Web-based processing of physiological noise in fMRI: addition of the PhysIO toolbox to CBRAIN

Neuroimaging research requires sophisticated tools for analyzing complex data, but efficiently leveraging these tools can be a major challenge, especially on large datasets. CBRAIN is a web-based platform designed to simplify the use and accessibility of neuroimaging research tools for large-scale, collaborative studies. In this paper, we describe how CBRAIN's unique features and infrastructure were leveraged to integrate TAPAS PhysIO, an open-source MATLAB toolbox for physiological noise modeling in fMRI data. This case study highlights three key elements of CBRAIN's infrastructure that enable streamlined, multimodal tool integration: a user-friendly GUI, a Brain Imaging Data Structure (BIDS) data-entry schema, and convenient in-browser visualization of results. By incorporating PhysIO into CBRAIN, we achieved significant improvements in the speed, ease of use, and scalability of physiological preprocessing. Researchers now have access to a uniform and intuitive interface for analyzing data, which facilitates remote and collaborative evaluation of results. With these improvements, CBRAIN aims to become an essential open-science tool for integrative neuroimaging research, supporting FAIR principles and enabling efficient workflows for complex analysis pipelines.

The association between information and communication technologies, loneliness and social connectedness: A scoping review

Older adults are at a higher risk of loneliness, compared to other demographics. The use of Internet Communication and Technologies (ICTs) among older adults is steadily increasing and given ICTs provide a means of enhancing social connectedness suggests they may have positive effects on reducing loneliness. Therefore, the aim of this scoping review was to examine the research that explores how ICTs may be implicated in mitigating loneliness and increasing social connectedness among older adults. After the examination of 54 articles, we identified three major themes within the literature: (1) ICTs were associated with a reduction in loneliness and increase in wellbeing. (2) ICTs promoted social connectedness by facilitating conversations. (3) Factors such as training, self-efficacy, self-esteem, autonomy, and the design/features, or affordances, of ICTs contribute toward the associations between ICT use and wellbeing. The heterogeneity of methodologies, statistical reporting, the small sample sizes of interventional and observational studies, and the diversity of the experimental contexts underline the challenges of quantitative research in this field and highlights the necessity of tailoring ICT interventions to the needs and contexts of the older users.

Effect of spinal anesthesia-induced deafferentation on pain processing in healthy male volunteers: A task-related fMRI study

BACKGROUND

Spinal anesthesia causes short-term deafferentation and alters the crosstalk among brain regions involved in pain perception and pain modulation. In the current study, we examined the effect of spinal anesthesia on pain response to noxious thermal stimuli in non-deafferented skin areas using a functional magnetic resonance imaging (fMRI) paradigm.

METHODS

Twenty-two healthy subjects participated in the study. We performed a task-based fMRI study using a randomized crossover design. Subjects were scanned under two conditions (spinal anesthesia or control) at two-time points: before and after spinal anesthesia. Spinal anesthesia resulted in sensory loss up to dermatome Th6. Calibrated heat-pain stimuli were administered to the right forearm (C8-Th1) using a box-car design (blocks of 10s on/25s off) during MRI scanning. Pain perception was measured using a visual analogue scale (1-100) at the beginning and the end of each session. Generalized estimating equations were used to examine the effect of intervention by time by order on pain scores. Similarly, higher-level effects were tested with appropriate general linear models (accounting for within-subject variations in session and time) to examine: (1) Differences in BOLD response to pain stimulus under spinal anesthesia versus control; and (2) Effects of spinal anesthesia on pain-related modulation of the cerebral activation.

RESULTS

Complete fMRI data was available for eighteen participants. Spinal anesthesia was associated with moderate pain score increase. Significant differences in brain response to noxious thermal stimuli were present in comparison of spinal versus control condition (post-pre). Spinal condition was associated with higher BOLD signal in the bilateral inferior parietal lobule and lower BOLD signal in bilateral postcentral and precentral gyrus. Within the angular regions, we observed a positive correlation between pain scores and BOLD signal. These observations were independent from order effect (whether the spinal anesthesia was administered in the first or the second visit). However, we did observe order effect on brain regions including medial prefrontal regions, possibly related to anticipation of the experience of spinal anesthesia.

CONCLUSIONS

The loss of sensory and motor activity caused by spinal anesthesia has a significant impact on brain regions involved in the sensorimotor and cognitive processing of noxious heat pain stimuli. Our results indicate that the anticipation or experience of a strong somatosensory response to the spinal intervention might confound and contribute to increased sensitivity to cognitive pain processing. Future studies must account for individual differences in subjective experience of pain sensation within the experimental context.

Toward a digital citizen lab for capturing data about alternative ways of self-managing chronic pain: An attitudinal user study

Background

Myriad psychosocial and cultural factors influence personal ways of coping with chronic pain (CP). Mobile health (mHealth) apps facilitate creation of citizen laboratories outside clinical frameworks. However, issues of safety, privacy and technostress must be addressed. This attitudinal user study aimed to assess whether persons with persistent pain (PwPP) would be open to sharing qualitative and quantitative data about their self-management of CP via mHealth platforms.

Methods

In March 2020, we invited PwPPs, their personal or medical caregivers, or those interested in the development of an app for researching alternative ways of self-managing CP to complete an anonymous survey. We formulated an attitudinal survey within the theoretical framework of stress to estimate whether the novelty, unpredictability, and risks of data-sharing via mHealth apps concerned users. Descriptive statistics (% Part/Group) were used to interpret the survey, and open comments were reflectively analyzed to identify emerging themes.

Results

Of 202 responses (June 2021), 127 identified as PwPPs (average age 43.86 ± 14.97; 100/127 female), and listed several primary and secondary CP diagnoses. In almost 90% of PwPPs, physical and emotional wellbeing were affected by CP. More than 90% of PwPPs used alternative therapies (acupuncture, homeopathy, massage therapy, etc.). Attitude toward mHealth apps were positive even though nearly half of PwPPs were unfamiliar with them. More than 72% of respondents were open to using a health-related app as a research tool for data collection in real life situations. Comprehensive data collection (especially about psychosocial factors) was the most important requirement. More respondents (especially medical professionals) were concerned about health hazards of misinformation communicated via health-related information and communication systems (maximum 80%) than about privacy (maximum 40%). Qualitative analyses revealed several promises and impediments to creation of data-sharing platforms for CP.

