Learning-based single-step quantitative susceptibility mapping reconstruction without brain extraction Publication date: 15 November 2019 Source: NeuroImage, Volume 202 Author(s): Hongjiang Wei, Steven Cao, Yuyao Zhang, Xiaojun Guan, Fuhua Yan, Kristen W. Yeom, Chunlei Liu Abstract Quantitative susceptibility mapping (QSM) estimates the underlying tissue magnetic susceptibility from MRI gradient-echo phase signal and typically requires several processing steps. These steps involve phase unwrapping, brain volume extraction, background phase removal and solving an ill-posed inverse problem relating the tissue phase to the underlying susceptibility distribution. The resulting susceptibility map is known to suffer from inaccuracy near the edges of the brain tissues, in part due to imperfect brain extraction, edge erosion of the brain tissue and the lack of phase measurement outside the brain. This inaccuracy has thus hindered the application of QSM for measuring susceptibility of tissues near the brain edges, e.g., quantifying cortical layers and generating superficial venography. To address these challenges, we propose a learning-based QSM reconstruction method that directly estimates the magnetic susceptibility from total phase images without the need for brain extraction and background phase removal, referred to as autoQSM. The neural network has a modified U-net structure and is trained using QSM maps computed by a two-step QSM method. 209 healthy subjects with ages ranging from 11 to 82 years were employed for patch-wise network training. The network was validated on data dissimilar to the training data, e.g., in vivo mouse brain data and brains with lesions, which suggests that the network generalized and learned the underlying mathematical relationship between magnetic field perturbation and magnetic susceptibility. Quantitative and qualitative comparisons were performed between autoQSM and other two-step QSM methods. AutoQSM was able to recover magnetic susceptibility of anatomical structures near the edges of the brain including the veins covering the cortical surface, spinal cord and nerve tracts near the mouse brain boundaries. The advantages of high-quality maps, no need for brain volume extraction, and high reconstruction speed demonstrate autoQSM’s potential for future applications.

Transdiagnostic variations in impulsivity and compulsivity in obsessive-compulsive disorder and gambling disorder correlate with effective connectivity in cortical-striatal-thalamic-cortical circuits Publication date: 15 November 2019 Source: NeuroImage, Volume 202 Author(s): Linden Parkes, Jeggan Tiego, Kevin Aquino, Leah Braganza, Samuel R. Chamberlain, Leonardo F. Fontenelle, Ben J. Harrison, Valentina Lorenzetti, Bryan Paton, Adeel Razi, Alex Fornito, Murat Yücel Abstract Individual differences in impulsivity and compulsivity is thought to underlie vulnerability to a broad range of disorders and are closely tied to cortical-striatal-thalamic-cortical function. However, whether impulsivity and compulsivity in clinical disorders is continuous with the healthy population and explains cortical-striatal-thalamic-cortical dysfunction across different disorders remains unclear. Here, we characterized the relationship between cortical-striatal-thalamic-cortical effective connectivity, estimated using dynamic causal modelling of resting-state functional magnetic resonance imaging data, and dimensional phenotypes of impulsivity and compulsivity in two symptomatically distinct but phenotypically related disorders, obsessive-compulsive disorder and gambling disorder. 487 online participants provided data for modelling of dimensional phenotypes. These data were combined with 34 obsessive-compulsive disorder patients, 22 gambling disorder patients, and 39 healthy controls, who underwent functional magnetic resonance imaging. Three core dimensions were identified: disinhibition, impulsivity, and compulsivity. Patients’ scores on these dimensions were continuously distributed with the healthy participants, supporting a continuum model of psychopathology. Across all participants, higher disinhibition correlated with lower bottom-up connectivity in the dorsal circuit and greater bottom-up connectivity in the ventral circuit, and higher compulsivity correlated with lower bottom-up connectivity in the dorsal circuit. In patients, higher clinical severity was also linked to lower bottom-up connectivity in the dorsal circuit, but these findings were independent of phenotypic variation, demonstrating convergence towards behaviourally and clinically relevant changes in brain dynamics. Effective connectivity did not differ as a function of traditional diagnostic labels and only weak associations were observed for functional connectivity measures. Together, our results demonstrate that cortical-striatal-thalamic-cortical dysfunction across obsessive-compulsive disorder and gambling disorder may be better characterized by dimensional phenotypes than diagnostic comparisons, supporting investigation of quantitative liability phenotypes.

