Abstract The Stimulating Peripheral Activity to Relieve Conditions (SPARC; https://sparc.science) program is supported by the NIH Common Fund to provide a scientific and technological foundation for future bioelectronic medicine devices and protocols.The goal of the SPARC program is to identify neural targets and accelerate the development of therapeutic devices that modulate electrical activity in the vagus and other nerves to help treat diseases and conditions, such as hypertension and gastrointestinal disorders, by precisely adjusting organ function. Some of the ways the SPARC program is working to advance this goal include: (1) Constructing anatomical and functional datasets from organ-specific neural circuitry, including those that mediate visceral pain. (2) Mapping the human vagus nerve, including circuit-level descriptions of human vagal anatomy and physiology. (3) Creating new tools and technologies, including open-source neuromodulation platforms, to enable precise manipulation and measurement of nerve-organ interactions and their associated functions. (4) Establishing effective research partnerships with clinicians, basic scientists, engineers, and private industry to pursue data-intensive, mechanistic clinical studies. (5) Implementing prize challenges for the research and development community to demonstrate proof-of-principle neuromodulation therapeutic benefits with limited off-target effects. (6) Developing the SPARC Portal to make high value autonomic nervous system data sets, maps, and computational studies freely available to the wider research community. The overall vision for the SPARC Portal is to accelerate autonomic neuroscience research and device development by providing access to digital resources that can be shared, cited, visualized, computed, and used for virtual experimentation. The top 3 key questions that SPARC can answer: 1. Where can I find a detailed map ANS-end organ interactions? 2. Where can I find anatomical and physiological data for constructing computational models of the heart? 3. What are the targets of the vagus nerve? Presenter: Dr. Maryann Martone, Professor Emerita, Department of Neurosciences, University of California San Diego Upcoming webinars schedule: https://dknet.org/about/webinar

1. Date
Presented by
Affiliation
Stimulating Peripheral Activity to
Relieve Conditions (SPARC)
Advancing bioelectronic medicine through open science
2/11/2022
Maryann E. Martone, Ph. D.
University of California, San Diego
dkNET
SPARC DRC: K-CORE

2. Outline
1. Introduction to SPARC
2. What does SPARC offer?
3. A look inside the SPARC Portal
4. SCKAN: The SPARC Connectivity Knowledge Base
5. What’s next?
Disclosure: Dr. Martone is a founder and has equity interest in
SciCrunch Inc, a tech start up providing services in support of
enhancing transparency and reproducibility in the scientific literature

3. Bioelectronic Medicine and Neuromodulation Therapy
The power of convergence: molecular
medicine, neuroscience, engineering and
computational science to develop devices
to diagnose and treat diseases
Therapies in development for:
• Heart failure
• Sleep apnea
• Hypertension
• PTSD
• Stroke
• Diabetes
• Parkinsons
• Obesity
• Gastroparesis - and more

4. Stimulating Peripheral Activity to Relieve Conditions
Neuromodulation is an emerging therapeutic approach
to treat diseases of the autonomic nervous system
Challenge: Limited understanding of which
neural targets to influence and how to precisely
control organ function.
Opportunity: Develop more effective and
targeted neuromodulation therapies by
providing a scientific and technological
foundation for future bioelectronic medical
devices and protocols.
Approach: Deliver detailed, integrated,
functional and anatomical maps and models of
the peripheral nervous system and its
innervation of target organs
https://commonfund.nih.gov/sparc

5. *As of February 2022. 200+ datasets expected by end of 2022
SPARC Consortium
Supported by NIH Common Fund
SPARC Portal: https://sparc.science/
• Over 60 research groups spanning 90
institutions and companies, working
across >15 organs and systems and 8
species
• >150+ curated datasets and
computational studies* containing
multimodal data: physiology,
morphology, anatomy, transcriptomics
• SPARC Data & Resource Center
infrastructure for sharing and using data
and other publicly available resources

6. Data & Resource Center (DRC)
Tools and services to:
• Make SPARC data available to the
public
• Build modeling and simulation
pipelines and platforms
• Create spatial and semantic maps of
ANS connectivity
• Institute standards and curation for
FAIR* data (*Findable, Accessible,
Interoperable and Reusable)
• Make SPARC Portal and resources
user-friendly
Knowledge
Curation
Map
Synthesis
Data
Coordination
UX
Computation &
Simulation
Four cores

