---
title: "Electrophysiological signatures of temporal context in the bisection task"
author: "Cemre Baykan, Xiuna Zhu, Artyom Zinchenko, Hermann Mueller, Zhuanghua Shi"
date: "February 2023"
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE, eval = TRUE)
source('dataana.R')
options(mc.cores = parallel::detectCores())
# flag for save figures 
saveFigure = TRUE
```

# Experiment 1- Spacing Effect
## Fit psychometric functions
```{r}
fits_EEG_exp1 = quickpsy(dat_EEG_exp1, x = targetDur, k =RP, prob = .5,
                         grouping = .(cond, SubName),
                         fun = logistic_fun,
                         thresholds = FALSE,bootstrap='none')
```


```{r, fig.cap= 'PSE: Bisection task performance in Experiment 1'}
# plot fitted function
plot(fits_EEG_exp1)+ mytheme
```

```{r}
par_EEG_exp1 <-fits_EEG_exp1$par %>%  dplyr::select(cond, SubName, parn, par) %>%
  pivot_wider(names_from = parn, values_from = par) %>% 
  mutate(jnd = log(3)/p2)

par_EEG_exp1$pse <- par_EEG_exp1$p1
par_EEG_exp1$p2 <-  NULL
par_EEG_exp1$p1 <-  NULL
head(par_EEG_exp1)
```


```{r}
dat_EEG_exp1$cond= factor(dat_EEG_exp1$cond, levels=c("PS","NS"))
fits_EEG_exp1_all = quickpsy(dat_EEG_exp1, x = targetDur, k =RP, 
                             grouping = .(cond),
                             fun = logistic_fun,
                             thresholds = FALSE,bootstrap='none')
fits_EEG_exp1_all
```

## plot averaged 
```{r, fig.cap= 'PSE: Bisection task performance in Experiment 1'}
# plot fitted function
plot_fit_EEG_exp1 <- plot(fits_EEG_exp1_all) + mytheme+
  labs(x = "Target interval (ms)", y = "Proportion of 'long' responses") +
  scale_color_manual(values = colors_plot) +
  scale_fill_manual(values = colors_plot) +
  theme(legend.position = "top", legend.title = element_blank()) 

plot_fit_EEG_exp1
```

```{r}
plot_pse_EEG_exp1_box <- ggplot(par_EEG_exp1%>% mutate(cond = factor(cond, levels = c("PS", "NS"))),aes(x=cond, y=pse, color = cond))+
  geom_boxplot(outlier.shape = NA) + 
  geom_jitter(position=position_jitter(0.2))+
  geom_signif(comparisons=list(c("PS", "NS")), annotations="*", y_position = 1350, tip_length = 0, vjust=0.4, color = 'black') +
  labs(x = "Context", y = "PSE (ms)") +
  coord_cartesian(ylim = c(450,1500)) +
  scale_color_manual(values = colors_plot) +
  scale_fill_manual(values = colors_plot) +
   mytheme + theme(legend.position = "none")

plot_pse_EEG_exp1_box
```

```{r}
plot_jnd_EEG_exp1_box <- ggplot(par_EEG_exp1%>% mutate(cond = factor(cond, levels = c("PS", "NS"))),aes(x=cond, y=jnd, color = cond))+
  geom_boxplot(outlier.shape = NA) + 
  geom_jitter(position=position_jitter(0.2))+
  labs(x = "Context", y = "JND (ms)") +
  coord_cartesian(ylim = c(0,250))+
  scale_color_manual(values = colors_plot) +
  scale_fill_manual(values = colors_plot) + mytheme + theme(legend.position = "none")

plot_jnd_EEG_exp1_box
```

##figure2
```{r}
figure1 <- cowplot::plot_grid(plot_fit_EEG_exp1, plot_pse_EEG_exp1_box, plot_jnd_EEG_exp1_box,  nrow = 1, labels = c("a", "b", "c"), rel_widths = c(4,3,3))

if (saveFigure == TRUE){
  ggsave("figures/figure2.png", figure1, width = 9, height = 4)
}

figure1
```


## Average fitted paramters and plot

```{r}
mpse_EEG_exp1 = par_EEG_exp1%>% 
  group_by(cond) %>%
  dplyr::summarise(m_pse = mean(pse), m_jnd = mean(jnd), n = n(),
                   pse_se = sd(pse)/sqrt(n-1), 
                   jnd_se = sd(jnd)/sqrt(n-1)) 

mpse_EEG_exp1
```


## ANOVA 

```{r}
Anova_EEG_exp1_pse <- ezANOVA(data = par_EEG_exp1, dv= pse, wid=SubName, within=.(cond))
Anova_EEG_exp1_pse
```


