Similar network activity from disparate circuit parameters

By Astrid A. Prinz, Dirk M. Bucher, Eve Marder. Nature Neuroscience, 2004

1,098 citations recorded by the source corpus.

Subfields: Cellular and Molecular Neuroscience, Cognitive Neuroscience, Ecology

View Paper: https://www.semanticscholar.org/paper/321b63446acb8397d7b445e2675d757f12ffd0bb

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Citations in the corpus

Variability, compensation and homeostasis in neuron and network function (2006, result): “The two- to fourfold ranges of conductance densities we have previously discussed are larger than most of us would have expected, but they also represent a smaller region of parameter space than can be found in neuronal models with similar activit”
Cell Types, Network Homeostasis, and Pathological Compensation from a Biologically Plausible Ion Channel Expression Model. (2015, neutral): “When systematically searched, the parameter space that produces a triphasic CPG in a similar model is found to be complex (Prinz et al., 2004).”
Looking for inspiration: new perspectives on respiratory rhythm (2006, background): “Distinct respiratory oscillators The nervous system could ensure that breathing remains robust and reliable by various means including multiple oscillator sites and multiple mechanisms for oscillatio”
Brian 2: an intuitive and efficient neural simulator (2019, methodology): “Case study: a model of the pyloric network of the crustacean stomatogastric ganglion, inspired by several modeling papers on this subject (Golowasch et al., 1999; Prinz et al., 2004; Prinz, 2006; O’Leary et al., 2014) (a) Schematic of the modeled circuit (after Prinz et al., 2004).”
A theory for how sensorimotor skills are learned and retained in noisy and nonstationary neural circuits (2013, background): “This point has been explicitly made for the crustacean pyloric circuit (16).”
Cell Types, Network Homeostasis, and Pathological Compensation from a Biologically Plausible Ion Channel Expression Model (2014, positive): “…states of ion channels–can be wildly disparate and nevertheless give rise to highly specific physiological properties that are essential for a functioning nervous system (Bhalla and Bower 1993; Golowasch et al., 2002; Marder and Goaillard 2006; Prinz et al., 2003, 2004; Taylor et al., 2009).”
Homeostatic control of neural activity: from phenomenology to molecular design. (2006, background): “Together, these data strongly suggest that it is not necessary to fine tune every parameter of a cell or neural network to achieve stable neural activity (Prinz et al. 2004).”
The Metastable Brain (2014, neutral): “Both the duration of transient functional groupings and the presence of escape tendencies depend entirely on the dynamical structure of the system (see also Briggman and Kristan, 2008; Prinz et al., 2004; Rabinovich et al., 2008; Cabral et al., 2011).”
Dendritic excitability and synaptic plasticity. (2008, positive): “Similarly, regulation of intrinsic excitability need not be exact, as several distinct regions of the entire possible parameter space may result in the same or similar outcome, such as demonstrated for the homeostasis of firing patterns in the crustacean stomatogastric ganglion (612).”
Multiple models to capture the variability in biological neurons and networks (2011, background): “1 ), a population of more than 20,000,000 model networks was create”
Variability, compensation, and modulation in neurons and circuits (2011, background): “The same principle holds at the level of circuit performance (8), as is shown in Fig.”