Research Topic

Aspects of computational approaches in neurophysiological data processing: mathematical and biomedical principles

  • Submission closed.

About this Research Topic

Despite a continuous effort in neurophysiological research during last decades, the understanding of mechanisms regulating vital functions is still rather deficient. Investigating the regulation of physiological processes has become a fully multidisciplinary task, highly dependent on the usage of principles ...

Despite a continuous effort in neurophysiological research during last decades, the understanding of mechanisms regulating vital functions is still rather deficient. Investigating the regulation of physiological processes has become a fully multidisciplinary task, highly dependent on the usage of principles from mathematics, physics and computer science in many aspects of view.
Due to changing degrees of neurophysiological data stationarity, the wavelet transformation is often performed in imaging or time-frequency analysis. This multiresolution decomposition results in a biosignal interpretation both in time and frequency domains. Therefore, it is continuously adapted to the analyzed signal properties, and an optimal time–frequency resolution may be reached. Wavelet analysis demonstrated attenuation of high frequency components characterized by great oxygen demands in phrenic neurogram of newborn mammals and even during some specific defence reflex behavior, suggesting dominance of the basic respiratory rhythm generator in hypoxia/hypercapnia conditions.
Beside time - frequency energy distribution, qualitative changes of the neurophysiological data could be demonstrated through nonlinear methods of analysis. Methods of nonlinear dynamics are based on finding that random behavior can arise in deterministic nonlinear systems with a few degrees of freedom. Many related parameters reflect system evolution in time and, subsequently, reflect level of new signal pattern generation. They are often understood as a rate of the system complexity. Particular parameters related to level of signal entropy can describe dynamical behavior associated with different neurogram stages. Decreasing of the entropy value detected in electroneurogram or electromyogram during defence reflex behavior is reflecting low probability of system disorder. Thus, different entropy measures show synchroncity of neural firing, level of diffusion energy over neurons or a degree of synaptic activity.
In this research topic, innovative approaches in neurophysiological data modeling will be introduced, and we welcome contributions ranging from original research reports, reviews, technical or methodology articles. The topic will introduce novel biomedical, physical or computational principles in understanding the complex processes of neurophysiological regulations, including, but not limited to, time – frequency analysis, fuzzy logic, brain mapping, artificial neuronal networks or nonlinear dynamics and the chaos theory.


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.

Recent Articles

Loading..

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

Submission closed.

Participating Journals

Loading..

Topic Editors

Loading..

Submission Deadlines

Submission closed.

Participating Journals

Loading..
Loading..

total views article views article downloads topic views

}
 
Top countries
Top referring sites
Loading..

Comments

Loading..

Add a comment

Add comment
Back to top