A comparison of neuroelectrophysiology databases

As data sharing has become more prevalent, three pillars - archives, standards, and analysis tools - have emerged as critical components in facilitating effective data sharing and collaboration. This paper compares four freely available intracranial neuroelectrophysiology data repositories: Data Archive for the BRAIN Initiative (DABI), Distributed Archives for Neurophysiology Data Integration (DANDI), OpenNeuro, and Brain-CODE. The aim of this review is to describe archives that provide researchers with tools to store, share, and reanalyze both human and non-human neurophysiology data based on criteria that are of interest to the neuroscientific community. The Brain Imaging Data Structure (BIDS) and Neurodata Without Borders (NWB) are utilized by these archives to make data more accessible to researchers by implementing a common standard. As the necessity for integrating large-scale analysis into data repository platforms continues to grow within the neuroscientific community, this article will highlight the various analytical and customizable tools developed within the chosen archives that may advance the field of neuroinformatics.

A Comparison of Neuroelectrophysiology Databases

As data sharing has become more prevalent, three pillars - archives, standards, and analysis tools - have emerged as critical components in facilitating effective data sharing and collaboration. This paper compares four freely available intracranial neuroelectrophysiology data repositories: Data Archive for the BRAIN Initiative (DABI), Distributed Archives for Neurophysiology Data Integration (DANDI), OpenNeuro, and Brain-CODE. The aim of this review is to describe archives that provide researchers with tools to store, share, and reanalyze both human and non-human neurophysiology data based on criteria that are of interest to the neuroscientific community. The Brain Imaging Data Structure (BIDS) and Neurodata Without Borders (NWB) are utilized by these archives to make data more accessible to researchers by implementing a common standard. As the necessity for integrating large-scale analysis into data repository platforms continues to grow within the neuroscientific community, this article will highlight the various analytical and customizable tools developed within the chosen archives that may advance the field of neuroinformatics.

FAIR in action: Brain-CODE - A neuroscience data sharing platform to accelerate brain research

The effective sharing of health research data within the healthcare ecosystem can have tremendous impact on the advancement of disease understanding, prevention, treatment, and monitoring. By combining and reusing health research data, increasingly rich insights can be made about patients and populations that feed back into the health system resulting in more effective best practices and better patient outcomes. To achieve the promise of a learning health system, data needs to meet the FAIR principles of findability, accessibility, interoperability, and reusability. Since the inception of the Brain-CODE platform and services in 2012, the Ontario Brain Institute (OBI) has pioneered data sharing activities aligned with FAIR principles in neuroscience. Here, we describe how Brain-CODE has operationalized data sharing according to the FAIR principles. Findable-Brain-CODE offers an interactive and itemized approach for requesters to generate data cuts of interest that align with their research questions. Accessible-Brain-CODE offers multiple data access mechanisms. These mechanisms-that distinguish between metadata access, data access within a secure computing environment on Brain-CODE and data access via export will be discussed. Interoperable-Standardization happens at the data capture level and the data release stage to allow integration with similar data elements. Reusable - Brain-CODE implements several quality assurances measures and controls to maximize data value for reusability. We will highlight the successes and challenges of a FAIR-focused neuroinformatics platform that facilitates the widespread collection and sharing of neuroscience research data for learning health systems.

Data and Tools Integration in the Canadian Open Neuroscience Platform

We present the Canadian Open Neuroscience Platform (CONP) portal to answer the research community's need for flexible data sharing resources and provide advanced tools for search and processing infrastructure capacity. This portal differs from previous data sharing projects as it integrates datasets originating from a number of already existing platforms or databases through DataLad, a file level data integrity and access layer. The portal is also an entry point for searching and accessing a large number of standardized and containerized software and links to a computing infrastructure. It leverages community standards to help document and facilitate reuse of both datasets and tools, and already shows a growing community adoption giving access to more than 60 neuroscience datasets and over 70 tools. The CONP portal demonstrates the feasibility and offers a model of a distributed data and tool management system across 17 institutions throughout Canada.

