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. 2019 Oct;9(10):e01365.
doi: 10.1002/brb3.1365. Epub 2019 Sep 19.

Parcellation-based tractographic modeling of the dorsal attention network

Parker G Allan  1 , Robert G Briggs  1 , Andrew K Conner  1 , Christen M O'Neal  1 , Phillip A Bonney  2 , Brian D Maxwell  1 , Cordell M Baker  1 , Joshua D Burks  3 , Goksel Sali  1 , Chad A Glenn  1 , Michael E Sughrue  4
Affiliations

Parcellation-based tractographic modeling of the dorsal attention network

Parker G Allan et al. Brain Behav. 2019 Oct.

Abstract

Introduction: The dorsal attention network (DAN) is an important mediator of goal-directed attentional processing. Multiple cortical areas, such as the frontal eye fields, intraparietal sulcus, superior parietal lobule, and visual cortex, have been linked in this processing. However, knowledge of network connectivity has been devoid of structural specificity.

Methods: Using attention-related task-based fMRI studies, an anatomic likelihood estimation (ALE) of the DAN was generated. Regions of interest corresponding to the cortical parcellation scheme previously published under the Human Connectome Project were co-registered onto the ALE in MNI coordinate space and visually assessed for inclusion in the network. DSI-based fiber tractography was performed to determine the structural connections between relevant cortical areas comprising the network.

Results: Twelve cortical regions were found to be part of the DAN: 6a, 7AM, 7PC, AIP, FEF, LIPd, LIPv, MST, MT, PH, V4t, VIP. All regions demonstrated consistent u-shaped interconnections between adjacent parcellations. The superior longitudinal fasciculus connects the frontal, parietal, and occipital areas of the network.

Conclusions: We present a tractographic model of the DAN. This model comprises parcellations within the frontal, parietal, and occipital cortices principally linked through the superior longitudinal fasciculus. Future studies may refine this model with the ultimate goal of clinical application.

Keywords: anatomy; attention; parcellation; tractography.

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Conflict of interest statement

None declared.

Figures

Figure 1
Figure 1
Activation likelihood estimation (ALE) of 15 task‐based fMRI experiments related to goal‐oriented attentional processing. The three‐dimensional ALE data (in red) are displayed in Mango on a brain normalized to the MNI coordinate space. (a–b) ALE data highlighting the left lateral occipital lobe. (b–c) ALE data highlighting the left superior parietal lobule and intraparietal sulcus. (c–d) ALE data highlighting the left frontal eye field region
Figure 2
Figure 2
Comparison overlays between cortical parcellations (shown in blue) and the activation likelihood estimation (shown in red) as seen on a left cerebral hemisphere. Regions were visually assessed for inclusion in the network if they overlapped with the activation likelihood estimation. Cortical parcellations assessed for inclusion in our model of the dorsal attention network included areas FEF and 6a in the frontal lobe; areas MST, MT, PH, and V4t in the lateral occipital lobe; and areas 7PC, 7AM, AIP, LIPd, LIPv, and VIP in the superior parietal lobule and intraparietal sulcus. Labels indicate the region of interest shown in each panel
Figure 3
Figure 3
Tractographic model of the dorsal attention network (DAN) as shown on T1‐weighted magnetic resonance images in the left cerebral hemisphere. TOP ROW: sagittal sections through the network demonstrate the extent of the superior longitudinal fasciculus (SLF) which projects between the frontal, parietal, and occipital regions of the DAN. MIDDLE ROW: coronal sections highlight the parieto‐occipital projections of the SLF within the DAN. BOTTOM ROW: axial sections highlight the fronto‐parietal projections of the SLF within the DAN
Figure 4
Figure 4
Simplified schematic of the white matter connections identified between individual parcellations of the dorsal attention network during fiber tracking analysis. Connections are labeled with their average strength measured across all 25 subjects used in this analysis
See this image and copyright information in PMC

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