Article
Neurosciences
Sridhar R. Jagannathan, Corinne A. Bareham, Tristan A. Bekinschtein
Summary: This study used EEG and behavioral modeling to examine the cognitive and neural dynamics of decision-making in awake and low-alertness states in humans. The results showed that during periods of low alertness, reaction times were slower, attention to the left side of space decreased, and the rate of evidence accumulation was lower. Additionally, there was a delay in the neural signatures distinguishing between left and right decisions and a spatial reconfiguration of neural activity. These findings reveal the mechanisms of cognitive resilience in the face of decreased alertness.
JOURNAL OF NEUROSCIENCE
(2022)
Article
Multidisciplinary Sciences
Jeroen Brus, Helena Aebersold, Marcus Grueschow, Rafael Polania
Summary: The study reveals that confidence in value-based decisions is influenced by endogenous attentional effort and downstream noise in the comparison process, rather than by fluctuations in the precision of value encoding.
NATURE COMMUNICATIONS
(2021)
Article
Computer Science, Artificial Intelligence
Luca Crosato, Hubert P. H. Shum, Edmond S. L. Ho, Chongfeng Wei
Summary: This paper proposes a framework based on Social Value Orientation and Deep Reinforcement Learning (DRL) for decision-making in the presence of pedestrians. The framework trains decision-making policies with different driving styles using state-of-the-art DRL algorithms in a simulated environment. It also introduces a computationally-efficient pedestrian model suitable for DRL training.
IEEE TRANSACTIONS ON INTELLIGENT VEHICLES
(2023)
Article
Psychology, Multidisciplinary
Heinrich Peters, Sandra C. Matz, Moran Cerf
Summary: This paper explores a novel approach to improving human decision-making through sensory substitution. The results from a within-subject design study show that translating numerical information into sensory experiences leads to higher decision accuracy. The benefits of sensory substitution are attributed to a shift from explicit rule abstraction to intuitive configural learning.
COMPUTERS IN HUMAN BEHAVIOR
(2023)
Article
Plant Sciences
Yubin Lan, Yaqi Guo, Qizhen Chen, Shaoming Lin, Yuntong Chen, Xiaoling Deng
Summary: A visual question answering (VQA) model for fruit tree diseases based on multimodal feature fusion was designed in this study. By querying questions about fruit tree disease images, the model obtains the decision-making answer. The proposed model achieved 86.36% accuracy in decision-making, outperforming existing multimodal methods, and can be widely deployed in intelligent agriculture.
FRONTIERS IN PLANT SCIENCE
(2023)
Article
Computer Science, Information Systems
Faiza Samreen, Gordon S. Blair, Yehia Elkhatib
Summary: This article presents a transfer learning based decision support system that reduces time and cost in building new models for performance of new applications and cloud infrastructures.
IEEE TRANSACTIONS ON CLOUD COMPUTING
(2022)
Article
Computer Science, Artificial Intelligence
Liu Sun, Ming He, Nianbin Wang, Hongbin Wang
Summary: Under an open dynamic environment, the challenge in object detection is to determine whether samples belong to known classes. Novelty detection can identify classes that have not appeared in the training process. Current methods use autoencoder to model inlier samples and distinguish them from outlier samples using reconstruction error. However, autoencoder generalizes well and makes it difficult to differentiate inlier from outlier samples. To overcome this, we propose a novelty detection model based on shuffle attention mechanism and mutual information maximization (MIM) to modify the effect of autoencoder on reconstruction. Experimental results on four public datasets validate the potential performance of our proposed method.
APPLIED INTELLIGENCE
(2023)
Article
Geriatrics & Gerontology
Akie Saito, Wataru Sato, Sakiko Yoshikawa
Summary: Previous studies using visual search paradigms have provided inconsistent results regarding rapid detection of emotional faces among older adults. This study aimed to examine older adults' ability to detect faces with emotional meaning by excluding the influence of visual factors. Results showed that older adults who were successful at learning could detect neutral faces associated with reward or punishment more rapidly, suggesting that they retain the ability to detect faces that evoke emotions.
