ELFT HÍRADÓ

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ELTE Fizikai Intézet

                                ORTVAY KOLLOKVIUM

                    2018. március 22., csütörtök, 15:00-kor
                Az ELTE Pázmány Péter s. 1/A alatti épületében
                           földszinti 0.81 előadóban


                                Nusser Zoltán
                    (Institute of Experimental Medicine, HAS)

   Molecular mechanisms underlying complex computations of single nerve cells


Kivonatos ismertetés:
Most nerve cells receive synaptic inputs from thousands of presynaptic neurons 
and combine these inputs to generate their output signal, the action potential 
(AP). The synaptic inputs are distributed over a complex and elaborate 
dendritic tree, which consists of hundreds of branches and extends several 
hundreds of micrometers. Because APs are generated in the initial part of the 
axon, where it emerges from the cell body, the distance of each synapse from 
the site of the AP generation varies tremendously. Because the synaptic 
potentials get smaller and slower (attenuate) as they spread from their origin 
towards the cell body along the dendrite, the weight of each synapse at the 
site of AP generation is very different (lack of synaptic democracy). This 
attenuation is so severe that synaptic potentials that are generated few 
hundred microns away from the soma are virtually invisible at the cell body. 
How could then nerve cells get activated by distal (far away) synapses? 
Theoretical studies predicted that dendritically located ion channels that are 
activated by changes in voltage (voltage-gated) could amplify local synaptic 
potentials and enhance their effectiveness in generating APs. We employed 
high-resolution localization techniques to investigate the subcellular 
distribution and densities of voltage-gated ion channels on the surface of 
hippocampal pyramidal cells and revealed complex, ion channels-specific 
distribution patterns. Our work will provide a molecular map of the neuronal 
surface, which will be essential for revealing the complex computation of 
single nerve cells.