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Biomechanical study of brain injuries originated from mechanical damages to white matter tissue requires detailed information on mechanical characteristics of its main components, the axonal fibers and extracellular matrix, which is very limited due to practical difficulties of direct measurement. In this paper, a new theoretical framework was established based on microstructural modeling of brain white matter tissue as a soft composite for bidirectional hyperelastic characterization of its main components. First the tissue was modeled as an Ogden hyperelastic material, and its principal Cauchy stresses were formulated in the axonal and transverse directions under uniaxial and equibiaxial tension using the theory of homogenization. Upon fitting these formulae to the corresponding experimental test data, direction-dependent hyperelastic constants of the tissue were obtained. These directional properties then were used to estimate the strain energy stored in the homogenized model under each loading scenario. A new microstructural composite model of the tissue was also established using principles of composites micromechanics, in which the axonal fibers and surrounding matrix are modeled as different Ogden hyperelastic materials with unknown constants. Upon balancing the strain energies stored in the homogenized and composite models under different loading scenarios, fully coupled nonlinear equations as functions of unknown hyperelastic constants were derived, and their optimum solutions were found in a multi-parametric multi-objective optimization procedure using the response surface methodology. Finally, these solutions were implemented, in a bottom-up approach, into a micromechanical finite element model to reproduce the tissue responses under the same loadings and predict the tissue responses under unseen non-equibiaxial loadings. Results demonstrated a very good agreement between the model predictions and experimental results in both directions under different loadings. Moreover, the axonal fibers with hyperelastic characteristics stiffer than the extracellular matrix were shown to play the dominant role in directional reinforcement of the tissue., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Background: White matter stimulation in an awake patient is currently the gold standard for identification of functional pathways. Despite the robustness and reproducibility of this method, very little is known about the electrophysiological mechanisms underlying the functional disruption. Axono-cortical evoked potentials (ACEPs) provide a reliable technique to explore these mechanisms., Objective: To describe the shape and spatial patterns of ACEPs recorded when stimulating the white matter of the caudal part of the right superior frontal gyrus while recording in the precentral gyrus., Methods: We report on three patients operated on under awake condition for a right superior frontal diffuse low-grade glioma. Functional sites were identified in the posterior wall of the cavity, whose 2-3-mA stimulation generated an arrest of movement. Once the resection was done, axono-cortical potentials were evoked: recording electrodes were put over the precentral gyrus, while stimulating at 1 Hz the white matter functional sites during 30-60 s. Unitary evoked potentials were averaged off-line. Waveform was visually analyzed, defining peaks and troughs, with quantitative measurements of their amplitudes and latencies. Spatial patterns of ACEPs were compared with patients' own and HCP-derived structural connectomics., Results: Axono-cortical evoked potentials (ACEPs) were obtained and exhibited complex shapes and spatial patterns that correlated only partially with structural connectivity patterns., Conclusion: ACEPs is a new IONM methodology that could both contribute to elucidate the propagation of neuronal activity within a distributed network when stimulating white matter and provide a new technique for preserving motor control abilities during brain tumor resections.

Reading in children has been associated with microstructural properties of the cerebellar peduncles, the white matter pathways connecting the cerebellum to the cerebrum. In this study, we used two independent neuroimaging modalities to assess which features of the cerebellar peduncles would be associated with reading. Twenty-three 8-year-old children were evaluated on word reading efficiency and imaged using diffusion MRI (dMRI) and quantitative T1 relaxometry (qT1). We segmented the superior (SCP), middle, and inferior cerebellar peduncles and extracted two metrics: fractional anisotropy (FA) from dMRI and R1 from qT1. Tract-FA was significantly correlated with tract-R1 in left and right SCPs (left: r P (21) = .63, right: r P (21) = .76, p ≤ .001) suggesting that FA of these peduncles, at least in part, indexed myelin content. Tract-FA and tract R1 were not correlated in the other cerebellar peduncles. Reading efficiency negatively correlated with tract-FA of the left (r P (21) = - .43, p = .040) and right SCP (r P (21) = - .37, p = .079). Reading efficiency did not correlate with tract-R1 in the SCPs. The negative association of reading efficiency with tract-FA and the lack of association of reading efficiency with tract-R1 implicate properties other than myelin content as relevant to the information flow between the cerebellum and the cerebrum for individual differences in reading skills in children.

