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Title: Scalable bundle design for massively parallel neuronal recordings in vivo
Author: Wray, William
ISNI:       0000 0004 6498 9110
Awarding Body: Open University
Current Institution: Open University
Date of Award: 2017
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Neural coding consists of precise interactions between related neurons. New techniques are needed to measure the time sensitive interactions within entire neural networks to understand how the brain functions. Extracellular recording is the oldest method of measuring neural activity and can sample at a temporal resolution to resolve fast spiking neurons. If scaled to a sufficiently large number of simultaneous recorded neurons, this technique would be an excellent candidate for such large scale recording. I propose the combined use of glass ensheathed microwire bundle electrodes and an infrared camera readout integrated circuit to collect massively parallel neuronal recordings in vivo. This design will allow for the recording of high quality signals because of the non-intrusive dimensions, low stray capacitance, and enhanced surface impedance of the electrodes, as well as the high signal to noise amplification of the camera electronics. Here the construction of a system to record neural activity is described and its electrical properties are characterized. The results demonstrate the ability to successfully connect fabricated bundle electrodes to the indium bumps of the readout integrated circuit chip and to record voltage waveforms with a signal to noise ratio to resolve simulated spikes. In vivo experiments in the olfactory bulb of anaesthetized mice have resulted in recordings of action potentials from single units. The spike rate of these units increases with odor presentation and is pharmacologically inhibited which demonstrates the biological origin of the recorded activity. To further advance this technology, the stability and rate of connection to the readout electronics need to improve and insertion of electrode bundles with hundreds of more recording sites needs to be optimized. This promising design has several distinct advantages over existing fluorescence imaging and extracellular recording neurotechnologies for large scale neuronal recording.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral