Advance Computational Neuroscience Network (ACNN) Spoke

2016
University of Michigan
2017
Indiana University
2018
Ohio State University
Case Western Reserve University

2019
University of Michigan

Workshops

2018
2018
Sep
2018 ACNN Workshop on Big Neuroscience Data, Tools, Protocols & Services
Ohio State University - Case Western Reserve University
2019
2019
Sep
2019 ACNN Workshop on Big Neuroscience Data, Tools, Protocols & Services
University of Michigan

About

The Advanced Computational Neuroscience Network (ACNN) aims to build broad consensus on the core requirements, infrastructure, and components needed to develop a new generation of sustainable interdisciplinary Neuroscience Big Data research. As a network, ACNN leverages community strengths and resources to drive innovation and collaboration for the understanding of the structure, physiology, and function of the human brain through partnerships and services in education, tools, and best practices. Six major universities in the Midwest (Michigan, Ohio, Indiana, Case Western, Northwestern and Washington U, St. Louis) coordinate the ACNN research, development, training, and dissemination activities. Over 25 other universities, industry partners, neuroscience research centers and hospitals collaborator with ACNN investigators on a wire range or basic science, modeling, analytics and applied neuroscience research.

ACNN identifies barriers to neuroscience data sharing, interoperability, and challenges associated with managing Big Data. ACNN forges new collaborations to establish standards using neuroscience-focused ontologies, incorporate provenance metadata management, aggregate tools, index resources and repositories, and curate and share validated pipeline workflow.

The ACNN partners provide strong support to the creation of a sustainable neuroscience community that can effectively address the challenges of neuroscience Big Data and leverage the unique resources as well as human capital. The ACNN lead institutions and partners represent aggregated neuroscience domain expertise, computational science in Big Data, and resources from their members to focus on different aspects of neuroscience Big Data: (1) UM (University of Michigan): Automated data workflows, data processing protocols, and analytic tools, (2) WIN (Indiana-Northwestern-Washington Universities): Data management, communication and neuroscience analytics, (3) OCW (Ohio-State and Case Western Universities): neuroscience ontologies, provenance metadata, and high performance computing tools for neuroscience Big Data processing and Application Programming Interface (API). A particular strength of the ACNN is the existing array of neuroscience datasets, analytical tools, and provenance metadata platforms that can be bought together as part of a common data sharing and interoperability platform for the neuroscience research community.

The core team of transdisciplinary investigators include:

Resources


This web-form can be used to submit items for inclusion in the sharable resources. Examples (not an exclusive list) of appropriate resources that may be suggested includes:

You can see a real-time summary of the results and a tabular representation of previously submitted resource meta-data.

Training

An important component of the ACNN Spoke is its focus on training, education and diversity. With its strong and integrated programs in Neuroscience, Computer Science, and high performance computing resources, ACNN aims to build a skill cadre of young scientists by building innovative educational resources, interactive learning activities, sharing of powerful neuroscience data management tools, and online documentation and training manuals.

All partner universities are committed to extensive diversity, equity and engagement of minority and underserved populations including African-American, Hispanic, and Native American Populations. ACNN activities involve extensive efforts to recruit, train and engage underserved populations in our community building, training and education opportunities in the rapidly emerging neuroscience research domain.

See the Events page for details on various dissemination and training activities.

Partners & Collaborators

ACNN Investigators encourage junior and senior, academic and industry, government and foundation researchers interested in Big Neuroscience Data to contact us, actively engage in resource development and maintenance, contribute to standards and formats, and broadly participate in all ACNN activities.

Indiana University

Indiana.

Northwestern University

Northwestern U.

Ohio State University

OSU.

Case Western Reserve University

CWRU.

Washington University

WashU.

