The MNI data-sharing and processing ecosystem

AbstractNeuroimaging 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

Propofol requirement and EEG alpha band power during general anesthesia provide complementary views on preoperative cognitive decline

Background: Although cognitive decline (CD) is associated with increased post-operative morbidity and mortality, routinely screening patients remains difficult. The main objective of this prospective study is to use the EEG response to a Propofol-based general anesthesia (GA) to reveal CD. Methods: 42 patients with collected EEG and Propofol target concentration infusion (TCI) during GA had a preoperative cognitive assessment using MoCA. We evaluated the performance of three variables to detect CD (MoCA < 25 points): age, Propofol requirement to induce unconsciousness (TCI at SEF95: 8–13 Hz) and the frontal alpha band power (AP at SEF95: 8–13 Hz). Results: The 17 patients (40%) with CD were significantly older (p < 0.001), had lower TCI (p < 0.001), and AP (p < 0.001). We found using logistic models that TCI and AP were the best set of variables associated with CD (AUC: 0.89) and performed better than age (p < 0.05). Propofol TCI had a greater impact on CD probability compared to AP, although both were complementary in detecting CD. Conclusion: TCI and AP contribute additively to reveal patient with preoperative cognitive decline. Further research on post-operative cognitive trajectory are necessary to confirm the interest of intra operative variables in addition or as a substitute to cognitive evaluation

Open video data sharing in developmental and behavioural science

Video recording is a widely used method for documenting infant and child behaviours in research and clinical practice. Video data has rarely been shared due to ethical concerns of confidentiality, although the need of shared large-scaled datasets remains increasing. This demand is even more imperative when data-driven computer-based approaches are involved, such as screening tools to complement clinical assessments. To share data while abiding by privacy protection rules, a critical question arises whether efforts at data de-identification reduce data utility? We addressed this question by showcasing the Prechtl's general movements assessment (GMA), an established and globally practised video-based diagnostic tool in early infancy for detecting neurological deficits, such as cerebral palsy. To date, no shared expert-annotated large data repositories for infant movement analyses exist. Such datasets would massively benefit training and recalibration of human assessors and the development of computer-based approaches. In the current study, sequences from a prospective longitudinal infant cohort with a total of 19451 available general movements video snippets were randomly selected for human clinical reasoning and computer-based analysis. We demonstrated for the first time that pseudonymisation by face-blurring video recordings is a viable approach. The video redaction did not affect classification accuracy for either human assessors or computer vision methods, suggesting an adequate and easy-to-apply solution for sharing movement video data. We call for further explorations into efficient and privacy rule-conforming approaches for deidentifying video data in scientific and clinical fields beyond movement assessments. These approaches shall enable sharing and merging stand-alone video datasets into large data pools to advance science and public health

Multisite Comparison of MRI Defacing Software Across Multiple Cohorts

With improvements to both scan quality and facial recognition software, there is an increased risk of participants being identified by a 3D render of their structural neuroimaging scans, even when all other personal information has been removed. To prevent this, facial features should be removed before data are shared or openly released, but while there are several publicly available software algorithms to do this, there has been no comprehensive review of their accuracy within the general population. To address this, we tested multiple algorithms on 300 scans from three neuroscience research projects, funded in part by the Ontario Brain Institute, to cover a wide range of ages (3–85 years) and multiple patient cohorts. While skull stripping is more thorough at removing identifiable features, we focused mainly on defacing software, as skull stripping also removes potentially useful information, which may be required for future analyses. We tested six publicly available algorithms (afni_refacer, deepdefacer, mri_deface, mridefacer, pydeface, quickshear), with one skull stripper (FreeSurfer) included for comparison. Accuracy was measured through a pass/fail system with two criteria; one, that all facial features had been removed and two, that no brain tissue was removed in the process. A subset of defaced scans were also run through several preprocessing pipelines to ensure that none of the algorithms would alter the resulting outputs. We found that the success rates varied strongly between defacers, with afni_refacer (89%) and pydeface (83%) having the highest rates, overall. In both cases, the primary source of failure came from a single dataset that the defacer appeared to struggle with - the youngest cohort (3–20 years) for afni_refacer and the oldest (44–85 years) for pydeface, demonstrating that defacer performance not only depends on the data provided, but that this effect varies between algorithms. While there were some very minor differences between the preprocessing results for defaced and original scans, none of these were significant and were within the range of variation between using different NIfTI converters, or using raw DICOM files

