Potential flow of frontal midline theta activity during a mental task in the human electroencephalogram

The movement of potential field (potential flow) of frontal midline theta activity (Fm theta) as well as its potential distribution was examined in 7 subjects by using optical flow detection techniques in image processing. Electroencephalograms (EEGs) over the fronto-central region were recorded from 13 electrodes near the frontal midline (Fz) while the subjects were performing a mental task. The potential flow of Fm theta was estimated on a frame consisting of a square grid with Fz at its center. In regions anterior to Fz, the direction of potential flow was from lateral to medial, whereas it was from medial to lateral in regions posterior to Fz. The peak-to-trough amplitude distribution was round or oval with a maximum just anterior to Fz. The source density distribution showed the greatest potential along the midline in the frontal region and bilaterally symmetric smaller maximum areas mostly in the prefrontal regions. Our findings suggested the presence of 2 different source areas of opposite direction in each hemisphere in spite of a round or oval amplitude distribution.

[1]  Masahiko Yachida.  Determining velocity maps by spatio-temporal neighborhoods from image sequences , 1983, Comput. Vis. Graph. Image Process..

[2]  P. Rappelsberger,et al.  On the search for the sources of the electroencephalogram , 1984, Neuroscience.

[3]  Wilfried Enkelmann,et al.  Investigations of multigrid algorithms for the estimation of optical flow fields in image sequences , 1988, Comput. Vis. Graph. Image Process..

[4]  Gilad Adiv,et al.  Determining Three-Dimensional Motion and Structure from Optical Flow Generated by Several Moving Objects , 1985, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[5]  D Lehmann,et al.  EEG alpha map series: brain micro-states by space-oriented adaptive segmentation. , 1987, Electroencephalography and clinical neurophysiology.

[6]  Kazuhiro Shinosaki,et al.  EEG Characteristics of Frontal Midline Theta Activity , 1988 .

[7]  Hans-Hellmut Nagel,et al.  An Investigation of Smoothness Constraints for the Estimation of Displacement Vector Fields from Image Sequences , 1983, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[8]  T. Ishihara,et al.  Multivariate analytic study of EEG and mental activity in juvenile delinquents. , 1972, Electroencephalography and clinical neurophysiology.

[9]  Berthold K. P. Horn,et al.  Determining Optical Flow , 1981, Other Conferences.

[10]  M. Scherg,et al.  Two bilateral sources of the late AEP as identified by a spatio-temporal dipole model. , 1985, Electroencephalography and clinical neurophysiology.

[11]  Joseph K. Kearney,et al.  Optical Flow Estimation: An Error Analysis of Gradient-Based Methods with Local Optimization , 1987, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[12]  B. Hjorth.  An on-line transformation of EEG scalp potentials into orthogonal source derivations. , 1975, Electroencephalography and clinical neurophysiology.