AIMC Topic: Models, Neurological

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Computational Principles of Supervised Learning in the Cerebellum.

Annual review of neuroscience Jul 8, 2018
Supervised learning plays a key role in the operation of many biological and artificial neural networks. Analysis of the computations underlying supervised learning is facilitated by the relatively simple and uniform architecture of the cerebellum, a...
Animals Time Factors Neuronal Plasticity Neurons Humans Models, Neurological Algorithms Supervised Machine Learning Cerebellum Nerve Net
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Improving EEG-Based Motor Imagery Classification via Spatial and Temporal Recurrent Neural Networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2018
Motor imagery (MI) based Brain-Computer Interface (BCI) is an important active BCI paradigm for recognizing movement intention of severely disabled persons. There are extensive studies about MI-based intention recognition, most of which heavily rely ...
Deep Learning Models, Neurological Humans Neural Networks, Computer Movement Electroencephalography Brain-Computer Interfaces
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A Deep Learning Approach for the Classification of Neuronal Cell Types.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2018
Classification of neurons from extracellular recordings is mainly limited to putatively excitatory or inhibitory units based on the spike shape and firing patterns. Narrow waveforms are considered to be fast spiking inhibitory neurons and broad wavef...
Neural Networks, Computer Machine Learning Action Potentials Deep Learning Neurons Models, Neurological
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Biophysically interpretable recurrent neural network for functional magnetic resonance imaging analysis and sparsity based causal architecture discovery.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2018
Recent efforts use state-of-the-art Recurrent Neural Networks (RNN) to gain insight into neuroscience. A limitation of these works is that the used generic RNNs lack biophysical meaning, making the interpretation of the results in a neuroscience cont...
Neural Networks, Computer Brain Models, Neurological Brain Mapping Magnetic Resonance Imaging
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[Review of the research of spiking neuron network based on memristor].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi Jun 25, 2018
The rapid development of artificial intelligence put forward higher requirements for the computational speed, resource consumption and the biological interpretation of computational neuroscience. Spiking neuron networks can carry a large amount of in...
Neurons Neural Networks, Computer Models, Neurological Neuronal Plasticity Action Potentials
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Correlations between synapses in pairs of neurons slow down dynamics in randomly connected neural networks.

Physical review. E Jun 1, 2018
Networks of randomly connected neurons are among the most popular models in theoretical neuroscience. The connectivity between neurons in the cortex is however not fully random, the simplest and most prominent deviation from randomness found in exper...
Neural Networks, Computer Animals Synapses Action Potentials Neurons Time Factors Models, Neurological
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Introduction.

International journal of neural systems Jun 1, 2018
Animals Models, Neurological Periodicals as Topic Neurons Parkinson Disease Neural Networks, Computer Brain Humans
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A Real-Time Reconfigurable Multichip Architecture for Large-Scale Biophysically Accurate Neuron Simulation.

IEEE transactions on biomedical circuits and systems Apr 1, 2018
Simulation of brain neurons in real-time using biophysically meaningful models is a prerequisite for comprehensive understanding of how neurons process information and communicate with each other, in effect efficiently complementing in-vivo experimen...
Animals Neural Networks, Computer Models, Neurological Olivary Nucleus Mice Computer Simulation Neurons
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An Extreme Learning Machine-Based Neuromorphic Tactile Sensing System for Texture Recognition.

IEEE transactions on biomedical circuits and systems Apr 1, 2018
Despite significant advances in computational algorithms and development of tactile sensors, artificial tactile sensing is strikingly less efficient and capable than the human tactile perception. Inspired by efficiency of biological systems, we aim t...
Humans Models, Neurological Signal Processing, Computer-Assisted Touch Pattern Recognition, Automated Machine Learning Action Potentials Algorithms Skin Neural Networks, Computer
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Skeleton-Based Human Action Recognition With Global Context-Aware Attention LSTM Networks.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society Apr 1, 2018
Human action recognition in 3D skeleton sequences has attracted a lot of research attention. Recently, long short-term memory (LSTM) networks have shown promising performance in this task due to their strengths in modeling the dependencies and dynami...
Humans Models, Neurological Pattern Recognition, Automated Algorithms Neural Networks, Computer Human Activities Databases, Factual Machine Learning
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