Evidence map›Paper›PMID 34418444›Full record

ArticleJournal of neuroscience methods2021

Light-Dark Open Field (LDOF): A novel task for sensitive assessment of anxiety.

Khadijah Shanazz, Rachael Dixon-Melvin, Kristopher M Bunting, Rebecca Nalloor, Almira I Vazdarjanova

Open access · greenAbstract read
In one paragraph

Article in Journal of neuroscience methods, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.9field-weighted citation impact, top 24% of its field
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

5 citing papers in PubMed, 6 citations in OpenAlex.

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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

5 authors at 1 institution in 1 country.

Khadijah ShanazzVA Research Service, Charlie Norwood VA Medical Center, Augusta, GA, United States; Department of Pharmacology and Toxicology, Augusta University, Augusta, GA, United States.
Rachael Dixon-MelvinVA Research Service, Charlie Norwood VA Medical Center, Augusta, GA, United States; Department of Pharmacology and Toxicology, Augusta University, Augusta, GA, United States.
Kristopher M BuntingVA Research Service, Charlie Norwood VA Medical Center, Augusta, GA, United States; Department of Pharmacology and Toxicology, Augusta University, Augusta, GA, United States.
Rebecca NalloorVA Research Service, Charlie Norwood VA Medical Center, Augusta, GA, United States; Department of Pharmacology and Toxicology, Augusta University, Augusta, GA, United States.
Almira I VazdarjanovaVA Research Service, Charlie Norwood VA Medical Center, Augusta, GA, United States; Department of Pharmacology and Toxicology, Augusta University, Augusta, GA, United States. Electronic address: avazdarjanova@augusta.edu.
Augusta University · US

Funding

BLRD VA I01 BX001978BLRD VA I01 BX003890
6 · The paper itself

Abstract

backgroundPre-clinical studies of psychiatric disorders often include a measure of anxiety-like behavior. Several tasks exist that serve this purpose, but because anxiety is complex with a myriad of anxiogenic stimuli, researchers are often compelled to use multiple tasks. The Light-Dark Open Field (LDOF) combines concepts from two such tasks, Light-Dark Box and Open Field, into one task with the synergistic effect of enhanced discrimination of anxiety-like behavior. NEW

methodsOur goal was to increase the sensitivity of the Open Field task with the addition of a shadow, conceptually similar to the Light-Dark Box, to detect concealed differences even under bright light, which is highly anxiogenic. The resulting LDOF allows assessment of anxiety due to bright light and open space simultaneously, while retaining the ability to assess the impact of each with custom indices. In addition, it maintains all the advantages and measures of the Open Field.

resultsUsing custom created indices from measures collected in the LDOF one can assess anxiety induced by light, open space, or light and open space combined and thus elucidate anxiety-inducing factors. Using two strains of rats: an outbred strain, Sprague-Dawley (SD), and a strain that exhibits high trait anxiety, Lewis rats, we found that increased discrimination for anxiety-like behavior can be achieved with the Light-Dark Open Field. COMPARISON WITH EXISTING MODELS: The LDOF allows researchers to extract the traditional measures of an Open Field, including valuable information about locomotion and habituation while adding a further layer of discrimination with the light-dark component. Because the LDOF is a combination of two different tests, it saves time compared to running multiple experiments in series that then need to be counterbalanced to reduce artefacts and task order effects. In addition, it detects differences even when traditional tasks of anxiety have reached their ceiling sensitivity (i.e. EPM under bright light conditions).

conclusionWe present the Light-Dark Open Field: a simple modification of an existing Open Field apparatus that incorporates aspects of the Light-Dark Box with the addition of a shadow. The shadow (Dark Perimeter) allows for increased discrimination in detecting anxiety-like behaviors. Comparison of anxiety-like behavior between Lewis and SD rats allowed us to develop the construct and face validity of the LDOF as well as demonstrate its sensitivity even under bright light conditions. In addition, we developed 3 indices that allow one to parse out, from one set of data, the effect of two anxiogenic stimuli- bright light and open space.

Indexed as

Behavior, AnimalMotor ActivityAnimalsAnxietyRatsRats, Inbred LewRats, Sprague-DawleyAnxietyBehaviorElevated Plus MazeLewis ratsLight AnxietyLight-Dark Open FieldOpen FieldOpen Space AnxietyRatsSprague Dawley rats

Identifiers

PMID34418444
PMCPMC8878097
OpenAlexW3194405277

What OpenQuestion holds

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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.