The Korean Journal of Applied Statistics (응용통계연구)

The Korean Statistical Society (한국통계학회)
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Statistical analysis issues for neuroimaging MEG data

뇌영상 MEG 데이터에 대한 통계적 분석 문제

  • Kim, Jaehee (Department of Statistics, Duksung Women's University)
  • Received : 2021.11.24
  • Accepted : 2021.12.24
  • Published : 2022.02.28
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Abstract

Oscillatory magnetic fields produced in the brain due to neuronal activity can be measured by the sensor. Magnetoencephalography (MEG) is a non-invasive technique to record such neuronal activity due to excellent temporal and fair amount of spatial resolution, which gives information about the brain's functional activity. Potential utilization of high spatial resolution in MEG is likely to provide information related to in-depth brain functioning and underlying factors responsible for changes in neuronal waves in some diseases under resting state or task state. This review is a comprehensive report to introduce statistical models from MEG data including graphical network modelling. It is also meaningful to note that statisticians should play an important role in the brain science field.

뇌활동으로 발생하는 전기신호는 다시 자기신호로 유도되는데 센서로 측정한 것을 뇌자도(magnetoencephalography, MEG)라고 한다. MEG 기술은 비접촉, 비침습적인 측정방법이고 시간분해능과 공간분해능력이이 우수하기 때문에 뇌의 기능적인 정보를 얻는데 유용하게 사용될 수 있다. 또한 MEG 신호를 측정하고 분석하여 뇌신경전류의 활동을 이해할 수 있고 나아가 정밀한 뇌기능 연구가 가능하다. 본 연구에서는 뇌 활동(brain activity) 현상에 관한 궁극적 정보를 얻기위해 MEG 데이터의 특성을 설명하고 통계적 문제를 다루어 앞으로 뇌연구에 통계학의 필요성과 뇌정보학의 중요성을 강조하고자 한다.

Keywords

Acknowledgement

이 성과는 정부(과학기술정보통신부)의 재원으로 한국연구재단의 연구 기초연구실 (No. 2021R1A4A5028907) 지원과 기본연구 (No. 2021R1F1A1054968) 지원을 받아 수행한 연구 과제입니다.

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