Search

White matter bundle segmentation using diffusion MRI fiber tractography has become the method of choice to identify white matter fiber pathways in vivo in human brains. However, like other analyses of complex data, there is considerable variability in segmentation protocols and techniques. This can result in different reconstructions of the same intended white matter pathways, which directly affects tractography results, quantification, and interpretation. In this study, we aim to evaluate and quantify the variability that arises from different protocols for bundle segmentation. Through an open call to users of fiber tractography, including anatomists, clinicians, and algorithm developers, 42 independent teams were given processed sets of human whole-brain streamlines and asked to segment 14 white matter fascicles on six subjects. In total, we received 57 different bundle segmentation protocols, which enabled detailed volume-based and streamline-based analyses of agreement and disagreement among protocols for each fiber pathway. Results show that even when given the exact same sets of underlying streamlines, the variability across protocols for bundle segmentation is greater than all other sources of variability in the virtual dissection process, including variability within protocols and variability across subjects. In order to foster the use of tractography bundle dissection in routine clinical settings, and as a fundamental analytical tool, future endeavors must aim to resolve and reduce this heterogeneity. Although external validation is needed to verify the anatomical accuracy of bundle dissections, reducing heterogeneity is a step towards reproducible research and may be achieved through the use of standard nomenclature and definitions of white matter bundles and well-chosen constraints and decisions in the dissection process.

As the global health crisis unfolded, many academic conferences moved online in 2020. This move has been hailed as a positive step towards inclusivity in its attenuation of economic, physical, and legal barriers and effectively enabled many individuals from groups that have traditionally been underrepresented to join and participate. A number of studies have outlined how moving online made it possible to gather a more global community and has increased opportunities for individuals with various constraints, e.g., caregiving responsibilities. Yet, the mere existence of online conferences is no guarantee that everyone can attend and participate meaningfully. In fact, many elements of an online conference are still significant barriers to truly diverse participation: the tools used can be inaccessible for some individuals; the scheduling choices can favour some geographical locations; the set-up of the conference can provide more visibility to well-established researchers and reduce opportunities for early-career researchers. While acknowledging the benefits of an online setting, especially for individuals who have traditionally been underrepresented or excluded, we recognize that fostering social justice requires inclusivity to actively be centered in every aspect of online conference design. Here, we draw from the literature and from our own experiences to identify practices that purposefully encourage a diverse community to attend, participate in, and lead online conferences. Reflecting on how to design more inclusive online events is especially important as multiple scientific organizations have announced that they will continue offering an online version of their event when in-person conferences can resume.

Brainhack is an innovative meeting format that promotes scientific collaboration and education in an open, inclusive environment. This NeuroView describes the myriad benefits for participants and the research community and how Brainhacks complement conventional formats to augment scientific progress.

The goal of this study was to compare brain structure between individuals with generalized anxiety disorder (GAD) and healthy controls. Previous studies have generated inconsistent findings, possibly due to small sample sizes, or clinical/analytic heterogeneity. To address these concerns, we combined data from 28 research sites worldwide through the ENIGMA-Anxiety Working Group, using a single, pre-registered mega-analysis. Structural magnetic resonance imaging data from children and adults (5-90 years) were processed using FreeSurfer. The main analysis included the regional and vertex-wise cortical thickness, cortical surface area, and subcortical volume as dependent variables, and GAD, age, age-squared, sex, and their interactions as independent variables. Nuisance variables included IQ, years of education, medication use, comorbidities, and global brain measures. The main analysis (1020 individuals with GAD and 2999 healthy controls) included random slopes per site and random intercepts per scanner. A secondary analysis (1112 individuals with GAD and 3282 healthy controls) included fixed slopes and random intercepts per scanner with the same variables. The main analysis showed no effect of GAD on brain structure, nor interactions involving GAD, age, or sex. The secondary analysis showed increased volume in the right ventral diencephalon in male individuals with GAD compared to male healthy controls, whereas female individuals with GAD did not differ from female healthy controls. This mega-analysis combining worldwide data showed that differences in brain structure related to GAD are small, possibly reflecting heterogeneity or those structural alterations are not a major component of its pathophysiology.

