AIMC Topic:
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...
Thalamus Sodium Channels Calcium Channels Cerebral Cortex Memory Neurons Neural Networks, Computer Synapses Neuronal Plasticity Algorithms Sleep Models, Neurological Computer Simulation Electroencephalography Humans
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Robots record brain activity inside neurons.

Nature Apr 7, 2016
Robotics Neurons Automation Brain Animals Imaging, Three-Dimensional Research Personnel Patch-Clamp Techniques
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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 Fuzzy Logic Algorithms Microscopy, Fluorescence Models, Neurological Animals Neurons Image Processing, Computer-Assisted
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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...
Neuronal Plasticity Nerve Net Models, Neurological Action Potentials Periodicity Neural Networks, Computer Humans Neurons Computer Simulation Locomotion Animals Homeostasis
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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...
Reinforcement, Psychology Formative Feedback Membrane Potentials Neural Networks, Computer Brain Supervised Machine Learning Learning Humans Neurons Concept Formation Speech Models, Neurological Unsupervised Machine Learning
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Building functional networks of spiking model neurons.

Nature neuroscience Mar 1, 2016
Most of the networks used by computer scientists and many of those studied by modelers in neuroscience represent unit activities as continuous variables. Neurons, however, communicate primarily through discontinuous spiking. We review methods for tra...
Neural Networks, Computer Action Potentials Neurons
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Goal-Directed Decision Making with Spiking Neurons.

The Journal of neuroscience : the official journal of the Society for Neuroscience Feb 3, 2016
UNLABELLED: Behavioral and neuroscientific data on reward-based decision making point to a fundamental distinction between habitual and goal-directed action selection. The formation of habits, which requires simple updating of cached values, has been...
Animals Rats Action Potentials Decision Making Neurons Goals Neural Networks, Computer Reinforcement, Psychology Choice Behavior
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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...
Computer Simulation Electronic Data Processing Humans Neural Pathways Animals Bayes Theorem Neural Networks, Computer Models, Neurological Neurons Sensation
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[Hardware Implementation of Numerical Simulation Function of Hodgkin-Huxley Model Neurons Action Potential Based on Field Programmable Gate Array].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi Dec 1, 2015
Neuron is the basic unit of the biological neural system. The Hodgkin-Huxley (HH) model is one of the most realistic neuron models on the electrophysiological characteristic description of neuron. Hardware implementation of neuron could provide new r...
Synaptic Transmission Models, Neurological Humans Neural Networks, Computer Action Potentials Computer Simulation Neurons
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Framework for single input single output nanonetwork-based realistic molecular communication.

IET nanobiotechnology Dec 1, 2015
Mobile ad hoc molecular nanonetwork (MAMNET) is a new paradigm for the realisation of future nanonetworks. In MAMNET, transmission of nanoscale information from nanomachine to infostation is based on collision and adhesion. In this study, the authors...
Nerve Net Synaptic Transmission Humans Computers, Molecular Action Potentials Neurotransmitter Agents Animals Neural Networks, Computer Neurons Nanoparticles Biomimetic Materials Models, Neurological
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