Design of Computational Models to Study Brain Functions
It is believed that the synapses are responsible for any actions we take at conscious or unconscious levels, responsible for processes such as learning and remembering. However, despite the intense work on brain chemistry, physiology, and neural dynamics, the link between the synaptic mechanics of learning and remembering and the higher-order processes of decision-making and understanding has not been fully understood. This failure stems from one simple fact we ignore: the brain actually works with both chemical signals and electrical signals.
In that regard, what we need is computational models that allow us to study both chemical phenomena and electrical signals together to understand how the brain really works. In this context, Prof. Dr. Neslihan S. Sengör (Istanbul Technical University, Department of Electronics Engineering) Assoc. Dr. Eva Navarro Lopez (the University of Wolverhampton, School of Mathematics and Computer Science), we develop new models that will enable simultaneous examination of chemical processes and electrical signal transmission in the brain. The production of these systems will enable the design of faster working networks in both computers and similar electronic systems, as well as the study and understanding of brain-related diseases.
Development of Chemical Probes for Point-of-Care Devices
The technology of chemical sensors is the current choice to selectively detect biomarkers in high precision and accuracy. There are many examples of sensors in the literature today where these synthetic structures are used as the recognition unit. However, these studies generally remain at the level of academic research. The main reason for this is that a number of additional laboratory devices, such as impedance spectroscopy, cyclic voltammetry, or amperemeter, are also required to measure with these sensor systems. These laboratory devices operate manually and can only be used by specialists. Even more importantly, the results obtained can only be analyzed by experts. However, there are simple analytical systems that can be used by everyone who can measure the level of sugar in the blood and which is sold in pharmacies. From this point of view, there is no doubt that diagnostic devices that can be integrated, self-working, and capable of yielding results in terms of the amount of concentration after the results are analyzed are undoubtedly needed so that end users can use them.
In collaboration with TUBITAK-Gebze, Middle East Technical University, Hacettepe University, Necmettin Erbakan University, we aim to develop automatic diagnostic devices, which can not only detect any given compound but also analyze the data, without demanding additional laboratory devices. We believe that the development of such diagnostic devices will undoubtedly accelerate the commercialization of chemical sensors, and will pave the way to developing integrated devices operating on their own.