Award Abstract # 1707398
NeuroNex Theory Team: Columbia University Theoretical Neuroscience Center

NSF Org: DBI
Division of Biological Infrastructure
Recipient: THE TRUSTEES OF COLUMBIA UNIVERSITY IN THE CITY OF NEW YORK
Initial Amendment Date: July 31, 2017
Latest Amendment Date: June 23, 2022
Award Number: 1707398
Award Instrument: Cooperative Agreement
Program Manager: Sridhar Raghavachari
sraghava@nsf.gov
 (703)292-4845
DBI
 Division of Biological Infrastructure
BIO
 Directorate for Biological Sciences
Start Date: August 1, 2017
End Date: July 31, 2023 (Estimated)
Total Intended Award Amount: $3,040,000.00
Total Awarded Amount to Date: $7,600,750.00
Funds Obligated to Date: FY 2017 = $1,520,000.00
FY 2018 = $1,520,000.00

FY 2019 = $2,275,750.00

FY 2020 = $765,000.00

FY 2021 = $1,520,000.00
History of Investigator:
  • Laurence Abbott (Principal Investigator)
    lfa2103@columbia.edu
  • Kenneth Miller (Co-Principal Investigator)
  • Liam Paninski (Co-Principal Investigator)
  • Stefano Fusi (Co-Principal Investigator)
  • Ashok Litwin-Kumar (Co-Principal Investigator)
  • John Cunningham (Former Co-Principal Investigator)
Recipient Sponsored Research Office: Columbia University
615 W 131ST ST
NEW YORK
NY  US  10027-7922
(212)854-6851
Sponsor Congressional District: 13
Primary Place of Performance: Columbia University
3227 Broadway
New York
NY  US  10027-1111
Primary Place of Performance
Congressional District:
13
Unique Entity Identifier (UEI): F4N1QNPB95M4
Parent UEI:
NSF Program(s): OFFICE OF MULTIDISCIPLINARY AC,
STATISTICS,
Cognitive Neuroscience,
PHYSICS OF LIVING SYSTEMS,
Cross-BIO Activities,
MATHEMATICAL BIOLOGY,
Activation
Primary Program Source: 01002122DB NSF RESEARCH & RELATED ACTIVIT
01001920DB NSF RESEARCH & RELATED ACTIVIT

01002021DB NSF RESEARCH & RELATED ACTIVIT

01001819DB NSF RESEARCH & RELATED ACTIVIT

01001718DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 9179, 1228, 9178, 9183, 8007, 8089, 8091
Program Element Code(s): 125300, 126900, 169900, 724600, 727500, 733400, 771300
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.074

ABSTRACT

Understanding how a healthy brain interprets sensory signals and guides actions, and why an unhealthy brain fails to perform these functions properly, is a profound and ambitious goal of 21st century science. Integrating knowledge of neural circuit function into a coherent picture of perception, cognition and action requires extraordinary cooperation and coordination between three research areas: experimentation, data analysis and modeling. The National Science Foundation Theory Team at Columbia University will unite exceptional resources in statistical data analysis and theoretical modeling with an extensive network of experimental collaborators to address the enormous challenges facing neuroscience. Never has the need been greater for theoretical insights and sophisticated data analysis. The field of neuroscience is facing a torrent of complex data from a system that is, itself, extraordinarily complex. Future progress requires developing the ability to extract knowledge and understanding from these data through analyses and modeling that capture the essence of what they mean. The goal of the NeuroNex Theory Team at Columbia is to establish, through the quality of its research, the excellence of its trainees, and the impact of its visitor, dissemination, and outreach programs, a new cooperative paradigm that will move neuroscience to unprecedented levels of discovery and understanding.

High-density electrode recording, wide-field calcium imaging and complex connectivity mapping are bringing neuroscience into an era of extensive multi-area and even whole-brain studies of neural activity and circuitry. The neuroscience community desperately needs new ways of interpreting data obtained from different species using myriad techniques and for thinking about neural processing over large length and time scales and across multiple brain areas. In response to these challenges, two major goals will drive and define research at the NeuroNex Theory Team at Columbia: first, integrating the analysis methods and theoretical models used to infer meaning from data with each other and with the experiments that generate these data; and second, providing analytic tools and theoretical frameworks to understand interactions between multiple brain regions and to draw important overarching lessons from experiments exploiting a variety of techniques across different species. Progress will be made through a tight integration of theoretical techniques with outstanding experimental collaborators working on a variety of systems and species. Graduate and postdoctoral training will stress technical excellence and broad perspectives in both theoretical and experimental neuroscience. Outreach will be made to other researchers through visitor and exchange programs, sponsored meetings and dissemination of research results and high-quality, user-friendly software. Outreach will be made to the broader community by sharing the excitement of neuroscience research with elementary and high school students and with the general public. This NeuroNex Theory Team award is co-funded by the Division of Emerging Frontiers within the Directorate for Biological Sciences, the Division of Physics and the Division of Mathematics within the Directorate of Mathematical and Physical Sciences, and by the Division of Brain and Cognitive Sciences within the Directorate of Social, Behavioral and Economic Sciences, as part of the BRAIN Initiative and NSF's Understanding the Brain activities.

PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

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(Showing: 1 - 10 of 137)
Abbott, Larry and Svoboda, Karel "Brain-wide interactions between neural circuits" Current Opinion in Neurobiology , v.65 , 2020 https://doi.org/10.1016/j.conb.2020.12.012 Citation Details
Abbott, Larry F. and Angelaki, Dora E. and Carandini, Matteo and Churchland, Anne K. and Dan, Yang and Dayan, Peter and Deneve, Sophie and Fiete, Ila and Ganguli, Surya and Harris, Kenneth D. and Häusser, Michael and Hofer, Sonja and Latham, Peter E. and "An International Laboratory for Systems and Computational Neuroscience" Neuron , v.96 , 2017 10.1016/j.neuron.2017.12.013 Citation Details
Abbott, Larry F. and Bock, Davi D. and Callaway, Edward M. and Denk, Winfried and Dulac, Catherine and Fairhall, Adrienne L. and Fiete, Ila and Harris, Kristen M. and Helmstaedter, Moritz and Jain, Viren and Kasthuri, Narayanan and LeCun, Yann and Lichtma "The Mind of a Mouse" Cell , v.182 , 2020 https://doi.org/10.1016/j.cell.2020.08.010 Citation Details
Abdelfattah, Ahmed S. and Kawashima, Takashi and Singh, Amrita and Novak, Ondrej and Liu, Hui and Shuai, Yichun and Huang, Yi-Chieh and Campagnola, Luke and Seeman, Stephanie C. and Yu, Jianing and Zheng, Jihong and Grimm, Jonathan B. and Patel, Ronak and "Bright and photostable chemigenetic indicators for extended in vivo voltage imaging" Science , v.365 , 2019 10.1126/science.aav6416 Citation Details
Abe, Taiga and Kinsella, Ian and Saxena, Shreya and Buchanan, E. Kelly and Couto, Joao and Briggs, John and Kitt, Sian Lee and Glassman, Ryan and Zhou, John and Paninski, Liam and Cunningham, John P. "Neuroscience Cloud Analysis As a Service: An open-source platform for scalable, reproducible data analysis" Neuron , v.110 , 2022 https://doi.org/10.1016/j.neuron.2022.06.018 Citation Details
Adam, Yoav and Kim, Jeong J. and Lou, Shan and Zhao, Yongxin and Xie, Michael E. and Brinks, Daan and Wu, Hao and Mostajo-Radji, Mohammed A. and Kheifets, Simon and Parot, Vicente and Chettih, Selmaan and Williams, Katherine J. and Gmeiner, Benjamin and F "Voltage imaging and optogenetics reveal behaviour-dependent changes in hippocampal dynamics" Nature , v.569 , 2019 10.1038/s41586-019-1166-7 Citation Details
Ahmadian, Yashar and Miller, Kenneth D. "What is the dynamical regime of cerebral cortex?" Neuron , v.109 , 2021 https://doi.org/10.1016/j.neuron.2021.07.031 Citation Details
Ahmed, Mohsin and Priestley, James and Castro, Angel and Stefanini, Fabio and Balough, Elizabeth and Lavoie, Erin and Mazzucato, Luca and Fusi, Stefano and Losonczy, Attila "O18. Changes in Effective Hippocampal Network Coupling Mediate Learning and Memory of Associations Between Temporally Discontiguous Stimuli" Biological Psychiatry , v.83 , 2018 10.1016/j.biopsych.2018.02.304 Citation Details
Ahmed, Mohsin S. and Priestley, James B. and Castro, Angel and Stefanini, Fabio and Solis Canales, Ana Sofia and Balough, Elizabeth M. and Lavoie, Erin and Mazzucato, Luca and Fusi, Stefano and Losonczy, Attila "Hippocampal Network Reorganization Underlies the Formation of a Temporal Association Memory" Neuron , v.107 , 2020 10.1016/j.neuron.2020.04.013 Citation Details
Akitake, Bradley and Douglas, Hannah M. and LaFosse, Paul K. and Beiran, Manuel and Deveau, Ciana E. and ORawe, Jonathan and Li, Anna J. and Ryan, Lauren N. and Duffy, Samuel P. and Zhou, Zhishang and Deng, Yanting and Rajan, Kanaka and Histed, Mark H. "Amplified cortical neural responses as animals learn to use novel activity patterns" Current Biology , v.33 , 2023 https://doi.org/10.1016/j.cub.2023.04.032 Citation Details
Aso, Yoshinori and Ray, Robert P and Long, Xi and Bushey, Daniel and Cichewicz, Karol and Ngo, Teri-TB and Sharp, Brandi and Christoforou, Christina and Hu, Amy and Lemire, Andrew L and Tillberg, Paul and Hirsh, Jay and Litwin-Kumar, Ashok and Rubin, Gera "Nitric oxide acts as a cotransmitter in a subset of dopaminergic neurons to diversify memory dynamics" eLife , v.8 , 2019 10.7554/eLife.49257 Citation Details
(Showing: 1 - 10 of 137)

PROJECT OUTCOMES REPORT

Disclaimer

This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.

Researchers at the Columbia's NSF Neuronex Theory Hub use advanced methods of statistics, machine learning, computer simulation and mathematical modeling to advance our understanding of the neural circuits of the brain.  This work is carried out in collaboration with numerous experimental colleagues.  Work over the course of this grant has led to new tools for extracting useful data from various imaging and recording technologies, methods for finding informative structure in the resulting data, and models illuminated the workings of the neural circuits performing a variety of functions ranging from vision to memory and navigation.  The Columbia Theory Hub is committed to developing the next generation of researchers entering the field of theoretical neuroscience as well as training experimental neuroscientists in the use of the latest statistical and theoretical analysis methods through online resources and hosted workshops.  Research from the Theory Hub has shown that the way information is represented in the brain reflects an animal's abstraction of the rules of complex tasks; uncovered how the dynamics of neural activity in different motor regions of the brain generate and direct the appropriate sequence of muscle activities; revealed how neural circuits learn to predict the outcome of an action, clarified the role of different types of inhibitory neurons in circuits of the neocortex; advanced our understanding of how experiences form memories; and illuminated how neural activities directs navigation through an environment to a goal.


Last Modified: 07/28/2023
Modified by: Laurence F Abbott

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