arXiv subjects

Quentin J. M. Huys

Publications and source records attributed to Quentin J. M. Huys.

3 recordsLinked to original sources

arXiv2026

Metareasoning constraints couple narratives, affect and cognition

Narratives and emotions shape thoughts, and thoughts shape our feelings and stories we tell. Why narrative, affective and cognitive states interact remains unclear. We examine whether this mutual relationship reflects constraints on metareasoning - deciding what to think about - imposed by a shared computational state. Combining self-report and quantification of depression narratives using large language models, Study 1 (n=704) shows narrative state structure closely reflects the factorial structure in formal affect assessments, and that perturbation of the narrative state has commensurate effects on affect via a latent computational state. Study 2 (n=553) uses exposure to structured narratives to test model predictions causally in vivo. Narrative exposure has consistent effect on narrative states, with consequences on momentary mood, cognition, and affect. Critically, effects are predicted by latent computational state engagement. This supports the hypothesis that metareasoning constraints determine interactions between narratives, cognition and affect via a shared computational state.

cs.CL↗

arXiv2018

Psychiatric Illnesses as Disorders of Network Dynamics

This review provides a dynamical systems perspective on psychiatric symptoms and disease, and discusses its potential implications for diagnosis, prognosis, and treatment. After a brief introduction into the theory of dynamical systems, we will focus on the idea that cognitive and emotional functions are implemented in terms of dynamical systems phenomena in the brain, a common assumption in theoretical and computational neuroscience. Specific computational models, anchored in biophysics, for generating different types of network dynamics, and with a relation to psychiatric symptoms, will be briefly reviewed, as well as methodological approaches for reconstructing the system dynamics from observed time series (like fMRI or EEG recordings). We then attempt to outline how psychiatric phenomena, associated with schizophrenia, depression, PTSD, ADHD, phantom pain, and others, could be understood in dynamical systems terms. Most importantly, we will try to convey that the dynamical systems level may provide a central, hub-like level of convergence which unifies and links multiple biophysical and behavioral phenomena, in the sense that diverse biophysical changes can give rise to the same dynamical phenomena and, vice versa, similar changes in dynamics may yield different behavioral symptoms depending on the brain area where these changes manifest. If this assessment is correct, it may have profound implications for the diagnosis, prognosis, and treatment of psychiatric conditions, as it puts the focus on dynamics. We therefore argue that consideration of dynamics should play an important role in the choice and target of interventions.

q-bio.NC↗

arXiv2016

Better safe than sorry: Risky function exploitation through safe optimization

Exploration-exploitation of functions, that is learning and optimizing a mapping between inputs and expected outputs, is ubiquitous to many real world situations. These situations sometimes require us to avoid certain outcomes at all cost, for example because they are poisonous, harmful, or otherwise dangerous. We test participants' behavior in scenarios in which they have to find the optimum of a function while at the same time avoid outputs below a certain threshold. In two experiments, we find that Safe-Optimization, a Gaussian Process-based exploration-exploitation algorithm, describes participants' behavior well and that participants seem to care firstly whether a point is safe and then try to pick the optimal point from all such safe points. This means that their trade-off between exploration and exploitation can be seen as an intelligent, approximate, and homeostasis-driven strategy.

stat.AP↗