publications | Giuseppe Chindemi

2026

eLife

Modeling and simulation of neocortical micro- and mesocircuitry. Part II: Physiology and experimentation

James B. Isbister, András Ecker, Christoph Pokorny, and 39 more authors

eLife, 2026

Cortical dynamics underlie many cognitive processes and emerge from complex multi-scale interactions, which are challenging to study in vivo. Large-scale, biophysically detailed models offer a tool which can complement laboratory approaches. We present a model comprising eight somatosensory cortex subregions, 4.2 million morphological and electrically-detailed neurons, and 13.2 billion local and mid-range synapses. In silico tools enabled reproduction and extension of complex laboratory experiments under a single parameterization, providing strong validation.

@article{isbisterModelingSimulationNeocortical2026,
  title = {Modeling and simulation of neocortical micro- and mesocircuitry. Part II: Physiology and experimentation},
  author = {Isbister, James B. and Ecker, András and Pokorny, Christoph and Bolaños-Puchet, Sirio and Santander, Daniela Egas and Arnaudon, Alexis and Awile, Omar and Barros-Zulaica, Natali and Alonso, Jorge Blanco and Boci, Elvis and Chindemi, Giuseppe and Courcol, Jean-Denis and Damart, Tanguy and Delemontex, Thomas and Dietz, Alexander and Ficarelli, Gianluca and Gevaert, Mike and Herttuainen, Joni and Ivaska, Genrich and Ji, Weina and Keller, Daniel and King, James and Kumbhar, Pramod and Lapere, Samuel and Litvak, Polina and Mandge, Darshan and Muller, Eilif B. and Pereira, Fernando and Planas, Judit and Ranjan, Rajnish and Reva, Maria and Romani, Armando and Rössert, Christian and Schürmann, Felix and Sood, Vishal and Teska, Aleksandra and Tuncel, Anil and Geit, Werner Van and Wolf, Matthias and Markram, Henry and Ramaswamy, Srikanth and Reimann, Michael W.},
  journal = {eLife},
  volume = {13},
  year = {2026},
  doi = {10.7554/eLife.99693.1},
  url = {https://doi.org/10.7554/eLife.99693.1},
}

2025

arXiv

From eye to AI: studying rodent social behavior in the era of machine learning

Giuseppe Chindemi, Camilla Bellone, and Benoit Girard

2025

Bib HTML

@misc{chindemi2025eyetoai,
  title = {From eye to AI: studying rodent social behavior in the era of machine learning},
  author = {Chindemi, Giuseppe and Bellone, Camilla and Girard, Benoit},
  year = {2025},
  archiveprefix = {arXiv},
  primaryclass = {q-bio.NC},
  url = {https://arxiv.org/abs/2508.04255},
}

eLife
Assemblies, synapse clustering and network topology interact with plasticity to explain structure-function relationships of the cortical connectome

András Ecker, Daniela Egas Santander, Marwan Abdellah, and 10 more authors

eLife, 2025

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Synaptic plasticity underlies the brain’s ability to learn and adapt. While experiments in brain slices have revealed mechanisms and protocols for the induction of plasticity between pairs of neurons, how these synaptic changes are coordinated in biological neuronal networks to ensure the emergence of learning remains poorly understood. Simulation and modeling have emerged as important tools to study learning in plastic networks, but have yet to achieve a scale that incorporates realistic network structure, active dendrites, and multi-synapse interactions, key determinants of synaptic plasticity. To rise to this challenge, we endowed an existing large-scale cortical network model, incorporating data-constrained dendritic processing and multi-synaptic connections, with a calcium-based model of functional plasticity that captures the diversity of excitatory connections extrapolated to in vivo-like conditions. This allowed us to study how dendrites and network structure interact with plasticity to shape stimulus representations at the microcircuit level.
@article{eckerAssembliesSynapseClustering2025, title = {Assemblies, synapse clustering and network topology interact with plasticity to explain structure-function relationships of the cortical connectome}, author = {Ecker, András and Santander, Daniela Egas and Abdellah, Marwan and Alonso, Jorge Blanco and Bolaños-Puchet, Sirio and Chindemi, Giuseppe and Mariyappan, Dhuruva Priyan Gowri and Isbister, James B. and King, James Gonzalo and Kumbhar, Pramod and Magkanaris, Ioannis and Muller, Eilif B. and Reimann, Michael W.}, journal = {eLife}, volume = {13}, year = {2025}, doi = {10.7554/eLife.101850.1}, url = {https://doi.org/10.7554/eLife.101850.1}, }

