scholarly journals Recovery-associated resting-state activity and connectivity alterations in Anorexia nervosa

2020 ◽  
Author(s):  
Leon D. Lotter ◽  
Georg von Polier ◽  
Jan Offermann ◽  
Kimberly Buettgen ◽  
Lukas Stanetzky ◽  
...  
Keyword(s):  
Anorexia Nervosa ◽  
Resting State ◽  
Low Frequency ◽  
Disease Status ◽  
Resting State Fmri ◽  
Grey Matter Volume ◽  
Cross Sectional ◽  
State Activity ◽  
Global Correlation ◽  
The Impact

AbstractBackgroundPrevious studies provided controversial insight on the impact of starvation, disease status as well as of underlying grey matter volume (GMV) changes on resting-state functional magnetic resonance imaging (rsfMRI) alterations in anorexia nervosa (AN). Here we adapt a combined longitudinal and cross-sectional approach to disentangle the effects of these factors on resting-state alterations in AN.MethodsOverall, 87 subjects were included in the study: adolescent patients with acute AN scanned at inpatient admission (N = 22) and at discharge (N = 21), 21 patients recovered from AN and two groups of healthy age-matched controls (both N = 22). Whole-brain measures of resting-state activity and functional connectivity were computed (Network Based Statistics, Global Correlation, Integrated Local Correlation, fractional Amplitude of Low Frequency Fluctuations) to assess rsfMRI alterations over the course of AN treatment before and after controlling for underlying GMV.ResultsPatients with acute AN displayed strong and widespread prefrontal, sensorimotor, parietal, temporal, precuneal and insular reductions of resting-state connectivity and activity. All alterations were independent of GMV and were largely normalized in short- and absent in long-term recovered AN.ConclusionsResting-state fMRI alterations in AN constitute acute and GMV independent presumably starvation-related phenomena. All alterations found here normalized over the course of recovery without evidence for possible preexisting trait- or remaining “scar”-effects.

scholarly journals Post-Training Sleep Modulates Topographical Relearning-Dependent Resting State Activity

2021 ◽  
Vol 11 (4) ◽  
pp. 476
Author(s):  
Michele Deantoni ◽  
Thomas Villemonteix ◽  
Evelyne Balteau ◽  
Christina Schmidt ◽  
Philippe Peigneux
Keyword(s):  
Resting State ◽  
Low Frequency ◽  
Brain Structures ◽  
Resting State Fmri ◽  
Related Activity ◽  
State Activity ◽  
Before And After ◽  
Task Practice ◽  
Behavioural Performance ◽  
The Town

Continuation of experience-dependent neural activity during offline sleep and wakefulness episodes is a critical component of memory consolidation. Using functional magnetic resonance imaging (fMRI), offline consolidation effects have been evidenced probing behavioural and neurophysiological changes during memory retrieval, i.e., in the context of task practice. Resting state fMRI (rsfMRI) further allows investigating the offline evolution of recently learned information without the confounds of online task-related effects. We used rsfMRI to investigate sleep-related changes in seed-based resting functional connectivity (FC) and amplitude of low frequency fluctuations (ALFF) after spatial navigation learning and relearning. On Day 1, offline resting state activity was measured immediately before and after topographical learning in a virtual town. On Day 4, it was measured again before and after relearning in an extended version of the town. Navigation-related activity was also recorded during target retrieval, i.e., online. Participants spent the first post-training night under regular sleep (RS) or sleep deprivation (SD) conditions. Results evidence FC and ALFF changes in task-related neural networks, indicating the continuation of navigation-related activity in the resting state. Although post-training sleep did not modulate behavioural performance, connectivity analyses evidenced increased FC after post-training SD between navigation-related brain structures during relearning in the extended environment. These results suggest that memory traces were less efficiently consolidated after post-learning SD, eventually resulting in the use of compensatory brain resources to link previously stored spatial elements with the newly presented information.

Functional abnormalities in Broca’s area in adolescents with ADHD: A resting-state fMRI study

2015 ◽  
Vol 51 (1) ◽  
Author(s):  
Michał Pikusa ◽  
Rafał Jończyk
Keyword(s):  
Resting State ◽  
Low Frequency ◽  
Resting State Fmri ◽  
Broca’S Area ◽  
Broca's Area ◽  
Hyperactivity Disorder ◽  
Spontaneous Neural Activity ◽  
Fmri Study ◽  
Brodmann Areas ◽  
Underlying Causes

AbstractThere is evidence that attention-deficit/hyperactivity disorder (ADHD) is associated with linguistic difficulties. However, the pathophysiology underlying these difficulties is yet to be determined. This study investigates functional abnormalities in Broca’s area, which is associated with speech production and processing, in adolescents with ADHD by means of resting-state fMRI. Data for the study was taken from the ADHD-200 project and included 267 ADHD patients (109 with combined inattentive/hyperactive subtype and 158 with inattentive subtype) and 478 typically-developing control (TDC) subjects. An analysis of fractional amplitude of low-frequency fluctuations (fALFF), which reflects spontaneous neural activity, in Broca’s area (Brodmann Areas 44/45) was performed on the data and the results were compared statistically across the participant groups. fALFF was found to be significantly lower in the ADHD inattentive group as compared to TDC in BA 44, and in the ADHD combined group as compared to TDC in BA 45. The results suggest that there are functional abnormalities in Broca’s area with people suffering from ADHD, and that the localization of these abnormalities might be connected to particular language deficits associated with ADHD subtypes, which we discuss in the article. The findings might help explore the underlying causes of specific language difficulties in ADHD.

