Neural representations of speech

How are speech features represented and combined in the brain to form a unified representation of meaning? Our research work seek to uncover the neural correlates of these representations, and the dynamical mechanisms by which they are transformed and integrated.

Key publications:

  • Imagined speech can be decoded from low- and cross-frequency intracranial EEG features.

Modeling neural manifolds

Neurons collectively and dynamically encode sensory and cognitive processes. We study the dynamical mechanisms by which network of neurons represent information in latent low-dimensional spaces.

Key publications:

  • Misinterpreting the horseshoe effect in neuroscience.

Epileptic seizure forecasting

Developing reliable methods to predicts seizures holds immense potential to improve the quality of life of patients with epilepsy. This field has recently quickly progressed thanks to the possibility of recording intracranial EEG human data over the course of several years. Our research work leverage those long-term datasets to forecast seizures at short (minutes to hours) and long (days) time horizons

Key publications:

  • Forecasting seizure risk in adults with focal epilepsy: a development and validation study.
  • Seizure forecasting: bifurcations in the long and winding road.
  • Chance and risk in epilepsy.
  • crowd-sourcing reproductible seizure prediction with long-term intracranial EEG.
  • Human focal seizures can be predicted from multiunit spiking activity away from epileptic onset zones.



Epileptic seizure modeling

Seizures are characterized by synchronous activity of a large number of connected neurons. In order to control and abate seizures, it is critical to better understand the mechanisms of seizure synchronization across complex networks. Our research works attempts to model the dynamical principles of seizure propagation across the brain, both at the spatial scale of brain regions and local spatial scales (a few millimeters). This research led to the development of individualized approaches based on seizure propagation patterns to help identify candidate brain areas for surgical resection.

Key publications:

  • Predicting the spatiotemporal diversity of seizure propagation and termination in human focal epilepsy.
  • Individual brain structure and modeling predict seizure propagation.
  • The virtual epileptic patient: individualized whole-brain models of epilepsy spread.
  • Permittivity coupling across brain regions determines seizure recruitment in partial epilepsy.