Research Highlights

An outline of our algorithmic framework for Intelligent Single Trial Analysis is provided in these slides Download PDF | Download PPT
More information can be found at Dr Ioannides website [LHBD]

The incorporation of Information Mining principles for understanding multichannel encephalographic recordings is discussed in these slides Download PDF | Download PPT

The application of Graph-theoretic tools for studying the influence of attention on auditory brain responses is described in these slides Download PDF | Download PPT

From ICANN 2009 Workshop on "Data, Data mining and Modelling of Brain Activity for Understanding Attentional Mechanisms"

We've extended classical FCM algorithm so as to perform manifold learning

For more information see: doi

We've introduced self-organizing lists for visualizing brain dynamics from optical recordings

For more information see: doi

The Conditional-FCM algorithm is used for signal enhancement in event related paradigms and further exploited to semantically organize brain response variability Download PDF | Download PPT

Network analysis is employed for characterizing presaccadic brain activity at a single-trial level Download PDF | Download PPT

From ICANN 2010

A novel Clustering scheme in exploited, in conjunction with manifold-learning, for spike sorting Download PDF | Download PPT

From MEDICON 2010

Brain’s self-organization trends, as reflected in EEG synchrony patterns, are detected during mathematical calculations. Download PDF | Download PPT