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Parallel processing of somatosensory information: Evidence from dynamic causal modeling of MEG data

机译:体感信息的并行处理:来自MEG数据动态因果模型的证据

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The advent of methods to investigate network dynamics has led to discussion of whether somatosensory inputs are processed in serial or in parallel. Both hypotheses are supported by DCM analyses of fMRI studies. In the present study, we revisited this controversy using DCM on magnetoencephalographic (MEG) data during somatosensory stimulation. Bayesian model comparison was used to allow for direct inference on the processing stream. Additionally we varied the duration of the time-window of analyzed data after the somatosensory stimulus. This approach allowed us to explore time dependent changes in the processing stream of somatosensory information and to evaluate the consistency of results. We found that models favoring a parallel processing route best describe neural activities elicited by somatosensory stimuli. This result was consistent for different time-windows. Although it is assumed that the majority of somatosensory information is delivered to the SI, the current results indicate that at least a small part of somatosensory information is delivered in parallel to the SII. These findings emphasize the importance of data analysis with high temporal resolution. (C) 2015 Elsevier Inc. All rights reserved.
机译:研究网络动态的方法的出现引发了对身体感应输入是串行还是并行处理的讨论。两种假说均得到了功能磁共振成像研究的DCM分析的支持。在本研究中,我们在体感刺激期间使用DCM对脑磁图(MEG)数据重新审视了这一争议。使用贝叶斯模型比较可以直接推断处理流。另外,在体感刺激之后,我们改变了分析数据的时间窗口的持续时间。这种方法使我们能够探索体感信息处理流中随时间变化的情况,并评估结果的一致性。我们发现,支持并行处理路径的模型可以最好地描述体感刺激引起的神经活动。对于不同的时间窗口,此结果是一致的。尽管假定大多数体感信息被传递到SI,但是当前结果表明至少一小部分体感信息与SII并行传递。这些发现强调了具有高时间分辨率的数据分析的重要性。 (C)2015 Elsevier Inc.保留所有权利。

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