Current position

• Associate Research Scientist, K99/R00 Scholar

  Center for Theoretical Neuroscience

  Zuckerman Institute, Columbia University 

  Jerome L Greene Science Center 3227 Broadway, New York, NY 10027

Education

• 2018 - Ph.D. in Statistical Physics

  École Normale Supérieure (Paris, FR)

  Dissertation title: Inference and modeling of biological networks: a statistical-physics approach to neural attractors and protein fitness landscapes.

• 2015 - M.S. International Master in Physics of Complex Systems 

  SISSA, ICTP, Politecnico di Torino, Sorbonne Universités, Université Paris-Saclay

  Final evaluation: 110/110 cum laude

• 2013 - B.S. Physics

  University of Bologna Alma Mater Studiorum

  Final evaluation: 110/110 cum laude

Academic Appointments

• 2024 - Columbia University, New York (NY), Associate Research Scientist

• 2020 - Columbia University, New York (NY), Postdoctoral Research Scientist

• 2019 - Institut Pasteur, Paris (France), Postdoctoral Researcher

Grants and Awards

• 2023 - NIMH: K99/R00 Transition to Independence Award (~1M$)

• 2019 - Org. for Computational Neuroscience: Travel Award

• 2015 - PSL Paris Sciences et Lettres: Doctoral fellowship (full funding for 3 years)

• 2014 - IDEX Paris Saclay: Excellence Grant International Master Student (10,000 €)

Preprints

• Rarely categorical, always high-dimensional: how the neural code changes along the cortical hierarchy

  L Posani*, S Wang*, SP Muscinelli, L Paninski, S Fusi

  BioRxiv preprint (2024) * indicates co-first author

  Featured in The Transmitter

• The representational geometry of emotional states in basolateral amygdala

  P.K. O'Neil*, L Posani*, J Meszaros, P Warren, C.E. Schoonover, A. Fink, S Fusi, C.D. Salzman

  BioRxiv preprint (2024) * indicates co-first author

• Prefrontal representations of retrospective spatial working memory in a rodent radial maze task

  JP Taliaferro, L Posani, J Greenwald, S Lim, JC McGowan, E Pekarskaya, C Lacefield, S Fusi, C Kellendonk

  BioRxiv preprint (2024)

• Impaired spatial coding and neuronal hyperactivity in the medial entorhinal cortex of APP-NL-G-F mice

  GA Rodriguez, EF Rothenberg, CO Shetler, A Aoun, L Posani, SV Vajram, T Tedesco, S Fusi, SA Hussaini

  BioRxiv preprint (2024)

Publications

• Tuned geometries of hippocampal representations meet the demands of social memory

  L Boyle*, L Posani*, S Irfan, SA Siegelbaum, S Fusi

  Neuron 112, no. 8 (2024): 1358-1371 * indicates co-first author

  Featured in Scientific American, Nature Rev. Neurosci. Highlights

• Functional effects of mutations in proteins can be predicted and interpreted by guided selection of sequence covariation information

  S Cocco, L Posani, R Monasson

  Proceedings of the National Academy of Sciences 121, no. 26 (2024): e2312335121.

• Transformation of spatial representations along hippocampal circuits

  B Gandit, L Posani, CL Zhang, S Saha, C Ortiz, M Allegra, C Schmidt-Hieber

  iScience, 27, no. 7 (2024)

• Infer global, predict local: quantity-quality trade-off in protein fitness predictions from sequence data

  L Posani, F Rizzato, R Monasson, S Cocco

  PLoS Computational Biology 19, no. 10 (2023): e1011521.

• Adolescent thalamic inhibition leads to long-lasting impairments in prefrontal cortex function

  L Benoit, E Holt, L Posani, S Fusi, A Harris, S Canetta, C Kellendonk

  Nature Neuroscience 25, no. 6 (2022): 714-725.

• A synaptic novelty signal to switch hippocampal attractor networks from generalization to discrimination 

  R Ocadiz-Gomez, M Trippa, L Posani, R Monasson, S Cocco, C Schmidt-Hieber

  Nature Communications 13, no. 1 (2022): 4122.

• Differential relation between neuronal and behavioral discrimination during hippocampal memory encoding 

  M Allegra, L Posani, R Ocasio-Gomez, C Schmidt-Hieber

  Neuron 108, no. 6 (2020): 1103-1112.

• Integration and multiplexing of positional and contextual information by the hippocampal network 

  L Posani, S Cocco, R Monasson

  PLoS Computational Biology 14, no. 8 (2018): e1006320.

• Functional connectivity models for decoding of spatial representations from CA1 recordings 

  L Posani, S Cocco, K Jezek, and R Monasson

  Journal of Computational Neuroscience 43, no. 1 (2017): 17-33.

• Statistical physics and representations in real and artificial neural networks 

  S Cocco, R Monasson, L Posani, S Rosay, and J Tubiana

  Physica A: Statistical Mechanics and its Applications 504 (2018): 45-76.