Brain iron deposits (IDs) are indicative of microvessel dysfunction which may predispose to small vessel disease (SVD) brain damage and worsen cognition later in life. Visible perivascular spaces in the centrum semiovale (CSO-PVS) are SVD features linked with microvessel dysfunction. We examined possible associations of CSO-PVS volume and count with brain IDs and cognitive abilities in 700 community-dwelling individuals from the Lothian Birth Cohort 1936 who underwent detailed cognitive testing and multimodal brain MRI at mean age 72.7 years. Brain IDs were assessed automatically followed by manual editing. PVS were automatically assessed in the centrum semiovale and deep corona radiata supraventricular. General factors of overall cognitive function (g), processing speed (g-speed) and memory (g-memory) were used in the analyses. Median (IQR) volumes of IDs and CSO-PVS expressed as a percentage of intracranial volume were 0.0021 (0.011) and 0.22 (0.13)% respectively. Median count of CSO-PVS was 410 (IQR = 201). Total volumes of CSO-PVS and ID, adjusted for head size, were correlated (Spearman ρ = 0.13, p < 0.001). CSO-PVS volume, despite being correlated with all three cognitive measures, was only associated with g-memory (B = -114.5, SE = 48.35, p = 0.018) in general linear models, adjusting for age, sex, vascular risk factors, childhood intelligence and white matter hyperintensity volume. The interaction of CSO-PVS count with diabetes (B = -0.0019, SE = 0.00093, p = 0.041) and volume with age (B = 1.57, SE = 0.67, p = 0.019) were also associated with g-memory. Linear regression models did not replicate these associations. Therefore, it does not seem that CSO-PVS burden is directly associated with general cognitive ability in older age.

In this study, we propose a computational characterization technique for obtaining the material properties of axons and extracellular matrix (ECM) in human brain white matter. To account for the dynamic behavior of the brain tissue, data from time-dependent relaxation tests of human brain white matter in different strain rates are extracted and formulated by a visco-hyperelastic constitutive model consisting of the Ogden hyperelastic model and the Prony series expansion. Through micromechanical finite element simulation, a derivative-free optimization framework designed to minimize the difference between the numerical and experimental data is used to identify the material properties of the axons and ECM. The Prony series expansion parameters of axons and ECM are found to be highly affected by the Prony series expansion coefficients of the brain white matter. The optimal parameters of axons and ECM are verified through micromechanical simulation by comparing the averaged numerical response with that of the experimental data. Moreover, the initial shear modulus and the reduced shear modulus of the axons are found for different strain rates of 0.0001, 0.01, and 1 s -1 . Consequently, first- and second-order regressions are used to find relations for the prediction of the shear modulus at the intermediate strain rates. Graphical Abstract The applied procedure for characterization of brain white matter micro-level constituents. The macro-level experimental data in different strain rates are used in the context of simulation-based optimization to obtain the properties of axons and extracellular matrix material.

In sensorimotor adaptation paradigms, participants learn to adjust their behavior in response to an external perturbation. Locomotor adaptation and reaching adaptation depend on the cerebellum and are accompanied by changes in functional connectivity in cortico-cerebellar circuits. In order to gain a better understanding of the particular cerebellar projections involved in locomotor adaptation, we assessed the contribution of specific white matter pathways to the magnitude of locomotor adaptation and to long-term motor adaptation effects (recall and relearning). Diffusion magnetic resonance imaging with deterministic tractography was used to delineate the inferior and superior cerebellar peduncles (ICP, SCP) and the corticospinal tract (CST). Correlations were calculated to assess the association between the diffusivity values along the tracts and behavioral measures of locomotor adaptation. The results point to a significant correlation between the magnitude of adaptation and diffusivity values in the left ICP. Specifically, a higher magnitude of adaptation was associated with higher mean diffusivity and with lower anisotropy values in the left ICP, but not in other pathways. Post hoc analysis revealed that the effect stems from radial, not axial, diffusivity. The magnitude of adaptation was further associated with the degree of ICP lateralization, such that greater adaptation magnitude was correlated with increased rightward asymmetry of the ICP. Our findings suggest that the magnitude of locomotor adaptation depends on afferent signals to the cerebellum, transmitted via the ICP, and point to the contribution of error detection to locomotor adaptation rate.

