Funding
Funding
Current
The Heart and the Mind: An Integrative Approach to Brain-Body Interactions in the Zebrafish
2U19NS104653 (None): 01-Sep-2022 to 31-Aug-2024Johns Hopkins University will be responsible for developing all algorithms and software in support of the Atlas project, as well as running the Data Core. This will include writing software to store, manage, and visualize the data, as well as algorithms for scalable analysis and support of modeling.
Neural Net Learning for Graph
NSF 2113099 (None): 01-Sep-2021 to 31-Aug-2024Goal of this project is methodological development, theoretical investigation, and simulation and real data experimentation toward the end goal of principled understanding and advancement of the mathematics and science of graph neural network
An Alignment Framework for Mapping Brain Dynamics and Substrates of Human Cognition Across Species
1RF1MH128696 (None): 01-Sep-2021 to 31-Aug-2024We will continue collecting, organizing, and analyzing another cohort of the NKI-Rockland Sample.
The NKI Rockland Sample II: An Open Resource of Multimodal Brain, Physiology & Behavior Data from a Community Lifespan Sample
2U19NS104653 (None): 01-Jul-2022 to 30-Apr-2026The major goal is to establish multimodal MRI and electrophysiology lifespan sample to open and prospectively share with the larger scientific community.
Collaborative Research: Transferable, Hierarchical, Expensive, Optimal, Robust, Interpretable Networks
NSF 20-540 (None): 01-Sep-2020 to 31-Aug-2025The goal of this project is to develop a mathematical, statistical and computational frame- work that helps explain the success of current network arcitectures, understand its pitfalls, and guide the design of novel architectures with guaranteed confidence, robustness, inter- pretability, optimality, and transferability
Federated Causal Inference for Multi-site Real-World Evidence & Clinical Trial Analysis
Studies in Pandemic Preparedness (None): 01-Aug-2020 to currentThis project will conduct federated retrospective analyses designed to assess the benefit of off-label drug use by pooling multiple disparate databases, to help prioritize and guide subsequent initiation and recruitment of randomized clinical trials. This will include evaluating the impact of the target drugs on patient outcomes from diseases similar to COVID-19, such as pneumonia or acute respiratory distress, generating artificial datasets using generative adversarial networks to asses performance of methods when 'ground truth' is known, applying the best methods to analyze the effect of the target drugs on the outcomes of COVID-19 patients across hospital systems, and using the results to evaluate the potential of these drugs and suggest guidelines for clinical trials.
Graspy: A python package for rigorous statistical analysis of populations of attributed connectomes
NIH MH-19-147 (None): 01-Jul-2020 to 30-Jun-2023The goal of this project is to establish a state-of-the-art toolbox for analysis of connectomes, spanning taxa, scale, and complexity. we will develop and extend implementations to enable neurobiologists to (1) estimate latent structure from attributed connectomes, (2) identify meaningful clusters among populations of connectomes, and (3) detect relationships be- tween connectomes and multivariate phenotypes
NeuroNex2: Enabling Identification and Impact of Synaptic Weight in Functional Networks
NSF 2014862 (None): 01-Apr-2020 to 31-Mar-2025The goal is to develop the requisite technology to understand the impact of synaptic weight on functional networks
CAREER: Foundational Statistical Theory and Methods for Analysis of Populations of Attributed Connectomes
NSF 17-537 (None): 01-Jan-2020 to 31-Dec-2025The goal is to establish foundaitonal theory and methods for analyzing populations of attributed connectomes
Brain Networks in Mouse Models of Aging
NIH RO1AG066184-01 (None): 01-Dec-2019 to 30-Nov-2023The goal of this grant is to generate connectomes and RNA-seq transcriptomes to characterize and differentiate APOE mice as a model of aging
Microsoft Research Award
(None): Unrestricted GiftResearch and development of neuroscience and connectomes around neuronal circuit and system modeling, application of time-series-of-graphs and dynamics to neuronal signaling analysis and connectomes, and in the abstractions of matter, math, machines that point toward complex systems composed of low-level components
Completed
AI Institute: Planning: BI4ALL: Understanding Biological
NSF 20-503 (None): 01-Oct-2020 to 31-Jul-2022The goal of this project is to plan an AI institution via several meetings and workshops
Accessible technologies for high-throughput, whole-brain reconstructions of molecularly characterized mammalian neurons
NIH RFA-MH-19-148 (None): 01-Sep-2019 to 31-Aug-2022The overall goal of the proposal is to develop technologies for the brain wide reconstruction of axonal arbors of molecularly defined neurons. The proposal aims at overcoming barriers in neuronal labeling, imaging and computation to achieve this goal, and to develop a technology platform that can be scaled to all neurons of the brain
Reproducible imaging-based brain growth charts for psychiatry
NIH R01MH120482-01 (None): 01-Aug-2019 to 31-May-2020Aggregate, harmonize, and analyze existing large-scale pediatric neuroimaging datasets to identify normative and clinical brain growth curves
SemiSynBio: Collaborative Research: YeastOns: Neural Networks Implemented in Communication Yeast Cells
NSF 1807369 (None): 16-Jul-2018 to 30-Jun-2021Provide neuroscience and machine learning expertise to guide the design of the computa- tional learning capabilities of the system
