AIMC Topic: Neurons

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Nutritionally Responsive PMv DAT Neurons Are Dynamically Regulated During Pubertal Transition.

FASEB journal : official publication of the Federation of American Societies for Experimental Biology
Pubertal development is tightly regulated by energy balance. The crosstalk between metabolism and reproduction is orchestrated by complex neural networks, and leptin action in the hypothalamus plays a critical role. The ventral premammillary nucleus ...

Spiking Neural Network Models of Interaural Time Difference Extraction via a Massively Collaborative Process.

eNeuro
Neuroscientists are increasingly initiating large-scale collaborations which bring together tens to hundreds of researchers. At this scale, such projects can tackle big challenges and engage diverse participants. Inspired by projects in mathematics, ...

Ternary spike-based neuromorphic signal processing system.

Neural networks : the official journal of the International Neural Network Society
Deep Neural Networks (DNNs) have been successfully implemented across various signal processing fields, resulting in significant enhancements in performance. However, DNNs generally require substantial computational resources, leading to significant ...

A guide to CNN-based dense segmentation of neuronal EM images.

Microscopy (Oxford, England)
Large-scale reconstitution of neuronal circuits from volumetric electron microscopy images is a remarkable research goal in neuroanatomy. However, the large-scale reconstruction is a result of automatic segmentation using convolutional neural network...

Homeostasis: Stay cool but keep on breathing.

Current biology : CB
Homeostatic control of neural networks is based on monitoring the activity level of neurons and adjusting excitability. A recent study demonstrates that the physical environment per se (temperature) can directly regulate the neural circuits underlyin...

Neural Metabolic Networks: Key Elements of Healthy Brain Function.

Journal of neurochemistry
Neural networks are responsible for processing sensory stimuli and driving the synaptic activity required for brain function and behavior. This computational capacity is expensive and requires a steady supply of energy and building blocks to operate....

Neuronal Waveform Classification in Multielectrode Recordings Using Machine Learning Techniques and Multidimensional Analysis.

International journal of neural systems
Extracellular recordings of neuronal spikes are crucial for studying brain activity. These signals are typically classified based on firing patterns and waveform shape, particularly trough-to-peak duration. While useful, this method oversimplifies th...

A mean field theory for pulse-coupled neural oscillators based on the spike time response curve.

Journal of neurophysiology
A mean field method for pulse-coupled oscillators with delays used a self-connected oscillator to represent a synchronous cluster of - 1 oscillators and a single oscillator assumed to be perturbed from the cluster. A periodic train of biexponential ...

Neurocounter - A deep learning framework for high-fidelity spatial localization of neurons.

Journal of neuroscience methods
BACKGROUND: Many neuroscientific applications require robust and accurate localization of neurons. It is still an unsolved problem because of the enormous variation in intensity, texture, spatial overlap, morphology, and background artifacts. In addi...

Toward Building Human-Like Sequential Memory Using Brain-Inspired Spiking Neural Models.

IEEE transactions on neural networks and learning systems
The brain is able to acquire and store memories of everyday experiences in real-time. It can also selectively forget information to facilitate memory updating. However, our understanding of the underlying mechanisms and coordination of these processe...