Cargando…

A numerical renormalisation group method for the analysis of critical spreading activity in spiking neural networks

Detalles Bibliográficos
Autores principales:	Corcoran, Thomas Greg, Phillipedes, Andrew, Nowotny, Thomas
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	BioMed Central 2013
Materias:	Poster Presentation
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3704573/ http://dx.doi.org/10.1186/1471-2202-14-S1-P297

Ejemplares similares

Coarse-grained statistics for attributing criticality to heterogeneous neural networks
por: Corcoran, Thomas Gregory, et al.
Publicado: (2011)

Estimating numerical error in neural network simulations on Graphics Processing Units
por: Turner, James P, et al.
Publicado: (2015)

Spiking neural network model of reinforcement learning in the honeybee implemented on the GPU
por: Yavuz, Esin, et al.
Publicado: (2015)

Neural spike prediction based on spreading activation
por: Zhang, Tielin, et al.
Publicado: (2014)

Subleading critical exponents from the renormalisation group
por: Litim, Daniel F., et al.
Publicado: (2003)

Introduction to a renormalisation group method
por: Bauerschmidt, Roland, et al.
Publicado: (2019)

Universality and the Renormalisation Group
por: Litim, Daniel F.
Publicado: (2005)

Critical exponents from optimised renormalisation group flows
por: Litim, Daniel F
Publicado: (2002)

Classification of multivariate data with a spiking neural network on neuromorphic hardware
por: Schmuker, Michael, et al.
Publicado: (2013)

Infrared QCD and the Renormalisation Group
por: Litim, Daniel F., et al.
Publicado: (2004)

Optimised Renormalisation Group Flows
por: Litim, Daniel F
Publicado: (2001)

Convergence and stability of the renormalisation group
por: Litim, Daniel F.
Publicado: (2002)

Covariant derivatives and the renormalisation group equation
por: Dolan, B P
Publicado: (1995)

On the covariant gauge parameter and the renormalisation group
por: Miller, R D C
Publicado: (1982)

Completeness and consistency of renormalisation group flows
por: Litim, Daniel F., et al.
Publicado: (2002)

Perturbation theory and renormalisation group equations
por: Litim, Daniel F., et al.
Publicado: (2001)

Derivative expansion and renormalisation group flows
por: Litim, Daniel F
Publicado: (2001)

Uncomputably complex renormalisation group flows
por: Watson, James D., et al.
Publicado: (2022)

Cross-modular processing in a spiking neural network model
por: Vieira, Diogo PC, et al.
Publicado: (2011)

Spiking neural network model of cortical auditory source segregation
por: Krishnan, Lakshmi, et al.
Publicado: (2014)

Determinants of associative memory performance in spiking and non-spiking neural networks with different synaptic plasticity regimes
por: Metaxas, Alex, et al.
Publicado: (2012)

Simulating spiking neural networks on massively parallel graphical processing units using a code generation approach with GeNN
por: Yavuz, Esin, et al.
Publicado: (2014)

Spiking neural network model of free-energy-based reinforcement learning
por: Nakano, Takashi, et al.
Publicado: (2011)

Assessing time-varying causality network of ensemble neural spiking activity
por: Kim, Sanggyun, et al.
Publicado: (2011)

Local unsupervised learning rules for a spiking neural network with dendrite
por: Manette, Olivier FL
Publicado: (2011)

CPU-GPU hybrid platform for efficient spiking neural-network simulation
por: Naveros, Francisco, et al.
Publicado: (2013)

Animal control by spiking neural networks evolved with a genetic algorithm
por: Wróbel, Borys, et al.
Publicado: (2015)

Modulation of a decision-making process by spatiotemporal spike patterns decoding: evidence from spike-train metrics analysis and spiking neural network modeling
por: Logiaco, Laureline, et al.
Publicado: (2013)

Role of STDP and heterogeneity in the emergence of long-range temporal correlations and frequency scaling in networks of LIF neurons
por: Corcoran, Thomas ‘Greg’, et al.
Publicado: (2010)

The c and a-theorems and the Local Renormalisation Group
por: Shore, Graham M
Publicado: (2016)

Renormalisation group aspects of $\eta$' --> $\gamma\gamma$
por: Shore, Graham M, et al.
Publicado: (1992)

From evolving artificial gene regulatory networks to evolving spiking neural networks for pattern recognition
por: Abdelmotaleb, Ahmed, et al.
Publicado: (2013)

Temporal sequence learning via adaptation in biologically plausible spiking neural networks
por: Duarte, Renato, et al.
Publicado: (2014)

Single and multiple-spikes traveling wave solutions in integrate and fire neural networks
por: Oşan, Remus
Publicado: (2007)

Emergent functional neural networks organized by spike timing dependent synaptic plasticity
por: Shin, Chang-Woo, et al.
Publicado: (2007)

ROS-MUSIC toolchain for spiking neural network simulations in a robotic environment
por: Weidel, Philipp, et al.
Publicado: (2015)

Flexible neuronal network simulation framework using code generation for NVidia(®) CUDA™
por: Nowotny, Thomas
Publicado: (2011)

Fluctuation scaling in neural spike trains
por: Koyama, Shinsuke
Publicado: (2014)

Spike history model for neural control
por: Kameneva, T, et al.
Publicado: (2014)

Self-organized criticality in structured neural networks
por: Uhlig, Maximilian, et al.
Publicado: (2013)

Cannot write session to /tmp/vufind_sessions/sess_aoc07ngq0mg3emor3324v6aa3a