The autonomic nervous system (ANS) and pain exhibit a reciprocal relationship, where acute pain triggers ANS responses, whereas resting ANS activity can influence pain perception. Nociceptive signalling can also be altered by 'top‐down' processes occurring in the brain, brainstem and spinal cord, known as 'descending modulation'. By employing the conditioned pain modulation (CPM) paradigm, we previously revealed a connection between reduced low‐frequency heart rate variability and CPM. Individuals with chronic pain often experience both ANS dysregulation and impaired CPM. Baroreceptors, which contribute to blood pressure and heart rate variability regulation, may play a significant role in this relationship, although their involvement in pain perception and their functioning in chronic pain have not been sufficiently explored. In the present study, we combined artificial 'baroreceptor stimulation' in both pressure pain and CPM paradigms, seeking to explore the role of baroreceptors in pain perception and descending modulation. In total, 22 individuals with chronic low back pain (CLBP) and 29 individuals with no‐pain (NP) took part in the present study. We identified a differential modulation of baroreceptor stimulation on pressure pain between the groups of NP and CLBP participants. Specifically, NP participants perceived less pain in response to baroreflex activation, whereas CLBP participants exhibited increased pain sensitivity. CPM scores were associated with baseline measures of baroreflex sensitivity in both CLBP and NP participants. Our data support the importance of the baroreflex in chronic pain and a possible mechanism of dysregulation involving the interaction between the ANS and descending pain modulation. Key points: Baroreflex stimulation has different effects on pressure pain in participants with chronic pain compared to matched individuals with no‐pain.Baroreceptor activation decreases pain in participants with no‐pain but increases pain perception in participants with chronic pain.Baroreflex sensitivity is associated with conditioned pain modulation in both groups of chronic pain and no‐pain participants.The reactivity of the baroreflex during autonomic stress demonstrated a positive correlation with Pain Trait scores in participants with chronic back pain. [ABSTRACT FROM AUTHOR]

Human group connectome analysis relies on combining individual connectome data to construct a single representative network which can be used to describe brain organisation and identify differences between subject groups. Existing methods adopt different strategies to select the network structural features to be retained or optimised at group level. In the absence of ground truth, however, it is unclear which structural features are the most suitable and how to evaluate the consequences on the group network of applying any given strategy. In this investigation, we consider the impact of defining a connectome as representative if it can recapitulate not just the structure of the individual networks in the cohort tested but also their dynamical behaviour, which we measured using a model of coupled oscillators. We applied the widely used approach of consensus thresholding to a dataset of individual structural connectomes from a healthy adult cohort to construct group networks for a range of thresholds and then identified the most dynamically representative group connectome as that having the least deviation from the individual connectomes given a dynamical measure of the system. We found that our dynamically representative network recaptured aspects of structure for which it did not specifically optimise, with no significant difference to other group connectomes constructed via methods which did optimise for those metrics. Additionally, these other group connectomes were either as dynamically representative as our chosen network or less so. While we suggest that dynamics should be at least one of the criteria for representativeness, given that the brain has evolved under the pressure of carrying out specific functions, our results suggest that the question persists as to which of these criteria are valid and testable. [ABSTRACT FROM AUTHOR]

It is demonstrated that the application of piezoelectric sensors to metallic bars and strands can enable determining the status of the integrity of these elements through the spectrum of their acoustic excitations. The voltage output of the piezo, secured to metal bars or strands, is fed to the input of a Fast Fourier Transform analyzer, which allows displaying the spectrum of the excitations from which information on the length, overall quality of the metal, and the presence of defects can be obtained. We show that the analysis, performed on several materials and strands of different lengths, could be useful for cases in which visible inspection and/or direct access to the entire body of the metallic elements is not possible. Applications of our study for testing metallic structures embedded in concrete foundations are reported for construction sites. [ABSTRACT FROM AUTHOR]

