Portable, field-based neuroimaging using high-density diffuse optical tomography

Behavioral and cognitive tests in individuals who were malnourished as children have revealed malnutrition-related deficits that persist throughout the lifespan. These findings have motivated recent neuroimaging investigations that use highly portable functional near-infrared spectroscopy (fNIRS) instruments to meet the demands of brain imaging experiments in low-resource environments and enable longitudinal investigations of brain function in the context of long-term malnutrition. However, recent studies in healthy subjects have demonstrated that high-density diffuse optical tomography (HD-DOT) can significantly improve image quality over that obtained with sparse fNIRS imaging arrays. In studies of both task activations and resting state functional connectivity, HD-DOT is beginning to approach the data quality of fMRI for superficial cortical regions. In this work, we developed a customized HD-DOT system for use in malnutrition studies in Cali, Colombia. Our results evaluate the performance of the HD-DOT instrument for assessing brain function in a cohort of malnourished children. In addition to demonstrating portability and wearability, we show the HD-DOT instrument\u27s sensitivity to distributed brain responses using a sensory processing task and measurements of homotopic functional connectivity. Task-evoked responses to the passive word listening task produce activations localized to bilateral superior temporal gyrus, replicating previously published work using this paradigm. Evaluating this localization performance across sparse and dense reconstruction schemes indicates that greater localization consistency is associated with a dense array of overlapping optical measurements. These results provide a foundation for additional avenues of investigation, including identifying and characterizing a child\u27s individual malnutrition burden and eventually contributing to intervention development

Decoding visual information from high-density diffuse optical tomography neuroimaging data

BACKGROUND: Neural decoding could be useful in many ways, from serving as a neuroscience research tool to providing a means of augmented communication for patients with neurological conditions. However, applications of decoding are currently constrained by the limitations of traditional neuroimaging modalities. Electrocorticography requires invasive neurosurgery, magnetic resonance imaging (MRI) is too cumbersome for uses like daily communication, and alternatives like functional near-infrared spectroscopy (fNIRS) offer poor image quality. High-density diffuse optical tomography (HD-DOT) is an emerging modality that uses denser optode arrays than fNIRS to combine logistical advantages of optical neuroimaging with enhanced image quality. Despite the resulting promise of HD-DOT for facilitating field applications of neuroimaging, decoding of brain activity as measured by HD-DOT has yet to be evaluated. OBJECTIVE: To assess the feasibility and performance of decoding with HD-DOT in visual cortex. METHODS AND RESULTS: To establish the feasibility of decoding at the single-trial level with HD-DOT, a template matching strategy was used to decode visual stimulus position. A receiver operating characteristic (ROC) analysis was used to quantify the sensitivity, specificity, and reproducibility of binary visual decoding. Mean areas under the curve (AUCs) greater than 0.97 across 10 imaging sessions in a highly sampled participant were observed. ROC analyses of decoding across 5 participants established both reproducibility in multiple individuals and the feasibility of inter-individual decoding (mean AUCs \u3e 0.7), although decoding performance varied between individuals. Phase-encoded checkerboard stimuli were used to assess more complex, non-binary decoding with HD-DOT. Across 3 highly sampled participants, the phase of a 60° wide checkerboard wedge rotating 10° per second through 360° was decoded with a within-participant error of 25.8±24.7°. Decoding between participants was also feasible based on permutation-based significance testing. CONCLUSIONS: Visual stimulus information can be decoded accurately, reproducibly, and across a range of detail (for both binary and non-binary outcomes) at the single-trial level (without needing to block-average test data) using HD-DOT data. These results lay the foundation for future studies of more complex decoding with HD-DOT and applications in clinical populations

Spontaneous Brain Activity Predicts Future Learning and Memory

From the Washington University Senior Honors Thesis Abstracts (WUSHTA), Volume 5, Spring 2013. Published by the Office of Undergraduate Research. Joy Zalis Kiefer, Director of Undergraduate Research / Assistant Dean in the College of Arts & Sciences; E. Holly Tasker, Editor; Kristin Sobotka, Undergraduate Research Coordinator. Mentor: Kathleen McDermot

Mapping brain function at the bedside during acute stroke recovery using High-Density Diffuse Optical Tomography

Within 72 hours of stroke onset, High-Density Diffuse Optical Tomography can detect disruptions in functional connectivity patterns that significantly differ from healthy subjects (p&lt;1E-5) and that correlate with the NIH Stroke Scale (p&lt;3.3E-4).</p

Mapping brain function at the bedside during acute stroke recovery using High-Density Diffuse Optical Tomography

Within 72 hours of stroke onset, High-Density Diffuse Optical Tomography can detect disruptions in functional connectivity patterns that significantly differ from healthy subjects (p&lt;1E-5) and that correlate with the NIH Stroke Scale (p&lt;3.3E-4).</p

ZerrSupplementalMaterial – Supplemental material for Learning Efficiency: Identifying Individual Differences in Learning Rate and Retention in Healthy Adults

<p>Supplemental material, ZerrSupplementalMaterial for Learning Efficiency: Identifying Individual Differences in Learning Rate and Retention in Healthy Adults by Christopher L. Zerr, Jeffrey J. Berg, Steven M. Nelson, Andrew K. Fishell, Neil K. Savalia and Kathleen B. McDermott in Psychological Science</p

ZerrOpenPracticesDisclosure – Supplemental material for Learning Efficiency: Identifying Individual Differences in Learning Rate and Retention in Healthy Adults

<p>Supplemental material, ZerrOpenPracticesDisclosure for Learning Efficiency: Identifying Individual Differences in Learning Rate and Retention in Healthy Adults by Christopher L. Zerr, Jeffrey J. Berg, Steven M. Nelson, Andrew K. Fishell, Neil K. Savalia and Kathleen B. McDermott in Psychological Science</p