Stochastic fluctuations are intrinsic to and unavoidable at every stage of neural dynamics. Ion channels undergo random conformational changes, neurotransmitter release at synapses is discrete and probabilistic, neural networks are embedded in spontaneous background activity, to name a few.
The mathematical and computational tool sets contributing to our understanding of stochastic neural dynamics have expanded rapidly in recent years. New theories have emerged detailing the dynamics and computational power of the balanced state in recurrent networks. At the cellular level, novel stochastic extensions to the classical Hodgkin-Huxley model have enlarged our understanding of neuronal dynamics and action potential initiation. Analytical methods have been developed that allow for the calculation of the firing statistics of simplified phenomenological integrate-and-fire models, taking into account adaptation currents or temporal correlations of the noise.
This Research Topic calls for papers that are focused on identified physiological/internal noise sources and mechanisms, where the meaning of "internal" can vary in scale from ion channel to synapse to neuron to network, and so forth, provided it is generated by intrinsic biophysical processes.
We encourage submissions that bridge noise sources across scales. For instance, how do synaptic and membrane noise sources filter through and reverberate in small networks? It is also timely to consider noise and variability from sources that have received relatively little attention. What are the effects of cell-type heterogeneity or membrane inhomogeneity? How do extracellular electrical interactions (ephaptic communication) and neurotransmitter diffusion in the synaptic cleft influence dynamics and computation?
Ideal contributions will introduce innovative mathematical analysis and/or computational methods that relate to empirical measures of neural activity and illuminate the functional role of intrinsic noise in the brain.
The following are OUT OF SCOPE for this Research Topic:
1. papers that do not make an informed attempt to state a neurophysiologically relevant intrinsic noise model as a starting point;
2. papers focused on non-invasive variability such as measured by EEG and fMRI;
3. papers on the impact of extrinsic noise that is artificially introduced into biological sensory systems, such as through injected currents;
4. papers concerned with artificial neural network algorithms/theory that lack a neurobiological foundation.
Stochastic fluctuations are intrinsic to and unavoidable at every stage of neural dynamics. Ion channels undergo random conformational changes, neurotransmitter release at synapses is discrete and probabilistic, neural networks are embedded in spontaneous background activity, to name a few.
The mathematical and computational tool sets contributing to our understanding of stochastic neural dynamics have expanded rapidly in recent years. New theories have emerged detailing the dynamics and computational power of the balanced state in recurrent networks. At the cellular level, novel stochastic extensions to the classical Hodgkin-Huxley model have enlarged our understanding of neuronal dynamics and action potential initiation. Analytical methods have been developed that allow for the calculation of the firing statistics of simplified phenomenological integrate-and-fire models, taking into account adaptation currents or temporal correlations of the noise.
This Research Topic calls for papers that are focused on identified physiological/internal noise sources and mechanisms, where the meaning of "internal" can vary in scale from ion channel to synapse to neuron to network, and so forth, provided it is generated by intrinsic biophysical processes.
We encourage submissions that bridge noise sources across scales. For instance, how do synaptic and membrane noise sources filter through and reverberate in small networks? It is also timely to consider noise and variability from sources that have received relatively little attention. What are the effects of cell-type heterogeneity or membrane inhomogeneity? How do extracellular electrical interactions (ephaptic communication) and neurotransmitter diffusion in the synaptic cleft influence dynamics and computation?
Ideal contributions will introduce innovative mathematical analysis and/or computational methods that relate to empirical measures of neural activity and illuminate the functional role of intrinsic noise in the brain.
The following are OUT OF SCOPE for this Research Topic:
1. papers that do not make an informed attempt to state a neurophysiologically relevant intrinsic noise model as a starting point;
2. papers focused on non-invasive variability such as measured by EEG and fMRI;
3. papers on the impact of extrinsic noise that is artificially introduced into biological sensory systems, such as through injected currents;
4. papers concerned with artificial neural network algorithms/theory that lack a neurobiological foundation.
