Evidence map›Paper›PMID 42523531›Full record

ArticleArXiv2026

STSBench: A Large-Scale Dataset for Modeling Neuronal Activity in the Dorsal Stream of Primate Visual Cortex.

Ethan B Trepka, Ruobing Xia, Shude Zhu, Sharif Saleki, Danielle Abreu Lopes, Stephen J Niño Cital, Konstantin F Willeke, Mindy Kim, Tirin Moore

Abstract readPreprint
PubMed Full text at PMC
In one paragraph

Article in ArXiv, 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

9 authors.

Ethan B TrepkaNeuroscience Interdepartmental Program, Stanford University, Stanford, CA.
Ruobing XiaDepartment of Neurobiology, Stanford University, Stanford, CA.
Shude ZhuDepartment of Neurobiology, Stanford University, Stanford, CA.
Sharif SalekiDepartment of Neurobiology, Stanford University, Stanford, CA.
Danielle Abreu LopesDepartment of Neurobiology, Stanford University, Stanford, CA.
Stephen J Niño CitalDepartment of Neurobiology, Stanford University, Stanford, CA.
Konstantin F WillekeDepartment of Opthalmology, Stanford University, Stanford, CA.
Mindy KimDepartment of Neurobiology, Stanford University, Stanford, CA.
Tirin MooreDepartment of Neurobiology, Stanford University, Stanford, CA.

Funding

Interaction of Visual and Oculomotor Signals in CortexR01EY014924 · NEI · STANFORD UNIVERSITY · PI MOORE, TIRIN · 2004 to 2024
$7.3M
Large-scale recordings in Primate Prefrontal Cortex: Mechanisms of Value and AttentionRF1NS116623 · NINDS · STANFORD UNIVERSITY · PI MOORE, TIRIN, SHENOY, KRISHNA V · 2020 to 2022
$1.8M
Large-scale recordings in Primate Prefrontal Cortex: Mechanisms of Value and AttentionR01NS116623 · NINDS · STANFORD UNIVERSITY · PI MOORE, TIRIN, WALLIS, JONI D · 2023 to 2024
$1.0M
Interaction of Visual and Oculomotor Signals in CortexR56EY014924 · NEI · STANFORD UNIVERSITY · PI MOORE, TIRIN · 2009 to 2009
$398k
NEI NIH HHS R01 EY014924NEI NIH HHS R56 EY014924NINDS NIH HHS R01 NS116623NINDS NIH HHS RF1 NS116623
6 · The paper itself

Abstract

The primate visual system is typically divided into two streams - the ventral stream, responsible for object recognition, and the dorsal stream, responsible for encoding spatial relations and motion. Recent studies have shown that convolutional neural networks (CNNs) pretrained on object recognition tasks are remarkably effective at predicting neuronal responses in the ventral stream, shedding light on the neural mechanisms underlying object recognition. However, similar models of the dorsal stream remain underdeveloped due to the lack of large scale datasets encompassing dorsal stream areas. To address this gap, we present STSBench, a dataset of large-scale, single neuron recordings from over 2,000 neurons in the superior temporal sulcus (STS), a nearly 50-fold increase over existing dorsal stream datasets, collected while Rhesus macaques viewed thousands of unique, natural videos. We show that our dataset can be used for benchmarking encoding models of dorsal stream neuronal responses and reconstructing visual input from neural activity.

Identifiers

PMID42523531
PMCPMC13405418

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Registered trials

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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 OpenQuestion graph.