Conclusions

This study shows a general willingness among PwPPs to become partners in studying alternative pain management. Despite a generally positive attitude toward the concept of sharing complex personal data to advance research, heterogeneity of attitudes shaped by personal experiences must be considered. Our study underlines the need for any digital strategy for CP research to be person-centered and flexible.

Play the Pain: A Digital Strategy for Play-Oriented Research and Action

The value of understanding patients' illness experience and social contexts for advancing medicine and clinical care is widely acknowledged. However, methodologies for rigorous and inclusive data gathering and integrative analysis of biomedical, cultural, and social factors are limited. In this paper, we propose a digital strategy for large-scale qualitative health research, using play (as a state of being, a communication mode or context, and a set of imaginative, expressive, and game-like activities) as a research method for recursive learning and action planning. Our proposal builds on Gregory Bateson's cybernetic approach to knowledge production. Using chronic pain as an example, we show how pragmatic, structural and cultural constraints that define the relationship of patients to the healthcare system can give rise to conflicted messaging that impedes inclusive health research. We then review existing literature to illustrate how different types of play including games, chatbots, virtual worlds, and creative art making can contribute to research in chronic pain. Inspired by Frederick Steier's application of Bateson's theory to designing a science museum, we propose DiSPORA (Digital Strategy for Play-Oriented Research and Action), a virtual citizen science laboratory which provides a framework for delivering health information, tools for play-based experimentation, and data collection capacity, but is flexible in allowing participants to choose the mode and the extent of their interaction. Combined with other data management platforms used in epidemiological studies of neuropsychiatric illness, DiSPORA offers a tool for large-scale qualitative research, digital phenotyping, and advancing personalized medicine.

A Simulation Toolkit for Testing the Sensitivity and Accuracy of Corticometry Pipelines

In recent years, the replicability of neuroimaging findings has become an important concern to the research community. Neuroimaging pipelines consist of myriad numerical procedures, which can have a cumulative effect on the accuracy of findings. To address this problem, we propose a method for simulating artificial lesions in the brain in order to estimate the sensitivity and specificity of lesion detection, using different automated corticometry pipelines. We have applied this method to different versions of two widely used neuroimaging pipelines (CIVET and FreeSurfer), in terms of coefficients of variation; sensitivity and specificity of detecting lesions in 4 different regions of interest in the cortex, while introducing variations to the lesion size, the blurring kernel used prior to statistical analyses, and different thickness metrics (in CIVET). These variations are tested in a between-subject design (in two random groups, with and without lesions, using T1-weigted MRIs of 152 individuals from the International Consortium of Brain Mapping (ICBM) dataset) and in a within-subject pre-/post-lesion design [using 21 T1-Weighted MRIs of a single adult individual, scanned in the Infant Brain Imaging Study (IBIS)]. The simulation method is sensitive to partial volume effect and lesion size. Comparisons between pipelines illustrate the ability of this method to uncover differences in sensitivity and specificity of lesion detection. We propose that this method be adopted in the workflow of software development and release.

What Media Helps, What Media Hurts: A Mixed Methods Survey Study of Coping with COVID-19 Using the Media Repertoire Framework and the Appraisal Theory of Stress

Background

Social and physical distancing in response to the coronavirus disease (COVID-19) pandemic has made screen-mediated information and communication technologies (media) indispensable. Whether an increase in screen use is a source of or a relief for stress remains to be seen.

Objective

In the immediate aftermath of the COVID-19 lockdowns, we investigated the relation between subjective stress and changes in the pattern of media use. Based on Lazarus’s transactional model of appraisal and coping, and building on an earlier similar survey, we hypothesize that individual differences in the appraisal of media predict variations in approach or avoidance of media for coping with COVID-19 stress.

Methods

Between March 20 and April 20, 2020, a brief snowball survey entitled: “What media helps, what media hurts: coping with COVID19 through screens” was distributed via Concordia University’s mailing lists and social media (PERFORM Centre, EngAGE Centre, and Media Health Lab). Using a media repertoire method, we asked questions about preferences, changes in use, and personal appraisal of media experiences (approach, avoid, and ignore) as a result of the COVID-19 pandemic and investigated interindividual differences in media use by factors such as subjective stress, age, gender, and self-reported mental health.

Results

More than 90% of the survey respondents were in Canada and the east coast of the United States. From 685 completed responses, 169 respondents were “very stressed” and 452 were “slightly worried” about the pandemic. COVID-19 stress led to increased use of Facebook (χ²₃=11.76, P=.008), television (χ²₃=12.40, P=.006), YouTube (χ²₃=8.577, P=.04), and streaming services such as Netflix (χ²₃=10.71, P=.01). Respondents who considered their mental health “not good” were twice as likely to prefer streaming services as a coping tool for self-isolation. Women and nonbinary respondents were twice as likely than men to pick social media for coping. Individuals younger than 35 years were 3 times more likely to pick computer games, and individuals older than 55 years were more likely to pick network television or print media. Gender affected the appraisal of media (less in men than others) in terms of avoid (F_1,637=5.84, P=.02) and approach scores (F_1,637=14.31, P<.001). Subjective mental health affected the ignore score (less in those who said “good” than others; F_1,637=13.88, P<.001). The appraisal score and use increase explained variations in worrying about physical and mental health stress due to increased screen time. A qualitative analysis of open-ended questions revealed that media (especially social networks) were important for coping if they provided support and connection through the dissemination of factual and positive information while avoiding the overflow of sensational and false news.

Conclusions

The relationship between appraisal of media’s positive and negative facets vary with demographic differences in mental health resiliency. The media repertoire approach is an important tool in studies that focus on assessing the benefits and harms of screen overuse in different populations, especially in the context of the COVID-19 pandemic.

