To further understanding of brain function in health and disease, our lab is focused on basic science and clinical applications including development of high density diffuse optical tomography (HD-DOT) methods, applying HD-DOT to studies in childhood development, and expanding analytical methods for relating brain function based connectomes to behavior, exposure and outcome. See below for some additional information on these primary aims of the lab.
The loud and constraining nature of MRI-based neuroimaging severely limits studies on direct within-room social communication, on auditory processing and language generation, and presents an excessively challenging setting for sensitive participants, such as school-aged children and in particular young infants, toddlers, and those severely affected with autism spectrum disorder. Near-infrared spectroscopy (NIRS) based methods measure variations in the time course of a signal between a source of safe near infrared light and a detector. When placed on the head, NIRS recovers underlying cerebral hemodynamic variations. High-density diffuse optical tomography (HD-DOT) employs a high-density grid of sources and detectors to provide the overlapping measurements necessary to obtain image quality comparable to fMRI. We have developed HD-DOT systems that can accurately map distributed brain activity within the outer ~1.5 cm of cortex in response to tasks, cortical resting state networks (RSN) during quiet rest and sleep, and distributed brain activity during movie watching. HD-DOT has greater comfort than fMRI (participants sit upright in a comfortable chair), and has comparable temporal and spatial resolution to fMRI. Dynamic measures of brain function are thus accessible without requiring super-cooled magnets and the constraints of the MRI bore and head coils. HD-DOT is inherently portable and deployable in natural settings more amenable to assessing brain function in young children than other common functional brain imaging technologies.
In addition to further advancing the Continuous Wave HD-DOT systems within the lab, we are also developing Frequency Domain HD-DOT systems that incorporate additional phase information capable of further improving image quality obtainable with optical systems. Please see here for a recent news article (https://www.sciencedaily.com/releases/2019/08/190821135246.htm).
As with the functional magnetic imaging community, multiple challenges exist in standardization of data format, analysis considerations, and processing pipelines. To address these challenges for the optical functional neuroimaging community, we are developing NeuroDOT, a fully self-contained and end-user-friendly tool that provides the flexibility for multiple array-based imaging modalities, and offers format compatibility, spatial registration, and analytical breadth and sophistication for post-processing. NeuroDOT is available on GitHub (https://github.com/WUSTL-ORL/NeuroDOT_Beta). To aid in end-user support at multiple levels of familiarity and expertise, beyond the basic functionality, NeuroDOT contains data samples, support files, help sections, appendices, and tutorials. Anonymized and published data samples have been chosen to reflect common experimental paradigms in neuroimaging (e.g., retinotopy and language based tasks), and are provided in both raw and pre-processed versions to aid in troubleshooting and training for the new user.
An ongoing and long-term focus of our lab is to advance HD-DOT methods for evaluating brain-behavior relationships in infants, toddlers, and school-aged children who are typically developing, have a diagnosis of autism spectrum disorder (ASD), or who are at risk for developing ASD. HD-DOT supports imaging brain function while children are awake and engaged within a naturalistic setting. A neurodevelopmental disorder affecting 1/59 children in the general population, ASD is defined by social communication deficits plus repetitive behaviors and restricted interests. Neuroimaging methods, including both task-based functional magnetic resonance imaging (fMRI) and task-free functional connectivity MRI, have demonstrated sensitivity to neural signatures of ASD that may inform diagnosis and track responses to interventions. However, the MRI environment can prove intolerable for many children due to noise, claustrophobia, and the need to lie supine and still. HD-DOT provides a compelling alternative that overcomes the significant ergonomic limitations of fMRI and silently images brain function with a wearable cap in a naturalistic setting ideal for studies on awake and engaged infants and toddlers. If you have a child under the age of 18 and are interested in participating in our research, please see the For Parents and Participants tab.
Determining the mechanisms by which the human brain generates cognition, perception, and emotion hinges upon quantifying the relationships between coordinated brain activity and behavior. NIH-funded brain mapping initiatives such as the Human Connectome Project (HCP) and the Adolescent Cognitive and Behavioral Development (ABCD) study, have accelerated the production of large brain connectivity (i.e. connectome) and behavioral datasets. Contemporary connectome research views the brain as a large-scale, complex network composed of nonadjacent, yet functionally and/or anatomically connected brain regions. We leverage the inherent network architecture of this brain connectome in order to investigate fundamental biological mechanisms underlying behavior, exposure, and outcome. To facilitate these investigations, we are working to formalize in-house analysis pipelines into a Network Level Analysis (NLA) toolbox as a comprehensive, versatile tool for use in connectome-wide association studies. NLA applies statistics commonly used in the genomics literature, known as ‘enrichment’ or ‘over expression analysis’ to assess connectome-wide associations with behavior. Additional details on these methods and applications in human brain development can be found in the following publications: Eggebrecht et al., (2017) Cerebral Cortex; Marrus et al., (2017) Cerebral Cortex; Wheelock et al., (2018) NeuroImage; Wheelock et al., (2019) Developmental Cognitive Neuroscience; Thomason et al. (2019) NeuroImage; McKinnon et al. (2019) Biological Psychiatry CNNI; Marek et al. (2019) Developmental Cognitive Neuroscience.