Patterned wireless transcranial optogenetics generates artificial perception

Area of Science:

• Neuroscience
• Biomedical Engineering
• Optogenetics

Background:

• Developing brain-machine interfaces (BMIs) requires creating artificial neural inputs without relying on traditional sensory pathways.
• A key challenge is establishing stable, minimally invasive, and wirelessly controlled platforms for artificial perceptual feedback.

Purpose of the Study:

• To demonstrate a miniaturized, implantable transcranial optogenetic neural stimulator for real-time, wireless patterning of cortical ensembles.
• To investigate the feasibility of generating artificial perceptions via direct neural stimulation.

Main Methods:

• Designed and validated a miniaturized, fully implantable transcranial optogenetic neural stimulator.
• Utilized experimentally validated numerical simulations for light and heat propagation analysis.
• Assessed neuronal responses through in vivo electrophysiology and molecular methods.
• Conducted cue discrimination tasks during operant learning in mice.

Main Results:

• Successfully demonstrated the wireless generation of artificial percepts perceived by mice.
• Showcased that spatial distance and sequential order in cortical networks predict discrimination performance.
• Validated the stimulator's efficacy in eliciting measurable neuronal responses and behavioral outcomes.

Conclusions:

• This study presents a significant advance in all-optical brain-machine communication by enabling wireless, real-time artificial perception generation.
• The developed technology expands the understanding of artificially patterned neural activity and its perception.
• These findings pave the way for next-generation BMIs capable of mediating artificial perceptual feedback.