Validating a novel deterministic privacy-preserving record linkage between administrative & clinical data: applications in stroke research

IntroductionResearch data combined with administrative data provides a robust resource capable of answering unique research questions. However, in cases where personal health data are encrypted, due to ethics requirements or institutional restrictions, traditional methods of deterministic and probabilistic record linkages are not feasible. Instead, privacy-preserving record linkages must be used to protect patients' personal data during data linkage. ObjectivesTo determine the feasibility and validity of a deterministic privacy preserving data linkage protocol using homomorphically encrypted data. MethodsFeasibility was measured by the number of records that successfully matched via direct identifiers. Validity was measured by the number of records that matched with multiple indirect identifiers. The threshold for feasibility and validity were both set at 95%. The datasets shared a single, direct identifier (health card number) and multiple indirect identifiers (sex and date of birth). Direct identifiers were encrypted in both datasets and then transferred to a third-party server capable of linking the encrypted identifiers without decrypting individual records. Once linked, the study team used indirect identifiers to verify the accuracy of the linkage in the final dataset. ResultsWith a combination of manual and automated data transfer in a sample of 8,128 individuals, the privacy-preserving data linkage took 36 days to match to a population sample of over 3.2 million records. 99.9% of the records were successfully matched with direct identifiers, and 99.8% successfully matched with multiple indirect identifiers. We deemed the linkage both feasible and valid. ConclusionsAs combining administrative and research data becomes increasingly common, it is imperative to understand options for linking data when direct linkage is not feasible. The current linkage process ensured the privacy and security of patient data and improved data quality. While the initial implementations required significant computational and human resources, increased automation keeps the requirements within feasible bounds.

Correlation between Cranial Nerve Microstructural Characteristics and Vestibular Schwannoma Tumor Volume

BACKGROUND AND PURPOSE

Vestibular schwannomas are common cerebellopontine angle tumors arising from the vestibulocochlear nerve and can result in cranial nerve dysfunction. Conventional MR imaging does not provide information that could correlate with cranial nerve compression symptoms of hearing loss or imbalance. We used multitensor tractography to evaluate the relationship between the WM microstructural properties of cranial nerves and tumor volume in a cohort of patients with vestibular schwannomas.

MATERIALS AND METHODS

A retrospective study was performed in 258 patients with vestibular schwannomas treated at the Gamma Knife clinic at Toronto Western Hospital between 2014 and 2018. 3T MR images were analyzed in 160 surgically naïve patients with unilateral vestibular schwannomas. Multitensor tractography was used to extract DTI-derived metrics (fractional anisotropy and radial, axial, and mean diffusivities of the bilateral facial and vestibulocochlear nerves [cranial nerves VII/VIII]). ROIs were placed in the transition between cisternal and intracanalicular segments, and images were analyzed using the eXtended Streamline Tractography reconstruction method. Diffusion metrics were correlated with 3D tumor volume derived from the Gamma Knife clinic.

RESULTS

DTI analyses revealed significantly higher fractional anisotropy values and a reduction in axial diffusivity, radial diffusivity, and mean diffusivity (all P < .001) within the affected cranial nerves VII and VIII compared with unaffected side. All specific diffusivities (axial, radial, and mean diffusivity) demonstrated an inverse correlation with tumor volume (axial, radial, and mean diffusivity, P < .01).

CONCLUSIONS

Multitensor tractography allows the quantification of cranial nerve VII and VIII WM microstructural alterations in patients with vestibular schwannomas. Our findings support the hypothesis that tumor volume may cause microstructural alterations of the affected cranial nerves VII and VIII. This type of advanced imaging may represent a possible avenue to correlate diffusivities with cranial nerve function.

