5575513
doi
10.1523/ENEURO.0122-21.2021
oai:zenodo.org:5575513
user-ai4eu
user-ai4media
Carrara Fabio
CNR-ISTI
Viglione Aurelia
CNR-IN
Lupori Leonardo
CNR-IN
Lo Verde Luca
CNR-IN
Benedetto Alessandro
UNIPI
Ricci Giulia
UNIFI
Sagona Giulia
CNR-IN
Amato Giuseppe
CNR-ISTI
Pizzorusso Tommaso
SNS
MEYE: Web-app for translational and real-time pupillometry
Mazziotti Raffaele
CNR-IN
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
Artificial Itelligence
Deep Learning
Pupillometry
<p>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.</p>
Zenodo
2021-09-13
info:eu-repo/semantics/article
5575512
user-ai4eu
user-ai4media
award_title=A European Excellence Centre for Media, Society and Democracy; award_number=951911; award_identifiers_scheme=url; award_identifiers_identifier=https://cordis.europa.eu/projects/951911; funder_id=00k4n6c32; funder_name=European Commission;
award_title=A European AI On Demand Platform and Ecosystem; award_number=825619; award_identifiers_scheme=url; award_identifiers_identifier=https://cordis.europa.eu/projects/825619; funder_id=00k4n6c32; funder_name=European Commission;
1634737063.453839
2211110
md5:5a458aca03711c36330df224215c52c5
https://zenodo.org/records/5575513/files/eneuro_0122_21_2021_full.pdf
public
eNeuro
8
5
2021-09-13