U-19 Brief Description - to identify the neural circuit mechanisms that control periarterial cerebrospinal fluid (CSF) pumping and glymphatic clearance of fluid and solutes. 

4 Projects:

1. Build quantitative fluid-dynamical models to establish how arterial dilation, mediated by neural activity, drives periarterial CSF pumping and glymphatic efflux across length scales.
2. Dissect how neural activity transmits Ca2+/cAMP signaling to the neurovascular unit, thereby altering the physical dimensions and functional properties of the perivascular spaces.
3. Dissect the local neural and global neuromodulatory drivers of vasodynamics during NREM sleep using optogenetic and chemogenetic manipulations.
4. Use novel MRI-based techniques to establish how neural activity and large-scale fluid flow are linked in the human brain.

Together, the Projects will provide a quantitative, circuit-based understanding of the neural mechanisms governing brain fluid flow and solute clearance during sleep.

Common Data Types/Elements: The Data Science Core is essential for facilitating collaboration among the Projects because, beyond developing novel tools for the specific needs of the Projects, it will enable seamless sharing of data and code. Members of all Projects will be able to access data simultaneously, write analysis scripts using the same code base, and run those scripts in-place on a supercomputer.

Data Sharing Goals: The Data Science Core will develop novel software, to be shared publicly and under open licenses, using the same git version-control package and GitHub platform as for our internal code sharing. We favor the integration of new tools into existing platforms and expect that new libraries for CSF flow might constitute a powerful addition.

Data Science tools used/devoloped: The Data Science Core will provide the essential infrastructure and produce innovative data methods to enable powerful synergy among the Projects of this U19 program. 
These include: fluid dynamics simulations, Macintosh-based network, 7 image analysis workstations and our Fluoview confocal - administered by an IT tech dedicated to the Center, High performance computing resources are available at The Center for Integrated Research Computing (CIRC) at the University of Rochester

Data Science Approach to be shared: The Data Science Core will provide the essential infrastructure and produce innovative data methods to enable powerful synergy among the Projects of this U19 program. The Data Science Core will benefit from the unique and outstanding collaborative research environment.

Data Science Challenges: Bottlenecks that slow transfer of enormous data files, long computation times, uncertainty about what data or tools are available, and lack of specific analysis methods.

Brain PI Meeting materials

Annually Update:

Link to Poster:

Demo:

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