AIMC Topic: Cognition

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The significance of spatial cognitive ability in robot-assisted surgery.

Surgical endoscopy
BACKGROUND: Robot-assisted surgery using the da Vinci Surgical System provides three-dimensional images. However, no research has yet been done on the relationship between the system's operation and spatial cognitive ability. This study focuses on th...

Predictors of schizophrenia spectrum disorders in early-onset first episodes of psychosis: a support vector machine model.

European child & adolescent psychiatry
Identifying early-onset schizophrenia spectrum disorders (SSD) at a very early stage remains challenging. To assess the diagnostic predictive value of multiple types of data at the emergence of early-onset first-episode psychosis (FEP), various suppo...

Learning to manipulate and categorize in human and artificial agents.

Cognitive science
This study investigates the acquisition of integrated object manipulation and categorization abilities through a series of experiments in which human adults and artificial agents were asked to learn to manipulate two-dimensional objects that varied i...

Cyberdelics: Virtual reality hallucinations modulate cognitive-affective processes.

Dialogues in clinical neuroscience
INTRODUCTION: Psychedelics were explored for their potential in the mental health field. However, research was delayed by concerns over short-term side effects and long-term consequences of substance use. Technological advances enabled the developmen...

Upper Airway Volume Predicts Brain Structure and Cognition in Adolescents.

American journal of respiratory and critical care medicine
One in 10 children experiences sleep-disordered breathing (SDB). Untreated SDB is associated with poor cognition, but the underlying mechanisms are less understood. We assessed the relationship between magnetic resonance imaging-derived upper airwa...

Transformer attention-based neural network for cognitive score estimation from sMRI data.

Computers in biology and medicine
Accurately predicting cognitive scores based on structural MRI holds significant clinical value for understanding the pathological stages of dementia and forecasting Alzheimer's disease (AD). Some existing deep learning methods often depend on anatom...

Visual reasoning in object-centric deep neural networks: A comparative cognition approach.

Neural networks : the official journal of the International Neural Network Society
Achieving visual reasoning is a long-term goal of artificial intelligence. In the last decade, several studies have applied deep neural networks (DNNs) to the task of learning visual relations from images, with modest results in terms of generalizati...

Role of Brain Age Gap as a Mediator in the Relationship Between Cognitive Impairment Risk Factors and Cognition.

Neurology
BACKGROUND AND OBJECTIVES: Cerebrovascular disease (CeVD) and cognitive impairment risk factors contribute to cognitive decline, but the role of brain age gap (BAG) in mediating this relationship remains unclear, especially in Southeast Asian populat...

Deep learning on high-density EEG during a cognitive task distinguishes patients with Parkinson's disease from healthy controls.

Journal of neural engineering
Parkinson's disease (PD) is a neurodegenerative disorder characterized by motor and non-motor symptoms, including cognitive impairment. Its diagnosis, which used to be based on clinical assessment, increasingly relies on biomarkers. While electroence...

Unraveling the neural dynamics of mathematical interference in english reading: A novel approach with deep learning and fNIRS data.

Brain research bulletin
English has emerged as the predominant global language, driving efforts to optimize its acquisition through interdisciplinary cognitive research. While behavioral studies suggest a link between English learning and mathematical cognition, the neural ...