The neurocognitive correlates of brain entropy estimated by resting state fMRI

Wang, Ze

doi:10.1016/j.neuroimage.2021.117893

Cited by 40 publications

(70 citation statements)

References 84 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Here we will investigate the 'pure' s/g differences in the mMSE features, without a reference to any cognitive task. In line with the previous studies (Ahmadi et al, 2013;Pravitha et al, 2005;Wang, 2021) we hypothesize that women will demonstrate higher total rsEEG complexity than men and this effect will be more likely observed for all analyzed electrode sets (networks).…”

Section: Introductionsupporting

confidence: 87%

“…Taking into account the speci c skewed inverted-U shape pro le of the mMSE vector (Fig. 1), observed in the previous studies (e.g., Costa et al, 2005;Dreszer et al, 2020;Kuntzelman et al, 2018;Wang et al, 2012;Wang, 2021), the following features of the mMSE curve were determined: the area under curve (AUC) to characterize the general (total) entropy level, the MaxSlope and the AvgEnt to capture the complexity at the high-frequency ne scales and at the low-frequency coarse scales respectively, as well as the DiffEnt to check whether the entropy level at the ne scales was relatively stable at the coarse scales.…”

Section: Mmse Featuresmentioning

confidence: 89%

“…spatial frequency of the brain surface gyri cation and ssuration, in females compared to males. Wang demonstrated higher SampEn values of restingstate fMRI activity in women than men in most cortical areas (Wang, 2021). Some rsEEG studies also revealed that females, relative to males, displayed greater complexity of the signals recorded over the anterior, central and posterior regions (Ahmadi et al, 2013;Fernández et al, 2012;Pravitha et al, 2005).…”

Section: Introductionmentioning

confidence: 93%

See 2 more Smart Citations

Multivariate Multiscale Entropy (mMSE) as a tool for understanding the resting-state EEG signal dynamics: the spatial distribution and sex/gender- related differences

Lewandowska

Tołpa

Rogala

et al. 2023

Preprint

View full text Add to dashboard Cite

Background The study aimed to determine the resting-state EEG (rsEEG) dynamics quantified using the multivariate Multiscale Entropy (mMSE), and the sex/gender (s/g) differences in the mMSE features. The rsEEG was acquired from 95 healthy adults. For each channel set the AUC, that represents the total complexity, the MaxSlope and AvgEnt referring to the entropy at the fine- and coarse-grained scales, respectively, were extracted. The difference in the entropy between the #9 and #4 timescale (DiffEnt) was also calculated. Results We found the highest AUC for the channel sets corresponding to the somatomotor (SMN), dorsolateral network (DAN) and default mode (DMN) whereas the visual network (VN), limbic (LN), and frontoparietal (FPN) network showed the lowest AUC. The largest MaxSlope were in the SMN, DMN, ventral attention network (VAN), LN and FPN, and the smallest in the VN. The SMN and DAN were characterized by the highest and the LN, FPN, and VN by the lowest AvgEnt. The most stable entropy were for the DAN and VN while the LN showed the greatest drop of entropy at the coarse scales. Women, compared to men, showed higher MaxSlope and DiffEnt but lower AvgEnt in all channel sets and there were no s/g differences in the AUC. Conclusions Novel results of the present study are: 1) an identification of the mMSE features that capture entropy at the fine and the coarse timescales in the channel sets corresponding to the main resting-state networks; 2) an indication of the sex/gender differences in these features.

show abstract

Section: Introductionsupporting

confidence: 87%

Section: Mmse Featuresmentioning

confidence: 89%

Section: Introductionmentioning

confidence: 93%

See 1 more Smart Citation

Multivariate Multiscale Entropy (mMSE) as a tool for understanding the resting-state EEG signal dynamics: the spatial distribution and sex/gender- related differences

Lewandowska

Tołpa

Rogala

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…Furthermore, it has been shown in the study by Song et al that BEN can provides features that cannot be fully described by other methods of resting-state brain activity, such as the cerebral blood ow (CBF) and the fractional amplitude of low-frequency uctuation (ALFF) [39]. Moreover, a current study also proposed the neurocognitive correlations of BEN in rs-fMRI [40]. BEN alterations have been shown in various disorder conditions in clinical research, including schizophrenia [41,42], MDD [43], attention de cit hyperactivity disorder [44], insomnia [45], and cocaine addiction [46].…”

