Eliciting Naturalistic Cortical Responses with a Sensory Prosthesis via Optimized Microstimulation

Abstract

Objective. Lost sensations, such as touch, could one day be restored by electrical stimulation along the sensory neural pathways. Such stimulation, when informed by electronic sensors, could provide naturalistic cutaneous and proprioceptive feedback to the user. Perceptually, microstimulation of somatosensory brain regions produces localized, modality-specific sensations, and several spatiotemporal parameters have been studied for their discernibility. However, systematic methods for encoding a wide array of naturally occurring stimuli into biomimetic percepts via multi-channel microstimulation are lacking. More specifically, generating spatiotemporal patterns for explicitly evoking naturalistic neural activation has not yet been explored. Approach. We address this problem by first modeling the dynamical inputoutput relationship between multichannel microstimulation and downstream neural responses, and then optimizing the input pattern to reproduce naturally occurring touch responses as closely as possible. Main results. Here we show that such optimization produces responses in the S1 cortex of the anesthetized rat that are highly similar to natural, tactile-stimulus-evoked counterparts. Furthermore, information on both pressure and location of the touch stimulus was found to be highly preserved. Significance. Our results suggest that the currently presented stimulus optimization approach holds great promise for restoring naturalistic levels of sensation.

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Document Details

Document Type
Technical Report
Publication Date
Aug 12, 2016
Accession Number
AD1016734

Entities

People

  • Austin J. Brockmeier
  • David B Mcniel
  • John S Choi
  • Joseph T. Francis
  • José Príncipe
  • Lee M Von Kraus

Tags

Communities of Interest

  • Energy and Power Technologies
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Accuracy
  • Algorithms
  • Behavioral Sciences
  • Biomedical Engineering
  • Brain
  • Central Nervous System
  • Coding
  • Decoding
  • Dimensionality Reduction
  • Frequency
  • Information Science
  • Information Transfer
  • Machine Learning
  • Prostheses And Implants
  • Prosthetics
  • Two Dimensional
  • Waveforms

Fields of Study

  • Biology

Readers

  • Brain and Cognitive Science; Experimental Psychology; Cognitive Neuroscience
  • Operations Research
  • Vision Science/Vision Psychology/Cognitive Neuroscience.

Technology Areas

  • Biotechnology
  • Biotechnology - Cancer Biotech
  • Microelectronics
  • Microelectronics - Microelectromechanical Systems