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Full-Text Articles in Medicine and Health Sciences
Deep-Learning-Based Multivariate Pattern Analysis (Dmvpa): A Tutorial And A Toolbox, Karl M. Kuntzelman, Jacob M. Williams, Phui Cheng Lim, Ashtok Samal, Prahalada K. Rao, Matthew R. Johnson
Deep-Learning-Based Multivariate Pattern Analysis (Dmvpa): A Tutorial And A Toolbox, Karl M. Kuntzelman, Jacob M. Williams, Phui Cheng Lim, Ashtok Samal, Prahalada K. Rao, Matthew R. Johnson
Center for Brain, Biology, and Behavior: Faculty and Staff Publications
In recent years, multivariate pattern analysis (MVPA) has been hugely beneficial for cognitive neuroscience by making new experiment designs possible and by increasing the inferential power of functional magnetic resonance imaging (fMRI), electroencephalography (EEG), and other neuroimaging methodologies. In a similar time frame, “deep learning” (a term for the use of artificial neural networks with convolutional, recurrent, or similarly sophisticated architectures) has produced a parallel revolution in the field of machine learning and has been employed across a wide variety of applications. Traditional MVPA also uses a form of machine learning, but most commonly with much simpler techniques based on …
Resting Cerebral Oxygen Metabolism Exhibits Archetypal Network Features, Nicholas A. Hubbard, Monroe P. Turner, Kevin R. Sitek, Kathryn L. West, Jakub R. Kaczmarzyk, Lyndahl Himes, Binu P. Thomas, Hanzhang Lu, Bart Rypma
Resting Cerebral Oxygen Metabolism Exhibits Archetypal Network Features, Nicholas A. Hubbard, Monroe P. Turner, Kevin R. Sitek, Kathryn L. West, Jakub R. Kaczmarzyk, Lyndahl Himes, Binu P. Thomas, Hanzhang Lu, Bart Rypma
Center for Brain, Biology, and Behavior: Faculty and Staff Publications
Standard magnetic resonance imaging approaches offer high-resolution but indirect measures of neural activity, limiting understanding of the physiological processes associated with imaging findings. Here, we used calibrated functional magnetic resonance imaging during the resting state to recover low-frequency fluctuations of the cerebral metabolic rate of oxygen (CMRO2). We tested whether functional connections derived from these fluctuations exhibited organization properties similar to those established by previous standard functional and anatomical connectivity studies. Seventeen participants underwent 20 min of resting imaging during dual-echo, pseudocontinuous arterial spin labeling, and blood-oxygen-level dependent (BOLD) signal acquisition. Participants also underwent a 10 min normocapnic and hypercapnic …
Using Fmri Bold Imaging To Motion-Correct Associated, Simultaneously Imaged Pet Data, Joseph M. Williamitis
Using Fmri Bold Imaging To Motion-Correct Associated, Simultaneously Imaged Pet Data, Joseph M. Williamitis
Browse all Theses and Dissertations
Because magnetic resonance (MR) and positron emission tomography (PET) scanning sessions last long durations, motion blur during scanning constitutes a problem for clinical interpretation. To counteract this, motion-correction algorithms have been developed to reduce smearing between scan slices of MRI, but these algorithms are not commonplace for PET. This feasibility study determined if applying MRI motion-correction algorithms to simultaneously acquired PET data improved PET signal clarity in specific brain regions. Seven subjects received increasing levels of PET tracers while undergoing two separate simultaneous PET/MRI scans. We modified existing fMRI algorithms to apply them to the accompanying PET data. We hypothesized …