{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,22]],"date-time":"2026-07-22T05:05:44Z","timestamp":1784696744117,"version":"3.55.0"},"reference-count":104,"publisher":"MDPI AG","issue":"14","license":[{"start":{"date-parts":[[2026,7,20]],"date-time":"2026-07-20T00:00:00Z","timestamp":1784505600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJMS"],"abstract":"<jats:p>Alzheimer\u2019s 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.<\/jats:p>","DOI":"10.3390\/ijms27146444","type":"journal-article","created":{"date-parts":[[2026,7,20]],"date-time":"2026-07-20T13:18:31Z","timestamp":1784553511000},"page":"6444","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Large-Scale Neural Recording Technologies for Investigating Circuit Dysfunction and Functional Biomarker Discovery in Animal Models of Alzheimer\u2019s Disease"],"prefix":"10.3390","volume":"27","author":[{"given":"Dechuan","family":"Sun","sequence":"first","affiliation":[{"name":"Neural Dynamics Laboratory, Department of Medicine, The University of Melbourne, Melbourne, VIC 3010, Australia"},{"name":"Department of Electrical and Electronic Engineering, The University of Melbourne, Melbourne, VIC 3010, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Song","family":"Wang","sequence":"additional","affiliation":[{"name":"Neural Dynamics Laboratory, Department of Medicine, The University of Melbourne, Melbourne, VIC 3010, Australia"},{"name":"Department of Electrical and Electronic Engineering, The University of Melbourne, Melbourne, VIC 3010, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qi","family":"Meng","sequence":"additional","affiliation":[{"name":"Neural Dynamics Laboratory, Department of Medicine, The University of Melbourne, Melbourne, VIC 3010, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xinyi","family":"Wang","sequence":"additional","affiliation":[{"name":"Neural Dynamics Laboratory, Department of Medicine, The University of Melbourne, Melbourne, VIC 3010, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mona","family":"Amiri","sequence":"additional","affiliation":[{"name":"Neural Dynamics Laboratory, Department of Medicine, The University of Melbourne, Melbourne, VIC 3010, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ranjith R.","family":"Unnithan","sequence":"additional","affiliation":[{"name":"Department of Electrical and Electronic Engineering, The University of Melbourne, Melbourne, VIC 3010, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1445-8704","authenticated-orcid":false,"given":"Chris","family":"French","sequence":"additional","affiliation":[{"name":"Neural Dynamics Laboratory, Department of Medicine, The University of Melbourne, Melbourne, VIC 3010, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,7,20]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"505","DOI":"10.1016\/S0140-6736(15)01124-1","article-title":"Alzheimer\u2019s disease","volume":"388","author":"Scheltens","year":"2016","journal-title":"Lancet"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1577","DOI":"10.1016\/S0140-6736(20)32205-4","article-title":"Alzheimer\u2019s disease","volume":"397","author":"Scheltens","year":"2021","journal-title":"Lancet"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"812","DOI":"10.1038\/nn.2583","article-title":"Amyloid-\u03b2\u2013induced neuronal dysfunction in Alzheimer\u2019s disease: From synapses toward neural networks","volume":"13","author":"Palop","year":"2010","journal-title":"Nat. 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