BRAIN Initiative - Theories, Models and Methods

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Go to 2021 BRAIN BOOTH


TMM FOA requirements

Working Group Lead

Bill Lytton, Fidel Santamaria

TMM members

This Working Group supports the activities of the awardees in the NIH BRAIN Initiative developing new theories, models and methods to understand complex brain circuits.



1. DATA Scholar Project

Expanding Theories of Brain Circuits Using Knowledge Integration: Solving knowledge integration challenges and develop the BRAIN initiative Workspace to ORganize the Knowledge Space (BRAINWORKS) platform


All TMM Projects are encouraged to utilize the NIH BRAINWORKS platform (that organizes, integrates, and represents nuanced knowledge contained within the growing body of the scientific literature) to assist in the development of Theories, Models and Methods for understanding brain circuits from the cellular and subsecond resolution to behavior.  


2. BRAIN Awardee Welcome Meeting/Intro to DATA Scholar




4. U19/TMM Data & Model Match for Reuse

Deadline to upload abstracts was September 25th, 2020.


5. RFAs and other calls

BRAIN Initiative:  Theories Models and Methods RFA
Current FOA: {Released June 29, 2020}

Letter of Intent Due Date(s) August 14, 2020

Application Due Date(s) September 14, 2020All applications are due by 5:00 PM local time of applicant organization.

Past FOAs:

1-Slide Template: to explain the math inside the tools being developed NIBIB Math Project Template_final.pptx {use this to post in your project pages!}

6. Activity Log

6.1 Discussion on roadblocks to theoretical neuroscience from 2020 BRAIN PI meeting

THEORIES Discussion {Please post your thoughts!}


6.2 Meeting notes

July 27, 2020 Call

2020 BRAIN PI Meeting - TMM vitual booth materials

February 14, 2020 Call 

2019 BRAIN PI Meeting Materials

2019 TMM group shot


Additional Information

TMM Projects

  • Add your 1-slide project description in your pages below
  • Use the IMAG wiki forms to tell the world about your project (see wiki editing instructions in the lower navigation bar)

*Participating in Data Reuse Effort and Abstract is Linked


PI Name(s) All Title Grant #
BROWN, EMERY N Filtered Point Process Inference Framework for Modeling Neural Data EB022726
*CARLSON, DAVID E Uncovering Population-Level Cellular Relationships to Behavior via Mesoscale Networks EB026937


Efficient resource allocation and information retention in working memory circuits EB028154
CHUNG, MOO K BRAIN Initiative:  Theories, Models and Methods for Analysis of Complex Data from the Brain EB022856
CURTO, CARINA  Emergent dynamics from network connectivity: a minimal model EB022862


Tools for modeling state-dependent sensory encoding by neural populations across spatial and temporal scales EB028155
*DOIRON, BRENT D (contact); SMITH, MATTHEW A; YU, BYRON M Neuronal population dynamics within and across cortical areas EB026953
*DRUCKMANN, SHAUL  Dissecting distributed representations by advanced population activity analysis methods and modeling EB028171


A comparative framework for modeling the low-dimensional geometry of neural population states



Discovering dynamic computations from large-scale neural activity recordings EB026949
ENGEL, TATIANA Multiscale computational frameworks for integrating large-scale cortical dynamics, connectivity, and behavior DA055666
FLETCHER, PRESTON THOMAS Beyond Diagnostic Classification of Autism: Neuroanatomical, Functional, and Behavioral Phenotypes EB022876
GATES, KATHLEEN  Network Connectivity Modeling of Heterogeneous Brain Data to Examine Ensembles of Activity Across Two Levels of Dimensionality EB022904
GOLD, JOSHUA I (contact); BALASUBRAMANIAN, VIJAY  Mental, measurement, and model complexity in neuroscience EB026945
HANSON, STEPHEN JOSE EFFECTIVE CONNECTIVITY IN BRAIN NETWORKS: Discovering Latent Structure, Network Complexity and Recurrence EB022858
*HOWARD, MARC W Toward a Theory for Macroscopic Neural Computation Based on Laplace Transform EB022864
JONES, STEPHANIE RUGGIANO (contact); HAMALAINEN, MATTI ; HINES, MICHAEL L Human Neocortical Neurosolver EB022889

