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Li CJ, Hui YQ, Zhang R, Zhou HY, Cai X, Lu L. A comparison of behavioral paradigms assessing spatial memory in tree shrews. Cereb Cortex 2023; 33:10303-10321. [PMID: 37642602 PMCID: PMC11640784 DOI: 10.1093/cercor/bhad283] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2023] [Revised: 07/13/2023] [Accepted: 07/14/2023] [Indexed: 08/31/2023] Open
Abstract
Impairments in spatial navigation in humans can be preclinical signs of Alzheimer's disease. Therefore, cognitive tests that monitor deficits in spatial memory play a crucial role in evaluating animal models with early stage Alzheimer's disease. While Chinese tree shrews (Tupaia belangeri) possess many features suitable for Alzheimer's disease modeling, behavioral tests for assessing spatial cognition in this species are lacking. Here, we established reward-based paradigms using the radial-arm maze and cheeseboard maze for tree shrews, and tested spatial memory in a group of 12 adult males in both tasks, along with a control water maze test, before and after bilateral lesions to the hippocampus, the brain region essential for spatial navigation. Tree shrews memorized target positions during training, and task performance improved gradually until reaching a plateau in all 3 mazes. However, spatial learning was compromised post-lesion in the 2 newly developed tasks, whereas memory retrieval was impaired in the water maze task. These results indicate that the cheeseboard task effectively detects impairments in spatial memory and holds potential for monitoring progressive cognitive decline in aged or genetically modified tree shrews that develop Alzheimer's disease-like symptoms. This study may facilitate the utilization of tree shrew models in Alzheimer's disease research.
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Affiliation(s)
- Cheng-Ji Li
- Key Laboratory of Animal Models and Human Disease Mechanisms of Yunnan
Province, Kunming Institute of Zoology, Chinese Academy of
Sciences, Kunming, Yunnan 650201, China
- National Research Facility for Phenotypic & Genetic Analysis of Model
Animals (Primate Facility), Kunming Institute of Zoology,
Chinese Academy of Sciences, Kunming, Yunnan
650107, China
| | - Yi-Qing Hui
- Key Laboratory of Animal Models and Human Disease Mechanisms of Yunnan
Province, Kunming Institute of Zoology, Chinese Academy of
Sciences, Kunming, Yunnan 650201, China
| | - Rong Zhang
- Key Laboratory of Animal Models and Human Disease Mechanisms of Yunnan
Province, Kunming Institute of Zoology, Chinese Academy of
Sciences, Kunming, Yunnan 650201, China
- National Research Facility for Phenotypic & Genetic Analysis of Model
Animals (Primate Facility), Kunming Institute of Zoology,
Chinese Academy of Sciences, Kunming, Yunnan
650107, China
| | - Hai-Yang Zhou
- Key Laboratory of Animal Models and Human Disease Mechanisms of Yunnan
Province, Kunming Institute of Zoology, Chinese Academy of
Sciences, Kunming, Yunnan 650201, China
| | - Xing Cai
- Key Laboratory of Animal Models and Human Disease Mechanisms of Yunnan
Province, Kunming Institute of Zoology, Chinese Academy of
Sciences, Kunming, Yunnan 650201, China
- National Research Facility for Phenotypic & Genetic Analysis of Model
Animals (Primate Facility), Kunming Institute of Zoology,
Chinese Academy of Sciences, Kunming, Yunnan
650107, China
| | - Li Lu
- Key Laboratory of Animal Models and Human Disease Mechanisms of Yunnan
Province, Kunming Institute of Zoology, Chinese Academy of
Sciences, Kunming, Yunnan 650201, China
- National Research Facility for Phenotypic & Genetic Analysis of Model
Animals (Primate Facility), Kunming Institute of Zoology,
Chinese Academy of Sciences, Kunming, Yunnan
650107, China
- Center for Excellence in Brain Science and Intelligence Technology, Chinese
Academy of Sciences, Shanghai 200031, China
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Friedman R. Measurements of neuronal morphological variation across the rat neocortex. Neurosci Lett 2020; 734:135077. [PMID: 32485285 DOI: 10.1016/j.neulet.2020.135077] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2020] [Accepted: 05/20/2020] [Indexed: 11/16/2022]
Abstract
Neuron morphology is highly variable across the mammalian brain. It is thought that these attributes of neuronal cell shape, such as soma surface area and branching frequency, are determined by biological function and information processing. In this study, a large data set of neurons across the rat neocortex were clustered by their anatomical characters for evidence of distinctiveness among neocortical regions and the somatosensory layers. This data set of neuronal morphologies was compiled from 31 different lab sources with a validation procedure so that data records are potentially comparable across research studies. With this large set of heterogeneous data and by clustering analysis, this study shows that neuronal morphological traits overlap among neocortical and somatosensory regions. In the context of past neuroanatomical studies, this result is not congruent with tissue level analysis and strongly suggests further sampling of neuronal data to lessen the effect of confounding factors, such as the influence of different methodologies from use of heterogeneous samples of neuronal data.
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Affiliation(s)
- Robert Friedman
- Department of Biological Sciences, University of South Carolina, Columbia, SC, United States.
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