PT  - JOURNAL ARTICLE
AU  - Raffaele Mazziotti
AU  - Fabio Carrara
AU  - Aurelia Viglione
AU  - Leonardo Lupori
AU  - Luca Lo Verde
AU  - Alessandro Benedetto
AU  - Giulia Ricci
AU  - Giulia Sagona
AU  - Giuseppe Amato
AU  - Tommaso Pizzorusso
TI  - MEYE: Web App for Translational and Real-Time Pupillometry
AID  - 10.1523/ENEURO.0122-21.2021
DP  - 2021 Sep 01
TA  - eneuro
PG  - ENEURO.0122-21.2021
VI  - 8
IP  - 5
4099  - http://www.eneuro.org/content/8/5/ENEURO.0122-21.2021.short
4100  - http://www.eneuro.org/content/8/5/ENEURO.0122-21.2021.full
SO  - eNeuro2021 Sep 01; 8
AB  - 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 noninvasive 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 nonspecialist and nontechnical operators. Because a modern web browser is the only software requirement, this choice is of great interest given its easy deployment and setup 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 to state-of-the-art commercial devices.