Submitted by ZHANG_RESTadmin on Tue, 04/19/2016 - 09:51
PreSurgMapp is a toolbox for pipelined processing dedicated to individualized presurgical mapping of eloquent functional areas based on multimodal functional MRI.
The current release is PreSurgMapp v2.0.
Set up and Start:
1. Simply add the path to MATLAB just like SPM.
2. Enter "PreSurgMapp" in MATLAB command window (no quotation marks).
New Features of PreSurgMapp v2.0
1. An input box for user to adjust the level of smoothing (FWHM) is added.
2. Provide three types of individual-level ICA analyses for users to choose. For task fMRI, Traditional ICA (task) can be used. For rs-fMRI, both Traditional ICA (rest) and ICA with DICI (rest) can be used. There is a difference between Traditional ICA (rest) and ICA with DICI (rest), Traditional ICA (rest) is intended for users who have a strong hypothesis on the pattern of the target component and want to set the number of components by themself (i.e., 50), while ICA with DICI (rest) will be fully-automatic as long as the user have a template at hand. It uses multiple settings of the number of components and utilizes an automatic component identification method based on discriminability-index. All the components from multiple ICA runs with multiple number of component settings are ranked and the best component. Thus, the identification of target component will be less biased, and the problem of inconsistency due to the preset number of components can be avoided.
3. For ICA with DICI (rest), a set of commonly used templates, e.g., sensorimotor, language, etc. are provided for convenience.
3. Support task activation analysis with more than one condition (two conditions).
4. More parameter templates are added (incuding "Calculate Traditional ICA (rest) only", "Calculate Traditional ICA (task) only", "Calculate ICA with DICI (rest) only" and "Calculate Task activation only").
5. The processing steps can be freely skipped or combined.
Help:
Please refer to http://www.restfmri.net.
Copyright(c) 2014; GNU GENERAL PUBLIC LICENSE
Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments,Center for Cognition and Brain Disorder, Hangzhou Normal University, China
Mail to Author: Huang Hui-Yuan < missy139@163.com>
-----------------------------------------------------------
Citing Information:
Zhang H., Jia W.B., Liao W., Zang Y.F., 2013. Automatic component identification method based on normalized sensitivity/specificity measurement. OHBM 2013. Seattle, US.
Acknowledgement:
Several processing functions in PreSurgMapp v2.0 was modified from SPM8, REST (Song et al., 2009), DPARSF (Yan and Zang et al., 2010) and MICA (Zhang et al., 2010).
PreSurgMapp is a toolbox for pipelined processing dedicated to individualized presurgical mapping of eloquent functional areas based on multimodal functional MRI.
The current release is PreSurgMapp v2.0.
Set up and Start:
1. Simply add the path to MATLAB just like SPM.
2. Enter "PreSurgMapp" in MATLAB command window (no quotation marks).
New Features of PreSurgMapp v2.0
1. An input box for user to adjust the level of smoothing (FWHM) is added.
2. Provide three types of individual-level ICA analyses for users to choose. For task fMRI, Traditional ICA (task) can be used. For rs-fMRI, both Traditional ICA (rest) and ICA with DICI (rest) can be used. There is a difference between Traditional ICA (rest) and ICA with DICI (rest), Traditional ICA (rest) is intended for users who have a strong hypothesis on the pattern of the target component and want to set the number of components by themself (i.e., 50), while ICA with DICI (rest) will be fully-automatic as long as the user have a template at hand. It uses multiple settings of the number of components and utilizes an automatic component identification method based on discriminability-index. All the components from multiple ICA runs with multiple number of component settings are ranked and the best component. Thus, the identification of target component will be less biased, and the problem of inconsistency due to the preset number of components can be avoided.
3. For ICA with DICI (rest), a set of commonly used templates, e.g., sensorimotor, language, etc. are provided for convenience.
3. Support task activation analysis with more than one condition (two conditions).
4. More parameter templates are added (incuding "Calculate Traditional ICA (rest) only", "Calculate Traditional ICA (task) only", "Calculate ICA with DICI (rest) only" and "Calculate Task activation only").
5. The processing steps can be freely skipped or combined.
Help:
Please refer to http://www.restfmri.net.
Copyright(c) 2014; GNU GENERAL PUBLIC LICENSE
Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments,Center for Cognition and Brain Disorder, Hangzhou Normal University, China
Mail to Author: Huang Hui-Yuan < missy139@163.com>
-----------------------------------------------------------
Citing Information:
Zhang H., Jia W.B., Liao W., Zang Y.F., 2013. Automatic component identification method based on normalized sensitivity/specificity measurement. OHBM 2013. Seattle, US.
