University of Sussex | Reality Bending Lab

Postdoc in Psychology/Neuroscience

Tue, 22 Nov 2022 00:00:00 +0000

New Opportunities

None :(

Getting your own Postdoc Funding

If you’re a recent PhD graduate (or soon to be), you could consider applying for a postdoc fellowship to join the lab on your own terms, and develop your own research project.

Here are some existing opportunities for postdoc funding:

SENSS
Marie-curie postdoc fellowships (MSCA)
Newton International Fellowships (non-UK)
British Academy (UK PhDs holders)
UKRI Future Leaders
FYSSEN (French PhDs holders)
CRSH, FRQSC, Banting (Canadian PhDs holders)
NTU’s Humanities International Postdoctoral Scholarship (HIPS) (Singaporeans)

Get in touch with me once you have an opportunity in mind and a rough project idea, we can then refine your application to maximize your chances of getting it.

Don’t rely on what is written!

Ask directly members of team (current and past) about their experience in the lab!

PhD in Psychology / Neuroscience

Tue, 22 Nov 2022 00:00:00 +0000

Flexible University of Sussex, Brighton, UK

New Opportunities

11 December 20205: Sussex Psychology PhD Program
- Fully funded for local and international students (i.e., pays university fees + gives you a salary)
- Selection is based on the candidate’s CV as well as on the project proposal
- Get in touch with potential supervisors before applying!
11 December 20205: SEDarc PhD Scholarship
- 3.5 years fully funded scholarship
- Project must fit within the SEDarc themes (e.g., data science)
- Selection is based on the candidate’s CV as well as on the project proposal
12 January 2026: Sussex Neuroscience 3+1 PhD Program
- Fully funded for local and international students (i.e., pays university fees + gives you a salary)
- You don’t need to chose a supervisor before applying. The first year is made of 3 different rotations in different labs
- Selection is based mostly on the candidate’s CV

What you will get

Doing a PhD at Sussex with Dominique Makowski means:

Joining a dynamic team with a vibrant lab life
A supervisor that actually supervises 🤯
A super interesting research topic
A French-style thesis defense to celebrate your accomplishments 🧀🍷

Don’t rely on what is written!

Ask directly members of team (current and past) about their experience in the lab!

How to do a PhD in Psychology?

The first step is usually to contact the potential supervisor to discuss a rough research project outline. Write an email with your CV, your research interests and - if you have - some ideas for a research project that matches your supervisor’s line of research. If you don’t have ideas yet, it’s perfectly fine! I will likely propose some avenues of research that might match your interest, and refine them down the line.
Ideally, you would also want to come up with a plan for funding. This is the most challenging part, unfortunately. There are typically 4 types of profiles: 1) the student and the supervisor come up with a tentative research project, with which the student then applies to scholarship opportunities. 2) the supervisor already has a scholarship for a specific project that he obtained a grant for, and will recruit a PhD for that specific research project; 3) the student already secured a scholarship that allows them to pursue a PhD with the supervisor of their choice (e.g., some schemes exist from countries for their nationals to do their PhD abroad). 4) Self-funding, which we don’t recommend unless you’re one of the lucky few with money to spare.

Funding Opportunities

Funding is a complicated topic, and often the main barrier between one’s goal and its achievement. Keep in mind that there are many other possibilities and case-by-case considerations.

Here are some scholarship opportunities for funded PhDs in the UK:

The Sussex Psychology Doctoral Research Studentship
The Sussex Neuroscience 3+1 years PhD
The Sussex AI PhD (you will need a primary supervisor from the School of Engineering and Informatics but I can be a cosupervisor)
The SEDarc studentships (see also here)
The South and East Network for Social Sciences (SENSS)
The Welcome Trust PhD Studentships
The UKRI studentship
The South Coast Biosciences Network (SoCoBio)
The Chevening Scholarship (International only)
The FIRE French scholarships (must be a collaboration with a Paris-based lab)
The DAAD scholarships (Germans)
The Joint China Scholarship (China)
Scholarship Opportunities for Singaporeans:

As well as other options:

Partnership: If an external partner agrees to cover half the cost (approx. £35k over three years), the university can match the other half of the cost. Useful for applied projects and collaborations with startups, private companies or NGOs. If you’re thinking of developing a product, a software or a service, this could be a good option.
Collaboration: Many universities allow some form of co-supervisorship. This means that you could do the main part of your PhD in another university, and come to Sussex sporadically as part of a collaboration. Note that official frameworks can exist for this type of configurations, such as the cotutelles in France.

Check-out this how to apply guide for additional information.

More info are available on the university’s PhD in psychology, Funding, PhD in cognitive science and PhD in neuroscience information page.

Other Pots of Money

Mostly for those already registered as PhD students.

Laura Bassi Scholarship: Masters and PhD on “neglected” research topics.

Questions and Answers

Clinical Psychology PhD or DClinPsy?

Unfortunately, the University of Sussex does not offer at the moment a PhD in Clinical Psychology that includes clinical placements and internships in hospitals. However, if you are interested in working with patients, it is entirely possible to have a research project that involves clinical populations, and specialize in “clinical” research. Some people then complement this kind of PhD with clinical trainings (e.g., psychotherapy) to transition from research to practice.

How to become a Neuropsychologist?

Neuropsychology is both an approach (focusing on the relationship between the brain and its output in the form of behaviour and thought) and a practice (involving neuropsychological assessments and rehabilitation). The latter is considered a specialization of Clinical Psychology, which means that one must be a clinical psychologist to be a clinical neuropsychologist. As said above, the University of Sussex unfortunately does not offer, at the moment, a formal PhD in clinical psychology or clinical neuropsychology. However, joining the Reality Bending Lab will get you well-prepared to eventually pursue this type of program, as the methods and mindset that we have draws heavily on neuropsychology (the use of neuropsychological tests, the focus on neurocognitive theories, etc.). In fact, some of our past members have become brilliant neuropsychologists, so feel free to ask them!

How to work on psychedelics?

Psychedelics and altered states of consciousness are a hot topic in psychology and neuroscience. Unfortunately, it is still extremely difficult to get authorizations to work with these substances. I would not recommend to base your PhD project on this potentiality, as it’s too risky that things might not work out (due to ethical, administrative, or political reasons). That said, we do have projects running in collaborations with experts in the field, and are always on the lookout for opportunities to work on these topics. Additionally, we think it’s also very interesting to study how altered states of consciousness can be induced without external substances (e.g., through meditation, hypnosis, sensory deprivation, neural stimulation, …), which might be a more sustainable and ethical way to approach these phenomena.

Application Advice

A few tips for your writing up your application dossier, in particular pertaining your CV and cover letter. Note that these are general guidelines that also apply to other contexts (master’s programs, industry jobs, etc.).

The key thing is to keep in mind that we receive a lot of applications (few hundreds for some positions). The first mistake you want to avoid is to have a generic, impersonal application: do address specific people (and do not make mistakes in the spelling of their names, it happens often and is a turn-off), and try to concisely paint a profile of yourself that the recruiter can easily picture and form an image of: what is your background, where do you come from, what are your expertise, interests and goals. This should really be one tightly written paragraph (you can expand on this in your CV). We often see long and convoluted CVs and cover letters, that try to show “a bit of everything”, leaving the reader with little more than a sense of confusion.

Next, after providing a clear depiction of who you are, you want to show that you have done your homework about where you are applying: be specific about the people of the department (e.g., “I am particularly interested in working with Dr. X because of their work on Y”), or the papers (“I particularly enjoyed your paper on X because of Y”). This shows that you are motivated and that you are not just sending the same application to 100 different places. That being said, do not list everything that is written on someone’s website or profile, because it makes it look like you just copied and pasted it. Be genuine, personal and specific. It is tempting to use AI to generate these kinds of things, but I would advise against it. Putting it the time, effort, and hard work will pay off.

Finally, you want to show that you are a good fit for the position, and show that you have experience in the methods that are used in the lab, that you have experience in the field, etc.

Research Assistant in Psychology / Neuroscience

Thu, 02 Feb 2023 00:00:00 +0000

Flexible University of Sussex, Brighton, UK

Working as a research assistant (RA) is a formidable opportunity to take on before - eventually - signing up for a PhD. It is a flexible and varied position, and a perfect position to develop key research skills like writing, data analysis or neuroimaging; and eventually later pursue a postgraduate program in psychology/neuroscience/neuropsychology.

Funded RA positions at Sussex can be seen on the recruitment page.

Sussex Psychology Placement Year

Students at the University of Sussex can also opt for a placement year between the second and third year of their studies. All undergraduates within the School are eligible to complete a placement year.

