NEUROMODULATION OF NEURONAL CIRCUITS: BACK TO THE FUTURE

By Eve Marder. 2012

887 citations recorded by the source corpus.

All nervous systems are subject to neuromodulation. Neuromodulators can be delivered as local hormones, as cotransmitters in projection neurons, and through the general circulation. Because neuromodulators can transform the intrinsic firing properties of circuit neurons and alter effective synaptic strength, neuromodulatory substances reconfigure neuronal circuits, often massively altering their output. Thus, the anatomical connectome provides a minimal structure and the neuromodulatory environment constructs and specifies the functional circuits that give rise to behavior.

Subfields: Cellular and Molecular Neuroscience, Molecular Biology, Neurology

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Citations in the corpus

Continual learning with hypernetworks (2019, background): “For example, a hypernetwork can output lower-dimensional modulatory signals (Marder, 2012), instead of a full set of weights.”
Coordinated and Compartmentalized Neuromodulation Shapes Sensory Processing in Drosophila (2015, neutral): “Neuromodulators provide an evolutionarily conserved mechanism to generate behavioral variability (Bargmann, 2012; Marder, 2012).”
Homeostatic Activity-Dependent Tuning of Recurrent Networks for Robust Propagation of Activity (2015, background): “, and Marder, E. (2014). Cell types, network homeostasis, and pathological compensation from a biologically plausible ion channel expression model.”
Neuromodulated Spike-Timing-Dependent Plasticity, and Theory of Three-Factor Learning Rules (2016, background): “The multiple ways in which neuromodulators can interact with neural activity (Kaczmarek and Levitan, 1987; Nicola et al., 2000; Marder, 2012; Nadim and Bucher, 2014) combined with complex network structures suggest many different mechanisms of interplay between them (Marder, 2012).”
A connectome of the Drosophila central complex reveals network motifs suitable for flexible navigation and context-dependent action selection (2020, background): “…the experimental evidence summarized above, it seems likely that the CX operates as a multifunctional network that can be dynamically reconfigured (Marder, 2012) to support a variety of goal-directed behaviors based on immediate sensorimotor variables, learned associations, time of day, sleep…”
The Invariance Hypothesis Implies Domain-Specific Regions in Visual Cortex (2014, background): “Another possibility is that localization on cortex enables the use of neuromodulatory mechanisms that act on local neighborhoods of cortex to affect all the circuitry for a particular domain at once [91].”
The unreasonable effectiveness of deep learning in artificial intelligence (2020, background): “Several other neuromodulatory systems also control global brain states to guide behavior, representing negative rewards, surprise, confidence and temporal discounting (28).”
The human connectome: Origins and challenges (2013, background): “The inability of connectome maps to capture modulatory processes has been cited as a major limitation of the structural approach inherent in all of connectomics (Bargmann, 2012; Brezina, 2010; Marder, 2012).”
Evaluating Topological Models of Neuromodulation in Polyworld (2014, methodology): “In fact, a neural wiring diagram (i.e. synaptic connections between neurons) alone is insufficient to understand most natural neural circuits (Brezina, 2010; Marder, 2012).”
Plasticity of Cortical Excitatory-Inhibitory Balance (2015, background): “F or p er so na l u se o nl y. circuits, such as neuromodulatory systems that provide contextual or feedback signals (Marder 2012, Yu & Dayan 2005).”
Motor primitives in space and time via targeted gain modulation in cortical networks (2018, background): “In line with known physiological effects [6, 8, 26, 28], 135 we have shown that relatively subtle changes in neuronal excitability in cortical circuits can have 136 dramatic effects on ensuing muscular activity, suggesting the possibility that gain modulation is a 137 central part of neuronal motor ”
Robot coverage control by evolved neuromodulation (2013, background): “An extensive review of computational models of neuromodulation can be found in [15], and some recent models are reviewed in [23].”