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.
Impaired activation of cortical circuits might contribute to working memory deficits in schizophrenia. In this disorder, layer 3 pyramidal neurons (L3PNs) of the prefrontal (PFC), primary visual (V1) and posterior parietal (PPC) cortices, three cortical areas essential for working memory, display alterations that may impair network activity. We review evidence suggesting that L3PN morphology and physiology differ significantly across PFC, PPC and V1 in primates. These differences are much less pronounced in rodents, suggesting a primate-enhanced regional variability that may be the substrate for area-specific L3PN vulnerability in schizophrenia. PFC L3PNs exhibit larger dendrites with higher spine density, thus substantially more excitatory synapses than V1 or PPC L3PNs. Furthermore, the PFC contains a unique stripe-like connectivity system mediated by the horizontal axon collaterals of L3PNs that might support robust recurrent excitation, and thus the mnemonic persistent activity thought to contribute to working memory storage. Physiologically, PFC L3PNs display higher spontaneous excitatory post-synaptic current (sEPSC) frequency and amplitude, indicating functionally more potent individual synapses in PFC than in V1 L3PNs. Although sEPSC differences are less pronounced between PPC and PFC L3PNs, the greater spine density in PFC suggests stronger excitatory drive in PFC L3PNs. We conclude by identifying open questions that are relevant for understanding schizophrenia pathophysiology: i) What are the sources of synaptic input on L3PNs in each area?, ii) What is the significance of dendritic spine density differences across areas?, and iii) Do NMDAR-mediated synaptic currents differ in strength between L3PNs in PFC, PPC, and V1?
G. González-Burgos, Ruth Benavides-Piccione, A. Neef et al.· Biological Psychiatry· 0 citations