BRAIN Initiative - Theories, Models and Methods

This wiki supports the activities of the NIH BRAIN Theories, Models and Methods grantees.

 

TMM FOA requirements

Working Group Leads

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.

Slack: https://braincircuits.slack.com/

Activities

2024

070324: GCYPeng:  something for everyone to ponder!  Must a theory be falsifiable to contribute to good science?

(You'll recognize your fellow TMM awardees in this conversation!)

 


2023 BRAINWORKS on the Federal GitHub

2021-2022 DATA Scholar Project

 

  • 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.  

 

 


 

2020 U19/TMM Data & Model Match for Reuse

Deadline to upload abstracts was September 25th, 2020.

 


RFAs and other calls

BRAIN Initiative:  Theories Models and Methods RFA
Current FOA:  https://grants.nih.gov/grants/guide/rfa-files/RFA-EB-20-002.html {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:

https://grants.nih.gov/grants/guide/rfa-files/rfa-eb-17-005.html

https://grants.nih.gov/grants/guide/rfa-files/rfa-eb-15-006.html


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!}



Activity Log

Discussion on roadblocks to theoretical neuroscience from 2020 BRAIN PI meeting

THEORIES Discussion {Please post your thoughts!}

 

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)

All BRAIN Theories, Models and Methods Awardees

*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
CHEN, ZHE SAGE (contact); BUZSAKI, GYORGY Dissection of spatiotemporal activity from large-scale, mutli-modal, multi-resolution hippocampal-neocortical recordings DA056394

*CHING, SHINUNG  (contact); SNYDER, LAWRENCE H

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
COEN-CAGLI, RUBEN Computational Tools for assessing mechanisms and functional relevance of divisive normalization DA056400
CURTO, CARINA  Emergent dynamics from network connectivity: a minimal model EB022862
     

*DAVID, STEPHEN V (contact); MESGARANI, NIMA 

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

DYER, EVA

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

EB029852

*ENGEL, TATIANA 

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
KEILHOLZ, SHELLA D

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

EB029857

*KILPATRICK, ZACHARY PETER

Connecting neural circuit architecture and experience-driven probabilistic computations

EB029847

KORDING, KONRAD P Quantifying causality for neuroscience EB028162

*KRAMER, MARK ALAN (contact); EDEN, URI TZVI

Measuring, Modeling, and Modulating Cross-Frequency Coupling EB026938

LITWIN-KUMAR, ASHOK

Relating structure and function in synapse-level wiring diagrams

EB029858

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

*MAKSE, HERNAN

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

EB028157

MAKSE, HERNAN  (contact); HOLODNY, ANDREI I

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

MIHALAS, STEFAN (contact); ARKHIPOV, ANTON

Modeling the structure-function relation in a reconstructed cortical tissue

EB029813

MILLER, KENNETH D.  Modeling the development of orientation selectivity, maps, and the associated recurrent circuit DA056397

*MISHNE, GAL 

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
PEARSON, JOHN Real-time mapping and adaptive testing for neural population hypotheses DA056376

 

PILLOW, JONATHAN WILLIAM (contact); PARK, IL MEMMING

Adaptive statistical algorithms for learning and control of neural dynamics  DA065404

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
RAJAN, KANAKA  Neural Network Models Constrained by Multiscale Data to Infer Minimal Functional Motifs in the Brain  DA056403
RINGACH, DARIO L Bayesian estimation of network connectivity and motifs EB022915

*SANTAMARIA, FIDEL 

A unified framework to study history dependence in the nervous system EB026939
SAXENA, SHREYA Elucidating Principles of Sensorimotor Control using Deep Learning DA056377
SEJNOWSKI, TERRENCE J Nonlinear Causal Analysis of Neural Signals EB026899

SHADMEHR, RAZA

A new theory of population coding in the cerebellum

EB028156

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

*WITTEN, DANIELA  (contact); BUICE, MICHAEL 

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