Multi-GPU Brain: A multi-node implementation for an extended Hodgkin-Huxley simulator

Current brain simulators do no scale linearly to realistic problem sizes (e.g. >100,000 neurons), which makes them impractical for researchers. The goal of the thesis is to explore the use of true multi-GPU acceleration on computationally challenging brain models and to assess the scalability of such models given sufficient access to multi...

Prediction interval methodology based on fuzzy numbers and its extension to fuzzy systems and neural networks

Prediction interval modelling has been proposed in the literature to characterize uncertain phenomena and provide useful information from a decision-making point of view. In most of the reported studies, assumptions about the data distribution are made and/or the models are trained at one step ahead, which can decrease the quality of the...

Digital Neuron Cells for Highly Parallel Cognitive Systems

The high level of realism of spiking neuron networks and their complexity require a considerable computational resources limiting the size of the realized networks. Consequently, the main challenge in building complex and biologically accurate spiking neuron network is largely set by the high computational and data transfer demands. In this...

Determination of the mechanism behind the formation of spatio-temporal hexagonal activity patterns in a model neuronal network

In this report I present the results from the mathematical analysis of a model neuronal network introduced by Ermentrout and Curtu, extended to two space dimensions. The model can be seen as a simple model of a cortical sheet that describes the firing rate activity of two populations of neurons coupled together, one excitatory that displays...

The correlation of metrics in complex networks with applications in functional brain networks

An increasing number of network metrics have been applied in network analysis. If metric relations were known better, we could more effectively characterize networks by a small set of metrics to discover the association between network properties/metrics and network functioning. In this paper, we investigate the linear correlation coefficients...