Evidence map›Paper›PMID 41951676›Full record

ArticleNature communications2026

Retinocortical in-sensor neuromorphic vision platform for NIR-augmented artificial vision.

Jong Bin An, Kyungtae Park, I Sak Lee, Shilin Lu, Hong Gyu Park, Nam Su Heo, Yong Seon Hwang, Kyungmoon Kwak, Kyungho Park, Si Hyun Park and 4 more

Abstract read
In one paragraph

Article in Nature communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Jong Bin An *Electronic Device Laboratory, School of Electrical and Electronic Engineering, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul, Republic of Korea.
Kyungtae Park *Department of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.ORCID http://orcid.org/0000-0003-4785-1921
I Sak LeeElectronic Device Laboratory, School of Electrical and Electronic Engineering, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul, Republic of Korea.
Shilin LuElectronic Device Laboratory, School of Electrical and Electronic Engineering, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul, Republic of Korea.
Hong Gyu ParkDepartment of Intelligent Semiconductor Engineering, Chung-Ang University, 84 Heukseok-ro, Dongjak-Gu, Seoul, Republic of Korea.
Nam Su HeoElectronic Device Laboratory, School of Electrical and Electronic Engineering, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul, Republic of Korea.
Yong Seon HwangElectronic Device Laboratory, School of Electrical and Electronic Engineering, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul, Republic of Korea.ORCID http://orcid.org/0009-0002-3174-9172
Kyungmoon KwakElectronic Device Laboratory, School of Electrical and Electronic Engineering, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul, Republic of Korea.ORCID http://orcid.org/0009-0003-7203-5851
Kyungho ParkElectronic Device Laboratory, School of Electrical and Electronic Engineering, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul, Republic of Korea.
Si Hyun ParkElectronic Device Laboratory, School of Electrical and Electronic Engineering, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul, Republic of Korea.
Jong Min LeeDepartment of Intelligent Semiconductor Engineering, Chung-Ang University, 84 Heukseok-ro, Dongjak-Gu, Seoul, Republic of Korea.ORCID http://orcid.org/0009-0009-7993-6621
Jinkee HongDepartment of Chemical & Biomolecular Engineering, College of Engineering, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul, Republic of Korea.ORCID http://orcid.org/0000-0003-3243-8536
Sung Kyu ParkDepartment of Intelligent Semiconductor Engineering, Chung-Ang University, 84 Heukseok-ro, Dongjak-Gu, Seoul, Republic of Korea.ORCID http://orcid.org/0000-0001-9617-2541
Hyun Jae KimElectronic Device Laboratory, School of Electrical and Electronic Engineering, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul, Republic of Korea. hjk3@yonsei.ac.kr.ORCID http://orcid.org/0000-0002-6879-9256

Funding

National Research Foundation of Korea (NRF) RS-2023-00256917
6 · The paper itself

Abstract

In-sensor neuromorphic vision platforms with near-infrared (NIR) sensitivity are essential for intelligent imaging in low-light and multispectral environments. Here, a retinocortical dual-mode platform based on evolved-synaptic transistor (Evo-SynT) devices using upconversion nanoparticles (UCNP) and their integration into evolved-retina optical synapse (EROS) arrays is introduced. Evo-SynT devices exhibit key synaptic features, including paired-pulse facilitation indices exceeding 183.93% and 136.36% at a 0.5 s interval under 808 nm and 940 nm illumination, respectively, and analog weight modulation across 512 conductance states. A 12×12 EROS array enables dual-mode operation: retinal-like in-sensor preprocessing and cortical-like in-memory classification. The EROS array improves pedestrian detection accuracy under low-light conditions from 0.7806 to 0.8481 (808 nm) and 0.9071 (940 nm), and achieves classification accuracies of 77.19% and 79.40%, respectively. These results highlight the EROS platform as a scalable solution for integrated NIR-sensitive neuromorphic vision systems.

Indexed as

RetinaHumansInfrared RaysIntelligent SystemsNanoparticlesSynapsesTransistors, ElectronicVisual Cortex

Identifiers

PMID41951676
PMCPMC13234114

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.