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Darshan Mandge edited this page Nov 1, 2024 · 5 revisions

Publications and Software Packages Using eFEL

Publications using eFEL

Alessio Paolo Buccino, Tanguy Damart, Julian Bartram, Darshan Mandge, Xiaohan Xue, Mickael Zbili, Tobias Gänswein, Aurélien Jaquier, Vishalini Emmenegger, Henry Markram, Andreas Hierlemann, and Werner Van Geit. A Multimodal Fitting Approach to Construct Single-Neuron Models With Patch Clamp and High-Density Microelectrode Arrays. Neural Computation, 36(7):1286–1331, June 2024. doi:10.1162/neco_a_01672.
Virág Takács, Zsuzsanna Bardóczi, Áron Orosz, Abel Major, Luca Tar, Péter Berki, Péter Papp, Márton I. Mayer, Hunor Sebők, Luca Zsolt, Katalin E. Sos, Szabolcs Káli, Tamás F. Freund, and Gábor Nyiri. Synaptic and dendritic architecture of different types of hippocampal somatostatin interneurons. PLOS Biology, 22(3):e3002539, March 2024. doi:10.1371/journal.pbio.3002539.
José Francis-Oliveira, Guilherme Shigueto Vilar Higa, Felipe José Costa Viana, Emily Cruvinel, Estevão Carlos-Lima, Fernando Da Silva Borges, Thais Tessari Zampieri, Fernanda Pereira Rebello, Henning Ulrich, and Roberto De Pasquale. TREK-1 inhibition promotes synaptic plasticity in the prelimbic cortex. Experimental Neurology, 373:114652, March 2024. doi:10.1016/j.expneurol.2023.114652.
Estevão Carlos-Lima, Guilherme Shigueto Vilar Higa, Felipe José Costa Viana, Alicia Moraes Tamais, Emily Cruvinel, Fernando Da Silva Borges, José Francis-Oliveira, Henning Ulrich, and Roberto De Pasquale. Serotonergic Modulation of the Excitation/Inhibition Balance in the Visual Cortex. International Journal of Molecular Sciences, 25(1):519, December 2023. doi:10.3390/ijms25010519.
Nadia Rosenberg, Maria Reva, Francesca Binda, Leonardo Restivo, Pauline Depierre, Julien Puyal, Marc Briquet, Yann Bernardinelli, Anne-Bérengère Rocher, Henry Markram, and Jean-Yves Chatton. Overexpression of \textsc UCP4 in astrocytic mitochondria prevents multilevel dysfunctions in a mouse model of Alzheimer's disease. Glia, 71(4):957–973, April 2023. doi:10.1002/glia.24317.
Alexandre Guet-McCreight, Homeira Moradi Chameh, Sara Mahallati, Margaret Wishart, Shreejoy J Tripathy, Taufik A Valiante, and Etay Hay. Age-dependent increased sag amplitude in human pyramidal neurons dampens baseline cortical activity. Cerebral Cortex, 33(8):4360–4373, April 2023. doi:10.1093/cercor/bhac348.
Guilherme Shigueto Vilar Higa, José Francis-Oliveira, Estevão Carlos-Lima, Alicia Moraes Tamais, Fernando Da Silva Borges, Alexandre Hiroaki Kihara, Ianê Carvalho Shieh, Henning Ulrich, Silvana Chiavegatto, and Roberto De Pasquale. 5-HT-dependent synaptic plasticity of the prefrontal cortex in postnatal development. Scientific Reports, 12(1):21015, December 2022. doi:10.1038/s41598-022-23767-9.
Anatoly Buchin, Rebecca De Frates, Anirban Nandi, Rusty Mann, Peter Chong, Lindsay Ng, Jeremy Miller, Rebecca Hodge, Brian Kalmbach, Soumita Bose, Ueli Rutishauser, Stephen McConoughey, Ed Lein, Jim Berg, Staci Sorensen, Ryder Gwinn, Christof Koch, Jonathan Ting, and Costas A. Anastassiou. Multi-modal characterization and simulation of human epileptic circuitry. Cell Reports, 41(13):111873, December 2022. doi:10.1016/j.celrep.2022.111873.
Shailesh Appukuttan and Andrew P. Davison. Reproducing and quantitatively validating a biologically-constrained point-neuron model of CA1 pyramidal cells. Frontiers in Integrative Neuroscience, 16:1041423, November 2022. doi:10.3389/fnint.2022.1041423.
Fernando S. Borges, Joao V. S. Moreira, Lavinia M. Takarabe, William W. Lytton, and Salvador Dura-Bernal. Large-scale biophysically detailed model of somatosensory thalamocortical circuits in NetPyNE. Frontiers in Neuroinformatics, 16:884245, September 2022. doi:10.3389/fninf.2022.884245.
Luca Leonardo Bologna, Roberto Smiriglia, Carmen Alina Lupascu, Shailesh Appukuttan, Andrew P. Davison, Genrich Ivaska, Jean-Denis Courcol, and Michele Migliore. The EBRAINS Hodgkin-Huxley Neuron Builder: An online resource for building data-driven neuron models. Frontiers in Neuroinformatics, 16:991609, September 2022. doi:10.3389/fninf.2022.991609.
Alexander Ladd, Kyung Geun Kim, Jan Balewski, Kristofer Bouchard, and Roy Ben-Shalom. Scaling and Benchmarking an Evolutionary Algorithm for Constructing Biophysical Neuronal Models. Frontiers in Neuroinformatics, 16:882552, June 2022. doi:10.3389/fninf.2022.882552.
