2023-06-20: CONECT at the CENTURI summer school

2023-06-20 62:00

Title: Neural computation through population dynamics

Program in construction - you can already check the program of the summer school (June 20 - July 01, 2023) or directly access the detailed program.


Detecting precise spiking motifs in neurobiological data

Preliminary program

  • Monday, June 19 – Room 4 at CIELL (Hexagone building – 1st floor)
    • 14 – 16h : introduction par Rosa and Pierre
    • 16h-17h : group project presentation (in Hexagone auditorium)
  • Tuesday, June 20
    • 13h-14h15: group lunch at CROUS (booking in the small room)
  • Tuesday, June 20 to Thursday, June 29
    • Afternoon 14:30 - 17:00: group projects in Room 4 at CIELL
    • Room 4 at CIELL (Hexagone building- 1st floor)
  • Wednesday, June 28 and Thursday, June 29
    • Room 4 at CIELL (Hexagone building- 1st floor)
    • All day: Group projects in Institutes
  • Friday, June 30 – HEXAGONE AUDITORIUM
    • 09h30-12h: presentation of group projects
    • 12h-13h30 : group lunch – buffet in the HEXAGONE Hall
    • 13h30: end of the event


At any given instant, hundreds of billions of cells in our brains are lighting up in a complicated yet highly coordinated manner to give rise to our thoughts, percepts, and movements. A single neuron may be connected to thousands of other cells, sending out and receiving information through electrical impulses called spikes. From an engineering perspective, these spikes form a signal that may be viewed as a series of ones and zeros rapidly unfolding in time. Altogether, these signals reflect the ongoing computations taking place inside the nervous system, and as such, constitute a window into the brain’s inner workings. Recent advances in recording techniques have allowed experimenters to collect data from hundreds to thousands of neurons simultaneously while animals perform simple tasks. Dealing with such high-dimensional data poses important technical challenges that require elaborate methods for data mining and analysis. In this project, students will deal with datasets of increasing complexity and develop a set of analyses to extract meaningful information from the data.

Type of data

The folowing datasets will be shared by the teaching staff:


Data visualisation, neural decoding, principal component analysis, kinematic and geometric analyses of neural trajectories in high-dimensional space, hypothesis-testing, null distributions and statistics


Nicolas Meirhaeghe
Nicolas Meirhaeghe
Postdoctoral Fellow in Neuroscience

My research focuses on cortical dynamics in adaptive sensorimotor behavior.

Laurent U Perrinet
Laurent U Perrinet
Researcher in Computational Neuroscience

My research interests include Machine Learning and computational neuroscience applied to Vision.