This paper presents a bi-directional closed-form analytical solution, in the framework of nonlinear soft composites mechanics, for top-down hyperelastic characterization of brain white matter tissue components, based on the directional homogenized responses of the tissue in the axial and transverse directions. The white matter is considered as a transversely isotropic neo-Hookean composite made of unidirectional distribution of axonal fibers within the extracellular matrix. First, two homogenization formulations are derived for the homogenized axial and transverse shear moduli of the tissue, based on definition of the strain energy density function. Next, the rule of mixtures and Hashin-Shtrikman theories are used to derive two coupled nonlinear equations which correlates the tissue shear moduli to these of its components. Closed-form solutions for shear moduli of the components are then obtained by solving these equations simultaneously. In order to validate the hyperelastic characteristics of components obtained in previous step, they are used in a bottom-up approach in a micromechanical model of the tissue with the aim of predicting the directional homogenized responses of the tissue. Comparison of model predictions with the experimental test results reported for corona radiata and corpus callosum white matter structures reveals very good agreements with the experimental results in both directions. The model predictions are also in good agreement with the analytical solution obtained by the iterated homogenization technique. Results indicate that axonal fibers are almost ten times stiffer than the extracellular matrix under large deformations.

Diffusion MRI (dMRI) is commonly used to map large axonal pathways in the white matter. Recent technical advances have also enabled dMRI to resolve the small and complex axonal and dendritic projections in the gray matter. This study investigated whether high-resolution dMRI can resolve the hippocampal neuronal projections and detect abnormal connections due to neurological injury. We performed 3D high spatial and angular resolution dMRI of the mouse brains of the offspring survivors from a model of intrauterine (UI) inflammation, who had known functional deficiency in the hippocampus. We used a novel hippocampal connection mapping method to quantify the intra- and inter-hippocampal projections among 34 automatically segmented hippocampal sub-regions. The results demonstrated wide-spread intra-hippocampal projections, but rather specific intra-hippocampal projections that primarily connected through the CA3 region. Compared with the control group (n = 9), UI-injured mice (n = 11) exhibited significantly reduced inter-hippocampal projection strength (p < 0.01), which correlated well with the neurobehavioral assessments (R 2  = 0.47). Furthermore, using a whole-brain fixel-based analysis, we identified reduced fiber-density in the CA3 and the ventral hippocampal commissure of the UI-injured mice, which may explain the reduced inter-hippocampal projections. Histological findings also indicated reduced commissural fibers due to the UI-injury. Our study suggested that the dMRI-based connectivity mapping technique can potentially characterize abnormal hippocampal projections in neurological disorders.

The physiological basis of resilience to age-associated and AD-typical neurodegenerative pathology is still not well understood. So far, the established resilience factor intelligence has been shown to be associated with white matter network global efficiency, a key constituent of which are highly connected hubs. However, hub properties have also been shown to be impaired in AD. Individual predisposition or vulnerability of hub properties may thus modulate the impact of pathology on cognitive outcome and form part of the physiological basis of resilience. 85 cognitively normal elderly subjects and patients with MCI with DWI, MRI and AV45-PET scans were included from ADNI. We reconstructed the global WM networks in each subject and characterized hub-properties of GM regions using graph theory by calculating regional betweenness centrality. Subsequently, we investigated whether regional GM volume (GMV) and structural WM connectivity (WMC) of more hub-like regions was more associated with resilience, quantified as cognitive performance independent of amyloid burden, tau and WM lesions. Subjects with higher resilience showed higher increased regional GMV and WMC in more hub-like compared to less hub-like GM-regions. Additionally, this association was in some instances further increased at elevated amounts of brain pathology. Higher GMV and WMC of more hub-like regions may contribute more to resilience compared to less hub-like regions, reflecting their increased importance to brain network efficiency, and may thus form part of the neurophysiological basis of resilience. Future studies should investigate the factors leading to higher GMV and WMC of hubs in non-demented elderly with higher resilience.

The aim of this study is to characterise the stiffness of white and grey matter in paediatric subjects using magnetic resonance elastography (MRE) and to determine whether these properties change throughout normal development. MRE was performed using a clinical 3T MRI scanner at three frequencies (30, 40 and 60 Hz) on 36 healthy paediatric subjects aged between 7 and 18 years (19 F) and 11 adults aged 23-44 years (6 F). Anatomical and diffusion tensor imaging was also collected. The stiffness quantified as the magnitude of the complex shear modulus (G*), fractional anisotropy (FA), mean diffusivity (MD) and volume of white and grey matter were calculated. One-way analysis of variance and Tukey's multiple comparison tests were used to compare data in age groups separated into children (7-12 years), adolescents (13-18 years) and adults (18+ years), and Spearman's correlations were performed for paediatric data. White and grey matter stiffness for each frequency and their frequency dependence was found to be very similar in paediatric and adult subjects (p > 0.05 all variables). No significant correlations were found when comparing G* with age, FA, MD or volume. Adult G*, FA, MD and volume values were within range of others reported in the literature. Paediatric white and grey matter stiffness values are similar to those of adults. We conclude that clinically, adult values can be used as a baseline measure in paediatric brain MRE.

