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<p>The brain coordinates multiple parallel motor programs, ensuring synergy and preventing interference during movements. Yet, performance often degrades when brain–machine interfaces are used during concurrent tasks or ongoing movements. We suggest that latent neural representations may represent a strategy to solve this issue. In this study, we addressed this question using neural signals from a tetraplegic individual with partial residual motor function, implanted with a wireless epidural electrocorticography (ECoG) device. By adapting dimensionality reduction techniques, we found that motor execution and motor imagery span partially overlapping subspaces in mesoscale neural signals, shaped by specific frequency band contributions. Despite substantial shared variance, we show that identifying orthogonal, condition-specific dimensions enables successful decoding of executed and imagined movements, even when performed simultaneously. These findings show that ECoG signals can expose separable neural subspaces, allowing executed and imagined actions to be harnessed independently and in concert. This opens a promising avenue to develop brain–machine interfaces that can simultaneously control multiple external devices or operate alongside natural movements.</p>

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Decoupling simultaneous motor imagination and execution via orthogonal ECoG neural representations

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年3月31日

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  • Leonardo Pollina,
  • Lucas Struber,
  • Valeria de Seta,
  • Eleonora Russo,
  • Serpil Karakas,
  • Stephan Chabardes,
  • Tetiana Aksenova,
  • Guillaume Charvet,
  • Solaiman Shokur,
  • Silvestro Micera

摘要

The brain coordinates multiple parallel motor programs, ensuring synergy and preventing interference during movements. Yet, performance often degrades when brain–machine interfaces are used during concurrent tasks or ongoing movements. We suggest that latent neural representations may represent a strategy to solve this issue. In this study, we addressed this question using neural signals from a tetraplegic individual with partial residual motor function, implanted with a wireless epidural electrocorticography (ECoG) device. By adapting dimensionality reduction techniques, we found that motor execution and motor imagery span partially overlapping subspaces in mesoscale neural signals, shaped by specific frequency band contributions. Despite substantial shared variance, we show that identifying orthogonal, condition-specific dimensions enables successful decoding of executed and imagined movements, even when performed simultaneously. These findings show that ECoG signals can expose separable neural subspaces, allowing executed and imagined actions to be harnessed independently and in concert. This opens a promising avenue to develop brain–machine interfaces that can simultaneously control multiple external devices or operate alongside natural movements.