Brain Data Analysis Group

Welcome to the Brain Data Analysis Group of KEDRI!

The Brain Data Analysis Group was established in November 2015. Its main objectives are to offer contemporary tools and systems for brain data modelling, analysis and understanding, including EEG data; fMRI data; integrated static and dynamic brain data.

Its applications span across: Neuromarketing; EEG data modelling; fMRI data modelling; Brain computer interfaces (BCI) and other.

This R&D system uses spiking neural networks for the analysis of Neuromarketing data.

This methodology uses spiking neural networks for the classification, analysis and understanding of spatio-temporal brain EEG data. Some of the applications are: predicting the outcome of a drug treatment, neurological event diagnose and neurorehabilitation.

A new, generic methodology for mapping, learning, visualisation, classification and understanding of fMRI data using the NeuCube architecture of SNN. A solution to a problem defined by fMRI data is not a single formula or an algorithm, but an evolving spatio-temporal data machine (eSTDM) that consists of several modules, each of them having a set of alternative algorithms and parameter values that can be optimised.

Brain Computer Interface (BCI) monitors the neural activities of the brain and translate them to machine commands to control devices such as computers, wheelchairs, robots etc. This tool demonstrates the application of NeuCube Spiking Neural Network architecture for developing a functional Brain Computer Interface platform. Through this approach we aim to detect the patient’s intention to move his or her hand and pass the command to control an exoskeleton or Functional Electric Stimulation (FES) system.