Eliciting naturalistic cortical responses with a sensory prosthesis via optimized microstimulation

Area of Science:

• Neuroscience
• Biomedical Engineering
• Sensory Feedback Systems

Background:

• Restoring lost sensations, such as touch, is a significant challenge in neuroprosthetics.
• Electrical stimulation of sensory neural pathways offers a potential solution for providing cutaneous and proprioceptive feedback.
• Current methods lack systematic approaches for encoding natural stimuli into biomimetic percepts via multi-channel microstimulation.

Purpose of the Study:

• To develop and validate a method for generating biomimetic percepts through optimized multi-channel microstimulation.
• To create spatiotemporal stimulation patterns that evoke naturalistic neural activation mirroring natural touch.

Main Methods:

• Modeling the dynamical input-output relationship between multichannel microstimulation and neural responses.
• Optimizing microstimulation input patterns to replicate natural touch-evoked neural activity.
• Utilizing an anesthetized rat model with S1 cortex recordings.

Main Results:

• Optimized microstimulation patterns elicited neural responses in the S1 cortex highly similar to natural tactile stimuli.
• The approach successfully preserved information regarding both the pressure and location of the simulated touch.
• Demonstrated the feasibility of generating naturalistic neural activation patterns.

Conclusions:

• The developed stimulus optimization approach shows significant promise for restoring naturalistic sensory feedback.
• This method could advance the field of neuroprosthetics and sensory restoration.
• Further research can build upon this technique to improve artificial sensation for users.