Using A Privacy Preserving Record Linkage to Facilitate an Ongoing Crosswalk Between Research and Health Administrative Databases

IntroductionThe Ontario Brain Institute has developed Brain-CODE, an informatics platform designed to support the collection, storage, federation, sharing and analysis of different neuroscience research data types across several brain disorders. Linking such “deep” research data with “broad” health administrative data allows for improved characterization of disorders and supports the development of related health and social policies (Anderson et al., 2015). A privacy preserving record linkage protocol, developed through the Indoc Consortium, has been used to facilitate such linkages between Brain-CODE and administrative data holdings at the Institute for Clinical Evaluative Sciences (ICES; e.g., emergency department use, inpatient records, prescription drug utilization) (Gee et al., 2018). Objectives and ApproachThree linkage pilots in the areas of neurodevelopmental disorders, epilepsy, and stroke research have been completed with >99% success match rates across all projects. However, each of these projects required a significant amount of human and computational resources to complete. With other similar data linkages being planned, it was determined that a more permanent solution was required rather than completing linkages on a project-by-project basis. The governance and technical elements to support the creation and maintenance of such a crosswalk between Brain-CODE and ICES were reviewed with an implementation plan subsequently developed. Results:A methodology for creating a crosswalk between Brain-CODE and ICES has been established. The same privacy preserving record linkage protocol, as used in the previous linkage pilots, will support the creation of this crosswalk. A plan has been established to update this crosswalk annually to account for new study participants on Brain-CODE. Conclusion / ImplicationsThe creation of this crosswalk will allow for a more streamlined approach of data linkage between Brain-CODE and ICES. Such an approach can significantly reduce overall resourcing requirements, enable more efficient data linkages, and contribute to the coupling of “broad” and “deep” data.

Cannabis-dependent adolescents show differences in global reward-associated network topology: A functional connectomics approach

Adolescence may be a period of increased vulnerability to the onset of drug misuse and addiction due to changes in developing brain networks that support cognitive and reward processing. Cannabis is a widely misused illicit drug in adolescence which can lead to dependence and alterations in reward-related neural functioning. Concerns exist that cannabis-related alterations in these reward networks in adolescence may sensitize behaviour towards all forms of reward that increase the risk of further drug use. Taking a functional connectomics approach, we compared an acutely abstinent adolescent cannabis-dependent (CAN) group with adolescent controls (CON) on global measures of network topology associated with anticipation on a monetary incentive delay task. In the presence of overall superior accuracy, the CAN group exhibited superior global connectivity (clustering coefficient, efficiency, characteristic path length) during monetary gain anticipation compared with the CON group. Additional analyses showed that the CAN group exhibited significantly greater connectivity strength during monetary gain anticipation across a subnetwork that included mesocorticolimbic nodes involving both interhemispheric and intrahemispheric connections. We discuss how these differences in reward-associated connectivity may allude to subtle functional alterations in network architecture in adolescent cannabis-dependence that could enhance the motivation for nondrug reward during acute abstinence.

Big Data Needs Big Governance: Best Practices From Brain-CODE, the Ontario-Brain Institute's Neuroinformatics Platform

The Ontario Brain Institute (OBI) has begun to catalyze scientific discovery in the field of neuroscience through its large-scale informatics platform, known as Brain-CODE. The platform supports the capture, storage, federation, sharing, and analysis of different data types across several brain disorders. Underlying the platform is a robust and scalable data governance structure which allows for the flexibility to advance scientific understanding, while protecting the privacy of research participants. Recognizing the value of an open science approach to enabling discovery, the governance structure was designed not only to support collaborative research programs, but also to support open science by making all data open and accessible in the future. OBI’s rigorous approach to data sharing maintains the accessibility of research data for big discoveries without compromising privacy and security. Taking a Privacy by Design approach to both data sharing and development of the platform has allowed OBI to establish some best practices related to large-scale data sharing within Canada. The aim of this report is to highlight these best practices and develop a key open resource which may be referenced during the development of similar open science initiatives.