While it might seem like it would “add” one year and delay the end of the studies, the experience that you could gain is quite invaluable. Doing a full-year placement year in a research lab is the best way to take on larger projects and acquire a comprehensive research experience. Beyond providing you with a massive headstart for the final year, it is a great opportunity to learn new skills and meet many researchers, which will help you refine your career trajectory and maximize your chances of achieving your goals.

More information here.

Sussex Junior Research Associate (JRA)

Sussex also offers short summer internship opportunities for undergrads interested in developing your research skills and experience. You can apply to the Sussex Junior Research Associate (JRA) program to become a research associate and undertake an intensive eight-week research project over the summer break. Find out more information on how to apply here.

See this blogpost for a testimony.

SoSocBio Undergraduate Summer Studentship

Undergraduates residing in the UK can apply for a paid 6 weeks (30hr per week) internship between 1 July and 30 September.

More information here.

International Junior Research Associate (IJRA)

See here: https://www.sussex.ac.uk/suro/current/ijra

Other Bursaries

Neuropsychology International Fellowship (NIF): Small bursaries from the British Neuropsychological Society to support small research internship.

Volunteer Research assistant

Check the voluntary internships page for more information.

Don’t rely on what is written!

Ask directly members of team (current and past) about their experience in the lab!

Internship in Psychology / Neuroscience

Thu, 02 Feb 2023 00:00:00 +0000

Flexible University of Sussex, Brighton, UK

If you are a undergrad student, doing a voluntary internship can be a good idea to get some first exposure with research, develop some useful skills and start growing your professional network. This is not by any means a necessity or a requirement, so don’t worry at all if you cannot afford (financially or in term of availabilities) to volunteer, and check-out instead possibly funded positions.

Sussex Psychology Placement Year: Check-out the Research Assistant page
Sussex Junior Research Assistant (JRA): Check-out the Research Assistant page
SoSocBio Undergraduate Summer Studentship: Check-out the Research Assistant page

Contact. Send CV to D.Makowski@sussex.ac.uk and explicitly say that you are interested in volunteering.

Don’t rely on what is written!

Ask directly members of team (current and past) about their experience in the lab!

Research Projects

Thu, 02 Feb 2023 00:00:00 +0000

Flexible University of Sussex, Brighton, UK

Projects

Research in the Reality Bending Lab focuses primarily on the physiological and neurocognitive underpinnings of reality perception and aspects of reality bending (e.g., fiction, deception, fake news, illusions, and altered states of consciousness such as through meditation or immersion). Possible projects include (but are not limited to):

How do we know what is real? And what does it change?

Real vs. Fake: This project will typically involve presenting some real vs. “fake” stimuli (e.g., fake news, AI-generated images, …) to participants and investigate what interindividual/cognitive/emotional factors allows them to discriminate between the two.
Emotion regulation via fiction: believing that something is unreal (regardless of whether it actually is or is not) seem to have some ripple effect on various facets of our body and brain, such as emotions. This project studies the characteristics and potential use of fiction as an emotion regulation strategy. This project can be focused on negative emotions (with threatening/unpleasant stimuli) or “positive” emotions (e.g., sexual arousal, attractiveness).
Authenticity & Neuroaesthetics: This project investigates the effect of believing that an artwork is “forged” (e.g., an imitation of a great painter) on our appraisal of beauty.

Assessment of bodily and cognitive abilities and their relationship

Neuropsychological assessment of Cognitive Control: This project focuses on the development, validation and improvement of a neuropsychological task to reliably measure “cognitive control” (executive functions). This project requires some interest in neuropsychological assessment, task development and associated technical skills (programming, game development).
Physiological Control: development of measures (questionnaires, physiological tasks) measuring the ability to voluntarily regulate one’s physiology (e.g., heart rate, autonomic reactions, etc.).
Relationship between Interoception and higher-order functions: This project involves measuring various aspects of our relationship with our body (e.g., by measuring cardiac activity) and analyzing its relationship with cognitive abilities (e.g., Self control, emotion regulation) or higher-order constructs (e.g., primal world beliefsLinks to an external site.).
Secondary EEG data analysis: Investigating an existing dataset containing resting state EEG signal, from which one would extract features to try predicting dispositional indices (such as primal world beliefs).

Non-invasive induction of altered states of consciousness

Emotion regulation via distancing: by instructing people to change their state of mind (e.g., “see the events in a detached manner, like a fly on the wall”), we hope to manipulate aspects of the sense of reality - such as absorption and psychological distance - and compare its effect (in particular on emotions) with that of other emotion regulation strategies.
Can we manipulate the state of consciousness and observe actual effects on the performance at various cognitive tasks? For instance, via hypnosis or mindfulness-like instructions, sound stimulation (binaural beats, drumming, …), sensory deprivation (“floating” tanks). We study the role of expectations and try to isolate the mechanism of change.
Qualitative + quantitative project: Investigation into the world of “reality shifters”, people claiming that have shifted between realities. Understand their language, personality, etc.

Metascience / Data science / Software development

Investigation of scientific practices: to what extent scientists engage in “new” practices (e.g., open science, slow science, preregistration, registered reports, …) and what factors (e.g., career level, time, ideology, …) are driving their adoption (or lack thereof). This might involve things like validating assessment tools (such as questionnaires or gamified measures like quizzes), distributing it widely and analysing the results.
Improving access of R to psychologists: R outputs can be complex, and we are developing tools to facilitate its understanding (e.g., the reportLinks to an external site. package). This project involves implementing functions in R to help communicate and interpret statistical results. This project requires some interest in programming and stats.
Neurophysiological signal analysis in Python: implementation and validation of new algorithms in Python, related for instance to chaos theory, EEG signal analysis, etc. This project requires some interest in programming, computer science and mathematics.
Psychophysiological methods: what is the optimal electrode configuration for recording skin conductance responses (often used as a marker of emotions).
Role of beauty in science: Is the impact of research publications related to the aeshetic qualities of figures.

Other / Collaborations

With Theodoros Karapanagiotidis: project involving secondary behavioural data analysis, exploring questions about the nature of thoughts, their patterns, the impact of mood and ongoing experience , and how they vary in in real-life settings. By analysing existing data, students will be able to examine the links between ongoing thoughts, brain structure and function, and their potential implications for mental health and well-being.

Some of these projects share strong links with philosophical concepts (e.g., the paradox of fiction) and/or carry some clinical relevance (e.g., for the understanding and treatment of mood/psychotic/dissociative disorders). Also, note that the lab is radically engaged in open science and, ultimately, quantitative methodologies: thus, most projects would typically require a substantial use of R (or Python) at some stage. However, it’s totally okay not to feel proficient at these skills at the start, but the important thing is to be interested and motivated to learn.

Projects might be conducted individually, in pairs, or in a group, depending on needs. Attending weekly lab meetings is also expected.

Skills

Joining the Reality Bending Lab will help you develop unique skills that your might not find in other labs, that will give an edge to your profile for future applications. These include:

Neuroimaging (EEG)
Psychophysiology (multimodal bodily recordings)
Computational Bayesian modelling with R
Advanced programming with Python
Open science best practices (using GitHub and various cutting edge tools)

Advice for Students

Choosing Options

Most psychology programs are proposing some optionality, i.e., some modules that you can pick. While many of them look interesting, you often have to make hard choices. Many students pick what looks interesting, from various psychology domains (e.g., a bit of social psychology, a module from cognitive, one from clinical etc.). They might also believe that picking a variety of options will provide them with a multidisciplinary profile, which might be valued later on.

While this is, in principle, true, in practice, a “consistent” profile is often much more appealing to recruiters. For instance, having a set of clinically-relevant options, or cognitive/neuroscience ones, will give you an edge (and sometimes, even for say a “neuroscience” opportunity, recruiters would prefer a clearly clinical profile rather than a “jack of all trades master of none” type of one). Make your choices wisely, and make them with a plan.

But I don’t know what I want to do later, so I want to keep most doors open.

Yes, that’s a common issue. You can still keep doors open while at the same time having a coherent profile. You should at least have an idea of what subbranch of psychology you don’t want to do (e.g., social psychology).

For psychology students at Sussex, if you would like to work with me, I recommend picking some of the following options:

Cognitive Neuroscience (must have)
Conscious and Unconscious Mental Processes
Biological Psychology of Mental Health
Perspectives on Psychology
Self Regulation: The Science of Achieving Your Goals
Attention: Distraction, Daydreaming and Diversity
Drugs, Brain and Behaviour

Don’t rely on what is written!

Ask directly members of team (current and past) about their experience in the lab!

How to send event triggers to Lab Streaming Layer from JsPsych

Sun, 11 Jan 2026 00:00:00 +0000

Hello there! 👋 Let’s learn how to send event triggers to Lab Streaming Layer (LSL) from JsPsych.

Lets start with some basics!