Acknowledgement:
Several processing functions in PreSurgMapp v2.0 was modified from SPM8, REST (Song et al., 2009), DPARSF (Yan and Zang et al., 2010) and MICA (Zhang et al., 2010).
PreSurgMapp is a toolbox for pipelined processing dedicated to individualized presurgical mapping of eloquent functional areas based on multimodal functional MRI.
The current release is PreSurgMapp v2.1.
Set up and Start:
1. Simply add the path to MATLAB just like SPM.
2. Enter "PreSurgMapp" in MATLAB command window (no quotation marks).
New Features of PreSurgMapp v2.1
1. An input box for user to adjust the level of smoothing (FWHM) is added.
2. Provide three types of individual-level ICA analyses for users to choose. For task fMRI, Traditional ICA (task) can be used. For rs-fMRI, both Traditional ICA (rest) and ICA with DICI (rest) can be used. There is a difference between Traditional ICA (rest) and ICA with DICI (rest), Traditional ICA (rest) is intended for users who have a strong hypothesis on the pattern of the target component and want to set the number of components by themself (i.e., 50), while ICA with DICI (rest) will be fully-automatic as long as the user have a template at hand. It uses multiple settings of the number of components and utilizes an automatic component identification method based on discriminability-index. All the components from multiple ICA runs with multiple number of component settings are ranked and the best component. Thus, the identification of target component will be less biased, and the problem of inconsistency due to the preset number of components can be avoided.
3. For ICA with DICI (rest), a set of commonly used templates, e.g., sensorimotor, language, etc. are provided for convenience.
4. Support task activation analysis with more than one condition (two conditions).
5. More parameter templates are added (incuding "Calculate Traditional ICA (rest) only", "Calculate Traditional ICA (task) only", "Calculate ICA with DICI (rest) only" and "Calculate Task activation only").
6. The processing steps can be freely skipped or combined.
Help and Bug Report:
Please refer to http://www.restfmri.net.
Copyright(c) 2014; GNU GENERAL PUBLIC LICENSE
Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments,Center for Cognition and Brain Disorder, Hangzhou Normal University, China
Mail to Author: Hui-Yuan Huang< missy139@163.com>
-----------------------------------------------------------
Citing Information:
Huang H, Ding Z, Mao D, Yuan J, Zhu F, Chen S, Xu Y, Lou L, Feng X, Qi L (2016) PreSurgMapp: a MATLAB Toolbox for Presurgical Mapping of Eloquent Functional Areas Based on Task-Related and Resting-State Functional MRI. Neuroinformatics 1-18.
Zhang H., Jia W.B., Liao W., Zang Y.F., 2013. Automatic component identification method based on normalized sensitivity/specificity measurement. OHBM 2013. Seattle, US.
Acknowledgement:
Several processing functions in PreSurgMapp v2.1 was modified from SPM8, REST (Song et al., 2009), DPARSFA (Yan and Zang et al., 2010) and MICA (Zhang et al., 2010).
| Attachment | Size |
|---|---|
 PreSurgMapp_v2.1.zip | 2.19 MB |
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Comments
Submitted by Cassandra on Tue, 01/17/2017 - 23:20 Permalink
Re: New version (v2.1) of Pipeline-based individual ...
张老师，您好！
我在做两组被试（正常及病例组）两个亚频段（S4，S5) ALFF的分析，使用贵团队开发的dpabi V2.3 mixed effect ANOVA 运行时报错，我试过把协变量去掉以后运行成功，重新加入协变量后再次报同样的错误。我检查过数据的维度和mask 是一致的，协变量我是按照视频里说的方法在每个TXT文档下放四列（age，sex，eduyear，mean FD），顺序与group image对应，group image加载的顺序参照教程（Group1condition1，Group1condition2，Group2condition1，Group2condition2）如下图。请教老师我这里报错的原因为何？静候老师的回复，谢谢！
Submitted by Cassandra on Tue, 01/17/2017 - 23:11 Permalink
Re: New version (v2.1) of Pipeline-based individual ...
张老师，您好！
我在做两组被试（正常及病例组）两个亚频段（S4，S5) ALFF的分析，使用贵团队开发的dpabi V2.3 mixed effect ANOVA 运行时报错，我试过把协变量去掉以后运行成功，重新加入协变量后再次报同样的错误。我检查过数据的维度和mask 是一致的，协变量我是按照视频里说的方法在每个TXT文档下放四列（age，sex，eduyear，mean FD），顺序与group image对应，group image加载的顺序参照教程（Group1condition1，Group1condition2，Group2condition1，Group2condition2）如下图。请教老师我这里报错的原因为何？静候老师的回复，谢谢！