The CAMH Neuroinformatics Platform: A Hospital-Focused Brain-CODE Implementation

Investigations of mental illness have been enriched by the advent and maturation of neuroimaging technologies and the rapid pace and increased affordability of molecular sequencing techniques, however, the increased volume, variety and velocity of research data, presents a considerable technical and analytic challenge to curate, federate and interpret. Aggregation of high-dimensional datasets across brain disorders can increase sample sizes and may help identify underlying causes of brain dysfunction, however, additional barriers exist for effective data harmonization and integration for their combined use in research. To help realize the potential of multi-modal data integration for the study of mental illness, the Centre for Addiction and Mental Health (CAMH) constructed a centralized data capture, visualization and analytics environment—the CAMH Neuroinformatics Platform—based on the Ontario Brain Institute (OBI) Brain-CODE architecture, towards the curation of a standardized, consolidated psychiatric hospital-wide research dataset, directly coupled to high performance computing resources.

Designing and Implementing a Privacy Preserving Record Linkage Protocol

IntroductionThe Ontario Brain Institute has developed Brain-CODE, an informatics platform, to support the acquisition, storage, management and analysis of multi-modal data. The standardized research data within Brain-CODE spans several brain disorders, allowing for integrative analyses, while also providing the opportunity to leverage existing clinical administrative data holdings through external linkages. Objectives and ApproachWithin Ontario, the majority of individuals who access the healthcare system have a unique identifier, the Ontario Health Insurance Plan (OHIP) number. The OHIP number can facilitate linkages with administrative data holdings, such as those at the Institute for Clinical Evaluative Sciences (ICES). Given that OBI is not permitted under Ontario’s privacy legislation to hold OHIP numbers, identifiers for consented participants are encrypted using a public key mechanism upon entry into Brain-CODE, where the private key is inaccessible. To facilitate linkages involving OHIP numbers between Brain-CODE and ICES, Brain-CODE Link software was co-developed by members of the Indoc Consortium. ResultsBrain-CODE Link allows a deterministic linkage between encrypted identifiers (OHIP numbers), without revealing participant identity. The same homomorphic encryption algorithm applied to identifiers upon entry to Brain-CODE, is applied to relevant identifiers within ICES data holdings. Encrypted identifiers from Brain-CODE are securely transferred to ICES, where a comparison computation calculates differences between the encrypted sets. These differences are sent to a semi-trusted third party, who has no access to the original data, to decrypt the differences using the private key. A zero difference indicates a set of matching identifiers. One of the main challenges during testing and development of Brain-CODE Link was ensuring the software was capable of scaling to a population level, performing a large number of comparisons, in a computationally efficient manner. Conclusion/ImplicationsOngoing pilot projects within the areas of epilepsy, neurodevelopment disorders, and neurodegeneration will be the first examples of linkages between Brain-CODE and ICES. Brain-CODE Link has successfully performed several billion test comparisons, indicating its suitability to function as a scalable privacy preserving record linkage to support comprehensive analyses.

Brain-CODE: A Secure Neuroinformatics Platform for Management, Federation, Sharing and Analysis of Multi-Dimensional Neuroscience Data

Historically, research databases have existed in isolation with no practical avenue for sharing or pooling medical data into high dimensional datasets that can be efficiently compared across databases. To address this challenge, the Ontario Brain Institute’s “Brain-CODE” is a large-scale neuroinformatics platform designed to support the collection, storage, federation, sharing and analysis of different data types across several brain disorders, as a means to understand common underlying causes of brain dysfunction and develop novel approaches to treatment. By providing researchers access to aggregated datasets that they otherwise could not obtain independently, Brain-CODE incentivizes data sharing and collaboration and facilitates analyses both within and across disorders and across a wide array of data types, including clinical, neuroimaging and molecular. The Brain-CODE system architecture provides the technical capabilities to support (1) consolidated data management to securely capture, monitor and curate data, (2) privacy and security best-practices, and (3) interoperable and extensible systems that support harmonization, integration, and query across diverse data modalities and linkages to external data sources. Brain-CODE currently supports collaborative research networks focused on various brain conditions, including neurodevelopmental disorders, cerebral palsy, neurodegenerative diseases, epilepsy and mood disorders. These programs are generating large volumes of data that are integrated within Brain-CODE to support scientific inquiry and analytics across multiple brain disorders and modalities. By providing access to very large datasets on patients with different brain disorders and enabling linkages to provincial, national and international databases, Brain-CODE will help to generate new hypotheses about the biological bases of brain disorders, and ultimately promote new discoveries to improve patient care.

