In the actual complex environment,the recognition accuracy of crop leaf disease is often not high.Inspired by the brain parallel interaction mechanism,a two-stream parallel interactive convolutional neural network(TSP...In the actual complex environment,the recognition accuracy of crop leaf disease is often not high.Inspired by the brain parallel interaction mechanism,a two-stream parallel interactive convolutional neural network(TSPI-CNN)is proposed to improve the recognition accuracy.TSPI-CNN includes a two-stream parallel network(TSP-Net)and a parallel interactive network(PI-Net).TSP-Net simulates the ventral and dorsal stream.PI-Net simulates the interaction between two pathways in the process of human brain visual information transmission.A large number of experiments shows that the proposed TSPI-CNN performs well on MK-D2,PlantVillage,Apple-3 leaf,and Cassava leaf datasets.Furthermore,the effect of numbers of interactions on the recognition performance of TSPI-CNN is discussed.The experimental results show that as the number of interactions increases,the recognition accuracy of the network also increases.Finally,the network is visualized to show the working mechanism of the network and provide enlightenment for future research.展开更多
The neuroimmune system of the brain:Early studies(1990’s)on the neurological consequences of human immunodeficiency virus-1(HIV-1)infection in the brain were instrumental in establishing that specific brain cell type...The neuroimmune system of the brain:Early studies(1990’s)on the neurological consequences of human immunodeficiency virus-1(HIV-1)infection in the brain were instrumental in establishing that specific brain cell types can function as an innate immune system within the brain and in that role influence cognitive function(Kaul et al.,2005).展开更多
Attention deficit and hyperactivity disorder(ADHD) is a disorder characterized by behavioral symptoms including hyperactivity/impulsivity among children,adolescents,and adults.These ADHD related symptoms are influen...Attention deficit and hyperactivity disorder(ADHD) is a disorder characterized by behavioral symptoms including hyperactivity/impulsivity among children,adolescents,and adults.These ADHD related symptoms are influenced by the complex interaction of brain networks which were under explored.We explored age-related brain network differences between ADHD patients and typically developing(TD) subjects using resting state f MRI(rs-f MRI) for three age groups of children,adolescents,and adults.We collected rs-f MRI data from 184 individuals(27 ADHD children and 31 TD children;32 ADHD adolescents and 32 TD adolescents;and 31 ADHD adults and 31 TD adults).The Brainnetome Atlas was used to define nodes in the network analysis.We compared three age groups of ADHD and TD subjects to identify the distinct regions that could explain age-related brain network differences based on degree centrality,a well-known measure of nodal centrality.The left middle temporal gyrus showed significant interaction effects between disease status(i.e.,ADHD or TD) and age(i.e.,child,adolescent,or adult)(P 0.001).Additional regions were identified at a relaxed threshold(P 0.05).Many of the identified regions(the left inferior frontal gyrus,the left middle temporal gyrus,and the left insular gyrus) were related to cognitive function.The results of our study suggest that aberrant development in cognitive brain regions might be associated with age-related brain network changes in ADHD patients.These findings contribute to better understand how brain function influences the symptoms of ADHD.展开更多
基金National Natural Science Foundation of China(Nos.61806051 and 61903078)Fundamental Research Funds for the Central Universities,China(Nos.2232021A-10 and 2232021D-32)Natural Science Foundation of Shanghai,China(No.20ZR1400400)。
文摘In the actual complex environment,the recognition accuracy of crop leaf disease is often not high.Inspired by the brain parallel interaction mechanism,a two-stream parallel interactive convolutional neural network(TSPI-CNN)is proposed to improve the recognition accuracy.TSPI-CNN includes a two-stream parallel network(TSP-Net)and a parallel interactive network(PI-Net).TSP-Net simulates the ventral and dorsal stream.PI-Net simulates the interaction between two pathways in the process of human brain visual information transmission.A large number of experiments shows that the proposed TSPI-CNN performs well on MK-D2,PlantVillage,Apple-3 leaf,and Cassava leaf datasets.Furthermore,the effect of numbers of interactions on the recognition performance of TSPI-CNN is discussed.The experimental results show that as the number of interactions increases,the recognition accuracy of the network also increases.Finally,the network is visualized to show the working mechanism of the network and provide enlightenment for future research.
基金supported by National Institutes of Health Grant AA024484(to DLG)。
文摘The neuroimmune system of the brain:Early studies(1990’s)on the neurological consequences of human immunodeficiency virus-1(HIV-1)infection in the brain were instrumental in establishing that specific brain cell types can function as an innate immune system within the brain and in that role influence cognitive function(Kaul et al.,2005).
基金supported by the Institute for Basic Science[grant No.IBS-R015-D1]the National Research Foundation of Korea(grant No.NRF-2016R1A2B4008545)
文摘Attention deficit and hyperactivity disorder(ADHD) is a disorder characterized by behavioral symptoms including hyperactivity/impulsivity among children,adolescents,and adults.These ADHD related symptoms are influenced by the complex interaction of brain networks which were under explored.We explored age-related brain network differences between ADHD patients and typically developing(TD) subjects using resting state f MRI(rs-f MRI) for three age groups of children,adolescents,and adults.We collected rs-f MRI data from 184 individuals(27 ADHD children and 31 TD children;32 ADHD adolescents and 32 TD adolescents;and 31 ADHD adults and 31 TD adults).The Brainnetome Atlas was used to define nodes in the network analysis.We compared three age groups of ADHD and TD subjects to identify the distinct regions that could explain age-related brain network differences based on degree centrality,a well-known measure of nodal centrality.The left middle temporal gyrus showed significant interaction effects between disease status(i.e.,ADHD or TD) and age(i.e.,child,adolescent,or adult)(P 0.001).Additional regions were identified at a relaxed threshold(P 0.05).Many of the identified regions(the left inferior frontal gyrus,the left middle temporal gyrus,and the left insular gyrus) were related to cognitive function.The results of our study suggest that aberrant development in cognitive brain regions might be associated with age-related brain network changes in ADHD patients.These findings contribute to better understand how brain function influences the symptoms of ADHD.