Focusing on Comorbidity A Novel Meta-Analytic Approach and Protocol to Disentangle the Specific Neuroanatomy of Co-occurring Mental Disorders

Background: In mental health, comorbidities are the norm rather than the exception. However, current meta-analytic methods for summarizing the neural correlates of mental disorders do not consider comorbidities, reducing them to a source of noise and bias rather than benefitting from their valuable information. Objectives: We describe and validate a novel neuroimaging meta-analytic approach that focuses on comorbidities. In addition, we present the protocol for a meta-analysis of all major mental disorders and their comorbidities. Methods: The novel approach consists of a modification of Seed-based d Mapping with Permutation of Subject Images (SDM-PSI) in which the linear models have no intercept. As in previous SDM meta-analyses, the dependent variable is the brain anatomical difference between patients and controls in a voxel. However, there is no primary disorder, and the independent variables are the percentages of patients with each disorder and each pair of potentially comorbid disorders. We use simulations to validate and provide an example of this novel approach, which correctly disentangled the abnormalities associated with each disorder and comorbidity. We then describe a protocol for conducting the new meta-analysis of all major mental disorders and their comorbidities. Specifically, we will include all voxel-based morphometry (VBM) studies of mental disorders for which a meta-analysis has already been published, including at least 10 studies. We will use the novel approach to analyze all included studies in two separate single linear models, one for children/adolescents and one for adults. Discussion: The novel approach is a valid method to focus on comorbidities. The meta-analysis will yield a comprehensive atlas of the neuroanatomy of all major mental disorders and their comorbidities, which we hope might help develop potential diagnostic and therapeutic tools

Braak neurofibrillary tangle staging prediction from in vivo MRI metrics

INTRODUCTION: Alzheimer’s disease (AD) diagnosis requires postmortem visualization of amyloid and tau deposits. As brain atrophy can provide assessment of consequent neurodegeneration, our objective was to predict postmortem neurofibrillary tangles (NFT) from in vivo MRI measurements. METHODS: All participants with neuroimaging and neuropathological data from the Alzheimer’s Disease Neuroimaging Initiative, the National Alzheimer’s Coordinating Center and the Rush Memory and Aging Project were selected (n=186). 232 variables were extracted from last MRI before death using FreeSurfer. Nonparametric correlation analysis and multivariable support vector machine classification were performed to provide a predictive model of Braak NFT staging. RESULTS: We demonstrated that 59 of our MRI variables, mostly temporal lobe structures, were significantly associated with Braak NFT stages (p<.005). We obtained a 62.4% correct classification rate for discrimination between transentorhinal, limbic and isocortical groups. DISCUSSION: Structural neuroimaging may therefore be considered as a potential biomarker for early detection of AD-associated neurofibrillary degeneration

Resisting Sleep Pressure:Impact on Resting State Functional Network Connectivity

In today's 24/7 society, sleep restriction is a common phenomenon which leads to increased levels of sleep pressure in daily life. However, the magnitude and extent of impairment of brain functioning due to increased sleep pressure is still not completely understood. Resting state network (RSN) analyses have become increasingly popular because they allow us to investigate brain activity patterns in the absence of a specific task and to identify changes under different levels of vigilance (e.g. due to increased sleep pressure). RSNs are commonly derived from BOLD fMRI signals but studies progressively also employ cerebral blood flow (CBF) signals. To investigate the impact of sleep pressure on RSNs, we examined RSNs of participants under high (19 h awake) and normal (10 h awake) sleep pressure with three imaging modalities (arterial spin labeling, BOLD, pseudo BOLD) while providing confirmation of vigilance states in most conditions. We demonstrated that CBF and pseudo BOLD signals (measured with arterial spin labeling) are suited to derive independent component analysis based RSNs. The spatial map differences of these RSNs were rather small, suggesting a strong biological substrate underlying these networks. Interestingly, increased sleep pressure, namely longer time awake, specifically changed the functional network connectivity (FNC) between RSNs. In summary, all FNCs of the default mode network with any other network or component showed increasing effects as a function of increased 'time awake'. All other FNCs became more anti-correlated with increased 'time awake'. The sensorimotor networks were the only ones who showed a within network change of FNC, namely decreased connectivity as function of 'time awake'. These specific changes of FNC could reflect both compensatory mechanisms aiming to fight sleep as well as a first reduction of consciousness while becoming drowsy. We think that the specific changes observed in functional network connectivity could imply an impairment of information transfer between the affected RSNs

