Poster Slam Session A, Tuesday, August 20, 2019, 10:00 – 10:15 am, Finlandia Hall, Michal Ben-Shachar
Grey and white matter correlates of verbal and non-verbal working memory
Dimitrios Kasselimis1,2, Georgia Angelopoulou1, Panagiotis Simos2, Dimitrios Tsolakopoulos1, Georgios Papageorgiou1, Michel Rijntjes3, Marco Reisert4, Georgios Velonakis5, Efstratios Karavasilis5, Nikolaos Kelekis5, Cornelius Weiller6, Michael Petrides7, Constantin Potagas1;1Neuropsychology and Language Disorders Unit, 1st Neurology Department, Eginition Hospital, Faculty of Medicine, National and Kapodistrian University of Athens, 2Division of Psychiatry and Behavioral Sciences, School of Medicine, University of Crete, 3Department of Neurology and Neurophysiology, University Hospital Freiburg, 4Medical Physics, Department of Diagnostic Radiology, Faculty of Medicine, University Freiburg, 5Radiology and Medical Imaging Research Unit, University of Athens, 6Department of Neurology, University Medical Center, University of Freiburg, 7Montreal Neurological Institute, Department of Neurology and Neurosurgery and Department of Psychology, McGill University
Introduction Several studies indicate an association between Working Memory (WM) and language functions (e.g. Potagas, Kasselimis, and Evdokimidis, 2011). However, the hypothesized common neurological substrate has not been yet established, either through imaging data derived from healthy subjects or based on evidence from aphasia. The purpose of the present study is to investigate possible associations between WM performance and grey and white matter indices of the left perisylvian region, which is traditionally considered to support language functions. Methods 60 healthy participants (33 women), 19-65 years old, with 6 to 24 years of formal schooling were assessed with the Digit Span and the Corsi Block-tapping Task. 3D T1-weighted and 30-directional DTI protocol were acquired for all participants on a 3T Philips Achieva-Tx MR scanner (Philips, Best, The Netherlands), equipped with an eight-channel head coil. Whole brain cortical reconstruction of T1 MR images was first accomplished, using the automated pipeline of FreeSurfer 6.0.0 (http://www.surfter.nmr.mgh.harvard.edu/) (Fischl and Dale 2000). We ran separate whole brain general linear models for WM scores and three brain metrics (surface area, cortical thickness, grey matter volume). Monte Carlo simulations were used to correct all vertex-wise results at an individual vertex level of p < 0.05 (Hagler, Saygin, & Sereno, 2006). White matter fibers were reconstructed using the global tractography approach implemented in DTI&Fibertools (Reisert et al., 2011). Results Whole brain general linear model analysis revealed significant associations between verbal WM scores and thickness of the pars opercularis (p= 0.0136), as well as surface area of the angular gyrus and the superior temporal sulcus (p= 0.0122). Corsi performance was associated with insula’s surface area (p= 0.049), insula and temporal pole’s grey matter volume (p= 0.0001). Discussion Even though there are several functional brain imaging studies focusing on associations between specific brain regions and performance on WM tasks (Wager and Smith, 2003), no study thus far has investigated structural correlates of WM in healthy participants. Our findings show that anatomical indices such as cortical thickness and surface area may play a role in cognition, and more specifically in temporary storage and manipulation of verbal and visuospatial information. Interestingly, clusters significantly associated with WM performance, included inferior frontal, inferior parietal and superior temporal regions of the left hemisphere, which have been shown to be involved in the perisylvian language network (Petrides, 2013). Overall, our findings stress the importance of brain structural variables in cognitive performance, and further support the notion of a relationship between language functions and WM at an anatomical level. The involvement of white matter tracts is also discussed.
Themes: Phonology and Phonological Working Memory, Control, Selection, and Executive Processes
Method: Other
Poster A79