Event-Related Coherence in Visual Cortex and Brain Noise: An MEG Study

Chholak, Parth; Kurkin, Semen A.; Hramov, Alexander E.; Pisarchik, Alexander N.

doi:10.3390/app11010375

Cited by 30 publications

(6 citation statements)

References 57 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The rest of the processing was very similar and was performed in the FieldTrip software [170]. The results from his analyses closely match the results and inferences of this study [36].…”

Section: Cortical Distribution Of Ercsupporting

confidence: 72%

“…Frequency-tagged stimuli can be used to elicit brain responses in the visual cortex at the chosen tag frequencies [182,36]. Therefore, tagging the two orientations of the Necker cube with different frequencies allowed us to monitor the attention of the subjects on the two percepts by analysing the spectral content of the brain activity in the visual cortex.…”

Section: Visual Attentionmentioning

confidence: 99%

See 1 more Smart Citation

Neuronal Mechanisms of Perception and Cognition : an anthology of abstract models and experimental deductions in prevailing neuroscience paradigms

Chholak¹

Self Cite

View full text Add to dashboard Cite

Neuronal Mechanisms of Perception and CognitionAn anthology of abstract models and experimental deductions in prevailing neuroscience paradigmsThe thesis explores neural substrates functioning as complex networks in several predominant neuroscience paradigms, including motor imagery, flickering images, picture naming, semantic anomalies, auditory oddball, and motion-onset visual evoked potentials.The corresponding experimental designs and algorithms for recording electrophysiological data, such as magnetoencephalography (MEG) and electroencephalography (EEG), obtained during experimental tasks by the subjects are presented. We use standard tools and develop new physical and mathematical methods for data analysis.Models of underlying mechanisms of perception and cognition are discussed, proposed, tested, and compared with modern approaches and our own experiments. Key models / mechanisms include neural communication during motor imagery, generalised perceptual models, coherence resonance in visual perception, and the use of a neural network for object recognition.New brain-computer interface (BCI) applications are introduced, and existing systems are improved. Key suggestions include proper signal filtering for using artificial neural networks in BCI to classify imaginary movement, model-free estimation of brain noise, efficient BCI percepttracking using wavelet transforms, measuring voluntary attention performance, and real-time monitoring of pedestrian traffic based on wireless EEG data, as well as designing a cryptosystem, whose access is only possible through cognitive activity.XII

show abstract

“…The rest of the processing was very similar and was performed in the FieldTrip software [170]. The results from his analyses closely match the results and inferences of this study [36].…”

Section: Cortical Distribution Of Ercsupporting

confidence: 72%

Section: Visual Attentionmentioning

confidence: 99%

Neuronal Mechanisms of Perception and Cognition : an anthology of abstract models and experimental deductions in prevailing neuroscience paradigms

Chholak¹

Self Cite

View full text Add to dashboard Cite

show abstract

“…In this study, we analyze the MEG data of 15 control subjects (aged 17-64 years; 10 men and 5 women) obtained in the experiment based on a flickering image paradigm [39] at the Center for Biomedical Technology of the Universidad Politécnica de Madrid, Spain. The MEG data have been downloaded from https://zenodo.org/record/4408648#.X-72UdYo-Cc (accessed on 10 August 2023).…”

Section: Subjectsmentioning

confidence: 99%

Hypergraph of Functional Connectivity Based on Event-Related Coherence: Magnetoencephalography Data Analysis

Peña Serrano,

Jaimes-Reátegui,

Pisarchik

2024

Applied Sciences

Self Cite

View full text Add to dashboard Cite

We construct hypergraphs to analyze functional brain connectivity, leveraging event-related coherence in magnetoencephalography (MEG) data during the visual perception of a flickering image. Principal network characteristics are computed for the delta, theta, alpha, beta, and gamma frequency ranges. Employing a coherence measure, a statistical estimate of correlation between signal pairs across frequencies, we generate an edge time series, depicting how an edge evolves over time. This forms the basis for constructing an edge-to-edge functional connectivity network. We emphasize hyperedges as connected components in an absolute-valued functional connectivity network. Our coherence-based hypergraph construction specifically addresses functional connectivity among four brain lobes in both hemispheres: frontal, parietal, temporal, and occipital. This approach enables a nuanced exploration of individual differences within diverse frequency bands, providing insights into the dynamic nature of brain connectivity during visual perception tasks. The results furnish compelling evidence supporting the hypothesis of cortico–cortical interactions occurring across varying scales. The derived hypergraph illustrates robust activation patterns in specific brain regions, indicative of their engagement across diverse cognitive contexts and different frequency bands. Our findings suggest potential integration or multifunctionality within the examined lobes, contributing valuable perspectives to our understanding of brain dynamics during visual perception.

show abstract

“…Even small noise can induce changes of qualitative behavior in nonlinear dynamical systems. In neurodynamics, various complex stochastic phenomena can be observed: noise-induced excitability, 16,17 stochastic and coherence resonances, 16,[18][19][20][21][22][23][24][25][26][27] noise-activated chaos-order transitions, 28 noise-induced transitions between equilibrium and oscillatory regimes, 28 and between different types of limit cycles, 29,30 and stochastic generation of quasi-periodic oscillations. 27 Interrelation of noise and cardiac EADs is less studied.…”

Section: Introductionmentioning

confidence: 99%

Stochastic generation and suppression of early afterdepolarizations in a three‐dimensional model of cardiac action potential

Slepukhina

Bashkirtseva

Kügler

et al. 2021

Math Methods in App Sciences

View full text Add to dashboard Cite

The influence of random disturbances on a three-dimensional simplification of Luo-Rudy model of the cardiac action potential is studied. We show that in the parameter region, where the deterministic model is in the equilibrium regime, noise can trigger large-amplitude oscillations that correspond with pathological early afterdepolarizations (EADs). For this stochastic excitement, the phenomenon of coherence resonance was discovered. On the contrary, in another parameter zone of the model, noise can suppress EADs. We analyze these stochastic phenomena using the stochastic sensitivity functions technique, Mahalanobis distance, the methods of principal directions, and confidence domains.

show abstract

Event-Related Coherence in Visual Cortex and Brain Noise: An MEG Study

Cited by 30 publications

References 57 publications

Neuronal Mechanisms of Perception and Cognition : an anthology of abstract models and experimental deductions in prevailing neuroscience paradigms

Neuronal Mechanisms of Perception and Cognition : an anthology of abstract models and experimental deductions in prevailing neuroscience paradigms

Hypergraph of Functional Connectivity Based on Event-Related Coherence: Magnetoencephalography Data Analysis

Stochastic generation and suppression of early afterdepolarizations in a three‐dimensional model of cardiac action potential

Contact Info

Product

Resources

About