Deconstructing the architecture of dorsal and ventral attention systems with dynamic causal modeling

Abstract

Attentional orientation to a spatial cue and reorientation-after invalid cueing-are mediated by two distinct networks in the human brain. A bilateral dorsal frontoparietal network, comprising the intraparietal sulcus (IPS) and the frontal eye fields (FEF), controls the voluntary deployment of attention and may modulate visual cortex in preparation for upcoming stimulation. In contrast, reorienting attention to invalidly cued targets engages a right-lateralized ventral frontoparietal network comprising the temporoparietal junction (TPJ) and ventral frontal cortex. The present fMRI study investigated the functional architecture of these two attentional systems by characterizing effective connectivity during lateralized orienting and reorienting of attention, respectively. Subjects performed a modified version of Posner's location-cueing paradigm. Dynamic causal modeling (DCM) of regional responses in the dorsal and ventral network, identified in a conventional (SPM) whole-brain analysis, was used to compare different functional architectures. Bayesian model selection showed that top-down connections from left and right IPS to left and right visual cortex, respectively, were modulated by the direction of attention. Moreover, model evidence was highest for a model with directed influences from bilateral IPS to FEF, and reciprocal coupling between right and left FEF. Invalid cueing enhanced forward connections from visual areas to right TPJ, and directed influences from right TPJ to right IPS and IFG (inferior frontal gyrus). These findings shed further light on the functional organization of the dorsal and ventral attentional network and support a context-sensitive lateralization in the top-down (backward) mediation of attentional orienting and the bottom-up (forward) effects of invalid cueing.

Figure 1.

Illustration of the experimental design and paradigm. A, Trials were presented using a mixed event-related and block design with % validity (90% or 60%) being manipulated across different blocks. The % validity was indicated to the subjects by instruction as well as by the color of the cue (blue or orange). B, In the example shown here, the subject was asked to discriminate the orientation of the green grating while maintaining fixation at the center of the display (i.e., the dot in the diamond).

Figure 2.

Model space for Bayesian model comparison of dorsal network DCMs. A, Models including IPS and visual cortex. B, Models including FEF, IPS, and visual cortex. Fixed connections are indicated by dashed arrows and are identical across competing models. Solid arrows represent the model-specific modulatory (bilinear) effects on connections. L, Left; R, right.

Figure 3.

Model space for Bayesian model comparison of ventral network DCMs. Fixed connections are indicated by dashed arrows and are identical across competing models. Solid arrows represent the model-specific modulatory (bilinear) effects on connections. L, Left; R, right.

Figure 4.

Eye movement data for the cue (A) and target (B) periods, response times (C) and error rates (D) in the different experimental conditions.

Figure 5.

A, Results of the SPM analysis of valid trials (shown at p < 0.05—corrected using an extent threshold of 100 voxels). B, Results of the GLM analysis of invalid compared with valid trials (shown at p < 0.05—corrected using a height threshold of the p = 0.001 uncorrected).

Figure 6.

Location of the mean coordinates (depicted with 8 mm spheres) of the time series extraction of visual areas (green) and regions of the dorsal (blue) and ventral (orange) networks. ROIs in left and right visual cortex (Vis L and R) were located in V4/V3 according to a probabilistic cytoarchitectonic atlas (SPM Anatomy toolbox; Eickhoff et al., 2005).

Figure 7.

DCM with the highest model evidence for connectivity between FEF, IPS, and visual cortex—in relation to the direction of attentional orienting. Fixed connections and modulatory (bilinear) effects on connections are illustrated with dashed and solid arrows, respectively. Coupling parameters were positive for all fixed connections. Connections exhibiting significant (according to post hoc classical t tests) bilinear or modulatory effects are highlighted in color (red indicating significant negative modulatory effects and green indicating significant positive modulatory effects).

Figure 8.

DCM with the highest model evidence for the connectivity between the areas activated in the contrast of invalid versus valid trials; in relation to the effects of invalid cueing per se and invalid cueing in the context of high % validity. Fixed connections and effects on (bilinear) connections are illustrated with dashed and solid arrows, respectively. Again, coupling parameters were positive for all fixed connections. Connections exhibiting significant (according to post hoc classical t tests) bilinear or modulatory effects are highlighted in color (green indicating significant positive modulatory effects).