The global agricultural sector needs to implement good soil management practices, in particular to prevent erosion and to improve water-retention capacity. The introduction of tillage techniques along particular theoretical lines, called keylines, can make a significant contribution to improving the management of the soil and agricultural crops. The keyline system has been around for less than 100 years. With this preliminary work, we performed a comparative analysis of two small river basins (less than 100 ha) before and after keyline application, based on GIS computational models (TWI and SIMWE). The calculation models were elaborated starting from a DTM with 2 m resolution, obtained from a LIDAR survey. The comparative analysis, in qualitative terms, showed a positive effect of the keylines, both in terms of erodibility and infiltration of runoff water. The use of GIS models to verify the effectiveness in the planning phase can constitute a decision support system that guides agronomists, technicians, and farmers. [ABSTRACT FROM AUTHOR]

The hypothesis that patients with scleroderma have serum autoantibodies that stimulate the platelet-derived growth factor (PDGF) receptor (PDGFR), activating collagen-gene expression is tested. The purification of anti-PDGFR reactive oxygen species (ROS)-stimulating antibodies and the results of tests of their biologic activity as purified clones strongly argue that these antibodies have a causal role in the pathogenesis of scleroderma.

Background: Even though Parkinson's disease (PD) is typically viewed as largely affecting gray matter, there is growing evidence that there are also structural changes in the white matter. Traditional connectomics methods that study PD may not be specific to underlying microstructural changes, such as myelin loss. Objective: The primary objective of this study is to investigate the PD‐induced changes in myelin content in the connections emerging from the basal ganglia and the brainstem. For the weighting of the connectome, we used the longitudinal relaxation rate as a biologically grounded myelin‐sensitive metric. Methods: We computed the myelin‐weighted connectome in 35 healthy control subjects and 81 patients with PD. We used partial least squares to highlight the differences between patients with PD and healthy control subjects. Then, a ring analysis was performed on selected brainstem and subcortical regions to evaluate each node's potential role as an epicenter for disease propagation. Then, we used behavioral partial least squares to relate the myelin alterations with clinical scores. Results: Most connections (~80%) emerging from the basal ganglia showed a reduced myelin content. The connections emerging from potential epicentral nodes (substantia nigra, nucleus basalis of Meynert, amygdala, hippocampus, and midbrain) showed significant decrease in the longitudinal relaxation rate (P < 0.05). This effect was not seen for the medulla and the pons. Conclusions: The myelin‐weighted connectome was able to identify alteration of the myelin content in PD in basal ganglia connections. This could provide a different view on the importance of myelination in neurodegeneration and disease progression. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society [ABSTRACT FROM AUTHOR]

Network models based on structural connectivity have been increasingly used as the blueprint for large-scale simulations of the human brain. As the nodes of this network are distributed through the cortex and interconnected by white matter pathways with different characteristics, modeling the associated conduction delays becomes important. The goal of this study is to estimate and characterize these delays directly from the brain structure. To achieve this, we leveraged microstructural measures from a combination of advanced magnetic resonance imaging acquisitions and computed the main determinants of conduction velocity, namely axonal diameter and myelin content. Using the model proposed by Rushton, we used these measures to calculate the conduction velocity and estimated the associated delays using tractography. We observed that both the axonal diameter and conduction velocity distributions presented a rather constant trend across different connection lengths, with resulting delays that scale linearly with the connection length. Relying on insights from graph theory and Kuramoto simulations, our results support the approximation of constant conduction velocity but also show path- and region-specific differences. [ABSTRACT FROM AUTHOR]

Several MRI measures have been proposed as in vivo biomarkers of myelin, each with applications ranging from plasticity to pathology. Despite the availability of these myelin-sensitive modalities, specificity and sensitivity have been a matter of discussion. Debate about which MRI measure is the most suitable for quantifying myelin is still ongoing. In this study, we performed a systematic review of published quantitative validation studies to clarify how different these measures are when compared to the underlying histology. We analyzed the results from 43 studies applying meta-analysis tools, controlling for study sample size and using interactive visualization (https://neurolibre.github.io/myelin-meta-analysis). We report the overall estimates and the prediction intervals for the coefficient of determination and find that MT and relaxometry-based measures exhibit the highest correlations with myelin content. We also show which measures are, and which measures are not statistically different regarding their relationship with histology. [ABSTRACT FROM AUTHOR]

