This work presents results of test series, performed for earlier on designed and successfully fabricated twisted silica fewmode microstructured optical fibers (MOF) with six GeO2-doped cores. While Part I introduces results of differential mode delay map measurements, Part II is focused on researches of spectral responses, measured for fiber Bragg gratings, recorded in these multi-core MOFs with core graded refractive index profiles and induced twisting 100 revolutions per meter. Specially setup for spectral response measurement for described complicated fiber optic element was developed, that provides selected alignment of matching singlemode optical fiber with particular single core of MOF via free space and reducing of reflection by precision 8 angle cleaving. Comparing analysis of measured spectral responses confirmed written FBGs in 2 of 6 cores, and demonstrated potentiality of fabricated complicated structure, containing multi-core MOF with FBG, for applications in multichannel fiber optic sensors with spatial division multiplexing technique.
In this paper, we investigated the fatigue-related processes of reconfiguring the human brain functional network while solving the cognitive task. We analyzed the correlations between the psychophysiological state of the subject with the characteristics of neural activity. We found that the subject’s fatigue positively correlates with the average degree of functional connectivities between neural ensembles in the beta and alpha frequency ranges. The obtained results indicate the increase in the integrative processes of a functional neural network. We revealed that the increasing fatigue during the experiment does not decrease the efficiency of the task completion: the speed and correctness of responses do not change. This suggests that functional integration may reflect the optimization of the brain’s neural network during the experiment.
When creating motor imagery brain-computer interfaces (BCI), there is a problem with the accuracy of determining which limb made the movement. The accuracy of the classifiers is no more than 80-85%. In this work, we examined this problem from the point of view of the well-known phenomenon of lateralization during motor movements. Several different algrorithms were used to investigate proportion of contralateralization and ipsilateralization based on event related desynchronization/synchronization (ERD/ERS) calculations using EEG data gathered throughout motor function related experiment.
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