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June 12, 2009

Nikola Kasabov

Today, I had the honor and pleasure of spending some time with Professor Nikola Kasabov.

Professor Nikola Kasabov is the Founding Director and the Chief Scientist of the Knowledge Engineering and Discovery Research Institute (KEDRI), Auckland (www.kedri.info/). He holds a Chair of Knowledge Engineering at the School of Computing and Mathematical Sciences at Auckland University of Technology. He is a Fellow of the Royal Society of New Zealand, Fellow of the New Zealand Computer Society and a Senior Member of IEEE. He is the President of the International Neural Network Society (INNS) and a Past President of the Asia Pacific Neural Network Assembly (APNNA). He is a member of several technical committees of the IEEE Computational Intelligence Society and of the IFIP AI TC12. Kasabov is Associate Editor of several international journals, that include Neural Networks, IEEE TrNN, IEEE TrFS, Information Science, J. Theoretical and Computational Nanosciences. He chairs a series of int. conferences ANNES/NCEI in New Zealand. Kasabov holds MSc and PhD from the Technical University of Sofia. His main research interests are in the areas of intelligent information systems, soft computing, neuro-computing, bioinformatics, brain study, speech and image processing, novel methods for data mining and knowledge discovery. He has published more than 400 publications that include 15 books, 120 journal papers, 60 book chapters, 32 patents and numerous conference papers. He has extensive academic experience at various academic and research organisations: University of Otago, New Zealand; University of Essex, UK; University of Trento, Italy; Technical University of Sofia, Bulgaria; University of California at Berkeley; RIKEN and KIT, Japan; TUniversity Kaiserslautern, Germany, and others. More information of Prof. Kasabov can be found on the KEDRI web site: http://www.kedri.info/

June 02, 2009

A Conceptual Cortical Surface Atlas

Today, the journal PLoS ONE published a paper entitled "A Conceptual Cortical Surface Atlas" that I authored. The paper should be useful to neuro-anatomically-challenged lay people ("dummies") seeking a bird's eye view of cortical surface atlas. The key contribution is encapsulated in Figure S1. You can download the atlas in excel format here.


Volumetric, slice-based, 3-D atlases are invaluable tools for understanding complex cortical convolutions. We present a simple scheme to convert a slice-based atlas to a conceptual surface atlas that is easier to visualize and understand. The key idea is to unfold each slice into a one-dimensional vector, and concatenate a succession of these vectors – while maintaining as much spatial contiguity as possible – into a 2-D matrix. We illustrate our methodology using a coronal slice-based atlas of the Rhesus Monkey cortex. The conceptual surface-based atlases provide a useful complement to slice-based atlases for the purposes of indexing and browsing.

Cortical Surface Atlas





The key idea is to take slices in a stereotaxic atlas (for example, Paxinos G, Huang XF, Petrides M, Toga AW (2009) The Rhesus Monkey Brain in Stereotaxic Coordinates. Elsevier Science & Technology) and then convert each slice into a one-dimensional vector. The 1D vectors are then concatenated together to create a 2D representation.

The process of creating 1D vectors is hown below for Slices 23 and 22, respectively.

Slice 23




















Slice 22