Roy Ben-Shalom, Alexander Ladd, Nikhil S. Artherya, Christopher Cross, Kyung Geun Kim, Hersh Sanghevi, Alon Korngreen, Kristofer E. Bouchard, and Kevin J. Bender. NeuroGPU: Accelerating multi-compartment, biophysically detailed neuron simulations on GPUs. Journal of Neuroscience Methods, 366:109400, January 2022. doi:10.1016/j.jneumeth.2021.109400.
Luca L. Bologna, Roberto Smiriglia, Dario Curreri, and Michele Migliore. The EBRAINS NeuroFeatureExtract: An Online Resource for the Extraction of Neural Activity Features From Electrophysiological Data. Frontiers in Neuroinformatics, 15:713899, August 2021. doi:10.3389/fninf.2021.713899.
Matus Tomko, Lubica Benuskova, and Peter Jedlicka. A new reduced-morphology model for CA1 pyramidal cells and its validation and comparison with other models using HippoUnit. Scientific Reports, 11(1):7615, April 2021. doi:10.1038/s41598-021-87002-7.
Johanna Frost Nylén, Ilaria Carannante, Sten Grillner, and Jeanette Hellgren Kotaleski. Reciprocal interaction between striatal cholinergic and low-threshold spiking interneurons — A computational study. European Journal of Neuroscience, 53(7):2135–2148, April 2021. doi:10.1111/ejn.14854.
Martina Francesca Rizza, Francesca Locatelli, Stefano Masoli, Diana Sánchez-Ponce, Alberto Muñoz, Francesca Prestori, and Egidio D'Angelo. Stellate cell computational modeling predicts signal filtering in the molecular layer circuit of cerebellum. Scientific Reports, 11(1):3873, February 2021. doi:10.1038/s41598-021-83209-w.
Sára Sáray, Christian A. Rössert, Shailesh Appukuttan, Rosanna Migliore, Paola Vitale, Carmen A. Lupascu, Luca L. Bologna, Werner Van Geit, Armando Romani, Andrew P. Davison, Eilif Muller, Tamás F. Freund, and Szabolcs Káli. HippoUnit: A software tool for the automated testing and systematic comparison of detailed models of hippocampal neurons based on electrophysiological data. PLOS Computational Biology, 17(1):e1008114, January 2021. doi:10.1371/journal.pcbi.1008114.
Mate Mohacsi, Mark Patrik Torok, Sara Saray, and Szabolcs Kali. A unified framework for the application and evaluation of different methods for neural parameter optimization. In 2020 International Joint Conference on Neural Networks (IJCNN), 1–7. Glasgow, United Kingdom, July 2020. IEEE. doi:10.1109/IJCNN48605.2020.9206692.
Stefano Masoli, Marialuisa Tognolina, Umberto Laforenza, Francesco Moccia, and Egidio D'Angelo. Parameter tuning differentiates granule cell subtypes enriching transmission properties at the cerebellum input stage. Communications Biology, 3(1):222, May 2020. doi:10.1038/s42003-020-0953-x.
J. J. Johannes Hjorth, Alexander Kozlov, Ilaria Carannante, Johanna Frost Nylén, Robert Lindroos, Yvonne Johansson, Anna Tokarska, Matthijs C. Dorst, Shreyas M. Suryanarayana, Gilad Silberberg, Jeanette Hellgren Kotaleski, and Sten Grillner. The microcircuits of striatum in silico. Proceedings of the National Academy of Sciences, 117(17):9554–9565, April 2020. doi:10.1073/pnas.2000671117.
Mario Michiels. Electrophysiology prediction of single neurons based on their morphology. February 2020. doi:10.1101/2020.02.04.933697.
Alexander Bryson, Robert John Hatch, Bas-Jan Zandt, Christian Rossert, Samuel F. Berkovic, Christopher A. Reid, David B. Grayden, Sean L. Hill, and Steven Petrou. GABA-mediated tonic inhibition differentially modulates gain in functional subtypes of cortical interneurons. Proceedings of the National Academy of Sciences, 117(6):3192–3202, February 2020. doi:10.1073/pnas.1906369117.
Roy Ben-Shalom, Jan Balewski, Anand Siththaranjan, Vyassa Baratham, Henry Kyoung, Kyung Geun Kim, Kevin J. Bender, and Kristofer E. Bouchard. Inferring neuronal ionic conductances from membrane potentials using CNNs. August 2019. doi:10.1101/727974.
Elisabetta Iavarone, Jane Yi, Ying Shi, Bas-Jan Zandt, Christian O'Reilly, Werner Van Geit, Christian Rössert, Henry Markram, and Sean L. Hill. Experimentally-constrained biophysical models of tonic and burst firing modes in thalamocortical neurons. PLOS Computational Biology, 15(5):e1006753, May 2019. doi:10.1371/journal.pcbi.1006753.
Simen Tennøe, Geir Halnes, and Gaute T. Einevoll. Uncertainpy: A Python Toolbox for Uncertainty Quantification and Sensitivity Analysis in Computational Neuroscience. Frontiers in Neuroinformatics, 12:49, August 2018. doi:10.3389/fninf.2018.00049.