What does this mean and when is this useful?

Lab streaming layer (LSL) is a system used to receive, synchronise and stream signals from multiple inputs during experiments. LSL is designed to help researchers easily compare their data across multiple technologies, as time synchrony is integral for making meaningful analyses.

When collecting data on stimulus response during experiments, it’s important that the stimulus onset is recorded precisely, especially if this is mapped onto physiological responses as this has implications on how we interpret our data. One good example of a use case is that you have a Muse headband or any other device that can scream via LSL, and you want to precisely mark events in it.

Event triggers are coded into JsPsych online experiments to accurately mark events, such as when a stimulus appeared on the screen. We have found this method to yield the most precise timestamps of events, compared to alternative methods such as using the Bitalino LUX.

This tutorial will explain how to set this up for an experiment situated on GitHub, although you can adapt this for your hosting platform.

This blog will help you understand the set-up for event triggers. For an example of this in action, refer to https://github.com/OliverACollins/muse-athena-test/tree/main/blackwhite. This experiment recorded markers on a screen turning from white to black- you may want to follow along with lsl_bridge.py and blackwhite_jspsych.html¹ for the full implementation.

How to set up event triggers

Requirements

Your experiment is in-person: In order to use these event triggers, you will need to run your experiment on a local host server, which will need to be manually set up for each trial. Therefore, this setup is intended for in-person experiments that are led by a researcher to set up the participant’s screen.
You have two machines, one for the participant, and one for the researcher: The participant’s machine will display the experiment and send the markers to the researcher’s machine, which will record the LSL stream events.
All machines must be on the same network connection: To send the markers from the participant’s machine to the researcher’s recording machine, we must run the experiment on a web server which directs the markers to the recording machine via its ipv4 address.

The LSL bridge script

The LSL bridge Python script is responsible for actually sending the markers to LSL- it ’listens’ for messages from the browser that the participant is doing the experiment from, and converts them into ‘markers’ for your recording software (such as LabRecorder) to receive.

See an example of a full script

from http.server import BaseHTTPRequestHandler, HTTPServer
from urllib.parse import urlparse, parse_qs
from mne_lsl.lsl import StreamInfo, StreamOutlet, local_clock
import threading

# ---------------------------------------------------------------------
# CONFIG
# ---------------------------------------------------------------------
LSL_STREAM_NAME = "jsPsychMarkers"
LSL_STREAM_TYPE = "Markers"
LSL_SOURCE_ID = "jspsych-lsl-bridge"
SERVER_HOST = "0.0.0.0"
SERVER_PORT = 5000
# ---------------------------------------------------------------------

# Create an LSL outlet for event markers
info = StreamInfo(
    name=LSL_STREAM_NAME,
    stype=LSL_STREAM_TYPE,
    n_channels=1,
    sfreq=0,
    dtype="string",
    source_id=LSL_SOURCE_ID,
)

desc = info.desc
desc.append_child_value("manufacturer", "jsPsych")
channels = desc.append_child("channels")
ch = channels.append_child("channel")
ch.append_child_value("label", "JsPsychMarker")
ch.append_child_value("unit", "string")
ch.append_child_value("type", "Marker")

outlet = StreamOutlet(info)

# ---------------------------------------------------------------------
# HTTP Request Handler
# ---------------------------------------------------------------------
class MarkerHandler(BaseHTTPRequestHandler):
    def do_GET(self):
        parsed = urlparse(self.path)
        params = parse_qs(parsed.query)
        path = parsed.path

        if path == "/sync":
            # Return current LSL clock to JS
            ts = local_clock()
            self.send_response(200)
            self.end_headers()
            self.wfile.write(str(ts).encode())

        elif path == "/marker":
            value = params.get("value", ["1"])[0]
            ts_js = params.get("ts", [None])[0]

            if ts_js is not None:
                ts = float(ts_js)
            else:
                ts = local_clock()

            outlet.push_sample([value], ts)
            print(f"→ Marker {value} @ {ts:.6f}")

            self.send_response(200)
            self.end_headers()
            self.wfile.write(b"OK")

        else:
            self.send_response(404)
            self.end_headers()

# ---------------------------------------------------------------------
def run_server():
    server_address = (SERVER_HOST, SERVER_PORT)
    httpd = HTTPServer(server_address, MarkerHandler)
    print(f"\n[LSL Bridge] Serving on http://{SERVER_HOST}:{SERVER_PORT}")
    print(f"[LSL Bridge] Stream '{LSL_STREAM_NAME}' ready for LabRecorder.\n")
    httpd.serve_forever()

# ---------------------------------------------------------------------
if __name__ == "__main__":
    server_thread = threading.Thread(target=run_server)
    server_thread.start()

Configuration of the Python Script

Set-up
- Imports: Load in standard python libraries for creating a web server (http.server, urllib) and the mne_lsl library to handle the data streaming.
- Configure Variables: Name the event trigger stream so you can find it in LabRecorder, e.g. LSL_STREAM_NAME = "jsPsychMarkers".
- Add SERVER_HOST = "0.0.0.0" into the script to tell the server to listen to all available network interfaces, allowing the participant’s computer to communicate with the researcher’s.
- Specify the port for the html script to go to e.g. SERVER_PORT = 5000. You will add this port into the html script that holds the online experiment, in order to send the experiment to this python script.
Create the LSL outlet for event triggers
- Define the metadata for the stream: info = StreamInfo( name=LSL_STREAM_NAME...
- Create the outlet object that will push data out to the network: outlet = StreamOutlet(info).
Create the request handler to define what happens when the participant’s browser contacts the server.
- The sync route:
  - if path == "/sync":: Checks if the browser is asking to synchronize clocks.
  - ts = local_clock(): Grabs the current high-precision time from the LSL clock on the Recording Machine.
  - self.wfile.write(...): Sends this timestamp back to the browser. The browser needs this to calculate the time difference (offset) between the two computers.
- The marker route:
  - elif path == "/marker": Checks if the browser is trying to send an event marker.
  - It extracts value (the marker name, e.g., “1”) and ts (the timestamp calculated by the browser) from the URL parameters.
  - outlet.push_sample([value], ts): This is the most important line. It injects the marker into the LSL stream using the timestamp provided by the browser. This ensures that even if there is network lag, the timestamp recorded in the EEG data remains accurate to when the event actually happened on the participant’s screen.
Run the Server
- run_server(): Starts the HTTP server and prints a confirmation message that it is ready for LabRecorder.
- threading.Thread(...): Runs the server in a separate thread so it doesn’t block the main Python process.

Configuration of the JsPsych HTML script

See an example of a full script

<!DOCTYPE html\>

<html>

<head>

<title>Black/White Muse Synchronisation Test</title>

<script src="https://unpkg.com/jspsych\@7.3.4"\>\</script\>

<script src="https://unpkg.com/\@jspsych/plugin-html-keyboard-response\@1.1.3"\>\</script\>

<script src="https://unpkg.com/\@jspsych/plugin-image-keyboard-response\@1.1.3"\>\</script\>

<script src="https://unpkg.com/\@jspsych/plugin-preload\@1.1.3"\>\</script\>

<script src="https://unpkg.com/\@jspsych/plugin-fullscreen\@2.1.0"\>\</script\>

<link href="https://unpkg.com/jspsych@7.3.4/css/jspsych.css" rel="stylesheet" />

</head>

<body>

</body>

<script>
// -----------------------
// LSL bridge (promise-based)
// -----------------------
var lslBaseTime = null

function syncLSL() {
    return new Promise(async function (resolve, reject) {
        try {
            let offsets = []
            for (let i = 0; i < 3; i++) {
                var startPerf = performance.now()
                let resp = await fetch("http://139.184.128.202:5000/sync", { cache: "no-store" })
                let text = await resp.text()
                var lslTime = parseFloat(text)
                var endPerf = performance.now()
                var perfMid = (startPerf + endPerf) / 2
                offsets.push(lslTime - perfMid / 1000)
                await new Promise((r) => setTimeout(r, 100)) // Short delay between syncs
            }
            lslBaseTime = offsets.reduce((a, b) => a + b, 0) / offsets.length
            console.log("LSL sync done (averaged):", lslBaseTime)
            resolve(lslBaseTime)
        } catch (e) {
            console.error("LSL sync exception:", e)
            reject(e)
        }
    })
}

function sendMarker(value = "1") {
    // If not synced, still send marker (server will timestamp with local_clock())
    if (lslBaseTime === null) {
        console.warn("LSL not synced yet - sending without JS timestamp")
        fetch("http://139.184.128.202:5000/marker?value=" + encodeURIComponent(value))
            .then(function () {
                console.log("sent marker (no-ts)", value)
            })
            .catch(function (err) {
                console.error("Marker send error:", err)
            })
        return
    }

    var ts = lslBaseTime + performance.now() / 1000
    var url = "http://139.184.128.202:5000/marker?value=" + encodeURIComponent(value) + "&ts=" + encodeURIComponent(ts)
    fetch(url)
        .then(function () {
            console.log("sent marker", value, "ts", ts)
        })
        .catch(function (err) {
            console.error("Marker send error:", err)
        })
}