Time domain, near-infrared diffuse optical methods for path length resolved, non-invasive measurement of deep-tissue blood flow

The non-invasive and, often, continuous measurement of the hemodynamics of the body, and for the main purposes of this thesis, the brain, is desired because both the instantaneous values and their changes over time constantly adapt to the conditions affecting the body and its environment. They are altered in pathological situations and in response to increased function. It is desirable for these measurements to be continuous, reliable, minimally invasive, and relatively inexpensive. In recent years, optical techniques that, by using diffusing and deep-reaching (up to few centimeters) light at skin-safe levels of intensity, combine the aforementioned characteristics, have increasingly become used in clinical and research settings. However, to date there is, on one side the need to expand the number and scope of translational studies, and, on the other, to address shortcomings like the contamination of signals from unwanted tissue volumes (partial volume effects). A further important goal is to increase the depth of penetration of light without affecting the non-invasive nature of diffuse optics. My PhD was aimed at several aspects of this problem; (i) the development of new, more advanced methods, i.e. the time/pathlength resolved, to improve the differentiation between superficial and deeper tissues layers, (ii) the exploration of new application areas, i.e. to characterize the microvascular status of bones, to study the functional response of the baby brain, and (iii) to improve the quality control of the systems , i.e. by introducing a long shelf-life dynamic phantom. In conceptual order, first I introduce long shelf-life reference standards for diffuse correlation spectroscopy. Secondly, I describe the use of an existing hybrid time domain and diffuse correlation spectroscopy system to monitor the changes that some pathological conditions, in this case osteoporosis and human immunodeficiency virus infection, may have on many aspects of the human bone tissue that are currently not easy to measure (i.e. invasively assessed) by conventional techniques. Thirdly, I describe the development of a novel time domain optical technique that intimately combines, introducing many previously unmet advancements, the two previously cited optical spectroscopy techniques. For the first time I was able to produce a time domain device and protocol that can monitor the blood flow in vivo in the head and muscles of healthy humans. Lastly, I describe a device and method that I have used to monitor changes in blood flow in healthy human infants of three to five months of age, for the first time in this age bracket, as a marker of activation following visual stimulation. Overall, this work pushes the limit of the technology that makes use of diffuse light to minimally invasively, continuously, and reliably monitor endogenous markers of pathological and physiological processes in the human body.La medición no invasiva y, a menudo, continua de la hemodinámica del cuerpo, y para los propósitos principales de esta tesis, del cerebro, es conveniente porque tanto los valores instantáneos como sus variaciones en el tiempo se adaptan constantemente a las condiciones que afectan el cuerpo humano y su entorno. Estas suelen alterarse en situaciones patológicas o como respuesta a una mayor función. Es deseable que estas mediciones sean continuas, confiables, mínimamente invasivas y relativamente asequibles. En los últimos años, las técnicas ópticas que, mediante el uso de luz difusa para medir los tejidos en profundidad (hasta unos pocos centímetros) mediante niveles de intensidad que son seguros para la piel, combinan las características arriba mencionadas, se han utilizado cada vez más tanto en entornos clínicos como de investigación. Sin embargo, al día de hoy hay, por un lado, la necesidad de ampliar el número y el ámbito de los estudios translacionales y, por el otro, de suplir a las deficiencias como por ejemplo la contaminación de volúmenes de tejido no deseados (efectos de volumen parcial). Otro objetivo importante es aumentar la profundidad de penetración de la luz sin afectar la naturaleza no invasiva de la óptica difusa. Mi doctorado está destinado a mejorar varios aspectos de este problema; (i) el desarrollo de nuevos métodos más avanzados, es decir, el método resuelto en el tiempo/trayectoria de los fotones, para mejorar la diferenciación entre los tejidos superficiales y profundos, (ii) la exploración de nuevas áreas de aplicación, es decir, para caracterizar el estado microvascular de los huesos, para estudiar la respuesta funcional del cerebro en los niños, y (iii) para mejorar el control de calidad de los sistemas, es decir, mediante la introducción de un phantom dinámico de larga vida útil. En orden conceptual, primero voy a introducir estándares de referencia de larga vida útil para la espectroscopia de correlación difusa (DCS). En segundo lugar, voy a describir el uso de un sistema híbrido espectroscopia tiempo-resuelta (TRS) con DCS ya existente para monitorizar los cambios que algunas condiciones patológicas, en este caso la osteoporosis y la infección por el virus de la inmunodeficiencia humana, pueden comportar para muchos aspectos del tejido óseo humano que actualmente no se pueden medir con facilidad (es decir, se van evaluado de forma invasiva) mediante técnicas convencionales. En tercer lugar, voy a describir el desarrollo de una novedosa técnica óptica en el dominio temporal que combina íntimamente, introduciendo muchos avances previamente no cumplidos, TRS y DCS. Por primera vez pude producir un dispositivo y un protocolo tiempo-resueltos para medir el flujo de la sangre en la cabeza y en los músculos de seres humanos sanos. Por último, en esta tesis voy a describir un dispositivo y un método que he usado para monitorear los cambios en el flujo sanguíneo como marcadores de activación del cerebro debida a estímulos visivos en bebés entre tres y cinco meses de edad. En general, este trabajo amplia los limites de la tecnología que hace uso de la luz difusa para monitorizar, de forma mínimamente invasiva, continua y confiable los marcadores endógenos de procesos patológicos y fisiológicos en el cuerpo humano.Postprint (published version

