A common computational and neural anomaly across mouse models of autism
Jean‐Paul NoeliD, Edoardo BalzaniiD, Luigi AcerbiiD, Julius BensoniD, Dora E. AngelakiiD, Daniel BirmaniD, Niccolò BonacchiiD, Matteo CarandiniiD, Joana A. Catarino, Gaelle A. ChapuisiD, Anne K. ChurchlandiD, Yang DaniD, M. Felicia DavatolhaghiD, Peter DayaniD, Eric E. J. DeWittiD, Tatiana A. EngeliD, Mayo FaulkneriD, Ila FieteiD, Laura Freitas-SilvaiD, Berk GerçekiD, Kenneth D. Harris, Michael HäusseriD, Sonja B. HoferiD, Fei HuiD, Julia M. HuntenburgiD, , Cristina SaviniD
Abstract
Computational psychiatry has suggested that humans within the autism spectrum disorder (ASD) inflexibly update their expectations (i.e., Bayesian priors). Here, we leveraged high-yield rodent psychophysics (n = 75 mice), extensive behavioral modeling (including principled and heuristics), and (near) brain-wide single cell extracellular recordings (over 53k units in 150 brain areas) to ask (1) whether mice with different genetic perturbations associated with ASD show this same computational anomaly, and if so, (2) what neurophysiological features are shared across genotypes in subserving this deficit. We demonstrate that mice harboring mutations in Fmr1, Cntnap2, and Shank3B show a blunted update of priors during decision-making. Neurally, the differentiating factor between animals flexibly and inflexibly updating their priors was a shift in the weighting of prior encoding from sensory to frontal cortices. Further, in mouse models of ASD frontal areas showed a preponderance of units coding for deviations from the animals long-run prior, and sensory responses did not differentiate between expected and unexpected observations. These findings demonstrate that distinct genetic instantiations of ASD may yield common neurophysiological and behavioral phenotypes.
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