2023

arXiv

LISBET: a machine learning model for the automatic segmentation of social behavior motifs

Giuseppe Chindemi, Benoit Girard, and Camilla Bellone

2023

Bib HTML

@misc{chindemi2023lisbet,
  title = {LISBET: a machine learning model for the automatic segmentation of social behavior motifs},
  author = {Chindemi, Giuseppe and Girard, Benoit and Bellone, Camilla},
  year = {2023},
  archiveprefix = {arXiv},
  primaryclass = {cs.CV},
  url = {https://arxiv.org/abs/2311.04069},
}

2022

Nat. Commun.
A calcium-based plasticity model for predicting long-term potentiation and depression in the neocortex

Giuseppe Chindemi, Marwan Abdellah, Oren Amsalem, and 17 more authors

Nature Communications, 2022

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Pyramidal cells (PCs) form the backbone of the layered structure of the neocortex, and plasticity of their synapses is thought to underlie learning in the brain. However, such long-term synaptic changes have been experimentally characterized between only a few types of PCs, posing a significant barrier for studying neocortical learning mechanisms. Here we introduce a model of synaptic plasticity based on data-constrained postsynaptic calcium dynamics, and show in a neocortical microcircuit model that a single parameter set is sufficient to unify the available experimental findings on long-term potentiation (LTP) and long-term depression (LTD) of PC connections. In particular, we find that the diverse plasticity outcomes across the different PC types can be explained by cell-type-specific synaptic physiology, cell morphology and innervation patterns, without requiring type-specific plasticity. Generalizing the model to in vivo extracellular calcium concentrations, we predict qualitatively different plasticity dynamics from those observed in vitro. This work provides a first comprehensive null model for LTP/LTD between neocortical PC types in vivo, and an open framework for further developing models of cortical synaptic plasticity.
@article{chindemi_calcium-based_2022, title = {A calcium-based plasticity model for predicting long-term potentiation and depression in the neocortex}, author = {Chindemi, Giuseppe and Abdellah, Marwan and Amsalem, Oren and Benavides-Piccione, Ruth and Delattre, Vincent and Doron, Michael and Ecker, András and Jaquier, Aurélien T. and King, James and Kumbhar, Pramod and Monney, Caitlin and Perin, Rodrigo and Rössert, Christian and Tuncel, Anil M. and Van Geit, Werner and DeFelipe, Javier and Graupner, Michael and Segev, Idan and Markram, Henry and Muller, Eilif B.}, journal = {Nature Communications}, volume = {13}, number = {1}, pages = {3038}, year = {2022}, doi = {10.1038/s41467-022-30214-w}, url = {https://www.nature.com/articles/s41467-022-30214-w}, }

2019

Front. Syn. Neurosci.
Estimating the readily-releasable vesicle pool size at synaptic connections in the neocortex

Natalí Barros-Zulaica, John Rahmon, Giuseppe Chindemi, and 4 more authors

Frontiers in Synaptic Neuroscience, 2019

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Previous studies based on the ’Quantal Model’ for synaptic transmission suggested that neurotransmitter release is mediated by a single release site at individual synaptic contacts in the neocortex. However, recent studies seem to contradict this hypothesis and indicate that multi-vesicular release (MVR) could better explain the synaptic response variability observed in vitro. In this study we present a novel method to estimate the number of release sites per synapse, also known as the size of the readily-releasable pool (NRRP), from paired whole-cell recordings of layer 5 thick tufted pyramidal cell (L5_TTPC) connections in the somatosensory neocortex.
@article{barros-zulaica_estimating_2019, title = {Estimating the readily-releasable vesicle pool size at synaptic connections in the neocortex}, author = {Barros-Zulaica, Natalí and Rahmon, John and Chindemi, Giuseppe and Perin, Rodrigo and Markram, Henry and Muller, Eilif and Ramaswamy, Srikanth}, journal = {Frontiers in Synaptic Neuroscience}, volume = {11}, pages = {29}, year = {2019}, doi = {10.3389/fnsyn.2019.00029}, url = {https://www.frontiersin.org/articles/10.3389/fnsyn.2019.00029/full}, }

2017

Cell Rep.

