Evidence map›Paper›PMID 40089531›Full record

ArticleNPJ science of learning2025

Using virtual reality to study spatial mapping and threat learning.

Claire E Marino, Pavel Rjabtsenkov, Caitlin Sharp, Zonia Ali, Evelyn Pineda, Shreya Y Bavdekar, Tanya Garg, Kendal Jordan, Mary Halvorsen, Carlos Aponte and 3 more

Abstract read
In one paragraph

Article in NPJ science of learning, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

13 authors.

Claire E Marino *Department of Neuroscience, University of Rochester School of Medicine and Dentistry, Rochester, NY, USA.
Pavel Rjabtsenkov *Department of Neuroscience, University of Rochester School of Medicine and Dentistry, Rochester, NY, USA.
Caitlin SharpDepartment of Neuroscience, University of Rochester School of Medicine and Dentistry, Rochester, NY, USA.
Zonia AliDepartment of Neuroscience, University of Rochester School of Medicine and Dentistry, Rochester, NY, USA.
Evelyn PinedaDepartment of Neuroscience, University of Rochester School of Medicine and Dentistry, Rochester, NY, USA.
Shreya Y BavdekarDepartment of Neuroscience, University of Rochester School of Medicine and Dentistry, Rochester, NY, USA.
Tanya GargDepartment of Psychology, University of Rochester, Rochester, NY, USA.
Kendal JordanDepartment of Neuroscience, University of Rochester School of Medicine and Dentistry, Rochester, NY, USA.
Mary HalvorsenDepartment of Neuroscience, University of Rochester School of Medicine and Dentistry, Rochester, NY, USA.
Carlos AponteDepartment of Neuroscience, University of Rochester School of Medicine and Dentistry, Rochester, NY, USA.
Julie BlueDepartment of Neuroscience, University of Rochester School of Medicine and Dentistry, Rochester, NY, USA.
Xi ZhuDepartment of Psychiatry, Columbia University Irving Medical Center, New York, NY, USA.
Benjamin Suarez-JimenezDepartment of Neuroscience, University of Rochester School of Medicine and Dentistry, Rochester, NY, USA. benjamin_suarez-jimenez@urmc.rochester.edu.

Funding

Using novel virtual reality tasks to identify neural mechanisms of discrimination learning in PTSDR01MH131532 · NIMH · UNIVERSITY OF ROCHESTER · PI Benjamin Suarez-Jimenez · 2023 to 2026
$2.7M
Neural Correlates of Location-Specific Contextual Threat Discrimination in Post-Traumatic Stress Disorders REV1K01MH118428 · NIMH · UNIVERSITY OF ROCHESTER · PI SUAREZ-JIMENEZ, BENJAMIN · 2018 to 2022
$807k
Identification of Distinct Multimodal Biotypes of PTSD Using Data Driven Approach: A Multisite Big Data StudyK01MH122774 · NIMH · NEW YORK STATE PSYCHIATRIC INSTITUTE DBA RESEARCH FOUNDATION FOR MENTAL HYGIENE, INC · PI ZHU, XI · 2021 to 2024
$705k
NIMH NIH HHS K01 MH122774U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (NIMH) K01MH118428U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (NIMH) R01MH131532Wellcome Trust (Wellcome) 202805/Z/16/
6 · The paper itself

Abstract

Using spatial mapping processes to discriminate between threat and safety is crucial for survival. Little is known why some fail to discriminate during contextual conditioning. We used a virtual reality (VR) contextual conditioning paradigm to elucidate the effects of state and trait anxiety on contextual threat learning. Participants (n = 70) "picked" flowers in a VR environment. Dangerous zone flowers predicted an electric shock, while safe zone flowers did not. Between trials, participants completed a spatial memory task. Galvanic skin response (GSR) and State Trait Anxiety Inventory scores were recorded. Participants were considered learners for correctly identifying both zones. Non-learners, compared to learners, performed worse during the spatial memory task and demonstrated higher state anxiety scores and GSR. Learners showed higher skin conductance response (SCR) in the dangerous compared to the safe zone, while non-learners showed no SCR differences between zones. Results indicate state anxiety may impair spatial mapping, disrupting contextual threat learning.

Identifiers

PMID40089531
PMCPMC11910644

What OpenQuestion 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 OpenQuestion graph.