Research Topic

Stochastic nonlinear dynamics of collective neural activity in cortex and hippocampus

About this Research Topic

Collective neural activity (CA) is defined as emergent behavior of large populations of neurons, distinct from that of cell individuals, in that it characterizes the entire population and ignores the details of the dynamics of cell individuals, such as the exact form of the action potential. The spatiotemporal scales of CA are in the mesoscale range (e.g., 0.1 to 10 mm spatial scale and, 5 - 500 ms temporal scale), much larger than the cell scale, and much slower than single action potentials. In the mesoscale range, CA manifests as local field potential oscillations and propagating waves. Because cell individuality is microscopic and largely irrelevant at mesoscopic scales, it is natural to describe CA dynamics in the framework of statistical physics, or its thermodynamics/hydrodynamic limits, where the neural network is represented as a continuum (field). CA dynamics are fundamentally stochastic and nonlinear, which suggests that much discussed features of macroscopic measurements, such as the power-law shape of local field potentials (LFP) spectra, or the coupling of large and small-scale patterns (e.g., gamma/theta, sharp-waves/ripples, slow wave/spindles) may originate in the (macroscopic) field properties of CA dynamics, regardless of the microscopic details of the neural network.

This Research Topic aims to collect quantitative research relevant for understanding the nonlinear, stochastic nature of CA, regarded as a stochastic process. Such research may include experimental, theoretical, and/or numerical investigations on any and all physical and dynamical aspects of CA dynamics. However, we do not seek philosophical essays on the role of CA in cognition, or research using the "microcircuit" (microscopic) description of brain activity.

In an effort to encourage quantitative studies of nonlinear stochastic CA dynamics, we would like to receive contributions that represent original research or relevant reviews of the state of science. As a cross-disciplinary topic, we welcome general review of dynamical, kinetic, thermodynamic/hydrodynamic approximations of large physical systems, as well as pattern formation, wave turbulence and energy cascade, with application to CA dynamics. Original, quantitative research into CA dynamics is warmly welcome, whether experimental, numerical, and theoretical. Experimental research topic may include: methods of detection of collective activity in vivo; measurements of parameters relevant for CA, etc. Theoretical and numerical research that uses the macroscopic description: statistical, as well as thermodynamic, and hydrodynamic approximations of CA. Research consistent with the mesoscopic descriptions are welcome.


Keywords: collective neural activity, stochastic nonlinear dynamics, cortex, hippocampus, systems


Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

Collective neural activity (CA) is defined as emergent behavior of large populations of neurons, distinct from that of cell individuals, in that it characterizes the entire population and ignores the details of the dynamics of cell individuals, such as the exact form of the action potential. The spatiotemporal scales of CA are in the mesoscale range (e.g., 0.1 to 10 mm spatial scale and, 5 - 500 ms temporal scale), much larger than the cell scale, and much slower than single action potentials. In the mesoscale range, CA manifests as local field potential oscillations and propagating waves. Because cell individuality is microscopic and largely irrelevant at mesoscopic scales, it is natural to describe CA dynamics in the framework of statistical physics, or its thermodynamics/hydrodynamic limits, where the neural network is represented as a continuum (field). CA dynamics are fundamentally stochastic and nonlinear, which suggests that much discussed features of macroscopic measurements, such as the power-law shape of local field potentials (LFP) spectra, or the coupling of large and small-scale patterns (e.g., gamma/theta, sharp-waves/ripples, slow wave/spindles) may originate in the (macroscopic) field properties of CA dynamics, regardless of the microscopic details of the neural network.

This Research Topic aims to collect quantitative research relevant for understanding the nonlinear, stochastic nature of CA, regarded as a stochastic process. Such research may include experimental, theoretical, and/or numerical investigations on any and all physical and dynamical aspects of CA dynamics. However, we do not seek philosophical essays on the role of CA in cognition, or research using the "microcircuit" (microscopic) description of brain activity.

In an effort to encourage quantitative studies of nonlinear stochastic CA dynamics, we would like to receive contributions that represent original research or relevant reviews of the state of science. As a cross-disciplinary topic, we welcome general review of dynamical, kinetic, thermodynamic/hydrodynamic approximations of large physical systems, as well as pattern formation, wave turbulence and energy cascade, with application to CA dynamics. Original, quantitative research into CA dynamics is warmly welcome, whether experimental, numerical, and theoretical. Experimental research topic may include: methods of detection of collective activity in vivo; measurements of parameters relevant for CA, etc. Theoretical and numerical research that uses the macroscopic description: statistical, as well as thermodynamic, and hydrodynamic approximations of CA. Research consistent with the mesoscopic descriptions are welcome.


Keywords: collective neural activity, stochastic nonlinear dynamics, cortex, hippocampus, systems


Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

About Frontiers Research Topics

With their unique mixes of varied contributions from Original Research to Review Articles, Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area! Find out more on how to host your own Frontiers Research Topic or contribute to one as an author.

Topic Editors

Loading..

Submission Deadlines

16 January 2022 Abstract
14 March 2022 Manuscript

Participating Journals

Manuscripts can be submitted to this Research Topic via the following journals:

Loading..

Topic Editors

Loading..

Submission Deadlines

16 January 2022 Abstract
14 March 2022 Manuscript

Participating Journals

Manuscripts can be submitted to this Research Topic via the following journals:

Loading..
Loading..

total views article views article downloads topic views

}
 
Top countries
Top referring sites
Loading..