Mapping the brain structure and function is one of the hardest problems in science. Different image modalities, in particular the ones based on magnetic resonance imaging (MRI) can shed more light on how it is organised and how its functions unfold, but a theoretical framework is needed. In the last years, using network models and graph theory to represent the brain structure and function has become a major trend in neuroscience. In this review, we outline how network modelling has been used in neuroimaging, clarifying what are the underlying mathematical concepts and the consequent methodological choices. The major findings are then presented for structural, functional and multimodal applications. We conclude outlining what are still the current issues and the perspective for the immediate future. [ABSTRACT FROM AUTHOR]

Alzheimer's disease (AD) alters the functional connectivity of the default mode network (DMN) but also the topological properties of the functional connectome. Cognitive training (CT) is a tool to slow down AD progression and is likely to impact on functional connectivity. In this pilot study, we aimed at investigating brain functional changes after a period of CT and active control (AC) in a group of 26 subjects with mild AD (mAD), 26 with amnestic mild cognitive impairment (aMCI), and a control group of 29 healthy elderly (HE) people. They all underwent a CT and AC in a counterbalanced order following a crossover design. Resting-state functional MRI and neuropsychological testing were acquired before and after each period. We tested post-CT and post-AC changes of cognitive abilities, of the functional connectivity of the DMN, and of topological network properties derived from graph theory and network-based statistics. Only CT produced functional changes, increasing the functional connectivity of the posterior DMN in all three groups. mAD also showed functional changes in the medial temporal lobe and topological changes in the anterior cingulum, whereas aMCI showed more widespread topological changes involving the frontal lobes, the cerebellum and the thalamus. Our results suggest specific functional connectivity changes after CT for aMCI and mAD. [ABSTRACT FROM AUTHOR]

Cognitive reserve (CR) is known to modulate the clinical features of Alzheimer's disease (AD). This concept may be critical for the development of non-pharmacological interventions able to slow down patients' cognitive decline in the absence of disease-modifying treatments. We aimed at identifying the neurobiological substrates of CR (i.e., neural reserve) over the transition between normal aging and AD, by assessing the underlying brain networks and their topological properties. A cohort of 154 participants (n = 68 with AD, n = 61 with amnestic mild cognitive impairment (aMCI), and 25 healthy subjects) underwent resting-state functional MRI and neuropsychological testing. Within each group, participants were classified as having high or low CR, and functional connectivity measures were compared, within group, between high and low CR individuals. Network-based statistics and topological network properties derived from graph theory were explored. Connectivity differences between high and low CR were evident only for aMCI patients, with participants with high CR showing a significant increase of connectivity in a network involving mainly fronto-parietal nodes. Conversely, they showed significantly decreased connectivity in a network involving fronto-temporo-cerebellar nodes. Consistently, changes to topological measures were observed in either direction, and were associated with measures of global cognitive function. These findings support the hypothesis that CR impacts on neurodegenerative process in the early phase of AD only. In addition, they fit with the existence of a "neural reserve", characterized by specific neural networks and their efficiency. It remains to be demonstrated whether interventions later in life can modulate this "neural reserve". [ABSTRACT FROM AUTHOR]

Myotonic dystrophy type-1 (DM1) is a genetic multi-systemic disorder involving several organs including the brain. Despite the heterogeneity of this condition, some patients with non-congenital DM1 can present with minimal cognitive impairment on formal testing but with severe difficulties in daily-living activities including social interactions. One explanation for this paradoxical mismatch can be found in patients’ dysfunctional social cognition, which can be assessed in the framework of the Theory of Mind (ToM). We hypothesize here that specific disease driven abnormalities in DM1 brains may result in ToM impairments. We recruited 20 DM1 patients who underwent the “Reading the Mind in the Eyes” and the ToM-story tests. These patients, together with 18 healthy controls, also underwent resting-state functional MRI. A composite Theory of Mind score was computed for all recruited patients and correlated with their brain functional connectivity. This analysis provided the patients’ “Theory of Mind-network”, which was compared, for its topological properties, with that of healthy controls. We found that DM1 patients showed deficits in both tests assessing ToM. These deficits were associated with specific patterns of abnormal connectivity between the left inferior temporal and fronto-cerebellar nodes in DM1 brains. The results confirm the previous suggestions of ToM dysfunctions in patients with DM1 and support the hypothesis that difficulties in social interactions and personal relationships are a direct consequence of brain abnormalities, and not a reaction symptom. This is relevant not only for a better pathophysiological comprehension of DM1, but also for non-pharmacological interventions to improve clinical aspects and impact on patients’ success in life. [ABSTRACT FROM AUTHOR]

