Machine learning classification of functional neurological disorder using structural brain MRI features.

Background: Brain imaging studies investigating grey matter in functional neurological disorder (FND) have used univariate approaches to report group-level differences compared with healthy controls (HCs). However, these findings have limited translatability because they do not differentiate patients from controls at the individual-level.

Methods: 183 participants were prospectively recruited across three groups: 61 patients with mixed FND (FND-mixed), 61 age-matched and sex-matched HCs and 61 age, sex, depression and anxiety-matched psychiatric controls (PCs).

Sonolucent Cranial Implants: A Window into the Future of Management of Neurosurgical Patients? A Systematic Review and Cost Analysis.

Background: Computeed tomography (CT) is a cornerstone of the identification and management of acute changes in neurosurgery patients. In addition to the monetary expense of CT scans, further costs are incurred due to the time of patient transport and radiation exposure. Ultrasounds (USs)offer a safe, inexpensive, and bedside alternative to CT but obstacles remain due to decreased penetrance in the adult skull.

Developing a Curriculum for Functional Neurological Disorder in Neurology Training: Questions and Answers.

Functional neurologic disorder (FND) is a common condition for which neurology residents often receive little to no formal teaching. Using a question-and-answer format, this article puts forward a case for why an FND curriculum is needed and aims to provide guidance on possible curricular content including medical knowledge, clinical skills, communication, and team-based collaboration. The authors also discuss methods for teaching and evaluating this knowledge and associated clinical skills, linking this to current Accreditation Council for Graduate Medical Education neurology milestones.