EXPERIMENTAL RESEARCH ON FORECASTING INDEX OF BIOLOGICAL IMAGE AEROBIC EXERCISE ANALYSIS OF ARTIFICIAL NEURAL NETWORK

EXPERIMENTAL RESEARCH ON FORECASTING INDEX OF BIOLOGICAL IMAGE AEROBIC EXERCISE ANALYSIS OF ARTIFICIAL NEURAL NETWORK

ABSTRACT Objective: The paper uses artificial neural network images to explore the effects of aerobic exercise on the gamma rhythm of theta period in the awake hippocampal CA1 area of APP/PS1/tau mice and the low-frequency gamma rhythm of the sleep state hippocampal CA1 area SWR period. Methods: Clean grade 6-month-old APP/PS1/tau mice were randomly divided into quiet group (AS) and exercise group (AE), C57BL/6J control group mice were randomly divided into quiet group (CS) and exercise group (CE). The AE group and the CE group performed 12-week treadmill exercise, 5d/week, 60min/d, the first 10min exercise load was 12m/min, the last 50min was 15m/min treadmill slope was 0°. Eight-arm maze detection of behavioral changes in mice; multi-channel in vivo recording technology to record the electrical signals of the awake state and sleep state in the hippocampal CA1 area, MATLAB extracts the awake state theta period and sleep state SWR period, multi-window spectrum estimation method Perform time-frequency analysis and power spectral density analysis. Results: 12 weeks of aerobic exercise can significantly improve the working memory and reference memory of the AS group, increase the gamma energy in theta period of the awake hippocampus CA1 area and the low-frequency gamma energy in the sleep state CA1 area SWR period. Conclusions: Aerobic exercise can improve the neural network state of the AD model and increase the gamma energy in theta period of the hippocampus CA1 area, and the low-frequency gamma energy in the SWR period is one of the neural network mechanisms for its overall behavioral improvement. Level of evidence II; Therapeutic studies - investigation of treatment results.

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Main Author: Lin,Min
Format: Digital revista
Language:English
Published: Sociedade Brasileira de Medicina do Exercício e do Esporte 2021
Online Access:http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1517-86922021000400405
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spelling oai:scielo:S1517-869220210004004052021-08-18EXPERIMENTAL RESEARCH ON FORECASTING INDEX OF BIOLOGICAL IMAGE AEROBIC EXERCISE ANALYSIS OF ARTIFICIAL NEURAL NETWORKLin,Min Neural networks, computer Exercise Diagnostic imaging ABSTRACT Objective: The paper uses artificial neural network images to explore the effects of aerobic exercise on the gamma rhythm of theta period in the awake hippocampal CA1 area of APP/PS1/tau mice and the low-frequency gamma rhythm of the sleep state hippocampal CA1 area SWR period. Methods: Clean grade 6-month-old APP/PS1/tau mice were randomly divided into quiet group (AS) and exercise group (AE), C57BL/6J control group mice were randomly divided into quiet group (CS) and exercise group (CE). The AE group and the CE group performed 12-week treadmill exercise, 5d/week, 60min/d, the first 10min exercise load was 12m/min, the last 50min was 15m/min treadmill slope was 0°. Eight-arm maze detection of behavioral changes in mice; multi-channel in vivo recording technology to record the electrical signals of the awake state and sleep state in the hippocampal CA1 area, MATLAB extracts the awake state theta period and sleep state SWR period, multi-window spectrum estimation method Perform time-frequency analysis and power spectral density analysis. Results: 12 weeks of aerobic exercise can significantly improve the working memory and reference memory of the AS group, increase the gamma energy in theta period of the awake hippocampus CA1 area and the low-frequency gamma energy in the sleep state CA1 area SWR period. Conclusions: Aerobic exercise can improve the neural network state of the AD model and increase the gamma energy in theta period of the hippocampus CA1 area, and the low-frequency gamma energy in the SWR period is one of the neural network mechanisms for its overall behavioral improvement. Level of evidence II; Therapeutic studies - investigation of treatment results.info:eu-repo/semantics/openAccessSociedade Brasileira de Medicina do Exercício e do EsporteRevista Brasileira de Medicina do Esporte v.27 n.4 20212021-08-01info:eu-repo/semantics/articletext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1517-86922021000400405en10.1590/1517-8692202127042021_0116
institution SCIELO
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country Brasil
countrycode BR
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language English
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author Lin,Min
spellingShingle Lin,Min
EXPERIMENTAL RESEARCH ON FORECASTING INDEX OF BIOLOGICAL IMAGE AEROBIC EXERCISE ANALYSIS OF ARTIFICIAL NEURAL NETWORK
author_facet Lin,Min
author_sort Lin,Min
title EXPERIMENTAL RESEARCH ON FORECASTING INDEX OF BIOLOGICAL IMAGE AEROBIC EXERCISE ANALYSIS OF ARTIFICIAL NEURAL NETWORK
title_short EXPERIMENTAL RESEARCH ON FORECASTING INDEX OF BIOLOGICAL IMAGE AEROBIC EXERCISE ANALYSIS OF ARTIFICIAL NEURAL NETWORK
title_full EXPERIMENTAL RESEARCH ON FORECASTING INDEX OF BIOLOGICAL IMAGE AEROBIC EXERCISE ANALYSIS OF ARTIFICIAL NEURAL NETWORK
title_fullStr EXPERIMENTAL RESEARCH ON FORECASTING INDEX OF BIOLOGICAL IMAGE AEROBIC EXERCISE ANALYSIS OF ARTIFICIAL NEURAL NETWORK
title_full_unstemmed EXPERIMENTAL RESEARCH ON FORECASTING INDEX OF BIOLOGICAL IMAGE AEROBIC EXERCISE ANALYSIS OF ARTIFICIAL NEURAL NETWORK
title_sort experimental research on forecasting index of biological image aerobic exercise analysis of artificial neural network
description ABSTRACT Objective: The paper uses artificial neural network images to explore the effects of aerobic exercise on the gamma rhythm of theta period in the awake hippocampal CA1 area of APP/PS1/tau mice and the low-frequency gamma rhythm of the sleep state hippocampal CA1 area SWR period. Methods: Clean grade 6-month-old APP/PS1/tau mice were randomly divided into quiet group (AS) and exercise group (AE), C57BL/6J control group mice were randomly divided into quiet group (CS) and exercise group (CE). The AE group and the CE group performed 12-week treadmill exercise, 5d/week, 60min/d, the first 10min exercise load was 12m/min, the last 50min was 15m/min treadmill slope was 0°. Eight-arm maze detection of behavioral changes in mice; multi-channel in vivo recording technology to record the electrical signals of the awake state and sleep state in the hippocampal CA1 area, MATLAB extracts the awake state theta period and sleep state SWR period, multi-window spectrum estimation method Perform time-frequency analysis and power spectral density analysis. Results: 12 weeks of aerobic exercise can significantly improve the working memory and reference memory of the AS group, increase the gamma energy in theta period of the awake hippocampus CA1 area and the low-frequency gamma energy in the sleep state CA1 area SWR period. Conclusions: Aerobic exercise can improve the neural network state of the AD model and increase the gamma energy in theta period of the hippocampus CA1 area, and the low-frequency gamma energy in the SWR period is one of the neural network mechanisms for its overall behavioral improvement. Level of evidence II; Therapeutic studies - investigation of treatment results.
publisher Sociedade Brasileira de Medicina do Exercício e do Esporte
publishDate 2021
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1517-86922021000400405
work_keys_str_mv AT linmin experimentalresearchonforecastingindexofbiologicalimageaerobicexerciseanalysisofartificialneuralnetwork
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