The adult form of myotonic dystrophy type 1 (DM1) presents with paradoxical inconsistencies between severity of brain damage, relative preservation of cognition, and failure in everyday life. This study, based on the assessment of brain connectivity and mechanisms of plasticity, aimed at reconciling these conflicting issues. Resting-state functional MRI and graph theoretical methods of analysis were used to assess brain topological features in a large cohort of patients with DM1. Patients, compared to controls, revealed reduced connectivity in a large frontoparietal network that correlated with their isolated impairment in visuospatial reasoning. Despite a global preservation of the topological properties, peculiar patterns of frontal disconnection and increased parietal-cerebellar connectivity were also identified in patients’ brains. The balance between loss of connectivity and compensatory mechanisms in different brain networks might explain the paradoxical mismatch between structural brain damage and minimal cognitive deficits observed in these patients. This study provides a comprehensive assessment of brain abnormalities that fit well with both motor and nonmotor clinical features experienced by patients in their everyday life. The current findings suggest that measures of functional connectivity may offer the possibility of characterizing individual patients with the potential to become a clinical tool. [ABSTRACT FROM AUTHOR]

Background: Miombo woodlands play an important role in the livelihood of people living in sub-equatorial African countries, contributing to satisfy basic human needs such as food, medicine, fuelwood and building materials. However, over-exploitation of plant resources and unsustainable harvest practices can potentially degrade forests. The aim of this study was to document the use of Miombo plant products, other than medicinal plants, in local communities, within a wider framework in which we discussed possible links between traditional uses and conservation status of the used species and of the whole Miombo environment. Methods: Fieldwork took place in four communities of Muda-Serração, central Mozambique. We conducted semi-structured interviews with 52 informants about their knowledge, use and harvesting practices of useful plants. A survey on local Miombo vegetation was also carried out in order to assess abundance and distribution of useful woody plants cited in the interviews in areas exposed to different exploitation rates. A Conservation Priority index was also applied to rank conservation values of each used woody species. Results: Ninety-eight plants cited by the informants were botanically identified. The most relevant general category was represented by food plants (45 species), followed by handicraft plants (38 species) and domestic plants (37 species). Among the 54 woody species observed in vegetation plots, 52% were cited as useful in the interviews. Twenty-six woody species found in ‘natural’ Miombo areas were not found in ‘degraded’ ones: of these, 46% were cited in the interviews (58% in the food category, 50% in the handicraft category, 25% in the domestic category and 8% in the fishing category). Results of conservation ranking showed that 7 woody species deserve conservation priority in the investigated area. Conclusions: This study shows that the communities investigated rely heavily on local forest products for their daily subsistence requirements in food, firewood/charcoal and building materials. However, over-exploitation and destructive collection seem to threaten the survival of some of the woody species used. A sustainable approach including the involvement of local communities in the management of woody species is recommended. [ABSTRACT FROM AUTHOR]

Abstract: We use boundary field theory to describe the phases accessible to a tetrahedral qubit coupled to Josephson junction chains acting as Tomonaga–Luttinger liquid leads. We prove that, in a pertinent range of the fabrication and control parameters, an attractive finite coupling fixed point emerges due to the geometry of the composite Josephson junction network. We show that this new stable phase is characterized by the emergence of a quantum doublet which is robust not only against the noise in the external control parameters (magnetic flux, gate voltage) but also against the decoherence induced by the coupling of the tetrahedral qubit with the superconducting leads. We provide protocols allowing to read and to manipulate the state of the emerging quantum doublet and argue that a tetrahedral Josephson junction network operating near the new finite coupling fixed point may be fabricated with todayʼs technologies. [Copyright &y& Elsevier]

