Gamma-band synchronization in the neocortex: novel analysis methods and their application to sensory and motivational systems

By Martin A. Vinck. 2013

693 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/ec2ff852d44ce08ec6264f9b87d5d6078e4e0015

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Citations in the corpus

How reliable are MEG resting-state connectivity metrics? (2016, methodology): “…connectivity in a Stroop task; Hardmeier et al. (2014) assessed the phase lag index (PLI; Stam et al. (2007)) and weighted phase lag index (wPLI; Vinck et al. (2011)) in the resting state, but only analysed sensor-level signals, not cortical sources; Wang et al. (2014) undertook a large…”
A Tutorial Review of Functional Connectivity Analysis Methods and Their Interpretational Pitfalls (2016, methodology): “Therefore, in general it is advisable to interrogate the data using several of these measures, in order to get a feel for how the estimates relate to one another.”
EEG and MEG: relevance to neuroscience. (2013, background): “A variety of methods of signal analysis to estimate functional connectivity exist (Lachaux et al., 1999; Stam et al., 2007; Wendling et al., 2009; Vinck et al., 2011; Haufe et al., 2013), among which the phase-locking value (PLV) is currently the most widely used.”
Theta-Phase Connectivity between Medial Prefrontal and Posterior Areas Underlies Novel Instructions Implementation (2022, background): “According to prominent computational models, this phenomenon can be interpreted as reflecting the activity of the mPFC in coordinating the neural communication between distant task-relevant areas (Voloh and Womelsdorf, 2016; Verguts, 2017).”
Motor Interference, But Not Sensory Interference, Increases Midfrontal Theta Activity and Brain Synchronization during Reactive Control (2021, methodology): “For estimating synchronicity, we used the debiased weighted phase lag index (WPLI; Vinck et al., 2011).”
Alpha oscillatory activity is causally linked to working memory retention (2023, methodology): “Supporting the reliability and reproducibility of these results calculated using PLI, we again detected the anti-phase tACS-induced disturbance when we used another index (weighted PLI) that has been reported to offer an advantage in terms of reduced sensitivity to unrelated noise sources [36] (S6 F”
Learning in brain-computer interface control evidenced by joint decomposition of brain and behavior (2019, methodology): “Connectivity Analysis—To estimate phase-based connectivity, we calculated the weighted phase-locking index (wPLI) [107].”
Network-Targeted, Multi-site Direct Cortical Stimulation Enhances Working Memory by Modulating Phase Lag of Low-Frequency Oscillations (2019, methodology): “DWPLI measures the degree of consistency of phase lag 101 between two signals and is not affected by volume conduction [50] making it an effective tool for identifying 102 functional interactions in iEEG.”