Timed synaptic inhibition shapes NMDA spikes, influencing local dendritic processing and global I/O properties of cortical neurons

Michael Doron, Giuseppe Chindemi, Eilif Muller, and 2 more authors

Cell Reports, 2017

DOI Bib HTML

@article{doron_timed_2017,
  title = {Timed synaptic inhibition shapes NMDA spikes, influencing local dendritic processing and global I/O properties of cortical neurons},
  author = {Doron, Michael and Chindemi, Giuseppe and Muller, Eilif and Markram, Henry and Segev, Idan},
  journal = {Cell Reports},
  volume = {21},
  number = {6},
  pages = {1550--1561},
  year = {2017},
  doi = {10.1016/j.celrep.2017.10.035},
  url = {http://www.cell.com/cell-reports/abstract/S2211-1247(17)31467-5},
}

Front. Comput. Neurosci.
Cliques of neurons bound into cavities provide a missing link between structure and function

Michael W. Reimann, Max Nolte, Martina Scolamiero, and 7 more authors

Frontiers in Computational Neuroscience, 2017

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The lack of a formal link between neural network structure and its emergent function has hampered our understanding of how the brain processes information. We have now come closer to describing such a link by taking the direction of synaptic transmission into account, constructing graphs of a network that reflect the direction of information flow, and analyzing these directed graphs using algebraic topology. Applying this approach to a local network of neurons in the neocortex revealed a remarkably intricate and previously unseen topology of synaptic connectivity.
@article{reimann_cliques_2017, title = {Cliques of neurons bound into cavities provide a missing link between structure and function}, author = {Reimann, Michael W. and Nolte, Max and Scolamiero, Martina and Turner, Katharine and Perin, Rodrigo and Chindemi, Giuseppe and Dłotko, Paweł and Levi, Ran and Hess, Kathryn and Markram, Henry}, journal = {Frontiers in Computational Neuroscience}, volume = {11}, pages = {48}, year = {2017}, doi = {10.3389/fncom.2017.00048}, url = {https://www.frontiersin.org/articles/10.3389/fncom.2017.00048/full}, }

2016

Front. Neuroinform.
BluePyOpt: Leveraging open source software and cloud infrastructure to optimise model parameters in neuroscience

Werner Van Geit, Michael Gevaert, Giuseppe Chindemi, and 6 more authors

Frontiers in Neuroinformatics, 2016

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At many scales in neuroscience, appropriate mathematical models take the form of complex dynamical systems. Parametrising such models to conform to the multitude of available experimental constraints is a global nonlinear optimisation problem with a complex fitness landscape requiring numerical techniques to find suitable approximate solutions. Here we describe BluePyOpt, a Python package targeted at the broad neuroscience community to simplify this task.
@article{van_geit_bluepyopt_2016, title = {BluePyOpt: Leveraging open source software and cloud infrastructure to optimise model parameters in neuroscience}, author = {Van Geit, Werner and Gevaert, Michael and Chindemi, Giuseppe and Rössert, Christian and Courcol, Jean-Denis and Muller, Eilif B. and Schürmann, Felix and Segev, Idan and Markram, Henry}, journal = {Frontiers in Neuroinformatics}, volume = {10}, pages = {17}, year = {2016}, doi = {10.3389/fninf.2016.00017}, url = {https://www.frontiersin.org/articles/10.3389/fninf.2016.00017/full}, }

arXiv

Automated point-neuron simplification of data-driven microcircuit models

Christian Rössert, Christian Pozzorini, Giuseppe Chindemi, and 12 more authors

2016

Bib HTML

@misc{rossert_automated_2016,
  title = {Automated point-neuron simplification of data-driven microcircuit models},
  author = {Rössert, Christian and Pozzorini, Christian and Chindemi, Giuseppe and Davison, Andrew P. and Eroe, Csaba and King, James and Newton, Taylor H. and Nolte, Max and Ramaswamy, Srikanth and Reimann, Michael W. and Gewaltig, Marc-Oliver and Gerstner, Wulfram and Markram, Henry and Segev, Idan and Muller, Eilif},
  year = {2016},
  archiveprefix = {arXiv},
  primaryclass = {q-bio.NC},
  url = {https://arxiv.org/abs/1604.00087},
}