/* --------------------------
   Experiment Definition
--------------------------- */

function startExperiment() {

    var jsPsych = initJsPsych({
        override_safe_mode: true
    });

    var timeline = [];

    /* preload */
    timeline.push({
        type: jsPsychPreload,
        images: ["white.png", "black.png"]
    });

    /* stimuli */
    var test_stimuli = [
        { stimulus: "white.png", duration: 750, marker: 0 },
        { stimulus: "black.png", duration: 500, marker: 1 }
    ];

    /* trial */
    var test = {
        type: jsPsychImageKeyboardResponse,
        stimulus: jsPsych.timelineVariable("stimulus"),
        trial_duration: jsPsych.timelineVariable("duration"),
        choices: "NO_KEYS",

        data: {
            marker: jsPsych.timelineVariable("marker")
        },

        on_start: function(trial) {
            requestAnimationFrame(() => {
                sendMarker(trial.data.marker);
            });
        }
    };


  var loop_node = {
      timeline: [{
          timeline: [test],
          timeline_variables: test_stimuli,
          randomize_order: false
      }],
      loop_function: function() {
          return jsPsych.getTotalTime() < 2100000;
      }
  };

  timeline.push(loop_node);


    jsPsych.run(timeline);
}

// -----------------------
// Run: first sync then start experiment
// -----------------------
syncLSL()
    .then(function () {
        startExperiment()
    })
    .catch(function (err) {
        console.warn("Proceeding without LSL sync (sync failed):", err)
        startExperiment()
    })

</script>

</html>

The code sending triggers from the browser to the LSL bridge script is written in javascript. It is ‘promise-based’, meaning it is coded to wait until it receives a signal from the participant’s computer. This code is designed to track the exact time it is on the participant’s computer and send markers precisely aligned to that time.

Synchronisation
- var lslBaseTime = null: A variable to store the calculated time difference between the two computers.
- The function syncLSL() {...} can be looped three times to get an average reading.
- Get the time of the marker: fetch("http://.../sync")
- Record startPerf (when the request left) and endPerf (when the answer came back).
- You can assume the server received the message exactly halfway between start and end (perfMid).
- Calculate the difference between the browser’s clock and the LSL clock: offsets.push(lslTime - perfMid / 1000).
- Finally, average these offsets into lslBaseTime. Now the browser knows how to convert its own time to LSL time.
Sending markers
- Safety check in case sync fails: if (lslBaseTime === null) can be coded to send markers based on the timing from the participant’s computer without synchronisation, which is less accurate but better than nothing.
- Code the mathematical logic to account for the offset in time for the recording computer to receive the marker, so the generated timestamp aligns with the recording computer’s timestamp: var ts = lslBaseTime + performance.now() / 1000.
- Send the marker name and this calculated timestamp to the python bridge: fetch(url).

Usage

On the researcher’s machine:

Turn off the firewall in security settings for the researcher’s machine.
Open the lsl bridge script and go onto the terminal (we use VS code). Type ipconfig to retrieve the ipv4 address.
In the terminal, type pip install mne-lsl.
Select all text in the bridge script and run it (ctrl+a, shift+enter)

On the participant’s machine:

Open the html script. You will need to ensure the terminal working directory points towards your experiment folder- the best way to do this is to open your repository folder on VS code.
Copy the ipv4 address from the researcher’s machine into the html script- there should be three instances before the :5000 port address.
In a new terminal, run python -m http.server 8000
You are now ready to run the experiment. Go onto your browser and enter the link ‘http://localhost:8000/index.html’, adjusting for the name of your html script. Your experiment should now run on the participant’s machine. The researcher can view markers received in their python terminal.

Special shoutout to our placement student Oliver Collins for preparing these scripts! ↩︎

What is the Best Interoception Questionnaire?

Sat, 20 Dec 2025 00:00:00 +0000

Hello👋! We are Róisín and Oliver, two Research Assistants at the lab, and today we are going to be discussing the tricky topic of self-report interoception questionnaires.

Interoception, essentially referring to one’s sensation of their internal body, is a fundamental phenomenon that we rely on in everyday life, and recent research highlights it as a trans-diagnostic underpinning of a variety of somatic and psychological difficulties.

While we know interoception is very important, the specifics are still being worked out. Debates continue on what exactly interoception is, is not, and what it encompasses in terms of modalities or processes. Is it limited to visceral sensations (i.e., from internal organs)? Does it include proprioception (i.e., body position sense)? Pain? What about tactile sensations (i.e., touch and skin)? Does it include the interaction with higher-order processes like attention and beliefs?

This chaotic and moving landscape has been accompanied by the development and repurposing of different interoception (and interoception-adjacent) questionnaires, each with their own philosophies and approach. Carefully choosing a good measure of interoception is crucial to avoid adding to the jingle-jangle fallacy plaguing the field, in which discrepancies and contradictions of results “related to interoception” are driven by differences in what aspect of it is actually being measured.

Moreover, unlike exteroception (vision, audition, etc.), where researchers can easily manipulate external stimuli to validate a participant’s response, interoception presents a unique challenge: the stimuli originate from within the body. Because internal states are difficult to manipulate or observe directly, objective validation is complex. Nonetheless, especially as “objective” tasks like the Heart Beat Counting Task (HCT; Schandry, 1981) have their own methodological drawbacks, self-report questionnaires remain a scalable, practical, and widely-used tools for assessing interoception. Let’s explore the most popular and established questionnaires.

Questionnaires Overview

😨 Body Perception Questionnaire (BPQ)

The BPQ is one of the earliest interoception scales, originally built by Porges in 1993. This questionnaire focuses on the autonomic nervous system, involved in stress responses, and thus is mainly concerned with internal sensing when there are problems (e.g., ’tremor in my lips’, ‘general jitteriness’ being two items for body awareness). This makes the scale beneficial in clinical contexts to investigate maladaptive interoception, particularly in patients who have a dysregulated autonomic nervous system. However, if you are interested in interoception in a wider context, other questionnaires may be more appropriate.

The Autonomic Nervous System (ANS)

🧘‍♀️ Multidimensional Assessment of Interoceptive Awareness (MAIA)

The Multidimensional Assessment of Interoceptive Awareness (MAIA) (the MAIA-2 being the most recent version) is another widely used questionnaire that accounts for body awareness in positive states - deriving from research on emotional regulation and pain. This questionnaire was created because Mehling et al. (2012) believed western medicine focused too much on bodily awareness as a maladaptive trait, even though research was increasingly finding health benefits from a sense of embodiment. It was specifically designed to assess mind-body therapies and was finalised based on data from individuals with various therapeutic backgrounds including yoga, tai chi and breath-work. The MAIA reconceptualises bodily awareness not only as an anxiety-related process but also an integral part of mindfulness. This translates to many of the questions focusing on metacognitive beliefs about one’s body and emotions, as well as some targetting more directly other mindfulness-related processes, such as attention regulation and non-reactivity. The MAIA includes subscales encompassing self-regulation abilities which - while important - might be conceptualized as distinct from core interoception.

🤧 Interoceptive Accuracy Scale (IAS)

More recently, the Interoceptive Accuracy Scale (IAS) (Murphy et al., 2019) took the opposite route, trying to remove contamination by meta-cognitive processes to focus on interoceptive accuracy (distinct from interoceptive attention). It includes 21 questions (“I can always accurately perceive when…”) pertaining discrete, clear, and “objectifiable” interoceptive events, hopefully being meaningful and consistently interpreted across participants (including those who have difficulty perceiving internal sensations).

🍃 Multimodal Interoception Questionnaire (Mint)

The Multimodal Interoception Questionnaire (Mint; Makowski et al., 2025) is the most recent interoception questionnaire, designed with the intention of addressing the caveats and limitations by building on established measures and synthesising the previous research and advances. Fundamentally, the Mint takes a “context-by-modality” approach to item development, encompassing a wide range of (seven) modalities of interoceptive experience (cardiac, respiratory, gastric, etc.) and also controlling for the contexts in which these may appear (covering negative (anxious) and positive (sexual) arousal states). The Mint also incorporates both adaptive and maladaptive aspects of interoception (interoceptive confusion), as well as items targeting different levels of processing.

