The role of fast activity as a potential biomarker in localization of the epileptogenic zone (EZ) remains controversial due to recently reported unsatisfactory performance. We recently identified a “fingerprint” of the EZ as a time‐frequency pattern that is defined by a combination of preictal spike(s), fast oscillatory activity, and concurrent suppression of lower frequencies. Here we examine the generalizability of the fingerprint in application to an independent series of patients (11 seizure‐free and 13 non‐seizure‐free after surgery) and show that the fingerprint can also be identified in seizures with lower frequency (such as beta) oscillatory activity. In the seizure‐free group, only 5 of 47 identified EZ contacts were outside the resection. In contrast, in the non‐seizure‐free group, 104 of 142 identified EZ contacts were outside the resection. We integrated the fingerprint prediction with the subject's MR images, thus providing individualized anatomical estimates of the EZ. We show that these fingerprint‐based estimates in seizure‐free patients are almost always inside the resection. On the other hand, for a large fraction of the nonseizure‐free patients the estimated EZ was not well localized and was partially or completely outside the resection, which may explain surgical failure in such cases. We also show that when mapping fast activity alone onto MR images, the EZ was often over‐estimated, indicating a reduced discriminative ability for fast activity relative to the full fingerprint for localization of the EZ.

Summary: Purpose: The orbitofrontal (OF) region is one of the least explored regions of the cerebral cortex. There are few studies on patients with electrophysiologically and surgically confirmedOFepilepsy and a negative magnetic resonance imaging (MRI) study. We aimed to examine the neuroimaging characteristics ofMRI‐negativeOFepilepsy with the focus on a voxel‐based morphometricMRIpostprocessing technique.Methods: We included six patients withOFepilepsy, who met the following criteria: surgical resection of theOFlobe with/without adjacent cortex, seizure‐free for ≥12 months, invasive video–electroencephalography (EEG) monitoring showing ictal onset from theOFarea, and preoperativeMRIregarded as negative. Patients were investigated in terms of their image postprocessing and functional neuroimaging characteristics, electroclinical characteristics obtained from noninvasive and invasive evaluations, and surgical pathology.MRIpostprocessing on T₁‐weighted high‐resolution scans was implemented with a morphometric analysis program (MAP) inMATLAB.Key Findings: SingleMAP+ abnormalities were found in four patients; three were in theOFregion and one in the ipsilateral mesial frontal area. These abnormalities were included in the resection. One patient had bilateralMAP+ abnormalities in theOFregion, with the ipsilateral one completely removed. TheMAP+ foci were concordant with invasive electrophysiologic data in the majority ofMAP+ patients (four of five). The localization value of 18F‐fluorodeoxyglucose‐positron emission tomography (FDG‐PET) and ictal single‐photon emission computed tomography (SPECT) is low in this cohort. Surgical pathology included focal cortical dysplasia, remote infarct, Rosenthal fiber formation and gliosis.Significance: Our study highlights the importance ofMRIpostprocessing in the process of presurgical evaluation of patients with suspected orbitofrontal epilepsy and “normal”MRI. UsingMAP, we were able to positively identify subtle focal abnormalities in the majority of the patients.MAPresults need to be interpreted in the context of their electroclinical findings and can provide valuable targets in the process of planning invasive evaluation.

Thalamic electrical stimulation offers a therapeutic approach for refractory epilepsy patients ineligibles for resective surgery. Yet, there is currently no consensus on the optimal stimulation site. We hypothesized that targeting thalamic nuclei with precise anatomical and functional connections (hodological matching) to cortical seizure onset zones (SOZs) could enhance neuromodulatory effects. Thus, we examined three subnuclei (pulvinar, anterior, and ventral intermediate/oral posterior, VIM/VOP) in 41 focal epilepsy patients. Combining neuroimaging and electrophysiology, we identified hodologically-matched targets: pulvinar for posterior-quadrant and temporal SOZs, anterior for frontotemporal, and VIM/VOP for rolandic. Analysis of 274 seizures revealed the critical role of matched nuclei in seizure termination. Stimulation of hodologically-matched (but not unmatched) nuclei immediately suppressed interictal epileptiform discharges. Finally, in 10 chronically implanted patients, matched stimulation substantially reduced seizure frequency (87.5%), compared to unmatched targets (8.3%) over time. Our results underscore the potential of hodological thalamic targeting to modulate epileptiform activity in focal epilepsy.

Epilepsy is a neurological condition with a prevalence of 1%, and 14-34% have medically refractory epilepsy (MRE). Seizures in focal MRE are generated by a single epileptogenic zone (or focus), thus there is potentially a curative procedure - surgical resection. This procedure depends significantly on correct identification of the focus, which is often uncertain in clinical practice. In this study, we analyzed intracranial stereotaxic EEG (sEEG) data recorded in two human patients with drug-resistant epilepsy prior to undergoing resection surgery. We view the sEEG data as samples from the brain network and hypothesize that seizure foci can be identified based on their network connectivity during seizure. Specifically, we computed a time sequence of connectivity matrices from EEG recordings that represent network structure over time. For each patient, connectivity between electrodes was measured using the coherence in a given frequency band. Matrix structure was analyzed using singular value decomposition and the leading singular vector was used to estimate each electrode's time dependent centrality (importance to the network's connectivity). Our preliminary study suggests that seizure foci may be the most weakly connected regions in the brain during the beginning of a seizure and the most strongly connected regions towards the end of a seizure. Additionally, in one of the patients analyzed, the network connectivity under anesthesia highlights seizure foci. Ultimately, network centrality computed from sEEG activity may be used to develop an automated, reliable, and computationally efficient algorithm for identifying seizure foci.

Objective: Epilepsy is recognized increasingly as a network disease, with changes extending beyond the epileptogenic zone (EZ). However, more studies of structural connectivity are needed to better understand the behavior and nature of this condition.Methods: In this study, we applied differential tractography, a novel technique that measures changes in anisotropic diffusion, to assess widespread structural connectivity alterations in a total of 42 patients diagnosed with medically refractory epilepsy (MRE), including 27 patients with focal epilepsy and 15 patients with multifocal epilepsy that were included to validate our hypothesis. All patients were compared individually to an averaged database constructed from 19 normal controls regressed by age and sex.Results: Statistical analyses revealed specific distribution patterns of tracts with increased connectivity that were located in multiple subcortical structures across all patients including the arcuate fasciculus, inferior fronto‐occipital fasciculus, inferior longitudinal fasciculus, uncinate fasciculus, fornix, and short U fibers. Conversely, pathways with a significant decrease in connectivity (p < .05) exhibited a more central distribution near mesial structures across all patients (corpus callosum, cingulum, corticospinal tract, and sensory fibers).Significance: Our findings add to the growing evidence that focal epilepsy is not solely anatomically confined, but is rather a network disorder that extends beyond the EZ, and differential tractography shows strong potential as a clinical biomarker for assessing structural connectivity alterations in patients with epilepsy.