Special Issue "Entropy in Human Brain Networks"
Deadline for manuscript submissions: closed (31 July 2015)
Prof. Dr. Wassim M. Haddad (Website)
School of Aerospace Engineering, Georgia Institute of Technology, Atlanta, GA, USA
Interests: nonlinear systems; large-scale systems; hierarchical control; robust and adaptive control; impulsive and hybrid systems; system thermodynamics; network systems; system biology, clinical pharmacology; and mathematical neuroscience
An important area of science where a dynamical system framework of thermodynamics can prove invaluable is in neuroscience. Advances in neuroscience have been closely linked to mathematical modeling beginning with the integrate-and-fire model of Lapicque and proceeding through the modeling of the action potential by Hodgkin and Huxley to the current era of mathematical neuroscience. Neuroscience has always had models to interpret experimental results from a high-level complex systems perspective; however, expressing these models with dynamic equations rather than words fosters precision, completeness, and self-consistency. Nonlinear dynamical system theory, and in particular system thermodynamics, is ideally suited for rigorously describing the behavior of large-scale networks of neurons.
Merging the two universalisms of thermodynamics and dynamical systems theory with neuroscience can provide the theoretical foundation for understanding the network properties of the brain by rigorously addressing large-scale interconnected biological neuronal network models that govern the neuroelectronic behavior of biological excitatory and inhibitory neuronal networks. As in thermodynamics, neuroscience is a theory of large-scale systems wherein graph theory can be a very useful tool in capturing the connectivity properties of system interconnections, with neurons represented by nodes, synapses represented by edges or arcs, and synaptic efficacy captured by edge weighting giving rise to a weighted adjacency matrix governing the underlying directed graph network topology. However, unlike thermodynamics, wherein energy spontaneously flows from a state of higher temperature to a state of lower temperature, neuron membrane potential variations occur due to ion species exchanges which evolve from regions of higher concentrations to regions of lower concentrations. And this evolution does not occur spontaneously but rather requires the opening and closing of specific gates within specific ion channels. The purpose of this special issue is to use a dynamical systems framework merged with thermodynamic state notions (i.e., entropy, energy, free energy, chemical potential, etc.) to provide a fundamental understanding of the networks properties of the brain.
Prof. Dr. Wassim M. Haddad
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. Papers will be published continuously (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are refereed through a peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Entropy is an international peer-reviewed Open Access monthly journal published by MDPI.
- biological neural networks
- spiking and firing rate models
- dissipative nonlinear dynamical systems
- fractal variability and chaos
- interacting solitons
- theorems addressing stability in nonlinear networks
- cyclo-dissipative systems
- computational neuroscience
- spatio-temporal networks
- bistability and Multistability theory
- mathematical neuroscience
- network systems
- cellular control systems
- uncertain dynamical networks
- complex dynamical systems
- stochastic networks and ergodic systems
- system thermodynamics
- large-scale interconnected systems
- synchronization of biological networks
- arrow of time and the conscious brain
- brain network dynamics
- cortical field theory
- neurodynamics of consciousness
- neurodynamics of attention
- cortical modeling
- neural coding
- theoretical neuroscience
- neurophysiology of consciousness
- thermodynamics of the human brain