Estimation of the cortical functional connectivity with the multimodal integration of high-resolution EEG and fMRI data by directed transfer function

By Fabio Babiloni, Febo Cincotti, Claudio Babiloni, Filippo Carducci, Bin He. NeuroImage, 2005

435 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/5b64de208201db264ab616b6348f962b2061c79d

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In Cognitive Neuroscience

In Radiology, Nuclear Medicine and Imaging

Citations in the corpus

Electrophysiological Imaging of Brain Activity and Connectivity – Challenges and Opportunities (2011, background): “From the directionality information provided by the DTF, the degree to which each cortical region acts as either a source or sink of cortical activity during the task can be calculated (from [64] with permission).”
Error-Related EEG Potentials Generated During Simulated Brain–Computer Interaction (2008, background): “However, Babiloni et al. [15], [ 16 ] have recently developed the so-called cortical current density (CCD) inverse model that estimates the activity of the cortical mantle.”
Real-time Neuroimaging and Cognitive Monitoring Using Wearable Dry EEG (2015, neutral): “For example, Babiloni et al [17] studied spectral directed information transfer between cortical Tim R. Mullen*, Member, IEEE, Christian A.E. Kothe, Member, IEEE, Mike Chi, Alejandro Ojeda, Trevor Kerth, Scott Makeig, Tzyy-Ping Jung, Fellow, IEEE, Gert Cauwenberghs, Fellow, IEEE regions of interest…”
A critical assessment of connectivity measures for EEG data: A simulation study (2013, methodology): “Nevertheless, EEG recordings have beenwidely used in neuroscience to estimate brain connectivity (e.g., Astolfi et al., 2004; Babiloni et al., 2004; Babiloni et al., 2005; Blinowska et al., 2010; Kamiński et al., 1997; Silberstein, 2006; Srinivasan et al., 2007; Supp et al., 2007).”
Source connectivity analysis with MEG and EEG (2009, methodology): “ROIs can be selected based on a priori knowledge of their involvement in a given experimental task (e.g., from previous functional imaging studies) [Astolfi et al., 2004, 2005; Babiloni et al., 2005; Gross et al., 2001; Lin et al., 2004].”
Applications of functional magnetic resonance imaging for market research (2007, background): “…can generate identical potentials on the skin, estimated solutions of the inverse problem, i.e. source localization, require appropriate a priori assumptions about sources and volume conduction in order to yield physiologically meaningful data (Babiloni et al., 2005; Michel et al., 2004).”
Frequency-dependent functional connectivity within resting-state networks: An atlas-based MEG beamformer solution (2012, neutral): “, 2007), or for a limited set of a-priori defined Regions-ofInterest (ROIs; e.g. Astolfi et al., 2007; Babiloni et al., 2005; De Vico Fallani et al., 2007), where the time-series were subsequently used for the estimation of functional connectivity.”
A MATLAB toolbox for Granger causal connectivity analysis. (2010, neutral): “, 2004), EEG ignals (Babiloni et al., 2005; Keil et al., 2009), fMRI BOLD signals Roebroeck et al.”
Negative Covariation between Task-related Responses in Alpha/Beta-Band Activity and BOLD in Human Sensorimotor Cortex: an EEG and fMRI Study of Motor Imagery and Movements (2009, background): “, 2004) and event-related potentials (ERP) through phase-locked averaging (Huettel et al., 2004; Mulert et al., 2004; Schulz et al., 2004; Babiloni et al., 2005; Liu and He, 2008) – all of which are generated by synchronized neuronal populations.”