MEG FC analysis for conscious visual perception

🔗📕 Preprint: A data-driven approach to identifying and evaluating connectivity-based neural correlates of conscious visual perception

Systematically comparing different ways of quantifying functional coupling from MEG time series derived from regions hypothesized to support the IIT and/or GNWT theories of visual perception and consciousness

Figure 1 from Bryant & Whyte (2025): A data-driven approach to identifying and evaluating connectivity-based neural correlates of conscious visual perception.

Multiple properties of inter-areal coupling can distinguish between stimulus types across region–region pairs

Figure 2 from Bryant & Whyte (2025): A data-driven approach to identifying and evaluating connectivity-based neural correlates of conscious visual perception.

Statistics derived from the barycenter best distinguish stimuli, particularly faces

Figure 3 from Bryant & Whyte (2025): A data-driven approach to identifying and evaluating connectivity-based neural correlates of conscious visual perception.

Barycenter statistics dominate the top stimulus decoding results, along with basic covariance and spectral properties

Figure 4 from Bryant & Whyte (2025): A data-driven approach to identifying and evaluating connectivity-based neural correlates of conscious visual perception.

Testing predictions via data-driven analysis of theory-driven neural modeling

Figure 5 from Bryant & Whyte (2025): A data-driven approach to identifying and evaluating connectivity-based neural correlates of conscious visual perception.