AIMC Topic: Models, Neurological

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A supervised learning rule for classification of spatiotemporal spike patterns.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Aug 1, 2016
This study introduces a novel supervised algorithm for spiking neurons that take into consideration synapse delays and axonal delays associated with weights. It can be utilized for both classification and association and uses several biologically inf...
Supervised Machine Learning Neurons Synapses Algorithms Models, Neurological Action Potentials
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Tuning electrical stimulation for thalamic visual prosthesis: An autoencoder-based approach.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Aug 1, 2016
Visual prosthesis holds hope of vision restoration for millions with retinal degenerative diseases. Machine learning techniques such as artificial neural networks could help in improving prosthetic devices as they could learn how the brain encodes in...
Photic Stimulation Models, Statistical Humans Visual Prosthesis Thalamus Models, Neurological Geniculate Bodies
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Measuring the agreement between brain connectivity networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Aug 1, 2016
Investigating the level of similarity between two brain networks, resulting from measures of effective connectivity in the brain, can be of interest from many respects. In this study, we propose and test the idea to borrow measures of association use...
Electroencephalography Signal Processing, Computer-Assisted Analysis of Variance Brain Mapping Area Under Curve Nerve Net Humans Brain Computer Simulation Models, Neurological
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Arrangement and Applying of Movement Patterns in the Cerebellum Based on Semi-supervised Learning.

Cerebellum (London, England) Jun 1, 2016
Biological control systems have long been studied as a possible inspiration for the construction of robotic controllers. The cerebellum is known to be involved in the production and learning of smooth, coordinated movements. Therefore, highly regular...
Neurons Cerebellum Movement Humans Models, Neurological Supervised Machine Learning
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Storing Sequences in Binary Tournament-Based Neural Networks.

IEEE transactions on neural networks and learning systems May 1, 2016
An extension to a recently introduced architecture of clique-based neural networks is presented. This extension makes it possible to store sequences with high efficiency. To obtain this property, network connections are provided with orientation and ...
Neural Networks, Computer Computer Simulation Models, Neurological Neurons
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Synaptic Mechanisms of Memory Consolidation during Sleep Slow Oscillations.

The Journal of neuroscience : the official journal of the Society for Neuroscience Apr 13, 2016
UNLABELLED: Sleep is critical for regulation of synaptic efficacy, memories, and learning. However, the underlying mechanisms of how sleep rhythms contribute to consolidating memories acquired during wakefulness remain unclear. Here we studied the ro...
Neurons Synapses Sleep Models, Neurological Electroencephalography Thalamus Sodium Channels Calcium Channels Cerebral Cortex Memory Humans Neural Networks, Computer Algorithms Computer Simulation Neuronal Plasticity
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Fuzzy-Logic Based Detection and Characterization of Junctions and Terminations in Fluorescence Microscopy Images of Neurons.

Neuroinformatics Apr 1, 2016
Digital reconstruction of neuronal cell morphology is an important step toward understanding the functionality of neuronal networks. Neurons are tree-like structures whose description depends critically on the junctions and terminations, collectively...
Humans Microscopy, Fluorescence Neurons Image Processing, Computer-Assisted Fuzzy Logic Algorithms Models, Neurological Animals
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Homeostatic Activity-Dependent Tuning of Recurrent Networks for Robust Propagation of Activity.

The Journal of neuroscience : the official journal of the Society for Neuroscience Mar 30, 2016
UNLABELLED: Developing neuronal networks display spontaneous bursts of action potentials that are necessary for circuit organization and tuning. While spontaneous activity has been shown to instruct map formation in sensory circuits, it is unknown wh...
Nerve Net Periodicity Neurons Locomotion Computer Simulation Homeostasis Humans Animals Models, Neurological Neural Networks, Computer Neuronal Plasticity Action Potentials
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Spiking neurons can discover predictive features by aggregate-label learning.

Science (New York, N.Y.) Mar 4, 2016
The brain routinely discovers sensory clues that predict opportunities or dangers. However, it is unclear how neural learning processes can bridge the typically long delays between sensory clues and behavioral outcomes. Here, I introduce a learning c...
Concept Formation Humans Unsupervised Machine Learning Reinforcement, Psychology Neural Networks, Computer Supervised Machine Learning Formative Feedback Brain Neurons Membrane Potentials Learning Speech Models, Neurological
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Using goal-driven deep learning models to understand sensory cortex.

Nature neuroscience Mar 1, 2016
Fueled by innovation in the computer vision and artificial intelligence communities, recent developments in computational neuroscience have used goal-driven hierarchical convolutional neural networks (HCNNs) to make strides in modeling neural single-...
Somatosensory Cortex Models, Neurological Goals Visual Cortex Learning Animals Humans Neural Networks, Computer
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