Software Packages

BluePyEModel: Electrical Neuron model building pipeline https://github.com/BlueBrain/BluePyEModel
BluePyOpt: Blue Brain Python Optimisation Library: https://github.com/BlueBrain/BluePyOpt
BluePyEfe: Blue Brain Python E-feature extraction: https://github.com/BlueBrain/BluePyEfe
Repository for Reva et al, 2023: https://github.com/BlueBrain/SSCxEModelExamples
Repository for Buccino et al., 2024: https://github.com/alejoe91/multimodalfitting
emodel-generalisation: Generalisation of electrical models of neurons with MCMC: https://github.com/BlueBrain/emodel-generalisation
psp-validation: Validation of Post Synaptic Potentials (PSPs): https://github.com/BlueBrain/psp-validation
bbp-workflow: Automated pipelines of batch jobs using Python and the Luigi framework. https://github.com/BlueBrain/bbp-workflow
uncertainty: Python toolbox for uncertainty quantification and sensitivity analysis, tailored towards computational neuroscience: https://github.com/simetenn/uncertainpy
Hippounit: validation tests for models of the hippocampus, based on the SciUnit framework and the NeuronUnit package: https://github.com/KaliLab/hippounit
neuroagent: LLM agent made to communicate with different neuroscience-related tools: https://github.com/BlueBrain/neuroagent
e-model-packager: Creates e-model packages from circuits: https://github.com/BlueBrain/e-model-packager
Scidash: enables the reproducible execution and visualization of data-driven unit test (SciUnit) for assessing model quality.: https://github.com/MetaCell/scidash
neuronunit: package for data-driven validation of neuron and ion channel models using SciUnit: https://github.com/scidash/neuronunit
CompNeuroPy: General package for computational neuroscience with ANNarchy https://github.com/Olimaol/CompNeuroPy
EModelRunner: Runs cells from stand-alone packages: https://github.com/BlueBrain/EModelRunner
arborize: Package that allows Arbor-like descriptions of cell models for NEURON: https://github.com/dbbs-lab/arborize
brian2modelfitting: Model fitting toolbox for the Brian 2 simulator: https://github.com/brian-team/brian2modelfitting
NESTNeuronUnit: NEST ADEXP single cell model optimizable via NeuronUnit and BluePyOpt: https://github.com/russelljjarvis/NESTNeuronUnit
SpikOpt: Multiobjective Optimization Tool for Neural Models: https://github.com/ForthePareto/SpikOpt
Neural-Model-Optimization-toolkit: https://github.com/ASquaredM/Neural-Model-Optimization-toolkit
neuroptimus-hippoUnit: Neuroptimus is a graphical tool for fitting the parameters of neuronal models: https://github.com/eslam69/neuroptimus-hippoUnit
Hodgkin-Huxley Neuron Builder web application integrated in the Human Brain Project - Brain Simulation Platform.: https://github.com/cnr-ibf-pa/hbp-bsp-hh-neuron-builder

