Article
Neurosciences
Patrick A. F. Laing, Trevor Steward, Christopher G. Davey, Kim L. Felmingham, Miguel Angel Fullana, Bram Vervliet, Matthew D. Greaves, Bradford Moffat, Rebecca K. Glarin, Ben J. Harrison
Summary: This study investigates the neural basis of safety learning using advanced fMRI technology, and finds that safety learning is mediated through a cortico-striatal circuitry separate from broader cortical regions involved in processing standard safety signals.
JOURNAL OF NEUROSCIENCE
(2022)
Article
Neurosciences
Xue Li, Jing-Wang Zhao, Qian Ding, Cheng Wu, Wan-Qi Li, Yan-Chen Guo, Di Wang, Guang-Qing Xu, Ti-Fei Yuan, Wan-Kun Gong, Yue Lan
Summary: Region-specific plasticity in the dorsal striatum is reflected in the expression pattern of the activity-regulated cytoskeleton-associated protein (Arc) during instrumental learning processes, with Arc primarily detected in the DMS during initial learning stages and in the DLS during both early and late learning stages. The expression of Arc in the DMS correlates with the number of rewards received later in training, indicating its role in reward acquisition during later stages of learning.
FRONTIERS IN CELLULAR NEUROSCIENCE
(2021)
Article
Neurosciences
Zhiying Zhao, Shuxia Yao, Jana Zweerings, Xinqi Zhou, Feng Zhou, Keith M. Kendrick, Huafu Chen, Klaus Mathiak, Benjamin Becker
Summary: Real-time fMRI guided neurofeedback training is a noninvasive brain regulation technique with potential therapeutic applications, which can modulate functional brain alterations. By pooling data from three datasets, it was found that gray matter volume of the right putamen could predict learning success in neurofeedback training.
HUMAN BRAIN MAPPING
(2021)
Article
Automation & Control Systems
Chunxiao Li, Cynthia Rudin, Tyler H. McCormick
Summary: Instrumental variables are widely used in social and health sciences for causal inference. This paper presents a framework that utilizes machine learning to validate assumptions in the IV model and provides empirical evidence. Prediction validity is the key idea, and one-stage and two-stage approaches for IV are developed.
JOURNAL OF MACHINE LEARNING RESEARCH
(2022)
Article
Neurosciences
Ruggero Basanisi, Kevin Marche, Etienne Combrisson, Paul Apicella, Andrea Brovelli
Summary: Reward prediction error (RPE) signals are encoded in the neural activity of various brain areas, but their representation in different subregions of the striatum remains unclear. This study found that beta band oscillations in the ventral striatum are consistent with RPE encoding and suggest that the ventral striatum plays a major role in the updating of learning processes.
JOURNAL OF NEUROSCIENCE
(2023)
Article
Psychology, Experimental
Jutta Peterburs, Alena Frieling, Christian Bellebaum
Summary: The study found Pavlovian learning biases in both active and observational learning, indicating that action and outcome valence influence learning. Additionally, observational learners showed similar performance levels and result patterns as active learners, suggesting virtual co-players can effectively manipulate agency in a computerized task.
PSYCHOLOGICAL RESEARCH-PSYCHOLOGISCHE FORSCHUNG
(2021)
Article
Multidisciplinary Sciences
Alexander C. W. Smith, Sietse Jonkman, Alexandra G. Difeliceantonio, Richard M. O'Connor, Soham Ghoshal, Michael F. Romano, Barry J. Everitt, Paul J. Kenny
Summary: The study showed that neural activity increases in the anterior dorsolateral striatum when mice successfully learn a new lever-press response, indicating that D1-MSNs encode new instrumental actions while D2-MSNs promote the expression of habitual actions. Disruption of D1-MSNs inhibits the consolidation process, whereas inhibition of D2-MSNs strengthens consolidation but blocks the expression of previously learned habit-like responses.
NATURE COMMUNICATIONS
(2021)
Article
Neurosciences
Kurt M. Fraser, Bridget J. Chen, Patricia H. Janak
Summary: This study investigates the role of dopamine transmission and neural activity in different striatal subdomains in the performance of action chains leading to reward delivery. The results show that dopamine transmission in nucleus accumbens core (NAc) and dorsomedial striatum (DMS) is crucial for both cued and uncued action sequences, while the dorsolateral striatum (DLS) has no impact on sequence completion. This highlights the importance of intact NAc and DMS function for correct sequence performance.
