Objective: Nodular heterotopias (NHs) are malformations of cortical development associated with drug‐resistant focal epilepsy with frequent poor surgical outcome. The epileptogenic network is complex and can involve the nodule, the overlying cortex, or both. Single‐pulse electrical stimulation (SPES) during stereo‐electroencephalography (SEEG) allows the investigation of functional connectivity between the stimulated and responsive cortices by eliciting cortico‐cortical evoked potentials (CCEPs). We used SPES to analyze the NH connectome and its relation to the epileptogenic network organization.Methods: We retrospectively studied 12 patients with NH who underwent 1 Hz or 0.2 Hz SPES of NH during SEEG. Outbound connectivity (regions where CCEPs were elicited by NH stimulation) and inbound connectivity (regions where stimulation elicited CCEPs in the NH) were searched. SEEG channels were then classified as “heterotopic” (located within the NH), “connected” (located in normotopic cortex and showing connectivity with the NH), and “unconnected.” We used the epileptogenicity index (EI) to quantify implication of channels in the seizure‐onset zone and to classify seizures as heterotopic, normotopic, and normo‐heterotopic.Results: One hundred thirty‐five outbound and 72 inbound connections were found. Three patients showed connectivity between hippocampus and NH, and seven patients showed strong internodular connectivity. A total of 39 seizures were analyzed: 23 normo‐heterotopic, 12 normotopic, and 4 heterotopic. Logistic regression found that “connected” channels were significantly (p = 8.4e‐05) more likely to be epileptogenic than “unconnected” channels (odds ratio 4.71, 95% confidence interval (CI) [2.17, 10.21]) and heterotopic channels were also significantly (p = .024) more epileptogenic than “unconnected” channels (odds ratio 3.29, 95% CI [1.17, 9.23]).Significance: SPES reveals widespread connectivity between NH and normotopic regions. Those connected regions show higher epileptogenicity. SPES might be useful to assess NH epileptogenic network.

Background/Objectives: Artificial intelligence (AI), particularly large language models (LLMs), has demonstrated versatility in various applications but faces challenges in specialized domains like neurology. This study evaluates a specialized LLM’s capability and trustworthiness in complex neurological diagnosis, comparing its performance to neurologists in simulated clinical settings. Methods: We deployed GPT-4 Turbo (OpenAI, San Francisco, CA, US) through Neura (Sciense, New York, NY, US), an AI infrastructure with a dual-database architecture integrating “long-term memory” and “short-term memory” components on a curated neurological corpus. Five representative clinical scenarios were presented to 13 neurologists and the AI system. Participants formulated differential diagnoses based on initial presentations, followed by definitive diagnoses after receiving conclusive clinical information. Two senior academic neurologists blindly evaluated all responses, while an independent investigator assessed the verifiability of AI-generated information. Results: AI achieved a significantly higher normalized score (86.17%) compared to neurologists (55.11%, p < 0.001). For differential diagnosis questions, AI scored 85% versus 46.15% for neurologists, and for final diagnosis, 88.24% versus 70.93%. AI obtained 15 maximum scores in its 20 evaluations and responded in under 30 s compared to neurologists’ average of 9 min. All AI-provided references were classified as relevant with no hallucinatory content detected. Conclusions: A specialized LLM demonstrated superior diagnostic performance compared to practicing neurologists across complex clinical challenges. This indicates that appropriately harnessed LLMs with curated knowledge bases can achieve domain-specific relevance in complex clinical disciplines, suggesting potential for AI as a time-efficient asset in clinical practice.

Generalized tonic-clonic seizures (GTCSs) are the main risk factor for sudden unexpected death in epilepsy (SUDEP). Experimental and clinical data strongly suggest that the majority of SUDEP results from a postictal respiratory dysfunction progressing to terminal apnea. Postictal apnea could partly derive from a seizure-induced massive release of endogenous opioids. The main objective of this study is to evaluate the efficacy of an opioid antagonist, naloxone, administered in the immediate aftermath of a GTCS, in reducing the severity of the postictal central respiratory dysfunction. The Efficacy of Naloxone in Reducing Postictal Central Respiratory Dysfunction in Patients with Epilepsy (ENALEPSY) study is a multicenter, double-blind, randomized, placebo-controlled trial conducted in patients with drug-resistant focal epilepsy who are undergoing long-term video-electroencephalogram (EEG) monitoring (LTM) in an epilepsy monitoring unit (EMU). We plan to randomize 166 patients (1:1) to receive intravenous naloxone (0.4 mg) or placebo in the immediate aftermath of a GTCS. Because inclusion in the study needs to take place prior to the occurrence of the GTCS, and because such occurrence is observed in about one-fourth of patients undergoing LTM, we plan to include a maximum of 700 patients upon admission in the EMU. The primary endpoint will be the proportion of patients whose oxygen saturation is <90 % between 1 and 3 min after the end of a GTCS. Secondary outcomes will include the following: the proportion of patients who show postictal apnea, the occurrence and duration of postictal generalized EEG suppression, the total duration of the postictal coma, postictal pain, and the number of patients who have a second GTCS within 120 min after the intravenous injection. The demonstration of naloxone’s efficacy on the severity of postictal hypoxemia will have two primary consequences. First, naloxone would be the first and only therapeutic approach that could be delivered immediately to reverse postictal apnea. Second, demonstration that an opioid antagonist can effectively reduce postictal apnea would pave the way for an assessment of a preventive therapy for SUDEP targeting the same pathophysiological pathway using oral administration of naltrexone. ClinicalTrials.gov identifier: NCT02332447 . Registered on 5 January 2015.

Surgery for spinal cord tumors poses a significant challenge due to the inherent risk of neurological deterioration. Despite being performed at numerous centers, there is an ongoing debate regarding the efficacy of pre- and intraoperative neurophysiological investigations in detecting and preventing neurological lesions. This study begins by providing a comprehensive review of the neurophysiological techniques commonly employed in this context. Subsequently, we present findings from a cohort of 67 patients who underwent surgery for intradural tumors. These patients underwent preoperative and intraoperative multimodal somatosensory evoked potentials (SSEPs) and motor evoked potentials (MEPs), with clinical evaluation conducted three months postoperatively. The study aimed to evaluate the neurophysiological, clinical, and radiological factors associated with neurological outcomes. In univariate analysis, preoperative and intraoperative potential alterations, tumor size, and ependymoma-type histology were linked to the risk of worsening neurological condition. In multivariate analysis, only preoperative and intraoperative neurophysiological abnormalities remained significantly associated with such neurological deterioration. Interestingly, transient alterations in intraoperative MEPs and SSEPs did not pose a risk of neurological deterioration. The machine learning model we utilized demonstrated the possibility of predicting clinical outcome, achieving 84% accuracy.