lda (matlab 'fitcdiscr)  (MathWorks Inc)

Journal: eNeuro

Article Title: Hippocampal-Prefrontal θ Coupling Develops as Mice Become Proficient in Associative Odorant Discrimination Learning

doi: 10.1523/ENEURO.0259-22.2022

Figure Lengend Snippet: The accuracy for decoding the contextual identity of the odorant from tPRP decreased in the CaMKIIα knock-out mouse and was correlated with percent correct discrimination. A , B , Examples for one mouse of the time course for the accuracy of odorant identification by LDA trained using CA1 tPRP for the EAPA odor pair. A , β tPRP. B , γ tPRP. (i) WT. (ii) Het. (iii) KO. Shadow: confidence interval, black bar: odorant application. C , D , Bar graphs showing the differences in discriminant accuracy between the different genotypes. C , Accuracy for peak tPRP for (i) θ/β in the hippocampus, (ii) θ/γ in the hippocampus, (iii) θ/β in mPFC, (iv) θ/γ in mPFC. D , Accuracy for through for (i) θ/β in the hippocampus, (ii) θ/γ in the hippocampus, (iii) θ/β in mPFC, (iv) θ/γ mPFC. The bars show the average accuracy, and the points are the accuracy per mouse per odor pair. The vertical bars show the confidence interval. For β tPRP LDA GLM found statistically significant differences between WT and KO for all conditions ( p < 0.001) and between WT and Het for γ trough tPRP ( p < 0.05, 756 observations, 744 df, F statistic = 9.9–34.3, p < 0.001, 6 mice, 8 odor pairs; Extended Data ). Asterisks show significant p values ( p

Article Snippet: Decoding of contextual odorant identity from tPRP values was performed using LDA using MATLAB code as described by .

Techniques: Knock-Out

Journal: eNeuro

Article Title: Hippocampal-Prefrontal θ Coupling Develops as Mice Become Proficient in Associative Odorant Discrimination Learning

doi: 10.1523/ENEURO.0259-22.2022

Figure Lengend Snippet: LDA for decoding the contextual odorant identity from tPRP. A , Example for one mouse for the time course for the accuracy of odorant identity decoding by a LDA algorithm trained using tPRP calculated from CA1 LFP for the EAPA odor pair (i) naive θ/β, θ (ii) proficient θ/β, (iii) naive θ/γ, (iv) proficient θ/γ red: peak, blue: through, black: shuffled, shadow: confidence interval, black bar: odorant application. B , C , Bar graphs showing the differences in decoding accuracy between shuffled, naive, and proficient. B , Accuracy for peak tPRP for (i) θ/β in the hippocampus, (ii) θ/γ in the hippocampus, (iii) θ/β in mPFC, (iv) θ/γ in mPFC. C , Accuracy for through for (i) θ/β in the hippocampus, (ii) θ/γ in the hippocampus, (iii) θ/β in mPFC, (iv) θ/γ mPFC. The bars show the average accuracy, and the points are the accuracy per mouse per odor pair. The vertical bars show the confidence interval. The gray symbols and lines are per mouse averages. For β and γ tPRP for both prefrontal and hippocampus LDA, GLM found statistically significant differences for naive versus proficient and shuffled versus proficient ( p < 0.001, 380 observations, 372 df, F statistic = 355–494, p < 0.001, 6 mice, 8 odor pairs; Extended Data ). For γ tPRP for both prefrontal and hippocampus LDA, GLM found statistically significant differences between peak and trough ( p < 0.05, 380 observations, 372 df, F statistic = 355–494, p < 0.001, 6 mice, 8 odor pairs; Extended Data ). Asterisks show significant p values ( p

Article Snippet: Decoding of contextual odorant identity from tPRP values was performed using LDA using MATLAB code as described by .

Techniques: