AI Medical Compendium Topic:
Cognition

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Fuzzy-Rough Cognitive Networks.

Neural networks : the official journal of the International Neural Network Society
Rough Cognitive Networks (RCNs) are a kind of granular neural network that augments the reasoning rule present in Fuzzy Cognitive Maps with crisp information granules coming from Rough Set Theory. While RCNs have shown promise in solving different cl...

Emotional metacontrol of attention: Top-down modulation of sensorimotor processes in a robotic visual search task.

PloS one
Emotions play a significant role in internal regulatory processes. In this paper, we advocate four key ideas. First, novelty detection can be grounded in the sensorimotor experience and allow higher order appraisal. Second, cognitive processes, such ...

Infrastructural intelligence: Contemporary entanglements between neuroscience and AI.

Progress in brain research
In this chapter, I reflect on contemporary entanglements between artificial intelligence and the neurosciences by tracing the development of Google's recent DeepMind algorithms back to their roots in neuroscientific studies of episodic memory and ima...

Do Intelligent Robots Need Emotion?

Trends in cognitive sciences
What is the place of emotion in intelligent robots? Researchers have advocated the inclusion of some emotion-related components in the information-processing architecture of autonomous agents. It is argued here that emotion needs to be merged with al...

Using machine learning to identify air pollution exposure profiles associated with early cognitive skills among U.S. children.

Environmental pollution (Barking, Essex : 1987)
Data-driven machine learning methods present an opportunity to simultaneously assess the impact of multiple air pollutants on health outcomes. The goal of this study was to apply a two-stage, data-driven approach to identify associations between air ...

Feature selective temporal prediction of Alzheimer's disease progression using hippocampus surface morphometry.

Brain and behavior
INTRODUCTION: Prediction of Alzheimer's disease (AD) progression based on baseline measures allows us to understand disease progression and has implications in decisions concerning treatment strategy. To this end, we combine a predictive multi-task m...

Electroencephalogram-based decoding cognitive states using convolutional neural network and likelihood ratio based score fusion.

PloS one
Electroencephalogram (EEG)-based decoding human brain activity is challenging, owing to the low spatial resolution of EEG. However, EEG is an important technique, especially for brain-computer interface applications. In this study, a novel algorithm ...

Neural networks subtract and conquer.

eLife
Two theoretical studies reveal how networks of neurons may behave during reward-based learning.

Dual-memory neural networks for modeling cognitive activities of humans via wearable sensors.

Neural networks : the official journal of the International Neural Network Society
Wearable devices, such as smart glasses and watches, allow for continuous recording of everyday life in a real world over an extended period of time or lifelong. This possibility helps better understand the cognitive behavior of humans in real life a...