AIMC Topic: Neurons

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Automated Curation of CNMF-E-Extracted ROI Spatial Footprints and Calcium Traces Using Open-Source AutoML Tools.

Frontiers in neural circuits
1-photon (1p) calcium imaging is an increasingly prevalent method in behavioral neuroscience. Numerous analysis pipelines have been developed to improve the reliability and scalability of pre-processing and ROI extraction for these large calcium ima...

Neural networks of different species, brain areas and states can be characterized by the probability polling state.

The European journal of neuroscience
Cortical networks are complex systems of a great many interconnected neurons that operate from collective dynamical states. To understand how cortical neural networks function, it is important to identify their common dynamical operating states from ...

Selective Neuronal Vulnerability in Alzheimer's Disease: A Network-Based Analysis.

Neuron
A major obstacle to treating Alzheimer's disease (AD) is our lack of understanding of the molecular mechanisms underlying selective neuronal vulnerability, a key characteristic of the disease. Here, we present a framework integrating high-quality neu...

Prefrontal oscillations modulate the propagation of neuronal activity required for working memory.

Neurobiology of learning and memory
Cognition involves using attended information, maintained in working memory (WM), to guide action. During a cognitive task, a correct response requires flexible, selective gating so that only the appropriate information flows from WM to downstream ef...

A new Lyapunov functional for stability analysis of neutral-type Hopfield neural networks with multiple delays.

Neural networks : the official journal of the International Neural Network Society
This research paper conducts an investigation into the stability issue for a more general class of neutral-type Hopfield neural networks that involves multiple time delays in the states of neurons and multiple neutral delays in the time derivatives o...

A spiking neural network-based long-term prediction system for biogas production.

Neural networks : the official journal of the International Neural Network Society
Efficient energy production from biomass is a central issue in the context of clean alternative energy resource. In this work we propose a novel model based on spiking neural networks cubes in order to model the chemical processes that goes on in a d...

A Model for Structured Information Representation in Neural Networks of the Brain.

eNeuro
Humans can reason at an abstract level and structure information into abstract categories, but the underlying neural processes have remained unknown. Recent experimental data provide the hint that this is likely to involve specific subareas of the br...

Temporal Backpropagation for Spiking Neural Networks with One Spike per Neuron.

International journal of neural systems
We propose a new supervised learning rule for multilayer spiking neural networks (SNNs) that use a form of temporal coding known as rank-order-coding. With this coding scheme, all neurons fire exactly one spike per stimulus, but the firing order carr...

A Modeling Study of the Emergence of Eye Position Gain Fields Modulating the Responses of Visual Neurons in the Brain.

Frontiers in neural circuits
The responses of many cortical neurons to visual stimuli are modulated by the position of the eye. This form of gain modulation by eye position does not change the retinotopic selectivity of the responses, but only changes the amplitude of the respon...

Generation of Scale-Invariant Sequential Activity in Linear Recurrent Networks.

Neural computation
Sequential neural activity has been observed in many parts of the brain and has been proposed as a neural mechanism for memory. The natural world expresses temporal relationships at a wide range of scales. Because we cannot know the relevant scales a...