21 Oct 2026: Ultrasound-Driven Plasticity of Decision Making and Learning: Toward Clinical Translation

Posted on by Alyssa

Elsa Fouragnan
Professor of Neuroscience, Director
Center for Therapeutic Ultrasound (CENTUS)
University of Plymouth

This talk will present recent evidence demonstrating that low intensity Transcranial focused Ultrasound Stimulation (TUS) can induce transient, targeted neuroplastic changes in the human brain, with implications for both mechanistic research and therapeutic development. I will highlight TUS’s precision in targeting deep brain structures, its value in probing neural circuits, and its emerging clinical potential in psychiatric disorders. Drawing on recent human studies; including investigations into decision-making and their potential clinical translation; I will present evidence of TUS’s effects on task-related neural changes and behaviour demonstrating its promise as a transformative neuromodulation tool.

7 Oct 2026: An upcoming study on latent cause inference in disorders of compulsivity

Posted on by Alyssa

Ugne Ziausyte
MD/PhD Student, Robert Wood Johnson Medical School
Rutgers University/Princeton University

Compulsivity is characterized by repetitive, self-deleterious behavior, often performed despite the knowledge of its disruptive effects on the pursuit of long-term goals. While classically characterized as a symptom driven by overactive habit systems, recently, alternative conceptualizations have emerged. In this talk, I will introduce an upcoming study that investigates how compulsivity may be explained through the lens of latent cause inference – a theory describing how people understand their environment by categorizing their experiences into shared, unobservable causes – in populations with obsessive compulsive disorder (OCD) or alcohol use disorder (AUD), two canonical disorders of compulsivity. After providing a methodological overview of the novel task designed for this study, I will describe the behavioral and neural hypotheses in detail and share predictions for study results.

23 Sept 2026: Reinforcement learning states and the dynamics of mood

Posted on by Alyssa
Michael Hallquist
Associate Professor 
Department of Psychology
Emory University
Why do our moods change over days, sometimes without an obvious change in our circumstances? Computational accounts propose that mood reflects both rewarding and punishing experiences and how much we learn from them. I will present evidence that fluctuating reinforcement learning states help explain the emergence of positive and negative moods in everyday life.
In a 28-day study, 318 participants completed smartphone-based learning tasks twice daily and reported their mood and daily experiences four times daily, alongside wearable EEG and ECG recordings. A Bayesian reinforcement learning model used choices between stimuli learned on different days to identify dissociable changes in reward and punishment learning. States of amplified reward learning predicted subsequent increases in positive mood, whereas amplified punishment learning predicted increases in negative mood, across lags extending to seven days and accounting for prior mood. These learning states were also reflected in cortical and cardiac responses to reinforcement and moderated the relationship between everyday experiences and subsequent mood. Stronger coupling between punishment learning and later negative mood was associated with greater trait negative emotionality.
These findings support a computational account in which changing learning states influence how experiences accumulate into sustained affective states. I will discuss how connecting learning, physiology, and mood across naturalistic timescales can clarify mechanisms of psychiatric vulnerability and motivate new approaches to studying mood disturbances.
View a recording of this session here.

9 Sept 2026: Measuring latent cause inference in schizophrenia

Posted on by Alyssa

William Koller
Postdoctoral Research Associate, Princeton Neuroscience Institute
Princeton University

Schizophrenia is characterized by profound departures from consensus models of reality, with symptoms like delusions, disorganization, and perceptual disturbances implying breakdowns in how the mind infers structure from experience. In this talk, I’ll explore how schizophrenia may be connected to disruptions in latent cause inference — the process through which people cluster related observations according to shared, unobservable causes — and describe an ongoing CCNP study measuring this process in individuals with schizophrenia. After providing a methodological overview of three behavioral tasks (a movie-segmentation task, a sentence-reading task, and a “microbes” categorization task), I’ll share preliminary findings suggesting that schizophrenia is associated with disruptions in how people segment latent causes during naturalistic movie viewing.