Cargando…

Identifying steady state in the network dynamics of spiking neural networks

Analysis of the dynamics of complex networks can provide valuable information. For example, the dynamics can be used to characterize and differentiate between different network inputs and configurations. However, without quantitatively delineating the network's dynamic regimes, analysis of the...

Descripción completa

Detalles Bibliográficos
Autores principales:	George, Vivek Kurien, Gupta, Arkin, Silva, Gabriel A.
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Elsevier 2023
Materias:	Research Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10036509/ https://www.ncbi.nlm.nih.gov/pubmed/36967881 http://dx.doi.org/10.1016/j.heliyon.2023.e13913

Ejemplares similares

Generalizable Machine Learning in Neuroscience Using Graph Neural Networks
por: Wang, Paul Y., et al.
Publicado: (2021)

Steady state dynamics of intermediate filament networks
Publicado: (1992)

Steady-state and dynamic network modes for perceptual expectation
por: Choi, Uk-Su, et al.
Publicado: (2017)

Effects of Spike Anticipation on the Spiking Dynamics of Neural Networks
por: de Santos-Sierra, Daniel, et al.
Publicado: (2015)

Quantitative regulation of the dynamic steady state of actin networks
por: Manhart, Angelika, et al.
Publicado: (2019)

Effect of steady-state response versus excitatory/inhibitory balance on spiking synchronization in neural networks with log-normal synaptic weight distribution
por: Nobukawa, Sou, et al.
Publicado: (2021)

Dynamic Finite Size Effects in Spiking Neural Networks
por: Buice, Michael A., et al.
Publicado: (2013)

Generalized activity equations for spiking neural network dynamics
por: Buice, Michael A., et al.
Publicado: (2013)

Symmetry perception with spiking neural networks
por: George, Jonathan K., et al.
Publicado: (2021)

Dynamic neural network approach to targeted balance assessment of individuals with and without neurological disease during non-steady-state locomotion
por: Pickle, Nathaniel T., et al.
Publicado: (2019)

Quantum Transport in Networks and Photosynthetic Complexes at the Steady State
por: Manzano, Daniel
Publicado: (2013)

Spiking Neural Networks for Structural Health Monitoring
por: Joseph, George Vathakkattil, et al.
Publicado: (2022)

Unsupervised Spiking Neural Network with Dynamic Learning of Inhibitory Neurons
por: Yang, Geunbo, et al.
Publicado: (2023)

Multitask computation through dynamics in recurrent spiking neural networks
por: Pugavko, Mechislav M., et al.
Publicado: (2023)

Steady-State Analysis of Genetic Regulatory Networks Modelled by Probabilistic Boolean Networks
por: Shmulevich, Ilya, et al.
Publicado: (2003)

Recovery of Dynamics and Function in Spiking Neural Networks with Closed-Loop Control
por: Vlachos, Ioannis, et al.
Publicado: (2016)

A convolutional neural network for steady state visual evoked potential classification under ambulatory environment
por: Kwak, No-Sang, et al.
Publicado: (2017)

Scaling behaviour in steady-state contracting actomyosin networks
por: Malik-Garbi, Maya, et al.
Publicado: (2019)

Spiking neural networks for computer vision
por: Hopkins, Michael, et al.
Publicado: (2018)

Critical and steady-state characteristics of delay propagation in an airport network
por: Yao, Hong-Guang, et al.
Publicado: (2023)

Comparison of Gene Regulatory Networks via Steady-State Trajectories
por: Brun, Marcel, et al.
Publicado: (2007)

Scalable Steady State Analysis of Boolean Biological Regulatory Networks
por: Ay, Ferhat, et al.
Publicado: (2009)

Steady-State Visual Evoked Potential Classification Using Complex Valued Convolutional Neural Networks
por: Ikeda, Akira, et al.
Publicado: (2021)

A Sparse Reconstruction Approach for Identifying Gene Regulatory Networks Using Steady-State Experiment Data
por: Zhang, Wanhong, et al.
Publicado: (2015)

Integrating Non-spiking Interneurons in Spiking Neural Networks
por: Strohmer, Beck, et al.
Publicado: (2021)

SpikePropamine: Differentiable Plasticity in Spiking Neural Networks
por: Schmidgall, Samuel, et al.
Publicado: (2021)

Learning by stimulation avoidance: A principle to control spiking neural networks dynamics
por: Sinapayen, Lana, et al.
Publicado: (2017)

The geometry of robustness in spiking neural networks
por: Calaim, Nuno, et al.
Publicado: (2022)

Inferring Regulatory Networks by Combining Perturbation Screens and Steady State Gene Expression Profiles
por: Shojaie, Ali, et al.
Publicado: (2014)

Dynamics of Competition between Subnetworks of Spiking Neuronal Networks in the Balanced State
por: Lagzi, Fereshteh, et al.
Publicado: (2015)

Dynamic parallelism for synaptic updating in GPU-accelerated spiking neural network simulations
por: Kasap, Bahadir, et al.
Publicado: (2018)

SuperSpike: Supervised Learning in Multilayer Spiking Neural Networks
por: Zenke, Friedemann, et al.
Publicado: (2018)

Topological dynamics in spike-timing dependent plastic model neural networks
por: Stone, David B., et al.
Publicado: (2013)

Integration of Continuous-Time Dynamics in a Spiking Neural Network Simulator
por: Hahne, Jan, et al.
Publicado: (2017)

Statistical mechanics for metabolic networks during steady state growth
por: De Martino, Daniele, et al.
Publicado: (2018)

Neural encoding with unsupervised spiking convolutional neural network
por: Wang, Chong, et al.
Publicado: (2023)

A biomimetic neural encoder for spiking neural network
por: Subbulakshmi Radhakrishnan, Shiva, et al.
Publicado: (2021)

Anomaly Detection with Spiking Neural Networks
por: Borzyszkowski, Bartłomiej
Publicado: (2020)

Phase diagram of spiking neural networks
por: Seyed-allaei, Hamed
Publicado: (2015)

Exhaustive identification of steady state cycles in large stoichiometric networks
por: Wright, Jeremiah, et al.
Publicado: (2008)

Cannot write session to /tmp/vufind_sessions/sess_oe03l0dm6kt99kc4ncbhbh86hl