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experiment.js
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experiment.js
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/* ************************************ */
/* Define helper functions */
/* ************************************ */
function evalAttentionChecks() {
var check_percent = 1
if (run_attention_checks) {
var attention_check_trials = jsPsych.data.getTrialsOfType('attention-check')
var checks_passed = 0
for (var i = 0; i < attention_check_trials.length; i++) {
if (attention_check_trials[i].correct === true) {
checks_passed += 1
}
}
check_percent = checks_passed / attention_check_trials.length
}
return check_percent
}
function assessPerformance() {
/* Function to calculate the "credit_var", which is a boolean used to
credit individual experiments in expfactory.
*/
var experiment_data = jsPsych.data.getTrialsOfType('stop-signal');
var missed_count = 0;
var trial_count = 0;
var rt_array = [];
var rt = 0;
var avg_rt = -1;
//record choices participants made
var choice_counts = {}
choice_counts[-1] = 0
for (var k = 0; k < choices.length; k++) {
choice_counts[choices[k]] = 0
}
for (var i = 0; i < experiment_data.length; i++) {
trial_count += 1
rt = experiment_data[i].rt
key = experiment_data[i].key_press
choice_counts[key] += 1
if (rt == -1) {
missed_count += 1
} else {
rt_array.push(rt)
}
}
//calculate average rt
if (rt_array.length !== 0) {
avg_rt = math.median(rt_array)
} else {
avg_rt = -1
}
//calculate whether response distribution is okay
var responses_ok = true
Object.keys(choice_counts).forEach(function(key, index) {
if (choice_counts[key] > trial_count * 0.85) {
responses_ok = false
}
})
credit_var = (avg_rt > 200) && responses_ok
jsPsych.data.addDataToLastTrial({"credit_var": credit_var})
}
var randomDraw = function(lst) {
var index = Math.floor(Math.random() * (lst.length))
return lst[index]
}
var getPracticeFeedback = function() {
return '<div class = centerbox><p class = block-text>' + practice_feedback_text + '</p></div>'
}
var getSelectiveFeedback = function(){
var data_length = 0
var global_trial = jsPsych.progress().current_trial_global
if(jsPsych.data.getDataByTrialIndex(global_trial - 5).exp_stage == 'practice'){
data_length = 60
}else if (jsPsych.data.getDataByTrialIndex(global_trial - 5).exp_stage == 'test'){
data_length = 100
}
var start_cut = global_trial - data_length
var numIgnore = 0
var ignoreRespond = 0
for (var i = 0; i < data_length; i++){
if(jsPsych.data.getDataByTrialIndex(start_cut + i).trial_id == 'stim' && jsPsych.data.getDataByTrialIndex(start_cut + i).condition == 'ignore'){
numIgnore = numIgnore + 1
if(jsPsych.data.getDataByTrialIndex(start_cut + i).rt != -1){
ignoreRespond = ignoreRespond + 1
}
}
}
var ignoreRespond_percent = ignoreRespond / numIgnore
if (ignoreRespond_percent <= selective_threshold){
selective_feedback_text =
'<p class = block-text> You have been stopping to both the blue and orange stars. Please make sure to <strong>stop your response only when the blue star appears.</strong></p><p class = block-text>Press <strong>enter</strong> to view block feedback.'
} else {
selective_feedback_text =
'<p class = block-text>Press<strong> enter </strong>to view block feedback.'
