Fig. 4: Learned odor-reward associations recruit differential networks functionally connected to Tu and aPC. | Nature Communications

Fig. 4: Learned odor-reward associations recruit differential networks functionally connected to Tu and aPC.

From: Striatal hub of dynamic and stabilized prediction coding in forebrain networks for olfactory reinforcement learning

Fig. 4: Learned odor-reward associations recruit differential networks functionally connected to Tu and aPC.The alternative text for this image may have been generated using AI.

a Analogous to Fig. 3b. Task-based functional connectivity was examined between regions of the olfactory association-learning network (OB, AON, aPC, Tu, NAc, dStr, OFC, mPFC, and aIC). b, c Task-based functional connectivity between (b) Tu and the other regions for CS and US for each trial type. Pearson correlation coefficients between the region-wise beta-series were calculated for each session (n = 51 across 18 animals). The group-level significance was tested using a one-sample t test on the Fisher z-transformed correlation coefficients (P < 0.05, Bonferroni-corrected for multiple comparisons). Pairwise correlations that did not reach significance are indicated by empty boxes. The connectivity between Tu and higher-order regions depended on the respective CS. c Same as (b) showing aPC connectivity. d, e Analogous analysis as in (b) and (c), but voxel-wise. Group-level maps showing seed-based functional connectivity for CS100 in (d) Tu and in (e) aPC (n = 51 sessions in 18 animals). Significance threshold was set to P < 0.025, FDR-corrected for two-sided testing. Red color spectrum indicates a positive correlation, while blue color indicates anti-correlation. Seed regions marked in black. A composite mask of all ROIs listed in (a) was used for this analysis. See Supplementary Fig. 5a, b for the complete analysis performed on different task conditions.

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