Glioblastomas represent a challenging problem with an extremely poor survival rate. Since these tumour cells have a highly invasive character, an effective surgical resection as well as chemotherapy and radiotherapy is very difficult. Convection-enhanced delivery (CED), a technique that consists in the injection of a therapeutic agent directly into the parenchyma, has shown encouraging results. Its efficacy depends on the ability to predict, in the pre-operative phase, the distribution of the drug inside the tumour. This paper proposes a method to compute a fundamental parameter for CED modelling outcomes, the hydraulic permeability, in three brain structures. Therefore, a bidimensional brain-like structure was built out of the main geometrical features of the white matter: axon diameter distribution extrapolated from electron microscopy images, extracellular space (ECS) volume fraction and ECS width. The axons were randomly allocated inside a defined border, and the ECS volume fraction as well as the ECS width maintained in a physiological range. To achieve this result, an outward packing method coupled with a disc shrinking technique was implemented. The fluid flow through the axons was computed by solving Navier-Stokes equations within the computational fluid dynamics solver ANSYS. From the fluid and pressure fields, an homogenisation technique allowed establishing the optimal representative volume element (RVE) size. The hydraulic permeability computed on the RVE was found in good agreement with experimental data from the literature.

This study aims to detect the neural substrate underlying the language impairment in children with developmental language disorder (DLD) using diffusion tensor imaging (DTI) tractography. Deterministic DTI tractography was performed in a group of right-handed children with DLD (N = 17; mean age 10;07 ± 2;01 years) and a typically developing control group matched for age, gender and handedness (N = 22; mean age 11;00 ± 1;11 years) to bilaterally identify the superior longitudinal fascicle, arcuate fascicle, anterior lateral segment and posterior lateral segment (also called dorsal language network) and the middle and inferior longitudinal fascicle, extreme capsule fiber system and uncinate fascicle (also called ventral language network). Language skills were assessed using an extensive, standardized test battery. Differences in language performance, white matter organization and structural lateralization of the language network were statistically analyzed. Children with DLD showed a higher overall volume and higher ADC values for the left-hemispheric language related WM tracts. In addition, in children with DLD, the majority (88%; 7/8) of the studied language related WM tracts did not show a significant left or right lateralization pattern. These structural alterations might underlie the language impairment in children with DLD.

Several studies have investigated the trait-like characteristics of conflict processing at different levels. Our study extends these findings by reporting a practice-based improvement in within-trial conflict processing across two sessions. Eighty-three participants performed the same flanker task on two occasions 2 weeks apart. A subset of 37 subjects also underwent diffusion tensor imaging (DTI) scanning the day before the first behavioral task. Despite the trait-like characteristics of conflict processing, within-trial conflict processing in the second behavioral session was significantly shorter than that in the first session, indicating a practice-based improvement in conflict processing. Furthermore, changes in within-trial conflict processing across the two sessions exhibited significant individual differences. Tract-based spatial statistics revealed that the improvement across two sessions was related to the axial diffusivity values in white matter regions, including the body and splenium of the corpus callosum, right superior and posterior corona radiate, and right superior longitudinal fasciculus. Subsequently, lasso regression with leave-one-out cross validation was used to assess the predictive ability of white matter microstructural characteristics in significant regions. The results showed that 61% of individual variability in the improvement in the within-trial conflict processing could be explained by variations in the axial diffusivity values in the four significant regions and the within-trial conflict processing in the first session. These results suggest that axonal morphology in the white tracts connecting conflict-related regions predicts the degree of within-trial conflict processing improvement across two sessions.

Adults with severe traumatic brain injury (TBI) often suffer poor social cognition. Social cognition is complex, requiring verbal, non-verbal, auditory, visual and affective input and integration. While damage to focal temporal and frontal areas has been implicated in disorders of social cognition after TBI, the role of white matter pathology has not been examined. In this study 17 adults with chronic, severe TBI and 17 control participants underwent structural MRI scans and Diffusion Tensor Imaging. The Awareness of Social Inference Test (TASIT) was used to assess their ability to understand emotional states, thoughts, intentions and conversational meaning in everyday exchanges. Track-based spatial statistics were used to perform voxelwise analysis of Fractional Anisotropy (FA) and Mean Diffusivity (MD) of white matter tracts associated with poor social cognitive performance. FA suggested a wide range of tracts were implicated in poor TASIT performance including tracts known to mediate, auditory localisation (planum temporale) communication between nonverbal and verbal processes in general (corpus callosum) and in memory in particular (fornix) as well as tracts and structures associated with semantics and verbal recall (left temporal lobe and hippocampus), multimodal processing and integration (thalamus, external capsule, cerebellum) and with social cognition (orbitofrontal cortex, frontopolar cortex, right temporal lobe). Even when controlling for non-social cognition, the corpus callosum, fornix, bilateral thalamus, right external capsule and right temporal lobe remained significant contributors to social cognitive performance. This study highlights the importance of loss of white matter connectivity in producing complex social information processing deficits after TBI.

