Investigating the synaptic correlates of Alzheimer’s disease in the retrosplenial cortex of 5xFAD mice

Strategy updating is one of the recent roles assigned to the retrosplenial cortex (RSC). Studies have shown that lesions or inactivation of RSC cause impairment in exploring and learning new alternative options when previous ones were available but no longer appropriate, suggesting its importance for set-shifting behaviors1. Building on previous evidence of impaired reversal learning in 6-month-old 5xFAD mice2, this study focuses on uncovering the synaptic correlates of reversal learning in the RSC in the context of AD. Therefore, we use a set-shifting task that challenges the animals to develop a new behavioral strategy by responding to a stimulus that previously had a different spatial association with the reward3. So, the mice have to identify the change and update their behavioral strategy4,5. To provide a sub-cellular understanding of Alzheimer’s disease in 5xFAD mice, we also use in vivo two-photon microscopy to correlate behavioral deficits with spine dynamics and neuronal or dendritic activity. Prior studies have shown that Alzheimer’s is associated with a low synaptic turnover rate6, NMDAR loss, dendritic atrophy7, and dendritic spine loss in clusters8. Thus, we hypothesize that reversal learning will be gradually impaired in 5xFAD mice (as a function of age) and this impairment will be dependent on the extent of spine loss. This project aims to shed new light on the role of dendritic/synaptic alterations in RSC neurons in the early stages of AD and to bridge the scientific gap in understanding the biological mechanisms underlying adaptive behavior in 5XFAD mice.A/AReference1M. Serrano, M. Tripodi, and P. Caroni, Current Biology 2022, 32(16), 3477-3492.e5..2T.P. O’Leary, and R.E. Brown, Genes, Brain and Behavior 2022.3M. Merlini, V.A. Rafalski, P.E. Rios Coronado, T.M. Gill, M. Ellisman, G. Muthukumar, K.S. Subramanian, J.K. Ryu, C.A. Syme, D. Davalos, W.W. Seeley, L. Mucke, R.B. Nelson, and K. Akassoglou, Neuron 2019, 101(6), 1099-1108.e6.4D. A. Hamilton & J. L. Brigman, Genes, Brain and Behavior 2015, 14(1), 4–21.5J. M. Heisler, J. Morales, J. J. Donegan, J. D. Jett, L. Redus, & J. C. O’connor, Journal of Visualized Experiments 2015, 96, 2–7. 6S.E. Crowe, and G.C.R. Ellis-Davies, Brain Structure and Function 2013, 219(2), 571–580.7S.E. Crowe, and G.C.R. Ellis-Davies, Journal of Comparative Neurology 2013, 521(10), Spc1–Spc1.8M. Mijalkov, G. Volpe, I. Fernaud-Espinosa, J. DeFelipe, J.B. Pereira, and P. Merino-Serrais, Scientific Reports 2021, 11(1), 12350.