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Peter Raynham, Werner Osterhaus, Michael Davies
Pág. 87 - 92
A series of "proof-of-concept" projects are set out aimed at bringing together built environment researchers attempting to understand what constitutes ?comfortable? space and neuroscientists investigating the functional characteristics of the human brain...
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Robert Kleijnen, Markus Robens, Michael Schiek and Stefan van Waasen
Accelerated simulations of biological neural networks are in demand to discover the principals of biological learning. Novel many-core simulation platforms, e.g., SpiNNaker, BrainScaleS and Neurogrid, allow one to study neuron behavior in the brain at an...
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Shang Feng, Haifeng Li, Lin Ma and Zhongliang Xu
In the application of the brain-computer interface, feature extraction is an important part of Electroencephalography (EEG) signal classification. Using sparse modeling to extract EEG signal features is a common approach. However, the features extracted ...
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Hyoung-Gook Kim, Dong-Ki Jeong and Jin-Young Kim
The brain is more sensitive to stress than other organs and can develop many diseases under excessive stress. In this study, we developed a method to improve the accuracy of emotional stress recognition using multi-channel electroencephalogram (EEG) sign...
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Winter Sinkala and Tembinkosi F. Nkalashe
Two equations are considered in this paper?the Black?Scholes equation and an equation that models the spatial dynamics of a brain tumor under some treatment regime. We shall call the latter equation the tumor equation. The Black?Scholes and tumor equatio...
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Qiuying Chen and Hongwei Mo
Autonomous navigation in unknown environments is still a challenge for robotics. Many efforts have been exerted to develop truly autonomous goal-oriented robot navigation models based on the neural mechanism of spatial cognition and mapping in animals? b...
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Benjamin Plaster and Gautam Kumar
Modeling brain dynamics to better understand and control complex behaviors underlying various cognitive brain functions have been of interest to engineers, mathematicians and physicists over the last several decades. With the motivation of developing com...
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Longxin Yao, Yun Lu, Mingjiang Wang, Yukun Qian and Heng Li
The construction of complex networks from electroencephalography (EEG) proves to be an effective method for representing emotion patterns in affection computing as it offers rich spatiotemporal EEG features associated with brain emotions. In this paper, ...
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Jéssica Monteiro, João Castelhano, Duarte Pignatelli, Armando Tartaro and Nicoletta Cera
Background: Several functional magnetic resonance imaging (fMRI) studies investigated the brain correlates of psychogenic erectile dysfunction (PED) and premature ejaculation (PE), representing the most common sexual dysfunctions in men. These studies al...
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Bijen Khagi, Kun Ho Lee, Kyu Yeong Choi, Jang Jae Lee, Goo-Rak Kwon and Hee-Deok Yang
This paper presents an efficient computer-aided diagnosis (CAD) approach for the automatic detection of Alzheimer?s disease in patients? T1 MRI scans using the voxel-based morphometry (VBM) analysis of the region of interest (ROI) in the brain. The idea ...
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David Balderas, Pedro Ponce, Diego Lopez-Bernal and Arturo Molina
Education 4.0 is looking to prepare future scientists and engineers not only by granting them with knowledge and skills but also by giving them the ability to apply them to solve real life problems through the implementation of disruptive technologies. A...
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Simon Gay, Kévin Le Run, Edwige Pissaloux, Katerine Romeo and Christèle Lecomte
This paper presents a novel bio-inspired predictive model of visual navigation inspired by mammalian navigation. This model takes inspiration from specific types of neurons observed in the brain, namely place cells, grid cells and head direction cells. I...
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