}
return '<div class = centerbox>' + selective_feedback_text + '</p></div>'
}
/* After each test block let the subject know their average RT and accuracy. If they succeed or fail on too many stop signal trials, give them a reminder */
var getTestFeedback = function() {
var data = test_block_data
var rt_array = [];
var sum_correct = 0;
var go_length = 0;
var stop_length = 0;
var num_responses = 0;
var successful_stops = 0;
for (var i = 0; i < data.length; i++) {
if (data[i].SS_trial_type != 'stop') {
go_length += 1
if (data[i].rt != -1) {
num_responses += 1
rt_array.push(data[i].rt);
if (data[i].key_press == data[i].correct_response) {
sum_correct += 1
}
}
} else {
stop_length += 1
if (data[i].rt == -1) {
successful_stops += 1
}
}
}
var average_rt = -1;
if (rt_array.length !== 0) {
average_rt = math.median(rt_array);
rtMedians.push(average_rt)
}
var rt_diff = 0
if (rtMedians.length !== 0) {
rt_diff = (average_rt - rtMedians.slice(-1)[0])
}
var GoCorrect_percent = sum_correct / go_length;
var missed_responses = (go_length - num_responses) / go_length
var StopCorrect_percent = successful_stops / stop_length
stopAccMeans.push(StopCorrect_percent)
var stopAverage = math.mean(stopAccMeans)
test_feedback_text = "<br>Done with a test block. Please take this time to read your feedback and to take a short break! Press <strong>enter</strong> to continue after you have read the feedback."
test_feedback_text += "</p><p class = block-text><strong>Average reaction time: " + Math.round(average_rt) + " ms. Accuracy for non-blue star trials: " + Math.round(GoCorrect_percent * 100)+ "%</strong>"
if (average_rt > RT_thresh || rt_diff > rt_diff_thresh) {
test_feedback_text +=
'</p><p class = block-text>You have been responding too slowly, please respond to each shape as quickly and as accurately as possible.'
}
if (missed_responses >= missed_response_thresh) {
test_feedback_text +=
'</p><p class = block-text><strong>We have detected a number of trials that required a response, where no response was made. Please ensure that you are responding to each shape, unless a blue star appears.</strong>'
}
if (GoCorrect_percent < accuracy_thresh) {
test_feedback_text += '</p><p class = block-text>Your accuracy is too low. Remember, the correct keys are as follows: ' + prompt_text
}
if (StopCorrect_percent < (0.5-stop_thresh) || stopAverage < 0.45){
test_feedback_text +=
'</p><p class = block-text><strong>Remember to try and withhold your response when you see a blue stop signal.</strong>'
} else if (StopCorrect_percent > (0.5+stop_thresh) || stopAverage > 0.55){
test_feedback_text +=
'</p><p class = block-text><strong>Remember, do not slow your responses to the shape to see if a blue star will appear before you respond. Please respond to each shape as quickly and as accurately as possible.</strong>'
}
return '<div class = centerbox><p class = block-text>' + test_feedback_text + '</p></div>'
}
/* Staircase procedure. After each successful stop, make the stop signal delay longer (making stopping harder) */
var updateSSD = function(data) {
if (data.condition == 'stop') {
if (data.rt == -1 && SSD < 850) {
SSD = SSD + 50
} else if (data.rt != -1 && SSD > 0) {
SSD = SSD - 50
}
}
}
var getSSD = function() {
return SSD
}
/* These methods allow NoSSPractice and SSPractice to be randomized for each iteration
of the "while" loop */
var getNoSSPracticeStim = function() {
practice_trial_data = NoSS_practice_list.data.pop()
return NoSS_practice_list.stimulus.pop()
}
var getNoSSPracticeData = function() {
return practice_trial_data
}
var getSSPracticeStim = function() {
practice_stop_trial = practice_stop_trials.pop()
practice_trial_data = practice_list.data.pop()
practice_trial_data.condition = practice_stop_trial
return practice_list.stimulus.pop()
}
var getSSPracticeData = function() {
return practice_trial_data
}
var getSSPractice_trial_type = function() {
if (practice_stop_trial == 'ignore') {
