🧠 What if your brain could realize it made a mistake before anyone else notices? Can a brain-computer interface (BCI) detect when you're going off track—and correct itself in real time?

In this compelling episode of Neurocareers: Doing the Impossible!, we sit down with Camille Gontier, PhD, to explore his BCI Award–nominated project: Endogenous modifications in M1 activity allow online error detection and correction in human BCI, developed at the Rehab Neural Engineering Labs, University of Pittsburgh.

Camille shares how his team used intracortical recordings from the primary motor cortex (M1) to decode internal error signals—enabling a BCI system to slow down or stop unintended movements before they fully unfold. Discover how this real-time, feedback-free correction method could revolutionize precision in BCI applications, from neuroprosthetics to assistive technologies.

🔍 We dive into:

• How error detection works at the neural level—even before a mistake happens

• The design and implementation of a real-time error-sensing system

• What makes this work a translational leap in human BCI research

• Why this approach is especially powerful for tasks requiring high accuracy

But this episode goes beyond the tech.

Camille also shares:

• 💼 His unconventional path—from space engineering at Airbus to closed-loop neurotech

• 📚 His best advice for aspiring BCI researchers (hint: start with math and physics)

• 🏆 Tips on preparing a BCI Award submission—and why it’s worth doing even if you don’t win

Whether you're a student, a researcher, or just fascinated by the future of brain-machine interfaces, this episode is packed with insight, humility, and innovation.

🎧 Listen now to learn how the brain knows it’s wrong—and how that knowledge is reshaping BCI performance.

📍 Find this and other episodes at 🔗 www.neuroapproaches.org/podcast 🎧 Also on Apple Podcasts, Spotify, YouTube, and all major platforms.

#BCI #BrainComputerInterface #Neurotech #CamilleGontier #Neurocareers #NeuralDecoding #IntracorticalBCI #ErrorDetection #BCIAward #Neuroscience #BrainTech #MotorCortex #AssistiveTech #Neuroengineering