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Research Objectives To explore the relationship between attention/working memory (WM) performance and grey matter volume in the dorsal attention network (DAN), a neural network in the brain that supports encoding and maintenance of external information. Design Observational. Setting Data obtained from the Parkinson's Progression Marker Initiative (PPMI; www.ppmi-info.org ), an international longitudinal multisite study. Participants Participants with persistent WM impairment (n= 10) and persistent normal WM performance (n=10) were compared. WM was measured using the Letter Number Sequencing (LNS) test. Persistent impairment was defined by a standardized test score of 8 or less for 4 consecutive years since baseline imaging. Normal WM performance was defined by a standardized test score of 10 or more for 4 consecutive years since baseline imaging. Groups were matched on sex, age, years of education, and disease duration. Interventions Not Applicable. Main Outcome Measures Grey matter volume was measured using voxel-based morphometry (VBM) through SPM12 and CAT12. Region of interest analysis within the DAN (Schaeffer et al., 2018 100-parcel atlas), was conducted. Whole brain cluster analysis was conducted for confirmatory evidence. Significant clusters within a DAN mask (Schaeffer et al., 2018 100-parcel atlas) are reported with a FDR (p=0.05). Results For ROI analysis, grey matter atrophy in the bilateral visuomotor cortex (p=0.005), bilateral intraparietal sulcus (p=0.04), and right superior parietal lobule (p=0.021) was found in the impaired WM group compared to the normal WM group. Between groups, differences in several clusters within the DAN masks were observed. Conclusions These promising preliminary findings support the notion that changes in grey matter volume within cognitive neural networks, such as the DAN, can be a biomarker for decline in cognitive function, as well as treatment responsiveness in people living with PD. Author(s) Disclosures None.