Abstract: Ethnopharmacological relevance: Through this study, relevant information was gathered on the knowledge about medicinal remedies in some rural communities of Muda (central Mozambique). The use of 198 different medicinal plants has been recorded and a significant number of medicinal species and uses new for Africa and particularly for Mozambique has been detected. Our investigation appears to be the first comparing knowledge about medicinal plants between laypeople and traditional healers and also between the two kinds of healers (curandeiros and profetas). Materials and methods: Ethnobotanical data were gathered through semi-structured interviews with 67 informants: 9 curandeiros (traditional healers believed to be guided by spirits), 12 profetas (independent Pentecostal churches “prophets” healing both souls and bodies) and 46 untrained lay villagers. Data were entered in a data base and processed, also by means of suitable quantitative indexes. Results: A total of 546 citations were recorded for 198 different ethnospecies (i.e. basic ethno-taxonomical units). The species with the highest cultural value (estimated with Cultural Importance index) resulted to be Ximenia caffra (CI=0.224), Zanha golungensis (CI=0.194) Vernonia colorata (CI=0.149) and Ozoroa reticulata and Holarrhena pubescens (both with CI=0.134). Eight out of the 162 identified plants mentioned by the informants were not previously recorded as medicinal plants in Africa: Cissus bathyrhakodes, Clematis viridiflora, Combretum goetzei, Dioscorea cochleari-apiculata, Grewia pachycalyx, Indigofera antunesiana, Ipomoea consimilis, Tricliceras longipedunculatum. More than half of the species reported by our informants and already known as medicinal in Africa resulted to be newly documented for Mozambique. Comparing the mean number of species known by each informant group, statistically significant differences were observed both between curandeiros and laypeople and between profetas and laypeople. No significant differences emerged instead between curandeiros and profetas. Yet, even laypeople proved to hold quite a good knowledge about medicinal remedies; women in particular use several different plants to heal common diseases of the whole family, mostly for children and female health problems. Conclusions: The high number of plants and uses recorded demonstrates that in the study area ethnobotanical knowledge is still quite rich and alive. The finding of many medicinal plants and uses new for Mozambique or even Africa shows the importance of recording this knowledge before it vanishes, also as a basis for further investigations on possible pharmacological properties of local plants. The lack of health infrastructures in Muda results in the need for lay villagers of acquiring and developing a rather high degree of knowledge about plants remedies; in a different interaction between healers and lay villagers, compared to urban areas; ultimately, in a different distribution and wider spread of traditional knowledge on medicinal plants. [ABSTRACT FROM AUTHOR]

Magnetic resonance imaging (MRI) is the standard tool to image the human brain in vivo. In this domain, digital brain atlases are essential for subject-specific segmentation of anatomical regions of interest (ROIs) and spatial comparison of neuroanatomy from different subjects in a common coordinate frame. High-resolution, digital atlases derived from histology (e.g., Allen atlas [7], BigBrain [13], Julich [15]), are currently the state of the art and provide exquisite 3D cytoarchitectural maps, but lack probabilistic labels throughout the whole brain. Here we present NextBrain, a next-generation probabilistic atlas of human brain anatomy built from serial 3D histology and corresponding highly granular delineations of five whole brain hemispheres. We developed AI techniques to align and reconstruct ~10,000 histological sections into coherent 3D volumes with joint geometric constraints (no overlap or gaps between sections), as well as to semi-automatically trace the boundaries of 333 distinct anatomical ROIs on all these sections. Comprehensive delineation on multiple cases enabled us to build the first probabilistic histological atlas of the whole human brain. Further, we created a companion Bayesian tool for automated segmentation of the 333 ROIs in any in vivo or ex vivo brain MRI scan using the NextBrain atlas. We showcase two applications of the atlas: automated segmentation of ultra-high-resolution ex vivo MRI and volumetric analysis of Alzheimer's disease and healthy brain ageing based on ~4,000 publicly available in vivo MRI scans. We publicly release: the raw and aligned data (including an online visualisation tool); the probabilistic atlas; the segmentation tool; and ground truth delineations for a 100 μm isotropic ex vivo hemisphere (that we use for quantitative evaluation of our segmentation method in this paper). By enabling researchers worldwide to analyse brain MRI scans at a superior level of granularity without manual effort or highly specific neuroanatomical knowledge, NextBrain holds promise to increase the specificity of MRI findings and ultimately accelerate our quest to understand the human brain in health and disease., Competing Interests: Competing interests The authors have no relevant financial or non-financial interests to disclose.