Information decomposition of multichannel EMG to map functional interactions in the distributed motor system Publication date: 15 November 2019 Source: NeuroImage, Volume 202 Author(s): Tjeerd W. Boonstra, Luca Faes, Jennifer N. Kerkman, Daniele Marinazzo Abstract The central nervous system needs to coordinate multiple muscles during postural control. Functional coordination is established through the neural circuitry that interconnects different muscles. Here we used multivariate information decomposition of multichannel EMG acquired from 14 healthy participants during postural tasks to investigate the neural interactions between muscles. A set of information measures were estimated from an instantaneous linear regression model and a time-lagged VAR model fitted to the EMG envelopes of 36 muscles. We used network analysis to quantify the structure of functional interactions between muscles and compared them across experimental conditions. Conditional mutual information and transfer entropy revealed sparse networks dominated by local connections between muscles. We observed significant changes in muscle networks across postural tasks localized to the muscles involved in performing those tasks. Information decomposition revealed distinct patterns in task-related changes: unimanual and bimanual pointing were associated with reduced transfer to the pectoralis major muscles, but an increase in total information compared to no pointing, while postural instability resulted in increased information, information transfer and information storage in the abductor longus muscles compared to normal stability. These findings show robust patterns of directed interactions between muscles that are task-dependent and can be assessed from surface EMG recorded during static postural tasks. We discuss directed muscle networks in terms of the neural circuitry involved in generating muscle activity and suggest that task-related effects may reflect gain modulations of spinal reflex pathways.

Negative life experiences contribute to racial differences in the neural response to threat Publication date: 15 November 2019 Source: NeuroImage, Volume 202 Author(s): Nathaniel G. Harnett, Muriah D. Wheelock, Kimberly H. Wood, Adam M. Goodman, Sylvie Mrug, Marc N. Elliott, Mark A. Schuster, Susan Tortolero, David C. Knight Abstract Threat-related emotional function is supported by a neural circuit that includes the prefrontal cortex (PFC), hippocampus, and amygdala. The function of this neural circuit is altered by negative life experiences, which can potentially affect threat-related emotional processes. Notably, Black-American individuals disproportionately endure negative life experiences compared to White-American individuals. However, the relationships among negative life experiences, race, and the neural substrates that support threat-related emotional function remains unclear. Therefore, the current study investigated whether the brain function that supports threat-related emotional processes varies with racial differences in negative life experiences. In the present study, adolescent violence exposure, family income, and neighborhood disadvantage were measured prospectively (i.e., at 11–19 years of age) for Black-American and White-American volunteers. Participants then, as young adults (i.e., 18–23 years of age), completed a Pavlovian fear conditioning task during functional magnetic resonance imaging (fMRI). Cued and non-cued threats were presented during the conditioning task and behavioral (threat expectancy) and psychophysiological responses (skin conductance response; SCR) were recorded simultaneously with fMRI. Racial differences were observed in neural (fMRI activity), behavioral (threat expectancy), and psychophysiological (SCR) responses to threat. These threat-elicited responses also varied with negative life experiences (violence exposure, family income, and neighborhood disadvantage). Notably, racial differences in brain activity to threat were smaller after accounting for negative life experiences. The present findings suggest that racial differences in the neural and behavioral response to threat are due, in part, to exposure to negative life experiences and may provide new insight into the mechanisms underlying racial disparities in mental health.

A systematic optimization of 19F MR image acquisition to detect macrophage invasion into an ECM hydrogel implanted in the stroke-damaged brain Publication date: 15 November 2019 Source: NeuroImage, Volume 202 Author(s): Harmanvir Ghuman, T. Kevin Hitchens, Michel Modo Abstract 19F-MR imaging of perfluorocarbon (PFC)-labeled macrophages can provide a unique insight into their participation and spatio-temporal dynamics of inflammatory events, such as the biodegradation of an extracellular matrix (ECM) hydrogel implanted into a stroke cavity. To determine the most efficient acquisition strategy for 19F-MR imaging, five commonly used sequences were optimized using a design of experiment (DoE) approach and compared based on their signal-to-noise ratio (SNR). The fast imaging with steady-state precession (FISP) sequence produced the most efficient detection of a 19F signal followed by the rapid acquisition with relaxation enhancement (RARE) sequence. The multi-slice multi-echo (MSME), fast low angle shot (FLASH), and zero echo time (ZTE) sequences were significantly less efficient. Imaging parameters (matrix/voxel size; slice thickness, number of averages) determined the accuracy (i.e. trueness and precision) of object identification by reducing partial volume effects, as determined by analysis of the point spread function (PSF). A 96 × 96 matrix size (0.35 mm3) produced the lowest limit of detection (LOD) for RARE (2.85 mM PFPE; 119 mM 19F) and FISP (0.43 mM PFPE; 18.1 mM 19F), with an SNR of 2 as the detection threshold. Imaging of a brain phantom with PFC-labeled macrophages invading an ECM hydrogel further illustrated the impact of these parameter changes. The systematic optimization of sequence and imaging parameters provides the framework for an accurate visualization of 19F-labeled macrophage distribution and density in the brain. This will enhance our understanding of the contribution of periphery-derived macrophages in bioscaffold degradation and its role in brain tissue regeneration. Graphical abstract

