Integrated phenomenology and brain connectivity demonstrate changes in nonlinear processing in jhana advanced meditation

Figures

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  Figure 1:. Experimental design, oscillatory and non-oscillatory connectivity. (A) Mapping functional connectivity between two EEG signals. In this diagram, connectivity is depicted between signal X (in blue) and signal Y (in black) corresponding to two arbitrary electrodes of interest. (B) Linear transformations between two correlated signals at the same frequency. The transformed signal (signal Y) is the result of a phase-shifted version of the original signal (signal X) at the same frequency (e.g., a 10 Hz signal X can result in a phase-shifted signal Y at the same 10 Hz). The WPLI metric (weighted phase lagged index) captures this type of linear, oscillatory connectivity. (C) Left: Nonlinear transformations cause systematic relationships across different frequencies between signal X and Y, potentially in the absence of linear transformations. Thus, non-linear connectivity measures quantify arbitrary mappings between temporal patterns in one signal (signal X) and another signal (signal Y). This type of non-oscillatory mapping is captured by the WSMI metric (weighted symbolic mutual information). Right: Directed Information (dir-INFO) (also referred to as Transfer Entropy) measures the…

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  Figure 2:. WSMI and WPLI across ACAM-J (A) WSMI across ACAM-J and control (Counting) states in different frequency ranges. WSMI (30–45 Hz): One-way analysis of variance (ANOVA) using ‘state’ as a factor with seven levels (Control, and ACAM-J1 to J6–8) revealed a significant main effect of ‘state’ (F1,3728 = 50.96; p<0.001). Post-hoc comparisons revealed differences between control and ACAM-J states (C vs J1 and J2; p<0.01), and between ACAM-J (J1 vs J3, J4, J5, J6–8; J2 vs J3, J4, J5, J6–8; J3 vs J4, J5, J6–8; all p<0.01). WSMI (15–29 Hz): main effect (F1,3728 = 97.41; p<0.001), with post-hoc differences between control and ACAM-J (C vs J2, J3, J4, J5, J6–8; p<0.01), and between ACAM-J (J1 vs J3, J4, J5, J6–8; J2 vs J3, J4, J5, J6–8; J3 vs J4, J5, J6–8; all p<0.001). WSMI (8–14 Hz): main effect (F1,3728 = 108.70; p<0.001), with post-hoc differences between control and ACAM-J (C vs J1, J2, J3, J4, J5, J6–8; p<0.01), and between ACAM-J (J1 vs J3, J4, J5, J6–8; J2 vs J3, J4, J5, J6–8; J3 vs J4, J5, J6–8; all p<0.001). WSMI (4–7 Hz): main effect (F1,3728 = 3.04; p = 0.005), with post-hoc differences between control and ACAM-J (C vs J3, J4, J5, J6–8; p<0.02). (B) Similarly, a second one-way…

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  Figure 3:. Classification performance of WSMI and WPLI across EEG frequency ranges and ACAM-J meditation states with and without phenomenological data integration. (A) WSMI balanced accuracy is shown across the five EEG frequency bands (1–3 Hz, 4–7 Hz, 8–14 Hz, 15–29 Hz, and 30–45 Hz). The bar graph on the left compares model accuracy with (blue) and without (green) phenomenological data inclusion. Confusion matrices on the right show classification performance across baseline control (C) and ACAM-J (J1 to J6–8), indicating true class labels on the y-axis and predicted classes on the x-axis. Matrices depict instances count per cell, with background shading representing classifier performance. The percentages below and at the right side of each matrix represent precision and recall for each state. Precision (shown horizontally at the bottom) indicates the proportion of correctly predicted instances for each state, while recall (displayed vertically along the right side) represents the proportion of true instances that were correctly classified. Higher values in these metrics reflect improved classifier performance in distinguishing between different states. (B) WPLI balanced accuracy is…

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  Figure 4:. Directed information in ACAM-J (A) dir-INFO between the back and front ROIs (feedforward neural information; in blue) and between the front and back ROIs (feedback neural information; in blue) in during Access Concentration (AC) and ACAM-J (J1 to J6–8). Shaded bars represent the standard error of the mean (S.E.M) across epochs. Grey bars represent significant time points after false discovery rate (FDR) correction.