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Supplemental Information

Figure 1: Data simulation

Strategies used for synthetic neural data modeling. LFPs are simulated by four distinct generative models and the resulting time-series can be used by EEG or BOLD forward models to produce the respective signals.

DOI: 10.7287/peerj.preprints.737v1/supp-1

Figure 2: Three layer spherical head model

Three layer spherical head model for one current dipole with radius rq and scalp electrode with radius r. Adapted from (Mosher, Leahy & Lewis, 1999).

DOI: 10.7287/peerj.preprints.737v1/supp-2

Figure 3: GGC DOI for LFP signals with increasing coupling strength

GGC DOI for the time-series simulated with increasing coupling strength with the generative models: A) AR models, B) KIe,i sets, C) Kuramoto oscillators, D, E and F) Izhikevich columns.

DOI: 10.7287/peerj.preprints.737v1/supp-3

Figure 4: GGC DOI for LFP signals with increasing interaction delay

GGC DOI for the time-series simulated with increasing interaction delay with the generative models: A) AR models, B) KIe,i sets, C) Kuramoto oscillators, D) Izhikevich columns.

DOI: 10.7287/peerj.preprints.737v1/supp-4

Figure 5: Model orders for LFP signals with increasing interaction delay

Figure 5: Model orders estimated with BIC and AIC for the time-series simulated with increasing interaction delay with the generative models: A) AR models, B) KIe,i sets, C) Kuramoto oscillators, D) Izhikevich columns. The lagged observations for these interaction delays with 250 HZ sampling rate are [1, 5, 10, 15, 20, 25].

DOI: 10.7287/peerj.preprints.737v1/supp-5

Figure 6: GGC DOI for EEG signals with increasing coupling strengths

GGC DOI after EEG forwarding the time series from the generative models with varying coupling strengths: A) AR models, B) KIe,i sets, C) Kuramoto oscillators, D, E and F) Izhikevich columns.

DOI: 10.7287/peerj.preprints.737v1/supp-6

Figure 7: GGC DOI for EEG signals with increasing interaction delays

GGC DOI after EEG forwarding the time series from the generative models with varying interaction delays: A) AR models, B) KIe,i sets, C) Kuramoto oscillators, D) Izhikevich columns.

DOI: 10.7287/peerj.preprints.737v1/supp-7

Figure 8: Model orders for EEG signals with increasing interaction delay

Model orders estimated with BIC and AIC for the time-series simulated with increasing interaction delay after EEG forwarding with the generative models: A) AR models, B) KIe,i sets, C) Kuramoto oscillators, D) Izhikevich columns. The lagged observations for these interaction delays with 250 HZ sampling rate are [1, 5, 10, 15, 20, 25].

DOI: 10.7287/peerj.preprints.737v1/supp-8

Figure 9: GGC DOI for BOLD signals with increasing coupling strengths

GGC DOI in the 0.01-0.1 Hz band after BOLD forward modeling the time series from the generative models with varying coupling strengths: A) AR models, B) KIe,i sets, C) Kuramoto oscillators, D, E and F) Izhikevich columns.

DOI: 10.7287/peerj.preprints.737v1/supp-9

Figure 9: GGC DOI for BOLD signals with increasing interaction delays

GGC DOI in the 0.01-0.1 Hz band after BOLD forward modeling the time series from the generative models with varying interaction delays: A) AR models, B) KIe,i sets, C) Kuramoto oscillators, D) Izhikevich columns.

DOI: 10.7287/peerj.preprints.737v1/supp-10

Additional Information

Competing Interests

The authors declare they have no competing interests.

Author Contributions

João Rodrigues conceived and designed the experiments, performed the experiments, analyzed the data, wrote the paper, prepared figures and/or tables, reviewed drafts of the paper.

Alexandre Andrade conceived and designed the experiments, analyzed the data, wrote the paper, reviewed drafts of the paper.

Funding

The Portuguese Science Foundation (FCT) provided financial support through Project PTDC/SAU-ENB/112294/2009 and PEst-OE/SAU/UI0645/2011. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.


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