return 'stop'
} else {
return practice_stop_trial
}
}
var getSSPractice_stop_signal = function() {
if (practice_stop_trial == 'ignore') {
return ignore_signal
} else {
return stop_signal
}
}
var getInstructFeedback = function() {
return '<div class = centerbox><p class = center-block-text>' + feedback_instruct_text +
'</p></div>'
}
/* ************************************ */
/* Define experimental variables */
/* ************************************ */
// generic task variables
var run_attention_checks = false
var attention_check_thresh = 0.65
var sumInstructTime = 0 //ms
var instructTimeThresh = 0 ///in seconds
var credit_var = true
// task specific variables
// Define and load images
var prefix = 'images/'
var images = [prefix + 'rectangle.png', prefix + 'oval.png', prefix + 'trapezoid.png', prefix +
'moon.png'
]
jsPsych.pluginAPI.preloadImages(images);
/* Stop signal delay in ms */
var SSD = 250
var stop_signal =
'<div class = stopbox><div class = centered-shape id = stop-signal></div><div class = centered-shape id = stop-signal-inner></div></div>'
var ignore_signal =
'<div class = stopbox><div class = centered-shape id = ignore-signal></div><div class = centered-shape id = ignore-signal-inner></div></div>'
/* Instruction Prompt */
var possible_responses = [
["M key", 77],
["Z key", 90]
]
var choices = [possible_responses[0][1], possible_responses[1][1]]
var correct_responses = jsPsych.randomization.shuffle([possible_responses[0], possible_responses[0],
possible_responses[1], possible_responses[1]
])
var tab = '    '
var prompt_text = '<ul list-text><li><img class = prompt_stim src = ' + images[0] + '></img>' + tab +
correct_responses[0][0] + '</li><li><img class = prompt_oval_stim src = ' + images[1] + '></img>' + tab +
correct_responses[1][0] + ' </li><li><img class = prompt_stim src = ' + images[2] + '></img> ' +
'   ' + correct_responses[2][0] +
' </li><li><img class = prompt_stim src = ' + images[3] + '></img>' + tab + correct_responses[3][0] +
' </li></ul>'
/* Global task variables */
var current_trial = 0
var rtMedians = []
var stopAccMeans =[]
var RT_thresh = 1000
var rt_diff_thresh = 75
var selective_threshold = 0.6;
var missed_response_thresh = 0.1
var accuracy_thresh = 0.8
var stop_thresh = 0.2
var practice_repetitions = 1
var practice_repetition_thresh = 5
var test_block_data = [] // records the data in the current block to calculate feedback
var NoSSpractice_block_len = 12
var practice_block_len = 30
var test_block_len = 50
var numblocks = 6
/* Define Stims */
var stimulus = [{
stimulus: '<div class = shapebox><img class = stim src = ' + images[0] + '></img></div>',
data: {
correct_response: correct_responses[0][1],
trial_id: 'stim'
}
}, {
stimulus: '<div class = shapebox><img class = stim src = ' + images[1] + '></img></div>',
data: {
correct_response: correct_responses[1][1],
trial_id: 'stim'
}
}, {
stimulus: '<div class = shapebox><img class = stim src = ' + images[2] + '></img></div>',
data: {
correct_response: correct_responses[2][1],
trial_id: 'stim'
}
}, {
stimulus: '<div class = shapebox><img class = stim src = ' + images[3] + '></img></div>',
data: {
correct_response: correct_responses[3][1],
trial_id: 'stim'
}
}]
var practice_trial_data = '' //global variable to track randomized practice trial data
var NoSS_practice_list = jsPsych.randomization.repeat(stimulus, NoSSpractice_block_len / 4, true)
var practice_list = jsPsych.randomization.repeat(stimulus, practice_block_len / 4, true)
var practice_stop_trials = jsPsych.randomization.repeat(['stop', 'ignore', 'go',
'go', 'go'], practice_block_len / 5)
//setup blocks
var blocks = []
for (i = 0; i < numblocks; i++) {
blocks.push(jsPsych.randomization.repeat(stimulus, test_block_len / 4, true))
}
/* ************************************ */
/* Set up jsPsych blocks */
/* ************************************ */
// Set up attention check node
var attention_check_block = {
