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DOI 10.1002/brb3.1365

Медицинская библиотека · Brain and behavior · 2019

Parcellation-based tractographic modeling of the dorsal attention network.

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

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Аннотация

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.

Для цитирования: Allan Parker G, Briggs Robert G, Conner Andrew K, O'Neal Christen M, Bonney Phillip A, Maxwell Brian D, Baker Cordell M, Burks Joshua D, Sali Goksel, Glenn Chad A, Sughrue Michael E. Parcellation-based tractographic modeling of the dorsal attention network.. Brain and behavior. 2019. DOI: 10.1002/brb3.1365.

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