The ENIGMA group on Generalized Anxiety Disorder (ENIGMA-Anxiety/GAD) is part of a broader effort to investigate anxiety disorders using imaging and genetic data across multiple sites worldwide. The group is actively conducting a mega-analysis of a large number of brain structural scans. In this process, the group was confronted with many methodological challenges related to study planning and implementation, between-country transfer of subject-level data, quality control of a considerable amount of imaging data, and choices related to statistical methods and efficient use of resources. This report summarizes the background information and rationale for the various methodological decisions, as well as the approach taken to implement them. The goal is to document the approach and help guide other research groups working with large brain imaging data sets as they develop their own analytic pipelines for mega-analyses., (© 2020 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

Nonlinear inter-modality registration is often challenging due to the lack of objective functions that are good proxies for alignment. Here we propose a synthesis-by-registration method to convert this problem into an easier intra-modality task. We introduce a registration loss for weakly supervised image translation between domains that does not require perfectly aligned training data. This loss capitalises on a registration U-Net with frozen weights, to drive a synthesis CNN towards the desired translation. We complement this loss with a structure preserving constraint based on contrastive learning, which prevents blurring and content shifts due to overfitting. We apply this method to the registration of histological sections to MRI slices, a key step in 3D histology reconstruction. Results on two public datasets show improvements over registration based on mutual information (13% reduction in landmark error) and synthesis-based algorithms such as CycleGAN (11% reduction), and are comparable to registration with label supervision. Code and data are publicly available at https://github.com/acasamitjana/SynthByReg.

Understanding the association between autonomic nervous system [ANS] function and brain morphology across the lifespan provides important insights into neurovisceral mechanisms underlying health and disease. Resting-state ANS activity, indexed by measures of heart rate [HR] and its variability [HRV] has been associated with brain morphology, particularly cortical thickness [CT]. While findings have been mixed regarding the anatomical distribution and direction of the associations, these inconsistencies may be due to sex and age differences in HR/HRV and CT. Previous studies have been limited by small sample sizes, which impede the assessment of sex differences and aging effects on the association between ANS function and CT. To overcome these limitations, 20 groups worldwide contributed data collected under similar protocols of CT assessment and HR/HRV recording to be pooled in a mega-analysis (N = 1,218 (50.5% female), mean age 36.7 years (range: 12-87)). Findings suggest a decline in HRV as well as CT with increasing age. CT, particularly in the orbitofrontal cortex, explained additional variance in HRV, beyond the effects of aging. This pattern of results may suggest that the decline in HRV with increasing age is related to a decline in orbitofrontal CT. These effects were independent of sex and specific to HRV; with no significant association between CT and HR. Greater CT across the adult lifespan may be vital for the maintenance of healthy cardiac regulation via the ANS-or greater cardiac vagal activity as indirectly reflected in HRV may slow brain atrophy. Findings reveal an important association between CT and cardiac parasympathetic activity with implications for healthy aging and longevity that should be studied further in longitudinal research., (© 2020 The Authors. Psychophysiology published by Wiley Periodicals LLC on behalf of Society for Psychophysiological Research.)

Myelin plays a crucial role in how well information travels between brain regions. Complementing the structural connectome, obtained with diffusion MRI tractography, with a myelin-sensitive measure could result in a more complete model of structural brain connectivity and give better insight into white-matter myeloarchitecture. In this work we weight the connectome by the longitudinal relaxation rate (R1), a measure sensitive to myelin, and then we assess its added value by comparing it with connectomes weighted by the number of streamlines (NOS). Our analysis reveals differences between the two connectomes both in the distribution of their weights and the modular organization. Additionally, the rank-based analysis shows that R1 can be used to separate transmodal regions (responsible for higher-order functions) from unimodal regions (responsible for low-order functions). Overall, the R1-weighted connectome provides a different perspective on structural connectivity taking into account white matter myeloarchitecture., (© 2020 Massachusetts Institute of Technology.)

