Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Nonvolatile phase-programmable spintronic terahertz emitter via laser-induced spin polarization switching.

National science review·2026
Same author

Protective effects of resveratrol against perfluorooctane sulfonamide-induced cardiac developmental toxicity in zebrafish larvae.

Food and chemical toxicology : an international journal published for the British Industrial Biological Research Association·2026
Same author

L-DOPA enhances iRPE differentiation via Wnt signaling and improves cytotherapy for retinal degradation.

Stem cell research & therapy·2026
Same author

Epidemiological Investigation and Analysis of <i>Orthohantavirus hantanense</i> and <i>Orthohantavirus seoulense</i> From Wild Rodents in Liaoning Province, China.

Transboundary and emerging diseases·2026
Same author

Transmission Dominance Under Random-Contact Intensification in Epidemic Networks: Multilayer Contact Network Simulation Study.

JMIR formative research·2026
Same author

Detection of Global DNA Methylation in the Hearts of Zebrafish Larvae.

Journal of visualized experiments : JoVE·2026

Related Experiment Video

Updated: Jul 8, 2025

A Simple Stimulatory Device for Evoking Point-like Tactile Stimuli: A Searchlight for LFP to Spike Transitions
07:34

A Simple Stimulatory Device for Evoking Point-like Tactile Stimuli: A Searchlight for LFP to Spike Transitions

Published on: March 25, 2014

9.9K

Transformer-based light-evoked retinal spiking activity prediction.

Mingxuan Zhang, Orsolya Kekesi, Gregg J Suaning

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |December 12, 2023
    PubMed
    Summary

    This study explores using a deep learning transformer model to predict neural activity for retinal prosthetics. Preliminary results show promise for improving visual acuity in artificial vision devices.

    More Related Videos

    Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches
    10:50

    Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches

    Published on: June 21, 2022

    1.8K
    Preparations and Protocols for Whole Cell Patch Clamp Recording of Xenopus laevis Tectal Neurons
    05:25

    Preparations and Protocols for Whole Cell Patch Clamp Recording of Xenopus laevis Tectal Neurons

    Published on: March 15, 2018

    9.5K

    Related Experiment Videos

    Last Updated: Jul 8, 2025

    A Simple Stimulatory Device for Evoking Point-like Tactile Stimuli: A Searchlight for LFP to Spike Transitions
    07:34

    A Simple Stimulatory Device for Evoking Point-like Tactile Stimuli: A Searchlight for LFP to Spike Transitions

    Published on: March 25, 2014

    9.9K
    Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches
    10:50

    Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches

    Published on: June 21, 2022

    1.8K
    Preparations and Protocols for Whole Cell Patch Clamp Recording of Xenopus laevis Tectal Neurons
    05:25

    Preparations and Protocols for Whole Cell Patch Clamp Recording of Xenopus laevis Tectal Neurons

    Published on: March 15, 2018

    9.5K

    Area of Science:

    • Neuroscience
    • Biomedical Engineering
    • Artificial Intelligence

    Background:

    • Retinal prosthetic devices aim to restore vision using electrical stimulation.
    • Current stimulation strategies often fail to meet user expectations due to limitations in predicting neural responses.
    • Improved prediction of light-evoked neural activity is essential for enhancing visual acuity in prosthetic devices.

    Purpose of the Study:

    • To evaluate the predictive capacity of a deep learning transformer model for light-evoked retinal spikes.
    • To explore the potential of advanced AI in overcoming barriers to accurate neural activity prediction.
    • To investigate methods for enhancing the performance of retinal prosthetic devices.

    Main Methods:

    • Development and evaluation of a deep learning model based on the transformer architecture.
    • Utilizing the model to predict neural activities in response to light stimuli.
    • Assessing the model's performance in predicting spatial and temporal aspects of neural responses.

    Main Results:

    • Preliminary findings indicate that the transformer-based deep learning model can achieve good performance in predicting light-evoked retinal spikes.
    • The model demonstrates potential in handling the complex nonlinearities and spatial relationships in neural data.
    • The study validates the feasibility of using deep learning for neural activity prediction in this context.

    Conclusions:

    • Deep learning, particularly transformer models, offers a promising approach for predicting neural activity in the retina.
    • This predictive capability could lead to the development of more effective retinal prosthetic devices with enhanced visual acuity.
    • Future research can leverage these models for more complex physiological scenarios and improved artificial vision.