Organizers: Michela Chiappalone , Valentina Pasquale and Pierre Yger
- Department of Neuroscience and Brain Technologies, Istituto Italiano di Tecnologia, Genova, Italy
- Institut de la Vision, INSERM, Paris, France
Duration: 2 days
Understanding how assemblies of neurons encode information requires recording large populations of cells in the brain. In recent years, progress in population calcium imaging and multichannel electrophysiology opened the possibility to record from hundreds or even thousands of neurons simultaneously. While these techniques offer unprecedented chances to monitor large neural circuits, they also push for the design of new algorithms to gather and process information from such high-dimensional datasets.
This two-day workshop will gather leading experimentalists and theoreticians to discuss latest computational methods and analyses used to process such large-scale neuronal population recordings, both in vivo and in vitro. Focusing on high-density electrophysiology and calcium imaging, it will review recent advances in neuroinformatics research, including spike sorting techniques and characterization of neural assemblies’ spatio-temporal activity. It will be a unique opportunity to address various questions such as:
• How to enhance the robustness of new algorithms identifying spikes, and/or design a proper validation framework ensuring the quality of the data?
• How to detect neural assemblies’ activity and correlations both in space and time, and possibly link them to sensory perception and behavior?
• What are the links, from a signal processing point of view, between calcium imaging and high density electrophysiology recordings?
First day [to be modified]
- Matthias Hennig (University of Edinburgh, Scotland), Spike sorting for large scale multielectrode arrays: efficient methods and lessons learnt
- Felix Franke (ETH Zurich, Switzerland)
- Nick Steinmetz (University College London, UK), Recording large, distributed neuronal populations with Neuropixels electrode arrays in behaving mice
- Yannick Bornat (IMS Bordeaux, France), Low latency hardware computing to use electrode array inputs in closed loop experiments
- Pierre Yger or Olivier Marre (Institut de la Vision, France), Towards online accurate spike sorting for thousands of channels
- Marius Pachitariu (University College London, UK), Kilosort and Suite2p: robust and scalable frameworks for neural activity extraction in large-scale recordings
- Thomas Deneux (UNIC, CNRS, France), Spike inference from calcium signals: MLspike algorithm and general perspectives
- Paolo Bonifazi (Ikerbasque, Bilbao, Spain), Sparse synchronizations and neuronal network failures: astrocytes replacement recovers global synchronizations in Atm-deficient cerebellar circuits in-vitro
Second day [to be modified]
- George Dimitriadis (Sainsbury Welcome Centre, UK), Understanding large-scale neural recordings: Ground truth data sets and the T-sne visualizations tool
- Gaute Einevoll (NMBU, Norway), Biophysical modeling of benchmarking data for validation of methods for analysing electrophysiological data
- Ulisse Ferrari (Institut de la Vision, France), Closed-loop estimation of retinal network sensitivity reveals signature of efficient coding
- Adrien Peyrache (McGill University, Canada)
- Sonja Grün (Forschungszentrum Jülich, Germany), Analysis of massively parallel spike data for higher-order correlations
- Valentina Pasquale (Istituto Italiano di Tecnologia, Italy), Measuring similarity of endogenous and evoked activity patterns in cultured cortical networks
- Stephen J. Eglen (University of Cambridge, UK), Detecting pairwise correlations in high-density recordings: open science in action
- Arno Onken (Istituto Italiano di Tecnologia, Italy), Matrix and tensor factorizations for analyzing neural population activity