Hello there 👋 My team and myself are part of the Clinical Brain Lab’, in which we chart a new research direction.
Summary. Our conscious experience of reality being highly flexible, we study the mechanisms that lead to its distortion, and explore how reality alterations can in turn inform us about our Selves. Find out more about what is reality bending here.
Topics. This includes investigating the role of active mechanisms (e.g. cognitive control, emotions, interoception, immersion, meditation, deception…) in shaping our sense of reality (i.e., the feeling and belief that we and elements of our environment are real), as well as their crystallised form giving rise to dispositional characteristics in the form of personality phenotypes and neuropsychological profiles. Additionally, we develop novel methods (advanced statistical algorithms, tasks and tests) and apply cutting-edge techniques (multimodal neurophysiological recordings) to gain insight into the mechanisms at stake. Finally, we try to understand our research in a larger historical, epistemological and philosophical frame, informing us as we move ahead.
Approach. We place ourselves within a neuropsychological perspective, meaning that we analyse and dissect the phenomena of interests in terms of dynamic interaction between neurocognitive mechanisms and brain processes, and aim at validating or extending our results to particular populations, such as patients suffering from neuropsychiatric conditions.
What are the mechanisms by which our belief and feeling of reality can be altered? What are its consequences?
How do cognitive abilities unfold into personality traits and metastable neuropsychological profiles?
What is the history of psychology and psychiatry? What are the methods and tools of tomorrow?
The Nanyang (which means “Southeast Asia” in Chinese) Technological University (NTU) is one of the two main universities in Singapore. Although relatively young compared to most western institutes, NTU is a dynamic and vibrant university that has quickly achieved an international leadership in many areas. NTU has been ranked as 1st in the ranking of young universities in the QS World University Rankings since 2015, and is considered as a top-tier research institution in Asia.
Aside from its academic qualities, NTU is known for its green campus (NTU has been listed as one of the world’s most beautiful universities) and its architectural landmarks, making it an ideal location to foster a positive growth mindset.
Meet the people I work with (check-out the full lab here).
"Do not try and bend the spoon, that’s impossible. Instead, only try to realize the truth… There is no spoon.“
In 1896, the Lumière brothers presented a 50-seconds long movie of a train’s arrival at a station. Intense fear and awe rose up among the audience, as if they could not believe that it was not a real train. Several decades later, the edges of our reality still continue to fade. Through virtual reality, augmented reality, deep fakes and new forms of fictions, simulations of all kind populate our everyday experience and challenge our intuitive feeling and belief concerning its reality.
One of the component of the sense of reality takes the form of a more or less explicit belief that we hold regarding the information that we process. Is it “real” vs. “unreal”? Qualifiers that in this context are umbrella terms for adjectives such as genuine, authentic, true or on the contrary fake, fictional, forged and virtual.
Another more embodied, implicit dimension of the sense of reality is the feeling of reality.
The modulation of reality could also be connected to everyday processes, such as deceptive behaviours and lies. However, the creation and detection of information made with the purpose of fooling another might require a different set of cognitive processes, such as empathy, theory of mind, and planning.
Reality bending also shares a strong relationship with emotional processing, modifications of the sense of reality might be at stake in some forms of voluntary or involuntary emotion regulation mechanisms (such as distancing, decoupling, defusion, decentering or fictional reappraisal).
Exploring the fundamental features of what makes you “you”.
We are complex organisms which inter-individual unicity is blatantly salient, as demonstrated by the tremendous variability of behaviours, beliefs and experiences. And yet, it seems that the subtle combination of shared features in regards to heritage and experiences results in pseudo-similar patterns of being, that can be isolated and described as “traits”, “types”, “profiles”, or “disorders”.
Whether natural or artificial categories and dimensions, I am interested in pursuing the ancient quest for the description and classification of such profiles of being. I hope to extend this search beyond concepts like “personality types” and “cognitive profiles” by incorporating the core neurocognitive processes at play in multiple layers of the Self, and see how they unfold into metastable characteristics.
In this journey, the first step is to try gaining access to one’s core Self via objective behavioural measurements, which encompasses the development of new - or improvement of existing - measures (questionnaires, cognitive tasks, …).
The relationship between high-level personality (in its very large sense of typical behaviour) and lower-level aspects of the Self (measured at an inter-individual level), including cognitive abilities (e.g., response inhibition), neural wiring (e.g., features of the predictive coding system) and embodied processes (e.g., interoception) is an under-investigated question. I focus on the contribution of cognitive control and interoception to mid-level mechanisms like emotion regulation and self-control and high-level personality profiles.
As most of the core dimensions constitutive of our Self are likely to be individually continuous in nature, the distribution of individuals in the multidimensional space that they create together remains an open questions. Are we evenly spread, or are there densely populated subspaces, i.e., in statistical multivariate clusters, that would justify categorical approaches to personality.
