NeuralAct: A Tool to Visualize Electrocortical (ECoG) Activity on a Three-Dimensional Model of the Cortex.
NeuralAct: A Tool to Visualize Electrocortical (ECoG) Activity on a Three-Dimensional Model of the Cortex.
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DOI：
10.1007/s12021-014-9252-3
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发表时间：
2015-04
期刊：
影响因子：
3
通讯作者：
Schalk G
中科院分区：
文献类型：
--
作者：
Kubanek J;Schalk G
皮层电图（ECoG）直接记录来自皮层表面的神经信号。由于其高的时间分辨率和良好的空间分辨率，ECoG已成为认知和系统神经科学中获取皮层活动的有价值的新工具。许多研究使用ECoG可视化地形图的皮质活动或统计测试的三维模型的皮质，但专门的工具，这一功能尚未被描述。在本文中，我们描述了用于此目的的NeuralAct包。该软件包将记录传感器的3D坐标、同一坐标系中的皮层模型（例如，Talairach），并且激活数据在每个传感器处可视化。然后，它将传感器坐标与皮层模型对齐，将激活数据与空间内核进行卷积，并在皮层模型上以颜色呈现所得到的激活。NeuralAct软件包可以绘制个体受试者的皮层激活以及受试者的平均激活。它能够渲染单个图像以及图像序列。该软件在Matlab下运行，稳定可靠。我们在这里提供的工具，并描述其可视化功能和程序。提供的软件包包含完整的文档代码，并包括一个简单的演示，指导研究人员通过该工具的功能。
Electrocorticography (ECoG) records neural signals directly from the surface of the cortex. Due to its high temporal and favorable spatial resolution, ECoG has emerged as a valuable new tool in acquiring cortical activity in cognitive and systems neuroscience. Many studies using ECoG visualized topographies of cortical activity or statistical tests on a three-dimensional model of the cortex, but a dedicated tool for this function has not yet been described. In this paper, we describe the NeuralAct package that serves this purpose. This package takes as input the 3D coordinates of the recording sensors, a cortical model in the same coordinate system (e.g., Talairach), and the activation data to be visualized at each sensor. It then aligns the sensor coordinates with the cortical model, convolves the activation data with a spatial kernel, and renders the resulting activations in color on the cortical model. The NeuralAct package can plot cortical activations of an individual subject as well as activations averaged over subjects. It is capable to render single images as well as sequences of images. The software runs under Matlab and is stable and robust. We here provide the tool and describe its visualization capabilities and procedures. The provided package contains thoroughly documented code and includes a simple demo that guides the researcher through the functionality of the tool.
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影响因子：
4
作者：
Kubánek J;Miller KJ;Ojemann JG;Wolpaw JR;Schalk G
通讯作者：
Schalk G
使用人类电视图（ECOG）信号来解码秘密空间注意力。
影响因子：
5.7
作者：
Gunduz, Aysegul;Brunner, Peter;Daitch, Amy;Leuthardt, Eric C.;Ritaccio, Anthony L.;Pesaran, Bijan;Schalk, Gerwin
通讯作者：
Schalk, Gerwin
影响因子：
3.7
作者：
Kubanek J;Brunner P;Gunduz A;Poeppel D;Schalk G
通讯作者：
Schalk G
影响因子：
5.7
作者：
Dale, AM;Fischl, B;Sereno, MI
通讯作者：
Sereno, MI
影响因子：
5.7
作者：
Korzeniewska, Anna;Franaszczuk, Piotr J.;Crainiceanu, Ciprian M.;Kus, Rafal;Crone, Nathan E.
通讯作者：
Crone, Nathan E.