Browsing by Author "Parsa Gharamaleki, Mohammadbagher"

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Design and implementation of a real-time system to characterize functional connectivity between cortical areas
(Montana State University - Bozeman, College of Engineering, 2017) Parsa Gharamaleki, Mohammadbagher; Chairperson, Graduate Committee: Brendan Mumey
Despite a thorough mapping of the anatomical connectivity between brain regions and decades of neurophysiological studies of neuronal activity within the various areas, our understanding of the nature of the neural signals sent from one area to another remains rudimentary. Orthodromic and antidromic activation of neurons via electrical stimulation ('collision testing') has been used in the peripheral nervous system and in subcortical structures to identify signals propagating along specific neural pathways. However, low yield makes this method prohibitively slow for characterizing cortico-cortical connections. We employed recent advances in electrophysiological methods to improve the efficiency of the collision technique between cortical areas. There are three key challenges: 1) maintaining neuronal isolations following stimulation, 2) increasing the number of neurons being screened, and 3) ensuring low-latency triggering of stimulation after spontaneous action potentials. We have developed a software-hardware solution for online isolations and stimulation triggering, which operates in conjunction with two hardware options, Hardware Processing Platform (HPP) or a Software Processing Platform (SPP). The HPP is a 'system on a chip' solution enabling real-time processing in a re-programmable hardware platform, whereas the SPP is a small Intel Atom processor that allows soft real-time computing on a CPU. Employing these solutions for template matching both accelerates spike sorting and provides the low-latency triggering of stimulation required to produce collision trials. Recording with a linear tetrode array electrode allows simultaneous screening of multiple neurons, while the software package coordinates efficient collision testing of multiple user-selected units across channels. This real-time connectivity screening system enables researchers working with a variety of animal models and brain regions to identify the functional properties of specific projections between cortical areas in behaving animals.