Analysis of psycho-physiological features of a subject in simple tests with the registration of electroencephalograms

In this paper we found a correlation between the characteristics of a person revealed in classical psychological testing on the basis of Schulte tables, and its neurophysiological features of the functioning of the brain obtained from the time-frequency analysis of EEG. The results obtained are interesting from the point of view of the choice of training strategies for a particular individual. We believe that the obtained results are of interest for fundamental science and applied works of psychological testing and diagnostics. The study of such forming strategies on EEG data can be automated and do not require the work of highly skilled psychologists.

[1]  A. A. Koronovskii,et al.  Wavelet bicoherence analysis as a method for investigating coherent structures in an electron beam with an overcritical current , 2002 .

[2]  Alexander E. Hramov,et al.  Time-frequency characteristics and dynamics of sleep spindles in WAG/Rij rats with absence epilepsy , 2014, Brain Research.

[3]  Naofumi Takagi,et al.  Function evaluation by table look-up and addition , 1995, Proceedings of the 12th Symposium on Computer Arithmetic.

[4]  Michael J. Schulte,et al.  The Symmetric Table Addition Method for Accurate Function Approximation , 1999, J. VLSI Signal Process..

[5]  Vladimir A. Maksimenko,et al.  Methods of automated absence seizure detection, interference by stimulation, and possibilities for prediction in genetic absence models , 2016, Journal of Neuroscience Methods.

[6]  R. Barry,et al.  A brief historical perspective on the advent of brain oscillations in the biological and psychological disciplines , 2017, Neuroscience & Biobehavioral Reviews.

[7]  Jean-Michel Muller A Few Results on Table-Based Methods , 1998, SCAN.

[8]  Alexander E. Hramov,et al.  On–off intermittency of thalamo-cortical oscillations in the electroencephalogram of rats with genetic predisposition to absence epilepsy , 2012, Brain Research.

[9]  Poh Foong Lee,et al.  Neurophysiological correlates of depressive symptoms in young adults: A quantitative EEG study , 2018, Journal of Clinical Neuroscience.

[10]  A. Walker Electroencephalography, Basic Principles, Clinical Applications and Related Fields , 1982 .

[11]  Michael J. Schulte,et al.  Approximating Elementary Functions with Symmetric Bipartite Tables , 1999, IEEE Trans. Computers.

[12]  Alexey N. Pavlov,et al.  Wavelet analysis in neurodynamics , 2012 .

[13]  Alexander E. Hramov,et al.  Sleep spindles and spike–wave discharges in EEG: Their generic features, similarities and distinctions disclosed with Fourier transform and continuous wavelet analysis , 2009, Journal of Neuroscience Methods.

[14]  Alexey N. Pavlov,et al.  Wavelets in Neuroscience , 2014, Springer Series in Synergetics.

[15]  Alexey A Koronovskii,et al.  Separation of coexisting dynamical regimes in multistate intermittency based on wavelet spectrum energies in an erbium-doped fiber laser. , 2016, Physical review. E.