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

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.




(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,     


The following projects are using NeuCube:

  • 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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