Advanced Computational Neuroscience Network (ACNN) Spoke

University of Michigan
Indiana University
Ohio State University
Case Western Reserve University

University of Michigan
University of Illinois at Urbana-Champaign
University of Texas at Austin
Ohio State University


Sep 6-7
Ohio State University - Case Western Reserve University
Fall 2021
University of Illinois at Urbana-Champaign


The Advanced Computational Neuroscience Network (ACNN) aims to educate a new generation of data-science-ready trainees and build broad consensus on the core requirements, infrastructure, and components needed to develop a sustainable interdisciplinary Big Data Neuroscience research field. As a network, ACNN leverages community strengths and resources to drive innovation and collaboration for the understanding of the structure, cellular and molecular components, physiology, and function of the brain through research collaborations and education activities. Founded over 8 years ago, the ACNN benefits from a large body of over 50 partners – among universities, industry partners, research centers and hospitals.

The ACNN partners provide expertise, and strong support to the creation of a sustainable neuroscience community that can effectively address the new challenges in Big Data Neuroscience by leveraging transdisciplinary expertise, informatics and educational resources. The ACNN partners represent aggregated neuroscience domain expertise, computational science, informatics, and resources focussed on different aspects of Big Data Neuroscience.

Midwest States Pole

Southern States Pole

Past Members




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.


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

Northwestern University

Ohio State University

Case Western Reserve University

Washington University

University of Illinois at Urbana-Champaign

News & Events


June 12, 2017 - IU researchers awarded access to Microsoft cloud to advance neuroscience, big data training (via News at IU Bloomington)


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.

Summer 2017 Data Science and Predictive Analytics (DSPA) MOOC
Date: Starting July 01, 2017, self-paced
Instructor: Ivo D. Dinov
Institution: University of Michigan
Certification: Dynamic flowchart - pathways to partial DSPA MOOC completion certification
Coverage: The following topics will be covered
Prerequisites: General DSPA Prerequisites
Outcome Competencies: This course is designed to build specific data science skills and predictive analytic competencies
Registration is free

IBRO-APRC School on Neuroinformatics and Brain Network Analysis
Date: Aug 10-18, 2017
Location: Kuala Lumpur, Malaysia
Summary: ACNN Investigators are co-organizing a INCF/IBRO Neuroscience Summer School for graduate students and postdoctoral fellows on (1) Statistical Computing, (2) High Throughput Processing of Neuroscience Big Data, and (3) Neuroimaging-genetics. The Summer Neuroscience School is part of the International Neuroinformatics Coordinating Facility (INCF)/International Brain Research Organization

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

2017 Joint PI Meeting: NSF BIGDATA and Big Data Hubs & Spokes
Date: Mar 15-17, 2017
Location: Omni Shoreham Hotel, DC


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.

The ACNN publications illustrate the breadth and depth of neuroscience research conducted at member institutions.


To contact the ACNN investigators, please email:

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


The research, development, education activities, and scholarship of the Advanced 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:



Become an Affiliate

Please submit this form if you are interested in being an affiliate of the ACNN