Cortical Dysplasias and Epilepsy

Focal cortical dysplasias (FCD) are cortical malformations that represent a major cause of drug-resistant focal epilepsy (Blümcke, 2011). Magnetic resonance images (MRI) are the main tool for their diagnosis and subsequent surgical intervention. However, despite clear histopathological changes, many FCDs lack macro-anatomical abnormalities, often going undetected (Guerrini & Barba, 2021). It is necessary to find better methods for their detection.
Diffusion weighted MRI (dMRI) is ideally suited to probe the architecture of tissue. However, in complex structures such as the cortex, conventional dMRI methods (e.g. DTI) are insufficient (Benjamini, 2021). Novel dMRI methods have been used to reflect regional and layer-level abnormalities in the cerebral cortex of rodents (Villaseñor et al., 2023) and humans (Lampinen 2020, Lorio 2020).
The b-tensor encoding method provides additional information contained in the dMRI signal and yields parameters more specific to the microstructure of tissue. Q-space trajectory imaging (QTI), an analysis technique for b-tensor encoding images, is used to derive micro fractional anisotropy (µFA) and orientation coherence (Cc), information that is not available with standard dMRI (Westin, 2016).
We show the ability of b-tensor dMRI to evaluate the characteristics of the microarchitecture of the cerebral cortex in a rodent model of cortical dysplasia, aiming to improve the detection of FCDs in clinical populations. 

Excitation-inhibition (E:I) imbalance is posited as a fundamental pathophysiological mechanism in temporal lobe epilepsy (TLE).[1] However, previous evidence supporting this hypothesis has been primarily derived from experimental studies in non-human animals. This study aims to non-invasively elucidate the cortical pattern of E:I imbalance in TLE patients and explore its associations with disease severity and cognitive impairment. 

Rumination is uncontrollable, self-reflective, and repetitive thinking about the distress and its possible causes and consequences (Watkins & Roberts, 2020). A wealth of studies has linked it to major depressive disorder (MDD) and indicated its pivotal role in the psychopathology of MDD (Lyubomirsky et al., 2015). Accordingly, a better understanding of its neural basis may pave the way for the next-generation treatment of MDD. Existing evidence from studies using functional magnetic resonance imaging (fMRI) has shown that brain regions of the default mode network (DMN) are involved in active rumination (Zhou et al., 2020). Our previous study further highlighted the enhanced functional connectivity between two subsystems of DMN (i.e., core subsystem and medial temporal lobe (MTL) subsystem) in the neural mechanism underlying the rumination (Chen et al., 2020). To date, no research has investigated the electrophysiological organization underlying the existing functional neuroimaging evidence. Here, leveraging the intracranial electroencephalogram (iEEG) recordings from a group of patients with epilepsy engaging in an active rumination state, we intended to delineate the electrophysiological features of two key nodes from the core subsystem (precuneus) and the MTL subsystem (parahippocampal gyrus). We hypothesized that these two regions would show different electrophysiological activity patterns during rumination as compared to the control condition. 

Epilepsy is one of the most common brain diseases, affecting 1% of the world's population. Drug-resistant epilepsy (DRE) in particular affects 1 in 3 epileptic people. Recurrent seizures which characterize the disorder, occur due to sudden abnormal activity in the brain. This activity is generated in the so-called epileptogenic zone (EZ) network. A precise detection of the epileptogenic zone is crucial to treat DRE. Seizure recordings are used by clinicians to estimate the EZ network. In addition, brain stimulation is used to induce seizures (George 2020). By varying stimulation parameters via trial and error, clinicians aim to pinpoint regions responsible for seizure activity. In this work, we built a virtual epileptic patient cohort and evaluated this modeling framework for capturing empirical SEEG data. 

Hemispherotomy is an effective surgery for treating refractory epilepsy from diffuse unihemispheric lesions[1], [2]. To date, however, postsurgery neuroplastic changes following pediatric hemispherotomy remain unclear. In the present study, we aim to systematically investigate longitudinal changes in gray matter volume (GMV) before and after surgery in two groups of pediatric patients with left and right hemispherotomy. 

Surgery is the most effective treatment to control seizures in pharmaco-resistant temporal lobe epilepsy (TLE) [1-3]. Although this approach focuses on the hippocampus and nearby temporal lobe structures, most patients also show widespread cortical atrophy beyond this disease epicenter. How these alterations elsewhere in the brain are affected by a surgical lesion, however, remains a debate. Here, we assessed whether functional connectivity from surgical lesion locations map to brain networks that are associated with cortical atrophy before and after surgery.