Scientists have built an artificial neuron that’s so realistic it fires, learns, and responds to chemical signals just like the real thing – a breakthrough that could transform computing, medicine, ...

This paper provides a useful systematic quantification of the relationship between electrophysiological response properties of single neurons with their position in the brain. The quality of the ...

In this manuscript, the authors describe a software package for automatic differentiation of action potentials generated by excitatory and inhibitory neurons, acquired using high-density ...

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The CL1 computer is the first in the world that combines human neurons with a silicon chip. It could be used in disease modeling and drug discovery before it expires after six months. When you ...

Analyzing the types of neurons based on morphological characteristics is pivotal for understanding brain function and human development. Existing analysis approaches based on 2D view images fully use ...

Neuronal morphology can be represented using various feature representations, such as hand-crafted morphometrics and deep features. These features are complementary to each other, contributing to ...

Understanding the molecular basis of dopaminergic (DA) neuron diversity is crucial for both experimental work and clinical applications. Here, we present a comprehensive single-cell dataset ...

I tried deploying Bert on inf2, using the http://763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-pytorch-inference-neuronx:1.13.1-transformers4.36.2-neuronx ...

Abstract: With the extensive application of modulation classification in the field of wireless communication, various methods of modulation classification have been proposed to improve the ...