Brain hemispheric involvement in visuospatial and verbal divergent thinking Publication date: 15 November 2019 Source: NeuroImage, Volume 202 Author(s): Qunlin Chen, Roger E. Beaty, Zaixu Cui, Jiangzhou Sun, Hong He, Kaixiang Zhuang, Zhiting Ren, Guangyuan Liu, Jiang Qiu Abstract Hemispheric lateralization for creative thinking remains a controversial topic. Early behavioral and neuroimaging research supported right hemisphere dominance in creative thinking, but more recent evidence suggests the left hemisphere plays an equally important role. In addition, the extent to which hemispheric lateralization in specific brain regions relates to individual creative ability, and whether hemispheric dominance relates to distinct task performance, remain poorly understood. Here, using multivariate predictive modeling of resting-state functional MRI data in a large sample of adults (N = 502), we estimated hemispheric segregation and integration for each brain region and investigated these lateralization indices with respect to individual differences in visuospatial and verbal divergent thinking. Our analyses revealed that individual visuospatial divergent thinking performance could be predicted by right-hemispheric segregation within the visual network, sensorimotor network, and some regions within the default mode network. High visuospatial divergent thinking was related to stronger functional connectivity between the visual network, fronto-parietal network, and default mode network within the right hemisphere. In contrast, high verbal divergent thinking performance could be predicted by inter-hemispheric balance within regions mainly involved in complex semantic processing (e.g., lateral temporal cortex and inferior frontal gyrus) and cognitive control processing (e.g., inferior frontal gyrus, middle frontal cortex, and superior parietal lobule). The current study suggests that two distinct forms of functional lateralization support individual differences in visuospatial and verbal divergent thinking. These findings have important implications for our understanding of hemispheric interaction mechanisms of creative thinking.

The role of expecting feedback during decision-making under risk Publication date: 15 November 2019 Source: NeuroImage, Volume 202 Author(s): Francesco Rigoli, Cristina Martinelli, Sukhwinder S Shergill Abstract Sometimes choice is followed by outcome feedback and other times it is not. It remains unknown whether humans prefer gambling when they expect feedback to be revealed. Regarding this question, decision-making theories make alternative predictions. Some theories have proposed that choice is influenced by whether one expects to be disappointed in the future. Given that feedback is sometimes disappointing, these theories predict increased aversion towards gambling when feedback is expected compared to when feedback is not expected. The opposite effect is predicted by theories of curiosity, which postulate reduction of uncertainty as an important behavioural drive. Given that feedback reduces uncertainty, these theories predict that gambling will be favoured when feedback is expected. To examine whether expecting feedback influences gambling behaviour, we recorded functional neuroimaging data while participants performed a novel decision-making task requiring to chose between a sure option and a gamble. Crucially, participants expected to receive feedback in some trials but not in other trials. Consistent with theories of curiosity, we found that expecting feedback increased gambling propensity. At the neural level, at option presentation the increased value of gambling during feedback was reflected in activity in the ventral striatum. This suggests that, together with its established role in signalling reward, the ventral striatum also processes a form of epistemic value. Our study demonstrates that gambling becomes more attractive when feedback is expected and suggests that striatal activity could signal the value of feedback information.

Untangling featural and conceptual object representations Publication date: 15 November 2019 Source: NeuroImage, Volume 202 Author(s): Tijl Grootswagers, Amanda K. Robinson, Sophia M. Shatek, Thomas A. Carlson Abstract How are visual inputs transformed into conceptual representations by the human visual system? The contents of human perception, such as objects presented on a visual display, can reliably be decoded from voxel activation patterns in fMRI, and in evoked sensor activations in MEG and EEG. A prevailing question is the extent to which brain activation associated with object categories is due to statistical regularities of visual features within object categories. Here, we assessed the contribution of mid-level features to conceptual category decoding using EEG and a novel fast periodic decoding paradigm. Our study used a stimulus set consisting of intact objects from the animate (e.g., fish) and inanimate categories (e.g., chair) and scrambled versions of the same objects that were unrecognizable and preserved their visual features (Long et al., 2018). By presenting the images at different periodic rates, we biased processing to different levels of the visual hierarchy. We found that scrambled objects and their intact counterparts elicited similar patterns of activation, which could be used to decode the conceptual category (animate or inanimate), even for the unrecognizable scrambled objects. Animacy decoding for the scrambled objects, however, was only possible at the slowest periodic presentation rate. Animacy decoding for intact objects was faster, more robust, and could be achieved at faster presentation rates. Our results confirm that the mid-level visual features preserved in the scrambled objects contribute to animacy decoding, but also demonstrate that the dynamics vary markedly for intact versus scrambled objects. Our findings suggest a complex interplay between visual feature coding and categorical representations that is mediated by the visual system’s capacity to use image features to resolve a recognisable object.

