|
|
@@ -1,8 +1,8 @@
|
|
|
-# Behavior
|
|
|
+## Behavior
|
|
|
|
|
|
-## Initialization
|
|
|
+### Initialization
|
|
|
|
|
|
-### Load data and files
|
|
|
+#### Load data and files
|
|
|
|
|
|
We set the paths and source the basic setup script:
|
|
|
|
|
|
@@ -19,7 +19,7 @@ if ( basename(here::here()) == "highspeed" ) {
|
|
|
source(file.path(path_root, "code", "highspeed-analysis-setup.R"))
|
|
|
```
|
|
|
|
|
|
-### Signal-detection labeling
|
|
|
+#### Signal-detection labeling
|
|
|
|
|
|
We assign labels from signal detection theory that will be used in one of the analyses below:
|
|
|
|
|
|
@@ -38,7 +38,7 @@ dt_events$sdt_type[
|
|
|
dt_events$key_down == 1 & dt_events$stim_orient == 0] <- "false alarm"
|
|
|
```
|
|
|
|
|
|
-## Stimulus timings
|
|
|
+### Stimulus timings
|
|
|
|
|
|
We calculate the differences between consecutive stimulus onsets:
|
|
|
|
|
|
@@ -126,9 +126,9 @@ dt_odd_iti_mean = dt_events %>%
|
|
|
rmarkdown::paged_table(dt_odd_iti_mean)
|
|
|
```
|
|
|
|
|
|
-## Overview: Behavioral performance
|
|
|
+### Overview: Behavioral performance
|
|
|
|
|
|
-### Mean accuracy
|
|
|
+#### Mean accuracy
|
|
|
|
|
|
We calculate the mean behavioral accuracy across all trials of all three task conditions (slow, sequence, and repetition trials):
|
|
|
|
|
|
@@ -207,7 +207,7 @@ dt_acc_mean = dt_acc %>%
|
|
|
rmarkdown::paged_table(dt_acc_mean)
|
|
|
```
|
|
|
|
|
|
-### Above-chance performance
|
|
|
+#### Above-chance performance
|
|
|
|
|
|
We plot only data of above-chance performers:
|
|
|
|
|
|
@@ -238,7 +238,7 @@ fig_behav_all = ggplot(data = subset(dt_acc, exclude == "no"), aes(
|
|
|
fig_behav_all
|
|
|
```
|
|
|
|
|
|
-### Below chance performance
|
|
|
+#### Below chance performance
|
|
|
|
|
|
We plot data of all participants with below chance performers highlighted in red.
|
|
|
|
|
|
@@ -274,9 +274,9 @@ fig_behav_all_outlier = ggplot(data = dt_acc_mean,
|
|
|
fig_behav_all_outlier
|
|
|
```
|
|
|
|
|
|
-## Slow trials
|
|
|
+### Slow trials
|
|
|
|
|
|
-### Mean accuracy (all trials)
|
|
|
+#### Mean accuracy (all trials)
|
|
|
|
|
|
We calculate the mean accuracy on slow trials (oddball task condition) across all trials in the final sample (only participants who performed above chance):
|
|
|
|
|
|
@@ -316,7 +316,7 @@ fig_behav_odd = ggplot(data = dt_acc_odd, aes(
|
|
|
fig_behav_odd
|
|
|
```
|
|
|
|
|
|
-### Mean accuracy (per run)
|
|
|
+#### Mean accuracy (per run)
|
|
|
|
|
|
We calculate the mean behavioral accuracy on slow trials (oddball task condition) for each of the eight task runs *for each* participant:
|
|
|
|
|
|
@@ -414,7 +414,7 @@ plot_odd_run = ggplot(data = dt_odd_behav_run_mean, mapping = aes(
|
|
|
plot_odd_run
|
|
|
```
|
|
|
|
|
|
-### Misses vs. false alarms
|
|
|
+#### Misses vs. false alarms
|
|
|
|
|
|
We calculate the mean frequency of misses (missed response to upside-down images) and false alarms (incorrect response to upright images):
|
|
|
|
|
|
@@ -492,9 +492,9 @@ plot_odd_sdt = ggplot(data = dt_odd_behav_sdt_sub, mapping = aes(
|
|
|
plot_odd_sdt
|
|
|
```
|
|
|
|
|
|
-## Sequence trials
|
|
|
+### Sequence trials
|
|
|
|
|
|
-### Effect of sequence speed
|
|
|
+#### Effect of sequence speed
|
|
|
|
|
|
We calculate the mean behavioral accuracy on sequence trials for each of the five sequence speeds (inter-stimulus intervals):
|
|
|
|
|
|
@@ -625,7 +625,7 @@ fig_seq_speed = ggplot(data = dt_seq_behav_speed, mapping = aes(
|
|
|
fig_seq_speed
|
|
|
```
|
|
|
|
|
|
-### Effect of target position
|
|
|
+#### Effect of target position
|
|
|
|
|
|
We calculate the mean behavioral accuracy on sequence trials for each of possible serial position of the target stimulus:
|
|
|
|
|
|
@@ -680,9 +680,9 @@ fig_seq_position = ggplot(data = dt_seq_behav_position, mapping = aes(
|
|
|
fig_seq_position
|
|
|
```
|
|
|
|
|
|
-## Repetition trials
|
|
|
+### Repetition trials
|
|
|
|
|
|
-### Mean accuracy
|
|
|
+#### Mean accuracy
|
|
|
|
|
|
We calculate mean behavioral accuracy in repetition trials for each participant:
|
|
|
|
|
|
@@ -854,7 +854,7 @@ summary(lme_rep_behav_condition)
|
|
|
anova(lme_rep_behav_condition)
|
|
|
```
|
|
|
|
|
|
-## Figure Main
|
|
|
+### Figure Main
|
|
|
|
|
|
We plot the figure for the main text:
|
|
|
|
|
|
@@ -869,7 +869,7 @@ ggsave(filename = "highspeed_plot_behavior_horizontal.pdf",
|
|
|
scale = 1, dpi = "retina", width = 7, height = 3, units = "in")
|
|
|
```
|
|
|
|
|
|
-## Figure SI
|
|
|
+### Figure SI
|
|
|
|
|
|
We plot the figure for the supplementary information:
|
|
|
|
|
|
@@ -893,7 +893,7 @@ ggsave(filename = "wittkuhn_schuck_figure_s1.pdf",
|
|
|
dpi = "retina", width = 8, height = 5)
|
|
|
```
|
|
|
|
|
|
-# Participants
|
|
|
+## Participants
|
|
|
|
|
|
We analyze characteristics of the participants:
|
|
|
|
Lennart Wittkuhn