2015

Cell

Reconstruction and simulation of neocortical microcircuitry

Henry Markram, Eilif Muller, Srikanth Ramaswamy, and 79 more authors

Cell, 2015

Abs DOI Bib HTML

@article{markram_reconstruction_2015,
  title = {Reconstruction and simulation of neocortical microcircuitry},
  author = {Markram, Henry and Muller, Eilif and Ramaswamy, Srikanth and Reimann, Michael W. and Abdellah, Marwan and Sanchez, Carlos Aguado and Ailamaki, Anastasia and Alonso-Nanclares, Lidia and Antille, Nicolas and Arsever, Selim and Kahou, Guy Antoine Atenekeng and Berger, Thomas K. and Bilgili, Ahmet and Buncic, Nenad and Chalimourda, Athanassia and Chindemi, Giuseppe and Courcol, Jean-Denis and Delalondre, Fabien and Delattre, Vincent and Druckmann, Shaul and Dumusc, Raphael and Dynes, James and Eilemann, Stefan and Gal, Eyal and Gevaert, Michael Emiel and Ghobril, Jean-Pierre and Gidon, Albert and Graham, Joe W. and Gupta, Anirudh and Haenel, Valentin and Hay, Etay and Heinis, Thomas and Hernando, Juan B. and Hines, Michael and Kanari, Lida and Keller, Daniel and Kenyon, John and Khazen, Georges and Kim, Yihwa and King, James G. and Kisvarday, Zoltan and Kumbhar, Pramod and Lasserre, Sébastien and Le Bé, Jean-Vincent and Magalhães, Bruno R. C. and Merchán-Pérez, Angel and Meystre, Julie and Morrice, Benjamin Roy and Muller, Jeffrey and Muñoz-Céspedes, Alberto and Muralidhar, Shruti and Muthurasa, Keerthan and Nachbaur, Daniel and Newton, Taylor H. and Nolte, Max and Ovcharenko, Aleksandr and Palacios, Juan and Pastor, Luis and Perin, Rodrigo and Ranjan, Rajnish and Riachi, Imad and Rodríguez, José-Rodrigo and Riquelme, Juan Luis and Rössert, Christian and Sfyrakis, Konstantinos and Shi, Ying and Shillcock, Julian C. and Silberberg, Gilad and Silva, Ricardo and Tauheed, Farhan and Telefont, Martin and Toledo-Rodriguez, Maria and Tränkler, Thomas and Van Geit, Werner and Díaz, Jafet Villafranca and Walker, Richard and Wang, Yun and Zaninetta, Stefano M. and DeFelipe, Javier and Hill, Sean L. and Segev, Idan and Schürmann, Felix},
  journal = {Cell},
  volume = {163},
  number = {2},
  pages = {456--492},
  year = {2015},
  doi = {10.1016/j.cell.2015.09.029},
  url = {https://www.cell.com/cell/fulltext/S0092-8674(15)01191-5},
}

Front. Neural Circuits

The neocortical microcircuit collaboration portal: a resource for rat somatosensory cortex

Srikanth Ramaswamy, Jean-Denis Courcol, Marwan Abdellah, and 37 more authors

Frontiers in Neural Circuits, 2015

DOI Bib HTML

@article{ramaswamy_neocortical_2015,
  title = {The neocortical microcircuit collaboration portal: a resource for rat somatosensory cortex},
  author = {Ramaswamy, Srikanth and Courcol, Jean-Denis and Abdellah, Marwan and Adaszewski, Stanislaw R. and Antille, Nicolas and Arsever, Selim and Atenekeng, Guy and Bilgili, Ahmet and Brukau, Yury and Chalimourda, Athanassia and Chindemi, Giuseppe and Delalondre, Fabien and Dumusc, Raphael and Eilemann, Stefan and Gevaert, Michael Emiel and Gleeson, Padraig and Graham, Joe W. and Hernando, Juan B. and Kanari, Lida and Katkov, Yury and Keller, Daniel and King, James G. and Ranjan, Rajnish and Reimann, Michael W. and Rössert, Christian and Shi, Ying and Shillcock, Julian C. and Telefont, Martin and Van Geit, Werner and Villafranca Diaz, Jafet and Walker, Richard and Wang, Yun and Zaninetta, Stefano M. and DeFelipe, Javier and Hill, Sean L. and Muller, Jeffrey and Segev, Idan and Schürmann, Felix and Muller, Eilif B. and Markram, Henry},
  journal = {Frontiers in Neural Circuits},
  volume = {9},
  pages = {44},
  year = {2015},
  doi = {10.3389/fncir.2015.00044},
  url = {https://www.frontiersin.org/articles/10.3389/fncir.2015.00044/full},
}