Despite many studies reporting a variety of alterations in brain networks in patients with attention deficit hyperactivity disorder (ADHD), alterations in hemispheric anatomical networks are still unclear. In this study, we investigated topology alterations in hemispheric white matter in patients with ADHD and the relationship between these alterations and clinical features of the illness. Weighted hemispheric brain anatomical networks were first constructed for each of 40 right-handed patients with ADHD and 53 matched normal controls. Then, graph theoretical approaches were utilized to compute hemispheric topological properties. The small-world property was preserved in the hemispheric network. Furthermore, a significant group-by-hemisphere interaction was revealed in global efficiency, local efficiency and characteristic path length, attributed to the significantly reduced hemispheric asymmetry of global and local integration in patients with ADHD compared with normal controls. Specifically, reduced asymmetric regional efficiency was found in three regions. Finally, we found that the abnormal asymmetry of hemispheric brain anatomical network topology and regional efficiency were both associated with clinical features (the Adult ADHD Self-Report Scale and Wechsler Adult Intelligence Scale) in patients. Our findings provide new insights into the lateralized nature of hemispheric dysconnectivity and highlight the potential for using brain network measures of hemispheric asymmetry as neural biomarkers for ADHD and its clinical features.

The structure and function of the human brain is closely related to cognitive processes of the mind and physiological processes of the body, suggesting that an intricate relationship exists between cognitive health, body health, and underlying neural architecture. In the current study, morphometric differences in cortical and subcortical gray matter regions, white matter integrity, and resting-state functional connectivity was assessed to determine what combinations of neural variables best explain an interconnected behavioral relationship between body mass index (BMI), general intelligence, and specific measures of executive function. Data for 82 subjects were obtained from the Nathan Kline Institute Rockland Sample. Behavioral results indicated a negative relationship between BMI and intelligence, which exhibited mediation by an inhibitory measure of executive function. Neural analyses further revealed generally contrasting associations of BMI, intelligence, and executive function with cortical morphometric regions important for inhibitory control and directed attention. Moreover, BMI related to morphometric alterations in components of a frontolimbic network, namely reduced thickness in the anterior cingulate cortex and ventromedial prefrontal cortex, whereas intelligence and inhibitory control primarily related to increased thickness and volume in parietal regions, as well as significantly increased across-network connectivity of visual and default mode resting-state networks. These results propose that medial prefrontal structure and interconnected frontolimbic and frontoparietal networks are important to consider in the relationship between BMI, intelligence, and executive function.

Because the visual cortices are contra-laterally organized, inter-hemispheric transfer tasks have been used to behaviorally probe how information briefly presented to one hemisphere of the visual cortex is integrated with responses resulting from the ipsi- or contra-lateral motor cortex. By forcing rapid information exchange across diverse regions, these tasks robustly activate not only gray matter regions, but also white matter tracts. It is likely that the response hand itself (dominant or non-dominant) modulates gray and white matter activations during within and inter-hemispheric transfer. Yet the role of uni-manual responses and/or right hand dominance in modulating brain activations during such basic tasks is unclear. Here we investigated how uni-manual responses with either hand modulated activations during a basic visuo-motor task (the established Poffenberger paradigm) alternating between inter- and within-hemispheric transfer conditions. In a large sample of strongly right-handed adults (n = 49), we used a factorial combination of transfer condition [Inter vs. Within] and response hand [Dominant(Right) vs. Non-Dominant (Left)] to discover fMRI-based activations in gray matter, and in narrowly defined white matter tracts. These tracts were identified using a priori probabilistic white matter atlases. Uni-manual responses with the right hand strongly modulated activations in gray matter, and notably in white matter. Furthermore, when responding with the left hand, activations during inter-hemispheric transfer were strongly predicted by the degree of right-hand dominance, with increased right-handedness predicting decreased fMRI activation. Finally, increasing age within the middle-aged sample was associated with a decrease in activations. These results provide novel evidence of complex relationships between uni-manual responses in right-handed subjects, and activations during within- and inter-hemispheric transfer suggest that the organization of the motor system exerts sophisticated functional effects. Moreover, our evidence of activation in white matter tracts is consistent with prior studies, confirming fMRI-detectable white matter activations which are systematically modulated by experimental condition.

