NeuroImage

.evs raw data used for the analysis of the submitted study

EEG and behavioral dataset (full processed) acquired at Federal Fluminense University in Brazil consisting of EEG and behavioral responses following the presentation of pictures depicting mutilated bodies (potential threat) and people in daily life (neutral) to participants (n = 38) who have been through a very traumatic experience (victms of urban violence). For more details see the manuscript entitled "Hidden wounds of violence: abnormal motor oscillatory brain activity is related to posttraumatic stress symptoms".

Results for the LSD and Psilocybin data. Network fractal dimension, Higuchi temporal fractal dimension, Lempel-Ziv complexity.

The synthetic predictor tables and fully synthetic neuroimaging data produced for the analysis of fully synthetic data in the current study are available as Research Data available from Mendeley Data. Ten fully synthetic datasets include synthetic gray matter images (nifti files) that were generated for analysis with simulated participant data (text files). An archive file predictor_tables.tar.gz contains ten fully synthetic predictor tables with information for 264 simulated subjects. Due to large file sizes, a separate archive was created for each set of synthetic gray matter image data: RBS001.tar.gz, …, RBS010.tar.gz. Regression analyses were performed for each synthetic dataset, then average statistic maps were made for each contrast, which were then smoothed (see accompanying paper for additional information). The supplementary materials also include commented MATLAB and R code to implement the current neuroimaging data synthesis methods (SKexample.zip). The example data were selected from an earlier fMRI study (Kuchinsky et al., 2012) to demonstrate that the current approach can be used with other types of neuroimaging data. The example code can also be adapted to produce fully synthetic group-level datasets based on observed neuroimaging data from other sources. The zip archive includes a document with important information for performing the example analyses, and details that should be communicated with recipients of a synthetic neuroimaging dataset. Kuchinsky, S.E., Vaden, K.I., Keren, N.I., Harris, K.C., Ahlstrom, J.B., Dubno, J.R., Eckert, M.A., 2012. Word intelligibility and age predict visual cortex activity during word listening. Cerebral Cortex 22, 1360–71. https://doi.org/10.1093/cercor/bhr211

.EVS file of raw data collected for the experiment.

The matlab code package for evaluating the motion energies contained in a video clips.

The neural bases of anger are still a matter of debate. In particular we do not know whether anger perception and anger experience rely on similar or different neural mechanisms. To study this topic, we performed activation-likelihood-estimation meta-analyses of human neuroimaging studies on 62 previous studies on anger perception and experience. Anger perception analysis resulted in significant activation in the amygdala, the superior temporal gyrus and the right ventrolateral prefrontal cortex, thus revealing the role of perceptual areas such as the superior temporal gyrus and the amygdala for perceiving angry stimuli. Anger experience analysis resulted in the bilateral activation of the insula and the ventrolateral prefrontal cortex, thus revealing the role of the insula in the experience of anger. Conjunction analyses revealed a common area localized in the right inferior frontal gyrus, probably involved in the appraisal and labelling of anger for both perception and experience. Altogether these results provide new insights on the functional architecture underlying the neural processing of anger that involves separate and joint mechanisms, where the superior temporal gyrus and the amygdala are key regions for the perception of this emotion displayed by others, and the insula is a key region for the experience of anger. These data show the GingerALE output of the meta-analyses on: - Anger Perception - Anger Experience - The conjunction analysis between anger perception and anger experience

Category-tagged scaled cortical activation values across 1016 cortical and subcortical brain regions during auditory and visual imagery of familiar manipulable tools, instruments and fruits/vegetables.

This directory contains the data and scripts used in the Methods & Materials of the study "Discovering the shared biology of cognitive traits determined by genetic overlap". It is split into 3 sections: - Twin Modeling: genetic analysis estimating shared genetics among cognitive traits (each individually driven by genetic factors, i.e. heritable). - Functional Imaging Meta-analysis: estimation of brain maps representative of cognitive activation across studies, individually for each cognitive trait reporting shared genetics - Brain Activation Overlap: quantify and infer overlap among cognitive maps, mimicking their respective genetic association, via three approaches: shared number of voxels, dice similarity coefficient, and the permuted correlation approach reported by Alexander-Bloch et al 2018

Results from masked-ICA based on 20 components and dual regression at the local (within-A-MTL) and global (whole brain) level in three different samples.