Hemispheric asymmetry is a cardinal feature of human brain organization. Altered brain asymmetry has also been linked to some cognitive and neuropsychiatric disorders. Here the ENIGMA consortium presents the largest ever analysis of cerebral cortical asymmetry and its variability across individuals. Cortical thickness and surface area were assessed in MRI scans of 17,141 healthy individuals from 99 datasets worldwide. Results revealed widespread asymmetries at both hemispheric and regional levels, with a generally thicker cortex but smaller surface area in the left hemisphere relative to the right. Regionally, asymmetries of cortical thickness and/or surface area were found in the inferior frontal gyrus, transverse temporal gyrus, parahippocampal gyrus, and entorhinal cortex. These regions are involved in lateralized functions, including language and visuospatial processing. In addition to population-level asymmetries, variability in brain asymmetry was related to sex, age, and brain size (indexed by intracranial volume). Interestingly, we did not find significant associations between asymmetries and handedness. Finally, with two independent pedigree datasets (N = 1,443 and 1,113, respectively), we found several asymmetries showing modest but highly reliable heritability. The structural asymmetries identified, and their variabilities and heritability provide a reference resource for future studies on the genetic basis of brain asymmetry and altered laterality in cognitive, neurological, and psychiatric disorders.Significance StatementLeft-right asymmetry is a key feature of the human brain's structure and function. It remains unclear which cortical regions are asymmetrical on average in the population, and how biological factors such as age, sex and genetic variation affect these asymmetries. Here we describe by far the largest ever study of cerebral cortical brain asymmetry, based on data from 17,141 participants. We found a global anterior-posterior 'torque' pattern in cortical thickness, together with various regional asymmetries at the population level, which have not been previously described, as well as effects of age, sex, and heritability estimates. From these data, we have created an on-line resource that will serve future studies of human brain anatomy in health and disease.

Objective: Although lower brain volume has been routinely observed in individuals with substance dependence compared with nondependent control subjects, the brain regions exhibiting lower volume have not been consistent across studies. In addition, it is not clear whether a common set of regions are involved in substance dependence regardless of the substance used or whether some brain volume effects are substance specific. Resolution of these issues may contribute to the identification of clinically relevant imaging biomarkers. Using pooled data from 14 countries, the authors sought to identify general and substance-specific associations between dependence and regional brain volumes. Method: Brain structure was examined in a mega-analysis of previously published data pooled from 23 laboratories, including 3,240 individuals, 2,140 of whom had substance dependence on one of five substances: alcohol, nicotine, cocaine, methamphetamine, or cannabis. Subcortical volume and cortical thickness in regions defined by FreeSurfer were compared with nondependent control subjects when all sampled substance categories were combined, as well as separately, while controlling for age, sex, imaging site, and total intracranial volume. Because of extensive associations with alcohol dependence, a secondary contrast was also performed for dependence on all substances except alcohol. An optimized split-half strategy was used to assess the reliability of the findings. Results: Lower volume or thickness was observed in many brain regions in individuals with substance dependence. The greatest effects were associated with alcohol use disorder. A set of affected regions related to dependence in general, regardless of the substance, included the insula and the medial orbitofrontal cortex. Furthermore, a support vector machine multivariate classification of regional brain volumes successfully classified individuals with substance dependence on alcohol or nicotine relative to nondependent control subjects. Conclusions: The results indicate that dependence on a range of different substances shares a common neural substrate and that differential patterns of regional volume could serve as useful biomarkers of dependence on alcohol and nicotine.

These findings suggest that in cocaine addiction 1) activation of the corticolimbic reward circuit to gradations of money is altered; 2) the lack of a correlation between objective and subjective measures of state motivation may be indicative of disrupted perception of motivational drive, which could contribute to impairments in self-control; and 3) the lateral prefrontal cortex modulates trait motivation and deficits in self-control, and a possible underlying mechanism may encompass a breakdown in prefrontal-orbitofrontal cortical communication.

This parametric functional magnetic resonance imaging (fMRI) study investigates the balance of negative, and positive fMRI signals in the brain. A set of visual attention (VA) and of working memory (WM) tasks with graded levels of difficulty was used to deactivate separate, but overlapping networks that include the frontal, temporal, occipital, and limbic lobes; regions commonly associated with auditory and emotional processing. Brain activation (% signal change, and volume) was larger for VA tasks than for WM tasks, but deactivation was larger for WM tasks. BOLD responses crosscorrelated strongly in the deactivated network during VA but less so during WM. The variability of the deactivated network across different cognitive tasks supports the hypothesis that global CBF vary across different tasks, but not between conditions of the same task. The task-dependent balance of activation and deactivation might allow maximization of resources for the activated network.

Mechanical vibrations of the gradient coil system during readout in echo-planar imaging (EPI) can increase the temperature of the gradient system and alter the magnetic field distribution during functional magnetic resonance imaging (fMRI). This effect is enhanced by resonant modes of vibrations and results in apparent motion along the phase encoding direction in fMRI studies. The magnetic field drift was quantified during EPI by monitoring the resonance frequency interleaved with the EPI acquisition, and a novel method is proposed to correct the apparent motion. The knowledge on the frequency drift over time was used to correct the phase of the k-space EPI dataset. Since the resonance frequency changes very slowly over time, two measurements of the resonance frequency, immediately before and after the EPI acquisition, are sufficient to remove the field drift effects from fMRI time series. The frequency drift correction method was tested "in vivo" and compared to the standard image realignment method. Growing demands on magnetic resonance imaging (MRI) systems to speed up image acquisition have led to the use of higher magnetic fields and to the development of ultrafast imaging techniques, e.g., echo planar imaging (EPI). Rapidly switched gradient fields during EPI-readout interact with the static magnetic field, producing strong timedependent mechanical forces in the gradient coil system that can stimulate natural modes of vibration in the coil assembly (1) and produce large vibrational amplitudes under on-resonance conditions (2).Friction between vibrating parts of the MRI scanner transforms mechanical vibration energy into heat, thereby increasing their temperature. Ferromagnetic shim elements frequently are attached to the vibrating gradient coil; therefore, vibrations can transiently increase their temperature and reduce their magnetization, which ultimately changes the homogeneity and strength of the local magnetic field. Even slight magnetic field shifts during EPI can lead to large apparent movements of the object in the phase encoding direction in functional MRI (fMRI) studies (3-6). If not corrected properly, such mismatches of the object's position in subsequent images may result in erroneous activation patterns in fMRI analyses (7,8).In this work we propose a simple approach to monitor the water resonance frequency during EPI experiments with interleaved one-dimension free-induction-decay (1D-FID) acquisitions, which provide high-resolution spectral information. We show that the frequency drift caused by vibration-related thermal effects, as observed in our system, is sufficiently slow in time; therefore, the instant frequency can be determined using two measures of the resonance frequency: immediately before and after the EPI time series and linear interpolation in between. We demonstrate that these measurements can be used to correct the observed frequency drift during EPI experiments by linear phase correction of the EPI k-space data. This approach does not significantly increase the overall scan ...