Variability, compensation and homeostasis in neuron and network function

By Eve Marder, Jean-Marc Goaillard. 2006

1,233 citations recorded by the source corpus.

Subfields: Cellular and Molecular Neuroscience, Cognitive Neuroscience

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Citations in the corpus

Toward an Integration of Deep Learning and Neuroscience (2016, background): “…by diverse local properties of neurons and networks, such as homeostatic rules of neural structure, gene expression and function (Marder and Goaillard, 2006), the diversity of synapse types, cell-type-speciﬁc connectivity (Jiang et al., 2015), patterns of inter-laminar projection,…”
The Self-Tuning Neuron: Synaptic Scaling of Excitatory Synapses (2008, background): “Synaptic Scaling in the Visual Cortex Homeostatic plasticity appears to stabilize circuit function in vivo in a number of organisms and brain areas (Davis and Bezprozvanny, 2001; Marder and Goaillard, 2006; Turrigiano, 1999).”
Models of Metaplasticity: A Review of Concepts (2015, background): “The study of the dynamical implications of the interaction between homeostatic mechanisms and Hebbian plasticity requires the integration of experimental data in model studies (Marder and Goaillard, 2006).”
A Single-Cell Atlas of Cell Types, States, and Other Transcriptional Patterns from Nine Regions of the Adult Mouse Brain (2018, background): “An elegant body of experimental and theoretical work suggests that individual neurons can attain their type-specific electrophysiological properties by expressing unique combinations of voltage-gated ion channels (Marder and Goaillard, 2006).”
Neuronal homeostasis: time for a change? (2011, background): “Not only do these phenomena contribute to the development and ongoing function of neuronal networks, they also stand as important determinants of the nervous system’s response to physiological insult and disease (Turrigiano & Nelson, 2004; Davis, 2006; Marder & Goaillard, 2006; Turrigiano, 2007).”
Could a Neuroscientist Understand a Microprocessor? (2016, background): “Much has been written about the differences between computation in silico and computation in biological systems [18, 19]—the stochasticity, redundancy, and robustness [20] present in biological systems seems dramatically different from that of a microprocessor.”
Homeostatic Activity-Dependent Tuning of Recurrent Networks for Robust Propagation of Activity (2015, methodology): “In neural systems as diverse as the crustacean stomatogastric system and the vertebrate visual system, homeostatic mechanisms control neuronal function through the regulation of synaptic efficacy and the modulation of intrinsic ionic conductances (Pérez-Otaño and Ehlers, 2005; Davis, 2006; Marder an”
Non-Canonical Odor Coding in the Mosquito (2020, background): “If this were the case, it remains to be seen how the CO2-sensing circuitry is altered, whether it is the sensory neuron or downstream neurons involved in host-seeking, and if changes occur at the level of the receptor, synapse, or the intrinsic firing properties of the sensory neurons themselves (Ma”
Firing Rate Homeostasis in Visual Cortex of Freely Behaving Rodents (2013, background): “…and runaway synaptic potentiation during experience-dependent plasticity (Abbott and Nelson, 2000; Turrigiano and Nelson, 2004; Davis 2006; Marder and Goaillard, 2006; Pozo and Goda, 2010), but the exact form this homeostatic process takes, and the aspect of neuronal activity it…”
The action potential in mammalian central neurons (2007, background): “Already, such modelling has given insight into an important general question in systems biology — how tolerant is the overall behaviour of the system to alterations in the magnitude or properties of system elements? In the case of burst firing of a particular neuron in the crab stomatogastric gangli”
Neuroscience Needs Behavior: Correcting a Reductionist Bias. (2017, neutral): “The same behavior may result from alternative circuit configurations (Marder and Goaillard, 2006), from different circuits altogether or the same circuit may generate different behaviors (Katz, 2016) (Figures 1D and 1E).”
Cell Types, Network Homeostasis, and Pathological Compensation from a Biologically Plausible Ion Channel Expression Model (2014, neutral): “…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).”
Cell Types, Network Homeostasis, and Pathological Compensation from a Biologically Plausible Ion Channel Expression Model. (2015, neutral): “We know from realistic biophysical models that sets of conductance parameters—which, in biological terms, represent the expression levels and enzymatic states of ion channels—can bewildly disparate and nevertheless give rise to highly specific physiological properties that are essential for a functi”