Quantification of Oculomotor Responses and Accommodation through Instrumentation and Analysis Toolboxes.


Journal

Journal of visualized experiments : JoVE
ISSN: 1940-087X
Titre abrégé: J Vis Exp
Pays: United States
ID NLM: 101313252

Informations de publication

Date de publication:
03 03 2023
Historique:
pmc-release: 03 03 2024
entrez: 20 3 2023
pubmed: 21 3 2023
medline: 23 3 2023
Statut: epublish

Résumé

Through the purposeful stimulation and recording of eye movements, the fundamental characteristics of the underlying neural mechanisms of eye movements can be observed. VisualEyes2020 (VE2020) was developed based on the lack of customizable software-based visual stimulation available for researchers that does not rely on motors or actuators within a traditional haploscope. This new instrument and methodology have been developed for a novel haploscope configuration utilizing both eye tracking and autorefractor systems. Analysis software that enables the synchronized analysis of eye movement and accommodative responses provides vision researchers and clinicians with a reproducible environment and shareable tool. The Vision and Neural Engineering Laboratory's (VNEL) Eye Movement Analysis Program (VEMAP) was established to process recordings produced by VE2020's eye trackers, while the Accommodative Movement Analysis Program (AMAP) was created to process the recording outputs from the corresponding autorefractor system. The VNEL studies three primary stimuli: accommodation (blur-driven changes in the convexity of the intraocular lens), vergence (inward, convergent rotation and outward, divergent rotation of the eyes), and saccades (conjugate eye movements). The VEMAP and AMAP utilize similar data flow processes, manual operator interactions, and interventions where necessary; however, these analysis platforms advance the establishment of an objective software suite that minimizes operator reliance. The utility of a graphical interface and its corresponding algorithms allow for a broad range of visual experiments to be conducted with minimal required prior coding experience from its operator(s).

Identifiants

pubmed: 36939267
doi: 10.3791/64808
pmc: PMC10375222
mid: NIHMS1916539
doi:

Types de publication

Journal Article Video-Audio Media Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : NEI NIH HHS
ID : R01 EY023261
Pays : United States

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Auteurs

Sebastian N Fine (SN)

Department of Biomedical Engineering, New Jersey Institute of Technology.

Yi Guo (Y)

Department of Biomedical Engineering, New Jersey Institute of Technology; Neural Automations Ltd.

Henry Talasan (H)

Department of Biomedical Engineering, New Jersey Institute of Technology.

Stephen LeStrange (S)

Department of Biomedical Engineering, New Jersey Institute of Technology.

Chang Yaramothu (C)

Department of Biomedical Engineering, New Jersey Institute of Technology; School of Applied Engineering and Technology, New Jersey Institute of Technology.

Tara L Alvarez (TL)

Department of Biomedical Engineering, New Jersey Institute of Technology; tara.l.alvarez@njit.edu.

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