From fc810cbd3fb81c45865df2fa1039ce423f0a6563 Mon Sep 17 00:00:00 2001 From: Laura Porta Date: Thu, 12 Dec 2024 11:49:20 +0000 Subject: [PATCH] Update aritmetic_sum.m --- scripts/aritmetic_sum.m | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/scripts/aritmetic_sum.m b/scripts/aritmetic_sum.m index ca3ae87..e8ef55d 100644 --- a/scripts/aritmetic_sum.m +++ b/scripts/aritmetic_sum.m @@ -1,5 +1,7 @@ % Fit a linear model on the passive same luminance dataset, -% on the equation : VT = b_0 + b_1 * T_Vstatic + b_2 * V +% on the equation : FC_predicted(VF + T) = b_0 + b_1 * FC(T_VS) + b_2 * FC(V) +% where FC(x) is the measured fold change per trial type (calculated as explained below) +% and FC_predicted(x) is the fold change as predicted by the model for a given condition. % How are fold changes calculated? % M is the 3D matrix of motion responses, with shape trial_types x clusters x trials @@ -15,7 +17,7 @@ % initialization experiment_groups = 'passive_same_luminance'; -trial_types = {'T_Vstatic', 'V', 'VT'}; +trial_types = {'T_Vstatic', 'V', 'VT'}; % T_Vstatic represents T_VS and VT is VF + T restricted = true; % If restricted true, select only for clusters that are positively or negatively modulated ctl = RC2Analysis();