Objective: Recent MRI studies have shown that the orientation of nerve fibres relative to the main magnetic field affects the R 2 *(= 1/T 2 *) relaxation rate in white matter (WM) structures. The underlying physical causes have been discussed in several studies but are still not completely understood. However, understanding these effects in detail is of great importance since this might serve as a basis for the development of new diagnostic tools and/or improve quantitative susceptibility mapping techniques. Therefore, in addition to the known angular dependence of R 2 *, the current study investigates the relationship between fibre orientation and the longitudinal relaxation rate, R 1 (= 1/T 1 ), as well as the apparent water content., Materials and Methods: For a group of 16 healthy subjects, a series of gradient echo, echo-planar and diffusion weighted images were acquired at 3T from which the decay rates, the apparent water content and the diffusion direction were reconstructed. The diffusion weighted data were used to determine the angle between the principle fibre direction and the main magnetic field to examine the angular dependence of R 1 and apparent water content., Results: The obtained results demonstrate that both parameters depend on the fibre orientation and exhibit a positive correlation with the angle between fibre direction and main magnetic field., Conclusion: These observations could be helpful to improve and/or constrain existing biophysical models of brain microstructure by imposing additional constraints resulting from the observed angular dependence R 1 and apparent water content in white matter.

Functional connectivity density mapping (FCDM) is a newly developed data-driven technique that quantifies the number of local and global functional connections for each voxel in the brain. In this study, we evaluated reproducibility, sensitivity, and specificity of both local functional connectivity density (lFCD) and global functional connectivity density (gFCD). We compared these metrics using the human connectome project (HCP) compatible high-resolution (2 mm isotropic, TR = 0.8 s) multiband (MB), and more typical, lower resolution (3.5 mm isotropic, TR = 2.0 s) single-band (SB) resting state functional MRI (rs-fMRI) acquisitions. Furthermore, in order to be more clinically feasible, only rs-fMRI scans that lasted seven minutes were tested. Subjects were scanned twice within a two-week span. We found sensitivity and specificity increased and reproducibility either increased or did not change for the MB compared to the SB acquisitions. The MB scans also showed improved gray matter/white matter contrast compared to the SB scans. The lFCD and gFCD patterns were similar across MB and SB scans and confined predominantly to gray matter. We also observed a strong spatial correlation of FCD between MB and SB scans indicating the two acquisitions provide similar information. These findings indicate high-resolution MB acquisitions improve the quality of FCD data, and seven minute rs-fMRI scan can provide robust FCD measurements.

Population studies of brain function with resting-state functional magnetic resonance imaging (rs-fMRI) largely rely on the accurate inter-subject registration of functional areas. This is typically achieved through registration of the corresponding T1-weighted MR images with more structural details. However, accumulating evidence has suggested that such strategy cannot well-align functional regions which are not necessarily confined by the anatomical boundaries defined by the T1-weighted MR images. To mitigate this problem, various registration algorithms based directly on rs-fMRI data have been developed, most of which have utilized functional connectivity (FC) as features for registration. However, most of the FC-based registration methods usually extract the functional features only from the thin and highly curved cortical grey matter (GM), posing a great challenge in accurately estimating the whole-brain deformation field. In this paper, we demonstrate that the additional useful functional features can be extracted from brain regions beyond the GM, particularly, white-matter (WM) based on rs-fMRI, for improving the overall functional registration. Specifically, we quantify the local anisotropic correlation patterns of the blood oxygenation level-dependent (BOLD) signals, modeled by functional correlation tensors (FCTs), in both GM and WM. Functional registration is then performed based on multiple components of the whole-brain FCTs using a multichannel Large Deformation Diffeomorphic Metric Mapping (mLDDMM) algorithm. Experimental results show that our proposed method achieves superior functional registration performance, compared with other conventional registration methods.