7. What does SPARC offer?

8. • Includes diverse and large, curated
experimental and computational datasets
• Enables browsing, searching, and dataset
file downloads
• Builds novel visualizations and
integrations to add context
• Adheres to Findable, Accessible,
Interoperable and Reusable principles
• Built on Pennsieve data platform (formerly
Blackfynn) and offers cloud-based access
to datasets via Amazon AWS services
Public access to FAIR data

9. • Explore computational models from neural
interface modeling to downstream
physiological impact
• Sustainable, integrated, and reproducible
simulations and computational analysis
• Open and online resources
• Simulation, data analysis, image
processing, visualization, coupling
• Coming: optimization, control, AI and much
more!
Computing Platform
o2
S2
PARC supports simulations that predict the effects of
autonomic neuromodulation on organ function
https://docs.osparc.io/#/
Computational Modeling
and Analysis

10. Organ scaffolds are fit to segmented data to permit data
integration into a uniform reference space
Common Reference Spaces
• Scaffolds:
• define all anatomical structures that are
relevant to the physiological function
• create computational meshes on which
the biophysical equations governing
organ level function can be solved
• spatially incorporate other data types
(e.g., RNAseq, physiology)
• fully automated registration pipeline for
multi-species, multi-subjects data
• enable comparisons both within a species
(individual differences) and across multiple
species

11. Maps and knowledge
base of ANS Circuitry
• Detailed semantic knowledge base of ANS
connections derived from SPARC data and
literature supports the flatmap interface
=SCKAN
• Detailed circuitry being modeled uses a
toolkit called ApiNATOMY to create FAIR
models of neural and vascular circuitry
• Users will be able to query for detailed
topological information through the
knowledge base
ApiNATOMY model

12. A look inside the SPARC Portal

13. The SPARC Portal is the gateway to SPARC
• Unified access to SPARC data, tools
and platforms
• Supported by the SPARC Knowledge
Graph which is building connections
between data, metadata, knowledge and
tools
• Work in progress: We are constantly
adding data and functionality
• SPARC Roadmap is available on-line
• UI/UX evolution informed by user testing
and interactions SPARC Portal: https://sparc.science/
https://sparc.science/about/sparc-portal/sparc-roadmap

14. Getting started with the SPARC Portal
• Provides access to
data, models, maps,
tools and news and
events
• Tools:
⇒ O2
SPARC
simulation
platform
⇒ Viewers
⇒ 3D scaffolds
and mapping
tools
⇒ SCKAN
knowledge
base
Help!
https://sparc.science/

15. Faceted search provides easy exploration of SPARC
Access to data, maps, models and simulations
https://sparc.science/

16. Exploring the SPARC Knowledge Graph
• The SPARC Portal is
undergird by the SPARC
Knowledge Graph
• New faceted search
features allows easy
exploration of the
knowledge graph
• Data sets are connected
to models and additional
knowledge about
connectivity and spatial
distributions
Underlying knowledge graph connects data, tools, anatomy and connectivity
https://sparc.science/datasets/125?type=dataset

17. Exploring the SPARC Knowledge Graph
Underlying knowledge graph connects data, anatomical structures and connectivity
• New faceted search
allows easy exploration
of the knowledge graph
• Anatomical
structures
• Technique
• Species
• Sex
• Age
• Authors
• Coming soon:
Related datasets
https://sparc.science/datasets/125?type=dataset

18. Anatomy of a SPARC dataset
• SPARC datasets
undergo
semi-automated and
human curation
• All data are
organized according
to a common
standard: The SPARC
Dataset Structure
• Linked to detailed
experimental
protocols
• On-line viewers and
exploration tools
available
Rich metadata, data citations, visualization tools
https://sparc.science/datasets/34?type=dataset

19. Anatomy of a SPARC dataset
• SPARC datasets undergo
semi-automated and
human curation
• All data are organized
according to a common
standard: the SPARC
Dataset Structure
• Linked to detailed
experimental protocols
• On-line viewers and
exploration tools
available
• Download individual
files or entire datasets
Rich metadata, data citations, visualization tools
https://sparc.science/datasets/34?type=dataset
https://doi.org/10.17504/protocols.io.3rmgm46
Download
dataset
Download
files

20. Anatomy of a SPARC dataset
• SPARC datasets undergo
semi-automated and
human curation
• All data are organized
according to a common
standard: the SPARC
Dataset Structure
• Linked to detailed
experimental protocols
• On-line viewers and
exploration tools
available
Rich metadata, data citations, visualization tools
https://sparc.science/datasets/34?type=dataset
https://doi.org/10.17504/protocols.io.3rmgm46