type: 'attention-check',
data: {
trial_id: "attention_check"
},
timing_response: 180000,
response_ends_trial: true,
timing_post_trial: 200
}
var attention_node = {
timeline: [attention_check_block],
conditional_function: function() {
return run_attention_checks
}
}
//Set up post task questionnaire
var post_task_block = {
type: 'survey-text',
data: {
trial_id: "post task questions"
},
questions: ['<p class = center-block-text style = "font-size: 20px">Please summarize what you were asked to do in this task.</p>',
'<p class = center-block-text style = "font-size: 20px">Do you have any comments about this task?</p>'],
rows: [15, 15],
columns: [60,60]
};
/* define static blocks */
var end_block = {
type: 'poldrack-text',
timing_response: 180000,
data: {
trial_id: "end",
exp_id: 'stim_selective_stop_signal'
},
text: '<div class = centerbox><p class = center-block-text>Thanks for completing this task!</p><p class = center-block-text>Press <strong>enter</strong> to continue.</p></div>',
cont_key: [13],
timing_post_trial: 0,
on_finish: assessPerformance
};
var feedback_instruct_text =
'Welcome to the experiment. This experiment will take about 22 minutes. Press <strong>enter</strong> to begin.'
var feedback_instruct_block = {
type: 'poldrack-text',
data: {
trial_id: "instruction"
},
cont_key: [13],
text: getInstructFeedback,
timing_post_trial: 0,
timing_response: 180000
};
/// This ensures that the subject does not read through the instructions too quickly. If they do it too quickly, then we will go over the loop again.
var instructions_block = {
type: 'poldrack-instructions',
data: {
trial_id: "instruction"
},
pages: [
'<div class = centerbox><p class = block-text>In this task you will see black shapes appear on the screen one at a time. You will respond to them by pressing the "Z" and "M" keys.</p></div>',
'<div class = centerbox><p class = block-text>Only one key is correct for each shape. The correct keys are as follows:' + prompt_text +
'</p><p class = block-text>These instructions will remain on the screen during practice, but will be removed during the test phase.</p><p class = block-text>You should respond as quickly and accurately as possible to each shape.</p></div>',
],
allow_keys: false,
show_clickable_nav: true,
timing_post_trial: 1000
};
var instruction_node = {
timeline: [feedback_instruct_block, instructions_block],
/* This function defines stopping criteria */
loop_function: function(data) {
for (i = 0; i < data.length; i++) {
if ((data[i].trial_type == 'poldrack-instructions') && (data[i].rt != -1)) {
rt = data[i].rt
sumInstructTime = sumInstructTime + rt
}
}
if (sumInstructTime <= instructTimeThresh * 1000) {
feedback_instruct_text =
'Read through instructions too quickly. Please take your time and make sure you understand the instructions. Press <strong>enter</strong> to continue.'
return true
} else if (sumInstructTime > instructTimeThresh * 1000) {
feedback_instruct_text =
'Done with instructions. Press <strong>enter</strong> to continue.'
return false
}
}
}
var fixation_block = {
type: 'poldrack-single-stim',
stimulus: '<div class = centerbox><div class = fixation>+</div></div>',
is_html: true,
choices: 'none',
data: {
trial_id: "fixation",
exp_stage: "test"
},
timing_post_trial: 0,
timing_stim: 500,
timing_response: 500
}
/* prompt blocks are used during practice to show the instructions */
var prompt_fixation_block = {
type: 'poldrack-single-stim',
stimulus: '<div class = shapebox><div class = fixation>+</div></div>',
is_html: true,
choices: 'none',
data: {
trial_id: "fixation",
exp_stage: "practice"
},
timing_post_trial: 0,
timing_stim: 500,
timing_response: 500,
prompt: prompt_text
}
/* Initialize 'feedback text' and set up feedback blocks */
var practice_feedback_text =
'We will now start with a practice session. In this practice concentrate on responding quickly and accurately to each shape. Press <strong>enter</strong> to continue.'