Magnetic resonance spectroscopy extended by oscillating diffusion gradients: Cell-specific anomalous diffusion as a probe for tissue microstructure in human brain Publication date: 15 November 2019 Source: NeuroImage, Volume 202 Author(s): André Döring, Roland Kreis Abstract Purpose To demonstrate that oscillating gradient spin-echo sequences can be combined with diffusion-weighted magnetic resonance spectroscopy even on clinical MR systems to study human brain at short diffusion times to provide apparent diffusion coefficients (ADCs) sensitive to a narrower cellular length scale than pulsed gradient spin-echo sequences at long diffusion time. Methods Measurements were performed on a 3T MR system using a semiLaser sequence with diffusion-weighting realized by oscillating and pulsed gradient modules, encoding diffusion times <10 ms and >50 ms, respectively. Metabolite-cycling was included to measure metabolites and water simultaneously. The sequence was tested in a phantom and in a parieto-occipital cerebral region of interest with mixed gray/white matter content of 6 subjects. The water reference was used for phase, frequency, and eddy-current correction as well as motion compensation. ADCs were estimated by 1D sequential and 2D simultaneous fitting. Results Measurements in the phantom established that both sequences yield equal ADCs, independent of diffusion time, as expected for free diffusion. In contrast, averaged metabolite diffusion in vivo was found to be 1.9 times faster at short (8.3 ms) than at long (155 ms) diffusion times. The difference in ADC was found to be statistically significant for the creatines, cholines, N-acetylaspartate, myo-inositol, and glutamate. The water ADC was measured to be 1.3 times larger at short than at long diffusion time. Conclusion It is demonstrated that application of oscillating gradients in diffusion-weighted MRS is feasible on clinical MR systems to establish the dependence of ADCs on diffusion times in humans. The initial results largely confirm earlier reports for mice’ and rats’ brain at short and long diffusion times. ADCs representing diffusion at short and ultra-short diffusion times are of interest to probe cellular or subcellular changes in disease. The presented methodology may thus open the door for investigation of pathophysiological changes in cell-specific microstructures in human cohorts. Graphical abstract

Genetic and environmental influences on functional connectivity within and between canonical cortical resting-state networks throughout adolescent development in boys and girls Publication date: 15 November 2019 Source: NeuroImage, Volume 202 Author(s): Jalmar Teeuw, Rachel M. Brouwer, João P.O.F.T. Guimarães, Philip Brandner, Marinka M.G. Koenis, Suzanne C. Swagerman, Maxime Verwoert, Dorret I. Boomsma, Hilleke E. Hulshoff Pol Abstract The human brain is active during rest and hierarchically organized into intrinsic functional networks. These functional networks are largely established early in development, with reports of a shift from a local to more distributed organization during childhood and adolescence. It remains unknown to what extent genetic and environmental influences on functional connectivity change throughout adolescent development. We measured functional connectivity within and between eight cortical networks in a longitudinal resting-state fMRI study of adolescent twins and their older siblings on two occasions (mean ages 13 and 18 years). We modelled the reliability for these inherently noisy and head-motion sensitive measurements by analyzing data from split-half sessions. Functional connectivity between resting-state networks decreased with age whereas functional connectivity within resting-state networks generally increased with age, independent of general cognitive functioning. Sex effects were sparse, with stronger functional connectivity in the default mode network for girls compared to boys, and stronger functional connectivity in the salience network for boys compared to girls. Heritability explained up to 53% of the variation in functional connectivity within and between resting-state networks, and common environment explained up to 33%. Genetic influences on functional connectivity remained stable during adolescent development. In conclusion, longitudinal age-related changes in functional connectivity within and between cortical resting-state networks are subtle but wide-spread throughout adolescence. Genes play a considerable role in explaining individual variation in functional connectivity with mostly stable influences throughout adolescence.