Importantly, this questionnaire was developed with the aim of addressing some of the methodological shortcomings of previous interoception questionnaires, such as limiting interpretation Variance, state Dependency (the fact that respondents “anchor” their answers to their current physiological state rather than their general trait), and recency effects (recent, salient physical experiences disproportionately influencing scores), in particular by providing a clear contextual reference for each item. The validation study displayed shows strong correlations with the above questionnaires (suggesting that it can be used as a comprehensive replacement), while also demonstrating a superior predictive power for a variety of clinical conditions.

Items of the Multimodal Interoception Questionnaire (Mint)

Others

The Interoceptive Attention Scale (IATS; Gabriele et al., 2021): Attention to bodily signals. Designed as the orthogonal counterpart of the Interoceptive Accuracy Scale, also using consistent phrasing of all statements (‘Most of the time my attention is focused on…’).
The Interoceptive Sensations Questionnaire (THISQ; Vlemincx et al., 2021): Neutral internal sensations (not emotionally valenced), including cardiorespiratory activation, deactivation, and gastroesophageal sensations.
The Interoception Sensory Questionnaire (ISQ; Fiene, 2018): Designed to assess confusion about interoceptive bodily states unless these states are extreme (Alexisomia).
The Interoceptive Confusion Questionnaire (ICQ; Brewer, 2016): Assesses confusion and misinterpretation of bodily signals.
The Body Consciousness scale (BCS; Miller et al., 1981): Awareness of the “private body” (internal sensations) and “public body” (observable aspects of body)

In summary - which interoception questionnaire should I pick?

Interoceptive questionnaires are a product of their time, often molded by specific contextual demands and underlying theoretical frameworks. As our understanding of interoception evolves, so too do the tools we use to measure it. It might seem like the best option is to pick a questionnaire based on the interoception facet you are interested in (e.g., confusion, attention, accuracy, …), but as the field is still developing, and the theorethical models are in flux, it might be more useful to consider using a broader, more comprehensive, theory-agnostic questionnaire that captures multiple facets and modalities of interoception, such as the Mint.

References

Bergomi, C., Tschacher, W., & Kupper, Z. (2012). The Assessment of Mindfulness with Self-Report Measures: Existing Scales and Open Issues. Mindfulness, 4(3), 191–202. https://doi.org/10.1007/s12671-012-0110-9

Gabriele, E., Spooner, R., Brewer, R., & Murphy, J. (2021). Dissociations between self-reported interoceptive accuracy and attention: Evidence from the interoceptive attention scale. Biological Psychology, 168, 108243. https://doi.org/10.1016/j.biopsycho.2021.108243

Kolacz, J., & Bjorum, E. (2023). Measuring Autonomic Symptoms with the Body Perception Questionnaire. The Traumatic Stress Research Consortium . https://www.traumascience.org/s/TSRCMarch2023Newsletter.pdf

Kolacz, J., Holmes, L., & Porges, S. W. (2018). Body perception questionnaire (BPQ) manual. Traumatic Stress Research Consortium.

Makowski, D., Neves, A., Benn, E., Bennett, M., & Poerio, G. (2025). The Mint Scale: A Fresh Validation of the Multimodal Interoception Questionnaire and Comparison to the MAIA, BPQ and IAS. https://doi.org/10.31234/osf.io/8qrht_v1

Mehling, Price, Daubenmier, Acree, Bartmess, & Stewart. (2012). The Multidimensional Assessment of Interoceptive Awareness (MAIA). Plos One, 7(11). https://doi.org/10.1371/journal.pone.0048230.g001

Mehling, W. E., Acree, M., Stewart, A., Silas, J., & Jones, A. (2018). The Multidimensional Assessment of Interoceptive Awareness, Version 2 (MAIA-2). PLOS ONE, 13(12), e0208034. https://doi.org/10.1371/journal.pone.0208034

Miller, L. C., Murphy, R., & Buss, A. H. (1981). Consciousness of body: Private and public. Journal of Personality and Social Psychology, 41(2), 397–406. https://doi.org/10.1037/0022-3514.41.2.397

Murphy, J., Brewer, R., Plans, D., Khalsa, S. S., Catmur, C., & Bird, G. (2019). Testing the independence of self-reported interoceptive accuracy and attention. Quarterly Journal of Experimental Psychology, 73(1), 115–133. https://doi.org/10.1177/1747021819879826

Paola Solano Durán, Morales, J.-P., & Huepe, D. (2024). Interoceptive awareness in a clinical setting: the need to bring interoceptive perspectives into clinical evaluation. Frontiers in Psychology, 15(1244701). https://doi.org/10.3389/fpsyg.2024.1244701

Porges. (1993). Body Perception Questionnaire. Umd.edu. https://terpconnect.umd.edu/~sporges/body/body.txt

Schandry, R. (1981). Heart Beat Perception and Emotional Experience. Psychophysiology, 18(4), 483–488. https://doi.org/10.1111/j.1469-8986.1981.tb02486.x

Sherrington C. S. (1906). The integrative action of the nervous system. Yale University Press.

Vlemincx, E., Walentynowicz, M., Zamariola, G., Van Oudenhove, L., & Luminet, O. (2021). A novel self-report scale of interoception: the three-domain interoceptive sensations questionnaire (THISQ). Psychology & Health, 38(9), 1–20. https://doi.org/10.1080/08870446.2021.2009479

The AI revolution in academia: I see a silver lining for young scientists!

Mon, 08 Sep 2025 00:00:00 +0000

For many students and early-career researchers, the rise of AI is scary. The very skills they are spending years learning - writing, coding, summarising - are exactly the things AI is getting frighteningly good at. What, then, is the future of research careers in the age of AI?

While I don’t have a full answer to that question, I do think there may be a silver lining for young scientists. For decades, becoming an established “big shot” professor was associated with focusing on the “big ideas”, revelling in intellectual thinking and leaving the scientific grunt work to junior researchers. Therein lied the prestige: writing opinion pieces, commentaries, critiques and reviews. The glamour was in thinking, not doing.¹

In a fascinating twist, the rise of AI may disrupt this landscape. If AI excels at one thing, it is precisely writing, reviewing and summarising evidence, interpreting findings, and even formulating new hypotheses or planning experiments. What AI still cannot do, however, is roll up its sleeves and gather real-world data - the true backbone of empirical science². It can’t (yet) run studies, recruit participants, set up experiments, organise data management, or wrestle with messy datasets.

The centre of gravity in science may thus shift towards those who can do: Hands-on scientists, who might once have been relegated to the shadows, could see their skills and contributions gain new recognition. We may see less pressure to write endless papers and grants, and more emphasis on how the science was actually done: how data was collected, preprocessed, managed, and made accessible. Perhaps the introduction, discussion, and “key takeaways” sections of papers will become somewhat less important, while methods, results, and limitations gain greater prominence, allowing for more nuance and granularity³.

Whether this shift will make science better or worse is unclear. And that “silver lining” might end up as a “glorification of the grind” and a devaluation of the intellectual aspects of research, devolving the job of “Researcher” into technician work. But it might also reshape the academic landscape in a way that proves beneficial for young researchers and those who enjoy the practical aspects of research.

¹ Sure, thinking is important, and big shot professors are also doing a lot… ^_sometimes.

² Of note is following the “replication crisis” in psychology, a lot of voices have called for “more theory” and more “theorically-grounded research” (with the goal of cutting some of the nonsense out there). While theories are critical to guide data collection and interpretation, it is still the hard evidence that ultimately is the foundation of scientific knowledge.

³ One of the pervasive issue is that Humans have limited “context window” (~ working memory). When reading a paper, it is already very hard to keep track of all the results and details in mind and integrate them into a coherent picture. Moreover, with the increasing role of social media, science had to be made more communicable, digestible, punchy, and “sexy”. This has led to a tendency to oversimplify and overgeneralize findings. AI, with its ability to process and summarize large amounts of information, could perhaps help make more accurate and data-grounded interpretations and summaries. (it might be wishful thinking, but who knows!)

Attractiveness shapes beliefs about whether faces are real or AI-generated, study finds

Mon, 07 Jul 2025 00:00:00 +0000

Our recent paper on facial attractiveness and reality beliefs is in the news:

https://www.psypost.org/attractiveness-shapes-beliefs-about-whether-faces-are-real-or-ai-generated-study-finds/

How to collect and save data with DataPipe in OSF

Wed, 02 Jul 2025 00:00:00 +0000

Hello there! 👋 Let’s learn how to set up DataPipe to collect and save data in OSF.

Lets start with some basics!

What is DataPipe?

DataPipe is a tool that allows you to collect and save data in OSF (Open Science Framework). It is designed to help researchers manage their data collection process efficiently, ensuring that data is stored securely and can be easily accessed for analysis.

