Using high-field fMRI and a novel connectivity analysis, this study found abnormal network hubs across multiple systems in FDS, supporting a predictive processing model and offering preliminary biomarkers to improve FDS differentiation, pending validation in larger cohorts.
Abstract
Objective
This study investigates alterations in brain functional networks in patients with functional/dissociative seizures (FDS) using a novel functional connectivity framework, with the goal of showing network-level biomarkers that may differentiate FDS from healthy controls.
Methods
We conducted a 7-Tesla fMRI study involving 11 patients with FDS and 11 healthy controls (HC) gotten during both resting-state (rs) and a naturalistic-stimulus (ns) movie paradigm. Functional connectivity) was computed using parcel-wise Pearson correlations, and centrality measures, including eigenvector centrality, were derived to assess network influence. Group differences were evaluated using motion-controlled general linear models A sensitivity index found key ROIs, which were used in cross-validated logistic regression models. The classification model uses eigenvector centrality with 5-fold cross-validation.
Results
FDS patients showed consistent alterations in eigenvector centrality across both resting-state and naturalistic-stimulus fMRI, particularly within limbic, somatomotor, and ventral attention network. Three key ROIs during rest and fifteen during naturalistic stimulation yielded high classification accuracies (96% and 93%, respectively). Several hubs found in the movie condition remained altered at rest. Logistic regression models using these network features distinguished FDS from controls, though findings require cautious interpretation due to sample size limitations.
Conclusions
Using high-field fMRI and a novel connectivity analysis, this study found abnormal network hubs across multiple systems in FDS. These findings support a predictive processing model and offer preliminary biomarkers to improve FDS differentiation, pending validation in larger cohorts.
BACKGROUND
Functional/dissociative seizure (FDS) disorder presents diagnostic challenges due to its complex semiology and the lack of positive diagnostic biomarkers. Current evidence suggests that specific patterns of brain activity and distinct dynamics in the brain network may underlie the neurobiological mechanisms of FDS.
METHODS
We retrospectively analyzed ictal EEG recordings from 46 patients with FDS, in three different conditions: during resting wakefulness (RW), during resting while having eyes closed (EC), and during functional/dissociative seizures of variable semiology (FDS). The occipital EEG in the alpha band (8-13 Hz) was assessed in terms of power and functional connectivity, quantified by debiased weighted phase lag index (dwPLI). Heart rate was also analyzed across conditions. Statistical comparisons were performed via paired permutation testing with Benjamini-Hochberg correction for multiple comparisons, complemented by Bayes factors for the key FDS-EC comparisons.
RESULTS
EEG during FDS exhibited significantly higher occipital alpha power than RW (p = 0.0003) and levels not significantly different from EC, with moderate Bayesian evidence for the absence of a difference (BF01 = 6.1). Alpha power was elevated across all FDS subtypes and was, paradoxically, numerically highest in hypermotor seizures, although subtype differences did not survive correction for multiple comparisons. Control analyses showed that the alpha power did not significantly differ across video-rated states of eyes during FDS (open, intermittently closed, closed), including when conditions were matched for eye state. Functional whole-brain connectivity in the alpha band was intermediate between the two resting conditions, being higher during FDS than during RW but lower than during EC. Heart rate was highest during FDS, with a non-significant tendency toward higher rates in hypermotor than atonic FDS. No significant correlation was found between occipital alpha power and heart rate during FDS.
CONCLUSION
Our findings suggest that FDS are characterized by a paradoxical hypersynchronization in the EEG alpha band, similar to EC, despite concurrent motor activity. Increased functional alpha connectivity, simultaneous with elevated heart rate during FDS, suggests that FDSs involve altered brain network dynamics rather than simple alpha power suppression by voluntary motor activity. These findings may aid in developing positive biomarkers for FDS diagnosis.
T. Dubček, Meret Küenzler, M. Schmutz et al.· Epilepsy & Behavior· 0 citations
Objective To investigate alterations in resting-state functional connectivity (rs-FC) and the standard deviation of dynamic functional connectivity (dFCstd) of the bilateral insula in patients with migraine without aura (MwoA), and to examine their associations with clinical symptoms. Methods Resting-state functional magnetic resonance imaging (rs-fMRI) was conducted on 45 patients with MwoA and 45 healthy controls (HCs). The left and right insulae were defined as seed regions according to the AAL116 atlas. rs-FC and dFCstd were calculated between each insular seed and the remaining 115 brain regions, with dFCstd defined as the standard deviation of Fisher-z transformed connectivity estimates across sliding windows. Group differences were evaluated with general linear models adjusted for age and sex, with false discovery rate (FDR) correction applied for multiple comparisons. Associations between altered functional connectivity and clinical measures were further examined within the MwoA group. Results Patients with MwoA had higher rs-FC than HCs for the left and right insulae with the right hippocampus. Dynamic connectivity analysis identified lower dFCstd involving the left insula and ipsilateral caudate nucleus and higher dFCstd involving the left insula and ipsilateral superior frontal gyrus, orbital part. All group differences survived FDR correction. Exploratory correlation analyses showed that several altered connectivity measures were associated with monthly migraine attack frequency, visual analog scale (VAS) scores, and Self-Rating Depression Scale (SDS) standard scores. Conclusion Combined rs-FC and dFCstd analyses revealed altered functional connectivity involving the insula in patients with MwoA. These connectivity patterns may reflect disturbances in neural circuits supporting pain processing, emotion regulation, and cognitive control, providing complementary imaging evidence for brain network dysfunction in MwoA.
Guo-Yun Liu, Ziting Cao, Yi-Chao Chen et al.· Frontiers in Neurology· 0 citations
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