A new paradigm in sport performance.
Cognitive preparation becomes measurable, trainable, and part of daily practice instead of staying a subjective routine.
The company building brain performance for movement.
Cirus brings BCI research, motor imagery protocols, non-invasive EEG, and sport validation into one measurable training loop.
Our storyTrain the movement before the body moves.
Cirus exists because athletes already train their mental preparation, but still lack an instrument that makes that work measurable, repeatable, and coachable.
Make EEG-guided cognitive training a standard tool.
Athletes and coaches should be able to train the mental rehearsal of movement with the same discipline they already apply to physical performance.
Bring motor imagery out of the lab.
Cirus turns guided motor imagery, non-invasive EEG, and progress feedback into simple, repeatable training protocols.
Origin
Five years of R&D across INRIA and the Paris Brain Institute shaped the Cirus approach.
Belief
Physical performance is already measured in detail. Cognitive preparation deserves the same rigour.
Ethics
Cirus reads brain signals and trains through feedback. It does not stimulate, diagnose, treat, or modify the brain.
Built by BCI researchers, made for the field.
The founding team connects brain-computer interface research, AI for neuroscience, and applied protocol design.
Turning EEG into useful training feedback.
The hard part is not reading EEG in a lab. The hard part is turning noisy, individual brain signals into useful feedback in a real training routine.
Signal quality
Capture usable EEG signals in conditions that are less controlled than a laboratory and more demanding than a demo.
Algorithmic robustness
Handle individual, noisy, session-to-session variation and turn it into feedback that can be compared over time.
Usable training experience
Make the session short, clear, non-invasive, and repeatable enough to enter a real athlete routine.
Motor imagery is measurable. Validation still matters.
Cirus builds from established motor imagery and EEG research, then validates protocols in sport and rehabilitation contexts before making strong product claims.
Our publications
- 2026
Feature Interpretability in Motor Imagery Brain Computer Interfaces: A Meta-Analysis Across Connectivity, Spatial Filtering, and Riemannian Methods
Juliana Gonzalez-Astudillo · Fabrizio de Vico Fallani
Brain Connectivity
- 2025
Medical Imaging AI Competitions Lack Fairness
Annika Reinke · Evangelia Christodoulou · Sthuthi Sadananda · A. Emre Kavur · Khrystyna Faryna · Daan Schouten · Bennett A. Landman · Carole Sudre · Olivier Colliot · Nick Heller · Sophie Loizillon · Martin Maška · Maëlys Solal · Arya Yazdan-Panah · Vilma Bozgo · Ömer Sümer · Siem de Jong · Sophie Fischer · Michal Kozubek · Tim Rädsch · Nadim Hammoud · Fruzsina Molnár-Gábor · Steven Hicks · Michael A. Riegler · Anindo Saha · Vajira Thambawita · Pal Halvorsen · Amelia Jiménez-Sánchez · Qingyang Yang · Veronika Cheplygina · Sabrina Bottazzi · Alexander Seitel · Spyridon Bakas · Alexandros Karargyris · Kiran Vaidhya Venkadesh · Bram van Ginneken · Lena Maier-Hein
arXiv
- 2025
Neural mechanisms of training in Brain-Computer Interface: A Biophysical modeling approach
Apurba Debnath · Tristan Venot · Marie-Constance Corsi · Parul Verma
bioRxiv
- 2024
Automatic quality control of segmentation results using early epochs as data augmentation: application to choroid plexuses
Arya Yazdan-Panah · Bruno Stankoff · Olivier Colliot
Medical Imaging 2024: Image Processing
- 2024
Intentional binding for noninvasive BCI control
Tristan Venot · Arthur Desbois · Marie-Constance Corsi · Laurent Hugueville · Ludovic Saint-Bauzel · Fabrizio de Vico Fallani
Journal of Neural Engineering
- 2024
HappyFeat—An interactive and efficient BCI framework for clinical applications
Arthur Desbois · Tristan Venot · Fabrizio de Vico Fallani · Marie-Constance Corsi
Software Impacts
- 2024
Dynamic brain networks in motor imagery-based BCI
Tristan Venot · Arthur Desbois · Fabrizio de Vico Fallani
Graz BCI Conference
- 2023
Automatic segmentation of the choroid plexuses: Method and validation in controls and patients with multiple sclerosis
Arya Yazdan-Panah · Marius Schmidt-Mengin · Vito A. G. Ricigliano · Théodore Soulier · Bruno Stankoff · Olivier Colliot
NeuroImage: Clinical
- 2022
EEG as signal on graph: a multilayer network model for BCI applications
Tiziana Cattai · Gaetano Scarano · Marie-Constance Corsi · Fabrizio de Vico Fallani · Stefania Colonnese
30th European Signal Processing Conference (EUSIPCO)
- 2021
Network-based brain–computer interfaces: principles and applications
Juliana Gonzalez-Astudillo · Tiziana Cattai · Giulia Bassignana · Marie-Constance Corsi · Fabrizio de Vico Fallani
Journal of Neural Engineering
- 2021
Phase/amplitude synchronization of brain signals during motor imagery BCI tasks
Tiziana Cattai · Stefania Colonnese · Marie-Constance Corsi · Danielle S. Bassett · Gaetano Scarano · Fabrizio de Vico Fallani
IEEE Transactions on Neural Systems and Rehabilitation Engineering
- 2019
Network neuroscience for optimizing brain–computer interfaces
Fabrizio de Vico Fallani · Danielle S. Bassett
Physics of Life Reviews
- 2014
Graph analysis of functional brain networks: practical issues in translational neuroscience
Fabrizio de Vico Fallani · Jonas Richiardi · Mario Chavez · Sophie Achard
Philosophical Transactions of the Royal Society B
- 2008
Cortical Network Dynamics during Foot Movements
Fabrizio de Vico Fallani · Laura Astolfi · Febo Cincotti · Donatella Mattia · Maria Grazia Marciani · Andrea Tocci · Serenella Salinari · Herbert Witte · Wolfram Hesse · Shangkai Gao · Alfredo Colosimo · Fabio Babiloni
Neuroinformatics