Identifying sources of human interictal discharges with travelling wave and white matter propagation.

Interictal epileptiform discharges have been shown to propagate from focal epileptogenic sources as travelling waves or through more rapid white matter conduction. We hypothesize that both modes of propagation are necessary to explain interictal discharge timing delays. We propose a method that, for the first time, incorporates both propagation modes to identify unique potential sources of interictal activity. We retrospectively analysed 38 focal epilepsy patients who underwent intracranial EEG recordings and diffusion-weighted imaging for epilepsy surgery evaluation. Interictal discharges were detected and localized to the most likely source based on relative delays in time of arrival across electrodes, incorporating travelling waves and white matter propagation. We assessed the influence of white matter propagation on distance of spread, timing and clinical interpretation of interictal activity. To evaluate accuracy, we compared our source localization results to earliest spiking regions to predict seizure outcomes. White matter propagation helps to explain the timing delays observed in interictal discharge sequences, underlying rapid and distant propagation. Sources identified based on differences in time of receipt of interictal discharges are often distinct from the leading electrode location. Receipt of activity propagating rapidly via white matter can occur earlier than more local activity propagating via slower cortical travelling waves. In our cohort, our source localization approach was more accurate in predicting seizure outcomes than the leading electrode location. Inclusion of white matter in addition to travelling wave propagation in our model of discharge spread did not improve overall accuracy but allowed for identification of unique and at times distant potential sources of activity, particularly in patients with persistent postoperative seizures. Since distant white matter propagation can occur more rapidly than local travelling wave propagation, combined modes of propagation within an interictal discharge sequence can decouple the commonly assumed relationship between spike timing and distance from the source. Our findings thus highlight the clinical importance of recognizing the presence of dual modes of propagation during interictal discharges, as this may be a cause of clinical mislocalization.

Lateralization of interictal temporal lobe hypoperfusion in lesional and non-lesional temporal lobe epilepsy using arterial spin labeling MRI.

PURPOSE: Non-invasive imaging studies play a critical role in the presurgical evaluation of patients with drug-resistant temporal lobe epilepsy (TLE), particularly in helping to lateralize the seizure focus. Arterial Spin Labeling (ASL) MRI has been widely used to non-invasively study cerebral blood flow (CBF), with somewhat variable interictal alterations reported in TLE. Here, we compare temporal lobe subregional interictal perfusion and symmetry in lesional (MRI+) and non-lesional (MRI-) TLE compared to healthy volunteers (HVs). METHODS: Twenty TLE patients (9 MRI+, 11 MRI-) and 14 HVs under went 3 T Pseudo-Continuous ASL MRI through an epilepsy imaging research protocol at the NIH Clinical Center. We compared normalized CBF and absolute asymmetry indices in multiple temporal lobe subregions. RESULTS: Compared to HVs, both MRI+ and MRI- TLE groups demonstrated significant ipsilateral mesial and lateral temporal hypoperfusion, specifically in the hippocampal and anterior temporal neocortical subregions, with additional hypoperfusion in the ipsilateral parahippocampal gyrus in the MRI+ and contralateral hippocampus in the MRI- TLE groups. Contralateral to the seizure focus, there was significant relative hypoperfusion in multiple subregions in the MRI- compared to the MRI+ TLE groups. The MRI+ group therefore had significantly greater asymmetry across multiple temporal subregions compared to the MRI- TLE and HV groups. No significant differences in asymmetry were found between the MRI- TLE and HV groups. CONCLUSION: We found a similar extent of interictal ipsilateral temporal hypoperfusion in MRI+ and MRI- TLE. However, significantly increased asymmetries were found only in the MRI+ group due to differences in perfusion contralateral to the seizure focus between the patient groups. The lack of asymmetry in the MRI- group may negatively impact the utility of interictal ASL for seizure focus lateralization in this patient population.

An approach for collaborative development of a federated biomedical knowledge graph-based question-answering system: Question-of-the-Month challenges.

Knowledge graphs have become a common approach for knowledge representation. Yet, the application of graph methodology is elusive due to the sheer number and complexity of knowledge sources. In addition, semantic incompatibilities hinder efforts to harmonize and integrate across these diverse sources. As part of The Biomedical Translator Consortium, we have developed a knowledge graph-based question-answering system designed to augment human reasoning and accelerate translational scientific discovery: the Translator system. We have applied the Translator system to answer biomedical questions in the context of a broad array of diseases and syndromes, including Fanconi anemia, primary ciliary dyskinesia, multiple sclerosis, and others. A variety of collaborative approaches have been used to research and develop the Translator system. One recent approach involved the establishment of a monthly "Question-of-the-Month (QotM) Challenge" series. Herein, we describe the structure of the QotM Challenge; the six challenges that have been conducted to date on drug-induced liver injury, cannabidiol toxicity, coronavirus infection, diabetes, psoriatic arthritis, and ATP1A3-related phenotypes; the scientific insights that have been gleaned during the challenges; and the technical issues that were identified over the course of the challenges and that can now be addressed to foster further development of the prototype Translator system. We close with a discussion on Large Language Models such as ChatGPT and highlight differences between those models and the Translator system.