The MVGC multivariate Granger causality toolbox: a new approach to Granger-causal inference
Abstract Background Wiener–Granger causality (“G-causality”) is a statistical notion of
causality applicable to time series data, whereby cause precedes, and helps predict, effect. It …
causality applicable to time series data, whereby cause precedes, and helps predict, effect. It …
Adding dynamics to the Human Connectome Project with MEG
Abstract The Human Connectome Project (HCP) seeks to map the structural and functional
connections between network elements in the human brain. Magnetoencephalography …
connections between network elements in the human brain. Magnetoencephalography …
Neurophysiological signatures of Alzheimer's disease and frontotemporal lobar degeneration: pathology versus phenotype
The disruption of brain networks is characteristic of neurodegenerative dementias. However,
it is controversial whether changes in connectivity reflect only the functional anatomy of …
it is controversial whether changes in connectivity reflect only the functional anatomy of …
A framework for the design of flexible cross‐talk functions for spatial filtering of EEG/MEG data: DeFleCT
Brain activation estimated from EEG and MEG data is the basis for a number of time‐series
analyses. In these applications, it is essential to minimize “leakage” or “cross‐talk” of the …
analyses. In these applications, it is essential to minimize “leakage” or “cross‐talk” of the …
A nonlinear causality measure in the frequency domain: Nonlinear partial directed coherence with applications to EEG
Abstract Background Frequency domain Granger causality measures have been proposed
and widely applied in analyzing rhythmic neurophysiological and biomedical signals. Almost …
and widely applied in analyzing rhythmic neurophysiological and biomedical signals. Almost …
Beamformer source analysis and connectivity on concurrent EEG and MEG data during voluntary movements
M Muthuraman, H Hellriegel, N Hoogenboom… - PloS one, 2014 - journals.plos.org
Electroencephalography (EEG) and magnetoencephalography (MEG) are the two
modalities for measuring neuronal dynamics at a millisecond temporal resolution. Different …
modalities for measuring neuronal dynamics at a millisecond temporal resolution. Different …
Analysis of functional connectivity and oscillatory power using DICS: from raw MEG data to group-level statistics in python
Communication between brain regions is thought to be facilitated by the synchronization of
oscillatory activity. Hence, large-scale functional networks within the brain may be estimated …
oscillatory activity. Hence, large-scale functional networks within the brain may be estimated …
Markov model-based method to analyse time-varying networks in EEG task-related data
The dynamic nature of functional brain networks is being increasingly recognized in
cognitive neuroscience, and methods to analyse such time-varying networks in EEG/MEG …
cognitive neuroscience, and methods to analyse such time-varying networks in EEG/MEG …
Theta-modulated gamma-band synchronization among activated regions during a verb generation task
Expressive language is complex and involves processing within a distributed network of
cortical regions. Functional MRI and magnetoencephalography (MEG) have identified brain …
cortical regions. Functional MRI and magnetoencephalography (MEG) have identified brain …
Optimal sampling designs for multidimensional streaming time series with application to power grid sensor data
Optimal sampling designs for multidimensional streaming time series with application to power
grid sensor data Page 1 The Annals of Applied Statistics 2023, Vol. 17, No. 4, 3195–3215 …
grid sensor data Page 1 The Annals of Applied Statistics 2023, Vol. 17, No. 4, 3195–3215 …