2019
DOI: 10.1371/journal.pcbi.1007316
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Large-scale cortical travelling waves predict localized future cortical signals

Abstract: Predicting future brain signal is highly sought-after, yet difficult to achieve. To predict the future phase of cortical activity at localized ECoG and MEG recording sites, we exploit its predominant, large-scale, spatiotemporal dynamics. The dynamics are extracted from the brain signal through Fourier analysis and principal components analysis (PCA) only, and cast in a data model that predicts future signal at each site and frequency of interest. The dominant eigenvectors of the PCA that map the large-scale p… Show more

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Cited by 24 publications
(29 citation statements)
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References 82 publications
(202 reference statements)
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“…On the other hand, a direct comparison between FW and BW waves in each time-bin is not readily interpretable, as it is possible to simultaneously record waves propagating in both directions-as observed during visual stimulation epochs (see below). In addition, it's important to note that our waves' analysis focuses on the sensor level, as source projections presents a number of important limitations, such as impairing long-range connections, as well as smearing of signals due to scalp interference (Alexander et al, 2019;Freeman and Barrie, 2000;Nunez, 1974). From each 1-s EEG epoch we extract a 2D-map, obtained by stacking signals from 5 midline electrodes.…”
Section: Quantifying Travelling Wavesmentioning
confidence: 99%
“…On the other hand, a direct comparison between FW and BW waves in each time-bin is not readily interpretable, as it is possible to simultaneously record waves propagating in both directions-as observed during visual stimulation epochs (see below). In addition, it's important to note that our waves' analysis focuses on the sensor level, as source projections presents a number of important limitations, such as impairing long-range connections, as well as smearing of signals due to scalp interference (Alexander et al, 2019;Freeman and Barrie, 2000;Nunez, 1974). From each 1-s EEG epoch we extract a 2D-map, obtained by stacking signals from 5 midline electrodes.…”
Section: Quantifying Travelling Wavesmentioning
confidence: 99%
“…We only included trials where fixation had been maintained for at least 300 ms prior to target onset to avoid including waves triggered by the saccade to fixation that initiated each trial 19 . To avoid any confounding effect due to the activation by the target itself, we leveraged the observation that similar wave phases tend to recur over 1–2 sequential cycles 34 , and examined wave alignments before the presentation of the target that predicted detection performance. Detected targets (hits) tended to be preceded by the alignment of a particular wave phase (peak −60 ms relative to target onset monkey W, p < 1 × 10–3; −33 ms monkey T, p < 1 × 10–5; Rayleigh test; Fig.…”
mentioning
confidence: 99%
“…(E) Psychophysical studies in human subjects (47)(48)52) found that duration threshold can increase or decrease with stimulus luminance contrast depending on stimulus size (indicated in the figure to the right of each curve). Since stimulus size is known to determine the amount of inhibition in cortical circuits (35)(36), our model can explain the reversal of relationship between stimulus contrast and duration threshold shown in E (47): from threshold decreasing with contrast for small stimuli (corresponding to the gray curve in D) to threshold increasing with contrast for large stimuli (green curve in D).…”
Section: Discussionmentioning
confidence: 99%