JOURNALS OF GERONTOLOGY SERIES B-PSYCHOLOGICAL SCIENCES AND SOCIAL SCIENCES
(2022)
Article
Psychology, Multidisciplinary
Ziyi Wang, Guibing He
Summary: The study explored the influence of subjective importance on the consideration of common features in multi-attribute decision-making, finding that the level of consideration increases with the subjective importance of the common feature. This provides a new explanation for individual differences and insights into the underlying process of multi-attribute decision-making.
FRONTIERS IN PSYCHOLOGY
(2021)
Article
Computer Science, Artificial Intelligence
Weronika Wojtak, Flora Ferreira, Paulo Vicente, Luis Louro, Estela Bicho, Wolfram Erlhagen
Summary: Modern manufacturing and assembly environments are characterized by high variability in the built process, challenging human-robot cooperation. Research shows that robots can learn, plan, and make decisions through brain-like computations based on Dynamic Neural Fields, reducing the cognitive workload of operators and improving efficiency.
NEURAL COMPUTING & APPLICATIONS
(2021)
Article
Biology
Goni Naamani, Nitzan Shahar, Yoav Ger, Yossi Yovel
Summary: This study examined the bats' ability to adjust their decision strategy in different environments and found that their decisions were influenced by natural priors.
Article
Neurosciences
Zuzanna Z. Balewski, Thomas W. Elston, Eric B. Knudsen, Joni D. Wallis
Summary: During decision-making, neurons in the orbitofrontal cortex (OFC) switch between representing the value of different options, influencing the encoding of choice response in the anterior cingulate cortex (ACC). By studying simultaneous recordings from OFC and ACC in nonhuman primates, it was found that ACC neurons encoding the choice response steadily increased their firing rate throughout the decision-making process, with OFC value dynamics affecting the ramping of ACC activity. The interaction between OFC and ACC explains how the more valuable response is selected.
NATURE NEUROSCIENCE
(2023)
Article
Multidisciplinary Sciences
Claudia Lunghi, Arezoo Pooresmaeili
Summary: The study investigates whether monetary value can influence conscious access to rewarding stimuli using the b-CFS paradigm. Results show that monetary value accelerates the access to visual awareness during CFS and shortens suppression durations for stimuli associated with high monetary reward compared to low monetary reward.
SCIENTIFIC REPORTS
(2023)
Article
Psychology, Multidisciplinary
Qiliang He, Elizabeth H. Beveridge, Vanesa Vargas, Ashley Salen, Thackery I. Brown
Summary: The study examined the impact of stress on value-based decision-making during spatial navigation and different types of learning. It was found that stress impairs rigid learning in females, but does not have negative effects on flexible learning and may even improve it. Computational models revealed that stress reduces memory integration, leading participants to rely more on recent memory and less on information from other sources when making decisions. Overall, the results demonstrate how stress affects different memory systems and the communication between memory and decision-making.
PSYCHOLOGICAL SCIENCE
(2023)
Article
Engineering, Industrial
Guang Zou, Michael Havbro Faber, Arturo Gonzalez, Kian Banisoleiman
Summary: This paper introduces a holistic decision modeling and optimization approach, considering the combined effects of interventions and dependencies in intervention decisions. Compared to a sequential decision making approach, the proposed method yields optimal decisions associated with higher utilities.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2021)
Review
Neurosciences
Laurence T. Hunt
Summary: There is a consensus that circuits in the prefrontal and anterior cingulate cortex play a critical role in reward-based decision making. The functional specialization of PFC/ACC circuits in humans and primates involve microcircuits that support persistent activity during cognitive tasks and macrocircuit connections that vary between different cytoarchitectonic subregions, contributing uniquely to reward-based decision tasks. This variation in circuit connections predicts distinctive neural representations in different regions of the brain during sequential attention-guided choice.
