Concurrent fMRI-NIRS measurements for investigation of physiological Low Frequency Oscillations (LFO).
Hocke, Lia.
2017-04-20T13:58:13.885Z
-
Abstract: In neuroscience, the goal is to understand the structure and function of the brain, and how they are related. This understanding is worthwhile in its own right, but it is also essential in order to protect brain health and develop detection and treatments for brain dysfunction. In the past several decades, functional neuroimaging has become a critical tool for the exploration of brain fu... read morenction. Functional Magnetic Resonance Imaging (fMRI) is the gold standard functional neuroimaging method, due to its high spatial resolution for mapping brain activity. Near Infrared Spectroscopy (NIRS) has been used increasingly and compliments fMRI due to its high temporal resolution. However both methods use indirect measures to infer neuronal activity through its effect on blood flow and oxygenation. This signal is often contaminated with non-neuronal signals in the same domain, namely the low frequency (LF) domain. In this thesis I investigate these LF Oscillations (LFOs) with concurrent fMRI/NIRS in order to further characterize non-neuronal LFOs and the implications of these characterizations for both modalities in neuroscience. In particular, I characterize the non-neuronal NIRS LFOs which appear to be systemic signals moving through the cerebral vasculature, by demonstrating 1) that they are purely non-neuronal, as they can be measured with peripheral NIRS, 2) that these oscillations appear to have an endogenous origin close to the heart and 3) that these purely non-neuronal LFOs are unique in their spatial and temporal characteristics in comparison to existing LF models based on respiration and cardiac variations. I address the debate of the non-neuronal influences in fMRI resting state studies by demonstrating that significant portions, especially in the sensory resting state networks, are non-neuronal. Furthermore, I show that these influences are connected to the vasculature and heterogeneous, stressing the importance to account for them. I address the sensitivity of NIRS to non-neuronal LFOs by mapping neuronal and non-neuronal LFOs with ultra-high spatial and temporal resolution. Finally, I discuss how the circulatory characteristics can provide information on the function of the brain through its overlap with blood supply and how these characteristics can be used to track revascularization.
Thesis (Ph.D.)--Tufts University, 2015.
Submitted to the Dept. of Biomedical Engineering.
Advisors: Blaise Frederick, and Sergio Fantini.
Committee: Andrew Bennett, and Christoph Boergers.
Keywords: Biomedical engineering, and Neurosciences.read less - ID:
- 1c18dt36d
- To Cite:
- DCA Citation Guide EndNote