A consensus guide to using functional near-infrared spectroscopy in posture and gait research

BACKGROUND: Functional near-infrared spectroscopy (fNIRS) is increasingly used in the field of posture and gait to investigate patterns of cortical brain activation while people move freely. fNIRS methods, analysis and reporting of data vary greatly across studies which in turn can limit the replication of research, interpretation of findings and comparison across works. RESEARCH QUESTION AND METHODS: Considering these issues, we propose a set of practical recommendations for the conduct and reporting of fNIRS studies in posture and gait, acknowledging specific challenges related to clinical groups with posture and gait disorders. RESULTS: Our paper is organized around three main sections: 1) hardware set up and study protocols, 2) artefact removal and data processing and, 3) outcome measures, validity and reliability; it is supplemented with a detailed checklist. SIGNIFICANCE: This paper was written by a core group of members of the International Society for Posture and Gait Research and posture and gait researchers, all experienced in fNIRS research, with the intent of assisting the research community to lead innovative and impactful fNIRS studies in the field of posture and gait, whilst ensuring standardization of research

Performance of Humans vs. Exploration Algorithms on the Tower of London Test

The Tower of London Test (TOL) used to assess executive functions was inspired in Artificial Intelligence tasks used to test problem-solving algorithms. In this study, we compare the performance of humans and of exploration algorithms. Instead of absolute execution times, we focus on how the execution time varies with the tasks and/or the number of moves. This approach used in Algorithmic Complexity provides a fair comparison between humans and computers, although humans are several orders of magnitude slower. On easy tasks (1 to 5 moves), healthy elderly persons performed like exploration algorithms using bounded memory resources, i.e., the execution time grew exponentially with the number of moves. This result was replicated with a group of healthy young participants. However, for difficult tasks (5 to 8 moves) the execution time of young participants did not increase significantly, whereas for exploration algorithms, the execution time keeps on increasing exponentially. A pre-and post-test control task showed a 25% improvement of visuo-motor skills but this was insufficient to explain this result. The findings suggest that naive participants used systematic exploration to solve the problem but under the effect of practice, they developed markedly more efficient strategies using the information acquired during the test