5XFAD Mice Show Early Onset Gap Detection Deficits.

Alzheimer's acoustic startle response auditory processing gap detection mouse model

Journal

Frontiers in aging neuroscience
ISSN: 1663-4365
Titre abrégé: Front Aging Neurosci
Pays: Switzerland
ID NLM: 101525824

Informations de publication

Date de publication:
2019
Historique:
received: 22 01 2019
accepted: 07 03 2019
entrez: 20 4 2019
pubmed: 20 4 2019
medline: 20 4 2019
Statut: epublish

Résumé

Alzheimer's patients show auditory temporal processing deficits very early in disease progression, before the onset of major cognitive impairments. In addition to potentially contributing to speech perception and communication deficits in patients, this also represents a potential early biomarker for Alzheimer's. For this reason, tests of temporal processing such as gap detection have been proposed as an early diagnosis tool. For a biomarker such as gap detection deficits to have maximum clinical value, it is important to understand what underlying neuropathology it reflects. For example, temporal processing deficits could arise from alterations at cortical, midbrain, or brainstem levels. Mouse models of Alzheimer's disease can provide the ability to reveal in detail the molecular and circuit pathology underlying disease symptoms. Here we tested whether 5XFAD mice, a leading Alzheimer's mouse model, exhibit impaired temporal processing. We found that 5XFAD mice showed robust gap detection deficits. Gap detection deficits were first detectable at about 2 months of age and became progressively worse, especially for males and for longer gap durations. We conclude that 5XFAD mice are well-suited to serve as a model for understanding the circuit mechanisms that contribute to Alzheimer's-related gap detection deficits.

Identifiants

pubmed: 31001105
doi: 10.3389/fnagi.2019.00066
pmc: PMC6454034
doi:

Types de publication

Journal Article

Langues

eng

Pagination

66

Subventions

Organisme : NIDCD NIH HHS
ID : R01 DC015828
Pays : United States

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Auteurs

Katherine Kaylegian (K)

Department of Psychology, Institute of Neuroscience, University of Oregon, Eugene, OR, United States.

Amanda J Stebritz (AJ)

Department of Psychology, Institute of Neuroscience, University of Oregon, Eugene, OR, United States.

Aldis P Weible (AP)

Department of Psychology, Institute of Neuroscience, University of Oregon, Eugene, OR, United States.

Michael Wehr (M)

Department of Psychology, Institute of Neuroscience, University of Oregon, Eugene, OR, United States.

Classifications MeSH