Diffusion tensor imaging fiber tracking (DTI FT) is used to visualize subcortical fiber tracts. Yet, there is no standard at hand to visualize language-involved subcortical fibers reliably. Thus, this study investigates the feasibility of using language-related cortical areas identified via repetitive navigated transcranial magnetic stimulation (rTMS) to seed DTI FT of subcortical language tracts. From 2011 to 2014, 37 patients with left-hemispheric perisylvian lesions were examined. Language-positive rTMS stimulation spots were integrated in the deterministic tractography software (BrainLAB, iPlanNet 3.0) as objects and used as seed regions for DTI FT. Tractography was then performed in each patient with 77 different combinations of fiber lengths (40 - 100 mm) and fractional anisotropy (FA; 0.01 - 0.5). The rTMS-based DTI FT identified all commonly known subcortical language tracts, such as the corticonuclear tract, arcuate fascicle, uncinate fascicle, superior longitudinal fascicle, inferior longitudinal fascicle, arcuate fibers, commissural fibers, corticothalamic fibers, and the fronto-occipital fascicle. In 32 patients (86.5 %), each above-named tract could be visualized, while at least 6 out of these 9 tracts were identified in each patient. A fiber length of 100 mm and an FA of 0.1 or 0.15 provided optimal visualization by revealing 125 and 61 individually tracked fibers per visualized language tract and 90 % and 73 % of all language-related tracts, respectively. This study proves the feasibility of rTMS-based DTI FT for subcortical language tracts, provides suitable settings, and shows its easy and standardizable application for the visualization of every language tract in 86.5 % of patients.

High education, as a proxy of cognitive reserve (CR), has been associated with cognitive advantage amongst old adults and may operate through neuroprotective and/or compensation mechanisms. In neuromaging studies, indirect evidences of neuroprotection can be inferred from positive relationships between CR and brain integrity measures. In contrast, compensation allows high CR elders to sustain greater brain damage. We included 100 cognitively normal old-adults and investigated the associations and interactions between education, speed of processing (SP), memory and two brain integrity measures: cortical thickness (CTh) of gray matter (GM) and fractional anisotropy (FA) in the white matter (WM). High education was associated with better cognitive performance, enlarged CTh in frontal lobe areas and reduced measures of FA in several areas. Better SP performance in higher educated subjects was related to more preserved GM and WM, while memory status amongst high educated elders was better explained by a putative compensatory mechanism and independently from cerebrovascular risk indicators. Moreover, we analyzed the direct effect of age on measures of brain integrity and found a stronger negative effect on WM than in CTh, which was accentuated amongst the high CR sample. Our study suggests that the cognitive advantage associated to high education among healthy aging is related to the coexistence of both neuroprotective and compensatory mechanisms. In particular, high educated elders seem to have greater capacity to counteract a more abrupt age impact on WM integrity.

The concept of attachment in long-term interpersonal relationships has been linked to relationship outcome and social-emotional health. To date, no relationship between the structural properties of the human amygdala and attachment in romantic relationships (measured through self-reported attachment related anxiety and avoidance) has been described. The aim of the current study was to investigate the relationship between amygdala structure as well as amygdala structural and functional connectivity and attachment anxiety and avoidance. To this end, we collected self-report attachment data on a sample of female young adults. We then examined associations between attachment and mean diffusivity, fractional anisotropy and resting state functional connectivity MRI (rs-FC) of the amygdala and its white matter connections with the prefrontal cortex. We found that lower integrity of the left amygdala was linked with attachment avoidance (e.g., being less comfortable in seeking proximity with others and depending on others) and that greater structural integrity of the uncinate fasciculus was positively associated with avoidance. Lastly, we found that stronger rs-FC between the bilateral amygdala and medial prefrontal regions was linked with greater avoidance. Our findings are compatible with and expand previous results reported by studies that have taken a task-related fMRI approach, furthering our understanding of the neurobiological mechanisms of attachment, and in particular implicating the system formed by amygdala and prefrontal areas in the patterns of behavior that regulate emotional proximity in romantic relationships. These findings have the potential to further our understanding of the affective mechanisms underlying attachment behavior.

Individual differences in self-monitoring, which are the capability to adjust behavior to adapt to social situations, influence a wide range of social behaviors. However, understanding of focal differences in brain structures related to individual self-monitoring is minimal, particularly when micro and macro structures are considered simultaneously. The present study investigates the relationship between self-monitoring and brain structure in a relatively large sample of young adults. Voxel-based morphometry (VBM) revealed a significant positive correlation between self-monitoring and gray matter volume in the dorsal cingulate anterior cortex (dACC), dorsal lateral prefrontal cortex (DLPFC), and bilateral ventral striatum (VS). Further analysis revealed a significant negative correlation between self-monitoring and white matter (WM) integrity, as indexed by fractional anisotropy (FA) in the anterior cingulum (ACG) bundle. Moreover, there was a significant positive correlation between self-monitoring and mean radius diffusion (RD). These results shed light on the structural neural basis of variation in self-monitoring.