Section: Introductionmentioning

confidence: 67%

Aberrant Brain Entropy in Posttraumatic Stress disorder Comorbid with Major Depressive Disorder during the Coronavirus Disease 2019 Pandemic

Fu,

Liang,

Lin

et al. 2023

Preprint

View full text Add to dashboard Cite

Aim Previously, neuroimaging studies on comorbid Posttraumatic-Major depression disorder (PTSD-MDD) comorbidity found abnormalities in multiple brain regions among patients. Recent neuroimaging studies have revealed dynamic nature on human brain activity during resting state, and entropy as an indicator of dynamic regularity may provide a new perspective for studying abnormalities of brain function among PTSD-MDD patients. During the COVID-19 pandemic, there has been a significant increase in the number of patients with PTSD-MDD. We have decided to conduct research on resting-state brain functional activity of patients who developed PTSD-MDD during this period using entropy.Methods 33 patients with PTSD-MDD and 36 matched TCs were recruited. PTSD and depression symptoms were assessed using multiple clinical scales. All subjects underwent functional magnetic resonance imaging (fMRI) scans. And the brain entropy (BEN) maps were calculated using the BEN mapping toolbox. A two-sample t-test was used to compare the differences in the brain entropy between the PTSD-MDD comorbidity group and TC group. Furthermore, correlation analysis was conducted between the BEN changes in patients with PTSD-MDD and clinical scales.Results Compared to the TCs, PTSD-MDD patients had a reduced BEN in the right middle frontal orbital gyrus (R_MFOG), left putamen, and right inferior frontal gyrus, opercular part (R_IFOG). Furthermore, a higher BEN in the R_MFOG was related to higher CAPS and HAMD-24 scores in the patients with PTSD-MDD.Conclusion The results showed that the R_MFOG is a potential marker for showing the symptom severity of PTSD-MDD comorbidity. Consequently, PTSD-MDD may have reduced BEN in frontal and basal ganglia regions which are related to emotional dysregulation and cognitive deficits.

show abstract

“…There is usually an inverted U-shaped relationship between entropy and age, across the lifespan, resting-state brain entropy (BEN) is positively correlated with age during youth (Z. Wang, 2021), but BEN is generally reduced in aging subjects (Smith et al, 2014;Sokunbi, 2014;Sokunbi et al, 2015) and cognitive-impaired patients (Niu et al, 2018;Ren et al, 2020;B. Wang et al, 2017).…”

Section: Definition Of Entropy and Its Applicationsmentioning

confidence: 99%

From local properties to brain‐wide organization: A review of intraregional temporal features in functional magnetic resonance imaging data

Wang

Chen

et al. 2023

Human Brain Mapping

View full text Add to dashboard Cite

Based on the fluctuations ensembled over neighbouring neurons, blood oxygen level‐dependent (BOLD) signal is a mesoscale measurement of brain signals. Intraregional temporal features (IRTFs) of BOLD signal, extracted from regional neural activities, are utilized to investigate how the brain functions in local brain areas. This literature highlights four types of IRTFs and their representative calculations including variability in the temporal domain, variability in the frequency domain, entropy, and intrinsic neural timescales, which are tightly related to cognitions. In the brain‐wide spatial organization, these brain features generally organized into two spatial hierarchies, reflecting structural constraints of regional dynamics and hierarchical functional processing workflow in brain. Meanwhile, the spatial organization gives rise to the link between neuronal properties and cognitive performance. Disrupted or unbalanced spatial conditions of IRTFs emerge with suboptimal cognitive states, which improved our understanding of the aging process and/or neuropathology of brain disease. This review concludes that IRTFs are important properties of the brain functional system and IRTFs should be considered in a brain‐wide manner.

show abstract

The neurocognitive correlates of brain entropy estimated by resting state fMRI

Cited by 40 publications

References 84 publications

Multivariate Multiscale Entropy (mMSE) as a tool for understanding the resting-state EEG signal dynamics: the spatial distribution and sex/gender- related differences

Multivariate Multiscale Entropy (mMSE) as a tool for understanding the resting-state EEG signal dynamics: the spatial distribution and sex/gender- related differences

Aberrant Brain Entropy in Posttraumatic Stress disorder Comorbid with Major Depressive Disorder during the Coronavirus Disease 2019 Pandemic

From local properties to brain‐wide organization: A review of intraregional temporal features in functional magnetic resonance imaging data

Contact Info

Product

Resources

About