21. • SPARC datasets undergo
semi-automated and
human curation
• All data are organized
according to a common
standard: the SPARC
Dataset Structure
• Linked to detailed
experimental protocols
• On-line viewers and
exploration tools
available
Anatomy of a SPARC dataset
Rich metadata, data citations, visualization tools
https://sparc.science/datasets/73?type=dataset

22. Exploring the SPARC Knowledge Graph
• On-line viewers allow
exploration of 2D, 3D and
4D data
• Connects data to 3D
models, simulations and
connectivity knowledge
Underlying knowledge graph connects data, anatomical structures and connectivity

23. Connecting to Connectivity Knowledge
• A prime directive for
SPARC is build maps of
ANS connectivity
• The Flatmap viewer
places datasets within a
connectivity context
SPARC is building maps and a knowledge base of ANS circuitry
https://sparc.science/datasets/164?type=dataset

24. Bladder connectivity
Viewers within datasets reveal connectivity information for structures
https://sparc.science/datasets/164?type=dataset
• Coming up: More details
about connectivity
information in SPARC

25. Exploring models and simulations
• SPARC provides access to
computational models,
scaffolds and simulations
• Many are linked to additional
tools and may be run on
platforms such as O2
S2
PARC

26. Connecting data to models and computational
• SPARC is building connections
between SPARC data sets and
computational platforms such
as O2
S2
PARC
• Users can use and publish
tools like Jupyter Notebooks
to explore SPARC data on
O2
S2
PARC
https://sparc.science/datasets/86/version/3

27. 3D anatomical scaffolds
• MAPCORE has developed
species-specific 3D
computational scaffolds of
individual organs that can
be used for computational
studies and 3D mapping of
daata
• Library and tools available
through SPARC

28. Science Highlight:
Mapping intrinsic cardiac nervous system (ICN)
B
B
L
P
V
M
P
V
S
V
C
R
P
V
L
A
R
A
SVC
L
P
V
MP
V
RP
V
Integrative atrial
scaffold to
compare datasets
“The ICN is “the little brain of the heart” integrating multiple local
sensory and autonomic inputs and regulates cardiac function. In
this study, we investigated the structural consistency and
variability of the rat ICN within and between sexes.”
-Mahyar Osanlouy
Leung, C., Chen, J., Moss, A., Tappan, S., Heal, M., Huffman, T., Farahani, N., Eisenman, L., Cheng, Z.,
Vadigepalli, R., & Schwaber, J. (2020). Mapping of ICN Neurons in a 3D Reconstructed Rat Heart (Version 2)
[Data set]. Blackfynn Discover. https://doi.org/10.26275/WCJE-HXIB
Leung, C., et al (2020).BioRXiv https://doi.org/10.1101/2020.07.29.227538

29. Building and visualizing a knowledge base of
ANS circuitry: SCKAN

30. Navigating the SPARC Portal: Maps
• Provides access to
data, models, maps,
tools and news and
events
• Tools:
⇒ O2
SPARC
simulation
platform
⇒ Viewers
⇒ 3D scaffolds
and mapping
tools
⇒ SCKAN
knowledge
base

31. SPARC MAPS: Explore SPARC Data, Models and
simulations through ANS Connectivity
Find SPARC data and simulations
on the vagus nerve
See data mapped onto
interactive 3D scaffolds
Explore connectivity
https://sparc.science/maps
SPARC-MAP Core: Peter Hunter, PI

32. Multiresolution maps of ANS connectivity
Zoomable interface reveals additional levels of detail
SPARC-MAP Core: Peter Hunter, PI

33. Building the SPARC Connectivity Map
• The ANS connectivity map is currently being populated on a system by system basis
• Detailed “subway maps” of circuitry of these systems are produced through consultation
with anatomical and physiological experts, literature and SPARC data using the ApiNATOMY
toolkit
• Connections represented manually in the interactive on-line atlas
https://github.com/open-physiology/apinatomy-models/blob/master/keast-bladder/docs/keast-bladder-neurons.pdf
Keast Bladder Connectivity Model
Bernard de Bono, SAWG, Other Experts Auckland Bioengineering Institute
Text/datasets

34. Neuron populations course through nerves
• Detailed connectivity is
provided at the neuron
population level
• Neuron populations travel
via nerves indicated by cuffs
• Individual neuron
populations in each system
and their courses are
identified by model and ID
Pudendal nerve
Lumbar splanchnic nerve
Keast bladder neuron type 9
Pelvic ganglion
Bladder connectivity model: Janet Keast
Urethra
Bladder
Keast bladder neuron type 9
Keast bladder neuron type 2
Keast bladder neuron type 2