Graph-theoretical approaches have become a popular way to model brain data collected using magnetic resonance imaging (MRI), both from the structural and the functional perspectives. In structural networks, tract-based mapping allows to model different aspects of brain structures by means of the specific characteristics of the different MRI modalities. However, there has been little effort to join the information carried by each modality and to understand what level of common variance is shown in these data. In this paper, we proposed a combined approach based on graph theory and factor analysis to model magnetization transfer and microstructural properties in 18 relapsing remitting multiple sclerosis (RRMS) patients and 17 healthy controls. After defining the common factors and outlining their relationships with MRI data, we evaluated between-group differences using global and local graph measures. The results showed that one common factor describes brain structures in terms of myelin and global integrity, and such factor is able to highlight specific between-group differences.

Transcranial direct current stimulation (tDCS) is a non-invasive brain stimulation method that can be used in cognitive and clinical protocols in order to modulate neural activity. Although some macro effects are known, the underlying mechanisms are still not clear. tDCS in combination with electroencephalography (EEG) could help to understand these mechanisms from a neural point of view. However, simultaneous tDCS-EEG still remains challenging because of the artifacts that affect the recorded signals. In this paper, an automated artifact cancellation method based on adaptive filtering is proposed. Using independent component analysis (ICA), the artifacts were characterized using data from both a phantom and a group of healthy subjects. The resulting filter can successfully remove tDCS-related artifacts during anodal and cathodal stimulations.

The static magnetic field generated by MRI systems is highly non-homogenous and rapidly decreases when moving away from the bore of the scanner. Consequently, the movement around the MRI scanner is equivalent to an exposure to a time-varying magnetic field at very low frequency (few Hz). For patients with an implanted cardiac stimulators, such as an implantable cardioverter/defibrillator (ICD), the movements inside the MRI environment may thus induce voltages on the loop formed by the leads of the device, with the potential to affect the behavior of the stimulator. In particular, the ICD's detection algorithms may be affected by the induced voltage and may cause inappropriate sensing, arrhythmia detections, and eventually inappropriate ICD therapy.We performed in-vitro measurements on a saline-filled humanshaped phantom (male, 170 cm height), equipped with an MRconditional ICD able to transmit in real-time the detected cardiac activity (electrograms). A biventricular implant was reproduced and the ICD was programmed in standard operating conditions, but with the shock delivery disabled. The electrograms recorded in the atrial, left and right ventricle channels were monitored during rotational movements along the vertical axis, in close proximity of the bore. The phantom was also equipped with an accelerometer and a magnetic field probe to measure the angular velocity and the magnetic field variation during the experiment. Pacing inhibition, inappropriate detection of tachyarrhythmias and of ventricular fibrillation were observed. Pacing inhibition began at an angular velocity of about 7 rad/s, (dB/dt of about 2 T/s). Inappropriate detection of ventricular fibrillation occurred at about 8 rad/s (dB/dt of about 3 T/s). These findings highlight the need for a specific risk assessment of workers with MR-conditional ICDs, which takes into account also effects that are generally not considered relevant for patients, such as the movement around the scanner bore.

Central autonomic control on the cardiovascular system has been widely investigated in the last decades. More recently, with the advent of brain imaging techniques, considerable effort is being spent on defining the role of specific brain areas, and their dynamic network, acting on autonomic efferents. A way to assess autonomic modulation is offered by carotid stimulation. In this work, we propose a methodology to investigate autonomic control in carotid stimulation experiments using heartbeat series in combination with fMRI imaging. We modeled cardiovascular signals using the point process model, and processed fMRI data in order to estimate independent components of correlated information. Using cross-correlation and surrogate analysis, we assessed the responsiveness of subjects to neck suction stimuli and identified stimulus-related fMRI independent components.