Computational intelligence and neuroscience
Oct 10, 2016
Humans can easily classify different kinds of objects whereas it is quite difficult for computers. As a hot and difficult problem, objects classification has been receiving extensive interests with broad prospects. Inspired by neuroscience, deep lear...
Neural networks : the official journal of the International Neural Network Society
Aug 26, 2016
Free-energy based reinforcement learning (FERL) was proposed for learning in high-dimensional state and action spaces. However, the FERL method does only really work well with binary, or close to binary, state input, where the number of active states...
Computational intelligence and neuroscience
Jul 26, 2016
Brain-computer interfaces represent a range of acknowledged technologies that translate brain activity into computer commands. The aim of our research is to develop and evaluate a BCI control application for certain assistive technologies that can be...
Neural networks : the official journal of the International Neural Network Society
Jun 23, 2016
Recent research has shown the speed advantage of extreme learning machine (ELM) and the accuracy advantage of sparse representation classification (SRC) in the area of image classification. Those two methods, however, have their respective drawbacks,...
Neural networks : the official journal of the International Neural Network Society
Apr 6, 2016
This study reports the design and implementation of a pattern recognition algorithm to classify electroencephalographic (EEG) signals based on artificial neural networks (NN) described by ordinary differential equations (ODEs). The training method fo...
Human scene recognition is a rapid multistep process evolving over time from single scene image to spatial layout processing. We used multivariate pattern analyses on magnetoencephalography (MEG) data to unravel the time course of this cortical proce...
Neural networks : the official journal of the International Neural Network Society
Mar 31, 2016
There is a long-standing, sometimes contentious debate in AI concerning the relative merits of a symbolic, top-down approach vs. a neural, bottom-up approach to engineering intelligent machine behaviors. While neurocomputational methods excel at lowe...
Wiley interdisciplinary reviews. Cognitive science
Mar 20, 2016
Visual categorization refers to our ability to organize objects and visual scenes into discrete categories. It is an essential skill as it allows us to distinguish friend from foe or edible versus poisonous food. Understanding how the visual system c...
Proceedings of the National Academy of Sciences of the United States of America
Feb 16, 2016
Discovering the visual features and representations used by the brain to recognize objects is a central problem in the study of vision. Recently, neural network models of visual object recognition, including biological and deep network models, have s...
Learning associations between co-occurring events enables us to extract structure from our environment. Medial-temporal lobe structures are critical for associative learning. However, the role of the ventral visual pathway (VVP) in associative learni...