End-to-end deep learning approach to mouse behavior classification from cortex-wide calcium imaging
Fig 6
The forelimb and hindlimb areas of the somatosensory cortex contribute to behavioral state classification.
(A) The absolute SHAP values at each ROI during the input window across all GRU decoders (50 ROIs × 31 frames (−0.5 ~ 0.5 s) on 20 models average). (B) The absolute SHAP values for all frames at each ROI in GRU decoders with preprocessing data (GRU) and randomly shuffled data (Random). *P < 0.05, **P < 0.01, ***P < 0.001, Wilcoxon rank-sum test with Holm correction, n = 20 models. See S2 Fig for ROIs 1–50. (C) Red ovals indicate the position of the somatosensory cortex anterior forelimb and hindlimb areas (ROIs 6, 8, 31, and 33). (D) Decoder performance using fluorescent signals from all cortical areas (All), somatosensory cortex anterior forelimb and hindlimb areas (FLa&HLa, ROIs 6, 8, 31, and 33), and the other 46 ROIs (Other). ***P < 0.001, Wilcoxon rank-sum test with Holm correction, n = 20 models. (E) The ROIs were divided into five parts: motor areas (M2&M1, ROIs 1–4 and 26–29), somatosensory limb areas (FL&HL, ROIs 6–9 and 31–34), parietal and retrosplenial areas (PT&RS, ROIs 14–17 and 39–42), primary visual and visual medial areas (V1&Vm, ROIs 18–21 and 43–46), and visual lateral and auditory area (Vl&A1, ROIs 22–25 and 47–50). (F) Decoder performance using fluorescent signals from M2&M1, FL&HL, PT&RS, V1&Vm, and Vl&A1. ***P < 0.001, Wilcoxon rank-sum test with Holm correction, n = 20 models.