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Learning in logopenic variant Primary Progressive Aphasia: an EEG investigation
Poster Session B, Friday, October 25, 10:00 - 11:30 am, Great Hall 3 and 4
Kyriaki Neophytou1, Panteleimon Chriskos2, Jessica Gallegos1, Nathan Crone1, Panagiotis D. Bamidis2, Kyrana Tsapkini1,3; 1Johns Hopkins School of Medicine, 2Aristotle University of Thessaloniki, 3Johns Hopkins University
Introduction: The logopenic variant of Primary Progressive Aphasia (lvPPA) is primarily characterized by repetition and naming deficits. In addition, previous research has shown that learning disabilities occur more frequently in lvPPA compared to the other PPA variants (Miller et al., 2013). However, learning abilities in this group remain understudied. The primary area of atrophy in lvPPA is the left parietal lobe, while, usually, the underlining pathology is Alzheimer’s Disease (AD) (Gorno-Tempini et al., 2008). In AD there is evidence of increased delta rhythm in EEG signal during resting-state (Babiloni et al., 2013; Huang et al., 2000; Kwak, 2006). Although delta rhythm is the main characteristic of slow wave sleep, relationships between delta rhythm have also been reported during cognitive tasks across populations (Başar et al., 2001; Knyazev, 2007). Regarding the relationship of delta rhythm and learning abilities, increased delta rhythm has been reported in children with learning disabilities (Jäncke & Alahmadi, 2016; Martínez-Briones et al., 2020). EEG studies in PPA are scarce (Chriskos et al., Submitted; Moral-Rubio et al., 2021; Utianski et al., 2019). To the best of our knowledge, this is the first investigation of the relationship between resting-state EEG signal and cognitive processing in PPA, specifically of the delta rhythm and its relationship to learning abilities in lvPPA. Methods: Participants were 9 patients with lvPPA (mean age=68.3 years, SD=9.5). Learning ability was assessed using the total score (i.e., the sum of trials 1-5) of the Rey Auditory Verbal Learning Test (RAVLT), which has been found to be a significant predictor in the early diagnosis of AD (Moradi et al., 2017). Delta rhythms (0.5-4 Hz) were extracted from eyes-closed resting-state 8-channel EEG recordings, and analyzed both per channel and as an average across all channels. The statistical analysis included a set of multiple linear regressions with RAVLT total score as the dependent variable and delta rhythm as predictor. Disease severity and age were also included as covariates. In total, 9 regression models were used: one for the average delta rhythm across all channels, and one for every channel separately. Results: The analysis showed a statistically significant relationship between the RAVLT total score and the average delta rhythm across all channels (p=0.006; R2=0.65), such that the higher the delta rhythm, the lower the learning performance. Significant relationships in the same direction were also found with the delta rhythm of every channel separately, but after Bonferroni correction, only channel P5 (i.e., left parietal lobe) showed a statistically significant effect (p=0.026; R2=0.68). Conclusion: These results show, for the first time, a relationship between delta rhythm and learning ability in PPA, specifically in lvPPA. The significant association of learning abilities with the delta rhythm in the left parietal lobe in lvPPA suggests that this area could be an appropriate neuromodulation target for improving learning abilities. Finally, our findings highlight the importance of evaluating the power of delta rhythm in lvPPA, which might relate to AD being the underlying pathology in this population, and can potentially serve as an electrophysiological biomarker.
Topic Areas: Disorders: Acquired,