Volitional control of a recurrent brain computer interface via covert reinforcement of endogenous reward networks
- 1Washington University in St. Louis School of Medicine
Abstract
Recurrent brain-computer interfaces (rBCIs) deliver targeted stimulation to one brain region based on neural activity recorded and processed in real-time at another. In a volitionally controlled rBCI, the user must also learn to intentionally produce the triggering neural activity, a process typically facilitated by an external reward. However, reliance on an external reward introduces a delay between the triggering event and reinforcement that can slow association between the two and, ultimately, control of the rBCI (particularly for neural activity not directly related to an observable behavior such as a goal-directed movement). The constraint to an external reward also limits studies of neural dynamics during natural, free behavior. In contrast, delivering activity-dependent stimulation directly to the brain's own reward centers - i.e., covert reinforcement - would bypass the need for external feedback, enabling precise temporal coupling between triggering events and reward and allowing for unrestrained rBCI use. Here, we show that rats can gain volitional control of an rBCI using activity-dependent electrical stimulation of the medial forebrain bundle as a sole reinforcer. Animals successfully learned to modulate motor unit discharge rates as well as specific electrocorticographic frequency bands (beta and gamma) to self-trigger stimulation. Furthermore, rats demonstrated flexible control by independently modulating distinct spectral features from the same cortical site. These findings suggest that covert reinforcement of endogenous reward networks can drive operant conditioning of specific neural signals during unrestrained behavior, opening new avenues for adaptive BCIs and closed-loop psychiatric therapies.
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BibTeX
@misc{mcpherson2026volitional,
title = {{Volitional control of a recurrent brain computer interface via covert reinforcement of endogenous reward networks}},
author = {J. G. McPherson and R. R. Miller and E. E. Fetz and S. I. Perlmutter},
howpublished = {bioRxiv},
year = {2026},
month = oct,
doi = {10.64898/2026.10.01.755922},
url = {https://www.biorxiv.org/content/10.64898/2026.10.01.755922v1},
note = {CC BY-NC-ND},
}
RIS
TY - UNPB
TI - Volitional control of a recurrent brain computer interface via covert reinforcement of endogenous reward networks
AU - J. G. McPherson
AU - R. R. Miller
AU - E. E. Fetz
AU - S. I. Perlmutter
PY - 2026
DA - 2026/10/01
PB - bioRxiv
DO - 10.64898/2026.10.01.755922
UR - https://www.biorxiv.org/content/10.64898/2026.10.01.755922v1
AB - Recurrent brain-computer interfaces (rBCIs) deliver targeted stimulation to one brain region based on neural activity recorded and processed in real-time at another. In a volitionally controlled rBCI, the user must also learn to intentionally produce the triggering neural activity, a process typically facilitated by an external reward. However, reliance on an external reward introduces a delay between the triggering event and reinforcement that can slow association between the two and, ultimately, control of the rBCI (particularly for neural activity not directly related to an observable behavior such as a goal-directed movement). The constraint to an external reward also limits studies of neural dynamics during natural, free behavior. In contrast, delivering activity-dependent stimulation directly to the brain's own reward centers - i.e., covert reinforcement - would bypass the need for external feedback, enabling precise temporal coupling between triggering events and reward and allowing for unrestrained rBCI use. Here, we show that rats can gain volitional control of an rBCI using activity-dependent electrical stimulation of the medial forebrain bundle as a sole reinforcer. Animals successfully learned to modulate motor unit discharge rates as well as specific electrocorticographic frequency bands (beta and gamma) to self-trigger stimulation. Furthermore, rats demonstrated flexible control by independently modulating distinct spectral features from the same cortical site. These findings suggest that covert reinforcement of endogenous reward networks can drive operant conditioning of specific neural signals during unrestrained behavior, opening new avenues for adaptive BCIs and closed-loop psychiatric therapies.
ER -