35. ApiNATOMY models available through SPARC
• Bolser-Lewis model of
defensive breathing
• Don Bolser, Steve Lewis
• Keast bladder model
• Janet Keast
• Bronchomotor control
• SPARC Anatomical Working
Group
• Ardell-Armour model of heart
• Jeff Ardell, John Armour
• SAWG model of distal colon
• SPARC Anatomical Working
Group
• Powley stomach
• Terry Powley
Full list: https://scicrunch.org/sawg/about/ApiNATOMY
defensive breathing
bladder
heart
distal colon bronchomotor
stomach
Total: 91 neuron populations

36. Limitations to current approach
• Keeping pace with new connectivity
knowledge
• Modifying or correcting
• Representing granular connections
and routes, resulting in loss of
topological information
• Understanding connectivity patterns
• Comparing across species
• Visualizing points of contention
Manual drawing and upkeep leads to difficulties in…

37. SCKAN: A knowledge base for ANS connectivity
● Connectivity represented according to ApiNATOMY is stored in SciGraph, a neo4j graph
database
● It is also available as RDF via Blazegraph
SCKAN makes the detailed knowledge of ApiNATOMY maps computable
Knowledge engineers
Bernard de Bono
ANS experts,
SPARC Anatomy
Working Group
Tom Gillespie, Monique Surles-Zeigler, Bernard de Bono

38. ApiNATOMY
● Models flow between biological
structures, e.g., fluid, information
● Represents neuron populations
and the location of their parts:
soma, dendrite, axon segments,
terminals
● Provides a compact
representation for chaining
together individual segments of
neuronal processes
● FAIR: All anatomical structures
are mapped to UBERON/FMA
identifiers
Bernard de Bono
Bladder connectivity model in consultation with Janet Keast

39. What can we do with SCKAN?
39
Query
SCKAN
● Support knowledge-based queries:
○ Find anatomical regions connected by
specified neuron types.
○ Find connections that course through a
specified tract, nerve, or ganglion.
● Automatically populate models, interactive
visualizations with up to date connectivity
information
● Provide detailed provenance

40. Find anatomical regions traversed by a neuron population
Query results: Axon chain for L1 Neuron 6 from the Keast bladder model
David Nickerson (ABI) and Tom Gillespie
pelvic ganglion
lamina VII of gray
matter of spinal cord
Lumbar splanchnic nerve
L1
L2

41. Automatic visualization of connections on SPARC flatmap
MAP-CORE
David Nickerson (ABI), David Brooks (ABI) and Tom Gillespie
SCKAN Query: Neuron 11 keast model
Soma, Axon terminal locations
Axon chain

42. Provenance is attached to each neuron population in
SCKAN: model + literature + SPARC datasets
Models are published with a DOI in
Zenodo
Currently in beta testing

43. Find all neurons with processes in IMG
FAIR representation combines across models and other sources
● L1 DRG neuron
● L4 sympathetic pre-ganglionic neuron
● Interstitial neuron of MP of colon
● Intestinal-fugal neuron in myenteric
plexus of colon
● Symp postganglionic neuron in IMG
● Symp postganglionic neuron in IMG
● Symp postganglionic neuron in IMG
● Sympathetic post ganglionic neuron in
IMG
● Sympathetic preganglionic neuron in
L1
● Sympathetic preganglionic neuron in L1
● Sympathetic preganglionic neuron in L2
● Sympathetic preganglionic neuron in L2
● First order sensory neuron in L1 DRG

44. ● Soma of Symp postganglionic neuron in
IMG_Neuron G (colon)
● Dendrite chain of Symp postganglionic neuron in
IMG_Neuron G (colon)
● Axon chain of intestinafugal neuron in myenteric
plexus of colon_Neuron Q (colon)
● Soma of Symp postganglionic neuron in
IMG_Neuron F (colon)
● Dendrite chain of Symp postganglionic neuron in
IMG_Neuron F (colon)
● Axon chain of Symp postganglionic neuron in
IMG_Neuron F (colon)
● Soma to SPOG neuron 3 in IMG_Neuron 3
(bladder)
● IMG SPO axon chain_Neuron 3 (bladder)
… more
inferior mesenteric ganglion
Integration across models through shared ontologies
Neurons with processes in IMG are referenced in two models

