Improving Target Tracking by Enhancing Neural Synchrony

Abstract

Approved for public release The ability to simultaneously track multiple targets is critical to the success of many tasks and missi,ons. But a curious and important divide impacts target tracking. The right and left sides of vision (hemifields) are processed separ,ately and independently, by the left vs right cerebral cortices (hemispheres) respectively. This means that targets must be handed o,ff between the hemispheres as the targets pass from one hemifield to the other. That is, rather than being a single tracking system,, the brain has two separate mechanisms that must frequently collaborate to produce a seemingly unified experience of tracking across, the visual field. The problem is that these handoffs come at a cost for successful performance. Tracking accuracy decreases when a,target crosses hemifields. This project aims to characterize and understand this fundamental collaboration between the hemispheres.,We aim to improve target tracking by electrical augmentation of the neural mechanisms that handoff targets between the hemispheres.,Our overarching goal is a non-invasive device that could enable military personnel to become super target trackers. We will do so,by employing cutting-edge technology: An ultra-fast closed-loop electrical brain stimulation developed by our lab. Closed-loop mea,ns reading from, and matching stimulation to, the brains own rhythms/oscillations. This will allow us to boost the neural rhythms, that handoff targets between the hemispheres. This can protect against the loss of target information, thereby improving tracking p,erformance. We will conduct parallel studies in non-human primates (NHPs) and humans performing a multiple-target tracking task. We,will apply multivariate analytics and machine learning techniques to data collected from intracranial multiple-electrode recordings,in the NHPs and EEG recordings from the humans. From this, we will identify the cortical areas and neural dynamics that support targ,et tracking. This, in turn, will allow us to derive the closed-loop stimulation parameters that could improve tracking performance. ,The understanding of neural mechanisms for target tracking and their causal manipulation could dramatically enhance the design, func,tion, and performance of ONR operators and systems that track targets across a range of different contexts including combat conditio,ns as well as supply systems, traffic control, etc. An understanding of how to enhance the neural mechanisms that handoff targets be,tween the hemispheres can lead directly to non-invasive electrical stimulation for enhancing multiple target tracking in humans. Thi,s would mean more accurate tracking of target trajectories and avoidance of target loss due to human error and limitations.

Document Details

Document Type
DoD Grant Award
Publication Date
Jul 08, 2022
Source ID
N000142212453

Entities

People

  • Earl K. Miller

Organizations

  • Massachusetts Institute of Technology
  • Office of Naval Research
  • United States Navy

Tags

Readers

  • Distributed Systems and Data Platform Development
  • Sensor Fusion and Tracking Systems.
  • Vision Science/Vision Psychology/Cognitive Neuroscience.

Technology Areas

  • AI & ML
  • AI & ML - Neural Networks