Events & News

The ACNN Spoke organizes annual neuroscience Big Data All Hands Meetings (AHM) that feature workshops, hackathons, training, and related events. These events are hosted at participating institutions. The annual events bring together a wide spectrum of stakeholders from research centers, educational institutions, and industry partners to build new partnerships and forge new collaborations across the Midwest region. A number of initiatives are planned for the AHM, including establishment of focused workgroups to establish best practices for neuroscience data interoperability, disseminate those practices and provide education about methods as well as technology for data analysis, computational management, and sharing. In addition, the meetings will feature public lectures, scientific talks as well as events targeting young trainees involved in neuroscience research. The AHM materials will be available on our web portal.

Smaller focused regional events are organized throughout the year.

Events

2017 Joint PI Meeting: NSF BIGDATA and Big Data Hubs & Spokes
Date: Mar 15-17, 2017
Location: Omni Shoreham Hotel, DC
Website: https://www.bi.vt.edu/nsf-big-data

Big Data Regional Innovation Hubs and Spokes Workshop BDHubs, Held in conjunction with the 31st IEEE International Parallel and Distributed Processing Symposium
Date: June 2, 2017
Location: Buena Vista Palace Hotel, Orlando, Florida, USA
Website: https://www.nsf.gov/cise/bdspokes/index.jsp

Research

ACNN aspires to build the foundation for modern, Big Data neuroscience technologies through community partnership. Among the key challenges impeding greater accessibility and sharing of neuroscience data is the lack of community-approved common data representation formats and metadata elements. In addition, communication between computational resources and existing informatics tools is a significant bottleneck in faster and more computation-intensive neuroscience analysis tools. ACNN proposes to address three specific problems related to neuroscience Big Data:

  1. data capture, organization, management involving multiple centers and research groups,
  2. quality assurance, preprocessing and analysis that incorporates contextual metadata, and
  3. data communication to software and hardware computational resources that can scale with the volume, velocity, and variety of neuroscience datasets.

More specifically, we plan to leverage the expertise and technologies developed by the ACNN Spoke investigators and our partners to integrate:

  1. Data Sharing and Interoperability using ontology-driven standardization, provenance metadata management, integrated into the most modern database and database-mediator technologies. Deliverable: We will work toward a neuroimaging data base federation within the Midwest region by organizing and mediating data across the 20+ partner neuroimaging centers;
  2. Analytics leveraging upon the most agreed upon preprocessing pipelines (LONI and HCP) and advanced network science approaches to brain mapping. Deliverable: We will integrate the Brain Connectivity Toolbox, the LONI, the SOCR and Human Connectome Pipelines to provide advanced access to standard brain analysis tools;
  3. Computing approaches based on high performance clusters, MapReduce and Hadoop as well as canonical architectures will be deployed and connected to data and analytics. Deliverable: We will implement fast high-throughput brain mapping analysis pipelines by exploiting the most advanced software and hardware architectures for big-data harnessing. The combined contribution of scientific expertise and technologies will allow bringing “online” and harnessing the long tail of neuroscience data currently available but limitedly accessible to a majority of investigators within the Midwest.

The core goal of the ACNN Spoke is to build a sustainable ecosystem of neuroscience community partners in both academia and industry using existing technologies for collaboration and virtual meeting together with face-to-face group meetings. Use of Web-based conferencing systems and remote communication technologies with regular monthly meetings will allow us to achieve our project objectives without incurring additional travel and related expenses for logistics.

The figure illustrates the details of the different technological and application components of the ACNN Spoke with participation of the different partners. In order to accomplish these three areas of integration, we will establish neuroscience-specific community-driven standards using scientific workflows systems, ontology and meta data standards. The creation and implementation of these standards will involve a great deal of community building over a number of years.

Contact

To contact the ACNN investigators, please email:

info@neurosciencenetwork.org

We will attempt to respond to all inquiries within a reasonable timeframe.

Credits

The research, development, education activities, and scholarship of the Advance Computational Neuroscience Network (ACNN) is made possible by:

The National Science Foundation (NSF)

NSF grants 1636840, 1636846, 1636893, 1636850, and 1550320 provide partial ACNN support

Participating organizations

Principal investigators

A team of transdisciplinary investigators from the Advanced Computational Neuroscience Network (ACNN), including:

Web-development