Changes in Eating Behaviors and Confidence Towards Cooking After an 8-Week Online Cooking and Nutrition Tutorials in Adults Living with an Overweight Condition or Obesity

Objectives

This study tested the impact of online cooking and nutrition tutorials on eating behaviours and psychosocial determinants of cooking skills among adults living with an overweight condition or obesity.

Methods

Healthy adults 18–65 y living with an overweight condition or obesity (25 &lt; body mass index [BMI] &lt; 40 kg/m2) living in the greater Montreal (Quebec) Canada were randomized (1:1:1) to one of three groups: Control [Ctrl; weekly delivery of food with paper-based recipes], Nutrition [weekly delivery of food, access to online cooking and nutrition tutorials] or Behaviour [weekly delivery of food, access to online cooking and eating behaviour tutorials] over 8 weeks. Cooking and education videos were &lt;4 min long total and were viewed through private YouTube links. At baseline and 8 weeks, anthropometrics and sociodemographic were surveyed, as were appetitive traits (i.e., Food Responsiveness, Hunger, Emotional Overeating, Enjoyment of Food, Satiety Responsiveness, Food Fussiness, Emotional Undereating and Slowness in Eating) using the Adult Eating Behavior Questionnaire [AEBQ]. Cooking barriers and confidence towards cooking, confidence in consuming fruits and vegetables and self-efficacy were also assessed. Mixed model ANOVAs were used to test for differences among groups over time.

Results

At baseline, forty-eight participants with a mean age of 34.0 ± 12.9 y and BMI of 30.2 ± 4.5 kg/m2 were enrolled. Significant differences were seen in the Slowness in Eating subscale between Behaviour (1.64 ± 0.98) and Ctrl (2.46 ± 0.88) (P &lt; 0.02). At 8 weeks, Emotional Overeating scores significantly decreased in both Nutrition and Behaviour compared to Ctrl (P = 0.03). Other AEBQ subscales did not vary by time or group. From baseline to 8 weeks, all groups significantly increased scores for confidence towards cooking (P &lt; 0.001), confidence in consuming of fruits and vegetables (P &lt; 0.001) and general self-efficacy (P &lt; 0.001).

Conclusions

The weekly provision of food baskets with online cooking and nutrition tutorials elicited changes in eating behaviours in adults living with an overweight condition and obesity. Future studies including a long-term follow-up and larger sample size are needed to confirm these positive findings.

Funding Sources

R. Howard Webster Foundation.

Reflective and Reflexive Stress Responses of Older Adults to Three Gaming Experiences In Relation to Their Cognitive Abilities: Mixed Methods Crossover Study

BACKGROUND

The gamification of digital health provisions for older adults (eg, for rehabilitation) is a growing trend; however, many older adults are not familiar with digital games. This lack of experience could cause stress and thus impede participants' motivations to adopt these technologies.

OBJECTIVE

This crossover longitudinal multifactorial study aimed to examine the interactions between game difficulty, appraisal, cognitive ability, and physiological and cognitive responses that indicate game stress using the Affective Game Planning for Health Applications framework.

METHODS

A total of 18 volunteers (mean age 71 years, SD 4.5; 12 women) completed a three-session study to evaluate different genres of games in increasing order of difficulty (S₁-BrainGame, S₂-CarRace, and S₃-Exergame). Each session included an identical sequence of activities (t₁-Baseline, t₂-Picture encode, t₃-Play, t₄-Stroop test, t₅-Play, and t₆-Picture recall), a repeated sampling of salivary cortisol, and time-tagged ambulatory data from a wrist-worn device. Generalized estimating equations were used to investigate the effect of session×activity or session×activity×cognitive ability on physiology and cognitive performance. Scores derived from the Montreal Cognitive Assessment (MoCA) test were used to define cognitive ability (MoCA-high: MoCA>27, n=11/18). Kruskal-Wallis tests were used to test session or session×group effects on the scores of the postgame appraisal questionnaire.

RESULTS

Session×activity effects were significant on all ambulatory measures (χ²₁₀>20; P<.001) other than cortisol (P=.37). Compared with S₁ and S₂, S₃ was associated with approximately 10 bpm higher heart rate (P<.001) and approximately 5 muS higher electrodermal activity (P<.001), which were both independent of the movement caused by the exergame. Compared with S₁, we measured a moderate but statistically significant drop in the rate of hits in immediate recall and rate of delayed recall in S₃. The low-MoCA group did not differ from the high-MoCA group in general characteristics (age, general self-efficacy, and perceived stress) but was more likely to agree with statements such as digital games are too hard to learn. In addition, the low-MoCA group was more likely to dislike the gaming experience and find it useless, uninteresting, and visually more intense (χ²₁>4; P<.04). Group differences in ambulatory signals did not reach statistical significance; however, the rate of cortisol decline with respect to the baseline was significantly larger in the low-MoCA group.

CONCLUSIONS

Our results show that the experience of playing digital games was not stressful for our participants. Comparatively, the neurophysiological effects of exergame were more pronounced in the low-MoCA group, suggesting greater potential of this genre of games for cognitive and physical stimulation by gamified interventions; however, the need for enjoyment of this type of challenging game must be addressed.

Affective Game Planning for Health Applications: Quantitative Extension of Gerontoludic Design Based on the Appraisal Theory of Stress and Coping

User retention is the first challenge in introducing any information and communication technologies (ICT) for health applications, particularly for seniors who are increasingly targeted as beneficiaries of such technologies. Interaction with digital technologies may be too stressful to older adults to guarantee their adoption in their routine selfcare. The second challenge, which also relates to adoption, is to supply empirical evidence that support the expectations of their beneficial outcomes. To address the first challenge, persuasive technologies such as serious games (SGs) are increasingly promoted as ludic approaches to deliver assistive care to older adults. However, there are no standards yet to assess the efficacy of different genres of games across populations, or compare and contrast variations in health outcomes arising from user interface design and user experience. For the past 3 decades, research has focused either on qualitative assessment of the appeal of digital games for seniors (by game designers) or on the quantitative evaluation of their clinical efficacy (by clinical researchers). The consensus is that interindividual differences play a key role in whether games can be useful or not for different individuals. Our challenge is to design SGs that retain their users long enough to sustain beneficial transfer effects. We propose to add a neuropsychological experimental framework (based on the appraisal theory of stress and coping) to a Gerontoludic design framework (that emphasizes designing positive and meaningful gaming experience over benefit-centric ones) in order to capture data to guide SG game development. Affective Game Planning for Health Applications (AGPHA) adds a model-driven mixed-methods experimental stage to a user-centered mechanics-dynamics-aesthetics game-design cycle. This intersectoral framework is inspired by latest trends in the fields of neuroimaging and neuroinformatics that grapple with similar challenges related to the psychobiological context of an individual's behaviors. AGPHA aims to bring users, designers, clinicians, and researchers together to generate a common data repository that consists of 4 components to define, design, evaluate, and document SGs. By unifying efforts under a standard approach, we will accelerate innovations in persuasive and efficacious ICTs for the aging population.

