Computational Neuroscience projet

CENTURI Summer school

https://conect-int.github.io/talk/2022-06-20-conect-at-the-centuri-summer-school/

Who are we?

Nicolas
Meirhaeghe		Laurent
Perrinet

Challenge: brain decoding

Objectives

  • Learn computational methods to interpret and interrogate neural data
  • Learn to reduce the complexity of high-dimensional neural data
  • Learn statistical approaches to perform hypothesis-testing on neural data
  • Learn the principles of decoding analyses to relate neural data to behavioral data

Datasets

  • Dataset 1: reaching task (Hatsopoulos et al., J. Neurophysiol., 2004)
  • Dataset 2: grasping task (Brochier et al., Sci. Data, 2018)
  • Dataset 3: time interval task (Meirhaeghe et al., Neuron, 2021)

Dataset 1: reaching task

Goal: decode intended arm movements from motor cortical activity

Hatsopoulos, Joshi, and O’Leary (2004) doi:10.1152/jn.01245.2003

Dataset 2: grasping task

Goal: predicting animals’ reaction times from neural preparatory activity

Brochier, Zehl, Hao, Duret, Sprenger, Denker, Grün, & Riehle (2018) Scientific Data 5 : 180055. doi:10.1038/sdata.2018.55

Dataset 3: time interval task

Goal: relating neural dynamics to animals’ behavioral performance

Meirhaeghe, Sohn, and Jazayeri (2021) doi:10.1016/j.neuron.2021.08.025

Questions?