Deep learning-based pupil model predicts time and spectral dependent light responses

Abstract Although research has made significant findings in the neurophysiological process behind the pupillary light reflex, the temporal prediction of the pupil diameter triggered by polychromatic or chromatic stimulus spectra is still not possible. State of the art pupil models rested in estimati...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Babak Zandi, Tran Quoc Khanh
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/603c5261898e4052ae61d50517c37d87
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:603c5261898e4052ae61d50517c37d87
record_format	dspace
spelling	oai:doaj.org-article:603c5261898e4052ae61d50517c37d872021-12-02T14:12:42ZDeep learning-based pupil model predicts time and spectral dependent light responses10.1038/s41598-020-79908-52045-2322https://doaj.org/article/603c5261898e4052ae61d50517c37d872021-01-01T00:00:00Zhttps://doi.org/10.1038/s41598-020-79908-5https://doaj.org/toc/2045-2322Abstract Although research has made significant findings in the neurophysiological process behind the pupillary light reflex, the temporal prediction of the pupil diameter triggered by polychromatic or chromatic stimulus spectra is still not possible. State of the art pupil models rested in estimating a static diameter at the equilibrium-state for spectra along the Planckian locus. Neither the temporal receptor-weighting nor the spectral-dependent adaptation behaviour of the afferent pupil control path is mapped in such functions. Here we propose a deep learning-driven concept of a pupil model, which reconstructs the pupil’s time course either from photometric and colourimetric or receptor-based stimulus quantities. By merging feed-forward neural networks with a biomechanical differential equation, we predict the temporal pupil light response with a mean absolute error below 0.1 mm from polychromatic (2007 $$\pm$$ ± 1 K, 4983 $$\pm$$ ± 3 K, 10,138 $$\pm$$ ± 22 K) and chromatic spectra (450 nm, 530 nm, 610 nm, 660 nm) at 100.01 ± 0.25 cd/m2. This non-parametric and self-learning concept could open the door to a generalized description of the pupil behaviour.Babak ZandiTran Quoc KhanhNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-16 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Babak Zandi Tran Quoc Khanh Deep learning-based pupil model predicts time and spectral dependent light responses
description	Abstract Although research has made significant findings in the neurophysiological process behind the pupillary light reflex, the temporal prediction of the pupil diameter triggered by polychromatic or chromatic stimulus spectra is still not possible. State of the art pupil models rested in estimating a static diameter at the equilibrium-state for spectra along the Planckian locus. Neither the temporal receptor-weighting nor the spectral-dependent adaptation behaviour of the afferent pupil control path is mapped in such functions. Here we propose a deep learning-driven concept of a pupil model, which reconstructs the pupil’s time course either from photometric and colourimetric or receptor-based stimulus quantities. By merging feed-forward neural networks with a biomechanical differential equation, we predict the temporal pupil light response with a mean absolute error below 0.1 mm from polychromatic (2007 $$\pm$$ ± 1 K, 4983 $$\pm$$ ± 3 K, 10,138 $$\pm$$ ± 22 K) and chromatic spectra (450 nm, 530 nm, 610 nm, 660 nm) at 100.01 ± 0.25 cd/m2. This non-parametric and self-learning concept could open the door to a generalized description of the pupil behaviour.
format	article
author	Babak Zandi Tran Quoc Khanh
author_facet	Babak Zandi Tran Quoc Khanh
author_sort	Babak Zandi
title	Deep learning-based pupil model predicts time and spectral dependent light responses
title_short	Deep learning-based pupil model predicts time and spectral dependent light responses
title_full	Deep learning-based pupil model predicts time and spectral dependent light responses
title_fullStr	Deep learning-based pupil model predicts time and spectral dependent light responses
title_full_unstemmed	Deep learning-based pupil model predicts time and spectral dependent light responses
title_sort	deep learning-based pupil model predicts time and spectral dependent light responses
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/603c5261898e4052ae61d50517c37d87
work_keys_str_mv	AT babakzandi deeplearningbasedpupilmodelpredictstimeandspectraldependentlightresponses AT tranquockhanh deeplearningbasedpupilmodelpredictstimeandspectraldependentlightresponses
_version_	1718391785467674624

Deep learning-based pupil model predicts time and spectral dependent light responses

Ejemplares similares