Development of two in vitro methodologies for the study of brain network dynamics and an application to the study of seizure-evoked adenosine release

Understanding the brain in both health and disease is of critical practical importance as well as fundamental scientific interest. The acute neural tissue slice is a widely used experimental preparation, it facilitates treatments and measurements not practical in vivo while preserving a largely connected network representative of the true in vivo structure. This thesis presents the development of two techniques for the study of the acute neural tissue slice, both particularly well suited to the study of epilepsy, followed by an application of one of these techniques. A slice chamber is presented that allows extended regions of a tissue slice to be exposed, in isolation, to changes in ionic environment or pharmacological manipulation, readily providing an entirely in vitro model of focal epilepsy. Secondly, a transformation is derived that converts the slow dynamics of the intrinsic optical signal (IOS) associated with neuronal activity both in vivo and in vitro to the form of the associated local field potential, allowing the advantages of the IOS to be exploited while mitigating the primary disadvantage - the lack of direct correspondence between the IOS and the associated network dynamics. Finally a study is presented that employs the transformation of the IOS to facilitate a quantitative characterisation of the spatio-temporal dynamics of adenosine release in response to electrographic seizure activity

26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 - Meeting Abstracts - Antwerp, Belgium. 15–20 July 2017

This work was produced as part of the activities of FAPESP Research,\ud Disseminations and Innovation Center for Neuromathematics (grant\ud 2013/07699-0, S. Paulo Research Foundation). NLK is supported by a\ud FAPESP postdoctoral fellowship (grant 2016/03855-5). ACR is partially\ud supported by a CNPq fellowship (grant 306251/2014-0)

Epilepsy

Epilepsy is the most common neurological disorder globally, affecting approximately 50 million people of all ages. It is one of the oldest diseases described in literature from remote ancient civilizations 2000-3000 years ago. Despite its long history and wide spread, epilepsy is still surrounded by myth and prejudice, which can only be overcome with great difficulty. The term epilepsy is derived from the Greek verb epilambanein, which by itself means to be seized and to be overwhelmed by surprise or attack. Therefore, epilepsy is a condition of getting over, seized, or attacked. The twelve very interesting chapters of this book cover various aspects of epileptology from the history and milestones of epilepsy as a disease entity, to the most recent advances in understanding and diagnosing epilepsy

Integration eines Neuro-Sensors in ein Messsystem sowie Untersuchungen zur Unit-Separation

An der Universität Rostock wurde im Rahmen einer Dissertation ein neuartiger CMOS (Complementary Metal Oxide Semiconductor) Sensorchip zur extrazellulären Analyse elektrisch aktiver biologischer Zellen eingesetzt. Dieser Chip besitzt außer einem MEA (Multielektrodenarray) noch weitere FET (Field Effect Transistor)-basierte Sensoren zur Erfassung unterschiedlicher Zellparameter. Neben der Inbetriebnahme dieses Sensors wurden externe Hardware zur Messwerterfassung und Algorithmen zur Signalaufbereitung entworfen und realisiert. Das Ziel war die Schaffung eines Cell Monitor Systems (CMS) zur teilautomatisierten Nutzung des Silizium-basierten Sensorchips.At the University of Rostock a new hybrid CMOS (Complementary Metal Oxide Semiconductor) sensor chip has been applied to analyse biological electrogenic cells. This chip consists of a MEA (Multi Electrode Array) and several types of FET (Field Effect Transistor) based sensors to monitor substance dependent cell reactions in-vitro. The system consists of the actual sensor chip including a cell culture area, an external hardware platform for data acquisition and digital signal processing algorithms for signal conditioning. Finally a Cell Monitor System (CMS) for the semi-automatic data acquisition was realised to increase the efficiency of the sensor chip usage

Non-invasive biochemical analysis of cells, tissues and tissue constructs with Raman micro-spectroscopy

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