NS+: A new meta-analysis tool to extend the utility of NeuroSynth

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Poster No:


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Abstract Submission 


Meng Du1, Matthew Lieberman1


1University of California, Los Angeles, Los Angeles, CA

First Author:

Meng Du  
University of California, Los Angeles
Los Angeles, CA


Matthew Lieberman  
University of California, Los Angeles
Los Angeles, CA


A vast amount of human neuroimaging research seeks to understand the functional mapping of brains with forward inference analyses, which show brain activities produced by specific manipulations but do not indicate causal relationships in the opposite direction. NeuroSynth (Yarkoni, et al., 2011) is a tool that aims to address this problem by synthesizing more than 14000 fMRI studies, and automating reverse inference meta-analysis such as mapping activation probabilities (e.g., in Broca's area) given terms of interest (e.g., "language"). However, Neurosynth can be limited in its flexibility: it is easy to get regions of interest given predefined research topics, but not vice versa. Here, we created a new software tool, NS+, which explores research terms given ROIs, and further extends the utility of NeuroSynth-based reverse inference meta-analysis.


The software tool, NS+, was developed as a standalone software application with a graphical interface. It is based on the core Neurosynth package, together with NeuroSynth's database of 14371 fMRI studies and 3168 predefined research terms. To be friendly for users of all levels, NS+ can be operated either with just button clicks or as a Python package, and does not require a separate installation of any programming environments or NeuroSynth itself.

In this presentation, we will use NS+ to examine the functions and subdivisions of the temporo-parietal junction (TPJ) as a demonstration.


NS+ supports automated and highly customizable forward and reverse inference analyses within any given ROI, which are not allowed by the NeuroSynth online tool or any other tools. Specifically, NS+ allows 1) Analyses of custom research topics by joining NeuroSynth predefined terms. For example, removing "self reported" from "self" to restrict the scope to "self"-related studies, or getting the overlap of "attention" and "shift" to create "attentional shift". 2) Ranking of 3000+ predefined and/or custom terms in any given ROI by their posterior probabilities, which reveals the most likely cognitive functions of ROIs based on reverse inference. 3) Pairwise and multi-term comparisons ("Battle Royale" analysis), which show the territory where each term dominates in the given ROI against all other considered terms, and provides an ROI map that is functionally subdivided by the terms of interest.

In the example analysis of TPJ, we first conducted an exploratory term ranking with NS+. Based on the resulted list together with previous literature, we summarized the most important roles of TPJ as "mentalizing" (theory of mind), "language", "autobiographical memory", "episodic memory", and "attentional orienting". Next, we customized multiple predefined terms to create these 5 topics, and compared them in NS+ ("Battle Royale"). The resulting map shows TPJ and its surrounding areas functionally subdivided by these topics.

The resulting map suggests a strong link between mentalizing and most of the central TPJ, as well as associations of posterior TPJ with autobiographical memory, anterior right TPJ with attentional orientation, and anterior left TPJ with language comprehension. We also further recognized and examined the relatively non-selective TPJ areas.
Supporting Image: figure.png


NS+ is a powerful meta-analysis tool based on NeuroSynth. We developed it to support automated analyses and comparisons of custom research topics, as well as acquisitions of functionally subdivided maps of any ROI. It can be helpful for researchers to gain insights into their research questions as well as results, and to explore the functional mapping of human brains in general. In this presentation, we will demonstrate how to conduct these analyses with only a few button clicks in NS+.

Emotion, Motivation and Social Neuroscience:

Social Neuroscience Other

Modeling and Analysis Methods:

Activation (eg. BOLD task-fMRI)
Methods Development 2
Other Methods

Neuroinformatics and Data Sharing:

Informatics Other 1


Data analysis
Meta- Analysis
Other - software

1|2Indicates the priority used for review

My abstract is being submitted as a Software Demonstration.


Please indicate below if your study was a "resting state" or "task-activation” study.


Healthy subjects only or patients (note that patient studies may also involve healthy subjects):

Healthy subjects

Are you Internal Review Board (IRB) certified? Please note: Failure to have IRB, if applicable will lead to automatic rejection of abstract.


Was any human subjects research approved by the relevant Institutional Review Board or ethics panel? NOTE: Any human subjects studies without IRB approval will be automatically rejected.

Not applicable

Was any animal research approved by the relevant IACUC or other animal research panel? NOTE: Any animal studies without IACUC approval will be automatically rejected.

Not applicable

Please indicate which methods were used in your research:

Other, Please specify  -   Large scale meta-analysis (on fMRI data)

For human MRI, what field strength scanner do you use?

If Other, please list  -   Various

Which processing packages did you use for your study?

Other, Please list  -   NeuroSynth

Provide references using author date format

Dufour, N. (2013). Similar brain activation during false belief tasks in a large sample of adults with and without autism. PloS one, 8(9), e75468.
Yarkoni, T. (2011). Large-scale automated synthesis of human functional neuroimaging data. Nature methods, 8(8), 665.