var practice_feedback_block = {
type: 'poldrack-text',
data: {
trial_id: "feedback",
exp_stage: "practice"
},
timing_response: 180000,
cont_key: [13],
text: getPracticeFeedback
};
var selective_feedback_text = ''
var selective_feedback_block = {
type: 'poldrack-text',
data: {
trial_id: "feedback",
exp_stage: "practice"
},
timing_response: 180000,
cont_key: [13],
text: getSelectiveFeedback
};
var test_feedback_block = {
type: 'poldrack-text',
data: {
trial_id: "feedback",
exp_stage: "test"
},
timing_response: 180000,
cont_key: [13],
text: getTestFeedback,
on_finish: function() {
test_block_data = []
}
};
/* ************************************ */
/* Set up experiment */
/* ************************************ */
var stim_selective_stop_signal_experiment = []
stim_selective_stop_signal_experiment.push(instruction_node);
/* Practice block w/o SS */
NoSS_practice_trials = []
NoSS_practice_trials.push(practice_feedback_block)
for (i = 0; i < NoSSpractice_block_len; i++) {
NoSS_practice_trials.push(prompt_fixation_block)
var stim_block = {
type: 'poldrack-single-stim',
stimulus: getNoSSPracticeStim,
data: getNoSSPracticeData,
is_html: true,
choices: choices,
timing_post_trial: 0,
timing_stim: 850,
timing_response: 1850,
prompt: prompt_text,
on_finish: function() {
jsPsych.data.addDataToLastTrial({
exp_stage: "NoSS_practice",
trial_num: current_trial
})
current_trial += 1
}
}
NoSS_practice_trials.push(stim_block)
}
var NoSS_practice_node = {
timeline: NoSS_practice_trials,
loop_function: function(data) {
practice_repetitions += 1
var rt_array = [];
var sum_correct = 0;
var go_length = 0;
var num_responses = 0;
for (var i = 0; i < data.length; i++) {
if (data[i].trial_id == 'stim') {
if (data[i].rt != -1) {
num_responses += 1
rt_array.push(data[i].rt);
if (data[i].key_press == data[i].correct_response) {
sum_correct += 1
}
}
go_length += 1
}
}
var average_rt = -1
if (rt_array.length !== 0) {
average_rt = math.median(rt_array);
}
var GoCorrect_percent = sum_correct / go_length;
var missed_responses = (go_length - num_responses) / go_length
practice_feedback_text = "</p><p class = block-text><strong>Average reaction time: " + Math.round(average_rt) + " ms. Accuracy for non-blue star trials: " + Math.round(GoCorrect_percent * 100)+ "%</strong>"
if ((average_rt < RT_thresh && GoCorrect_percent > accuracy_thresh && missed_responses <
missed_response_thresh) || practice_repetitions > practice_repetition_thresh) {
// end the loop
current_trial = 0
practice_repetitions = 1
practice_feedback_text +=
'</p><p class = block-text>For the rest of the experiment, on some proportion of trials a blue or orange star will appear around the shape. If the star is blue, it is a "stop signal". <strong>When a blue star appears please try your best to stop your response and press nothing on that trial. If the star is orange, please continue to respond to the shapes.</strong> </p><p class = block-text>The star will appear around the same time or shortly after the shape appears. Because of this, you will not always be able to successfully stop when a blue star appears. However, if you continue to try very hard to stop when a blue star appears, you will be able to stop sometimes but not always.</p><p class = block-text>If an orange star appears, respond as you normally would by pressing the correct key. </p><p class = block-text><strong>Please balance the requirement to respond quickly and accurately to the shapes while trying very hard to stop to the blue stop signal.</strong></p><p class = block-text>Press <strong>Enter</strong> to continue'
return false;
} else {
//rerandomize stim order
NoSS_practice_list = jsPsych.randomization.repeat(stimulus, 3, true)
// keep going until they are faster!
practice_feedback_text += '</p><p class = block-text>We will try another practice block. '
if (average_rt > RT_thresh) {
practice_feedback_text +=
'</p><p class = block-text>You have been responding too slowly, please respond to each shape as quickly and as accurately as possible.'