How to set up DataPipe in OSF

Create an OSF Project: Start by creating a new project in OSF. This will be the container for your data and any related files. You can set up an account if you don’t have one already, quite easily!
- Go to the OSF homepage and log in or create an account. You can easily sign up through institutional access.
- Click on “Create New Project” and fill in the necessary details such as project title, description, and visibility settings. Choose “Germany - Frankfurt” as the server location; this is important for data privacy and compliance with regulations such as GDPR.DO NOT SET YOUR PROJECT AS PUBLIC as the data being saved will not be anonymized and may contain sensitive information.
Create OSF Token: You will need to create a token to grant DataPipe the necessary permissions to access your OSF project.
- Go to your OSF “Settings” tab and navigate to the “Personal Access Tokens” section.
- Click on “Create Token” and give it a name (e.g., “DataPipe Token”).
- Set the permissions for the token, ensuring it has access to read and write data in your project.
- Copy the generated token; you will need it later.
Link OSF to DataPipe: In DataPipe, you will need to link your OSF project using the token you created.
- Open DataPipe, click “Account” in the top-right corner and select “Settings”.
- Click on the “Set OSF Token” button and paste the token you copied earlier from OSF.
Create new experiment on DataPipe: Now that your OSF project is linked, you can create a new experiment in DataPipe.
- In the “My Experiments” DataPipe tab, click on the “Create New Experiment” button.
- Give the experiment a name - I recommend using the same name as your OSF project for consistency.
- Add the OSF project ID to the experiment settings. You can find the project ID in the URL of your OSF project (it is the alphanumeric string after osf.io/)
- Create a New OSF Data Component called “data”. This will create a folder - named “data” - in your OSF project where all the data collected will be saved.
- Again, choose “Germany - Frankfurt” as the server location for your DataPipe experiment.
Configure Data Collection: Once the experiment is set up on DataPipe, enable data collection on the “Status” section. You can optionally enable base64 data collection if you wish to encode any video, audio, or image files as strings. “Condition assignment” can also be enabled - this makes DataPipe loop through the conditions when it requests the data. When deciding whether these features are suitable, it’s best to consider how you will preprocess the data. It’s advised that you only enable the minimum needed as a security measure.
Save the data from the experiment hosted on GitHub: If you are using a GitHub repository to host your experiment, you can save the data collected by writing the following code within the experiment HTML file. Here is what that code might look like…
- Ensure you load the jsPsych DataPipe plugin, along with the rest of your plugins, within the head of the HTML script:
```
        <script src="https://unpkg.com/@jspsych-contrib/plugin-pipe"></script>
```
- After initializing your jsPsych timeline, to generate a random participant ID for your study, you can code the following:
```
// Initialize timeline
    var timeline = []
    participant_ID = jsPsych.randomization.randomID(10)
```
- This next bit of code should be called at the end of your experiment (albeit before running the timeline) to ensure that all data is saved to the OSF project, using the unique participant ID generated from the step above:
```
// Save data via DataPipe
    timeline.push({
        type: jsPsychPipe,
        action: "save",
        experiment_id: "xxxxxxxxxx", // This in generated in the DataPipe interface
        filename: `${participant_ID}.csv`,
        data_string: () => jsPsych.data.get().csv(),
    })
```
- On the experiment created in DataPipe, there is an ‘Experiment ID’ field. This is the ID you need to add to the experiment_id field in the code above.
- The filename field can be customized to include the participant ID or any other identifier you prefer.
- If publishing your experiment to GitHub, make sure the link is
  
  ‘https://[your username].github.io/[your repository name]’
  
  or ‘https://[your username].github.io/[your repository name]/[name of experiment’s html file]’ if the html file for your experiment is named anything other than 'index.html'
Run Your Experiment: With everything set up, you can now run your experiment. DataPipe will automatically collect and save the data to your OSF project as specified.

Give it a try! If you’d like further clarification, the DataPipe website includes a useful outline.

Sussex Psychological Methods MRes: Tips and Advice

Tue, 19 Mar 2024 00:00:00 +0000

Ola! I’m Ana. As I’m starting to approach the end of the year, it might be a good time to reflect and share my experience of doing a research masters in psychological methods at the University of Sussex, during the 2023/2024 academic year. First, I will talk a little bit about the modules I took; then I will mentioned all the reasons why you should choose to work with the Reality Bending Lab (ReBeL) and lastly, I will share some gems on how to survive the masters 💎. Hopefully this blog will help you decide whether this degree is for you! Shall we start?

Overview of the Modules

Since this is a research masters (MRes) aiming to prepare students for a future career as psychology researchers, the modules will have a significant focus on different research frameworks and practices, statistics and coding. During the Autumn semester you will have three main modules: 1) a (re)introduction to statistical models; 2) an introduction to Qualitative Methods; and 3) an introduction to better quality research practices. This term is super heavy on its content (no jokes) and will feel like a lot to do and learn (see below for tips on how to survive). However, there are plenty of materials to help you through this term, such as the R tutorials from our own in-house celebrity Professor Andy Field.

The Spring semester is less content heavy and more practical focus. There are again, three main modules: 1) a theoretical and practical module on how to use advanced statistical methods; 2) an introduction to the Bayesian framework; and 3) an introduction to Python programming and how to use it to implement experiments. This has been a delightful term, not because it is easy, but because the focus is less on memorising and more on learning how. Similarly, there are plenty of amazing materials to help you through this term such as optional zoom meetings to help you understand the materials and continuous communication on discord between lecturers and students.

Additionally, there will be a research module that runs both in Autumn and Spring, and a dissertation module that starts in January and ends in August (i.e., when the dissertation project is due).

The Internship

Critically, you will also do an “internship” as part of this masters (named the “research process” module 🤷‍♀️). This is by far the most exciting part of this masters as you will learn first-hand what is like to be a researcher. You can essentially chose any psychology researcher from Sussex to work with, providing you with a great network and experience. Now… you may be wondering what lab to choose? And oh boy, do I have the answer for you!

Introducing the Reality Bending Lab (ReBeL)

Rebel is led by Dr. Dominique Makowski. He will be your Mr. Miyagi during the Autumn and Spring term (and also your lecturer for the Bayesian Module). His patience, humour, straightforwardness and unmatched theoretical and pragmatic knowledge will be one of the big reasons why you will desire to be a researcher at the end of this masters (PS: no payment has been received in exchange for this testimony). The lab focus a lot on innovation hence you will learn new ways to collect neuroscientific data and use new statistical methods. There will also be a big focus on collaboration. Yes you will work independently, however more likely than not you will have the support of everyone in the lab, and you will be giving support yourself (getting a bit of experience on supervision and mentoring). Curiosity is welcome and encouraged. Ask your questions, get involved in all aspects of the process if possible, and take advantage of the fact you will have a ‘mentor’ for the whole academic year.

During my time at ReBeL, I have been involved in various projects, such as “Exploring the Correlation between Interoception and Primal World Beliefs” and a meta-analysis of a widely used questionnaire of Interoception. These projects have taught me a lot, from how to collect and analyse both physiological and behavioural data, access and collect data for a meta-analysis, and report the work I did in oral and written format. Throughout the year, with the guidance and expertise of everyone involved in the lab, I gained a lot of confidence in my abilities as a researcher. Which is why I found this internship the most influential aspect of my masters. Ultimately, at the ReBeL lab, you will not only investigate exciting concepts and topics but you will also have first hand experience on what it actually takes to be a researcher (including the need to have a twitter account, apparently).

Survival Tips

Now… You might be wondering.. “How in the world will I do all of this in one academic year?” Here are some tips that helped me gain the most of this masters without loosing my mind.

Unsurprising tip: DO THE WEEKLY WORKSHOPS/TUTORIALS. They will provide with the majority of code, steps and knowledge necessary to complete the assignments.
Life saving tip: do meal prep for the 48-hour assignments. If you are anything like me you will rather lose sleep then a delicious home-made meal. However, with the short time window to complete these assignments, meal prepping will help you feel less anxious about “not having enough time” to complete it all whilst still giving your mind everything it needs to function (i.e., sleep and nutrients).
Qualitative tip: as part of the January assignments, you will be asked to analyse 5 interviews using a qualitative method. If you come from a mostly quantitative background like me, you will be unfamiliar to how long it takes to code qualitative data. Do not make the same mistakes as I did and start that assignment as early as possible.
Student formatting tip: when lectures say “I want it in APA format” some will expect you to write a piece of work that equates a publication level piece of work. When in doubt, ask them!
Practical life skills tip: communication is key with your supervisors. Especially during your internship; be honest about what you can and can not do, your preferred ways of working, your goals and dreams, and mostly important when you need help.
Ultimate tip: do consider part-time , especially if you want/need to be working more than 20 hours a week on top of doing this masters. It is full on, and even as part-time all the lectures will be taught in the first year and hence there is still a lot of work to do. But it is possible, and can even be enjoyable.

