Article
Neurosciences
Norman H. Lam, Thiago Borduqui, Jaime Hallak, Antonio Roque, Alan Anticevic, John H. Krystal, Xiao-Jing Wang, John D. Murray
Summary: The balance between excitation and inhibition in the brain is crucial for cognitive function. In this study, using a cortical circuit model, the researchers found that both increasing and decreasing the excitation/inhibition ratio can impair perceptual decision-making. These impairments manifest in different ways, but overall lead to decreased psychometric performance.
JOURNAL OF NEUROSCIENCE
(2022)
Article
Neurosciences
Margherita Giamundo, Franco Giarrocco, Emiliano Brunamonti, Francesco Fabbrini, Pierpaolo Pani, Stefano Ferraina
Summary: Reward prospect influences motor decisions, with animals adopting different strategies based on reward information and PMd neuronal activity correlating with behavior.
JOURNAL OF NEUROSCIENCE
(2021)
Article
Multidisciplinary Sciences
Patrick G. Bissett, Henry M. Jones, Russell A. Poldrack, Gordon D. Logan
Summary: The stop-signal paradigm, based on race models, shows severe violations of the independence assumption at short stop-signal delays (SSDs) across various conditions. Existing data may need to be reanalyzed, and adjustments to models are necessary to accommodate this finding.
Article
Clinical Neurology
Ana Marques, Bruno Pereira, Michela Figorilli, Tiphaine Vidal, Paul Deffarges, Franck Durif, Livia Fantini
Summary: This study aimed to assess decision-making abilities in Parkinson's disease patients with coexisting REM sleep behavior disorder (RBD). The results revealed impaired decision-making in PD-RBD compared to PD-nRBD and healthy controls, which may explain the increased risk of developing impulse control disorders in these patients.
Article
Psychology, Biological
Nour Ben Hassen, Francisco Molins, Monica Paz, Miguel-Angel Serrano
Summary: This study aims to investigate the effects of the later stages of acute stress on decision making and its underlying processes using a computational model. The results show that stress affects underlying cognitive strategies during decision making. Stressed participants showed deficits in reinforcement-learning and feedback sensitivity in decision tasks, but did not exhibit increased reward attraction.
BIOLOGICAL PSYCHOLOGY
(2023)
Article
Computer Science, Artificial Intelligence
J. Ignacio Serrano, Angel Iglesias, Steven P. Woods, M. Dolores del Castillo
Summary: This study examines a novel computational cognitive model of the Iowa Gambling Task (IGT) that captures fine-grained differences in decision-making styles in individuals with recent methamphetamine use disorders. The models generated from the study are more sensitive than traditional metrics in detecting risky decision-making behaviors in persons with methamphetamine use disorders. Methamphetamine users exhibit lower estimation of possible losses and associated risk, while multi-substance users show behavior patterns that affect the evaluation of losses and the risk associated with gains.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Computer Science, Information Systems
Marc Serramia, Maite Lopez-Sanchez, Stefano Moretti, Juan A. Rodriguez-Aguilar
Summary: Decision makers face challenges in comparing and ranking elements based on multiple criteria and personal preferences. This study introduces a new decision-making framework and presents a new method for ranking single elements. It is also proven that the contributions of this study generalize recent results in the field of social choice. The findings are illustrated through a case study on ethical decision-making.
INFORMATION SCIENCES
(2023)
Article
Neurosciences
Pragya Pandey, Supriya Ray
Summary: The pupil's light response is influenced not only by visual cognitive factors, but also by the location of attentional deployment. The study found that the magnitude of pupil constriction is smaller in tasks that require attention to be focused at the center, while it is larger in tasks that require attention to be dispersed.
FRONTIERS IN HUMAN NEUROSCIENCE
(2022)
Article
Automation & Control Systems
Longsheng Jiang, Yue Wang
Summary: A computational model is proposed to enable robots to make decisions under risk in a human-like way, incorporating psychological effects such as regret theory. The model is further quantified, trained with individual preference data, and shown to have high prediction accuracy compared to human decision-making.
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
(2022)
Review
Psychology
Medha Shekhar, Dobromir Rahnev
Summary: Research shows that human metacognitive ability decreases with higher confidence levels, leading to a non-linear zROC curve. A new mechanistic model incorporating lognormally distributed metacognitive noise better explains metacognitive inefficiency.
PSYCHOLOGICAL REVIEW
(2021)
Article
Neurosciences
Chunyu A. Duan, Marino Pagan, Alex T. Piet, Charles D. Kopec, Athena Akrami, Alexander J. Riordan, Jeffrey C. Erlich, Carlos D. Brody
Summary: The study uncovers circuit mechanisms within the superior colliculus (SC) of the midbrain that implement response inhibition and context-based vector inversion during executive control. This subset of neural activity in the SC plays a crucial role in linking context and motor choice representations in rats.
NATURE NEUROSCIENCE
(2021)
Review
Psychology, Multidisciplinary
Catherine E. Myers, Alejandro Interian, Ahmed A. Moustafa
Summary: In recent years, there has been a rise in studies using evidence-accumulation models like the drift diffusion model (DDM) in psychology and neuroscience. However, many articles assume a deep understanding of the mathematics and computation behind these models, which may limit readers' understanding of the results. This article aims to provide a practical introduction to DDM and its application to behavioral data without requiring a strong mathematical or computational background. It is primarily targeted at psychologists, neuroscientists, and health professionals interested in understanding and potentially applying DDMs in their own work.
