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Cognition

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Flexibility in conceptual combinations: A neural network model of gradable adjective modification.

PloS one
Our ability to combine simple constituents into more complex conceptual combinations is a fundamental aspect of cognition. Gradable adjectives (e.g., 'tall' and 'light') are a critical example of this process, as their meanings vary depending on the ...

Preparatory activity of anterior insula predicts conflict errors: integrating convolutional neural networks and neural mass models.

Scientific reports
Preparatory brain activity is a cornerstone of proactive cognitive control, a top-down process optimizing attention, perception, and inhibition, fostering cognitive flexibility and adaptive attention control in the human brain. In this study, we prop...

Effect of dexamethasone pretreatment using deep learning on the surgical effect of patients with gastrointestinal tumors.

PloS one
To explore the application efficacy and significance of deep learning in anesthesia management for gastrointestinal tumors (GITs) surgery, 80 elderly patients with GITs who underwent surgical intervention at our institution between January and Septem...

Cognitive and behavioral markers for human detection error in AI-assisted bridge inspection.

Applied ergonomics
Integrating Artificial Intelligence (AI) and drone technology into bridge inspections offers numerous advantages, including increased efficiency and enhanced safety. However, it is essential to recognize that this integration changes the cognitive er...

LGGNet: Learning From Local-Global-Graph Representations for Brain-Computer Interface.

IEEE transactions on neural networks and learning systems
Neuropsychological studies suggest that co-operative activities among different brain functional areas drive high-level cognitive processes. To learn the brain activities within and among different functional areas of the brain, we propose local-glob...

Psychology of AI: How AI impacts the way people feel, think, and behave.

Current opinion in psychology
Over the past decade, artificial intelligence (AI) technologies have transformed numerous facets of our lives. In this article, we summarize key themes in emerging AI research in behavioral science. In doing so, we aim to unravel the multifaceted imp...

Emotional and cognitive trust in artificial intelligence: A framework for identifying research opportunities.

Current opinion in psychology
This article briefly summarizes trust as a multi-dimensional construct, and trust in AI as a unique but related construct. It argues that because trust in AI is couched within an economic landscape, these two frameworks should be combined to understa...

Representations and generalization in artificial and brain neural networks.

Proceedings of the National Academy of Sciences of the United States of America
Humans and animals excel at generalizing from limited data, a capability yet to be fully replicated in artificial intelligence. This perspective investigates generalization in biological and artificial deep neural networks (DNNs), in both in-distribu...

A machine learning approach for differentiating bipolar disorder type II and borderline personality disorder using electroencephalography and cognitive abnormalities.

PloS one
This study addresses the challenge of differentiating between bipolar disorder II (BD II) and borderline personality disorder (BPD), which is complicated by overlapping symptoms. To overcome this, a multimodal machine learning approach was employed, ...

Cluster-CAM: Cluster-weighted visual interpretation of CNNs' decision in image classification.

Neural networks : the official journal of the International Neural Network Society
Despite the tremendous success of convolutional neural networks (CNNs) in computer vision, the mechanism of CNNs still lacks clear interpretation. Currently, class activation mapping (CAM), a famous visualization technique to interpret CNN's decision...