}
if (missed_responses >= missed_response_thresh) {
practice_feedback_text +=
'</p><p class = block-text><strong>We have detected a number of trials that required a response, where no response was made. Please ensure that you are responding to each shape.</strong>'
}
if (GoCorrect_percent <= accuracy_thresh) {
practice_feedback_text +=
'</p><p class = block-text>Your accuracy is too low. Remember, the correct keys are as follows: ' + prompt_text
}
practice_feedback_text += '</p><p class = block-text>Press <strong>Enter</strong> to continue'
return true;
}
}
}
/* Practice block with SS */
var practice_trials = []
practice_trials.push(practice_feedback_block)
for (i = 0; i < practice_block_len; i++) {
practice_trials.push(prompt_fixation_block)
var stop_signal_block = {
type: 'stop-signal',
stimulus: getSSPracticeStim,
SS_stimulus: getSSPractice_stop_signal,
SS_trial_type: getSSPractice_trial_type,
data: getSSPracticeData,
is_html: true,
choices: choices,
timing_stim: 850,
timing_response: 1850,
prompt: prompt_text,
SSD: SSD,
timing_SS: 500,
timing_post_trial: 0,
on_finish: function(data) {
jsPsych.data.addDataToLastTrial({
exp_stage: "practice",
trial_num: current_trial
})
current_trial += 1
}
}
practice_trials.push(stop_signal_block)
}
practice_trials.push(selective_feedback_block)
/* Practice node continues repeating until the subject reaches certain criteria */
var practice_node = {
timeline: practice_trials,
// This function defines stopping criteria
loop_function: function(data) {
practice_repetitions += 1
var rt_array = [];
var sum_correct = 0;
var go_length = 0;
var num_responses = 0;
var stop_length = 0
var successful_stops = 0
for (var i = 0; i < data.length; i++) {
if (data[i].trial_id == 'stim') {
if (data[i].SS_trial_type != 'stop') {
if (data[i].rt != -1) {
num_responses += 1
rt_array.push(data[i].rt);
if (data[i].key_press == data[i].correct_response) {
sum_correct += 1
}
}
go_length += 1
} else if (data[i].SS_trial_type == "stop") {
stop_length += 1
if (data[i].rt == -1) {
successful_stops += 1
}
}
}
}
var numIgnore = 0
var ignoreRespond = 0
for (var b = 0; b < data.length; b++){
if(data[b].trial_id == 'stim' && data[b].condition == 'ignore'){
numIgnore = numIgnore + 1
if (data[b].rt != -1){
ignoreRespond = ignoreRespond + 1
}
}
}
var average_rt = -1
if (rt_array.length !== 0) {
average_rt = math.median(rt_array);
}
var ignoreRespond_percent = ignoreRespond/numIgnore
var GoCorrect_percent = sum_correct / go_length;
var missed_responses = (go_length - num_responses) / go_length
var StopCorrect_percent = successful_stops / stop_length
practice_feedback_text = "</p><p class = block-text><strong>Average reaction time: " + Math.round(average_rt) + " ms. Accuracy for non-blue star trials: " + Math.round(GoCorrect_percent * 100)+ "%</strong>"
if ((average_rt < RT_thresh && GoCorrect_percent > accuracy_thresh && missed_responses <
missed_response_thresh && StopCorrect_percent > 0.2 && StopCorrect_percent < 0.8 && ignoreRespond_percent > selective_threshold) || practice_repetitions >
practice_repetition_thresh) {
// end the loop
current_trial = 0
practice_feedback_text +=
'</p><p class = block-text>Done with practice. We will now begin the ' +
numblocks +
' test blocks. There will be a break after each block. Press <strong>enter</strong> to continue.'
