Biology subjects

Pisarchik, A. N.

Publications and source records attributed to Pisarchik, A. N..

3 recordsLinked to original sources

bioRxiv2020

Neuronal adaptation during the prolonged cognitive task improves visual stimulus processing

Brain optimally utilizes resources to resist mental fatigue during the prolonged period of cognitive activity. Neural mechanisms underlying long-term cognitive performance remain unknown. We show that during the 40-minutes visual stimuli classification task, subjects improve behavioral performance in terms of response time and correctness. We observe that the prestimulus{theta} and power grows during the experiment manifesting the mental fatigue. The prestimulus {beta} power, in its turn, increases locally in the region, engaged in the ongoing stimulus processing, that may reflect the neuronal adaptation. Our results evidence that the neuronal adaptation is enhanced in the course of the experiment reducing the cognitive demands required to activate the stimulus-related brain regions.

neuroscience↗

bioRxiv2020

Estimating voluntary and involuntary attention in bistable visual perception: A MEG study

We introduce a method for measuring human attention when performing a visual task consisting in different interpretations of a bistable image. The Necker cube with flickering faces was presented to nine conditionally healthy volunteers. The pixels intensity in the front and rear cube faces were modulated by a sinusoidal signal with 6.67-Hz (60/9) and 8.57-Hz (60/7) frequencies, respectively. The tags of these frequencies and their second harmonics were clearly identified in the average Fourier spectra of the magnetoencephalographic (MEG) data recorded from the occipital cortex. In the first part of the experiment, the subjects were asked to voluntary control their attention by interpreting the cube orientation as either left- or right-orientated. Accordingly, we observed the dominance of the corresponding spectral component and voluntary attention performance was measured. In the second part of the experiment, the subjects were just asked to observe the cube image without any effort in its interpretation. The alternation of the dominant spectral energies at the second harmonic tag frequencies was treated as changes in the cube orientation. Based on the results of the first experimental stage and using wavelet analysis, we developed a novel method which allowed us to identify currently perceived cube orientations. Finally, we characterized involuntary attention using the dominance time distribution and related it to voluntary attention performance and brain noise. In particular, we have shown that higher attention performance is associated with stronger brain noise.

neuroscience↗

bioRxiv2018

Human personality reflects spatio-temporal and time-frequency EEG structure

The brain controls all physiological processes in the organism and regulates its interaction with the external environment. The way the brain solves mental tasks is determined by individual human features, which are reflected in neuronal network dynamics, and therefore can be detected in neurophysiological data. Every human action is associated with a unique brain activity (motor-related, cognitive, etc.) represented by a specific oscillatory pattern in a multichannel electroencephalogram (EEG). The connection between neurophysiological processes and personal mental characteristics is manifested when using simple psycho-diagnostic tests (Schulte tables) in order to study the attention span. The analysis of spatio-temporal and time-frequency structures of the multichannel EEG using the Schulte tables allows us to divide subjects into three groups depending on their neural activity. The personality multi-factor profile of every participant can be individually described based on both the Sixteen Personality Factor Questionnaire (16PF) and a personal interview with an experienced psychologist. The correlation of the EEG-based personality classification with individual multi-factor profiles provides a possibility to identify human personality by analyzing electrical brain activity. The obtained results are of great interest for testing human personality and creating automatized intelligent programs that employ simple tests and EEG measurements for an objective estimation of human personality features.

neuroscience↗