Figure 3: Cross-species representation learning resolves conserved epilepsy signatures and model-specific patient heterogeneity. A, Schematic of the cross-species framework, in which human EEG from TEMPLE/TUH is aligned independently with three mechanistically distinct mouse epilepsy models (AY9944, 4-AP and PTZ). B, Schematic of the seizure-specific alignment objective, jointly organizing mouse and human EEG ictal periods to compare shared features. C, Heatmap of cross-species associations between the three mouse epilepsy models and clinically annotated human seizure types. Values indicate standardized model-specific associations, with positive and negative values shown in red and blue, respectively. D, Frequency-dependent changes in spectral power during ictal relative to non-ictal activity in PTZ, AY9944, and 4-AP mice. Pairwise Pearson correlation coefficients between the model-specific spectral profiles are shown above the plot. E, Unified cross-species disease space showing the relative positions of healthy and epileptic human EEG and the three mouse models, illustrating a conserved disease direction together with model-specific structure. F, Heatmap of patient-level affinities to AY9944, PTZ, and 4-AP across 96 human epilepsy patients. Each column represents an individual patient, and values indicate affinity relative to patient controls. G, Ternary plot of the relative affinities of individual human epilepsy patients to the three mouse models. Each point represents one patient, with the three vertices corresponding to AY9944, PTZ, and 4-AP.### 2.3 Cross-species representation learning tracks clinical drug efficacy from mouse neural dynamics in epilepsy models 出处: Cross-species representation learning aligns mouse and human neural dynamics and tracks clinical drug efficacy（arXiv）Figure 2: Conventional EEG seizure readouts track human clinical efficacy worse than the cross-species biomarker. (A–E) Each panel plots one mouse EEG readout against frozen human efficacy (ordinal, −-1 to 4) for the same 10 drug–model arms: 5 in 4-AP (triangles), 3 in AY9944 (circles) and 2 in PTZ (squares). Colours mark the drug, as in Figure [4](https://arxiv.org/html/#S2.F4 "Figure 4 ‣ 2.3 Cross-species representation learning tracks clinical drug efficacy from mouse neural dynamics in epilepsy models ‣ 2 Results ‣ Cross-species representation learning aligns mouse and human neural dynamics and tracks clinical drug efficacy"). Each readout was averaged per arm over treated animals and z-scored within model family (4-AP; AY9944 + PTZ). Signs are set so that higher values always mean greater predicted rescue. (A) Number of seizure episodes per mouse in the 30 min after the convulsant. Episodes were detected algorithmically as ≥\\geq4σ\\sigma above the animal’s own pre-drug baseline, lasting ≥\\geq2 s. (B) Fraction of 1 s epochs exceeding 4σ\\sigma of the animal’s own baseline. (C) Mean EEG amplitude shift relative to the animal’s own pre-drug baseline. (D) Mouse-only control: health-directed displacement computed from mouse recordings alone, with no human data. (E) Percentage of the 30 min epoch spent in detected seizures. Grey lines are least-squares fits, shown only as a guide. Insets give the pooled Spearman correlation and PP from a two-sided exact blocked permutation test within the experimental family (all 14,400 relabellings). They also give the within-family correlations. (F) Pooled Spearman correlation of each readout with human efficacy under this identical test, with the cross-species biomarker from Figure [4](https://arxiv.org/html/#S2.F4 "Figure 4 ‣ 2.3 Cross-species representation learning tracks clinical drug efficacy from mouse neural dynamics in epilepsy models ‣ 2 Results ‣ Cross-species representation learning aligns mouse and human neural dynamics and tracks clinical drug efficacy") shown for reference (blue). \*PP << 0.05. None of the EEG readouts reached significance. The best, seizure count, reached ρ\\rho = +0.63 (PP = 0.062). The cross-species biomarker reached ρ\\rho = +0.87 (PP = 0.0039). (G) Pooled Spearman correlation with human efficacy as a function of the number of animals per arm, computed on random subsets of animals within each arm. Agreement with human efficacy increases with group size for the cross-species biomarker but not for the conventional readouts. 出处: Cross-species representation learning aligns mouse and human neural dynamics and tracks clinical drug efficacy（arXiv）