EUROPEAN JOURNAL OF NEUROSCIENCE
(2021)
Article
Biology
Yu Takagi, Laurence Tudor Hunt, Mark W. Woolrich, Timothy E. J. Behrens, Miriam C. Klein-Flugge
Summary: By analyzing neural activities during decision-making processes, researchers found that in non-invasive human recordings, the information related to choice was much stronger than the irrelevant information, a difference that persisted between humans and macaques. After extensive task training, humans still did not exhibit the same level of choice mechanism as macaques, suggesting that species differences may not be solely caused by training.
Article
Neurosciences
Paula Kaanders, Hamed Nili, Jill X. O'Reilly, Laurence Hunt
Summary: In this study using fMRI, researchers investigate the neural basis of information sampling in economic choice. The activity of the medial frontal cortex (MFC) was found to predict further information sampling, while a distributed network of regions across the prefrontal cortex encoded key features of the sampled information.
JOURNAL OF NEUROSCIENCE
(2021)
Meeting Abstract
Hematology
Jameel Abdulrehman, Carolyne Elbaz, David Aziz, Sameer Parpia, Gregoire Le Gal, Rouhi Fazelzad, Lisbeth Eischer, Suzanne Cannegieter, Arina J. Ten Cate-Hoek, Michael Nagler, Sam Schulman, Suely M. Rezende, Valerie Olie, Gualtiero Palareti, Maura Marcucci, James Douketis, Daniela Poli, Michal Zabczyk, Diana Aguiar de Sousa, Bruno Miranda, Mary Cushman, Alberto Tosetto, Clive Kearon, Leslie Skeith
Article
Clinical Neurology
Jose Castro, Bruno Miranda, Isabel de Castro, Isabel Conceicao
Summary: This study assessed 69 asymptomatic gene carriers over a 4-year period and found that 55.1% converted to symptomatic ATTRV30M-PN. Sensory nerve progression compared to baseline differed between asymptomatic carriers and converters, with converters experiencing a greater decline starting about 2 years before symptom onset. Motor nerve and sympathetic skin response showed no significant change.
EUROPEAN JOURNAL OF NEUROLOGY
(2022)
Article
Neurosciences
Catherine Manning, Cameron D. Hassall, Laurence T. Hunt, Anthony M. Norcia, Eric-Jan Wagenmakers, Margaret J. Snowling, Gaia Scerif, Nathan J. Evans
Summary: Children with dyslexia exhibit reduced evidence accumulation and neural correlates in visual motion processing tasks, suggesting atypical perceptual decision-making processes in dyslexia.
JOURNAL OF NEUROSCIENCE
(2022)
Article
Multidisciplinary Sciences
Catherine Manning, Cameron D. Hassall, Laurence T. Hunt, Anthony M. Norcia, Eric-Jan Wagenmakers, Nathan J. Evans, Gaia Scerif
Summary: This study investigates the differences in sensory information processing and decision-making processes in autistic children through the combination of diffusion modeling and high-density EEG. The study finds no conclusive evidence for task-dependent differences in sensory evidence accumulation, cautious decision-making style, and non-decision time in autistic children compared to typically developing children. The relationship between EEG measures and diffusion modeling is also found to be complex in autistic children. Motion processing differences in autistic children appear to be less pronounced compared to children with dyslexia. Exploratory analysis suggests weak evidence that ADHD symptoms may moderate perceptual decision-making in autistic children.
SCIENTIFIC REPORTS
(2022)
Review
Hematology
Jameel Abdulrehman, Carolyne Elbaz, David Aziz, Sameer Parpia, Rouhi Fazelzad, Lisbeth Eischer, Marc A. Rodger, Suzanne C. Cannegieter, Arina ten Cate-Hoek, Michael Nagler, Sam Schulman, Suely M. Rezende, Valerie Olie, Gualtiero Palareti, Maura Marcucci, James Douketis, Daniela Poli, Michal Zabczyk, Diana Aguiar de Sousa, Bruno Miranda, Mary Cushman, Alberto Tosetto, Gregoire Le Gal, Clive Kearon, Leslie Skeith
Summary: The risk of recurrent VTE is lower in women with COC-associated VTE compared to those with unprovoked VTE.
