Concurrent fMRI-NIRS measurements for investigation of physiological Low Frequency Oscillations (LFO).
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 bra... read morein function. 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
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