Elektroanalytik & Sensorik
Faculty of Chemistry and Biochemistry

Research program

Localized detection of the exocytosis of neurotransmitters and rational design of small neural networks

The local voltammetric detection of the secretion of neurotransmitters such as dopamin or serotonin from adherently growing cells by means of scanning electrochemical microscopy (SECM) was established recently (A. Hengstenberg, A. Blöchl, I. D. Dietzel, W. Schuhmann, Angew. Chem. Int. Ed. Engl. , 40 (2001) 905-908. Spatially Resolved Detection of Neurotransmitter Secretion from Individual Cells by Means of Scanning Electrochemical Microscopy). In order to improve the spatial resolution carbon-fiber electrodes with typical diameters of < 1 µm have to be developed and positioned in close proximity to the cell using a shear-force dependent positioning mode (A. Hengstenberg, C. Kranz, W. Schuhmann. Chemistry - A European Journal 6 (2000) 1547-1554. Facilitated tip-positioning and applications of non-electrode tips in Scanning Electrochemical Microscopy Using a Shear Force Based Constant-Distance Mode). Recently, we have developed a non-optical shear-force based positioning mode which is suitable for smaller electrodes and allows for the positioning of the electrode tip in typical distances of about 50 - 100 nm from the cell surface. Thus, sequential investigations of different potential release sites at the cell surface should be possible, and moreover, even smaller structures such as cell substructures, varicosities, or synapses should be accessible.

In addition, the microstructured deposition of laminin or laminin epitopes neurons should be guided to specific sites of the surface and the growing axons should follow the predefined pathways. By this, small neural networks should be created in a better controlled way finally allowing for the formation of synapses between a limited number of neurons. By means of localized detection of neurotransmitter release in combination with action potential measurements the cell-cell interaction in the neural network should be elucidated.