Marie-Constance Corsi

Marie-Constance Corsi

Research scientist

NERV Lab

Inria Paris

Paris Brain Institute

About me

I am an Inria research scientist at Paris Brain Institute in the NERV Lab.

My research currently focuses on the development of tools to address the “Brain-Computer Interface (BCI) inefficiency” issue, reflected by a non-negligible portion of users who cannot control the device even after several training sessions. I essentially consider two main approaches: the search for neurophysiological markers of BCI training and the integration of multimodal data to enrich the information provided to the classifier.

I previously served as secretary general of the French academic association promoting the advances in BCI, called CORTICO, and as co-chair of the Postdocs and Students Committee of the BCI Society.

You can download my CV in pdf.

Don’t hesitate to contact me if you want any additional information or if you are interested by a research collaboration!

Interests

  • Closed-loop systems (Brain-Computer Interfaces & Neurofeedback)
  • Linear and non-linear functional connectivity
  • Multimodal integration
  • Machine learning
  • Biomedical instrumentation

Education

  • PhD in Biomedical instrumentation, 2015

    CEA-LETI (Grenoble, France)

  • MSc in Neuropsychology and Clinical Neurosciences, 2015

    Grenoble Alpes University

  • MEng in Information and Communications Technology for Health, 2012

    IMT Atlantique (Brest, France)

Recent & Upcoming Talks

News

Cutting Gardens, here we go!

Truely happy to have taken part of the organization of the CuttingGardens, a multi-hub meeting on EEG and MEG methods! I have notably animated a session dedicated to the use of BCI with 3 insightful talks given by R. Kobler, M. Tangermann, and T. Vaughan. All the materials (and many other features!) are available in the dedicated github page

Projects

Neurophysiological markers of longitudinal processes

Functional connectivity and brain network reorganization underlying longitudinal processes, mainly BCI training

Improving neural decoders

Development of methods to enhance subjets’ mental state classification. They can be divided in two main approaches: the integration of multimodal information and the search for alternative features

Helium 4 optically-pumped magnetometers

Development of cryogenic-free sensors for magnetocardiography and magnetoencephalography

Recent Publications

Quickly discover relevant content by filtering publications.

Measuring Neuronal Avalanches to inform Brain-Computer Interfaces

Large-scale interactions among multiple brain regions manifest as bursts of activations called neuronal avalanches, which reconfigure …
Measuring Neuronal Avalanches to inform Brain-Computer Interfaces

Intentional binding enhances hybrid BCI control

Mental imagery-based brain-computer interfaces (BCIs) allow to interact with the external environment by naturally bypassing the …

Brain fingerprint is based on the aperiodic, scale-free, neuronal activity

Subject differentiation bears the possibility to individualize brain analyses. However, the nature of the processes generating …

Contact