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 8 (2021). doi:10.1523/ENEURO.0122-21.2021
Publisher: Society for Neuroscience, [Washington DC], Stati Uniti d'America
@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.}, publisher = {Society for Neuroscience, [Washington DC], Stati Uniti d'America}, doi = {10.1523/eneuro.0122-21.2021}, journal = {ENeuro}, volume = {8}, year = {2021} }