AIMC Topic: Models, Neurological

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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...
Humans Analysis of Variance Area Under Curve Computer Simulation Nerve Net Brain Models, Neurological Electroencephalography Signal Processing, Computer-Assisted Brain Mapping
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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 ...
Computer Simulation Models, Neurological Neurons Neural Networks, Computer
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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...
Humans Neural Networks, Computer Algorithms Electroencephalography Neurons Synapses Computer Simulation Neuronal Plasticity Models, Neurological Sleep Memory Calcium Channels Thalamus Cerebral Cortex Sodium Channels
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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...
Microscopy, Fluorescence Humans Image Processing, Computer-Assisted Neurons Algorithms Fuzzy Logic Animals Models, Neurological
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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...
Homeostasis Nerve Net Periodicity Action Potentials Neurons Locomotion Humans Neural Networks, Computer Computer Simulation Animals Neuronal Plasticity Models, Neurological
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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...
Humans Neural Networks, Computer Brain Concept Formation Reinforcement, Psychology Formative Feedback Membrane Potentials Unsupervised Machine Learning Learning Supervised Machine Learning Speech Neurons 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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BIT: Biologically Inspired Tracker.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society Mar 1, 2016
Visual tracking is challenging due to image variations caused by various factors, such as object deformation, scale change, illumination change, and occlusion. Given the superior tracking performance of human visual system (HVS), an ideal design of b...
Pattern Recognition, Automated Visual Perception Fourier Analysis Humans Machine Learning Image Processing, Computer-Assisted Models, Neurological Video Recording
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Decentralized Multisensory Information Integration in Neural Systems.

The Journal of neuroscience : the official journal of the Society for Neuroscience Jan 13, 2016
UNLABELLED: How multiple sensory cues are integrated in neural circuitry remains a challenge. The common hypothesis is that information integration might be accomplished in a dedicated multisensory integration area receiving feedforward inputs from t...
Models, Neurological Bayes Theorem Neurons Humans Sensation Neural Networks, Computer Electronic Data Processing Computer Simulation Neural Pathways Animals
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