Crossing space and time: uncovering the nonlinear dynamics of multimodal and multiscale brain activity



Connecting neural circuit architecture and experience-driven probabilistic computations


KORDING, KONRAD P Quantifying causality for neuroscience EB028162


Measuring, Modeling, and Modulating Cross-Frequency Coupling EB026938


Relating structure and function in synapse-level wiring diagrams


LUO, XI  Large-scale Network Modeling for Brain Dynamics: Statistical Learning and Optimization EB022911
*LYTTON, WILLIAM W (contact); ANTIC, SRDJAN D Embedded Ensemble Encoding EB022903


Application of the principle of symmetry to neural circuitry: from building blocks to neural synchronization in the connectome



Graph theoretical analysis of the effect of brain tumors on functional MRI networks EB022720
MENON, VINOD  Novel Bayesian linear dynamical systems-based methods for discovering human brain circuit dynamics in health and disease EB022907
MIHALAS, STEFAN (contact);SHEA-BROWN, ERIC TODD From diverse dynamics to diverse computation via neural cell types  DA055669


Modeling the structure-function relation in a reconstructed cortical tissue



Data-driven analysis for neuronal dynamic modeling EB026936
MITRA, PARTHA PRATIM (contact); WANG, YUSU  Methods from Computational Topology and Geometry for Analysing Neuronal Tree and Graph Data EB022899
MJOLSNESS, ErRIC Multiscale theory of synapse function with model reduction by machine learning DA055668
NEMENMAN, ILYA M (contact); SOBER, SAMUEL  Neural mechanisms and behavioral consequences of non-Gaussian likelihoods in sensorimotor learning EB022872
PALMER, STEPHANIE E (contact); BIALEK, WILLIAM ; SCHWAB, DAVID JASON Coarse-graining approaches to networks, learning, and behavior EB026943
PANDARINATH, CHETHAN (contact); MILLER, LEE E Robust modeling of within-and across-area population dynamics using recurrent neural networks   DA055667
PANINSKI, LIAM M Next-Generation Calcium Imaging Analysis Methods EB022913
*PARK, IL MEMMING (contact); PILLOW, JONATHAN WILLIAM Real-time statistical algorithms for controlling neural dynamics and behavior EB026946
RAJ, ASHISH  (contact); NAGARAJAN, SRIKANTAN S Multimodal modeling framework for fusing structural and functional connectome data EB022717
*RAJAN, KANAKA  Multi-region Network of Networks Recurrent Neural Network Models of Adaptive and Maladaptive Learning EB028166
RINGACH, DARIO L Bayesian estimation of network connectivity and motifs EB022915


A unified framework to study history dependence in the nervous system EB026939
SEJNOWSKI, TERRENCE J Nonlinear Causal Analysis of Neural Signals EB026899


A new theory of population coding in the cerebellum


SHEN, DINGGANG  (contact); YAP, PEW-THIAN  Diagnosis of Alzheimers Disease Using Dynamic High-Order Brain Networks EB022880
*SHOUVAL, HAREL ZEEV (contact); BRUNEL, NICOLAS  Learning spatio-temporal statistics from the environment in recurrent networks EB022891
SINGH, VIKAS  (contact); JOHNSON, STERLING C Manifold-valued statistical models for longitudinal morphometic analysis in preclinical Alzheimers disease (AD) EB022883
*SOMMER, FRIEDRICH T Building analysis tools and a theory framework for inferring principles of neural computation from multi-scale organization in brain recordings EB026955
SONG, DONG Combined Mechanistic and Input-Output Modeling of the Hippocampus During Spatial Navigation DA055665


Models and Methods for Calcium Imaging Data with Application to the Allen Brain Observatory EB026908
WOMELSDORF, THILO  Mechanisms of Information Routing in Primate Fronto-striatal Circuits EB028161
*YE, BING  (contact); DIERSSEN, MARA  New methods and theories to interrogate organizational principles from single cell to neuronal networks EB028159