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利用眼动、言语清晰度和脑活动动态来预测和跟踪轻度创伤性脑损伤筛查结果。

Using Dynamics of Eye Movements, Speech Articulation and Brain Activity to Predict and Track mTBI Screening Outcomes.

作者信息

Williamson James R, Sturim Doug, Vian Trina, Lacirignola Joseph, Shenk Trey E, Yuditskaya Sophia, Rao Hrishikesh M, Talavage Thomas M, Heaton Kristin J, Quatieri Thomas F

机构信息

Human Health and Performance Systems, MIT Lincoln Laboratory, Lexington, MA, United States.

Counter-WMD Systems, MIT Lincoln Laboratory, Lexington, MA, United States.

出版信息

Front Neurol. 2021 Jul 6;12:665338. doi: 10.3389/fneur.2021.665338. eCollection 2021.

Abstract

Repeated subconcussive blows to the head during sports or other contact activities may have a cumulative and long lasting effect on cognitive functioning. Unobtrusive measurement and tracking of cognitive functioning is needed to enable preventative interventions for people at elevated risk of concussive injury. The focus of the present study is to investigate the potential for using passive measurements of fine motor movements (smooth pursuit eye tracking and read speech) and resting state brain activity (measured using fMRI) to complement existing diagnostic tools, such as the Immediate Post-concussion Assessment and Cognitive Testing (ImPACT), that are used for this purpose. Thirty-one high school American football and soccer athletes were tracked through the course of a sports season. Hypotheses were that (1) measures of complexity of fine motor coordination and of resting state brain activity are predictive of cognitive functioning measured by the ImPACT test, and (2) within-subject changes in these measures over the course of a sports season are predictive of changes in ImPACT scores. The first principal component of the six ImPACT composite scores was used as a latent factor that represents cognitive functioning. This latent factor was positively correlated with four of the ImPACT composites: verbal memory, visual memory, visual motor speed and reaction speed. Strong correlations, ranging between = 0.26 and = 0.49, were found between this latent factor and complexity features derived from each sensor modality. Based on a regression model, the complexity features were combined across sensor modalities and used to predict the latent factor on out-of-sample subjects. The predictions correlated with the true latent factor with = 0.71. Within-subject changes over time were predicted with = 0.34. These results indicate the potential to predict cognitive performance from passive monitoring of fine motor movements and brain activity, offering initial support for future application in detection of performance deficits associated with subconcussive events.

摘要

在体育活动或其他接触性活动中,头部反复受到亚脑震荡冲击可能会对认知功能产生累积且持久的影响。需要对认知功能进行不引人注意的测量和跟踪,以便对有脑震荡损伤高风险的人群进行预防性干预。本研究的重点是调查利用精细运动动作的被动测量(平稳跟踪眼球运动和朗读语音)以及静息态脑活动(使用功能磁共振成像测量)来补充现有诊断工具(如用于此目的的脑震荡后即刻评估和认知测试(ImPACT))的可能性。31名美国高中橄榄球和足球运动员在一个体育赛季中接受了跟踪。研究假设为:(1)精细运动协调复杂性和静息态脑活动的测量可预测通过ImPACT测试测得的认知功能,以及(2)在一个体育赛季中这些测量的个体内部变化可预测ImPACT分数的变化。六个ImPACT综合分数的第一个主成分被用作代表认知功能的潜在因素。这个潜在因素与四个ImPACT综合指标呈正相关:言语记忆、视觉记忆、视觉运动速度和反应速度。在这个潜在因素与源自每种传感器模式的复杂性特征之间发现了强相关性,范围在 = 0.26至 = 0.49之间。基于回归模型,跨传感器模式组合复杂性特征,并用于预测样本外受试者的潜在因素。预测结果与真实潜在因素的相关性为 = 0.71。个体内部随时间的变化预测值为 = 0.34。这些结果表明,通过对精细运动动作和脑活动的被动监测来预测认知表现具有潜力,为未来在检测与亚脑震荡事件相关的表现缺陷中的应用提供了初步支持。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/beb9/8289895/4f977de64308/fneur-12-665338-g0001.jpg

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