Herman Max Charles, Cardoso Mariana M B, Lima Bruss, Sirotin Yevgeniy B, Das Aniruddha
Columbia University, Department of Neuroscience, New York, New York, United States.
University of California at San Francisco, Department of Physiology and Center for Integrative Neuroscience, San Francisco, California, United States.
Neurophotonics. 2017 Jul;4(3):031223. doi: 10.1117/1.NPh.4.3.031223. Epub 2017 Jul 10.
Task-related hemodynamic responses contribute prominently to functional magnetic resonance imaging (fMRI) recordings. They reflect behaviorally important brain states, such as arousal and attention, and can dominate stimulus-evoked responses, yet they remain poorly understood. To help characterize these responses, we present a method for parametrically estimating both stimulus-evoked and task-related components of hemodynamic responses from subjects engaged in temporally predictable tasks. The stimulus-evoked component is modeled by convolving a hemodynamic response function (HRF) kernel with spiking. The task-related component is modeled by convolving a Fourier-series task-related function (TRF) kernel with task timing. We fit this model with simultaneous electrode recordings and intrinsic-signal optical imaging from the primary visual cortex of alert, task-engaged monkeys. With high [Formula: see text], the model returns HRFs that are consistent across experiments and recording sites for a given animal and TRFs that entrain to task timing independent of stimulation or local spiking. When the task schedule conflicts with that of stimulation, the TRF remains locked to the task emphasizing its behavioral origins. The current approach is strikingly more robust to fluctuations than earlier ones and gives consistently, if modestly, better fits. This approach could help parse the distinct components of fMRI recordings made in the context of a task.
与任务相关的血流动力学反应对功能磁共振成像（fMRI）记录有显著贡献。它们反映了行为上重要的大脑状态，如觉醒和注意力，并且可以主导刺激诱发的反应，但人们对它们的了解仍然很少。为了帮助描述这些反应，我们提出了一种方法，用于从参与时间可预测任务的受试者中参数估计血流动力学反应的刺激诱发成分和与任务相关的成分。刺激诱发成分通过将血流动力学反应函数（HRF）内核与尖峰进行卷积来建模。与任务相关的成分通过将傅里叶级数任务相关函数（TRF）内核与任务时间进行卷积来建模。我们将该模型与清醒的、参与任务的猴子初级视觉皮层的同步电极记录和内在信号光学成像进行拟合。在高[公式：见正文]时，该模型返回的HRF在给定动物的不同实验和记录位点之间是一致的，并且TRF与任务时间同步，与刺激或局部尖峰无关。当任务时间表与刺激时间表冲突时，TRF仍然锁定在任务上，强调其行为起源。当前的方法比早期的方法对波动的鲁棒性明显更强，并且给出的拟合结果始终（尽管适度）更好。这种方法有助于解析在任务背景下进行的fMRI记录的不同成分。
