The rate of progress in human neurosciences is limited by the inability to easily apply a wide range of analysis methods to the plethora of different datasets acquired in labs around the world. In this work, we introduce a framework for creating, testing, versioning and archiving portable applications for analyzing neuroimaging data organized and described in compliance with the Brain Imaging Data Structure (BIDS). The portability of these applications (BIDS Apps) is achieved by using container technologies that encapsulate all binary and other dependencies in one convenient package. BIDS Apps run on all three major operating systems with no need for complex setup and configuration and thanks to the comprehensiveness of the BIDS standard they require little manual user input. Previous containerized data processing solutions were limited to single user environments and not compatible with most multi-tenant High Performance Computing systems. BIDS Apps overcome this limitation by taking advantage of the Singularity container technology. As a proof of concept, this work is accompanied by 22 ready to use BIDS Apps, packaging a diverse set of commonly used neuroimaging algorithms. Magnetic Resonance Imaging (MRI) is a non-invasive way to measure human brain structure and activity that has been used for over 25 years. There are thousands MRI studies performed every year generating a substantial amount of data. At the same time, many new data analysis methods are being developed every year. The potential of using new analysis methods on the variety of existing and newly acquired data is hindered by difficulties in software deployment and lack of support for standardized input data. Here we propose to use container technology to make deployment of a wide range of data analysis techniques easy. In addition, we adapt the existing data analysis tools to interface with data organized in a standardized way. We hope that this approach will enable researchers to access a wider range of methods when analyzing their data which will lead to accelerated progress in human neuroscience.

Magnetic resonance guided focused ultrasound (MRgFUS) thalamotomy is a novel and minimally invasive ablative treatment for essential tremor. The size and location of therapeutic lesions producing the optimal clinical benefits while minimizing adverse effects are not known. We examined these relationships in patients with essential tremor undergoing MRgFUS. We studied 66 patients with essential tremor who underwent MRgFUS between 2012 and 2017. We assessed the Clinical Rating Scale for Tremor (CRST) scores at 3 months after the procedure and tracked the adverse effects (sensory, motor, speech, gait, and dysmetria) 1 day (acute) and 3 months after the procedure. Clinical data associated with the postoperative Day 1 lesions were used to correlate the size and location of lesions with tremor benefit and acute adverse effects. Diffusion-weighted imaging was used to assess whether acute adverse effects were related to lesions encroaching on nearby major white matter tracts (medial lemniscus, pyramidal, and dentato-rubro-thalamic). The area of optimal tremor response at 3 months after the procedure was identified at the posterior portion of the ventral intermediate nucleus. Lesions extending beyond the posterior region of the ventral intermediate nucleus and lateral to the lateral thalamic border were associated with increased risk of acute adverse sensory and motor effects, respectively. Acute adverse effects on gait and dysmetria occurred with lesions inferolateral to the thalamus. Lesions inferolateral to the thalamus or medial to the ventral intermediate nucleus were also associated with acute adverse speech effects. Diffusion-weighted imaging revealed that lesions associated with adverse sensory and gait/dysmetria effects compromised the medial lemniscus and dentato-rubro-thalamic tracts, respectively. Lesions associated with adverse motor and speech effects encroached on the pyramidal tract. Lesions larger than 170 mm3 were associated with an increased risk of acute adverse effects. Tremor improvement and acute adverse effects of MRgFUS for essential tremor are highly dependent on the location and size of lesions. These novel findings could refine current MRgFUS treatment planning and targeting, thereby improving clinical outcomes in patients.

There is growing recognition that connectome architecture shapes cortical and subcortical gray matter atrophy across a spectrum of neurological and psychiatric diseases. Whether connectivity contributes to tissue volume loss in schizophrenia in the same manner remains unknown. Here, we relate tissue volume loss in patients with schizophrenia to patterns of structural and functional connectivity. Gray matter deformation was estimated in a sample of 133 individuals with chronic schizophrenia (48 women, mean age 34.7 ± 12.9 years) and 113 control subjects (64 women, mean age 23.5 ± 8.4 years). Deformation-based morphometry was used to estimate cortical and subcortical gray matter deformation from T1-weighted magnetic resonance images. Structural and functional connectivity patterns were derived from an independent sample of 70 healthy participants using diffusion spectrum imaging and resting-state functional magnetic resonance imaging. We found that regional deformation is correlated with the deformation of structurally and functionally connected neighbors. Distributed deformation patterns are circumscribed by specific functional systems (the ventral attention network) and cytoarchitectonic classes (limbic class), with an epicenter in the anterior cingulate cortex. Altogether, the present study demonstrates that brain tissue volume loss in schizophrenia is conditioned by structural and functional connectivity, accounting for 25% to 35% of regional variance in deformation.