Evidence map›Paper›PMID 40265357›Full record

ReviewNeuroSci2025

Methods for Assessing Neurodevelopmental Disorders in Mice: A Critical Review of Behavioral Tests and Methodological Considerations Searching to Improve Reliability.

Boniface Echefu, Maria Becker, Dan Stein, Asher Ornoy

Abstract readReview
In one paragraph

Review in NeuroSci, 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

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

4 authors.

Boniface EchefuDepartment of Morphological Sciences and Teratology, Adelson School of Medicine, Ariel University, Ariel 40700, Israel.ORCID 0000-0002-2212-726X
Maria BeckerDepartment of Morphological Sciences and Teratology, Adelson School of Medicine, Ariel University, Ariel 40700, Israel.ORCID 0000-0002-6720-6738
Dan SteinDepartment of Morphological Sciences and Teratology, Adelson School of Medicine, Ariel University, Ariel 40700, Israel.
Asher OrnoyDepartment of Morphological Sciences and Teratology, Adelson School of Medicine, Ariel University, Ariel 40700, Israel.ORCID 0000-0002-7268-3512

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Many neurobehavioral tests are used for the assessment of human-like behaviors in animals. Most of them were developed in rodents and are used for the assessment of animal models that mimic human neurodevelopmental and neuropsychiatric disorders (NDDs). We have described tests for assessing social behavior, social interaction, and social communication; tests for restricted and repetitive behaviors; tests for cognitive impairment, for sensory stimuli, for anxiety like behavior, and for motor coordination deviations. These tests are used to demonstrate autistic-like behavior as well as other NDDs. We described possible general pitfalls in the performance of such studies, as well as probable individual errors for each group of tests assessing specific behavior. The mentioned pitfalls may induce crucial errors in the interpretation of the results, minimizing the reliability of specific models of defined human NDD. It is imperative to minimize these pitfalls and use sufficient and reliable tests that can demonstrate as many of the traits of the human disorder, grade the severity of the specific deviations and the severity of the tested NDD by using a scoring system. Due to possible gender differences in the clinical presentations of NDD, it is important to carry out studies on males and females.

Indexed as

behavioral testsmiceneurobehavioral disorderspitfallsscoring system

Identifiers

PMID40265357
PMCPMC12015833

What OpenQuestion holds

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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.