Comparison of Diffusion-Weighted MRI Reconstruction Methods for Visualization of Cranial Nerves in Posterior Fossa Surgery

Diffusion-weighted imaging (DWI)-based tractography has gained increasing popularity as a method for detailed visualization of white matter (WM) tracts. Different imaging techniques, and more novel, advanced imaging methods provide significant WM structural detail. While there has been greater focus on improving tract visualization for larger WM pathways, the relative value of each method for cranial nerve reconstruction and how this methodology can assist surgical decision-making is still understudied. Images from 10 patients with posterior fossa tumors (4 male, mean age: 63.5), affecting either the trigeminal nerve (CN V) or the facial/vestibular complex (CN VII/VIII), were employed. Three distinct reconstruction methods [two tensor-based methods: single diffusion tensor tractography (SDT) (3D Slicer), eXtended streamline tractography (XST), and one fiber orientation distribution (FOD)-based method: streamline tractography using constrained spherical deconvolution (CSD)-derived estimates (MRtrix3)], were compared to determine which of these was best suited for use in a neurosurgical setting in terms of processing speed, anatomical accuracy, and accurate depiction of the relationship between the tumor and affected CN. Computation of the tensor map was faster when compared to the implementation of CSD to provide estimates of FOD. Both XST and CSD-based reconstruction methods tended to give more detailed representations of the projections of CN V and CN VII/VIII compared to SDT. These reconstruction methods were able to more accurately delineate the course of CN V and CN VII/VIII, differentiate CN V from the cerebellar peduncle, and delineate compression of CN VII/VIII in situations where SDT could not. However, CSD-based reconstruction methods tended to generate more invalid streamlines. XST offers the best combination of anatomical accuracy and speed of reconstruction of cranial nerves within this patient population. Given the possible anatomical limitations of single tensor models, supplementation with more advanced tensor-based reconstruction methods might be beneficial.

Affective Circuitry Alterations in Patients with Trigeminal Neuralgia

Trigeminal neuralgia (TN) is a severe chronic neuropathic facial pain disorder. Affect-related behavioral and structural brain changes have been noted across chronic pain disorders, but have not been well-studied in TN. We examined the potential impact of TN (37 patients: 23 with right-sided TN, 14 with left-sided TN), compared to age- and sex-matched healthy controls, on three major white matter tracts responsible for carrying affect-related signals—i.e., cingulum, fornix, and medial forebrain bundle. Diffusion magnetic resonance imaging (dMRI), deterministic multi-tensor tractography for tract modeling, and a model-driven region-of-interest approach was used. We also used volumetric gray matter analysis on key targets of these pathways (i.e., hippocampus, cingulate cortex subregions, nucleus accumbens, and ventral diencephalon). Hypotheses included: (1) successful modeling of tracts; (2) altered white matter microstructure of the cingulum and medial forebrain bundle (via changes in dMRI metrics such as fractional anisotropy, and mean, axial, and radial diffusivities) compared to controls; (3) no alterations in the control region of the fornix; (4) corresponding decreases in gray matter volumes. Results showed (1) all 325 tracts were successfully modeled, although 11 were partially complete; (2) The cingulum and medial forebrain bundle (MFB) were altered in those with TN, with dMRI metric changes in the middle (p = 0.001) and posterior cingulum (p < 0.0001), and the MFB near the ventral tegmental area (MFB-VTA) (p = 0.001). The posterior cingulum and MFB-VTA also showed unilateral differences between right- and left-sided TN patients; (3) No differences were noted at any fornix subdivision; (4) decreased volumes were noted for the hippocampus, posterior cingulate, nucleus accumbens, and ventral diencephalon. Together, these results support the notion of selectively altered affective circuits in patients with TN, which may be related to the experience of negative affect and the increased comorbidity of mood and anxiety disorders in this population.