EUROPEAN JOURNAL OF NEUROSCIENCE
(2023)
Article
Neurosciences
Karita E. Ojala, Athina Tzovara, Benedikt A. Poser, Antoine Lutti, Dominik R. Bach
Summary: Survival in biological environments requires learning associations between predictive sensory cues and threatening outcomes, which may be implemented through reinforcement learning algorithms driven by prediction errors (PEs). This study investigated the neural representation of PEs during maintenance of learned aversive associations using fMRI, revealing that PEs were encoded in the medial prefrontal cortex during the omission of aversive outcomes.
Review
Clinical Neurology
Kelly M. J. Diederen, Paul C. Fletcher
Summary: Dopaminergic signaling is crucial in learning and reward processing, coding reward prediction error and values of rewards received. Recent studies suggest dopamine plays a role in learning beyond rewards, modeling associative regularities and the reliability of such regularities in the environment.
Article
Psychology, Multidisciplinary
Emilie Bochud-Fragniere, Pamela Banta Lavenex, Pierre Lavenex
Summary: The Weather Prediction Task (WPT) was originally designed to assess probabilistic classification learning. However, the cognitive processes engaged in this task have not been firmly established. This study tested young adults on a modified version of WPT and found that detailed analyses of performance for different patterns of cue-outcome associations are essential to determine the learning strategies used by participants to solve the task.
FRONTIERS IN PSYCHOLOGY
(2022)
Article
Behavioral Sciences
Ramon Bartolo, Bruno Averbeck
Summary: Organisms have evolved to take advantage of environmental regularities, allowing them to acquire a model of the world and make decisions and adjust behavior efficiently under uncertainty. Recent research has focused on various aspects of model-based inference and its neural underpinnings.
CURRENT OPINION IN BEHAVIORAL SCIENCES
(2021)
Article
Computer Science, Artificial Intelligence
Adolfo Perrusquia
Summary: This paper reviews a novel method called Human-Behavior learning for designing optimal decision making controllers. Inspired by the complementary learning in different areas of the human brain, this method utilizes independent and well-identified sources of knowledge to enhance learning. The interaction is modeled as a Markov Decision Process and the paper connects existing methods from control and reinforcement learning theories for a class of linear systems.
Article
Neurosciences
Gina Joue, Karima Chakroun, Janine Bayer, Jan Glaescher, Lei Zhang, Johannes Fuss, Nora Hennies, Tobias Sommer
Summary: The study found that women showed enhanced brain activity related to reward prediction error compared to men, and this effect was further amplified when estrogen levels were elevated in both sexes. However, both female sex and estrogen slowed adaptation to reward prediction errors, resulting in a smaller learning rate.
Article
Biotechnology & Applied Microbiology
Yu-Hang Zhang, ShiJian Ding, Lei Chen, Tao Huang, Yu-Dong Cai
Summary: This study developed a predictive model for subcellular localization by using protein-protein interaction networks, functional enrichment analysis, and proteins with confirmed localization. Various machine learning algorithms and feature selection methods were utilized to identify key features and understand their biological functions.
BIOMED RESEARCH INTERNATIONAL
(2022)
Article
Neurosciences
Mimi Liljeholm, Simon Dunne, John P. O'Doherty
EUROPEAN JOURNAL OF NEUROSCIENCE
(2015)
Article
Neurosciences
Shinsuke Suzuki, Ryo Adachi, Simon Dunne, Peter Bossaerts, John P. O'Doherty
Article
Neurosciences
Simon Dunne, Arun D'Souza, John P. O'Doherty
JOURNAL OF NEUROPHYSIOLOGY
(2016)
Article
Multidisciplinary Sciences
Jean-Claude Dreher, Simon Dunne, Agnieszka Pazderska, Thomas Frodl, John J. Nolan, John P. O'Doherty
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2016)
Article
Neurosciences
Jeffrey C. Cooper, Simon Dunne, Teresa Furey, John P. O'Doherty
Review
Neurosciences
Simon Dunne, John P. O'Doherty
CURRENT OPINION IN NEUROBIOLOGY
(2013)
Article
Neurosciences
Jeffrey C. Cooper, Simon Dunne, Teresa Furey, John P. O'Doherty
JOURNAL OF NEUROSCIENCE
(2012)
Article
Neurosciences
Mimi Liljeholm, Simon Dunne, John P. O'Doherty
JOURNAL OF NEUROSCIENCE
(2014)
Editorial Material
Neurosciences
Simon Dunne, John P. O'Doherty
Article
Neurosciences
Elise Payzan-LeNestour, Simon Dunne, Peter Bossaerts, John P. O'Doherty
Article
Neurosciences
Simon Dunne, Vikram S. Chib, Joseph Berleant, John P. O'Doherty
SOCIAL COGNITIVE AND AFFECTIVE NEUROSCIENCE
(2019)