Posted 27 May 2016

Prof. György Buzsáki

Large-scale recording of local field and action potentials



To understand how function arises from the interactions between neurons, it is necessary to use methods that allow the monitoring of brain activity at the single-neuron, single-spike level and the targeted manipulation of the diverse neuron types selectively in a closed-loop manner. Large-scale recordings of neuronal spiking combined with optogenetic perturbation of identified individual neurons has emerged as a suitable method for such tasks in behaving animals. Although these tools can be scaled to some extent, their invasive nature prevents recordings from tens of thousands of neurons. The invasive nature of electrodes is a major obstacle in human recordings. Prof Buzsáki and his team addressed the latter challenge by developing an organic material-based, ultra-conformable, biocompatible and scalable neural interface array (the ‘NeuroGrid’) that can record both LFP and action potentials from superficial cortical neurons without penetrating the brain surface.

Prof. Buzsáki highlights the current state-of-the-art in electrophysiological recording methods, combined with optogenetics, and discusses directions for progress. In addition, he points to areas where rapid development is in progress and discusses topics where near-term improvements are possible and needed.

About speaker:
Prof. György Buzsáki is currently the Biggs Professor of Neuroscience at the Neuroscience Institute, New York University, USA. His primary research interest is how neuronal circuits code, transfer and store information, especially how different brain oscillations serve such mechanisms. His two-stage (wake-sleep) model of memory has been supported by research in numerous laboratories worldwide. Prof. Buzsáki is an elected Fellow of the American Association for the Advancement of Science and a member of the Hungarian Academy of Sciences. He sits on the editorial boards of several leading neuroscience journals, including Science and Neuron.