Characterization of spatiotemporal dynamics in EEG data during picture naming with optical flow patterns
Volpert, V.; Xu, B.; Tchechmedjiev, A.; Harispe, S.; Aksenov, A.; Mesnildrey, Q.; Beuter, A.
Show abstract
We present an analysis of the spatiotemporal dynamics of the oscillations in the electric potential that arises from neural activity. Depending on the frequency and phase of oscillations, these dynamics can be characterized as standing waves or as out-of-phase and modulated waves, which represent a combination of standing and moving waves. We characterize these dynamics as optical flow patterns, in terms of sources, sinks, spirals and saddles. Analytical and numerical solutions are compared with real EEG data acquired during a picture-naming task. Analytical approximation of standing waves allows us to establish some properties of pattern location and number. Namely, sources and sinks have mainly the same location, while saddles are located between them. The number of saddles correlates with the sum of all the other patterns. These properties are confirmed in both the simulated and real EEG data.
Matching journals
The top 5 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Is sensor space analysis good enough? Spatial patterns as a tool for assessing spatial mixing of EEG/MEG rhythms 97%
- Harmoni: a Method for Eliminating Spurious Interactions due to the Harmonic Components in Neuronal Data 96%
- Pumping Up your Predictive Power for Cognitive State Detection with the Proper GAINS 96%
Similar papers in this journal
- Alpha blocking and 1/fβ spectral scaling in resting EEG can be accounted for by a sum of damped alpha band oscillatory processes 97%
- Evidence for spreading seizure as a cause of theta-alpha activity electrographic pattern in stereo-EEG seizure recordings 96%
- The visual cortex produces gamma band echo in response to broadband visual flicker 96%
Similar papers in this journal
- Estimating Multiple Latencies in the Auditory System from Auditory Steady-State Responses on a Single EEG Channel 95%
- Automated methodology for optimal selection of the minimum electrode subset for accurate EEG source estimation based on Genetic Algorithm optimization 95%
- State Space Methods for Phase Amplitude Coupling Analysis 94%
Similar papers in this journal
- Computational modelling of the long-term effects of brain stimulation on the local and global structural connectivity of epileptic patients 95%
- Steady state evoked potential (SSEP) responses in the primary and secondary somatosensory cortices of anesthetized cats: nonlinearity characterized by harmonic and intermodulation frequencies 95%
- Velocities of Hippocampal Traveling Waves Proportional to Their Coherence Frequency 95%
Similar papers in this journal
- Qualitative and Quantitative Comparative Analysis of Common Normal Variants and Physiological Artifacts in MEG and EEG 94%
- Exploring Frequency-dependent Brain Networks from ongoing EEG using Spatial ICA during music listening 94%
- Modeling the hemodynamic response function using EEG-fMRI data during eyes-open resting-state conditions and motor task execution 94%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.