Other Software Repositories Using eFEL

synaptic_platicity: Synaptic Plasticity Notebook https://github.com/lbologna/synaptic_platicity
Repository for Tomko et al. (2023): https://github.com/tomko-neuron/ETDP-CA1
Cerebellum Models: https://github.com/dbbs-lab/models
All cerebellum related models for running validation tests in CerebTests against experimental data in CerebData: https://github.com/cerebunit/cerebmodels
A library of CWL components for use in building neuroscience data analysis workflows: https://github.com/apdavison/ebrains-workflow-components
bbp-workflow launcher service: https://github.com/BlueBrain/bbp-workflow-svc
Package to construct models of songbird nucleus HVC: https://github.com/shivChitinous/songburst
Jupyter Notebooks for 2023 CAMBAM Workshop on Neuronal Excitability: https://github.com/nkoch1/CAMBAM_Workshop_Neuron_Excitability
Standardization updates to the axon research using NeuroGPU: https://github.com/coder2003lucky/axonstandardized_fork
STDP-Spike-Timing-Extraction : https://github.com/TheBigRedDog/STDP-Spike-Timing-Extraction
A sensitivity analysis on an extended infection model using UQpy: https://github.com/teobucci/computational-statistics
Neuzy (https://neuzy.de/) is a neuroscientific software framework to create a population of optimized single cell, multi compartment models: https://github.com/git-abra/Neuzy
streamlit interface for BioGPT model from Microsoft: https://github.com/Elsword016/BioGPT
NeuroGPU + BBP TTPC Example: https://github.com/ModelDBRepository/267384
Analyzing BERT on a large multi-class classification problem: https://github.com/mmmaurer/teamlab2022
BBP hippocampus-workshop 2022: https://github.com/BlueBrain/hippocampus-workshop
Linux bash scripts used to automate the installation of 'In-Silico Framework' using Python 2 and Python 3: https://github.com/mpinb/isf-installer
NeuroGPU EA Benchmarking: https://github.com/xanderladd/EA_benchmarking
NeuroGPU benchmarking examples:https://github.com/xanderladd/benchmarking_examples
A Spiking Neuron Model for Path Integration in the Bee Brain (MSc project): https://github.com/filippoferrari/CX_Path_Integration
SciUnit library for demonstrating data-driven testing of electrophysiological features extracted from computational models: https://github.com/appukuttan-shailesh/TestUnitTemplate
Reduced Model Optimization: https://github.com/russelljjarvis/ReducedModelOptimization
scidashopt with Docker on the CENTOS spike server: https://github.com/russelljjarvis/scidashopt
Framework for image and flow cytometry analysis (Docker): https://github.com/schienstockd/ceceliaDocker
Road Segmentation - Extract roads from satellite images: https://github.com/jinyangp/road_segmentation