The application of artificial intelligence to understand the pathophysiological basis of psychogenic nonepileptic seizures

Abstract Psychogenic nonepileptic seizures (PNES) are episodes of paroxysmal impairment associated with a range of motor, sensory, and mental manifestations, which perfectly mimic epileptic seizures. Several patterns of neural abnormalities have been described without identifying a definite neurobiological substrate. In this multicenter cross-sectional study, we applied a multivariate classification algorithm on morphological brain imaging metrics to extract reliable biomarkers useful to distinguish patients from controls at an individual level. Twenty-three patients with PNES and 21 demographically matched healthy controls (HC) underwent an extensive neuropsychiatric/neuropsychological and neuroimaging assessment. One hundred and fifty morphological brain metrics were used for training a random forest (RF) machine-learning (ML) algorithm. A typical complex psychopathological construct was observed in PNES. Similarly, univariate neuroimaging analysis revealed widespread neuroanatomical changes affecting patients with PNES. Machine-learning approach, after feature selection, was able to perform an individual classification of PNES from controls with a mean accuracy of 74.5%, revealing that brain regions influencing classification accuracy were mainly localized within the limbic (posterior cingulate and insula) and motor inhibition systems (the right inferior frontal cortex (IFC)). This study provides Class II evidence that the considerable clinical and neurobiological heterogeneity observed in individuals with PNES might be overcome by ML algorithms trained on surface-based magnetic resonance imaging (MRI) data

THE LESSON WE CAN LEARN FROM THE CANADIAN DOCUMENTARY “MS. SCIENTIST” TO HAVE MORE WOMEN IN SCIENCE

Around the world the fields of scientific research and development remain a maledominated environment. Workplace with worse gender ratio has proven as the greatest predictor of the occurrence of sexual harassment. A system-wide change to the culture and organizational climate in science is required. The Canadian documentary “Ms. Scientist” by Brandy Yanchyk explores how Canada is trying to get female scientists to stay in the fields of science and progress to the top. Ms Scientist looks at the successes and challenges that ten Canada’s women in science face, and provides guidance and inspiration for young women and minorities who embark on a career in science all over the world.Questo volume presenta una serie di analisi che vanno dalla presentazione del quadro cognitivo dal punto di vista teorico, a quello dei (pochi) dati disponibili. Abbiamo raggruppato i temi in quattro parti: 1. Che cosa sappiamo?; 2. Come affrontare il problema: soluzioni; 3. Come affrontare il problema: prevenzione e 4. Prospettive più ampie. La prima parte, con i contributi di Claudine Hermann, Colette Guillopé, Sylvie Cromer, Ilaria Di Tullio, Francesca Torelli, fornisce una vista trasversale dello stato delle analisi condotte in Italia e all'estero. Conoscere i termini della domanda e i confini del problema è il passaggio preliminare per trovare gli strumenti per affrontarlo e, si spera, risolverlo. Quali soluzioni possono essere previste? Cosa si può fare? Nella seconda parte Ann Olivarius, Chiara de Fabritiis e Fernie Maas discutono le questioni relative ai diversi contesti. La terza parte affronta la questione delle possibili soluzioni al problema dal lato della prevenzione, come lo sviluppo di linee guida e regolamenti che prevengono l'insorgere di problemi, piuttosto che punirli in seguito. Lorenza Perini, Laura Chlebos, Agata Sangianantoni, Valeria De Paola, Ingrid Hunstad, Maria Luisa Chiofalo e Tiziana Metitieri presentano alcune delle possibili aree di intervento per evitare di ripetere episodi non più tollerabili. La quarta parte raccoglie alcuni contributi di autori selezionati che allargano la prospettiva tra storia e discriminazione. Mirella Orsi, Anna Lisa Somma, Sona Grigoryan, Antonella Nappi, Federica De Luca, Mariella Paciello, Pietro Greco e Monica Zoppè hanno contribuito a questa parte finale.Ogni sezione è preceduta da un'introduzione scritta da una delle curatrici, Lucia Martinelli, Giuliana Rubbia, Silvana Badaloni e Monica Zoppè, che descrive in dettaglio il contenuto dei vari contributi

Clinical features and outcome of 6 new patients carrying de novoKCNB1gene mutations

Objective: To describe electroclinical features and outcome of 6 patients harboring KCNB1 mutations.& para;& para;Methods: Clinical, EEG, neuropsychological, and brain MRI data analysis. Targeted next-generation sequencing of a 95 epilepsy gene panel.& para;& para;Results: The mean age at seizure onset was 11 months. The mean follow-up of 11.3 years documented that 4 patients following an infantile phase of frequent seizures became seizure free; the mean age at seizure offset was 4.25 years. Epilepsy phenotypes comprised West syndrome in 2 patients, infantile-onset unspecified generalized epilepsy, myoclonic and photosensitive eyelid myoclonia epilepsy resembling Jeavons syndrome, Lennox-Gastaut syndrome, and focal epilepsy with prolonged occipital or clonic seizures in each and every one. Five patients had developmental delay prior to seizure onset evolving into severe intellectual disability with absent speech and autistic traits in one and stereotypic hand movements with impulse control disorder in another. The patient with Jeavons syndrome evolved into moderate intellectual disability. Mutations were de novo, 4 missense and 2 nonsense, 5 were novel, and 1 resulted from somatic mosaicism.& para;& para;Conclusions: KCNB1-related manifestations include a spectrum of infantile-onset generalized or focal seizures whose combination leads to early infantile epileptic encephalopathy including West, Lennox-Gastaut, and Jeavons syndromes. Long-term follow-up highlights that following a stormy phase, seizures subside or cease and treatment may be eased or withdrawn. Cognitive and motor functions are almost always delayed prior to seizure onset and evolve into severe, persistent impairment. Thus, KCNB1 mutations are associated with diffuse brain dysfunction combining seizures, motor, and cognitive impairment