PI: Makse, Hernan (CCNY) and Zimmer, Manuel (Vienna)
Email: hmakse@ccny.cuny.edu
Institution: City College of New York and University of Vienna
Title: Application of the principle of symmetry to neural circuitry: from building blocks to neural synchronization in the connectome
Grant #: EB028157
Status: Start September 8, 2020
Deliverables:
We are building algorithms to obtain the functional building blocks of connectomes and other biological networks based on symmetries and graph fibrations.
Tools to calculate the building blocks of the connectome (and other biological networks) are available at:
https://github.com/makselab/fibrationSymmetries
https://github.com/makselab/PseudoBalancedColoring
https://github.com/makselab/FastFibration
https://github.com/makselab/LIP_Random_Networks
Tools to find and build quasi-fibration symmetries of graphs can be found at:
https://github.com/makselab/QuasiFibrations
Tools to calculate functional brain networks from fMRI images are available at:
A Matlab application to simulate the locomotive neural network of the C. elegans can be found at:
https://github.com/makselab/C.-elegans_locomotive_simulator
Link to Data/Model Reuse abstract, [Link]
Presentations:
2023 Brain Initiative
Poster Title: Fibration symmetries reveal neural synchronizations in the C. elegans connectome
Poster Number: 403
Presenter: Bryant Avila (CCNY, PhD candidate)
Link to Poster:
2022 Brain Initiative
Poster Title: From symmetric building blocks to neural synchronization in the connectome
Poster Number: 403
Presenter: Bryant Avila (CCNY, PhD student) & Pedro Augusto (Vienna, PhD student)
Link to Poster:
2021 Brain PI Meeting
Poster Title: Symmetries and synchronization in the connectome
Poster Number: 4050
Presenter: Hernan Makse
Link to Poster:
Publications:
[1] B. Avila, M. Serafino, P. Augusto, M. Zimmer, H.A. Makse. Fibration symmetries and cluster synchronization in the Caenorhabditis elegans connectome. Arxiv (q-bio), [Link] (2023)
[2] I. Leifer, D. Phillips, F. Sorrentino, H. A. Makse. Symmetry-driven network reconstruction through pseudobalanced coloring optimization. Journal of Statistical Mechanics: Theory and Experiment. 2022 Jul 15; 2022(7):073403. OSF, GitHub [Link] (2022)
[3 ]H. S. Monteiro, I. Leifer, S. D. S. Reis, J. S. Andrade Jr., H. A. Makse. Fast algorithm to identify cluster synchrony through fibration symmetries in large information-processing networks. Chaos 32, 033120 [Link] (2022)
[4] P. Boldi, I. Leifer, H. A. Makse. Quasifibrations of Graphs to Find Symmetries in Biological Networks. Journal of Statistical Mechanics: Theory and Experiment 2022, no. 11 (2022): 113401. OSF, GitHub, arxiv. [Link] (2022)
[5] H. S. Monteiro, I. Leifer, S. D. S. Reis, J. S. Andrade Jr., H. A. Makse. Fast algorithm to identify cluster synchrony through fibration symmetries in large information-processing networks. Chaos 32, 033120 [Link] (2022)
[6] I. Leifer, M. Sanchez-Perez, C. Ishida, H.A. Makse. Predicting synchronized gene coexpression patterns from fibration symmetries in gene regulatory networks in bacteria. BMC Bioinformatics volume 22, Article number: 363 [Link] (2021)
[7] F. Morone, I. Leifer, H.A. Makse. Fibration symmetries uncover the building blocks of biological networks Proc. Nat. Acad. Sci. USA. 117 (15) 8306-8314, April 14, 2020. SI, Structure of all fibers SI. OSF, GitHub [Link] (2020)
[8] Ian Leifer, Flaviano Morone, Saulo DS Reis, Jose S Andrade Jr, Mariano Sigman, and Hernan A Makse. Circuits with broken fibration symmetries perform core logic computations in biological networks. PLoS computational biology, 16(6):e1007776, [Link] (2020)
[9] Flaviano Morone and Hernan A Makse. Symmetry group factorization reveals the structure-function relation in the neural connectome of caenorhabditis elegans. Nature communications, 10(1):1–13, [Link] (2019)