Dosenbach Lab | Research

Plasticity is one of the hallmark features of the human brain. Use-driven plasticity is critically important for typical development as well as recovering from brain injury. Thus, the overarching goal of our research is to better understand use-driven brain plasticity. To this end we are using various structural and functional MRI and behavioral phenotyping techniques.

To properly study use-driven brain plasticity in humans, we must overcome a series of exciting challenges. Hence, we have created a multi-pronged plan of attack and are coming at this fascinating problem from several different angles.

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Real-time methods for improving MRI quality

A challenge common to all functional MRI research is the low signal-to-noise ratio of blood oxygenation level dependent (BOLD) data and how easily it is distorted by head motion and drowsiness. In addition to deploying the most advanced data denoising strategies we have developed a Framewise Integrated Real-Time MRI Monitoring (FIRMM) software suite for real-time quality control. We are currently working on further improvements to FIRMM, as well as expanding the approach to drowsiness monitoring and real-time feedback strategies to prevent head motion.

Precision functional mapping of individual human brains

Individual brains differ in the details of their network organization and use-driven plasticity further adds to this functional brain diversity. Therefore, we have moved away from averaging neuroimaging data across groups of people. Instead, we strive to collect large amounts of high-quality functional MRI data for each individual. This allows us to generate precise individual-specific functional network maps of human brains. The Midnight Scan Club project collected many hours of high quality, multi-modal MRI data in 10 young adults (24-34 yo; 5F). Even this small, fairly homogenous sample already revealed common variants in the brain’s global network organization.

Perinatal stroke as a model of successful neuroplasticity

Perinatal stroke (22 wks gest. - 28 days) occurs in > 1/3,000 live births. Some perinatal stroke survivors have no discernable deficits and many have only minimal impairments. Thus, perinatal stroke represents a best-case recovery scenario that reveals the brain’s full potential for successful use-driven neuroplasticity. Using novel high-fidelity individual functional connectomics, we seek to understand how the brains of individual perinatal stroke survivors can function so remarkably well despite structural damage. This information is critically important for developing therapies that can drive the brains of all brain injury survivors towards a similarly efficient functional architecture, independent of age.

Deep phenotyping

To understand how differences in functional brain organization relate to behavior and to learn how brain structures and behavioral abilities change with practice, we must do a much better job tracking and measuring real-world behaviors. Questionnaires are notoriously unreliable and laboratory-based assessments are unrealistic, therefore we have turned to wearable biosensors. We are building a database of normative activity, as measured by bilateral upper extremity accelerometry, in children from birth until 18 years of age. In addition to standard neuropsychological tests and the NIH Toolbox, we are also adding accelerometry which provides information about sleep and activity levels to our adult studies.

Plasticity interventions

Identifying and tracking plastic brain changes in single individuals requires a powerful intervention. Therefore, we have been studying Constraint-Induced Movement Therapy (CIMT), which requires restricting the more mobile limb with a cast, in children with chronic hemiparesis. We also adapted this treatment for the in-depth study of limb restriction and accompanying brain changes in healthy young adults.

The list of research areas above is far from exhaustive since our rate limiting factor is people-power, not ideas. The general tenor of all the ideas/projects is that we are looking for better and more data per subject than most, because we aren’t averaging across individuals. We’re interested in manipulations that will help us understand plasticity and we like going after difficult to obtain human data. We’re also interested in hardware and software tool development that will improve MRI data quality and bring us closer towards using functional MRI as a diagnostic tool in the hospital.