About

Matt Nassar is an Assistant Professor in the Department of Neuroscience at Brown University. His research focuses on Behavioral Neuroscience/Comparative, Cognitive Neuroscience, Higher-Level Cognition, Neural/Computational Models of Mind Brain and Behavior, and Perception and Action. He is engaged in exploring the neural mechanisms underlying cognition and perception, utilizing computational models to understand the mind and brain functions. His work aims to advance knowledge in these areas through experimental and theoretical approaches, contributing to the broader understanding of cognitive and psychological sciences.

Research topics

• Computer Science
• Artificial Intelligence
• Neuroscience
• Psychology
• Mathematics
• Communication
• Medicine
• Gerontology
• Cognitive psychology
• Audiology
• Developmental psychology
• Social psychology

Selected publications

• Shared effects of one’s own and others’ experiences during reinforcement learning on episodic memory

  npj Science of Learning · 2026-02-28

  articleOpen access

  Humans learn not only from their own experiences but also by observing others. Prior research has shown that reward prediction errors (RPEs) - the difference between expected and received outcomes - guide both experiential and observational reinforcement learning. While RPEs from direct experience have been linked to memory formation, it remains unclear whether vicarious RPEs play a similar role in observational learning. Using an incidental memory paradigm, we investigated how experiential and observational learning in a decision-making task shape memory and examined the role of RPEs in this process. Although recognition accuracy did not differ between learning conditions, participants reported higher confidence in memories from experiential trials. Notably, across both learning conditions, gambling and positive RPEs during memory item presentation were associated with enhanced memory. These findings advance our understanding of how observing others' choices and outcomes affects episodic memory by emphasizing shared encoding mechanisms with experiential learning.

  PublisherDOI

• Reduced mediodorsal thalamus activity underlies aberrant belief dynamics in a genetic mouse model of schizophrenia

  Nature Neuroscience · 2026-03-18

  article
  PublisherDOI

• A normative account of human temporal structure learning

  bioRxiv (Cold Spring Harbor Laboratory) · 2026-01-10

  articleOpen accessSenior authorCorresponding

  Abstract People rapidly recalibrate their expectations about the world in the face of surprising observations. This recalibration should depend on the temporal structure of the environment, however how people should and do learn temporal structures remains unknown. To examine this gap, we developed a Bayesian model that infers temporal structure of the environment directly from observations and makes accurate predictions across qualitatively different environments. We tested predictions of our model in an online behavioral study in which participants predicted outcomes generated according to various temporal structures, and demonstrated that people learned to exploit these structures in a qualitatively similar manner to that of our structure learning model. Furthermore, we show that normative structure learning accounts for puzzling asymmetries previously observed in sequential effects of temporal structures on human learning. Taken together our model and empirical data provide the first general account of how people use temporal structures to interpret unexpected observations in the service of learning.

  PublisherOA PDFDOI

• Author response: Methamphetamine-induced adaptation of learning rate dynamics depend on baseline performance

  2025-06-24

  peer-reviewOpen access

  The ability to calibrate learning according to new information is a fundamental component of an organism’s ability to adapt to changing conditions. Yet, the exact neural mechanisms guiding dynamic learning rate adjustments remain unclear. Catecholamines appear to play a critical role in adjusting the degree to which we use new information over time, but individuals vary widely in the manner in which they adjust to changes. Here, we studied the effects of a low dose of methamphetamine (MA), and individual differences in these effects, on probabilistic reversal learning dynamics in a within-subject, double-blind, randomized design. Participants first completed a reversal learning task during a drug-free baseline session to provide a measure of baseline performance. Then they completed the task during two sessions, one with MA (20 mg oral) and one with placebo (PL). First, we showed that, relative to PL, MA modulates the ability to dynamically adjust learning from prediction errors. Second, this effect was more pronounced in participants who performed moderately low at baseline. These results present novel evidence for the involvement of catecholaminergic transmission on learning flexibility and highlights that baseline performance modulates the effect of the drug.

  PublisherDOI

• Suboptimality in foraging and its association with age and mental health factors

  2025-02-23 · 1 citations

  preprintOpen access

  People constantly decide how much time to invest in more versus less rewarding activities. Foraging tasks, during which participants visit contexts with diminishing reward rates, examine this type of decision-making by measuring when individuals choose to switch contexts. It is widely known that humans and other animals perform suboptimally in these tasks. However, the precise nature of this suboptimality, and its links to other behaviourally relevant traits, remain unclear. Here, we developed a foraging task to disambiguate the impacts of initial reward rates and reward rate changes. We investigated how foraging behaviour differs with age and relates to apathy and depression, which are key factors known to influence reward-based decision-making, while controlling for cognitive factors. In addition to overstaying, we found that participants performed more suboptimally as reward decay rate increased, and that many participants expressed a heuristic preference for staying in the single best condition. Moreover, overstaying was strongly associated with higher scaling of stay durations to each condition, and this overstaying/scaling behaviour was positively associated with age but negatively associated with depressive symptoms. No associations were found between foraging behaviour and apathy. Together, our results suggest that people may counterproductively interpret staying in a patch as persistence in reward extraction, which would explain the tight link between overstaying but high sensitivity to reward conditions, and their association with depressive symptoms.

  PublisherOA PDFDOI

• Differences in learning across the lifespan emerge via resource-rational computations.

