各位老师，您好：

受实验室李小俚老师邀请，McLean Hospital/Harvard Medical  School的Dr. Yunjie Tong将来实验室做学术报告。他将和李小俚老师合作开发 fNIRS 系统。报告信息如下，欢迎各位感兴趣的老师和同学来听。

报告时间：5月14日上午10:00

报告地点：小红楼3层大会议室

报告题目：Partitioning of physiological noise  signals in the brain using concurrent near-infrared spectroscopy (NIRS) and  fMRI

内容简介：The effects of the non-neuronal  physiological processes in BOLD fMRI have been of concern to many investigators  in task studies and recently in the resting state studies. These processes  include the spontaneous low frequency oscillation, respiration and cardiac  pulsations. Because of the low sampling rate of fMRI, these signals are  generally not separable by frequency, as the cardiac and respiratory especially  signals are aliased. NIRS, with its high temporal resolution and sensitivity to  the blood changes, offers an opportunity to record the physiological changes  simultaneously with fMRI, which can then be used to uniquely identify the  spatial and temporal patterns on BOLD signal corresponding to each process. We  demonstrated a new way of integrated processing of NIRS and fMRI data acquired  simultaneously. The new method enables us to track cerebral blood flow as well  as pulse wave in the brain. Moreover, it can be used to identify and remove  systemic fluctuations in the BOLD signal (non-neuronal), thus enhance the  neuronal signal.

报告人简介：Dr. Yunjie Tong is an assistant neuroscientist at McLean Hospital and instructor in psychiatry at Harvard Medical School. He has extensive training in  bioengineering and physics (optics). His long-term goal is to develop high  quality, specialized brain imaging tools or procedures based on near infrared  spectroscopy (NIRS), functional MRI or both combined to study psychiatric  conditions, substance abuse. He started developing hardware (including our  current NIRS helmet, cross-communication circuit board) and software (including  the data processing tools) for concurrent NIRS-fMRI studies during his graduate  school training. The research confirmed the high temporal correlations between  Blood Oxygenated Level Dependent (BOLD) and changes in concentrations of oxy-  and deoxy-hemoglobins by using a spatially weighted average method (Sassaroli et  al., 2006). During his postdoctoral training under the direction of Dr.  Frederick at McLean Hospital/Harvard Medical School, he developed an interactive  data processing method, which enables him to track the cerebral blood flow using  the low frequency oscillations observed by both modalities (Tong et al., 2010;  Tong et al., 2012). More importantly, the technique offers a mean to separate  the physiological fluctuation from the neuronal signals in BOLD fMRI with great  accuracy (Tong et al., 2011a; Tong et al., 2011b; Frederick et al.,  2012).

    此致

敬礼！

认知神经科学与学习国家重点实验室

2012年5月2日

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