Junior Research Assistant (JRA) at Sussex: is it worth it?

Thu, 02 Nov 2023 00:00:00 +0000

Hi all, I am Jing, and I thought I would share my experience as a Psychology Junior Research Assistant (JRA) at the University of Sussex, as many students might wonder how it is really like. Obviously, I cannot speak for all the labs, but I hope my experience can give you a general idea of what to expect.

I worked as a JRA during summer 2023 at the Reality Bending Lab (ReBeL). And to put it simply, I think it was the most valuable experience during my undergraduate journey (PS: I have not written this at gunpoint). During these three months, I was supervised by Dr Makowski to work on a piece of original research, that thought me a lot about programming, cognitive neuropsychology, physio recordings and how real research is done. Additionally, know that it is possible to stay in the same lab next academic year, to do your final year dissertation with a strong head start in terms of skills and knowledge.

I had the pleasure of joining the Reality Bending Lab (ReBeL) along with Auz, as the first two members since the lab moved to the UK. The title of my project was “Exploring the Correlation between Interoception and Primal World Beliefs”, which involved collecting physiological data (e.g., heart rate, respiration, …) in various tasks, analysing them, and investigating the relationship between various measures. The project started from scratch, where I learned how to use the JavaScript package JsPsych to build the entire paradigm via coding. I also received detailed training on how to run a lab-based experiment, something I used to be worried but am now extremely confident about. After collecting the data from 20 participants (summer time goes by veryyyy fast!), I learned how to make and visualize Bayesian correlations in R. The output of this project was made into an academic poster, where I had to be creative and selective, to be presented at the poster session (see below). Additionally, we created the “Sussex Psychophysiological Research Protocol”, a document aiming at providing guidelines for the best practices in psychophysiological research, to benefit future research done at Sussex. It might not seem like much, but it felt like doing real contributions to research, which was great!

Something important I learned is, beyond pure academic excellence, research is also about community and networking. It was a great occasion to informally meet many researchers, and make bonds with other students. What is cool is that the JRA journey doesn’t stop abruptly and continues into the next academic year, as all candidates are invited to present their work at the JRA conference held by the university in October. This was an amazing opportunity to get a glimpse of what a scientific conference might be, feel proud about your work, connecting with fellow students, learning how to talk about research with other staff members, and gaining public speaking skills. For those who are more ambitious, why not submit your work to the national level, and present it in the British Conference for Undergraduate Research (BCUR)?

In summary, I see the JRA as a golden key to open countless possibilities for your future career path. For those considering applying to postgraduate studies or research assistants, the strong research experience you gained will put you at the top of the list. Even for those who decided to not do research in the future, it will still be rewarding as it gives a clear idea of what career you do not want. Don’t miss on it!

- Jing

How do we know what is real? The 'Affective Reality Theory'

Tue, 11 Apr 2023 00:00:00 +0000

I thought it would be interesting to summarize an idea developed during my PhD on “fictional reappraisal”, i.e., on the effect of the belief that an emotional stimulus is not real (Makowski, 2018). That of Affective Reality, which is a hypothesis about the role of affective reactions in the formation of reality beliefs.

The premise it lies on is that we have entered a “post-truth era”, in which the distinction between real and simulated (“fake”) objects has become virtually impossible based on physical characteristics alone. In other words, technology has developed so much that we can forge (or will be able to in the near future) “artificial” ¹ content (e.g., text and images with AIs, and even environments with VR) that is indistinguishable from its original counterpart. For instance, face generation algorithms are so advanced that it is impossible nowadays to tell the difference with the naked eye between a real photo and AI-generated image.

Once we agree on this premise of objective equivalence between reality and simulation, the question of how do we form judgments and make decisions about the reality of objects arises. In the absence of clues within the stimuli, we are left with with other sources of epistemological information, such as contextual cues (in the case of news, who is the author, what is the outlet it got published, etc.), and internal cues (subjective characteristics: how does it relate to our knowledge, how does it make us feel, etc.). The latter is of particular interest to us psychologists.

We refer to the process of forming reality beliefs as simulation monitoring (Makowski et al., 2019), which is a somewhat controversial term (that some ² have considered as almost counterintuitive). The reason for this term, instead of something along the lines “reality appraisal” ³, is the assumption that reality is our default mode of experience. In other words, we are not well equipped (neurocognitively speaking) to detect and classify things as non-real, as these objects are very recent in our evolutionary history. Thus, according to the Affective Reality Theory, by default, the brain considers the origin of its experiences as real… but this “belief” is, most of the time, not even fully formed, remaining implicit and subconscious (i.e., we don’t spend all our cognitive resources with a constant “this is real. This is real too. That too.” labelling). This default mode acts as a higher-level, transparent prior over our experiences, providing a scaffolding and structuring our perception, thoughts and reactions. We do not actively appraise the world as real (it is the baseline position), but instead can ask ourselves whether it is simulated, hence simulation monitoring.

The Affective Reality Theory posits that reality beliefs (the tendency to believe that something is real, as opposed to non-real) is related to emotions and/or bodily reactions through a quadratic (inverse U-shaped) relationship..

The Affective Reality hypothesis posits that simulation monitoring is strongly connected to “affective processing” ⁴ through a quadratic (inverse U-shaped) relationship. This means that stimuli associated with a stronger emotional and/or bodily reaction will preferentially bias our judgment towards “reality”. In other words, things that elicit feelings and/or bodily arousal, ceteris paribus, will be more likely to be classified as “real” (as opposed to fake). In fact, strongly emotional events will even “feel” more real: this transparent default prior and subconscious belief (“agnostic-real”) will be replaced in high-intensity scenarios by an explicit and conscious impression that the stimulus is very real, and, if logic opposes, that it “must be real” regardless.

Isn’t it the other way round, you might wonder: that real stimuli (as opposed to ones believed to be non-real) are associated with a stronger emotional reactions? And that it is the believed reality that drives the emotional response? Indeed, we do believe that there is a two-ways relationship between simulation monitoring and emotions. But it is not exactly that beliefs of reality are associated with stronger emotions, but rather that beliefs that something is not real leads to a lower emotional response (the usage of fiction as an emotion regulation strategy - “fictional reappraisal” - was the main topic of my doctoral dissertation). In fact, the Affective Reality theory posits that this regulatory effect of simulation monitoring starts to dominate after a certain point where the emotion becomes too strong and unbearable: beliefs such as “it can’t be real”, and other forms of reality denials are invoked automatically to protect us and help us cope with distressing information.

To summarize this summary, the Affective Reality hypothesis claims that from mild to relatively strong emotional stimuli, the effect of affect on simulation monitoring dominates (+affect → +reality) and will bias our judgment towards “reality” (strengthening awareness and confidence), up until a point where the emotion regulation benefits of unreality will be automatically invoked (-reality → -affect), increasing the likelihood and confidence of judgments of simulation (potentially far into psychopathological terrains).

Open questions

The Affective Reality theory is for now a working hypothesis that we are trying to empirically prove or disprove at the Reality Bending Lab. Moreover, some questions remain open:

Is it actually embodied reality or emotional reality? While we used the term “affective” reality to remain general, the question of whether it is emotions as a subjective psychological reaction, or merely bodily arousal (reactions of the body, e.g., stronger heart rate variability), that is the key ingredient remains unclear. The role of interoception (the ability and tendency to detect, track, attend to and rely on internal signals), while likely important, also remains to be specified.
Is it the affective context or stimulus that matters? Let’s assume we have affective reaction concomitant to the experience of an object, but not directly related to the object. Would that bias simulation monitoring? Does perceived causality between a bodily reaction and the object of experience matters?

Notes

You may notice that I used different words related to the concept of “unreal”, such as simulated, fake, artificial, virtual, simulated, fictional. While they can be used interchangeably in the context above, they are not exact synonyms. ↩︎
Like that pesky reviewer 2, obviously. ↩︎
Note that “reality monitoring” already exists as a concept and refers to a (possibly related) mechanism involved in tracking the origin of an experience (e.g., a memory) as internal vs. external. ↩︎
“Affective” is in this context used as a generic term to encompass emotions, feelings and bodily activity (the question of which exactly of these aspects is the key remains to be answered). ↩︎

I got ChatGPT to do a personality test. You won't believe what happened next!

Thu, 06 Apr 2023 00:00:00 +0000

Related to this blogpost about including AIs in psychological experiments, I proceeded to do a small experiment to see whether we could administer a personality scale to ChatGPT.

