Figure 7:
Inference of a four-population model with 36 free parameters. (A) Model represented E (blue) and I (red) populations from layers L2/3 and L4 of a cortical column. During training, only L4 populations received external sinusoidal input. The homogeneous microscopic model was used to generate data. (B) The mesoscopic model matches aggregate microscopic dynamics (“True – micro”), both when using theoretical (“Theory – meso”) and inferred parameters (“Inferred – meso”). In contrast to the previous section, correlation and RMSE scores are reported separately for each population; they are computed from 60 realizations of each models.

Inference of a four-population model with 36 free parameters. (A) Model represented E (blue) and I (red) populations from layers L2/3 and L4 of a cortical column. During training, only L4 populations received external sinusoidal input. The homogeneous microscopic model was used to generate data. (B) The mesoscopic model matches aggregate microscopic dynamics (“True – micro”), both when using theoretical (“Theory – meso”) and inferred parameters (“Inferred – meso”). In contrast to the previous section, correlation and RMSE scores are reported separately for each population; they are computed from 60 realizations of each models.

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