Professional AssociationsProfessional Associations: International Parkinson and Movement Disorder Society | New York Academy of Science
Dr Eleftheria K Pissadaki joined the IBM T.J. Watson Research Center and the Computational Biology Department in May 2016. Eleftheria has a long term research interest in brain anatomy and function, brain diseases, neurodegeneration and particularly in the etiopathology of Parkinson’s disease.
Eleftheria joined the Blue Sky project, a partnership between Pfizer and IBM which aims to use technology-based objective measures to passively monitor Parkinson’s disease signs, their fluctuation and their progression. By using machine learning approaches and developing remote solutions, this new technology will be applicable to a Phase III clinical trial that will test the efficacy of a new compound for the treatment of the motor symptoms of Parkinson’s.
Eleftheria contributes as a basic research neuroscientist since the early days of the Blue Sky project. Her duties included the design of human subject experimental studies, including the compilation of the Institutional Review Board protocol, the implementation of the operational and subject’s protocol, and the execution of the observational research study at the Bernen house, a house reconstructed to host the human subject studies of the Blue Sky project at IBM’s Yorktown Heights premises.
Currently, Eleftheria has focused her research interest in the clinically characterized traits of Parkinson’s that signify the disease as a means to phenotypically characterize people with Parkinson’s. She hopes that this approach will allow the deep understanding of that precise link between clinical phenotype, genes and deep phenotyping, and it will reveal the stratification of Parkinson’s phenotypes according to their biological and clinical relevance. Eleftheria aims in a scalable solution across the fields of neurodegeneration and in personalized and digital quantitative medicine for taking care better those people in need.
Eleftheria’s involvement with high impact research and human studies in IBM makes an excellent continuation to her prior research endevours in the University of Oxford and the MRC Anatomical Neuropharmacology Unit, now known as MRC Brain Network Dynamics Unit. Eleftheria implemented for the first time a detailed biophysical model of the axon arbourisation of dopamine neurons vulnerable in Parkinson’s disease to test hypotheses related to the cause of their neurodegeneration. The predictions of her model have recently been confirmed by a number of high caliber experimental studies. During this period in Oxford and her meetings with people that suffered from Parkinson’s, Eleftheria recognized the importance of bridging the microscale of basic research with the macroscopic observation of the symptoms of the disease as a means to guide basic research and find a cure.
Another active strand of her research is related to brain-based cognitive computing paradigms. Eleftheria is applying her prior research results from the field of hippocampal anatomy and dynamics, neural code and the hippocampal microcircuit to derive novel cognitive and interpretable cognitive architectures.
Eleftheria has studied Mathematics (Department of Mathematics), gained an MSc in Neuroscience (Faculty of Medicine) and a PhD on Computational Neuroscience from the Department of Biology, the Foundation for Research and Technology, Hellas, and the University of Crete. Postdoctoral research fellowship at the University of Oxford.
Research keywords: health care; brain diseases; neurodegeneration; Parkinson’s disease (PD); PD etiopathology; human studies; detailed biophysical compartmental modelling of single neurons and biophysical networks; SNc dopamine neurons; cellular energetics; dopamine axons – structure and physiology; sodium and calcium SNc axon channels; basal ganglia; animal models of disease; hippocampus; CA1 pyramidal neurons and interneurons; hippocampal microcircuit; phase precession; brain oscillations; rotenone animal model of PD; experimental design; biophysical compartmental modelling; brain inspired cognitive architectures