Travelling in the past and charting the future of neuropsychology
Neuropsychology and its connected disciplines are an evolving science, with a fascinating history and an exciting future. I do believe that in order to be able to push the boundaries of our field into uncharted territories, one must be endowed with some level of knowledge and understanding of the historical perspective and of the trajectories of ideas that we are part of. As such, I’m interested in exploring the roots of our current theories, excavating ancient perspectives that resonate with today’s interpretations and connecting the past with the present to chart our march onwards.
Today’s (and future’s) psychological methods largely take the form of software, code and algorithms. I am interested in developing and exploring the usage of cutting-edge statistical methods and theoretical frameworks (Bayesian statistics, machine learning, …) to answer challenges. By developing user-friendly tools and software to help users with their data analysis, I hope to promote the implementation of methodological best practices to elevate the quality standards of the field.
My research is methodologically located at the crossroads of traditional experimental neuropsychology (developing and using elegantly designed cognitive tests) and modern cognitive neuroscience (heavily relying on neuroimaging devices). Within this landscape, I am interested in promoting the combined usage of a large variety of techniques (bodily signals, neurophysiological activity, brain stimulation…), as much as I am dedicated to creating new tasks and measures to measure the process of interest. Finally, I am fascinated by “non-invasive” (a poor qualifier) techniques of brain stimulation, which can include the induction of altered states of consciousness via meditation or transcendental practices, or by the engagement in neo-realities (for instance using virtual reality).
Self control is a fascinating topic stemming out of millennia of philosophical and spiritual endeavors, related to fundamental questions pertaining to free-will, agency, responsibility, will and power. Self control is an umbrella term covering distinct aspects, such as cognitive control (and the so-called executive functions), emotion regulation or phenomenological control (the ability to modulate one’s subjective experience).
We are also interested in the neurocognitive mechanisms supporting aesthetic judgment and aesthetic experience, as well as more extreme states of consciousness such as Awe or the sublime (check-out one of my favourite comic on this topic).
While deception is considered as a common phenomenon with important implications, its conceptualization and study as a dispositional trait is under-represented in the literature. Critically, and despite scientific evidence supporting the existence of individual differences in lying, a validated measure of dispositional deception is still lacking. This study aims to explore the structure of dispositional deception by developing and validating a short and reliable 16-item questionnaire to characterize the lying pattern of individuals. Our findings suggest the existence of four distinct latent dimensions to lying, namely frequency, ability, negativity, and contextuality. We establish the convergent validity of our measure of lying by showing significant relationships with social desirability, malevolent traits, cognitive control deficits, normal and pathological personality traits, as well as demographic variables such as sex, age, and religiosity. Overall, the present study introduces a general framework to understanding deception as a dispositional trait which future deception studies can build on, accounting for the inter-individual variability in lying.
A crucial part of statistical analysis is evaluating a model’s quality and fit, or performance. During analysis, especially with regression models, investigating the fit of models to data also often involves selecting the best fitting model amongst many competing models. Upon investigation, fit indices should also be reported both visually and numerically to bring readers in on the investigative effort. The performance R-package (R Core Team, 2021) provides utilities for computing measures to assess model quality, many of which are not directly provided by R’s base or stats packages.
NeuroKit2 is an open-source, community-driven, and user-centered Python package for neurophysiological signal processing. It provides a comprehensive suite of processing routines for a variety of bodily signals (e.g., ECG, PPG, EDA, EMG, RSP). These processing routines include high-level functions that enable data processing in a few lines of code using validated pipelines, which we illustrate in two examples covering the most typical scenarios, such as an event-related paradigm and an interval-related analysis. The package also includes tools for specific processing steps such as rate extraction and filtering methods, offering a trade-off between high-level convenience and fine-tuned control. Its goal is to improve transparency and reproducibility in neurophysiological research, as well as foster exploration and innovation. Its design philosophy is centred on user-experience and accessibility to both novice and advanced users.
In both theoretical and applied research, it is often of interest to assess the strength of an observed association. This is typically done to allow the judgment of the magnitude of an effect (especially when units of measurement are not meaningful, e.g., in the use of estimated latent variables; Bollen, 1989), to facilitate comparing between predictors’ importance within a given model, or both. Though some indices of effect size, such as the correlation coefficient (itself a standardized covariance coefficient) are readily available, other measures are often harder to obtain. effectsize is an R package (R Core Team, 2020) that fills this important gap, providing utilities for easily estimating a wide variety of standardized effect sizes (i.e., effect sizes that are not tied to the units of measurement of the variables of interest) and their confidence intervals (CIs), from a variety of statistical models. effectsize provides easy-to-use functions, with full documentation and explanation of the various effect sizes offered, and is also used by developers of other R packages as the back-end for effect size computation, such as parameters (Lüdecke et al., 2020), ggstatsplot (Patil, 2018), gtsummary (Sjoberg et al., 2020) and more.