  Psychological Review · 2025-02-27 · 10 citations

  article

  = 94) show that children and older adults display biases characteristic of a more frugal sampling policy. This is reflected in (a) more frequent perseveration when participants are required to update from previous beliefs and (b) a stronger anchoring bias when updating beliefs from an externally generated value. These results are qualitatively consistent with simulated predictions of our resource-rational model, corroborating the assumption that the identified biases originate from sampling. Our model and results provide a unifying perspective on perseverative and anchoring biases, show that they can jointly emerge from efficient belief-updating computations, and suggest that resource-rational adjustments of sampling computations can explain age-related changes in adaptive learning. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

  PublisherDOI

• Toward a functional future for the cognitive neuroscience of human aging

  Neuron · 2025-01-01 · 25 citations

  reviewOpen access

  The cognitive neuroscience of human aging seeks to identify neural mechanisms behind the commonalities and individual differences in age-related behavioral changes. This goal has been pursued predominantly through structural or "task-free" resting-state functional neuroimaging. The former has elucidated the material foundations of behavioral decline, and the latter has provided key insight into how functional brain networks change with age. Crucially, however, neither is able to capture brain activity representing specific cognitive processes as they occur. In contrast, task-based functional imaging allows a direct probe into how aging affects real-time brain-behavior associations in any cognitive domain, from perception to higher-order cognition. Here, we outline why task-based functional neuroimaging must move center stage to better understand the neural bases of cognitive aging. In turn, we sketch a multi-modal, behavior-first research framework that is built upon cognitive experimentation and emphasizes the importance of theory and longitudinal design.

  PublisherDOI

• Author response: Methamphetamine-induced adaptation of learning rate dynamics depend on baseline performance

  2025-07-21

  peer-reviewOpen access
  PublisherDOI

• Suboptimality in foraging and its association with age and mental health factors

  2025-10-12

  articleOpen access

  People constantly decide how much time to invest in more versus less rewarding activities. Foraging tasks, during which participants visit contexts with diminishing reward rates, examine this type of decision-making by measuring when individuals choose to switch contexts. It is widely known that humans and other animals perform suboptimally in these tasks. However, the precise nature of this suboptimality, and its links to other behaviourally relevant traits, remain unclear. Here, we developed a foraging task to disambiguate the impacts of initial reward rates and reward rate changes. We investigated how foraging behaviour differs with age and relates to apathy and depression, which are key factors known to influence reward-based decision-making, while controlling for cognitive factors. In addition to overstaying, we found that participants performed more suboptimally as reward decay rate increased, and that many participants expressed a heuristic preference for staying in the single best condition. Moreover, overstaying was strongly associated with higher scaling of stay durations to each condition, and this overstaying/scaling behaviour was positively associated with age but negatively associated with depressive symptoms. No associations were found between foraging behaviour and apathy. Together, our results suggest that people may counterproductively interpret staying in a patch as persistence in reward extraction, which would explain the tight link between overstaying but high sensitivity to reward conditions, and their association with depressive symptoms.

  PublisherDOI

• Absence of Systematic Effects of Internalizing Psychopathology on Learning Under Uncertainty

  eLife · 2025-10-13

  articleOpen access

  Abstract Difficulties in adapting learning to meet the challenges of uncertain and changing environments are widely thought to play a central role in internalizing psychopathology, including anxiety and depression. This view stems from findings linking trait anxiety and transdiagnostic internalizing symptoms to learning impairments in laboratory tasks often used as proxies for real-world behavioral flexibility. These tasks typically require learners to adjust learning rates dynamically in response to uncertainty, for instance, increasing learning from prediction errors in volatile environments. However, prior studies have produced inconsistent and sometimes contradictory findings regarding the nature and extent of learning impairments in populations with internalizing disorders. To address this, we conducted eight experiments (N = 820) using predictive inference and reversal learning tasks, and applied a bi-factor analysis to capture internalizing symptom variance shared across and differentiated between anxiety and depression. While we observed robust evidence for adaptive learning-rate modulation across participants, we found no convincing evidence of a systematic relationship between internalizing symptoms and either learning rates or task performance. These findings challenge prominent claims that learning difficulties are a hallmark feature of internalizing psychopathology and suggest that the relationship between these traits and adaptive behavior under uncertainty may be more subtle than previously thought.

  PublisherDOI

Recent grants

• Cognitive and Molecular Challenges to Statistical Inference Across Healthy Aging.

  NIH · $223k · 2017–2019

• NIH Grant F31MH093099

  NIH · $78k · 2013

• Cognitive and Molecular Challenges to Statistical Inference Across Healthy Aging.

  NIH · $744k · 2019–2023

• Does prefrontal dopamine modulate error signals to optimally adjust learning?

  NIH · $134k · 2014–2017

• Administrative Core

  NIH · $46.6M · 2013–2025

Frequent coauthors

• Michael J. Frank

  69 shared

• Rasmus Bruckner

  49 shared

• Oriel FeldmanHall

  Providence College

  44 shared

• Markus Ullsperger

  Otto-von-Guericke University Magdeburg

  30 shared

• Amitai Shenhav

  University of California System

  26 shared

• Romy Frömer

  Brown University

  24 shared

• Harrison Ritz

  24 shared

• Joseph W. Kable

  University of Pennsylvania

  22 shared