To Each Stress Its Own Screen: A Cross-Sectional Survey of the Patterns of Stress and Various Screen Uses in Relation to Self-Admitted Screen Addiction

BACKGROUND

The relationship between stress and screen addiction is often studied by exploring a single aspect of screen-related behavior in terms of maladaptive dependency or the risks associated with the content. Generally, little attention is given to the pattern of using different screens for different types of stressors, and variations arising from the subjective perception of stress and screen addiction are often neglected. Given that both addiction and stress are complex and multidimensional factors, we performed a multivariate analysis of the link between individual's subjective perceptions of screen addiction, various types of stress, and the pattern of screen usage.

OBJECTIVE

Using the media-repertoires framework to study usage patterns, we explored (1) the relation between subjective and quantitative assessments of stress and screen addiction; and (2) differences in stress types in relation to subjective screen addiction and different types of needs for screens. We hypothesized that interindividual heterogeneity in screen-related behavior would reflect coping differences in dealing with different stressors.

METHODS

A multifactorial Web-based survey was conducted to gather data about screen-related behaviors (such as screen time, internet addiction, and salience of different types of screens and related activities), and different sources of stress (emotional states, perceptual risks, health problems, and general life domain satisfaction). We performed group comparisons based on whether participants reported themselves as addicted to internet and games (A1) or not (A0), and whether they had experienced a major life stress (S1) or not (S0).

RESULTS

Complete responses were obtained in 459 out of 654 survey responders, with the majority in the S1A0 (44.6%, 205/459) group, followed by S0A0 (25.9%, 119/459), S1A1 (19.8%, 91/459), and S0A1 (9.5%, 44/459). The S1A1 group was significantly different from S0A0 in all types of stress, internet overuse, and screen time (P<.001). Groups did not differ in rating screens important for short message service (SMS) or mail, searching information, shopping, and following the news, but a greater majority of A1 depended on screens for entertainment (χ²₃=20.5; P<.001), gaming (χ²₃=35.6; P<.001), and social networking (χ²₃=26.5; P<.001). Those who depended on screens for entertainment and social networking had up to 19% more emotional stress and up to 14% more perceptual stress. In contrast, those who relied on screens for work and professional networking had up to 10% higher levels of life satisfaction. Regression models including age, gender, and 4 stress types explained less than 30% of variation in internet use and less than 24% of the likelihood of being screen addicted.

CONCLUSIONS

We showed a robust but heterogeneous link between screen dependency and emotional and perceptual stressors that shift the pattern of screen usage toward entertainment and social networking. Our findings underline the potential of using ludic and interactive apps for intervention against stress.

Biomarkers, designs, and interpretations of resting-state fMRI in translational pharmacological research: A review of state-of-the-Art, challenges, and opportunities for studying brain chemistry

A decade of research and development in resting-state functional MRI (RSfMRI) has opened new translational and clinical research frontiers. This review aims to bridge between technical and clinical researchers who seek reliable neuroimaging biomarkers for studying drug interactions with the brain. About 85 pharma-RSfMRI studies using BOLD signal (75% of all) or arterial spin labeling (ASL) were surveyed to investigate the acute effects of psychoactive drugs. Experimental designs and objectives include drug fingerprinting dose-response evaluation, biomarker validation and calibration, and translational studies. Common biomarkers in these studies include functional connectivity, graph metrics, cerebral blood flow and the amplitude and spectrum of BOLD fluctuations. Overall, RSfMRI-derived biomarkers seem to be sensitive to spatiotemporal dynamics of drug interactions with the brain. However, drugs cause both central and peripheral effects, thus exacerbate difficulties related to biological confounds, structured noise from motion and physiological confounds, as well as modeling and inference testing. Currently, these issues are not well explored, and heterogeneities in experimental design, data acquisition and preprocessing make comparative or meta-analysis of existing reports impossible. A unifying collaborative framework for data-sharing and data-mining is thus necessary for investigating the commonalities and differences in biomarker sensitivity and specificity, and establishing guidelines. Multimodal datasets including sham-placebo or active control sessions and repeated measurements of various psychometric, physiological, metabolic and neuroimaging phenotypes are essential for pharmacokinetic/pharmacodynamic modeling and interpretation of the findings. We provide a list of basic minimum and advanced options that can be considered in design and analyses of future pharma-RSfMRI studies. Hum Brain Mapp 38:2276-2325, 2017. © 2017 Wiley Periodicals, Inc.

