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BACKGROUND The superior parietal lobule (SPL) is involved in somatosensory and visuospatial integration with additional roles in attention, written language, and working memory. A detailed understanding of the exact location and nature of associated white matter tracts could improve surgical decisions and subsequent postoperative morbidity related to surgery in and around this gyrus. OBJECTIVE To characterize the fiber tracts of the SPL based on relationships to other well-known neuroanatomic structures through diffusion spectrum imaging (DSI)-based fiber tracking validated by gross anatomical dissection as ground truth. METHODS Neuroimaging data of 10 healthy, adult control subjects was obtained from a publicly accessible database published in Human Connectome Project for subsequent tractographic analyses. White matter tracts were mapped between both cerebral hemispheres, and a lateralization index was calculated based on resultant tract volumes. Post-mortem dissections of 10 cadavers identified the location of major tracts and validated our tractography results based on qualitative visual agreement. RESULTS We identified 9 major connections of the SPL: U-fiber, superior longitudinal fasciculus, inferior longitudinal fasciculus, inferior fronto-occipital fasciculus, middle longitudinal fasciculus, extreme capsule, vertical occipital fasciculus, cingulum, and corpus callosum. There was no significant fiber lateralization detected. CONCLUSION The SPL is an important region implicated in a variety of tasks involving visuomotor and visuospatial integration. Improved understanding of the fiber bundle anatomy elucidated in this study can provide invaluable information for surgical treatment decisions related to this region.

Introduction: Data-driven approaches to transcranial magnetic stimulation (TMS) might yield more consistent and symptom-specific results based on individualized functional connectivity analyses compared to previous traditional approaches due to more precise targeting. We provide a proof of concept for an agile target selection paradigm based on using connectomic methods that can be used to detect patientspecific abnormal functional connectivity, guide treatment aimed at the most abnormal regions, and optimize the rapid development of new hypotheses for future study. Methods:We used the resting-state functional MRI data of 28 patients with medically refractory generalized anxiety disorder to perform agile target selection based on abnormal functional connectivity patterns between the Default Mode Network (DMN) and Central Executive Network (CEN). The most abnormal areas of connectivity within these regions were selected for subsequent targeted TMS treatment by a machine learning based on an anomalous functional connectivity detection matrix. Areas with mostly hyperconnectivity were stimulated with continuous theta burst stimulation and the converse with intermittent theta burst stimulation. An image-guided accelerated theta burst stimulation paradigm was used for treatment.Results: Areas 8Av and PGs demonstrated consistent abnormalities, particularly in the left hemisphere. Significant improvements were demonstrated in anxiety symptoms, and few, minor complications were reported (fatigue (n = 2) and headache (n = 1)). Conclusions:Our study suggests that a left-lateralized DMN is likely the primary functional network disturbed in anxiety-related disorders, which can be improvedThis is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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