School of Physics - Theses
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ItemTowards non-invasive quantum imaging of neuronal activity using optically-active spins in diamond( 2015)Resolving the biological neural network dynamics of the brain with subcellular spatial resolution remains a significant ongoing challenge. It has often been the case, however, that difficult problems in neuroscience have been illuminated by techniques developed at the intersection of various disciplines. This thesis focuses on progress towards such a technique, a nanoscale magnetic sensor for imaging neural networks that functions under physiological conditions. The nitrogen-vacancy (NV) centre defect in biocompatible diamond shows promise due to its nanoscale resolution, sensitivity, stable fluorescence, and room temperature operation. Although there is interest in using the NV centre as a non-invasive magnetic sensor of neural network activity, NV-based sensing techniques are ultimately limited by sources of magnetic noise that destroy the quantum phase coherence these techniques require for their operation. While there are several ways to improve the sensitivity of NV sensors, this thesis investigates the control settings needed to complement the ongoing improvements in diamond quality. We seek to reduce the control errors inherently present in NV sensing protocols: such errors are found to be reduced in the presence of sufficiently large magnetic and microwave fields, although it remains difficult to quantify these errors without accounting for hyperfine NV interactions. The long-term feasibility of NV sensors will be determined by their sensitivity to magnetic fields as well as the magnitude of magnetic fields that individual neurons generate. The external electric potentials generated by individual primary cortical neurons in mice are measured using multi-electrode arrays (MEAs), the prevailing non-invasive technology used to detect electric signals in neural networks. Signals detected by the MEAs are then converted into an equivalent magnetic field, which is found to be in the picotesla range. Although this estimate is lower than the best reported NV sensitivities to date, the actual fields are likely to be larger since MEAs can only detect the extracellular contribution to the magnetic field. This thesis complements existing progress towards realising the long-term goal of a wide-field NV neuron sensor with electrical co-recordings, and suggests that advances in control protocols and material quality may yet be needed to improve the overall sensitivity required to detect activity in neural networks.