AIMC Topic: Cerebellar Nuclei

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Automated segmentation of deep brain nuclei using convolutional neural networks and susceptibility weighted imaging.

Human brain mapping Jul 29, 2021
The advent of susceptibility-sensitive MRI techniques, such as susceptibility weighted imaging (SWI), has enabled accurate in vivo visualization and quantification of iron deposition within the human brain. Although previous approaches have been intr...
Humans Neural Networks, Computer Female Aged Young Adult Adult Male Middle Aged Image Processing, Computer-Assisted Magnetic Resonance Imaging Substantia Nigra Neuroimaging Subthalamic Nucleus Cerebellar Nuclei Red Nucleus
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Population coding in the cerebellum: a machine learning perspective.

Journal of neurophysiology Oct 28, 2020
The cere resembles a feedforward, three-layer network of neurons in which the "hidden layer" consists of Purkinje cells (P-cells) and the output layer consists of deep cerebellar nucleus (DCN) neurons. In this analogy, the output of each DCN neuron i...
Humans Machine Learning Learning Animals Eye Movements Action Potentials Cerebellum Motor Activity Conditioning, Classical Purkinje Cells Cerebellar Nuclei
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Classification of adult human dentate nucleus border neurons: Artificial neural networks and multidimensional approach.

Journal of theoretical biology Jun 15, 2016
AIMS: Primary aim in this study is to investigate whether external and internal border neurons of adult human dentate nucleus express the same neuromorphological features or belong to a different morphological types i.e. whether can be classified not...
Humans Neural Networks, Computer Adult Cluster Analysis Principal Component Analysis Neurons Dendrites Cerebellar Nuclei
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