Entropy of resting state networks and quality of life in functional seizures
Abstract number :
2.464
Submission category :
5. Neuro Imaging / 5B. Functional Imaging
Year :
2022
Submission ID :
2233040
Source :
www.aesnet.org
Presentation date :
12/4/2022 12:00:00 PM
Published date :
Nov 22, 2022, 05:29 AM
Authors :
Rodolphe Nenert, PhD – 1University of Alabama at Birmingham, Birmingham, AL; Jane Allendorfer, PhD – University of Alabama at Birmingham, Birmingham, AL; Stephen Correia, PhD – Brown University, Providence VAMC, Providence, RI; Tyler Gaston, MD – University of Alabama at Birmingham, Birmingham, AL; Adam Goodman, PhD – University of Alabama at Birmingham, Birmingham, AL; Leslie Grayson, MD – University of Alabama at Birmingham, Birmingham, AL; W. Curt LaFrance, MD – Brown University, Providence VAMC, Providence, RI; Noah Philip, MD – Brown University, Providence VAMC, Providence, RI; Jerzy Szaflarski, MD,PhD – University of Alabama at Birmingham, Birmingham, AL
This is a Late Breaking abstract
Rationale: Entropy analysis is a computational method used to quantify the complexity in a system. Abnormal entropy has been shown to be associated with mental health abnormalities and neurodegenerative disorders. We analyzed brain entropy in adults with functional seizures (FS; also known as psychogenic nonepileptic seizures) who underwent a neuro-behavioral therapy (NBT) aimed at reducing FS. We hypothesized that treatment response would be associated with significant changes in entropy in multiple resting-state networks (Default-mode -DMN, fronto-parietal-FPN, salience-SN, executive-EN and sensorimotor-SMN) and that these changes would correlate with post-treatment changes in behavioral and quality of life measures.
Methods: A total of 42 patients with traumatic brain injury (TBI) and FS (TBI+FS) underwent 12 sessions of NBT and provided pre-/post-intervention neuroimaging and behavioral data; 47 control individuals with TBI without FS (TBI-only) completed the same measures but did not receive NBT. Patients completed the Beck Depression Inventory II (BDI-II), the QOL in Epilepsy (QOLIE-31) and the Global Assessment of Functioning (GAF) and underwent resting-state functional MRI (rs-fMRI) during the same interval. Sample Entropy (SampEn) values representing FPN brain entropy and stability were calculated in each subject using the Brain Entropy Mapping Toolbox (BENtbx). The BENtbx utilizes SampEn, an extension of Approximate Entropy, which is stable for data such as fMRI time-series. Regions of interest representing the resting-state networks were computed using independent component analysis (Goodman et al., under review). Correlations were performed to examine relationships between depression symptom severity (BDI-II), overall QOL score and SampEn values before, and after NBT.
Results: TBI-FS group showed significant reduction in FS frequency in response to NBT (p=0.01). Neither group showed significant entropy changes over time. Repeated-measures ANOVA showed no significant group-by-time interaction for entropy values. Significant improvement for all behavioral scores were found only for TBI+FS group (all p< 0.0001). Regarding the relationships between entropy and behavioral scores in the TBI-only group, the overall QOL score change over time was negatively correlated with changes in entropy in SMN (r=-0.3, p=0.04) and showed a trend of negative correlation marginally for DMN (r=-0.29, p=0.059), ECN (r=-0.20, p=0.065), FP (r=-0.29, p=0.061) and SN (r=-0.28, p=0.07). No significant correlations were found with BDI and GAF scores (all p >0.1).
Conclusions: While NBT reduced frequency of FS, we did not observe a change in the energy state or complexity of resting-state networks in the FS cohort. However, in the untreated TBI-only group, we observed a negative correlation between change in QOL and change entropy. Thus, it is possible that the NBT, while significantly improving behavioral measures and seizure frequency, also disrupts the negative relationship between energy state and quality of life.
Funding: This work was supported by the US Department of Defense (W81XH-17-0619) to W.C.L. and J.P.S.
Neuro Imaging