Cargando…

A Spiking Neural Network Model of Rodent Head Direction Calibrated With Landmark Free Learning

Maintaining a stable estimate of head direction requires both self-motion (idiothetic) information and environmental (allothetic) anchoring. In unfamiliar or dark environments idiothetic drive can maintain a rough estimate of heading but is subject to inaccuracy, visual information is required to st...

Descripción completa

Detalles Bibliográficos
Autores principales:	Stentiford, Rachael, Knowles, Thomas C., Pearson, Martin J.
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/PMC9178238/ https://www.ncbi.nlm.nih.gov/pubmed/35692491 http://dx.doi.org/10.3389/fnbot.2022.867019

Ejemplares similares

Direct learning-based deep spiking neural networks: a review
por: Guo, Yufei, et al.
Publicado: (2023)

Age-Related Differences in Associative Learning of Landmarks and Heading Directions in a Virtual Navigation Task
por: Zhong, Jimmy Y., et al.
Publicado: (2016)

Meta-SpikePropamine: learning to learn with synaptic plasticity in spiking neural networks
por: Schmidgall, Samuel, et al.
Publicado: (2023)

Supervised Learning With First-to-Spike Decoding in Multilayer Spiking Neural Networks
por: Gardner, Brian, et al.
Publicado: (2021)

Backpropagation With Sparsity Regularization for Spiking Neural Network Learning
por: Yan, Yulong, et al.
Publicado: (2022)

Bayesian continual learning via spiking neural networks
por: Skatchkovsky, Nicolas, et al.
Publicado: (2022)

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

An On-chip Spiking Neural Network for Estimation of the Head Pose of the iCub Robot
por: Kreiser, Raphaela, et al.
Publicado: (2020)

Using Strategic Movement to Calibrate a Neural Compass: A Spiking Network for Tracking Head Direction in Rats and Robots
por: Stratton, Peter, et al.
Publicado: (2011)

Landmark-Based Updating of the Head Direction System by Retrosplenial Cortex: A Computational Model
por: Page, Hector J. I., et al.
Publicado: (2018)

Efficient parameter calibration and real-time simulation of large-scale spiking neural networks with GeNN and NEST
por: Schmitt, Felix Johannes, et al.
Publicado: (2023)

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

A Curiosity-Based Learning Method for Spiking Neural Networks
por: Shi, Mengting, et al.
Publicado: (2020)

Multisensory Concept Learning Framework Based on Spiking Neural Networks
por: Wang, Yuwei, et al.
Publicado: (2022)

Unsupervised Learning and Clustered Connectivity Enhance Reinforcement Learning in Spiking Neural Networks
por: Weidel, Philipp, et al.
Publicado: (2021)

Effects of Spike Anticipation on the Spiking Dynamics of Neural Networks
por: de Santos-Sierra, Daniel, 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)

Direct training high-performance spiking neural networks for object recognition and detection
por: Zhang, Hong, et al.
Publicado: (2023)

First Error-Based Supervised Learning Algorithm for Spiking Neural Networks
por: Luo, Xiaoling, et al.
Publicado: (2019)

Unsupervised Learning on Resistive Memory Array Based Spiking Neural Networks
por: Guo, Yilong, et al.
Publicado: (2019)

Learning Long Temporal Sequences in Spiking Networks by Multiplexing Neural Oscillations
por: Vincent-Lamarre, Philippe, et al.
Publicado: (2020)

Corrigendum: A Curiosity-Based Learning Method for Spiking Neural Networks
por: Shi, Mengting, et al.
Publicado: (2020)

A Heterogeneous Spiking Neural Network for Unsupervised Learning of Spatiotemporal Patterns
por: She, Xueyuan, et al.
Publicado: (2021)

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

Landmark-modulated directional coding in postrhinal cortex
por: LaChance, Patrick A., et al.
Publicado: (2022)

Neural Networks for Modeling Neural Spiking in S1 Cortex
por: Lucas, Alice, et al.
Publicado: (2019)

Information-Theoretic Intrinsic Plasticity for Online Unsupervised Learning in Spiking Neural Networks
por: Zhang, Wenrui, et al.
Publicado: (2019)

Training Spiking Neural Networks for Reinforcement Learning Tasks With Temporal Coding Method
por: Wu, Guanlin, et al.
Publicado: (2022)

Dynamic control of eye-head gaze shifts by a spiking neural network model of the superior colliculus
por: Alizadeh, Arezoo, et al.
Publicado: (2022)

Probabilistic Spike Propagation for Efficient Hardware Implementation of Spiking Neural Networks
por: Nallathambi, Abinand, et al.
Publicado: (2021)

Back-Propagation Learning in Deep Spike-By-Spike Networks
por: Rotermund, David, et al.
Publicado: (2019)

Plasticity in memristive devices for spiking neural networks
por: Saïghi, Sylvain, et al.
Publicado: (2015)

Implementing Signature Neural Networks with Spiking Neurons
por: Carrillo-Medina, José Luis, et al.
Publicado: (2016)

Sparse Computation in Adaptive Spiking Neural Networks
por: Zambrano, Davide, et al.
Publicado: (2019)

Quantization Framework for Fast Spiking Neural Networks
por: Li, Chen, et al.
Publicado: (2022)

Trainable quantization for Speedy Spiking Neural Networks
por: Castagnetti, Andrea, et al.
Publicado: (2023)

Recurrent Spiking Neural Network Learning Based on a Competitive Maximization of Neuronal Activity
por: Demin, Vyacheslav, et al.
Publicado: (2018)

Supervised Learning in All FeFET-Based Spiking Neural Network: Opportunities and Challenges
por: Dutta, Sourav, et al.
Publicado: (2020)

Non-linear Memristive Synaptic Dynamics for Efficient Unsupervised Learning in Spiking Neural Networks
por: Brivio, Stefano, et al.
Publicado: (2021)

Cannot write session to /tmp/vufind_sessions/sess_uqpebifcgl399oajln3d04med7