Neural network dynamics.

By Tim P. Vogels, Kanaka Rajan, L. F. Abbott. Annual Review of Neuroscience, 2005

514 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/f95965317ff415fa830e6873eda9209c3bec5b3f

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In Cognitive Neuroscience

In Electrical and Electronic Engineering

Citations in the corpus

The criticality hypothesis: how local cortical networks might optimize information processing (2008, methodology): “Here, we will describe in more detail a critical branching process model (Harris 1989; Beggs & Plenz 2003; Haldeman & Beggs 2005; reviewed by Vogels et al. 2005), because it captures the power-law distribution of avalanche sizes and the reproducible activity sequences seen in the data.”
Rhythms of the brain (2006, background): “Von der Malsburg (1985). 15. Goldstone (1998) discusses the literature on the ability of trained observers to recognize orders of magnitude more features than untrained subjects.”
From the neuron doctrine to neural networks (2015, background): “…methods to measure multi-neuronal activity in vitro or in vivo 14,149,178–180 or to analyse and model multidimensional and dynamical activity 37,109,181 may usher in a Kuhnian ‘scientific revolution’ 36 , in which the single-neuron doctrine taught in text-books is replaced by a new neural network…”
Balanced amplification: a new mechanism of selective amplification of neural activity patterns (2009, unknown): “When neural circuits operate in a regime in which synchronization of spiking of different neurons is weak, many aspects of their behavior can be understood from simple models of neuronal firing rates (Ermentrout, 1998; Pinto et al., 1996; Brunel, 2000; Vogels et al., 2005).”
Dynamic functional connectivity: Promise, issues, and interpretations (2013, background): “Simultaneous EEG–fMRI— Scalp EEG offers a non-invasive, electrophysiological window into endogenous shifts in “brain states.””
Synaptic Plasticity in Neural Networks Needs Homeostasis with a Fast Rate Detector (2013, background): “Theoretically, the background state is currently understood as the asynchronous and irregular (AI) firing regime resulting from a dynamic balance of excitation and inhibition in recurrent neural networks [6–9].”
Dimensionality reduction for large-scale neural recordings (2014, background): “To make this concept concrete, consider a hypothetical neural circuit as a dynamical system, in the sense that the activity of its constituent neurons changes over time 30 .”
How advances in neural recording affect data analysis (2011, methodology): “As the number of simultaneously recorded neurons grows, models that have traditionally only been tested using large-scale neural simulations will be able to access large, comparable dataset”
Dynamical principles in neuroscience (2006, unknown): “These results include the description of the diversity of dynamics in single neurons and synapses Koch, 1999; Vogels et al., 2005 , the spatiotemporal cooperative dynamics of small groups of neurons with different types of connections Selverston et al., 2000; Selverston, 2005 , and the principles…”
Resting‐state networks show dynamic functional connectivity in awake humans and anesthetized macaques (2013, background): “In fact, the results from converging methods have implied that the intrinsic neural and hemodynamic fluctuations represent an essential property of normal brain functioning [for reviews see Bullock, 2003; Ringach, 2009, 2010; Sadaghiani et al., 2010; Vogels et al., 2005].”