Cyberinfrastructure for Open Science at the Montreal Neurological Institute

Data sharing is becoming more of a requirement as technologies mature and as global research and communications diversify. As a result, researchers are looking for practical solutions, not only to enhance scientific collaborations, but also to acquire larger amounts of data, and to access specialized datasets. In many cases, the realities of data acquisition present a significant burden, therefore gaining access to public datasets allows for more robust analyses and broadly enriched data exploration. To answer this demand, the Montreal Neurological Institute has announced its commitment to Open Science, harnessing the power of making both clinical and research data available to the world (Owens, 2016a,b). As such, the LORIS and CBRAIN (Das et al., 2016) platforms have been tasked with the technical challenges specific to the institutional-level implementation of open data sharing, including: Comprehensive linking of multimodal data (phenotypic, clinical, neuroimaging, biobanking, and genomics, etc.)Secure database encryption, specifically designed for institutional and multi-project data sharing, ensuring subject confidentiality (using multi-tiered identifiers).Querying capabilities with multiple levels of single study and institutional permissions, allowing public data sharing for all consented and de-identified subject data.Configurable pipelines and flags to facilitate acquisition and analysis, as well as access to High Performance Computing clusters for rapid data processing and sharing of software tools.Robust Workflows and Quality Control mechanisms ensuring transparency and consistency in best practices.Long term storage (and web access) of data, reducing loss of institutional data assets.Enhanced web-based visualization of imaging, genomic, and phenotypic data, allowing for real-time viewing and manipulation of data from anywhere in the world.Numerous modules for data filtering, summary statistics, and personalized and configurable dashboards. Implementing the vision of Open Science at the Montreal Neurological Institute will be a concerted undertaking that seeks to facilitate data sharing for the global research community. Our goal is to utilize the years of experience in multi-site collaborative research infrastructure to implement the technical requirements to achieve this level of public data sharing in a practical yet robust manner, in support of accelerating scientific discovery.

2015 Brainhack Proceedings

I1 Introduction to the 2015 Brainhack Proceedings

R. Cameron Craddock, Pierre Bellec, Daniel S. Margules, B. Nolan Nichols, Jörg P. Pfannmöller

A1 Distributed collaboration: the case for the enhancement of Brainspell’s interface

AmanPreet Badhwar, David Kennedy, Jean-Baptiste Poline, Roberto Toro

A2 Advancing open science through NiData

Ben Cipollini, Ariel Rokem

A3 Integrating the Brain Imaging Data Structure (BIDS) standard into C-PAC

Daniel Clark, Krzysztof J. Gorgolewski, R. Cameron Craddock

A4 Optimized implementations of voxel-wise degree centrality and local functional connectivity density mapping in AFNI

R. Cameron Craddock, Daniel J. Clark

A5 LORIS: DICOM anonymizer

Samir Das, Cécile Madjar, Ayan Sengupta, Zia Mohades

A6 Automatic extraction of academic collaborations in neuroimaging

Sebastien Dery

A7 NiftyView: a zero-footprint web application for viewing DICOM and NIfTI files

Weiran Deng

A8 Human Connectome Project Minimal Preprocessing Pipelines to Nipype

Eric Earl, Damion V. Demeter, Kate Mills, Glad Mihai, Luka Ruzic, Nick Ketz, Andrew Reineberg, Marianne C. Reddan, Anne-Lise Goddings, Javier Gonzalez-Castillo, Krzysztof J. Gorgolewski

A9 Generating music with resting-state fMRI data

Caroline Froehlich, Gil Dekel, Daniel S. Margulies, R. Cameron Craddock

A10 Highly comparable time-series analysis in Nitime

Ben D. Fulcher

A11 Nipype interfaces in CBRAIN

Tristan Glatard, Samir Das, Reza Adalat, Natacha Beck, Rémi Bernard, Najmeh Khalili-Mahani, Pierre Rioux, Marc-Étienne Rousseau, Alan C. Evans

A12 DueCredit: automated collection of citations for software, methods, and data

Yaroslav O. Halchenko, Matteo Visconti di Oleggio Castello

A13 Open source low-cost device to register dog’s heart rate and tail movement

Raúl Hernández-Pérez, Edgar A. Morales, Laura V. Cuaya

A14 Calculating the Laterality Index Using FSL for Stroke Neuroimaging Data

Kaori L. Ito, Sook-Lei Liew

A15 Wrapping FreeSurfer 6 for use in high-performance computing environments

Hans J. Johnson

A16 Facilitating big data meta-analyses for clinical neuroimaging through ENIGMA wrapper scripts

Erik Kan, Julia Anglin, Michael Borich, Neda Jahanshad, Paul Thompson, Sook-Lei Liew

A17 A cortical surface-based geodesic distance package for Python

Daniel S Margulies, Marcel Falkiewicz, Julia M Huntenburg

A18 Sharing data in the cloud

David O’Connor, Daniel J. Clark, Michael P. Milham, R. Cameron Craddock

A19 Detecting task-based fMRI compliance using plan abandonment techniques

Ramon Fraga Pereira, Anibal Sólon Heinsfeld, Alexandre Rosa Franco, Augusto Buchweitz, Felipe Meneguzzi

A20 Self-organization and brain function

Jörg P. Pfannmöller, Rickson Mesquita, Luis C.T. Herrera, Daniela Dentico

A21 The Neuroimaging Data Model (NIDM) API

Vanessa Sochat, B Nolan Nichols

A22 NeuroView: a customizable browser-base utility

Anibal Sólon Heinsfeld, Alexandre Rosa Franco, Augusto Buchweitz, Felipe Meneguzzi

A23 DIPY: Brain tissue classification

Julio E. Villalon-Reina, Eleftherios Garyfallidis

MINC 2.0: A Flexible Format for Multi-Modal Images

It is often useful that an imaging data format can afford rich metadata, be flexible, scale to very large file sizes, support multi-modal data, and have strong inbuilt mechanisms for data provenance. Beginning in 1992, MINC was developed as a system for flexible, self-documenting representation of neuroscientific imaging data with arbitrary orientation and dimensionality. The MINC system incorporates three broad components: a file format specification, a programming library, and a growing set of tools. In the early 2000's the MINC developers created MINC 2.0, which added support for 64-bit file sizes, internal compression, and a number of other modern features. Because of its extensible design, it has been easy to incorporate details of provenance in the header metadata, including an explicit processing history, unique identifiers, and vendor-specific scanner settings. This makes MINC ideal for use in large scale imaging studies and databases. It also makes it easy to adapt to new scanning sequences and modalities.

