Mazziotti R, Carrara F, Viglione A, Lupori L, Lo Verde L, Benedetto A, Ricci G, Sagona G, Amato G, Pizzorusso T
Arousal Neural network Oddball Pupillometry Virtual reality Web app
Pupil dynamics alterations have been found in patients affected by a variety of neuropsychiatric conditions, including autism. Studies in mouse models have used pupillometry for phenotypic assessment and as a proxy for arousal. Both in mice and humans, pupillometry is non-invasive and allows for longitudinal experiments supporting temporal specificity, however, its measure requires dedicated setups. Here, we introduce a Convolutional Neural Network that performs online pupillometry in both mice and humans in a web app format. This solution dramatically simplifies the usage of the tool for the non-specialist and non-technical operators. Because a modern web browser is the only software requirement, this choice is of great interest given its easy deployment and set-up time reduction. The tested model performances indicate that the tool is sensitive enough to detect both locomotor-induced and stimulus-evoked pupillary changes, and its output is comparable with state-of-the-art commercial devices.
Source: ENEURO, vol. 8 (issue 5)
@article{oai:it.cnr:prodotti:457160, title = {MEYE: Web-app for translational and real-time pupillometry}, author = {Mazziotti R and Carrara F and Viglione A and Lupori L and Lo Verde L and Benedetto A and Ricci G and Sagona G and Amato G and Pizzorusso T}, doi = {10.1523/eneuro.0122-21.2021}, year = {2021} }