What is the place of emotion in intelligent robots? In the past two decades, researchers have advocated for the inclusion of some emotion-related components in the general information processing architecture of autonomous agents, say, for better comm...
AIMS: Describe the implementation and uses of fuzzy cognitive mapping (FCM) as a constructive method for meeting the unique and rapidly evolving needs of nursing inquiry and practice.
We review information-theoretic measures of cognitive load during sentence processing that have been used to quantify word prediction effort. Two such measures, surprisal and next-word entropy, suffer from shortcomings when employed for a predictive ...
Neural networks : the official journal of the International Neural Network Society
Sep 20, 2019
OBJECTIVE: This paper argues that Brain-Inspired Spiking Neural Network (BI-SNN) architectures can learn and reveal deep in time-space functional and structural patterns from spatio-temporal data. These patterns can be represented as deep knowledge, ...
Procrastination takes a considerable toll on people's lives, the economy and society at large. Procrastination is often a consequence of people's propensity to prioritize their immediate experiences over the long-term consequences of their actions. T...
Neural networks : the official journal of the International Neural Network Society
Aug 18, 2019
How can we study, characterize, and understand the neural underpinnings of cognitive-emotional behaviors as inherently dynamic processes? In the past 50 years, Stephen Grossberg has developed a research program that embraces the themes of dynamics, d...
IEEE transactions on neural networks and learning systems
Aug 13, 2019
In this paper, we propose a label-less learning for emotion cognition (LLEC) to achieve the utilization of a large amount of unlabeled data. We first inspect the unlabeled data from two perspectives, i.e., the feature layer and the decision layer. By...
In the last century, learning theory has been dominated by an approach assuming that associations between hypothetical representational nodes can support the acquisition of knowledge about the environment. The similarities between this approach and c...
Progress in neuro-psychopharmacology & biological psychiatry
Jul 25, 2019
There is a growing need to address the variability in detecting cognitive deficits with standard tests in cocaine dependence (CD). The aim of the current study was to identify cognitive deficits by means of Machine Learning (ML) algorithms: Generaliz...
We used two simple unsupervised machine learning techniques to identify differential trajectories of change in children who undergo intensive working memory (WM) training. We used self-organizing maps (SOMs)-a type of simple artificial neural network...