Evidence map›Paper›PMID 42298134›Full record

ArticleCommunications psychology2026

Early detection of distinct language development in infants of mothers with severe mental illness using fNIRS.

Alessandra Piatti, Holly Hope, Matthias Pierce, Kathryn Abel

Abstract read
In one paragraph

Article in Communications psychology, 2026. 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.

Alessandra PiattiCentre for Women's Mental Health, Division of Psychology and Mental Health, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK. Alessandra.piatti@gmail.com.ORCID http://orcid.org/0000-0003-0788-2600
Holly HopeCentre for Women's Mental Health, Division of Psychology and Mental Health, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK.
Matthias PierceCentre for Women's Mental Health, Division of Psychology and Mental Health, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK.
Kathryn AbelCentre for Women's Mental Health, Division of Psychology and Mental Health, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK.

Funding

EC | EU Framework Programme for Research and Innovation H2020 | H2020 Priority Excellent Science | H2020 European Research Council (H2020 Excellent Science - European Research Council) 682741 (CAPRI)
6 · The paper itself

Abstract

Infants of mothers with severe mental illness are at elevated risk of neurodevelopmental difficulties. This study used functional near-infrared spectroscopy (fNIRS) to compare 8-10-month-old infants exposed to severe maternal mental illness (n = 30) and unexposed controls (n = 30) during two experiments assessing brain activation to voice versus non-voice sounds and to sentences with angry, happy, or neutral prosody. Exposed infants showed atypical right-temporal activation, with stronger activation to non-voice than voice stimuli, unlike controls. Socioeconomic status was positively correlated with activation to non-voice and to sentences, independently of emotional prosody. Further analysis indicated that brain response to non-voice stimuli mediated the relation between socioeconomic status and activation to sentences. These findings reveal distinct neural trajectories in infants exposed to severe maternal mental illness, detectable within the first year of life, and highlight socioeconomic background as a key factor in early brain development.

Identifiers

PMID42298134
PMCPMC13630572

What OpenQuestion holds

Textmetadata
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.