AIMC Topic: Neurons

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Neural electrical activity and neural network growth.

Neural networks : the official journal of the International Neural Network Society Feb 9, 2018
The development of central and peripheral neural system depends in part on the emergence of the correct functional connectivity in its input and output pathways. Now it is generally accepted that molecular factors guide neurons to establish a primary...
Models, Neurological Neurons Neurogenesis Neural Networks, Computer
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GXNOR-Net: Training deep neural networks with ternary weights and activations without full-precision memory under a unified discretization framework.

Neural networks : the official journal of the International Neural Network Society Feb 2, 2018
Although deep neural networks (DNNs) are being a revolutionary power to open up the AI era, the notoriously huge hardware overhead has challenged their applications. Recently, several binary and ternary networks, in which the costly multiply-accumula...
Magnetic Resonance Imaging Algorithms Neurons Neural Networks, Computer Support Vector Machine Memory
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O(t)-synchronization and Mittag-Leffler synchronization for the fractional-order memristive neural networks with delays and discontinuous neuron activations.

Neural networks : the official journal of the International Neural Network Society Jan 31, 2018
This paper investigates O(t)-synchronization and adaptive Mittag-Leffler synchronization for the fractional-order memristive neural networks with delays and discontinuous neuron activations. Firstly, based on the framework of Filippov solution and di...
Time Factors Neural Networks, Computer Neurons Algorithms
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A novel type of activation function in artificial neural networks: Trained activation function.

Neural networks : the official journal of the International Neural Network Society Jan 31, 2018
Determining optimal activation function in artificial neural networks is an important issue because it is directly linked with obtained success rates. But, unfortunately, there is not any way to determine them analytically, optimal activation functio...
Neural Networks, Computer Neurons Artificial Intelligence Linear Models Humans Algorithms Databases, Factual Learning
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The modulation of neural gain facilitates a transition between functional segregation and integration in the brain.

eLife Jan 29, 2018
Cognitive function relies on a dynamic, context-sensitive balance between functional integration and segregation in the brain. Previous work has proposed that this balance is mediated by global fluctuations in neural gain by projections from ascendin...
Neurons Nerve Net Cognition Neural Networks, Computer Brain Computer Simulation
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Unsupervised heart-rate estimation in wearables with Liquid states and a probabilistic readout.

Neural networks : the official journal of the International Neural Network Society Jan 12, 2018
Heart-rate estimation is a fundamental feature of modern wearable devices. In this paper we propose a machine learning technique to estimate heart-rate from electrocardiogram (ECG) data collected using wearable devices. The novelty of our approach li...
Humans Algorithms Wearable Electronic Devices Heart Rate Probability Electrocardiography Unsupervised Machine Learning Action Potentials Neuronal Plasticity Neurons
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A border-ownership model based on computational electromagnetism.

Neural networks : the official journal of the International Neural Network Society Jan 10, 2018
The mathematical relation between a vector electric field and its corresponding scalar potential field is useful to formulate computational problems of lower/middle-order visual processing, specifically related to the assignment of borders to the sid...
Learning Neurons Photic Stimulation Pattern Recognition, Visual Electromagnetic Phenomena Humans Neural Networks, Computer Computer Simulation Visual Cortex Ownership
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A neural network model for the orbitofrontal cortex and task space acquisition during reinforcement learning.

PLoS computational biology Jan 4, 2018
Reinforcement learning has been widely used in explaining animal behavior. In reinforcement learning, the agent learns the value of the states in the task, collectively constituting the task state space, and uses the knowledge to choose actions and a...
Decision Making Neurons Probability Magnetic Resonance Imaging Models, Neurological Nerve Net Reinforcement, Psychology Frontal Lobe Markov Chains Electrophysiology Neural Networks, Computer Learning Prefrontal Cortex Cognition Animals Spatial Learning Humans
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A new approach to detect the coding rule of the cortical spiking model in the information transmission.

Neural networks : the official journal of the International Neural Network Society Jan 3, 2018
Investigation of the role of the local field potential (LFP) fluctuations in encoding the received sensory information by the nervous system remains largely unknown. On the other hand, transmission of these translation rules in information transmissi...
Neurons Synapses Models, Neurological Action Potentials Neural Networks, Computer Neuronal Plasticity Humans
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Multi-neuron intracellular recording in vivo via interacting autopatching robots.

eLife Jan 3, 2018
The activities of groups of neurons in a circuit or brain region are important for neuronal computations that contribute to behaviors and disease states. Traditional extracellular recordings have been powerful and scalable, but much less is known abo...
Patch-Clamp Techniques Robotics Neurons Anesthesia Automation, Laboratory Animals Cerebral Cortex Mice Wakefulness Action Potentials
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