Peter Mullen

Bio: Peter Mullen is an academic researcher. The author has contributed to research in topics: Network tomography & Random forest. The author has an hindex of 1, co-authored 1 publications receiving 1 citations.

Objective Multi-variable Classification and Inference of Biological Neuronal Networks.

Abstract: Classification of biological neuron types and networks poses challenges to the full understanding of the brain's organisation and functioning. In this paper, we develop a novel objective classification model of biological neuronal types and networks based on the communication metrics of neurons. This presents advantages against the existing approaches since the mutual information or the delay between neurons obtained from spike trains are more abundant data compare to conventional morphological data. We firstly designed two open-access supporting computational platforms of various neuronal circuits from the Blue Brain Project realistic models, named Neurpy and Neurgen. Then we investigate how the concept of network tomography could be achieved with cortical neuronal circuits for morphological, topological and electrical classification of neurons. We extract the simulated data to many different classifiers (including SVM, Decision Trees, Random Forest, and Artificial Neuron Networks) classifying the specific cell type (and sub-group types) achieving accuracies of up to 70\%. Inference of biological network structures using network tomography reached up to 65\% of accuracy. We also analysed recall, precision and F1score of the classification of five layers, 25 cell m-types, and 14 cell e-types. Our research not only contributes to existing classification efforts but sets the road-map for future usage of cellular-scaled brain-machine interfaces for in-vivo objective classification of neurons as a sensing mechanism of the brain's structure.

I and i

Abstract: There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality. Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …