TY  - JOUR
AU  - Capone, Cristiano
AU  - De Luca, Chiara
AU  - De Bonis, Giulia
AU  - Gutzen, Robin
AU  - Bernava, Irene
AU  - Pastorelli, Elena
AU  - Simula, Francesco
AU  - Lupo, Cosimo
AU  - Tonielli, Leonardo
AU  - Resta, Francesco
AU  - Allegra Mascaro, Anna Letizia
AU  - Pavone, Francesco
AU  - Denker, Michael
AU  - Paolucci, Pier Stanislao
TI  - Simulations approaching data: cortical slow waves in inferred models of the whole hemisphere of mouse
JO  - Communications biology
VL  - 6
IS  - 1
SN  - 2399-3642
CY  - London
PB  - Springer Nature
M1  - FZJ-2023-01645
SP  - 266
PY  - 2023
AB  - The development of novel techniques to record wide-field brain activity enables estimation of data-driven models from thousands of recording channels and hence across large regions of cortex. These in turn improve our understanding of the modulation of brain states and the richness of traveling waves dynamics. Here, we infer data-driven models from high-resolution in-vivo recordings of mouse brain obtained from wide-field calcium imaging. We then assimilate experimental and simulated data through the characterization of the spatio-temporal features of cortical waves in experimental recordings. Inference is built in two steps: an inner loop that optimizes a mean-field model by likelihood maximization, and an outer loop that optimizes a periodic neuro-modulation via direct comparison of observables that characterize cortical slow waves. The model reproduces most of the features of the non-stationary and non-linear dynamics present in the high-resolution in-vivo recordings of the mouse brain. The proposed approach offers new methods of characterizing and understanding cortical waves for experimental and computational neuroscientists.
LB  - PUB:(DE-HGF)16
C6  - 36914748
UR  - <Go to ISI:>//WOS:000948919700001
DO  - DOI:10.1038/s42003-023-04580-0
UR  - https://juser.fz-juelich.de/record/1006405
ER  -