FRONTIERS IN PSYCHOLOGY
(2022)
Article
Neurosciences
Joanna Jedrzejewska-Szmek, Daniel B. Dorman, Kim T. Blackwell
Summary: Calcium directly or indirectly controls various functions critical for neuronal activity. The tight regulation of intracellular calcium concentration is important for synaptic plasticity and ion channel activation, which determine neuron firing. Computational models are valuable for studying calcium control since experiments with high spatial and temporal resolution are technically challenging. Simulations reveal that specific calcium sources can couple to specific targets, providing a mechanism for determining synaptic plasticity direction. The cohesiveness of calcium domains opposes specificity, suggesting dendritic branches as the preferred computational unit of neurons.
CURRENT OPINION IN NEUROBIOLOGY
(2023)
Article
Clinical Neurology
Lidia Cabeza, Bahrie Ramadan, Julie Giustiniani, Christophe Houdayer, Yann Pellequer, Damien Gabriel, Sylvie Fauconnet, Emmanuel Haffen, Pierre-Yves Risold, Dominique Fellmann, David Belin, Yvan Peterschmitt
Summary: The study demonstrates that chronic exposure to glucocorticoids induces suboptimal decision making in uncertain environments, impairs spatial working memory, and affects motor learning processes. Neurobiological analysis shows that glucocorticoid receptor expression is downregulated in the medial prefrontal cortex of individuals exposed to cortisol, which negatively correlates with their decision making performance.
EUROPEAN NEUROPSYCHOPHARMACOLOGY
(2021)
Article
Engineering, Industrial
Sandra Hogenboom, Jan Erik Vinnem, Ingrid B. Utne, Trond Kongsvik
Summary: A Dynamic Positioning (DP) system allows vessels and rigs to maintain a predetermined position and heading accurately under harsh environmental conditions. The decisions made by DP operators (DPOs) are safety critical, and their roles are evaluated through applied cognitive task analysis. Recommendations for safety improvement, system design, training, and operations set-up are formulated based on the analysis results.
Article
Neurosciences
Varun Saravanan, Danial Arabali, Arthur Jochems, Anja-Xiaoxing Cui, Luise Gootjes-Dreesbach, Vassilis Cutsuridis, Motoharu Yoshida
Article
Behavioral Sciences
Vassilis Cutsuridis, Panayiota Poirazi
NEUROBIOLOGY OF LEARNING AND MEMORY
(2015)
Editorial Material
Neurosciences
Vassilis Cutsuridis
FRONTIERS IN NEUROSCIENCE
(2015)
Article
Neurosciences
Maria Psarrou, Stefanos S. Stefanou, Athanasia Papoutsi, Alexandra Tzilivaki, Vassilis Cutsuridis, Panayiota Poirazi
FRONTIERS IN CELLULAR NEUROSCIENCE
(2014)
Article
Neurosciences
Vassilis Cutsuridis, Veena Kumari, Ulrich Ettinger
FRONTIERS IN NEUROSCIENCE
(2014)
Article
Computer Science, Artificial Intelligence
Vassilis Cutsuridis
COGNITIVE COMPUTATION
(2019)
Article
Neurosciences
Vassilis Cutsuridis
FRONTIERS IN NEUROSCIENCE
(2019)
Article
Mathematics, Applied
Vassilis Cutsuridis, Shouyong Jiang, Matt J. Dunn, Anne Rosser, James Brawn, Jonathan T. Erichsen
Summary: The study found that early Huntington's disease patients exhibit slower and more variable responses in eye movement tasks, with higher error rates. The neural model indicates that the more gradual and noisy accumulation of evidence by HD patients is responsible for the prolonged and more variable reaction times observed.
Article
Chemistry, Analytical
Liyun Gong, Miao Yu, Shouyong Jiang, Vassilis Cutsuridis, Simon Pearson
Summary: Accurate prediction of crop yield in greenhouses is crucial for informed management and financial decision-making. The combination of state-of-the-art networks for temporal sequence processing has shown improved prediction performance compared to traditional machine learning methods and other deep neural networks. Historical yield information is identified as the most important factor for accurate forecasting of future crop yields.
Article
Computer Science, Artificial Intelligence
Fang Lei, Zhiping Peng, Mei Liu, Jigen Peng, Vassilis Cutsuridis, Shigang Yue
Summary: This article introduces a new collision detection model that enhances detection of looming objects while eliminating false alarms from translating objects, thereby improving collision selectivity. A complementary denoising mechanism ensures reliable collision detection.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
Article
Horticulture
Liyun Gong, Miao Yu, Vassilis Cutsuridis, Stefanos Kollias, Simon Pearson
Summary: In this study, a novel methodology for predicting greenhouse tomato yield is proposed, which combines the Tomgro model and the CNN-RNN model. Different fusion approaches are used to merge the prediction results of these models, and the neural network fusion approach yields the most accurate tomato predictions.
Meeting Abstract
Mathematical & Computational Biology
Nikolaos Andreakos, Vassilis Cutsuridis, Shigang Yue
JOURNAL OF COMPUTATIONAL NEUROSCIENCE
(2021)
Proceedings Paper
Computer Science, Artificial Intelligence
Fang Lei, Zhiping Peng, Vassilis Cutsuridis, Mei Liu, Yicheng Zhang, Shigang Yue
2020 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN)
(2020)
Meeting Abstract
Ophthalmology
Vassilis Cutsuridis, Matt J. Dunn, James Brawn, Anne Rosser, Jonathan T. Erichsen