Big Data, Big Responsibility! Building best-practice privacy strategies into a large-scale neuroinformatics platform

ABSTRACT ObjectiveThe Ontario Brain Institute (OBI) has begun to catalyze scientific discovery in the field of neuroscience through its’ large-scale informatics platform, known as Brain-CODE (Centre for Ontario Data Exploration). Brain-CODE manages the acquisition, storage, processing, and analytics of multidimensional data collected from patients with a variety of brain disorders. Our vision is for the platform to act as an informatics catalyst; encouraging multidisciplinary research collaboration, data integration, and innovation in neuroscience research. Brain-CODE’s infrastructure was designed with best-practice privacy strategies built at the forefront to enable secure data capture of sensitive patient information in a manner that abides by government legislation while fostering data sharing and linking opportunities. ApproachPrivacy and security features have been incorporated into the very foundation of Brain-CODE’s comprehensive guidelines, which are reinforced by our state-of-the-art approaches to keep patient data safe. To ensure clarity for study participants, we have developed standard consent language outlining how sensitive patient data will be collected, entered, de-identified, and shared using Brain-CODE. Moreover, our tiered approach to data accessibility enables the storage of encrypted Ontario Health Card Numbers as well as other patient information, secure long-term storage of de-identified data, and data sharing opportunities by request from third parties following risk-based analysis re-identification techniques. OBI has also established a comprehensive Information Security Policy and Informatics Governance Policies, as well as a carried out a Privacy Impact Assessment and Threat Risk Assessment for Brain-CODE. ResultsBrain-CODE is proudly named a "Privacy by Design" Ambassador by the Office of the Information and Privacy Commissioner of Ontario, Canada. Moreover, approximately 200 neuroscience researchers and 35 institutions from across Canada have adopted our standard consent language to enable secure data sharing within and across neurological disorders as well as linkage opportunities with national and international databases in a secure environment. ConclusionOBI’s rigorous approach to data sharing in the field of neuroscience maintains the accessibility of research data for big discoveries without compromising patient privacy and security. We believe that Brain-CODE is a powerful and advantageous tool; moving neuroscience research from independent silos to an integrative system approach for improving patient health. OBI’s vision for improved brain health for patients living with neurological disorders paired with Brain-CODE’s best-practice strategies in privacy protection of patient data offer a novel and innovative approach to “big data” initiatives aimed towards improving public health and society world-wide.

Merged Group Tractography Evaluation with Selective Automated Group Integrated Tractography

Introduction: Tractography analysis in group-based studies across large populations has been difficult to implement. We propose Selective Automated Group Integrated Tractography (SAGIT), an automated group tractography software platform that incorporates multiple diffusion magnetic resonance imaging (dMRI) practices which will allow great accessibility to group-wise dMRI. We use a merged tractography approach that permits evaluation of tractography datasets at the group level. We also introduce an image normalized overlap score (NOS) that measures the quality of the group tractography results. We deploy SAGIT to evaluate deterministic and probabilistic constrained spherical deconvolution (CST_det, CST_prob) tractography, eXtended Streamline Tractography (XST), and diffusion tensor tractography (DTT) in their ability to delineate different neuroanatomy, as well as validating NOS across these different brain regions.

Materials and methods: Magnetic resonance sequences were acquired from 42 healthy adults. Anatomical and group registrations were performed using Automated Normalization Tools. Cortical segmentation was performed using FreeSurfer. Four tractography algorithms were used to delineate six sets of neuroanatomy: fornix, facial/vestibular-cochlear cranial nerve complex, vagus nerve, rubral–cerebellar decussation, optic radiation, and auditory radiation. The tracts were generated both with and without region of interest filters. The generated visual reports were then evaluated by five neuroscientists.

