Multivariate neural markers of individual differences in thought control difficulties

Figures

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  Fig. 1. Pearson correlations between the PSWQ, WBSI, and RRS brooding subscale scores and the thought control difficulties score were calculated by taking the Z-score average of the PSWQ, WBSI, and RRS brooding subscale scores.

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  Fig. 2. Dimensionality reduction to derive gradients of A) representational similarity and B) functional connectivity patterns across the WM control operations: (maintain, green; replace, blue; suppress, red; clear, orange). Both A and B illustrate the gradient group-level diffusion map embedding solutions for illustration purposes. Parcels are colored by DeRosa et al. (2024) WMO Network: yellow, Visual WMO Network; teal, Somatomotor WMO Network; pink, Default Mode WMO Network; purple, Frontoparietal Control WMO Network. To derive the individual-level gradients for each participant, the normalized angle matrix across 360 Glasser parcels was thresholded to retain the top 10% of the connections for each of the four WM control operations, as well resting-state (not shown in this figure). Then, the representational similarity (RSA), as well as functional connectivity profile similarities were calculated using row-wise cosine similarity for symmetry. Separately, the normalized angle matrixes were subjected to diffusion map embedding, and the top three components were extracted. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of…

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  Fig. 3. Hypothesis-driven representation of WMO Network eccentricity. This figure illustrates the concept of WMO Network eccentricity and its hypothesized relationship with thought control difficulties. A) (left) displays group-level metrics for a sample WM operation, showing the general organization of WMO Networks. The WMO Networks are color-coded as per DeRosa et al. (2024): yellow for the Visual WMO Network, teal for the Somatomotor WMO Network, pink for the Default Mode WMO Network, and purple for the Fronto-parietal WMO Network. The magnified view on the right focuses on the Default Mode WMO Network, with the large central dot representing the average neural pattern across all WMO Networks. Individual Default Mode WMO Network parcels, shown as pink dots, are positioned according to their distance from this central average, illustrating eccentricity. B) Shows synthetic data from hypothetical Participant A, characterized by low WMO Network eccentricity within the Default Mode WMO Network. C) Shows synthetic data from hypothetical Participant B, characterized by high WMO Network eccentricity within the Default Mode WMO Network. The ruler icons illustrate distance, where a shorter…

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  Fig. 4. Hypothesis-driven representation of within-network dispersion. This figure illustrates the concept of within-network dispersion and its hypothesized relationship with thought control difficulties. A) (left) presents group-level metrics for a sample working memory operation, showing an overall view of WMO Network organization. WMO Networks are color-coded according to DeRosa et al. (2024): yellow for the Visual WMO Network, teal for the Somatomotor WMO Network, pink for the Default Mode WMO Network, and purple for the Frontoparietal Control WMO Network. The enlarged view on the right highlights the Frontoparietal Control WMO Network, with the large central dot representing the median pattern across Frontoparietal Control WMO Network parcels and the smaller purple dots representing individual Frontoparietal Control WMO Network parcels. The lines connecting each parcel to the median indicate the Mahalanobis distance across three gradients, reflecting dispersion within the WMO Network. B) Shows synthetic data from Participant A, characterized by low within-network dispersion within the Frontoparietal Control WMO Network. C) Shows synthetic data from Participant B, characterized by…

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  Fig. 5. Regression relationships between working memory operation accuracy and thought control difficulties. Each plot represents one working memory operation: maintain (green, top left), replace (blue, top right), suppress (red, bottom left), and clear (orange, bottom right). Points indicate individual participant data, with thought control problem scores plotted against the accuracy score of each operation. The regression line represents the linear association, with shaded areas indicating the confidence intervals. Regression statistics (Adj. R2, F-value, and FDR corrected p-value) are provided on the top of each subplot. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

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  Fig. 6. FPC WMO Network dispersion during thought suppression predicts individual differences in thought control difficulties. This figure illustrates the relationship between FPC WMO Network within-network dispersion during the suppress operation and self-reported thought control problems. Top left, a scatter plot shows the association between greater dispersion of the FPC WMO Network and higher thought control difficulty scores. Each point represents a participant; the shaded band indicates the 95 % confidence interval. Participants with low, medium, and high dispersion are marked and linked to their corresponding FPC WMO Network spatial configurations. Top right, dispersion is visualized in 3D gradient space for a single participant, showing parcel positions relative to the FPC WMO Network centroid across gradients 1–3. Bottom panels, six individual examples display increasing levels of within-network dispersion, from low (left) to high (right), with corresponding increases in spatial heterogeneity. Colored versions show all WMO Network parcel locations in gradient space.

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  Fig. 7. Thought control difficulties associations with RSA eccentricity metrics across WMO Networks and WM operations. This figure displays the relationships between RSA-derived eccentricity metrics and individual differences in self-reported thought control difficulties across the four WMO Networks (Visual, Somatomotor, Frontoparietal Control, and Default Mode). Each column corresponds to a WMO Network, and each row to a working memory operation (maintain, replace, suppress, clear), yielding a 4 × 4 matrix of regression subplots. In each plot, dispersion values are plotted along the x-axis and thought control difficulty scores along the y-axis. Points represent individual participants; linear regression lines reflect the estimated association between dispersion and thought control difficulty for each operation × network combination. Shaded regions denote 95 % confidence intervals. WMO network metrics significantly associated with thought control difficulties are noted by their FDR-corrected p-values in the top-left corner of the figure.

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  Fig. 8. Thought control difficulties associations with RSA dispersion metrics across WMO Networks and WM operations. This figure displays the relationships between RSA-derived within-network dispersion metrics and individual differences in self-reported thought control difficulties across the four WMO Networks (Visual, Somatomotor, Frontoparietal Control, and Default Mode). Each column corresponds to a WMO Network, and each row to a working memory operation (maintain, replace, suppress, clear), yielding a 4 × 4 matrix of regression subplots. In each plot, dispersion values are plotted along the x-axis and thought control difficulty scores along the y-axis. Points represent individual participants; linear regression lines reflect the estimated association between dispersion and thought control difficulty for each operation × network combination. Shaded regions denote 95 % confidence intervals. WMO network metrics significantly associated with thought control difficulties are noted by their FDR-corrected p-values in the top-left corner of the figure.