Subjective Effects of Ethanol, Morphine, Δ(9)-Tetrahydrocannabinol, and Ketamine Following a Pharmacological Challenge Are Related to Functional Brain Connectivity

This analysis examines the neuronal foundation of drug-induced psychomimetic symptoms by relating the severity of these symptoms to changes in functional connectivity for a range of different psychoactive compounds with varying degrees of psychomimetic effects. The repeated measures design included 323 resting-state functional magnetic resonance imaging time series and measures of subjective effects in 36 healthy male volunteers. Four different pharmacological challenges with ethanol, morphine, Δ(9)-tetrahydrocannabinol, and ketamine (12 subjects per drug) were applied. A set of 10 "template" resting-state networks was used to determine individual connectivity maps. Linear regression was used for each individual subject to relate these connectivity maps to three clusters of drug-induced subjective psychomimetic effects ("perception," "relaxation," and "dysphoria") as measured with visual analogue scales. Group analysis showed that the subjective effects of perception correlated significantly across drugs with the connectivity of the posterior cingulate cortex and precentral gyrus with the sensorimotor network (p < 0.005, corrected). No significant correlations were found for relaxation or dysphoria. The posterior cingulate cortex has a role in visuospatial evaluation and the precentral gyrus has been associated with auditory hallucinations. Both the posterior cingulate cortex and the precentral gyrus show changes in activation in patients with schizophrenia, which can be related to the severity of positive symptoms (i.e., hallucinations and delusions), and have previously been related to changes induced by psychoactive drugs. The similarity of functional connectivity changes for drug-induced psychomimetic effects and symptoms of psychosis provides further support for the use of pharmacological challenges with psychomimetic drugs as models for psychosis.

The MNI data-sharing and processing ecosystem

Neuroimaging has been facing a data deluge characterized by the exponential growth of both raw and processed data. As a result, mining the massive quantities of digital data collected in these studies offers unprecedented opportunities and has become paramount for today's research. As the neuroimaging community enters the world of "Big Data", there has been a concerted push for enhanced sharing initiatives, whether within a multisite study, across studies, or federated and shared publicly. This article will focus on the database and processing ecosystem developed at the Montreal Neurological Institute (MNI) to support multicenter data acquisition both nationally and internationally, create database repositories, facilitate data-sharing initiatives, and leverage existing software toolkits for large-scale data processing.

Single-dose serotonergic stimulation shows widespread effects on functional brain connectivity

The serotonergic system is widely distributed throughout the central nervous system. It is well known as a mood regulating system, although it also contributes to many other functions. With resting state functional magnetic resonance imaging (RS-fMRI) it is possible to investigate whole brain functional connectivity. We used this non-invasive neuroimaging technique to measure acute pharmacological effects of the selective serotonin reuptake inhibitor sertraline (75 mg) in 12 healthy volunteers. In this randomized, double blind, placebo-controlled, crossover study, RS-fMRI scans were repeatedly acquired during both visits (at baseline and 3, 5, 7 and 9h after administering sertraline or placebo). Within-group comparisons of voxelwise functional connectivity with ten functional networks were examined (p<0.005, corrected) using a mixed effects model with cerebrospinal fluid, white matter, motion parameters, heart rate and respiration as covariates. Sertraline induced widespread effects on functional connectivity with multiple networks; the default mode network, the executive control network, visual networks, the sensorimotor network and the auditory network. A common factor among these networks was the involvement of the precuneus and posterior cingulate cortex. Cognitive and subjective measures were taken as well, but yielded no significant treatment effects, emphasizing the sensitivity of RS-fMRI to pharmacological challenges. The results are consistent with the existence of an extensive serotonergic system relating to multiple brain functions with a possible key role for the precuneus and cingulate.

Reproducibility of neuroimaging analyses across operating systems

Neuroimaging pipelines are known to generate different results depending on the computing platform where they are compiled and executed. We quantify these differences for brain tissue classification, fMRI analysis, and cortical thickness (CT) extraction, using three of the main neuroimaging packages (FSL, Freesurfer and CIVET) and different versions of GNU/Linux. We also identify some causes of these differences using library and system call interception. We find that these packages use mathematical functions based on single-precision floating-point arithmetic whose implementations in operating systems continue to evolve. While these differences have little or no impact on simple analysis pipelines such as brain extraction and cortical tissue classification, their accumulation creates important differences in longer pipelines such as subcortical tissue classification, fMRI analysis, and cortical thickness extraction. With FSL, most Dice coefficients between subcortical classifications obtained on different operating systems remain above 0.9, but values as low as 0.59 are observed. Independent component analyses (ICA) of fMRI data differ between operating systems in one third of the tested subjects, due to differences in motion correction. With Freesurfer and CIVET, in some brain regions we find an effect of build or operating system on cortical thickness. A first step to correct these reproducibility issues would be to use more precise representations of floating-point numbers in the critical sections of the pipelines. The numerical stability of pipelines should also be reviewed.

Effect of deafferentation from spinal anesthesia on pain sensitivity and resting-state functional brain connectivity in healthy male volunteers

Patients may perceive paradoxical heat sensation during spinal anesthesia. This could be due to deafferentation-related functional changes at cortical, subcortical, or spinal levels. In the current study, the effect of spinal deafferentation on sensory (pain) sensitivity was studied and linked to whole-brain functional connectivity as assessed by resting-state functional magnetic resonance imaging (RS-fMRI) imaging. Deafferentation was induced by sham or spinal anesthesia (15 mg bupivacaine injected at L3-4) in 12 male volunteers. RS-fMRI brain connectivity was determined in relation to eight predefined and seven thalamic resting-state networks (RSNs) and measured before, and 1 and 2 h after spinal/sham injection. To measure the effect of deafferentation on pain sensitivity, responses to heat pain were measured at 15-min intervals on nondeafferented skin and correlated to RS-fMRI connectivity data. Spinal anesthesia altered functional brain connectivity within brain regions involved in the sensory discriminative (i.e., pain intensity related) and affective dimensions of pain perception in relation to somatosensory and thalamic RSNs. A significant enhancement of pain sensitivity on nondeafferented skin was observed after spinal anesthesia compared to sham (area-under-the-curve [mean (SEM)]: 190.4 [33.8] versus 13.7 [7.2]; p<0.001), which significantly correlated to functional connectivity changes observed within the thalamus in relation to the thalamo-prefrontal network, and in the anterior cingulate cortex and insula in relation to the thalamo-parietal network. Enhanced pain sensitivity from spinal deafferentation correlated with functional connectivity changes within brain regions involved in affective and sensory pain processing and areas involved in descending control of pain.

