Visual analytics of brain effective connectivity using convergent cross mapping
Visual analytics of brain effective connectivity using convergent cross mapping
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DOI：
10.1145/3139295.3139303
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发表时间：
2017-11
期刊：
影响因子：
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通讯作者：
H. Natsukawa;K. Koyamada
中科院分区：
文献类型：
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作者：
H. Natsukawa;K. Koyamada
为了阐明大脑中信息处理的动力学，有必要识别神经元网络中神经信息传输的方向并阐明其影响（即，因果关系）的神经元活动在一个地区的神经元活动在另一个地区。收敛交叉映射（CCM）已被用于神经科学领域，以检查大脑功能的有效连接。CCM可以从确定性和非线性系统创建的时间序列数据中检测因果关系。由于CCM包括复杂的过程，如提前参数的确定，非线性的确认，结果的解释，这导致CCM的可用性降低，有一个有效的可视化界面的强烈需求。在本文中，我们提出了一个可视化的分析系统，增加了CCM的可用性，并有助于在有效的连接新的发现。使用领域专家问卷对可用性进行了评估。从结果和过程可理解性的角度，通过将所提出的系统与原始字符用户界面进行比较，证实了可用性的提高。此外，利用该系统，从视觉认知任务和静息状态任务的脑磁图数据中获得了人脑连接的新发现。
To elucidate the dynamics of information processing in the brain, it is necessary to identify the direction of neural information transmission in the neuronal network and clarify the effects (i.e., the causal relationship) of neuronal activity in one area on neuronal activity in another area. Convergent cross mapping (CCM) has been employed in the neuroscience field to examine the effective connectivity of brain functions. CCM can detect causality from time series data created from deterministic and nonlinear systems. Because CCM includes complicated processes such as the determination of advance parameters, the confirmation of nonlinearity, and the interpretation of results, which results in a lowering of the usability of CCM, there is a strong need for an effective visual interface. In this paper, we propose a visual analytic system that increases the usability of CCM and contributes to new discoveries in effective connectivity. The usability was evaluated using a domain expert questionnaire. It was confirmed that the usability was improved by comparing the proposed system to the original character user interface from the viewpoint of the results and process comprehensibility. In addition, with the proposed system, new findings in human brain connectivity have been obtained from actual magnetoencephalography data during visual cognitive task and resting-state task.