Evidence map›Paper›PMID 42511787›Full record

ReviewInternational journal of molecular sciences2026

Large-Scale Neural Recording Technologies for Investigating Circuit Dysfunction and Functional Biomarker Discovery in Animal Models of Alzheimer's Disease.

Dechuan Sun, Song Wang, Qi Meng, Xinyi Wang, Mona Amiri, Ranjith R Unnithan, Chris French

Abstract readReview
In one paragraph

Review in International journal of molecular sciences, 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

7 authors.

Dechuan SunNeural Dynamics Laboratory, Department of Medicine, The University of Melbourne, Melbourne, VIC 3010, Australia.
Song WangNeural Dynamics Laboratory, Department of Medicine, The University of Melbourne, Melbourne, VIC 3010, Australia.
Qi MengNeural Dynamics Laboratory, Department of Medicine, The University of Melbourne, Melbourne, VIC 3010, Australia.
Xinyi WangNeural Dynamics Laboratory, Department of Medicine, The University of Melbourne, Melbourne, VIC 3010, Australia.
Mona AmiriNeural Dynamics Laboratory, Department of Medicine, The University of Melbourne, Melbourne, VIC 3010, Australia.
Ranjith R UnnithanDepartment of Electrical and Electronic Engineering, The University of Melbourne, Melbourne, VIC 3010, Australia.
Chris FrenchNeural Dynamics Laboratory, Department of Medicine, The University of Melbourne, Melbourne, VIC 3010, Australia.ORCID 0000-0002-1445-8704

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Alzheimer's disease (AD) is a progressive neurodegenerative disorder associated with amyloid beta accumulation, tau pathology, and neuronal loss. Increasing evidence suggests that AD is associated with disruptions in large-scale circuit activity across multiple disease animal models, even before clear cognitive decline. These findings highlight the need for functional biomarkers that capture dynamic changes in neuronal network activity, rather than relying solely on molecular or anatomical measures. Recent advances in neural recording technologies now allow AD-related network dysfunction to be examined with greater spatial and temporal resolution. This review summarises recent progress in large-scale neural recording technologies, including miniaturized fluorescence microscopy, voltage-sensitive optical recording, high-density probe electrophysiology, and high-density CMOS microelectrode array systems. These techniques provide improved characterization of large network-level abnormalities in AD animal models. Although they are unlikely to serve directly as routine clinical biomarkers, their translational value lies in clarifying circuit-level disease mechanisms, identifying functional features that may inform candidate clinical biomarkers, and supporting preclinical evaluation of therapeutic interventions.

Indexed as

Alzheimer DiseaseBiomarkersNerve NetAnimalsDisease Models, AnimalHumansNeuronsBiomarkersAlzheimer’s diseaseCMOS MEAsminiscopeNeuropixelsvoltage imaging

Identifiers

PMID42511787
PMCPMC13411594

What OpenQuestion holds

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LicenceCC BY
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.