Human brain function depends on directed interactions between multiple areas that evolve in the subsecond range. Time-varying multivariate autoregressive (tvMVAR) modeling has been proposed as a way to help quantify functional connectivity strengths with high temporal resolution. While several tvMVAR approaches are currently available, there is lack of unbiased systematic comparative analyses their performance and sensitivity parameter choices. Here, we critically compare four recursive...

Cognitive control allows behavior to be guided according environmental contexts and internal goals. During cognitive tasks, fMRI analyses typically reveal increased activation in frontal parietal networks, EEG amplitude of neural oscillations the delta/theta band (2-3, 4-7 Hz) electrodes. Previous studies proposed that theta-band activity reflects maintenance rules associating stimuli appropriate actions (i.e., rule set), whereas delta synchrony is specifically associated with over context...

Transcranial Magnetic Stimulation (TMS) allows for the direct activation of neurons in human neocortex and has proven to be fundamental causal hypothesis testing cognitive neuroscience. By administering TMS concurrently with functional Resonance Imaging (fMRI), effect cortical on activity distant subcortical structures can quantified by varying levels output intensity. However, generates significant fluctuations fMRI time series, their complex interaction warrants caution before interpreting...

In this study, we compared the brain activation profiles obtained from resting state Electroencephalographic (EEG) and Magnetoencephalographic (MEG) activity in six mild traumatic injury (mTBI) patients five orthopedic controls, using power spectral density (PSD) analysis. We first estimated intracranial dipolar EEG/MEG sources on a dense grid cortical surface then projected these standardized atlas with 68 regions of interest (ROIs). Averaging PSD values all each ROI across control subjects...

Brain mechanisms of visual selective attention involve both local and network-level activity changes at specific oscillatory rhythms, but their interplay remains poorly explored. Here, we investigate anticipatory reactive effects feature-based using separate fMRI EEG recordings, while participants attended to one two spatially overlapping features (motion orientation). We focused on source analysis neuronal rhythms nested oscillations graph connectivity in a network fMRI-defined regions...

Adaptive algorithms based on the Kalman filter are valuable tools to model dynamic and directed Granger causal interactions between neurophysiological signals simultaneously recorded from multiple cortical regions. Among these algorithms, General Linear Filter (GLKF) has proven be most accurate reliable. Here we propose a regularized smoothed GLKF (spsm-GLKF) with ℓ1 norm penalties lasso or group fixedinterval smoother. We show that penalty promotes sparse solutions by shrinking spurious...

In this study, we compared the brain activation profiles obtained from resting state Magnetoencephalographic (MEG) activity in 15 dyslexic patients with of normal controls, using power spectral density (PSD) analysis. We first estimated intracranial dipolar MEG sources on a dense grid cortical surface and then projected these standardized atlas 68 regions interest (ROIs). Averaging PSD values all each ROI across control subjects resulted normative database that was used to convert into...

Selective attention is a fundamental cognitive mechanism that allows our brain to preferentially process relevant sensory information, while filtering out distracting information. Attention thought flexibly gate the communication of irrelevant information through top-down alpha-rhythmic (8-12 Hz) functional connections, which influence early visual processing. However, dynamic effects on downstream processing remain unknown. Here, we used electroencephalography investigate local and network...

The ability to successfully retain and manipulate information in working memory (WM) requires that objects' individual features are bound into cohesive representations; yet, the mechanisms supporting feature binding remain unclear. Binding (or swap) errors, where memorized erroneously associated with wrong object, can provide a window intrinsic limits capacity of WM represent key bottleneck our cognitive ability. We tested hypothesis is accomplished via neural phase synchrony swap errors...

Nonparametric methods based on spectral factorization offer well validated tools for estimating measures of causality, called Granger–Geweke Causality (GGC). In Pagnotta et al. (2018) [1] we benchmarked nonparametric GGC using EEG data recorded during unilateral whisker stimulations in ten rats; here, include detailed information about the benchmark dataset. addition, provide codes and a simulation framework to evaluate effects analyses potential problems, such as common reference problem,...

Abstract Brain mechanisms of visual selective attention involve both local and network-level activity changes at specific oscillatory rhythms, but their interplay remains poorly explored. Here, we investigate anticipatory reactive effects feature-based using separate fMRI EEG recordings, while participants attended to one two spatially overlapping features (motion orientation). We focused on source analysis nested oscillations graph connectivity in a network fMRI-defined regions interest,...