Ketamine interactions with biomarkers of stress: a randomized placebo-controlled repeated measures resting-state fMRI and PCASL pilot study in healthy men

Ketamine, an NMDA receptor antagonist, is increasingly used to study the link between glutamatergic signaling dysregulation and mood and chronic pain disorders. Glutamatergic neurotransmission and stress corticosteroids (cortisol in human) are critical for Ca(2+) mediated neuroplasticity and behavioral adaptation. The mechanisms of action of glutamatergic neurotransmission and stress corticosteroids on the NMDA-receptors of the hippocampus have been long investigated in animals, but given little attention in human studies. In this randomized single-blinded placebo-controlled crossover study (12 healthy young men), five sets of resting-state fMRI (RSFMRI), pseudocontinuous arterial spin labeling (PCASL), and corresponding salivary cortisol samples were acquired over 4h, at given intervals under pharmacokinetically-controlled infusion of subanesthetic ketamine (20 & 40mg/70kg/h). An identical procedure was repeated under a sham placebo condition. Differences in the profile of ketamine versus placebo effect over time were examined. Compared to placebo, ketamine mimicked a stress-like response (increased cortisol, reduced calmness and alertness, and impaired working memory). Ketamine effects on the brain included a transient prefrontal hyperperfusion and a dose-related reduction of relative hippocampal perfusion, plus emerging hyperconnectivity between the hippocampus and the occipital, cingulate, precuneal, cerebellar and basal ganglia regions. The spatiotemporal profiles of ketamine effects on different hippocampal subnetworks suggest a topographically dissociable change in corticohippocampal functional connectivity. We discuss our findings in the context of the negative feedback inhibition theory of the hippocampal stress-control. This pilot study provides a methodological framework for multimodal functional neuroimaging under resting-state conditions, which may be generalized for translational studies of glutamatergic- or stress-related etiology of neuropsychiatric disorders.

Spatial heterogeneity of the relation between resting-state connectivity and blood flow: an important consideration for pharmacological studies

Resting state fMRI (RSfMRI) and arterial spin labeling (ASL) provide the field of pharmacological Neuroimaging tool for investigating states of brain activity in terms of functional connectivity or cerebral blood flow (CBF). Functional connectivity reflects the degree of synchrony or correlation of spontaneous fluctuations--mostly in the blood oxygen level dependent (BOLD) signal--across brain networks; but CBF reflects mean delivery of arterial blood to the brain tissue over time. The BOLD and CBF signals are linked to common neurovascular and hemodynamic mechanisms that necessitate increased oxygen transportation to the site of neuronal activation; however, the scale and the sources of variation in static CBF and spatiotemporal BOLD correlations are likely different. We tested this hypothesis by examining the relation between CBF and resting-state-network consistency (RSNC)--representing average intranetwork connectivity, determined from dual regression analysis with eight standard networks of interest (NOIs)--in a crossover placebo-controlled study of morphine and alcohol. Overall, we observed spatially heterogeneous relations between RSNC and CBF, and between the experimental factors (drug-by-time, time, drug and physiological rates) and each of these metrics. The drug-by-time effects on CBF were significant in all networks, but significant RSNC changes were limited to the sensorimotor, the executive/salience and the working memory networks. The post-hoc voxel-wise statistics revealed similar dissociations, perhaps suggesting differential sensitivity of RSNC and CBF to neuronal and vascular endpoints of drug actions. The spatial heterogeneity of RSNC/CBF relations encourages further investigation into the role of neuroreceptor distribution and cerebrovascular anatomy in predicting spontaneous fluctuations under drugs.

The impact of "physiological correction" on functional connectivity analysis of pharmacological resting state fMRI

Growing interest in pharmacological resting state fMRI (RSfMRI) necessitates developing standardized and robust analytical approaches that are insensitive to spurious correlated physiological signals. However, in pharmacological experiments physiological variations constitute an important aspect of the pharmacodynamic/pharmacokinetic profile of drug action; therefore retrospective corrective methods that discard physiological signals as noise may not be suitable. Previously, we have shown that template-based dual regression analysis is a sensitive method for model-free and objective detection of drug-specific effects on functional brain connectivity. In the current study, the robustness of this standard approach to physiological variations in a placebo controlled, repeated measures pharmacological RSfMRI study of morphine and alcohol in 12 healthy young men is tested. The impact of physiology-related variations on statistical inferences has been studied by: 1) modeling average physiological rates in higher level group analysis; 2) Regressing out the instantaneous respiration variation (RV); 3) applying retrospective image correction (RETROICOR) in the preprocessing stage; and 4) performing combined RV and heart rate correction (RVHRCOR) by regressing out physiological pulses convolved with canonical respiratory and cardiac hemodynamic response functions. Results indicate regional sensitivity of the BOLD signal to physiological variations, especially in the vicinity of large vessels, plus certain brain structures that are reported to be involved in physiological regulation, such as posterior cingulate, precuneus, medial prefrontal and insular cortices, as well as the thalamus, cerebellum and the brainstem. The largest impact of "correction" on final statistical test outcomes resulted from including the average respiration frequency and heart rate in the higher-level group analysis. Overall, the template-based dual regression method seems robust against physical noise that is corrected by RV regression or RETROICOR. However, convolving the RV and HR with canonical hemodynamic response functions caused a notable change in the BOLD signal variance, and in resting state connectivity estimates. The impact of RVHRCOR on statistical tests was limited to elimination of both morphine and alcohol effects related to the somatosensory network that consists of insula and cingulate cortex-important structures for autonomic regulation. Although our data do not warrant speculations about neuronal or vascular origins of these effects, these observations raise caution about the implications of physiological 'noise' and the risks of introducing false positives (e.g. increased white matter connectivity) by using generalized physiological correction methods in pharmacological studies. The obvious sensitivity of the posterior part of the default mode network to different correction schemes, underlines the importance of controlling for physiological fluctuations in seed-based functional connectivity analyses.

