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The influence of heart beat and respiration on functional connectivity networks

机译:心跳和呼吸对功能连接网络的影响

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We investigate the influence of physiological measures like heart beat and respiration on functional connectivity networks from fMRI. Cardiac and respiratory effects were measured simultaneously during high rate MRI data acquisition and the functional connectivity networks were determined in a data driven manner using graph theory. One of our findings is that removing the physiological effects from the data leads to disappearance of a considerable part of the functional connectivity networks and to the appearance of small, but consistent networks. We found further that high signal variance loss due to physiological effect removal does not coincide with a high correlation loss, on the contrary, a considerable part of the networks appears preferably at locations with high variance loss.
机译:我们调查了功能性连接网络从功能磁共振成像,如心跳和呼吸等生理措施的影响。在高速MRI数据采集期间同时测量心脏和呼吸作用,并使用图论以数据驱动方式确定功能连接网络。我们的发现之一是,从数据中删除生理影响会导致功能连接网络的相当一部分消失,并导致小型但一致的网络的出现。我们进一步发现,由于去除生理效应而导致的高信号方差损失与高相关性损失不重合,相反,网络的相当一部分最好出现在具有高方差损失的位置。

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