Extended Data Fig. 2: Neural tuning to conspecific sex and behavior.
From: Encoding of female mating dynamics by a hypothalamic line attractor
a, Choice Probability (CP) histograms and percentages of tuned cells for female behaviors. cutoff: CP > 0.7 or <0.3 and >2σ. N = 15 mice. b, Same as a, but for male behavior. c, Schematic showing generalized linear model (GLM) used to predict neural activity from male behaviors and distribution of cvR2 across all mice, or d, both male and female behaviors and distribution of cvR2 across all mice (N = 15 mice). e, Example generalized linear model fits and behavior filters for poorly and well fit neurons. (f-i), Decoder analysis. f, schematic showing linear support vector machine (SVM) decoder trained on frames of male mating behaviors. g, performance of the decoder trained to separate female behavior. Left, performance of decoder trained to separate frames of lordosis versus all remaining frames (***p < 0.001, N = 15 mice, mean decoder performance data: 0.85 ± 0.03, shuffle: 0.49 ± 0.003). Right, performance of decoder trained to separate frames of lordosis versus resistance behaviors (***p < 0.001, N = 15 mice, mean decoder performance data: 0.80 ± 0.03, shuffle: 0.48 ± 0.01). h, Same as f, but showing the decoder hyperplane for separating male behaviors (mount versus intromission) on right. (***p < 0.001). (N = 15 mice). i, performance of decoders trained to separate intromission versus mount (mean decoder performance data: 0.89 ± 0.02, shuffle: 0.49 ± 0.003), intromission versus male sniffing (mean decoder performance data: 0.90 ± 0.02, shuffle: 0.49 ± 0.003), mount versus male sniffing (mean decoder performance data: 0.83 ± 0.02, shuffle: 0.50 ± 0.006) and intromission versus remaining frames male sniffing (***p < 0.001, N = 15 mice, mean decoder performance data: 0.88 ± 0.03, shuffle: 0.48 ± 0.003).