• Functional networks from inverse modeling of neural population activity 

  S Cocco, R Monasson, L Posani, and G Tavoni

  Current Opinion in Systems Biology 3 (2017): 103-110.

Software and tools

• Decodanda: A toolbox for decoding and geometrical analysis of neural activity with built-in best practices https://github.com/lposani/decodanda

Invited Talks

• 2025 Faculty Search Seminar, New York University, Center for Neural Sciences, New York (NY)

• 2025 Faculty Search Seminar, CNRS, CRCN National Competition, Sections 51, 54, Paris (FR)

• 2025 Faculty Search Seminar, INSERM, CRCN CSS4 National Competition, Paris (FR)

• 2025 Faculty Search Seminar, Icahn School of Medicine at Mount Sinai, Department of Neuroscience, New York (NY)

• 2025 Faculty Search Seminar, Yale University, Department of Neuroscience, New Haven (CT)

• 2025 - Group Meeting, Flatiron Institute, New York (NY)

• 2024 - Department Seminar, ICM Paris Brain Institute, Paris (FR)

• 2024 - Department Seminar, EPFL Lausanne (CH)

• 2024 - Department Seminar, Icahn School of Medicine at Mount Sinai (NY)

• 2023 - Group Meeting, GNT Group for Neural Theory, ENS, Paris (FR)

• 2023 - Group Meeting, IFM, Sorbonne Université, Paris (FR)

• 2023 - Department Seminar, QBio Institute, Paris Sciences et Lettres, Paris (FR)

• 2022 - Conference Seminar, Gatsby Foundation Tri-Center Meeting, HU Jerusalem (IL)

• 2022 - Group Meeting, Cedars-Sinai Medical Center & Caltech (virtual)

• 2019 - Center Seminar, Center for Theoretical Neuroscience, Columbia University (NY)

• 2019 - Center Seminar, Donders Institute for Brain, Cognition and Behaviour, Radboud Univ. (NL)

• 2018 - Conference Seminar, ICTP Spring College, ICTP, Trieste (IT)

Conference Talks and Presentations

• 2025 - Poster Presentation, COSYNE 25, Montreal (CA)

• 2024 - Poster Presentation, SfN 2024, Chicago, IL

• 2024 - Poster Presentation, AREADNE 24, Milos (GR)

• 2024 - Poster Presentation, COSYNE 24, Computational and Systems Neuroscience, Lisbon (PT)

• 2023 - Poster Presentation, SfN 2023, Washington, D.C.

• 2023 - Selected Talk, NeuralNet 2023, Marseille (FR)

• 2023 - Poster Presentation, Bernstein Conference 2023, Berlin (GE)

• 2023 - Poster Presentation, COSYNE 23, Computational and Systems Neuroscience, Montreal (CA)

• 2022 - Poster Presentation, COSYNE 22, Computational and Systems Neuroscience, Lisbon (PT)

• 2019 - Poster Presentation, CNS 2019, OCNS 28th Computational Neuroscience Meeting, Barcelona (ES)

• 2018 - Selected Talk, TEX2018 M-GATE, SISSA, Trieste (IT)

• 2017 - Selected Talk, CNS 2017, OCNS 26th Computational Neuroscience Meeting, Antwerp (BE)

• 2016 - Selected Talk, Multi-scale Integration in Biological Systems, Paris (FR)

• 2016 - Selected Talk, Statistical Physics Methods in Biology and Computer Science, Paris (FR)

• 2016 - Poster Presentation, Co-evolution in proteins and RNA, Cargese (FR)

Service and Organization

• 2023 - Mentor, COSYNE 2024 Mentoring Forum

• 2023 - Workshop organizer, COSYNE 2023 Montreal: "Are neurons interpretable?"

• 2023 - Organizer, ZIPS Zuckerman Institute Post Doc Seminar series, Columbia University, New York (NY)

• 2022 - Workshop organizer, COSYNE 2022 Lisbon: "Is geometry all you need?"

• 2022 - Organizer, CTN Theory Center Seminar series, Columbia University, New York (NY)

• Reviewer: COSYNE, PLOS Computational Biology, Journal of Computational Neuroscience

Teaching

• 2024 - Teacher, Advanced Topics in Theoretical Neuroscience, Columbia University, New York (NY)

  Topics: Geometrical analysis of neural representations

• 2022 - Teacher, Advanced Topics in Theoretical Neuroscience, Columbia University, New York (NY)

  Topics: Computational methods for neural decoding and representational geometry

• 2018 - Teacher, Master course in Theoretical Systems Biology, École normale supérieure, Paris (FR) 

  Topics: Python programming and data analysis tools for quantitative biology

Non-academic Experience

• 2019 - current Cubbit, Co-founder and Scientific Advisor

• 2016 - 2019  Cubbit, Co-founder and Chief Scientist