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Cognition

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Deep learning identifies brain structures that predict cognition and explain heterogeneity in cognitive aging.

NeuroImage
Specific brain structures (gray matter regions and white matter tracts) play a dominant role in determining cognitive decline and explain the heterogeneity in cognitive aging. Identification of these structures is crucial for screening of older adult...

Constructing neural network models from brain data reveals representational transformations linked to adaptive behavior.

Nature communications
The human ability to adaptively implement a wide variety of tasks is thought to emerge from the dynamic transformation of cognitive information. We hypothesized that these transformations are implemented via conjunctive activations in "conjunction hu...

Integrating the HFACS Framework and Fuzzy Cognitive Mapping for In-Flight Startle Causality Analysis.

Sensors (Basel, Switzerland)
This paper discusses the challenge of modeling in-flight startle causality as a precursor to enabling the development of suitable mitigating flight training paradigms. The article presents an overview of aviation human factors and their depiction in ...

Cross-Task Cognitive Workload Recognition Based on EEG and Domain Adaptation.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Cognitive workload recognition is pivotal to maintain the operator's health and prevent accidents in the human-robot interaction condition. So far, the focus of workload research is mostly restricted to a single task, yet cross-task cognitive workloa...

Meta-analysis of human prediction error for incentives, perception, cognition, and action.

Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology
Prediction errors (PEs) are a keystone for computational neuroscience. Their association with midbrain neural firing has been confirmed across species and has inspired the construction of artificial intelligence that can outperform humans. However, t...

Learning Cognitive Map Representations for Navigation by Sensory-Motor Integration.

IEEE transactions on cybernetics
How to transform a mixed flow of sensory and motor information into memory state of self-location and to build map representations of the environment are central questions in the navigation research. Studies in neuroscience have shown that place cell...

Research on Teaching Resource Recommendation Algorithm Based on Deep Learning and Cognitive Diagnosis.

Journal of healthcare engineering
With the increasing abundance of network teaching resources, the recommendation technology based on network is becoming more and more mature. There are differences in the effect of recommendation, which leads to great differences in the effect of rec...

Subtyping of mild cognitive impairment using a deep learning model based on brain atrophy patterns.

Cell reports. Medicine
Trajectories of cognitive decline vary considerably among individuals with mild cognitive impairment (MCI). To address this heterogeneity, subtyping approaches have been developed, with the objective of identifying more homogeneous subgroups. To date...

Event parsing and the origins of grammar.

Wiley interdisciplinary reviews. Cognitive science
How did grammar evolve? Perhaps a better way to ask the question is what kind of cognition is needed to enable grammar. The present analysis departs from the observation that linguistic communication is structured in terms of agents and patients, a r...

London taxi drivers: A review of neurocognitive studies and an exploration of how they build their cognitive map of London.

Hippocampus
Licensed London taxi drivers have been found to show changes in the gray matter density of their hippocampus over the course of training and decades of navigation in London (UK). This has been linked to their learning and using of the "Knowledge of L...