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Moiseev, A.

Publications and source records attributed to Moiseev, A..

2 recordsLinked to original sources
bioRxiv2019

Neuromagnetic activation dynamics of stimulus-locked processing during a naturalistic viewing

Naturalistic stimuli such as watching a movie while in the scanner provide an ecologically valid paradigm that has the potential of extracting valuable information on how the brain processes complex stimuli in a short period of time. Naturalistic viewing is also easier to conduct with challenging participant groups including patients and children. Given the high temporal resolution of MEG, in the present study, we demonstrate how a short movie clip can be used to map distinguishable activation dynamics underlying the processing of specific classes of visual stimuli such as face and hand manipulations, as well as auditory stimuli with words and non-words.\n\nMEG data were collected from 22 healthy volunteers (6 females, 3 left handed, mean age - 27.7 {+/-} 5.28 years) during the presentation of naturalistic audiovisual stimuli. The MEG data were split into trials with the onset of the stimuli belonging to classes of interest (words, non-words, faces, hand manipulations). Based on the components of the averaged sensor ERFs time-locked to the visual and auditory stimulus onset, four and three time-windows, respectively, were defined to explore brain activation dynamics. Pseudo-Z, defined as the ratio of the source-projected time-locked power to the projected noise power for each vertex, was computed and used as a proxy of time-locked brain activation. Statistical testing using the mean-centered Partial Least Squares analysis indicated periods where a given visual or auditory stimuli had higher activation. Based on peak pseudo-Z differences between the visual conditions, time-frequency resolved analyses were carried to assess beta band desynchronization in motor-related areas, and inter-trial phase synchronization between face processing areas. Our results provide the first evidence that activation dynamics in canonical brain regions associated with the processing of particular classes of visual and auditory stimuli (words, faces, etc.) can be reliably mapped using MEG during presentation of naturalistic stimuli. Given the strength of MEG for brain mapping in temporal and frequency domains, the use of naturalistic stimuli may open new techniques in analyzing brain dynamics during ecologically valid sensation and perception.\n\nHighlightsO_LIA time-locking analysis was employed in naturalistic stimuli paradigm.\nC_LIO_LISpecific visual and auditory stimuli from the movie were mapped in brain space.\nC_LIO_LIMotor {beta}-suppression was evident in periods of watching hand manipulation.\nC_LIO_LIIncreased synchronization between core face-processing areas was found around 200 and 300ms in the face condition.\nC_LIO_LINaturalistic viewing paradigms provide a reliable approach for investigating brain dynamics.\nC_LI

neuroscience↗
bioRxiv2019

Multiple constrained minimum variance beamformer (MCMV) performance in connectivity analyses

Functional brain connectivity is increasingly being seen as critical for cognition, perception and motor control.Magnetoencephalography and electroencephalography are modalities that offer noninvasive mapping of electrophysiological interactions among brain regions, yet suffer from signal leakage and signal cancellation when estimating brain activity. This leads to biased connectivity values which complicate interpretation. In this study, we test the hypothesis that a Multiple Constrained Minimum Variance beamformer (MCMV) outperforms the more traditional Linearly Constrained Minimum Variance beamformer (LCMV) for estimation of electrophysiological connectivity. To this end, MCMV and LCMV performance is compared in task related analyses with both simulated data and human MEG recordings of visual steady state signals, and in resting state analyses with simulated data and human MEG data of 89 subjects. In task related scenarios connectivity was estimated using coherence and phase locking values, whereas envelope correlations were used for the resting state data. We also introduce a novel Augmented Pairwise MCMV (APW-MCMV) approach for signal leakage suppression in resting state analyses and assess its performance against LCMV and more conventional MCMV approaches. We demonstrate that with MCMV effects of signal mixing and coherent source cancellation are greatly reduced in both task related and resting state conditions, while in contrast to other approaches 0-and short time lag interactions are preserved. In addition, we demonstrate that in resting state analyses, APW-MCMV strongly reduces spurious connections while better controlling for false negatives compared to more conservative measures such as symmetrical orthogonalization.

neuroscience↗