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="en_US">SPARC</span> Priorities

SPARC - FOA Priorities

This webpage serves as the official list of Priorities for RFA-RM-17-009. This FOA provides application submission instructions, as well as guidance and restrictions on applicable tools and technologies.

Priorities for any specific receipt date will be finalized two months prior to the date. Preliminary Priorities may be listed sooner. All Priorities for a specific receipt date are of equal interest (i.e. the Priorities are not prioritized).

Priorities for the next available receipt date (applications due May 1, 2017) 
Notional Priorities for future receipt dates (applications due August  1, 2017 and later) 
Archived Priorities from previous receipt dates

If you have any questions or suggestions for future Priorities, please email SPARC_NextGen-Tools@mail.nih.gov

Priorities for the May 1, 2017 receipt date (final)
This is the next available receipt date

These are the final priorities for the May 1, 2017 receipt date (in no specific order).

  • Imaging and targeting
    • Quantitative imaging and analysis techniques for PNS and/or organ tissue
    • Contrast agents to identify variability due to individual subject differences in either neuroanatomy or neurophysiology
    • Whole-body imaging of neural tracts (in vivo or ex vivo); the ex-vivo approaches may be destructive or non-destructive to the tissue
    • Fascicular tracing/targeting (biochemical, surgical, and/or viral)
    • Fiber type targeting (biochemical, surgical, and/or viral); this includes plexi, unbundled nerves, and/or vascular nerves
    • Methods to assess blood flow within microvasculature of nerves and ganglia. Of particular interest are methods that can observe blood flow under electrodes.
    • Non-invasive imaging tools to locate and characterize isolated ganglia and/or nerve branches
    • Organ preparation and/or methods to image neural junctions/terminals in an organ of interest
    • Phantoms to support development of new imaging technologies for neuroanatomy
  • Modeling and simulation
    • Computational models to assess safety limits of stimulation and/or blocking of neural activity (e.g. biophysics and regulatory science for neural interfaces)
    • Computational models of neuromodulation that incorporate variability due to individual subject differences
    • Biophysical models of electrical, infrared, or ultrasonic neuromodulation that predict methods for selectively activating or blocking specific fiber types and locations. These computational models should be predictive of side effects (i.e. other fibers that may be activated or blocked).
  • Surgical
    • Surgical tools to safely find and/or access nerves, fascicles, and or ganglia/plexi (e.g. imaging, protocols, etc)
    • Surgical phantoms
    • Real-time in-vivo methods to determine if the PNS is damaged during surgery
    • Methods to repair PNS damage after implant of a neural interface
  • Interfacing
    • Adaptation and safety testing of existing systems to neuromodulate the PNS or for assessment of end-organ function in large animal models. 
      Must be on a translational pathway towards human use
    • Biosensors to detect end-organ function biomarkers. 
      Applicants are strongly encouraged to develop their concept in conjunction with a currently funded SPARC investigator
    • Methods to identify and understand chronic PNS tissue damage after implant of a neural interface
    • New approaches to neuromodulate the PNS that are inherently safe, have high specificity (temporal, spatial, fiber type), and are minimally or non-invasive. 
      Blocking must be reversible. 
      Potential approaches might include biologically derived methods to interface with the PNS in vivo, such as artificial biologic constructs, hydrogel-encapsulated cells, or engineered tissue grafts.
    • Multi-modal (e.g. optogenetic and electrical) neural interfaces that provide greater specificity than a single-mode interface.

Priorities for the August 1, 2017 receipt date (notional) 
This is the next available receipt date

Final Priorities will be posted on June 1, 2017 for applications due on August 1, 2017.

  • Multimodal tools (identified by SPARC1 PIs)
  • Data capture and analysis tools (identified by SPARC4 PIs)
  • Clinical tools (identified by SPARC3 PIs)
  • Validated animal models for an organ (identified by SPARC1 PIs)
  • Some Priorities from the previous receipt date may be included in this list before finalization

RFA RM 16-003 (previous FOA) 
These Priorities are archived for reference purposes only.

These priorities were posted February 8, 2016.

  • Modification of technologies, such as those previously developed to understand neural circuits in the Central Nervous System, to understand neural circuits in the Peripheral Nervous System; or technology used to understand neural circuits controlling one organ which can be modified for use with another target organ or multiple other organs
  • Sensing techniques for relevant biomarkers to inform closed-loop response systems in organs (e.g., biomolecule sampling/measuring)
  • Technologies for cell-class specific targeting and manipulation in peripheral nerves and ganglia, appropriate for animal models with clinical relevance (e.g., optogenetics)
  • Activity sensors and associated imaging technologies suitable for peripheral nerve and end-organ monitoring (e.g., voltage probes)
  • Reliable, wireless, high density technologies capable of simultaneous recording/stimulation of all neural signals going to and coming from a targeted organ; and or to facilitate functional mapping between multiple organs and nerves
  • Biomimetic or biologically-active interfaces for chronic implants of electrodes and sensors that enhance our ability to chronically study the function of a target organ
  • Invasive and non-invasive technologies for tunable stimulation/inhibition/block of nerve activity (e.g., ultrasound, magnetic fields, etc.)
  • Tools for non-invasive tracing and functional imaging to facilitate minimally invasive surgeries in humans and anatomical mapping
  • Computational platforms and predictive models that generate testable hypotheses of autonomic nervous system control of organs
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