AIMC Topic: Neurons

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Relating local connectivity and global dynamics in recurrent excitatory-inhibitory networks.

PLoS computational biology Jan 23, 2023
How the connectivity of cortical networks determines the neural dynamics and the resulting computations is one of the key questions in neuroscience. Previous works have pursued two complementary approaches to quantify the structure in connectivity. O...
Models, Neurological Neurons Neural Networks, Computer Normal Distribution Nerve Net Homeostasis
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Decoding of human identity by computer vision and neuronal vision.

Scientific reports Jan 12, 2023
Extracting meaning from a dynamic and variable flow of incoming information is a major goal of both natural and artificial intelligence. Computer vision (CV) guided by deep learning (DL) has made significant strides in recognizing a specific identity...
Temporal Lobe Computers Artificial Intelligence Neurons Humans Brain
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The centrality of population-level factors to network computation is demonstrated by a versatile approach for training spiking networks.

Neuron Jan 10, 2023
Neural activity is often described in terms of population-level factors extracted from the responses of many neurons. Factors provide a lower-dimensional description with the aim of shedding light on network computations. Yet, mechanistically, comput...
Action Potentials Nerve Net Neurons Neural Networks, Computer Models, Neurological
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NRN-EZ: an application to streamline biophysical modeling of synaptic integration using NEURON.

Scientific reports Jan 10, 2023
One of the fundamental goals in neuroscience is to determine how the brain processes information and ultimately controls the execution of complex behaviors. Over the past four decades, there has been a steady growth in our knowledge of the morphologi...
Models, Neurological Neurons Neural Networks, Computer Ion Channels Time Synapses
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Choice selective inhibition drives stability and competition in decision circuits.

Nature communications Jan 10, 2023
During perceptual decision-making, the firing rates of cortical neurons reflect upcoming choices. Recent work showed that excitatory and inhibitory neurons are equally selective for choice. However, the functional consequences of inhibitory choice se...
Neural Networks, Computer Neural Inhibition Models, Neurological Feedback Neurons
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Introducing the Dendrify framework for incorporating dendrites to spiking neural networks.

Nature communications Jan 10, 2023
Computational modeling has been indispensable for understanding how subcellular neuronal features influence circuit processing. However, the role of dendritic computations in network-level operations remains largely unexplored. This is partly because...
Dendrites Computer Simulation Neurons Neural Networks, Computer
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Spikebench: An open benchmark for spike train time-series classification.

PLoS computational biology Jan 10, 2023
Modern well-performing approaches to neural decoding are based on machine learning models such as decision tree ensembles and deep neural networks. The wide range of algorithms that can be utilized to learn from neural spike trains, which are essenti...
Neural Networks, Computer Animals Neurons Algorithms Machine Learning
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Deep learning in random neural fields: Numerical experiments via neural tangent kernel.

Neural networks : the official journal of the International Neural Network Society Jan 4, 2023
A biological neural network in the cortex forms a neural field. Neurons in the field have their own receptive fields, and connection weights between two neurons are random but highly correlated when they are in close proximity in receptive fields. In...
Neural Networks, Computer Deep Learning Machine Learning Neurons
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Coexistence and local stability of multiple equilibrium points for fractional-order state-dependent switched competitive neural networks with time-varying delays.

Neural networks : the official journal of the International Neural Network Society Jan 3, 2023
This paper investigates the coexistence and local stability of multiple equilibrium points for a class of competitive neural networks with sigmoidal activation functions and time-varying delays, in which fractional-order derivative and state-dependen...
Neural Networks, Computer Computer Simulation Neurons Algorithms Time Factors
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3D Soma Detection in Large-Scale Whole Brain Images via a Two-Stage Neural Network.

IEEE transactions on medical imaging Dec 29, 2022
3D soma detection in whole brain images is a critical step for neuron reconstruction. However, existing soma detection methods are not suitable for whole mouse brain images with large amounts of data and complex structure. In this paper, we propose a...
Image Processing, Computer-Assisted Neural Networks, Computer Animals Brain Neurons Mice
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