```{r}
Anova_EEG_exp1_jnd <- ezANOVA(data = par_EEG_exp1, dv= jnd, wid=SubName, within=.(cond))
Anova_EEG_exp1_jnd
```




# Experiment 2- Frequency Effect
## Fit psychometric functions
```{r}
fits_EEG_exp2_v2 = quickpsy(dat_EEG_exp2, x = targetDur, k =RP, prob = .5,
                            grouping = .(cond, SubName),
                            fun = logistic_fun,
                            thresholds = FALSE, bootstrap = 'none')
```


```{r, fig.cap= 'PSE: Bisection task performance in Experiment 2_v2'}
# plot fitted function
plot(fits_EEG_exp2_v2)+ mytheme
```

```{r}
par_EEG_exp2_v2 <-fits_EEG_exp2_v2$par %>%  dplyr::select(cond, SubName, parn, par) %>%
  pivot_wider(names_from = parn, values_from = par) %>% 
  mutate(jnd = log(3)/p2)

par_EEG_exp2_v2$pse <- par_EEG_exp2_v2$p1
par_EEG_exp2_v2$p2 <-  NULL
par_EEG_exp2_v2$p1 <-  NULL
head(par_EEG_exp2_v2)
```


```{r}
dat_EEG_exp2$cond= factor(dat_EEG_exp2$cond, levels=c("DF","AF"))
fits_EEG_exp2_v2_all = quickpsy(dat_EEG_exp2, x = targetDur, k =RP, 
                                grouping = .(cond),
                                fun = logistic_fun,
                                thresholds = FALSE, bootstrap = 'none')
fits_EEG_exp2_v2_all
```

## plot averaged
```{r, fig.cap= 'PSE: Bisection task performance in Experiment 2_v2'}
# plot fitted function
plot_fit_EEG_exp2_v2 <- plot(fits_EEG_exp2_v2_all) + mytheme+
  labs(x = "Target interval (ms)", y = "Proportion of 'long' responses") +
  scale_color_manual(values = colors_plot) +
  scale_fill_manual(values = colors_plot) +
  theme(legend.position = "top", legend.title = element_blank()) 

plot_fit_EEG_exp2_v2
```

```{r}
plot_pse_EEG_exp2_v2_box <- ggplot(par_EEG_exp2_v2%>% mutate(cond = factor(cond, levels = c("DF", "AF"))),aes(x=cond, y=pse, color = cond))+
  geom_boxplot() + 
  geom_jitter(position=position_jitter(0.2))+
  geom_signif(comparisons=list(c("DF", "AF")), annotations="***", y_position = 1350, tip_length = 0, vjust=0.4, color = 'black') +
  labs(x = "Context", y = "PSE (ms)") +
  coord_cartesian(ylim = c(400,1500)) +
  scale_color_manual(values = colors_plot) +
  scale_fill_manual(values = colors_plot) +mytheme+theme(legend.position = "none")

plot_pse_EEG_exp2_v2_box
```

```{r}
plot_jnd_EEG_exp2_v2_box <- ggplot(par_EEG_exp2_v2%>% mutate(cond = factor(cond, levels = c("DF", "AF"))),aes(x=cond, y=jnd, color = cond))+
  geom_boxplot() + 
  geom_jitter(position=position_jitter(0.2))+
  geom_signif(comparisons=list(c("DF", "AF")), annotations="**", y_position = 215, tip_length = 0, vjust=0.4, color = 'black')+mytheme+
  labs(x = "Context", y = "JND (ms)") +
  coord_cartesian(ylim = c(0,250))+
  scale_color_manual(values = colors_plot) +
  scale_fill_manual(values = colors_plot) + theme(legend.position = "none")

plot_jnd_EEG_exp2_v2_box
```
##figure 4

```{r}
figure4 <- cowplot::plot_grid(plot_fit_EEG_exp2_v2, plot_pse_EEG_exp2_v2_box, plot_jnd_EEG_exp2_v2_box,  nrow = 1, labels = c("a", "b", "c"), rel_widths = c(4,3,3))
if (saveFigure == TRUE){
  ggsave("figures/figure6.png", figure4, width = 9, height = 4)
}
figure4
```
## Average fitted parameters and plot

```{r}
mpse_EEG_exp2_v2 = par_EEG_exp2_v2%>% 
  group_by(cond) %>%
  dplyr::summarise(m_pse = mean(pse), m_jnd = mean(jnd), n = n(),
                   pse_se = sd(pse)/sqrt(n-1), 
                   jnd_se = sd(jnd)/sqrt(n-1)) 
mpse_EEG_exp2_v2
```


## ANOVA 

```{r}
Anova_EEG_exp2_v2_pse <- ezANOVA(data = par_EEG_exp2_v2, dv= pse, wid=SubName, within=.(cond))
Anova_EEG_exp2_v2_pse
```


```{r}
Anova_EEG_exp2_v2_jnd <- ezANOVA(data = par_EEG_exp2_v2, dv= jnd, wid=SubName, within=.(cond))
Anova_EEG_exp2_v2_jnd
```