Brain-inspired spiking neural networks (SNN) for spatio-temporal data and brain-inspired AI 

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NeuCube is a brain-inspired computational architecture based on spiking neural networks (SNN). NeuCube was designed by Professor Nikola Kasbov, who also oversaw its development and implementation. Knowledge Engineering Consulting offers a comprehensive suite of services designed to facilitate the deployment of NeuCube in a variety of projects across health, economic, and financial domains.

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(The NeuCube SNN architecture  from:   Kasabov, N. NeuCube: A Spiking Neural Network Architecture for Mapping, Learning and Understanding of Spatio-Temporal Brain Data, Neural Networks vol.52 (2014), pp. 62-76, http://dx.doi.org/10.1016/j.neunet.2014.01.006)     

 

The following projects are using NeuCube:

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• Brain data modelling

• EEG: peri-perceptual modelling; mindfulness; Depression; AD; response to treatment; BCI

• fMRI: cognitive data modelling

• fMRI+ DTI: response to treatment

• EEG + MRI data: epilepsy

• neurogenetic, integrated data

• Gene expression over time

• Audio/Visual data processing

• Speech, sound and music recognition

• Moving object recognition

• Language processing

• Multisensory streaming data

• Health risk event prediction from temporal climate data (stroke)

• Hazardous environmental event prediction (e.g. risk of earthquakes in NZ; flooding in Malaysia; pollution in London area; extreme weather from satellite images)

• Brain-Computer Interfaces and knowledge transfer between humans and machines

• Robot control

• Neuro-rehabilitation robots (with China Academy of Sciences)

• NeuCube is currently used in the labs of 25 countries

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