Daehan Won1, Wonsuk Kim2, W Art Chaovalitwongse3, Jeffrey J Tsai4. 1. Department of Industrial and Systems Engineering, University of Washington, Seattle, WA, USA. 2. Department of Radiology, University of California-Davis, Sacramento, CA, USA. 3. Department of Industrial and Systems Engineering, University of Washington, Seattle, WA, USA; Department of Radiology, University of Washington, Seattle, WA, USA. 4. Department of Neurology, University of Washington, Seattle, WA, USA. Electronic address: jjtsai@uw.edu.
Abstract
OBJECTIVE: Visual hyperexcitability in the form of abnormal contrast gain control has been shown in photosensitive epilepsy and idiopathic generalized epilepsies. We assessed the accuracy and reliability of measures of visual contrast gain control in discerning individuals with idiopathic generalized epilepsies from healthy controls. METHODS: Twenty-four adult patients with idiopathic generalized epilepsy and 32 neurotypical control subjects from two study sites participated in a prospective, cross-sectional study. We recorded steady-state visual evoked potentials to a wide range of contrasts of a flickering grating stimulus. The resultant response magnitude vs. contrast curves were fitted to a standard model of contrast response function, and the model parameters were used as input features to a linear classifier to separate patients from controls. Additionally we compared the relative contribution of model parameters towards the classification using a sparse feature-selection approach. RESULTS: Classification accuracy was 80% or better. Sensitivity and specificity both were 80-85%. Cross validation confirmed robust classifier performance generalizable across the data from the two samples. Patients' relative lack of gain control at high contrasts was the most important information distinguishing patients from controls. CONCLUSIONS: Individuals with idiopathic generalized epilepsy were distinguishable from the neurotypical with a high degree of accuracy and reliability by a reduction in gain control at high contrasts. SIGNIFICANCE: Gain control is an essential neural operation that regulates neuronal sensitivity to stimuli and may represent a novel biomarker of hyperexcitability. Published by Elsevier B.V.
OBJECTIVE:Visual hyperexcitability in the form of abnormal contrast gain control has been shown in photosensitive epilepsy and idiopathic generalized epilepsies. We assessed the accuracy and reliability of measures of visual contrast gain control in discerning individuals with idiopathic generalized epilepsies from healthy controls. METHODS: Twenty-four adult patients with idiopathic generalized epilepsy and 32 neurotypical control subjects from two study sites participated in a prospective, cross-sectional study. We recorded steady-state visual evoked potentials to a wide range of contrasts of a flickering grating stimulus. The resultant response magnitude vs. contrast curves were fitted to a standard model of contrast response function, and the model parameters were used as input features to a linear classifier to separate patients from controls. Additionally we compared the relative contribution of model parameters towards the classification using a sparse feature-selection approach. RESULTS: Classification accuracy was 80% or better. Sensitivity and specificity both were 80-85%. Cross validation confirmed robust classifier performance generalizable across the data from the two samples. Patients' relative lack of gain control at high contrasts was the most important information distinguishing patients from controls. CONCLUSIONS: Individuals with idiopathic generalized epilepsy were distinguishable from the neurotypical with a high degree of accuracy and reliability by a reduction in gain control at high contrasts. SIGNIFICANCE: Gain control is an essential neural operation that regulates neuronal sensitivity to stimuli and may represent a novel biomarker of hyperexcitability. Published by Elsevier B.V.
Authors: David Silver; Aja Huang; Chris J Maddison; Arthur Guez; Laurent Sifre; George van den Driessche; Julian Schrittwieser; Ioannis Antonoglou; Veda Panneershelvam; Marc Lanctot; Sander Dieleman; Dominik Grewe; John Nham; Nal Kalchbrenner; Ilya Sutskever; Timothy Lillicrap; Madeleine Leach; Koray Kavukcuoglu; Thore Graepel; Demis Hassabis Journal: Nature Date: 2016-01-28 Impact factor: 49.962
Authors: Viktoriya O Manyukhina; Ekaterina N Rostovtseva; Andrey O Prokofyev; Tatiana S Obukhova; Justin F Schneiderman; Tatiana A Stroganova; Elena V Orekhova Journal: Sci Rep Date: 2021-06-08 Impact factor: 4.379