Cargando…

Editorial: Symmetry as a guiding principle in artificial and brain neural networks

Detalles Bibliográficos
Autores principales:	Anselmi, Fabio, Patel, Ankit B.
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Frontiers Media S.A. 2022
Materias:	Neuroscience
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9638158/ https://www.ncbi.nlm.nih.gov/pubmed/36353212 http://dx.doi.org/10.3389/fncom.2022.1039572

Ejemplares similares

Editorial: Artificial Neural Networks as Models of Neural Information Processing
por: van Gerven, Marcel, et al.
Publicado: (2017)

Understanding Robustness and Generalization of Artificial Neural Networks Through Fourier Masks
por: Karantzas, Nikos, et al.
Publicado: (2022)

Editorial: The application of artificial intelligence in brain-computer interface and neural system rehabilitation
por: Xu, Fangzhou, et al.
Publicado: (2023)

Editorial: The new frontier in brain network physiology: from temporal dynamics to the principles of integration in physiological brain networks
por: Trenado, Carlos, et al.
Publicado: (2023)

On the similarities of representations in artificial and brain neural networks for speech recognition
por: Wingfield, Cai, et al.
Publicado: (2022)

Editorial: Recent advances in artificial neural networks and embedded systems for multi-source image fusion
por: Jin, Xin, et al.
Publicado: (2022)

Editorial: Plasticity and Reconstruction of Neural Network in Brain Injury
por: Zhang, Pengyue, et al.
Publicado: (2021)

Artificial neural networks for non-linear age correction of diffusion metrics in the brain
por: Kocar, Thomas D., et al.
Publicado: (2022)

Lessons From Deep Neural Networks for Studying the Coding Principles of Biological Neural Networks
por: Bae, Hyojin, et al.
Publicado: (2021)

Neurally plausible mechanisms for learning selective and invariant representations
por: Anselmi, Fabio, et al.
Publicado: (2020)

Erratum: Lessons From Deep Neural Networks for Studying the Coding Principles of Biological Neural Networks
por: Frontiers Production Office,
Publicado: (2022)

Brain serotonergic fibers suggest anomalous diffusion-based dropout in artificial neural networks
por: Lee, Christian, et al.
Publicado: (2022)

Symmetry-Based Representations for Artificial and Biological General Intelligence
por: Higgins, Irina, et al.
Publicado: (2022)

Comparison of Artificial and Spiking Neural Networks on Digital Hardware
por: Davidson, Simon, et al.
Publicado: (2021)

Editorial: Functional microcircuits in the brain and in artificial intelligent systems
por: Lee, Jung H., et al.
Publicado: (2023)

The Müller-Lyer illusion as seen by an artificial neural network
por: García-Garibay, Otto B., et al.
Publicado: (2015)

Quantifying the Brain Predictivity of Artificial Neural Networks With Nonlinear Response Mapping
por: Anand, Aditi, et al.
Publicado: (2021)

Editorial: Neural Signal Estimation in the Human Brain
por: Tyler, Christopher W., et al.
Publicado: (2016)

BSMM-Net: Multi-modal neural network based on bilateral symmetry for nasopharyngeal carcinoma segmentation
por: Zhou, Haoyang, et al.
Publicado: (2023)

A brain-inspired algorithm that mitigates catastrophic forgetting of artificial and spiking neural networks with low computational cost
por: Zhang, Tielin, et al.
Publicado: (2023)

Editorial: Artificial intelligence in brain-computer interfaces and neuroimaging for neuromodulation and neurofeedback
por: Ponce, Hiram, et al.
Publicado: (2022)

BSNN: Towards faster and better conversion of artificial neural networks to spiking neural networks with bistable neurons
por: Li, Yang, et al.
Publicado: (2022)

A Symmetry-Based Method to Infer Structural Brain Networks from Probabilistic Tractography Data
por: Shadi, Kamal, et al.
Publicado: (2016)

Using a Simple Neural Network to Delineate Some Principles of Distributed Economic Choice
por: Balasubramani, Pragathi P., et al.
Publicado: (2018)

Editorial: The intersection of artificial intelligence and brain for high-performance neuroprosthesis and cyborg systems
por: Qi, Yu, et al.
Publicado: (2023)

Editorial: Affective brain-computer interface in emotion artificial intelligence and medical engineering
por: Lu, Zhaohua, et al.
Publicado: (2023)

Editorial: Spiking Neural Network Learning, Benchmarking, Programming and Executing
por: Li, Guoqi, et al.
Publicado: (2020)

Editorial: Deep neural network based decision-making interpretability
por: Cao, Guitao, et al.
Publicado: (2023)

Intrinsic timescales as an organizational principle of neural processing across the whole rhesus macaque brain
por: Manea, Ana MG, et al.
Publicado: (2022)

Editorial: Hardware for artificial intelligence
por: Boybat, Irem, et al.
Publicado: (2022)

Editorial: Generative AI for brain imaging and brain network construction
por: Wang, Shu-Qiang, et al.
Publicado: (2023)

Editorial: Complexity and emergence in brain network analyses
por: Telesford, Qawi K., et al.
Publicado: (2015)

STNet: A novel spiking neural network combining its own time signal with the spatial signal of an artificial neural network
por: Liu, Fang, et al.
Publicado: (2023)

Neuroevolution Guided Hybrid Spiking Neural Network Training
por: Lu, Sen, et al.
Publicado: (2022)

Voltage slope guided learning in spiking neural networks
por: Hu, Lvhui, et al.
Publicado: (2022)

Representation learning in the artificial and biological neural networks underlying sensorimotor integration
por: Suhaimi, Ahmad, et al.
Publicado: (2022)

Physical principles for scalable neural recording
por: Marblestone, Adam H., et al.
Publicado: (2013)

Remembrance of things perceived: Adding thalamocortical function to artificial neural networks
por: Loeb, Gerald E.
Publicado: (2023)

The Problem of Meaning: The Free Energy Principle and Artificial Agency
por: Kiverstein, Julian, et al.
Publicado: (2022)

Generative network modeling reveals quantitative definitions of bilateral symmetry exhibited by a whole insect brain connectome
por: Pedigo, Benjamin D, et al.
Publicado: (2023)

Cannot write session to /tmp/vufind_sessions/sess_c45jt9t2d80eu79dja571mrjsj