A long-lasting and unresolved debate in the field of aesthetics is whether beauty is inherent to the object of appreciation or to the subject contemplating it. Several studies suggest that physical features (e.g., symmetry, contrast) of an artwork influence aesthetic rating. Nevertheless, this objectivist approach fails to explain the idiosyncratic nature of aesthetic experiences (AE). Recent models propose a multi-process account of AE, integrating a subjective evaluation based on self-referential processing. This proposition seems coherent with neuroimaging studies showing activation of a common neural network during AE and self-reference. Nevertheless, behavioural data supporting this hypothesis is missing. We took advantage of the self-reference effect (SRE) in memory – the mnemonic advantage for material encoded in a self-related mode - to test the hypothesis that aesthetic judgement is based on self-related processes. We predicted that if aesthetic judgement recruits self-referential processing, incidentally encoding artworks in this condition should produce a similar mnemonic advantage as the SRE. To test this hypothesis, 30 participants incidentally encoded 60 painting in three conditions: self-reference, judgement of beauty and judgement of symmetry (control condition). We found that items encoded in the aesthetic judgment condition were as well recognized as those encoded in self-reference condition when participants gave extreme judgements on the beauty scale during encoding. These findings suggest that at least intense AEs activate an individual’s sense of self.
The recent growth of data science is partly fuelled by the ever-growing amount of data and the joint important developments in statistical modelling, with new and powerful models and frameworks becoming accessible to users. Although there exist some generic functions to obtain model summaries and parameters, many package-specific modeling functions do not provide such methods to allow users to access such valuable information.
Correlations tests are arguably one of the most commonly used statistical procedures, and are used as a basis in many applications such as exploratory data analysis, structural modelling, data engineering etc. In this context, we present ‘correlation’, a toolbox for the R language and part of the ‘easystats’ collection, focused on correlation analysis. Its goal is to be lightweight, easy to use, and allows for the computation of many different kinds of correlations.
Episodic memory encoding is highly influenced by the availability of attentional resources. Mind wandering corresponds to a shift of attention toward task-unrelated thoughts. Few studies, however, have tested this link between memory encoding and mind wandering. The goal of the present work was to systematically investigate the influence of mind wandering during encoding on episodic memory performances in an ecological setting. Fifty-two participants were asked to navigate in a virtual urban environment. During the walk, they encountered different scenes that, unbeknownst to the participants, were target items presented in a subsequent recognition task associated with a Remember–Know–Guess paradigm. Each item triggered, after a random interval, a thought probe assessing current mind wandering. We found a significant linear positive relationship between the ratio of correctly recognized items and the overall mind wandering reported after the task. Moreover, we found a quadratic reversed U-shaped relationship between the probability of giving a ‘Remember’ response and both on-line and mind wandering reported a posteriori. The nearer to the medium value the level of mind wandering was, the higher was the probability to have a recollection-based recognition. Our results indicate that in a complex environment, the highest probability of actually remembering a scene would be when participants present a medium attentional level: neither distracted by inner thoughts nor too focused on the environment. This open attentional state would allow a better global processing of the environment by preventing one’s attention from being captured by internal thoughts or narrowed by an over-focusing on the environment.
Prospective memory (PM) consists of remembering to perform an action that was previously planned. The recovery and execution of these actions require attentional resources. Mindfulness, as a state or a dispositional trait, has been associated with better attentional abilities while mind wandering is linked with attentional failures. In this study, we investigated the impact of mindfulness on PM. Eighty participants learned 15 cue-action associations. They were, then, asked to recall the actions at certain moments (time-based items) or places (event-based items) during a walk in a virtual town. Before the PM task, participants were randomly assigned to a mindfulness or mind wandering (control condition) session. Dispositional mindfulness was measured via the Five Facets Mindfulness Questionnaire (FFMQ). Although considered as two opposite states, we did not report any difference between the two groups on PM abilities. Nevertheless, the natural tendency to describe one’s own sensations (the Describing facet of the FFMQ) predicted time-based performance in both groups. We discuss different hypotheses to explain this finding in light of recent findings on the impact of mind wandering on future oriented cognition. Our main observation is a positive link between the Describing facet and time-based PM performances. We propose that this link could be due to the common association of this mindfulness facets and PM with attentional and interoceptive abilities. Additional studies are needed to explore this hypothesis.
Turmoil has engulfed psychological science. Causes and consequences of the reproducibility crisis are in dispute. With the hope of addressing some of its aspects, Bayesian methods are gaining increasing attention in psychological science. Some of their advantages, as opposed to the frequentist framework, are the ability to describe parameters in probabilistic terms and explicitly incorporate prior knowledge about them into the model. These issues are crucial in particular regarding the current debate about statistical significance. Bayesian methods are not necessarily the only remedy against incorrect interpretations or wrong conclusions, but there is an increasing agreement that they are one of the keys to avoid such fallacies. Nevertheless, its flexible nature is its power and weakness, for there is no agreement about what indices of “significance” should be computed or reported. This lack of a consensual index or guidelines, such as the frequentist p-value, further contributes to the unnecessary opacity that many non-familiar readers perceive in Bayesian statistics. Thus, this study describes and compares several Bayesian indices, provide intuitive visual representation of their “behavior” in relationship with common sources of variance such as sample size, magnitude of effects and also frequentist significance. The results contribute to the development of an intuitive understanding of the values that researchers report, allowing to draw sensible recommendations for Bayesian statistics description, critical for the standardization of scientific reporting.