Results: At a group level, merged tractography demonstrated that different methods have different fiber distribution characteristics. CST_prob is prone to false-positives, and thereby suitable in anatomy with strong priors. CST_det and XST are more conservative, but have greater difficulty resolving hemispherical decussation and distant crossing projections. DTT consistently shows the worst reproducibility across the anatomies. Linear regression of rater scores against NOS shows significant (p < 0.05) correlation of the two sets of scores in filtered tractography. However, correlations are not significant (p > 0.05) for unfiltered tractography.

Conclusion: The tractography results demonstrated reliable and consistent performance of SAGIT across multiple subjects and techniques. Through SAGIT, we quantifiably demonstrated that different algorithms showed different strengths and weaknesses at a group level. While no single algorithm seems to be suitable for all anatomical tasks, it is useful to consider the use of a mix of algorithms for different anatomical segments. SAGIT appears to be a promising group-wise tractography analysis approach for this purpose.

MDMA 'ecstasy' increases cerebral cortical perfusion determined by bolus-tracking arterial spin labelling (btASL) MRI

BACKGROUND AND PURPOSE

The purpose of this study was to assess cerebral perfusion changes following systemic administration of the recreational drug 3,4-methylendioxymethamphetamine (MDMA 'ecstasy') to rats.

EXPERIMENTAL APPROACH

Cerebral perfusion was quantified using bolus-tracking arterial spin labelling (btASL) MRI. Rats received MDMA (20 mg·kg(-1); i.p.) and were assessed 1, 3 or 24 h later. Rats received MDMA (5 or 20 mg·kg(-1); i.p.) and were assessed 3 h later. In addition, rats received MDMA (5 or 10 mg·kg(-1); i.p.) or saline four times daily over 2 consecutive days and were assessed 8 weeks later. Perfusion-weighted images were generated in a 7 tesla (7T) MRI scanner and experimental data was fitted to a quantitative model of cerebral perfusion to generate mean transit time (MTT), capillary transit time (CTT) and signal amplitude.

KEY RESULTS

MDMA reduces MTT and CTT and increases amplitude in somatosensory and motor cortex 1 and 3 h following administration, indicative of an increase in perfusion. Prior exposure to MDMA provoked a long-term reduction in cortical 5-HT concentration, but did not produce a sustained effect on cerebral cortical perfusion. The response to acute MDMA challenge (20 mg·kg(-1); i.p.) was attenuated in these animals indicating adaptation in response to prior MDMA exposure.

CONCLUSIONS AND IMPLICATIONS

MDMA provokes changes in cortical perfusion, which are quantifiable by btASL MRI, a neuroimaging tool with translational potential. Future studies are directed towards elucidation of the mechanisms involved and correlating changes in cerebrovascular function with potential behavioural deficits associated with drug use.

Right prefrontal and ventral striatum interactions underlying impulsive choice and impulsive responding

Although a multifaceted concept, many forms of impulsivity may originate from interactions between prefrontally-mediated cognitive control mechanisms and limbic, reward or incentive salience approach processes. We describe a novel task that combines reward and control processes to probe this putative interaction. The task involves elements of the monetary incentive delay task (Knutson et al., [2000]: Neuroimage 12:20-27) and the Go/No-Go task (Garavan et al., [1999]: Neuroimage 17:1820-1829) and requires human subjects to make fast responses to targets for financial reward but to occasionally inhibit responding when a NoGo signal rather than a target is presented. In elucidating the dynamic between reward anticipation and control we observed that successful inhibitions on monetary trials, relative to unsuccessful inhibitions, were associated, during the anticipation phase, with increased activation in the right inferior frontal gyrus (rIFG), decreased activity in the ventral striatum (VS), and altered functional connectivity between the two. Notably, this rIFG area had a small overlap but was largely distinct from an adjacent rIFG region that was active for the subsequent motor response inhibitions. Combined, the results suggest a role for adjacent regions of the rIFG in impulsive choice and in impulsive responding and identify a functional coupling between the rIFG and the VS.