Results 11 to 20 of about 2,000,131 (360)
Emotional brain network decoded by biological spiking neural network
Frontiers in Neuroscience, 2023 IntroductionEmotional disorders are essential manifestations of many neurological and psychiatric diseases. Nowadays, researchers try to explore bi-directional brain-computer interface techniques to help the patients.
Hubo Xu +10 more
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Blind Nonnegative Source Separation Using Biological Neural Networks [PDF]
Neural Computation, 2017 Blind source separation—the extraction of independent sources from a mixture—is an important problem for both artificial and natural signal processing. Here, we address a special case of this problem when sources (but not the mixing matrix) are known to ...
Cengiz Pehlevan, S. Mohan, D. Chklovskii
semanticscholar +5 more sources
All-Optical Assay to Study Biological Neural Networks [PDF]
Frontiers in Neuroscience, 2018 We introduce a novel all-optical assay for functional studies of biological neural networks in vitro. We created a novel optogenetic construct named OptoCaMP which is a combination of a channelrhodopsin variant (CheRiff) and a red genetically encoded ...
Wardiya Afshar Saber +4 more
semanticscholar +6 more sources
An Overview of In Vitro Biological Neural Networks for Robot Intelligence
Cyborg and Bionic Systems, 2023 In vitro biological neural networks (BNNs) interconnected with robots, so-called BNN-based neurorobotic systems, can interact with the external world, so that they can present some preliminary intelligent behaviors, including learning, memory, robot ...
Zhe Chen +6 more
semanticscholar +1 more source
Advances in Multimedia, 2021 Biological neural network system is a complex nonlinear dynamic system, and research on its dynamics is an important topic at home and abroad. This paper briefly introduces the dynamic characteristics and influencing factors of the neural network system,
Hongyan Chen
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Deep problems with neural network models of human vision [PDF]
Behavioral and Brain Sciences, 2022 Deep neural networks (DNNs) have had extraordinary successes in classifying photographic images of objects and are often described as the best models of biological vision.
J. Bowers +12 more
semanticscholar +1 more source
Unsupervised pretraining in biological neural networks [PDF]
NatureAbstract Representation learning in neural networks may be implemented with supervised or unsupervised algorithms, distinguished by the availability of instruction. In the sensory cortex, perceptual learning drives neural plasticity1–13, but it is not known whether this is due to supervised or unsupervised learning.
Lin Zhong +6 more
openalex +3 more sources
Supervised biological network alignment with graph neural networks
Bioinformatics, 2023 AbstractMotivationDespite the advances in sequencing technology, massive proteins with known sequences remain functionally unannotated. Biological network alignment (NA), which aims to find the node correspondence between species’ protein-protein interaction (PPI) networks, has been a popular strategy to uncover missing annotations by transferring ...
Kerr Ding, Sheng Wang, Yunan Luo
openaire +2 more sources
Artificial Neural Networks [PDF]
, 2017 Artificial Neural Network is a mathematical model, made in the form of software or hardware, built on the principle of biological neural networks of living cells. The neural network is a system of connected processors interacting with each other.
Gulko, Illya +2 more
core +5 more sources
Spiking Neural Networks and Their Applications: A Review
Brain Sciences, 2022 The past decade has witnessed the great success of deep neural networks in various domains. However, deep neural networks are very resource-intensive in terms of energy consumption, data requirements, and high computational costs.
Kashu Yamazaki +3 more
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