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The Network Architecture of Cortical Processing in Visuo-Spatial Reasoning

Clinical Trial

The Network Architecture of Cortical Processing in Visuo-Spatial Reasoning

Ehsan Shokri-Kojori et al. Sci Rep.


Reasoning processes have been closely associated with prefrontal cortex (PFC), but specifically emerge from interactions among networks of brain regions. Yet it remains a challenge to integrate these brain-wide interactions in identifying the flow of processing emerging from sensory brain regions to abstract processing regions, particularly within PFC. Functional magnetic resonance imaging data were collected while participants performed a visuo-spatial reasoning task. We found increasing involvement of occipital and parietal regions together with caudal-rostral recruitment of PFC as stimulus dimensions increased. Brain-wide connectivity analysis revealed that interactions between primary visual and parietal regions predominantly influenced activity in frontal lobes. Caudal-to-rostral influences were found within left-PFC. Right-PFC showed evidence of rostral-to-caudal connectivity in addition to relatively independent influences from occipito-parietal cortices. In the context of hierarchical views of PFC organization, our results suggest that a caudal-to-rostral flow of processing may emerge within PFC in reasoning tasks with minimal top-down deductive requirements.


Figure 1
Figure 1. The VSRT and the associated brain activity.
Participants judged whether shapes changed across the 3 frames according to the following alteration rules: clockwise revolution for the shape in left upper corner, size increase for the left-side shape, multiplication for the center shape and clockwise rotation for the surrounding center shape. (a) One relation condition. The ellipsoid should continue revolving clockwise along the corners of the frame. (b) Two relation condition. The polygon should revolve clockwise and the ellipsoid should continue increasing in size. (c) Three relation condition. Together with the revolving triangle and multiplying ellipsoids, the surrounding rectangle should continue a clockwise rotation around the center. (d–f) Activation t-maps for one, two and three relations, respectively (brighter colors represent larger t-values, FDR, P < 0.05). More consistent recruitment of left caudal PFC is evident when relational complexity increases.
Figure 2
Figure 2. Topographical representations of causal connectivity maps.
ROIs are positioned based on their order along the coronal axis. (a) Group-level causal connectivity and sensitivity to task-demand. ROIs show regions with linear increase in activity in response to increased task complexity (FDR, P < 0.05). Yellow circles represent demand-sensitive ROIs where their activation significantly increased along with RT (FDR, P < 0.05). Green circles represent non-significant correlations with RT. The radius of the circles is proportional to the mean t-value of selected voxels within each ROI across all VSRT conditions. Directional influences are represented by red lines with thickness proportional to significance (FDR, P < 0.05). Blue lines represent significant bidirectional connections (FDR, P < 0.05). (b) Connectivity map of fast performers. Group-level connections were explored to detect those that are part of fast performers' connectivity network (P < 0.01). (c) Connectivity map of slow performers (P < 0.01).
Figure 3
Figure 3. Group-level investigation of causal influence of ROIi on ROIj (N = 20).
(a) Schematic of the multivariate Granger causality (MGC) at the subject-level (Subjectx). Initially, the predictability components of other possible interacting regions (except ROIi) were removed using multivariate auto regressive modeling (MVAR). (b) The residual signal was correlated with lagged time-series from ROIi to obtain the parameter estimate for unique causal influence of ROIi on ROIj. (c) Significant causal influences were then determined using a two tailed t-test comparing the mean of Fisher's z-transformed correlations against zero (FDR, P < 0.05).

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