Estimation of Locomotion States of a Rat by Neural Signals from the Motor Cortices Based on a Linear Correlation Model

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  • Fukayama Osamu
    Graduate School of Information Science and Technology, The University of Tokyo
  • Taniguchi Noriyuki
    Graduate School of Medicine, The University of Tokyo
  • Suzuki Takafumi
    Graduate School of Information Science and Technology, The University of Tokyo
  • Mabuchi Kunihiko
    Graduate School of Information Science and Technology, The University of Tokyo

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  • 線形相関モデルを用いた運動野神経信号によるラット歩行状態推定
  • センケイ ソウカン モデル オ モチイタ ウンドウヤ シンケイ シンゴウ ニ ヨル ラット ホコウ ジョウタイ スイテイ

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Abstract

We are developing a brain-machine interface (BMI) called “RatCar," a small vehicle controlled by the neural signals of a rat's brain. An unconfined adult rat with a set of bundled neural electrodes in the brain rides on the vehicle. Each bundle consists of four tungsten wires isolated with parylene polymer. These bundles were implanted in the primary motor and premotor cortices in both hemispheres of the brain. In this paper, methods and results for estimating locomotion speed and directional changes are described. Neural signals were recorded as the rat moved in a straight line and as it changed direction in a curve. Spike-like waveforms were then detected and classified into several clusters to calculate a firing rate for each neuron. The actual locomotion velocity and directional changes of the rat were recorded concurrently. Finally, the locomotion states were correlated with the neural firing rates using a simple linear model. As a result, the abstract estimation of the locomotion velocity and directional changes were achieved.

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