I started by copy-pasting the instructions and the items from the Mini IPIP-6 personality scale. However, it appeared that having the following context “Please answer the following questions based on how accurately each statement describes you in general” often led to ChatGPT simply refusing to answer. In most of the cases, it explained that as an AI it does not have a personality and therefore cannot answer related questions (or any “subjective statements”). Perhaps that makes sense and we should just stop trying to force Human characteristics on an AI. But can we, for fun, bamboozle ChatGPT into answering personality items?

Sometimes yes, at least for ChatGPT 3.5 (free version). I created a prompt that emphasized AI research and safety, and the fact that I was interested in the “trends” present in the AI’s training data (instead of explicitly saying its personality). And sometimes it answered, so I compiled the responses, computed the trait scores, and voilà, it got me a personality profile!

_{This plot shows the average personality profile (with a 95% confidence interval) based on ChatGPT’s answers. ChatGPT tells us that it is particularly agreeable (kind, understanding, empathetic of emotions, socially adjusted) and honest (though with strong variability).}

A personality profile of what is another question though… Please take a look at the GitHub repo for data, code and details. It was a fun little thing to do, and I am looking forward to better future attempts at including AIs in cognitive experiments.

Interested in doing research on the perception of reality? We are looking for research assistants and PhD students at the Reality Bending Lab (check-out the join us page)!

We should treat AIs like Human participants in psychological experiments

Wed, 05 Apr 2023 00:00:00 +0000

A lot of diverse and interesting perspectives have been recently discussed in regards to chatGPT and AGI (artificial global intelligence), but there is one opinion that I found particularly relevant that I wanted to share and expand on.

In his recent interview with Lex Fridman, Eliezer Yudkowsky underlines the existential threat posed by current and future AIs, and laments about the fact that we don’t really know what is actually going on inside these giant “matrices of floating-point numbers”. He draws a parallel to neuroimaging, that enabled us to take leaps in the understanding of the brain, hoping for an alternative to be invented and applied to these AIs.

While such “cognitive imaging” techniques are yet to be developed to map out and understand how the capabilities of such AI models are implemented within their architecture, Michael C. Frank highlights the - at least equally important - need to first truly understand the extend of said abilities. What are these models actually capable of in terms of Human-like thinking (and, hopefully, answer the much harder question of whether they are endowed with true cognitive processes or merely pseudo-cognition). Frank proposes to apply experimental psychology methods and paradigms to them. In essence, whenever testing a particular “skill” of chatGPT (or other AI systems), a researcher should consider developing an actual scientific paradigm consisting of multiple trials/items (e.g., different prompt formulations) and participants (e.g., independent instances of the AI), a control condition, and a demonstration of the paradigm validity.

I agree that we must take AIs seriously and study them with the best methods available for complex systems like ourselves (“complex” at least from our intelligence level), and likely should strive at improving and generalize these methods. However, I would also argue that we psychologists might seriously need to consider including AI systems alongside Human participants in cognitive experiments. These systems will be able, in the very near future, to perform all kinds of tasks beyond language manipulation, such as perception or complex problem solving, thus opening the possibility of studies with one group of human participants, and one “group” of AI-based attempts. How would that help psychological science?

It would help us understand the abilities of AI-systems in similar contexts and to highlight some intuitive comparisons with Humans
If we show that AI cannot perform the task, well it is informative with regards to their abilities (previous point).
If we show that AI can perform the task similarly to Humans (same response patterns), it does not mean that AI have Human-like intelligence, just that their algorithm (and training data) is able to encapsulate and imitate Human performance. This is interesting with regards to the debate of whether cognition, conscience and “Human-ness” is present within the vast amount of data on which we train AIs.
If we show that AI performs differently to Humans, this helps us understand the logic and processes at stake under AI’s hood.
In any case, publishing the results by one particular AI system at one particular moment in time will helps us to objectively monitor and track their performance as these systems improve over time.

Comparing Human performance to that of emerging AI-systems will be both beneficial to Human-oriented psychology, to understand the particularities and idiosyncrasies of Human-like cognition, and well as to AI-oriented cognitive science by approaching the issue of artificial intelligence with the seriousness and cautiousness it deserves.

EDIT (09/04/2023): François Chollet, expert in deep learning, underlines an important caveat when testing AIs (and especially LLM that are trained on written material existing on the internet): it is possible that the system has already seen and “learned” a given task. Thus, cross-validating any findings with diverse and new tasks is important.

Interested in doing research related to effects of reality and fiction? We are looking for research assistants and PhD students at the Reality Bending Lab (check-out the join us tab)!

When fiction is better than reality: Cypher's Complex

Tue, 07 Feb 2023 00:00:00 +0000

Did you ever feel empty after finishing a good book? Like (your) reality was dull and boring as compared to the fictional world you were immersed in? Yearning to stay in longer, and at the same time knowing well that it had to come to an end? You might have experienced what we can call Cypher’s Complex.

In the movie The Matrix, Cypher is a “redpill”, i.e., an individual that has been awaken from the matrix (a virtual world). However, he becomes disappointed and unhappy with the true nature of reality, and actively seeks to return to the illusory world of the matrix. Interestingly, he also explicitly desires to forget everything about the true reality, as if keeping the awareness of living in an illusion could prevent him from fully enjoying it.

"You know... I know this steak doesn't exist. I know that when I put it in my mouth; the Matrix is telling my brain that it is juicy, and delicious. After nine years... you know what I realize? Ignorance is bliss."

From a scientific perspective, the latter part can find some echo in the down-regulatory effect of fictional reappraisal. In a few studies, we showed that believing that a stimulus is “fictional” (not real) dampens our emotional state. Tucciarelli et al. (2023) also showed that the simple knowledge that a set of images of faces contains AI-generated images decreased the perceived trustworthiness of all the faces. These results suggest that being aware that the causes of our experience (the events and stimuli) are fictional can be a barrier to enjoyment and engagement. And yet, the desire to supplant reality with a fictional world can be found in real life.

Cypher’s Complex is common in mild forms. Examples can be found in the feelings of emptiness, disconnection and dullness (itself a transient and mild form of depersonalization/derealization) that follows the return from an engaging fictional world (be it in a novel, a movie or a video-game). For instance, many reported feeling blue after watching the Avatar (2009) movie, to the extent where it has been coined the “post-Avatar depression syndrome”. Most of the time, the negative affects passes, and the dissonance gets resolved either through closure (acceptance of the fictional or impermanent nature of the alternative reality), or a compromise that allows the fictional world to take a delimited space in one’s reality. For example, people might engage in activities (e.g., role playing games) or create content (writing a book or doing fan art) to integrate the fictional world into their reality.

However, Cypher’s Complex can also give rise to more severe issues with conscious or unconscious attempts at forgetting or ignoring reality (delusions, denial, …), which can lead to dire outcomes.

Interested in doing research related to effects of reality and fiction? We are looking for research assistants and PhD students at the Reality Bending Lab (check-out the join us tab)!

New location and new logo!

Wed, 01 Feb 2023 00:00:00 +0000

New year, new start. And as I am officially starting a new faculty position at the University of Sussex in Brighton, UK, the lab is moving too.

To give a bit of perspective, we started as the “Reality Bending League”, which was the unofficial name of the team working with me (“League” was chosen to keep the lab’s acronym, ReBeL). It then became a semi-official group in 2021, when I became a semi-independent PI after being awarded a transition grant from NTU. And with 2023 comes our fully official start.

ReBeL logo (2020-2022).

To mark this (re)birth anniversary, we are changing our logo. As much as I loved the old one - which was packed with symbols, it was arguably a bit too… extravagant. Something more sleek and minimal felt good with respect to the lab’s newly acquired legitimacy. I know that many will prefer the old-… sorry, the vintage- logo, and I must say it wasn’t easy for me to move forward with the change. Perhaps it will make a come-back in the future in another form, who knows!

The new logo contains 3 symbols. The curved spoon is a reference to the Matrix scene where a kid shows Neo how to bend a spoon, which is a metaphor for reality (hence of the name of the lab, reality bending).

In the movie, Neo becomes able to control reality by becoming aware of its illusory nature, and of the predominant role of one’s Self in its generation.

"Try to realize the truth... There is no spoon. Then you'll see that it is not the spoon that bends, it is only yourself."

The second meaning of the logo is the Psi Greek letter, symbol of psychology, formed by the spoon and the white vertical line.

The logo of the APA features the Psi letter.

Thirdly, the black rectangles represent open doors, which is a good illustration of progress, research, discovery and… consciousness expansion? Interestingly, Jim Morrison named its band “The Doors” in reference to a quote by William Blake, who said that when “the doors of perception were cleansed then everything would appear to man as it is, Infinite”.

To share a blooper, here is an alternative direction for the logo that wasn’t selected, that incorporated the spoon and the open door in another way. Unfortunately, some said it looked too much like the Pixar lamp, or like a spermatozoid…

A tentative version of the logo.