AIMC Topic: Action Potentials

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Robust computation with rhythmic spike patterns.

Proceedings of the National Academy of Sciences of the United States of America Aug 20, 2019
Information coding by precise timing of spikes can be faster and more energy efficient than traditional rate coding. However, spike-timing codes are often brittle, which has limited their use in theoretical neuroscience and computing applications. He...
Humans Nerve Net Memory Interneurons Neural Networks, Computer Models, Neurological Action Potentials
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A modeling and machine learning approach to ECG feature engineering for the detection of ischemia using pseudo-ECG.

PloS one Aug 12, 2019
Early detection of coronary heart disease (CHD) has the potential to prevent the millions of deaths that this disease causes worldwide every year. However, there exist few automatic methods to detect CHD at an early stage. A challenge in the developm...
Electrocardiography Ischemia Machine Learning Humans Action Potentials Biomarkers Models, Theoretical Neural Networks, Computer
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Probabilistic associative learning suffices for learning the temporal structure of multiple sequences.

PloS one Aug 1, 2019
From memorizing a musical tune to navigating a well known route, many of our underlying behaviors have a strong temporal component. While the mechanisms behind the sequential nature of the underlying brain activity are likely multifarious and multi-s...
Bayes Theorem Humans Memory Neural Networks, Computer Mental Recall Association Learning Models, Neurological Action Potentials
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Sensitivity to Stimulus Irregularity Is Inherent in Neural Networks.

Neural computation Jul 23, 2019
Behavior is controlled by complex neural networks in which neurons process thousands of inputs. However, even short spike trains evoked in a single cortical neuron were demonstrated to be sufficient to influence behavior in vivo. Specifically, irregu...
Neural Networks, Computer Animals Synapses Nerve Net Action Potentials Somatosensory Cortex Neurons
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A New Nonlinear Sparse Component Analysis for a Biologically Plausible Model of Neurons.

Neural computation Jul 23, 2019
It is known that brain can create a sparse representation of the environment in both sensory and mnemonic forms (Olshausen & Field, 2004). Such sparse representation can be combined in downstream areas to create rich multisensory responses to support...
Neurons Nonlinear Dynamics Humans Models, Neurological Neural Networks, Computer Action Potentials Brain Principal Component Analysis
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Learning with Precise Spike Times: A New Decoding Algorithm for Liquid State Machines.

Neural computation Jul 23, 2019
There is extensive evidence that biological neural networks encode information in the precise timing of the spikes generated and transmitted by neurons, which offers several advantages over rate-based codes. Here we adopt a vector space formulation o...
Algorithms Models, Neurological Action Potentials Speech Recognition Software Humans Neural Networks, Computer Machine Learning
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SpikeDeeptector: a deep-learning based method for detection of neural spiking activity.

Journal of neural engineering Jul 23, 2019
OBJECTIVE: In electrophysiology, microelectrodes are the primary source for recording neural data (single unit activity). These microelectrodes can be implanted individually or in the form of arrays containing dozens to hundreds of channels. Recordin...
Neurons Quadriplegia Brain Deep Learning Female Young Adult Adult Male Middle Aged Humans Neural Networks, Computer Action Potentials
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Intracortical neural activity distal to seizure-onset-areas predicts human focal seizures.

PloS one Jul 22, 2019
The apparent unpredictability of epileptic seizures has a major impact in the quality of life of people with pharmacologically resistant seizures. Here, we present initial results and a proof-of-concept of how focal seizures can be predicted early in...
Electroencephalography Seizures Signal Processing, Computer-Assisted Cerebral Cortex Middle Aged Action Potentials Algorithms Brain Mapping Adult Female Male Young Adult Humans Machine Learning
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Deep Spiking Neural Network for Video-Based Disguise Face Recognition Based on Dynamic Facial Movements.

IEEE transactions on neural networks and learning systems Jul 19, 2019
With the increasing popularity of social media and smart devices, the face as one of the key biometrics becomes vital for person identification. Among those face recognition algorithms, video-based face recognition methods could make use of both temp...
Video Recording Automated Facial Recognition Facial Expression Neural Networks, Computer Action Potentials Photic Stimulation Humans
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Modeling grid fields instead of modeling grid cells : An effective model at the macroscopic level and its relationship with the underlying microscopic neural system.

Journal of computational neuroscience Jul 8, 2019
A neuron's firing correlates are defined as the features of the external world to which its activity is correlated. In many parts of the brain, neurons have quite simple such firing correlates. A striking example are grid cells in the rodent medial e...
Animals Models, Neurological Action Potentials Neural Networks, Computer Computer Simulation Sensory Receptor Cells Orientation, Spatial Entorhinal Cortex
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