ArticleiScience2023
Early classification of Alzheimer's disease phenotype based on hippocampal electrophysiology in the TgF344-AD rat model.
Article in iScience, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Medial entorhinal-hippocampal desynchronization parallels the emergence of memory impairment in a mouse model of Alzheimer's disease pathology.Cell reports · 2026Article
- Quantifying spike train synchrony and directionality: Measures and Applications.Biological cybernetics · 2026Review
- G-ALPS: An index for evaluating cognitive decline and aging using diffusion tensor imaging.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Article
- Photobiomodulation at 660 nm Alleviates Alzheimer's Disease Pathology Through Amyloid-β Reduction and SIRT1 Upregulation in the Hippocampus of 5xFAD Mice.International journal of molecular sciences · 2025Article
- Article
- Differential Glial Response and Neurodegenerative Patterns in CA1, CA3, and DG Hippocampal Regions of 5XFAD Mice.International journal of molecular sciences · 2024Article
- Multimodal Gamma Stimulation Improves Activity but not Memory in Aged Tgf344-AD Rats.Current Alzheimer research · 2024Article
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Authors and funding
7 authors.
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Abstract
The hippocampus plays a vital role in navigation, learning, and memory, and is affected in Alzheimer's disease (AD). This study investigated the classification of AD-transgenic rats versus wild-type littermates using electrophysiological activity recorded from the hippocampus at an early, presymptomatic stage of the disease (6 months old) in the TgF344-AD rat model. The recorded signals were filtered into low frequency (LFP) and high frequency (spiking activity) signals, and machine learning classifiers were employed to identify the rat genotype (TG vs. WT). By analyzing specific frequency bands in the low frequency signals and calculating distance metrics between spike trains in the high frequency signals, accurate classification was achieved. Gamma band power emerged as a valuable signal for classification, and combining information from both low and high frequency signals improved the accuracy further. These findings provide valuable insights into the early stage effects of AD on different regions of the hippocampus.
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