BRITISH JOURNAL OF HAEMATOLOGY
(2022)
Editorial Material
Neurosciences
Cameron D. Hassall, Laurence T. Hunt
Summary: Novelty and uncertainty are important factors that drive exploration, but they are distinct. Close to task termination, novel options are more attractive compared to uncertain options.
Review
Transportation
M. A. Conceicao, M. M. Monteiro, D. Kasraian, P. E. W. van den Berg, S. Haustein, I. Alves, C. Lima Azevedo, B. Miranda
Summary: This review examines the influence of transport infrastructure and operational performance on mental health. The findings suggest that key transport infrastructure, congestion, and delay indicators have a negative impact on emotional states and psychological well-being. However, there is limited research on the effect of transport reliability, indicating a need for further investigation.
Article
Neurosciences
Cameron D. Hassall, Laurence T. Hunt, Clay B. Holroyd
Summary: This study investigates the impact of average task value on reward-related anterior cingulate cortex (ACC) activity, revealing that ACC evaluates outcomes and cues in the context of the current task value.
Review
Psychiatry
Leonardo A. Ancora, Diego Andres Blanco-Mora, Ines Alves, Ana Bonifacio, Paulo Morgado, Bruno Miranda
Summary: This review explores the neural mechanisms underlying cognitive and emotional processes elicited by exposure to urban built and natural spaces. The findings suggest that urban built exposure can activate brain regions related to perceptual, attentional, and cognitive demands, while also triggering neural circuits linked to stress and negative affect. Additionally, environmental diversity is critical for positive affect and well-being.
FRONTIERS IN PSYCHIATRY
(2022)
Review
Computer Science, Artificial Intelligence
Erica Tavazzi, Enrico Longato, Martina Vettoretti, Helena Aidos, Isotta Trescato, Chiara Roversi, Andreia S. Martins, Eduardo N. Castanho, Ruben Branco, Diogo F. Soares, Alessandro Guazzo, Giovanni Birolo, Daniele Pala, Pietro Bosoni, Adriano Chio, Umberto Manera, Mamede de Carvalho, Bruno Miranda, Marta Gromicho, Ines Alves, Riccardo Bellazzi, Arianna Dagliati, Piero Fariselli, Sara C. Madeira, Barbara Di Camillo
Summary: This systematic review focuses on the applications of artificial intelligence (AI) in Amyotrophic Lateral Sclerosis (ALS), especially in the automatic stratification of patients and the prediction of disease progression. The review includes 15 studies on patient stratification, 28 studies on the prediction of ALS progression, and 6 studies that cover both aspects. The results show a lack of validated models for ALS prediction and difficulty in reproducing published studies. While deep learning shows promise in prediction, its superiority over traditional methods is yet to be established. The role of new environmental and behavioral variables collected through real-time sensors remains an open question.
ARTIFICIAL INTELLIGENCE IN MEDICINE
(2023)
Article
Psychology, Biological
Cameron D. Hassall, Yan Yan, Laurence T. Hunt
Summary: Feedback processing is commonly studied by analyzing the brain's response to discrete events. Recent animal work suggests that midbrain dopaminergic activity can track moment-to-moment changes in reward, but there is a debate whether this activity reflects reward prediction errors or state values. In this study, researchers developed an EEG measure of continuous feedback processing and found that scalp-recorded potentials were consistent with reward anticipation and tonic dopamine release, supporting the hypothesis that this activity is related to reward prediction errors.
Article
Multidisciplinary Sciences
Cameron D. Hassall, Jack Harley, Nils Kolling, Laurence T. Hunt
Summary: Human behavior is influenced by processes that unfold over different timescales. A linear modeling approach was used to analyze human EEG data, revealing consistent temporal scaling and its relationship with behavior. This study provides a method for studying flexibly timed behavior in the human brain.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2022)