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Cognition

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Exploring new horizons: Emerging therapeutic strategies for pediatric stroke.

Experimental neurology
Pediatric stroke presents unique challenges, and optimizing treatment strategies is essential for improving outcomes in this vulnerable population. This review aims to provide an overview of new, innovative, and potential treatments for pediatric str...

Designing optimal behavioral experiments using machine learning.

eLife
Computational models are powerful tools for understanding human cognition and behavior. They let us express our theories clearly and precisely and offer predictions that can be subtle and often counter-intuitive. However, this same richness and abili...

Connectome-based reservoir computing with the conn2res toolbox.

Nature communications
The connection patterns of neural circuits form a complex network. How signaling in these circuits manifests as complex cognition and adaptive behaviour remains the central question in neuroscience. Concomitant advances in connectomics and artificial...

Development of the next-generation functional neuro-cognitive imaging protocol - Part 1: A 3D sliding-window convolutional neural net for automated brain parcellation.

NeuroImage
Functional MRI has emerged as a powerful tool to assess the severity of Post-concussion syndrome (PCS) and to provide guidance for neuro-cognitive therapists during treatment. The next-generation functional neuro-cognitive imaging protocol (fNCI2) ha...

Robotic assessment of sensorimotor and cognitive deficits in patients with temporal lobe epilepsy.

Epilepsy & behavior : E&B
OBJECTIVE: Individuals with temporal lobe epilepsy (TLE) frequently demonstrate impairments in executive function, working memory, and/or declarative memory. It is recommended that screening for cognitive impairment is undertaken in all people newly ...

Supervised diagnostic classification of cognitive attributes using data augmentation.

PloS one
Over recent decades, machine learning, an integral subfield of artificial intelligence, has revolutionized diverse sectors, enabling data-driven decisions with minimal human intervention. In particular, the field of educational assessment emerges as ...

Predicting low cognitive ability at age 5 years using perinatal data and machine learning.

Pediatric research
BACKGROUND: There are no early, accurate, scalable methods for identifying infants at high risk of poor cognitive outcomes in childhood. We aim to develop an explainable predictive model, using machine learning and population-based cohort data, for t...

Designing human-AI systems for complex settings: ideas from distributed, joint, and self-organising perspectives of sociotechnical systems and cognitive work analysis.

Ergonomics
Real-world events like the COVID-19 pandemic and wildfires in Australia, Europe, and America remind us that the demands of complex operational settings are met by multiple, distributed teams interwoven with a large array of artefacts and networked te...

AI-augmented clinical decision in paediatric appendicitis: can an AI-generated model improve trainees' diagnostic capability?

European journal of pediatrics
UNLABELLED: Accurate diagnosis of paediatric appendicitis remains a challenge due to its diverse clinical presentations and reliance on subjective assessments. The integration of artificial intelligence (AI) with an expert's ''clinical sense'' has th...

How to use machine learning and fuzzy cognitive maps to test hypothetical scenarios in health behavior change interventions: a case study on fruit intake.

BMC public health
BACKGROUND: Intervention planners use logic models to design evidence-based health behavior interventions. Logic models that capture the complexity of health behavior necessitate additional computational techniques to inform decisions with respect to...