AI Medical Compendium Topic:
Neurons

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Phase response approaches to neural activity models with distributed delay.

Biological cybernetics
In weakly coupled neural oscillator networks describing brain dynamics, the coupling delay is often distributed. We present a theoretical framework to calculate the phase response curve of distributed-delay induced limit cycles with infinite-dimensio...

Robotic high-throughput biomanufacturing and functional differentiation of human pluripotent stem cells.

Stem cell reports
Efficient translation of human induced pluripotent stem cells (hiPSCs) requires scalable cell manufacturing strategies for optimal self-renewal and functional differentiation. Traditional manual cell culture is variable and labor intensive, posing ch...

Reduced and stable feature sets selection with random forest for neurons segmentation in histological images of macaque brain.

Scientific reports
In preclinical research, histology images are produced using powerful optical microscopes to digitize entire sections at cell scale. Quantification of stained tissue relies on machine learning driven segmentation. However, such methods require multip...

Automating cell counting in fluorescent microscopy through deep learning with c-ResUnet.

Scientific reports
Counting cells in fluorescent microscopy is a tedious, time-consuming task that researchers have to accomplish to assess the effects of different experimental conditions on biological structures of interest. Although such objects are generally easy t...

Numerical Investigations through ANNs for Solving COVID-19 Model.

International journal of environmental research and public health
The current investigations of the COVID-19 spreading model are presented through the artificial neuron networks (ANNs) with training of the Levenberg-Marquardt backpropagation (LMB), i.e., ANNs-LMB. The ANNs-LMB scheme is used in different variations...

Manifold learning analysis suggests strategies to align single-cell multimodal data of neuronal electrophysiology and transcriptomics.

Communications biology
Recent single-cell multimodal data reveal multi-scale characteristics of single cells, such as transcriptomics, morphology, and electrophysiology. However, integrating and analyzing such multimodal data to deeper understand functional genomics and ge...

Neural population geometry: An approach for understanding biological and artificial neural networks.

Current opinion in neurobiology
Advances in experimental neuroscience have transformed our ability to explore the structure and function of neural circuits. At the same time, advances in machine learning have unleashed the remarkable computational power of artificial neural network...

Visual prototypes in the ventral stream are attuned to complexity and gaze behavior.

Nature communications
Early theories of efficient coding suggested the visual system could compress the world by learning to represent features where information was concentrated, such as contours. This view was validated by the discovery that neurons in posterior visual ...

Adaptive neurons compute confidence in a decision network.

Scientific reports
Humans and many animals have the ability to assess the confidence of their decisions. However, little is known about the underlying neural substrate and mechanism. In this study we propose a computational model consisting of a group of 'confidence ne...

Unsupervised deep learning identifies semantic disentanglement in single inferotemporal face patch neurons.

Nature communications
In order to better understand how the brain perceives faces, it is important to know what objective drives learning in the ventral visual stream. To answer this question, we model neural responses to faces in the macaque inferotemporal (IT) cortex wi...