] Children who could correctly report their own ignorance in a partial-knowledge task showed thicker cortices within medial orbitofrontal cortex.[3] This region was functionally connected to parts of the default-mode network.[4] The default-mode network might support the development of correct metacognitive monitoring.AbstractMetacognition plays a pivotal role in human development. The ability to realize that we do not know something, or meta-ignorance, emerges after approximately five years of age. We aimed at identifying the brain systems that underlie the developmental emergence of this ability in a preschool sample.Twenty-four children aged between five and six years answered questions under three conditions of a meta-ignorance task twice. In the critical partial knowledge condition, an experimenter first showed two toys to a child, then announced that she would place one of them in a box behind a screen, out of sight from the child. The experimenter then asked the child whether or not she knew which toy was in the box.Children who answered correctly both times to the metacognitive question in the partial knowledge condition (n=9) showed greater cortical thickness in a cluster within left medial orbitofrontal cortex than children who did not (n=15). Further, seed-based functional connectivity analyses of the brain during resting state revealed that this region is functionally connected to the medial orbitofrontal gyrus, posterior cingulate gyrus and precuneus, and mid- and inferior temporal gyri.This finding suggests that the default mode network, critically through its prefrontal regions, supports introspective processing. It leads to the emergence of metacognitive monitoring allowing children to explicitly report their own ignorance.

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