A neural-level model of spatial memory and imagery.
Ontology highlight
ABSTRACT:
SUBMITTER: Bicanski A
PROVIDER: S-EPMC6122954 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:EEG pattern recognition is an important part of motor imagery- (MI-) based brain computer interface (BCI) system. Traditional EEG pattern recognition algorithm usually includes two steps, namely, feature extraction and feature classification. In feature extraction, common spatial pattern (CSP) is one of the most frequently used algorithms. However, in order to extract the optimal CSP features, prior knowledge and complex parameter adjustment are often required. Convolutional neural network (CNN) is one of the most popular deep learning models at present. Within CNN, feature learning and pattern classification are carried out simultaneously during the procedure of iterative updating of network parameters; thus, it can remove the complicated manual feature engineering. In this paper, we propose a novel deep learning methodology which can be used for spatial-frequency feature learning and classification of motor imagery EEG. Specifically, a multilayer CNN model is designed according to the spatial-frequency characteristics of MI EEG signals. An experimental study is carried out on two MI EEG datasets (BCI competition III dataset IVa and a self-collected right index finger MI dataset) to validate the effectiveness of our algorithm in comparison with several closely related competing methods. Superior classification performance indicates that our proposed method is a promising pattern recognition algorithm for MI-based BCI system.
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Project description:IntroductionStem cells are a promising therapeutic in Alzheimer's disease (AD) given the complex pathophysiologic pathways involved. However, the therapeutic mechanisms of stem cells remain unclear. Here, we used spatial transcriptomics to elucidate therapeutic mechanisms of human neural stem cells (hNSCs) in an animal model of AD.MethodshNSCs were transplanted into the fimbria fornix of the hippocampus using the 5XFAD mouse model. Spatial memory was assessed by Morris water maze. Amyloid plaque burden was quantified. Spatial transcriptomics was performed and differentially expressed genes (DEGs) identified both globally and within the hippocampus. Subsequent pathway enrichment and ligand-receptor network analysis was performed.ResultshNSC transplantation restored learning curves of 5XFAD mice. However, there were no changes in amyloid plaque burden. Spatial transcriptomics showed 1,061 DEGs normalized in hippocampal subregions. Plaque induced genes in microglia, along with populations of stage 1 and stage 2 disease associated microglia (DAM), were normalized upon hNSC transplantation. Pathologic signaling between hippocampus and DAM was also restored.DiscussionhNSCs normalized many dysregulated genes, although this was not mediated by a change in amyloid plaque levels. Rather, hNSCs appear to exert beneficial effects in part by modulating microglia-mediated neuroinflammation and signaling in AD.
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Project description:The molecular mechanism of memory formation remains a mystery. Here, we show that TERT, the catalytic subunit of telomerase, gene knockout (Tert-/-) causes extremely poor ability in spatial memory formation. Knockdown of TERT in the dentate gyrus of adult hippocampus impairs spatial memory processes, while overexpression facilitates it. We find that TERT plays a critical role in neural development including dendritic development and neuritogenesis of hippocampal newborn neurons. A monosynaptic pseudotyped rabies virus retrograde tracing method shows that TERT is required for neural circuit integration of hippocampal newborn neurons. Interestingly, TERT regulated neural development and spatial memory formation in a reverse transcription activity-independent manner. Using X-ray irradiation, we find that hippocampal newborn neurons mediate the modulation of spatial memory processes by TERT. These observations reveal an important function of TERT through a non-canonical pathway and encourage the development of a TERT-based strategy to treat neurological disease-associated memory impairment.
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