Publications by authors named "A McGonigal"

Surgical resection for epilepsy often fails due to incomplete Epileptogenic Zone Network (EZN) localization from scalp electroencephalography (EEG), stereo-EEG (SEEG), and Magnetic Resonance Imaging (MRI). Subjective interpretation based on interictal, or ictal recordings limits conventional EZN localization. This study employs multimodal analysis using high-density-EEG (HDEEG), Magnetoencephalography (MEG), functional-MRI (fMRI), and SEEG to overcome these limitations in a patient with drug-resistant MRI-negative focal epilepsy.

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Article Synopsis
  • The study tested various AI face-swapping models on videos of epileptic seizures to maintain patient privacy while preserving important clinical details.
  • Three open-source models were used to replace original faces in seizure videos, with evaluations conducted by both AI metrics and expert clinicians.
  • Results showed that all models were effective at concealing original identities, but the GHOST model was slightly better at preserving clinically relevant details, suggesting potential for enhancing educational resources while protecting patients' identities.
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The concept of multimorbidity in psychiatry refers to the coexistence of multiple health conditions without conceptualizing a central disorder referring to a patient-centered approach that views every diagnosis equally. It emphasizes a shift from focusing on an index disorder to considering interrelated symptoms crucial in psychiatry due to frequent multimorbidity patterns. In clinical practice, multimorbidity guides patient-centered care helping to address the holistic needs of patients and challenging the organization of mental health care.

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Introduction: Epilepsy surgery is the only curative treatment for patients with drug-resistant focal epilepsy. Stereoelectroencephalography (SEEG) is the gold standard to delineate the seizure-onset zone (SOZ). However, up to 40% of patients are subsequently not operated as no focal non-eloquent SOZ can be identified.

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