return false;
} else {
//rerandomize stim and stop_trial order
practice_list = jsPsych.randomization.repeat(stimulus, practice_block_len/4, true)
practice_stop_trials = jsPsych.randomization.repeat(['stop', 'ignore', 'go', 'go', 'go'], practice_list.data.length / 5, false)
// keep going until they are faster!
practice_feedback_text += '</p><p class = block-text>We will try another practice block. '
if (average_rt > RT_thresh) {
practice_feedback_text +=
'</p><p class = block-text>You have been responding too slowly, please respond to each shape as quickly and as accurately as possible.'
}
if (missed_responses >= missed_response_thresh) {
practice_feedback_text +=
'</p><p class = block-text><strong>We have detected a number of trials that required a response, where no response was made. Please ensure that you are responding to each shape, unless a blue star appears.</strong>'
}
if (GoCorrect_percent <= accuracy_thresh) {
practice_feedback_text +=
'</p><p class = block-text>Your accuracy is too low. Remember, the correct keys are as follows: ' + prompt_text
}
if (StopCorrect_percent < 0.8){
practice_feedback_text +=
'</p><p class = block-text><strong>Remember to try and withhold your response when you see a blue stop signal.</strong>'
} else if (StopCorrect_percent > 0.2){
practice_feedback_text +=
'</p><p class = block-text><strong>Remember, do not slow your responses to the shape to see if a blue star will appear before you respond. Please respond to each shape as quickly and as accurately as possible.</strong>'
}
practice_feedback_text += '</p><p class = block-text>Press <strong>Enter</strong> to continue'
return true;
}
}
}
stim_selective_stop_signal_experiment.push(NoSS_practice_node)
stim_selective_stop_signal_experiment.push(practice_node)
stim_selective_stop_signal_experiment.push(practice_feedback_block)
/* Test blocks */
// Loop through the multiple blocks within each condition
for (var b = 0; b < numblocks; b++) {
stop_signal_exp_block = []
var block = blocks[b]
var stop_trials = jsPsych.randomization.repeat(['stop', 'ignore', 'go', 'go', 'go'],
test_block_len / 5)
// Loop through each trial within the block
for (var i = 0; i < test_block_len; i++) {
stop_signal_exp_block.push(fixation_block)
//Label each trial as an ignore, stop or go trial
var trial_data = $.extend({}, block.data[i])
trial_data.condition = stop_trials[i]
trial_data.exp_stage = 'test'
if (stop_trials[i] == 'ignore') {
var stop_trial = 'stop'
var stop_stim = ignore_signal
} else {
var stop_stim = stop_signal
var stop_trial = stop_trials[i]
}
var stop_signal_block = {
type: 'stop-signal',
stimulus: block.stimulus[i],
SS_stimulus: stop_stim,
SS_trial_type: stop_trial,
data: trial_data,
is_html: true,
choices: choices,
timing_stim: 850,
timing_response: 1850,
SSD: getSSD,
timing_SS: 500,
timing_post_trial: 0,
on_finish: function(data) {
updateSSD(data)
test_block_data.push(data)
jsPsych.data.addDataToLastTrial({
trial_num: current_trial
})
current_trial += 1
}
}
stop_signal_exp_block.push(stop_signal_block)
}
stim_selective_stop_signal_experiment = stim_selective_stop_signal_experiment.concat(
stop_signal_exp_block)
if ($.inArray(b, [0, 1, 4]) != -1) {
stim_selective_stop_signal_experiment.push(attention_node)
}
stim_selective_stop_signal_experiment.push(selective_feedback_block)
stim_selective_stop_signal_experiment.push(test_feedback_block)
}
stim_selective_stop_signal_experiment.push(post_task_block)
stim_selective_stop_signal_experiment.push(end_block)