Manipulating brain connectivity with δ⁹-tetrahydrocannabinol: a pharmacological resting state FMRI study

Resting state-functional magnetic resonance imaging (RS-FMRI) is a neuroimaging technique that allows repeated assessments of functional connectivity in resting state. While task-related FMRI is limited to indirectly measured drug effects in areas affected by the task, resting state can show direct CNS effects across all brain networks. Hence, RS-FMRI could be an objective measure for compounds affecting the CNS. Several studies on the effects of cannabinoid receptor type 1 (CB(1))-receptor agonist δ(9)-tetrahydrocannabinol (THC) on task-dependent FMRI have been performed. However, no studies on the effects of cannabinoids on resting state networks using RS-FMRI have been published. Therefore, we investigated the effects of THC on functional brain connectivity using RS-FMRI. Twelve healthy volunteers (9 male, 3 female) inhaled 2, 6 and 6 mg THC or placebo with 90-minute intervals in a randomized, double blind, cross-over trial. Eight RS-FMRI scans of 8 min were obtained per occasion. Subjects rated subjective psychedelic effects on a visual analog scale after each scan, as pharmacodynamic effect measures. Drug-induced effects on functional connectivity were examined using dual regression with FSL software (FMRIB Analysis Group, Oxford). Eight maps of voxel-wise connectivity throughout the entire brain were provided per RS-FMRI series with eight predefined resting-state networks of interest. These maps were used in a mixed effects model group analysis to determine brain regions with a statistically significant drug-by-time interaction. Statistical images were cluster-corrected, and results were Bonferroni-corrected across multiple contrasts. THC administration increased functional connectivity in the sensorimotor network, and was associated with dissociable lateralized connectivity changes in the right and left dorsal visual stream networks. The brain regions showing connectivity changes included the cerebellum and dorsal frontal cortical regions. Clear increases were found for feeling high, external perception, heart rate and cortisol, whereas prolactin decreased. This study shows that THC induces both increases and (to a lesser extent) decreases in functional brain connectivity, mainly in brain regions with high densities of CB(1)-receptors. Some of the involved regions could be functionally related to robust THC-induced CNS-effects that have been found in previous studies (Zuurman et al., 2008), such as postural stability, feeling high and altered time perception.

Effects of morphine and alcohol on functional brain connectivity during "resting state": a placebo-controlled crossover study in healthy young men

A major challenge in central nervous system (CNS) drug research is to develop a generally applicable methodology for repeated measurements of drug effects on the entire CNS, without task-related interactions and a priori models. For this reason, data-driven resting-state fMRI methods are promising for pharmacological research. This study aimed to investigate whether different psychoactive substances cause drug-specific effects in functional brain connectivity during resting-state. In this double blind placebo-controlled (double dummy) crossover study, seven resting-state fMRI scans were obtained in 12 healthy young men in three different drug sessions (placebo, morphine and alcohol; randomized). Drugs were administered intravenously based on validated pharmacokinetic protocols to minimize the inter- and intra-subject variance in plasma drug concentrations. Dual-regression was used to estimate whole-brain resting-state connectivity in relation to eight well-characterized resting-state networks, for each data set. A mixed effects analysis of drug by time interactions revealed dissociable changes in both pharmacodynamics and functional connectivity resulting from alcohol and morphine. Post hoc analysis of regions of interest revealed adaptive network interactions in relation to pharmacokinetic and pharmacodynamic curves. Our results illustrate the applicability of resting-state functional brain connectivity in CNS drug research.

Hippocampal activation during a cognitive task is associated with subsequent neuroendocrine and cognitive responses to psychological stress

Increased activation of the hypothalamus pituitary adrenal (HPA) axis, marked by increased secretion of cortisol, is a biological marker of psychological stress. It is well established that the hippocampus plays an important role in the regulation of HPA axis activity. The relationship between cortisol (stress-related elevation or exogenous administration) and the hippocampal-related cognitive function is often examined. However, few human studies to date have examined the effect of stress on hippocampal activity and the interactions between stress-induced activation of the HPA axis and hippocampal function during different phases of cognitive function. On the basis of our previous work, we hypothesized that group differences in stress-sensitivity relate to differences in hippocampal-related stress-integration. To test this hypothesis, we conducted a functional MRI study using tasks known to involve the hippocampal formation: novel-picture encoding, psychological stress, and paired-picture recognition. On the basis of their cortisol responses to stress, we divided subjects into stress-responders (increase in cortisol, n = 9) and nonresponders (decrease in cortisol, n = 10). Responders showed higher hippocampal deactivation during the stress task and lower recognition scores due to a larger number of misses. Intriguingly, stress-responders showed significant differences in hippocampal activation already prior to stress, with higher levels of hippocampal activity during the picture encoding. Although effects of both cortisol and hippocampal activation on recognition were present in responders, similar effects were absent in the nonresponder group. Our results indicate that hippocampus plays an important role in adaptive behavioral responses. We hypothesize that states of hippocampal activation prior to stress might reflect states of vigilance or anxiety, which might be important for determining interindividual differences in subsequent stress response and cognitive performance.

Deactivation of the limbic system during acute psychosocial stress: evidence from positron emission tomography and functional magnetic resonance imaging studies

BACKGROUND

Stress-induced metabolic changes can have detrimental health effects. Newly developed paradigms to investigate stress in neuroimaging environments allow the assessment of brain activation changes in association with the perception of and the metabolic response to stress.

METHODS

We exposed human subjects to a psychosocial stressor in one positron emission tomography (n = 10) and one functional magnetic resonance imaging (fMRI; n = 40) experiment.

RESULTS

We observed a profound deactivation of limbic system components including hippocampus, hypothalamus, medio-orbitofrontal cortex and anterior cingulate cortex in subjects who reacted to the stressor with a significant increase of the endocrine stress marker cortisol. Further, in the fMRI study, the degree of deactivation in the hippocampus was correlated with the release of cortisol in response to the stress task.

CONCLUSIONS

The observed deactivation of limbic system structures suggests elevated activation at rest and during nonstressful situations. A model is proposed where the observed reduction in limbic system activity is essential for the initiation of the stress response.