45. IMG stimulation potentially hits 10+ neuron populations*
traversing 30 anatomical compartments
1. hypogastric nerve
2. L2 ventral root
3. Gray communicating ramus of
second lumbar nerve
4. L2 ventral root
5. lumbar splanchnic nerve
6. inferior mesenteric ganglion
7. ventral root of spinal cord
8. submucous nerve plexus
9. circular layer (TA98)
10. lamina propria of mucosa of colon
11. lumbar nerve
12. serosa of colon
13. longitudinal layer (TA98)
14. colon
15. myenteric nerve plexus
16. Second lumbar dorsal root ganglion
Laying the foundation for modeling and simulation of neuromodulation
17. First lumbar dorsal root ganglion
18. Gray communicating ramus of
first lumbar nerve
19. nerve of bladder
20. neck of urinary bladder
21. fundus of urinary bladder
22. Blood vessel
23. pelvic ganglion
24. Second lumbar ganglion
25. First lumbar ganglion
26. Third lumbar spinal cord segment
27. Fourth lumbar spinal cord
segment
28. Second lumbar spinal cord
segment
29. First lumbar spinal cord segment
30. Axial regional part of spinal cord
*current flat map does not reflect all ApiNATOMY models in SCKAN
All structures mapped to UBERON, FMA and EMAPA

46. SCKAN: Flexible knowledge visualization
W
i
r
i
n
g
d
i
a
g
r
a
m
s
3D models
A
t
l
a
s
e
s

47. What’s next?

48. Looking Forward
SPARC Portal and tools will continue to
increase in breadth, depth and functionality
• Improve ability to explore and discover
SPARC output, e.g., incorporate more
online viewers for SPARC data
• Facilitate finding related/associated data,
computational models, analysis
functionality, and anatomical models
• Launch SPARC Knowledge Base, including
information and insight about/into the
ANS and its integrated physiological role
SPARC will continue to develop as a
community hub for ANS research
• Provide collaboration space for SPARC
researchers
• Broaden participation beyond the
SPARC-funded Consortium
See SPARC Roadmap
https://sparc.science/help/sparc-roadmap

49. Integration with other resources
HuBMAP
Partnership
(Anatomy-based
Spatial Organ Gene-
Expression
Management)
Common Fund Data Ecosystem
(CFDE)
Anatomy
Working
Group
SPARC SCKAN
CFDE Anatomy
Working Group
(cAWG)
CFDE-wide
Anatomy
Knowledge
Management
ReproTox
Partnership
(Anatomy-based
Teratogenicity
Information
Management.)
CLOVoc
Partnership
(Anatomy-based
Clinical Data
Management.)
Core CFDE Ontology Pipeline
(Anatomy-based
Term Management
Workflow)
Bernard de Bono
SCKAN is a unique asset within
the CFDE that can augment
molecular and physiological
mapping efforts
https://www.nih-cfde.org/

50. NEW SPARC Initiatives
VESPA Applications
due April 1, 2022
Neuromodprize.com
Submissions due April
1, 2022
REVA Initiative open
January 26, 2022
SPARC-V: Vagus nerve mapping and physiology
•VNS Endpoints from Standardized Parameters (VESPA)
Center (U54): will implement a large multisite clinical study of the
multi-organ effects of vagus nerve stimulation
•Reconstructing Vagal Anatomy (REVA): is a new initiative to
create detailed maps of the human vagus nerve
SPARC-X: Prize Competition
•Neuromod Prize aims to incentivize selective neuromodulation of
multiple outcomes without off-target effects

51. Thank you!
➢ K-CORE
■ Tom Gillespie
■ Monique Surles-Zeigler
■ Anna Pilko
■ Jyl Boline (Informed Minds)
■ Bernard de Bono (Whitby Inc)
■ Jeff Grethe
■ Anita Bandrowski
➢ MAP-CORE
○ Auckland Bioengineering Institute
■ Peter Hunter
■ David Nickerson
■ David Brooks
■ Alan Wu
■ Hugh Sorby
■ Richard Christie
■ Bernard de Bono
➢ All my SPARC and FDI Lab colleagues
○ Gary Mawe (UVa): SAWG
○ Jackie Breshnahan (UCSF): SAWG
○ Joost Waggoner, U Penn DAT-CORE
○ Esra Neufield, ITIS, Geneva, SIM-CORE
Supported by NIH SPARC Program: OTOD030541,OTOD032619 and OTOD025349