scholarly journals The effect of global signal regression on DCM estimates of noise and effective connectivity from resting state fMRI

2019 ◽  
Author(s):  
Hannes Almgren ◽  
Frederik Van de Steen ◽  
Adeel Razi ◽  
Karl Friston ◽  
Daniele Marinazzo
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Effective Connectivity ◽  
Network Connectivity ◽  
Resting State Fmri ◽  
Measurement Noise ◽  
Resting State Networks ◽  
Cross Sectional ◽  
Global Signal ◽  
Leibler Divergence

AbstractThe influence of the global BOLD signal on resting state functional connectivity in fMRI data remains a topic of debate, with little consensus. In this study, we assessed the effects of global signal regression (GSR) on effective connectivity within and between resting-state networks – as estimated with dynamic causal modelling (DCM) for resting state fMRI (rsfMRI). DCM incorporates a forward (generative) model that quantifies the contribution of different types of noise (including global measurement noise), effective connectivity, and (neuro)vascular processes to functional connectivity measurements. DCM analyses were applied to two different designs; namely, longitudinal and cross-sectional designs. In the modelling of longitudinal designs, we included four extensive longitudinal resting state fMRI datasets with a total number of 20 subjects. In the analysis of cross-sectional designs, we used rsfMRI data from 361 subjects from the Human Connectome Project. We hypothesized that (1) GSR would have no discernible impact on effective connectivity estimated with DCM, and (2) GSR would be reflected in the parameters representing global measurement noise. Additionally, we performed comparative analyses of the informative value of data with and without GSR. Our results showed negligible to small effects of GSR on connectivity within small (separately estimated) RSNs. For between-network connectivity, we found two important effects: the effect of GSR on between-network connectivity (averaged over all connections) was negligible to small, while the effect of GSR on individual connections was non-negligible. Contrary to our expectations, we found either no effect (in the longitudinal designs) or a non-specific (cross-sectional design) effect of GSR on parameters representing (global) measurement noise. Data without GSR were found to be more informative than data with GSR; however, in small resting state networks the precision of posterior estimates was greater using data after GSR. In conclusion, GSR is a minor concern in DCM studies; however, individual between-network connections (as opposed to average between-network connectivity) and noise parameters should be interpreted quantitatively with some caution. The Kullback-Leibler divergence of the posterior from the prior, together with the precision of posterior estimates, might offer a useful measure to assess the appropriateness of GSR, when nuancing data features in resting state fMRI.

scholarly journals The concept of control in chronic obstructive pulmonary disease: Development of the criteria and validation for use in clinical practice

2020 ◽  
Vol 30 (2) ◽  
pp. 135-141
Author(s):  
M. Miravitlles ◽  
B. Alcázar ◽  
J. J. Soler-Cataluña
Keyword(s):  
Chronic Obstructive Pulmonary Disease ◽  
Pulmonary Disease ◽  
Clinical Status ◽  
Disease Status ◽  
Chronic Obstructive ◽  
Cross Sectional ◽  
Obstructive Pulmonary Disease ◽  
Clinical Criteria ◽  
The Impact ◽  
Control Tool

Guidelines of treatment of chronic obstructive pulmonary disease (COPD) identify symptom reduction and prevention of exacerbations as the main goals of therapy. Initial pharmacological treatment must be guided by these parameters, and effectiveness must be assessed at each clinical visit. However, there is no clear guidance as to how this assessment must be performed. The concept of control has been well developed in asthma, but it has been elusive in COPD. Patients with COPD may not be completely free from symptoms or exacerbations even under optimized therapy; therefore, control in COPD does not mean cure or absence of symptoms, but rather reaching the best clinical status possible according to the level of disease severity. A control tool has been developed based on a cross sectional evaluation of the impact of the disease and a longitudinal evaluation of stability. Low impact is a disease status defined by at least 3 of the following: low levels of dyspnoea, absence of or white sputum, low use of rescue medication and self-declared walking time of more than 30 minutes a day, and stability is the absence of moderate or severe exacerbations in the previous 3 months. Control can also be defined by COPD Assessment Test (CAT) scores ≤ 10 units for patients with FEV1 ≥ 50% and 16 for patients with FEV1 < 50% and stability as a change in CAT ≤ 2 units. Control of COPD is then defined as a status of low impact and stability. The control tool has been validated prospectively in several studies and has demonstrated to be sensitive to clinical changes and to have a good predictive value for poor outcomes. Clinical criteria are more reliable than CAT scores for the evaluation of control. The control tool is a quick and inexpensive method to evaluate clinical status and future risk of exacerbations that can be used at all levels of healthcare. 

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