Department of Neurology, University of Lübeck, Lübeck, Germany.
Department of Psychology, University of Lübeck, Lübeck, Germany.
Neuroimage. 2019 Nov 15;202:116060. doi: 10.1016/j.neuroimage.2019.116060. Epub 2019 Jul 27.
Electroencephalography (EEG) continues to be the most popular method to investigate cognitive brain mechanisms in young children and infants. Most infant studies rely on the well-established and easy-to-use event-related brain potential (ERP). As a severe disadvantage, ERP computation requires a large number of repetitions of items from the same stimulus-category, compromising both ERPs' reliability and their ecological validity in infant research. We here explore a way to investigate infant continuous EEG responses to an ongoing, engaging signal (i.e., "neural tracking") by using multivariate temporal response functions (mTRFs), an approach increasingly popular in adult EEG research. N = 52 infants watched a 5-min episode of an age-appropriate cartoon while the EEG signal was recorded. We estimated and validated forward encoding models of auditory-envelope and visual-motion features. We compared individual and group-based ('generic') models of the infant brain response to comparison data from N = 28 adults. The generic model yielded clearly defined response functions for both, the auditory and the motion regressor. Importantly, this response profile was present also on an individual level, albeit with lower precision of the estimate but above-chance predictive accuracy for the modelled individual brain responses. In sum, we demonstrate that mTRFs are a feasible way of analyzing continuous EEG responses in infants. We observe robust response estimates both across and within participants from only 5 min of recorded EEG signal. Our results open ways for incorporating more engaging and more ecologically valid stimulus materials when probing cognitive, perceptual, and affective processes in infants and young children.
脑电图(EEG)仍然是研究幼儿和婴儿认知大脑机制的最流行方法。大多数婴儿研究依赖于成熟且易于使用的事件相关脑电位(ERP)。作为一个严重的缺点,ERP 计算需要大量重复来自同一刺激类别的项目,从而影响婴儿研究中 ERP 的可靠性和生态有效性。我们在这里探索了一种通过使用多变量时间响应函数(mTRF)来研究婴儿对持续、吸引人的信号(即“神经跟踪”)的连续 EEG 反应的方法,这种方法在成人 EEG 研究中越来越受欢迎。N=52 名婴儿观看了一段 5 分钟的适合年龄的卡通片,同时记录 EEG 信号。我们估计并验证了听觉包络和视觉运动特征的前向编码模型。我们将婴儿大脑对比较数据的个体和基于群体(“通用”)模型与 N=28 名成年人的比较数据进行了比较。通用模型为听觉和运动回归器都产生了明确界定的响应功能。重要的是,即使个体估计的精度较低,但在模拟个体大脑反应时具有高于机会的预测准确性,这种响应特征也存在于个体水平上。总之,我们证明 mTRF 是一种可行的分析婴儿连续 EEG 反应的方法。我们从仅 5 分钟的记录 EEG 信号中观察到了跨参与者和参与者内的稳健响应估计。我们的结果为在婴儿和幼儿中探测认知、感知和情感过程时纳入更吸引人且更具生态有效性的刺激材料开辟了道路。