Connectome Coding at the Synaptic Scale
Nascent Innovation Grant 128503 (None): 01-Jan-2018 to 31-Dec-2020Study learning and plasticity at an unprecedented scale, revealing the dynamics of large populations of synapses comprising an entire local cortical circuit. No previously conducted experiment could answer the questions about the dynamics of large populations of synapses, which is crucial to understanding the learning process
Continual Learning Across Synapses, Circuits, and Brain Areas
FA8650-18-2-7834 (None): 01-Nov-2017 to 30-Oct-2021Develop the pre-processing analysis pipeline for the imaging data collected in this project
Lifelong Learning Forests
FA8650-18-2-7834 (None): 01-Nov-2017 to 31-Oct-2021Lifelong Learning Forests (L2Fs) will learn continuously, selectively adapting to new environ- ments and circumstances utilizing top-down feedback to impact low-level processing, with provable statistical guarantees, while maintaining computational tractability at scale
Sensorimotor processing, decision making, and internal states: towards a realistic multiscale circuit model of the larval zebrafish brain
NIH 1U19NS104653-01 (None): 01-Sep-2017 to 31-Aug-2022Generate a realistic multiscale circuit model of the larval zebrafish’s brain – the multiscale virtual fish (MSVF). The model will span spatial ranges from the nanoscale at the synaptic level, to local microcircuits to inter-area connectivity - and its ultimate purpose is to explain and simulate the quantitative and qualitative nature of behavioral output across various timescales
NeuroNex Innovation Award: Towards Automatic Analysis of Multi-Terabyte Cleared Brains
NSF 1707298 (None): 01-Sep-2017 to 31-Aug-2020 (No Cost Extension)We propose to lower the barrier to connecting data to analyses and models by providing a coherent cloud computational ecosystem that minimizes current bottlenecks in the scientific process
CRCNS US-German Res Prop: functional computational anatomy of the auditory cortex
NIH 1R01DC016784-01 (None): 01-Jul-2017 to 30-Jun-2020Create a robust computational framework for analyzing the cortical ribbon in a specific region: the auditory cortex
Multiscale Generalized Correlation: A Unified Distance-Based Correlation Measure for Dependence Discovery
NSF 1921310 (None): 01-May-2017 to 30-Apr-2020Establish a unified methodology framework for statistical testing in high-dimensional, noisy, big data, through theoretical advancements, comprehensive simulations, and real data experiments
NeuroNex Technology Hub: Towards the International Brain Station for Accelerating and Democratizing Neuroscience Data Analysis and Modeling
NSF 16-569 (None): 2017 to 2019We propose to lower the barrier to connecting data to analyses and models by providing a coherent cloud computational ecosystem that minimizes current bottlenecks in the scientific process
The International Brain Station
90071826 (None): 2017 to 2018Take the first few steps towards building the international brain station
Brain Comp Infra: EAGER: BrainLab CI: Collaborative, Community Experiments
ACI-1649880 (None): 2017 to 2018The BrainLab CI prototype system will deploy an experimental-management infrastruc- ture that allows users to construct community-wide experiments that implement data and metadata controls on the inclusion and exclusion of data
The Brain Ark
90076467 (None): 2017 to 2018Characterize the statistical properties of the individual graphs, to identify circuit motifs, both that specialize in a species specific fashion, and that are preserved across species. As a test, will compare the connectomes of sea lions and coyotes
D3M: What Would Tukey Do?
FA8750-17-2-0112 (None): 01-Oct-2016 to 30-Sep-2020Develop theory and methods for generating a discoverable archive of data modeling primi- tives and for automatically selecting model primitives and for composing selected primitives into complex modeling pipelines based on user-specified data and outcome(s) of interest
A Scientific Planning Workshop for Coordinating Brain Research Around the Globe
NIH RFA-MH-19-148 (None): 2016 to 2019This travel grant is for the expressed purposes of gathering researchers from around the globe to discuss the new way to further brain research during part one of a two day conference
A Scientific Planning Workshop for Coordinating Brain Research Around the Globe
NSF 1637376 (None): 2016 to 2019This travel grant is for the expressed purposes of gathering researchers from around the globe to further discuss advancements in brain research during the second part of a two day conference
From RAGs to Riches: Utilizing Richly Attributed Graphs to Reason from
N66001-15-C-40401 (None): 01-Sep-2019 to 31-Aug-2022Multiple, large, multifarious brain imaging datasets are rapidly becoming standards in neuroscience. Yet, we lack the tools to analyze individual datasets, much less populations thereof. Therefore, we will develop theory and methods to analyze and otherwise make such data available
Scalable Grain Graph Analyses Using Big-Memory, High-IPS Compute Architectures
N66001-14-1-4028 (None): 2014 to 2016Build software infrastructure to enable analytics on billion node, terabyte sized networks using commodity hardware
Synaptomes of Mouse and Man
NIH R01NS092474 (None): 2014 to 2019The major goals of this project are to discover the synaptic diversity and complexity in mammalian brains, specifically comparing and contrasting humans with mice, the leading experimental animal
CRCNS: Data Sharing: The EM open Connectome Project
RO1EB16411 (None): 2012 to 2015Develop cyberinfrastructure to support management, visualization, storage, and analysis of large-scale electron microscopy data