This study examined the reliability of high angular resolution diffusion tensor imaging (HARDI) data collected on a single individual across several sessions using the same scanner. HARDI data was acquired for one healthy adult male at the same time of day on ten separate days across a one-month period. Environmental factors (e.g. temperature) were controlled across scanning sessions. Tract Based Spatial Statistics (TBSS) was used to assess session-to-session variability in measures of diffusion, fractional anisotropy (FA) and mean diffusivity (MD). To address reliability within specific structures of the medial temporal lobe (MTL; the focus of an ongoing investigation), probabilistic tractography segmented the Entorhinal cortex (ERc) based on connections with Hippocampus (HC), Perirhinal (PRc) and Parahippocampal (PHc) cortices. Streamline tractography generated edge weight (EW) metrics for the aforementioned ERc connections and, as comparison regions, connections between left and right rostral and caudal anterior cingulate cortex (ACC). Coefficients of variation (CoV) were derived for the surface area and volumes of these ERc connectivity-defined regions (CDR) and for EW across all ten scans, expecting that scan-to-scan reliability would yield low CoVs. TBSS revealed no significant variation in FA or MD across scanning sessions. Probabilistic tractography successfully reproduced histologically-verified adjacent medial temporal lobe circuits. Tractography-derived metrics displayed larger ranges of scanner-to-scanner variability. Connections involving HC displayed greater variability than metrics of connection between other investigated regions. By confirming the test retest reliability of HARDI data acquisition, support for the validity of significant results derived from diffusion data can be obtained.

Mind pops or involuntary semantic memories refer to words, phrases, images, or melodies that suddenly pop into one's mind without any deliberate attempt to recall them. Despite their prevalence in everyday life, research on mind pops has started only recently. Notably, mind pops are very similar to clinical involuntary phenomena such as hallucinations in schizophrenia, suggesting their potential role in pathology. The present study aimed to investigate the relationship between mind pops and the brain morphometry measured in 302 healthy young adults; after exclusions, 256 participants were included in our analyses. Specifically, the Mind Popping Questionnaire (MPQ) was employed to measure the degree of individual mind pops, whereas the Voxel-Based Morphometry (VBM) was used to compute the volumes of both gray and white matter tissues. Multiple regression analyses on MPQ and VBM metrics indicated that high-frequency mind pops were significantly associated with smaller gray matter volume in the left middle temporal gyrus as well as with larger gray and white matter volume in the right medial prefrontal cortex. This increase in mind pops is also linked to higher creativity and the personality trait of 'openness'. These data not only suggest a key role of the two regions in generating self-related thoughts, but also open a possible link between brain and creativity or personality.

Susceptibility to scams is a significant issue among older adults, even among those with intact cognition. Age-related changes in brain macrostructure may be associated with susceptibility to scams; however, this has yet to be explored. Based on previous work implicating frontal and temporal lobe functioning as important in decision making, we tested the hypothesis that susceptibility to scams is associated with smaller grey matter volume in frontal and temporal lobe regions in a large community-dwelling cohort of non-demented older adults. Participants (N = 327, mean age = 81.55, mean education = 15.30, 78.9 % female) completed a self-report measure used to assess susceptibility to scams and an MRI brain scan. Results indicated an inverse association between overall grey matter and susceptibility to scams in models adjusted for age, education, and sex; and in models further adjusted for cognitive function. No significant associations were observed for white matter, cerebrospinal fluid, or total brain volume. Models adjusted for age, education, and sex revealed seven clusters showing smaller grey matter in the right parahippocampal/hippocampal/fusiform, left middle temporal, left orbitofrontal, right ventromedial prefrontal, right middle temporal, right precuneus, and right dorsolateral prefrontal regions. In models further adjusted for cognitive function, results revealed three significant clusters showing smaller grey matter in the right parahippocampal/hippocampal/fusiform, right hippocampal, and right middle temporal regions. Lower grey matter concentration in specific brain regions may be associated with susceptibility to scams, even after adjusting for cognitive ability. Future research is needed to determine whether grey matter reductions in these regions may be a biomarker for susceptibility to scams in old age.

Traumatic injury to axons in white matter of the brain and spinal cord occurs primarily via tensile stretch. During injury, the stress and strain experienced at the tissue level is transferred to the microscopic axons. How this transfer occurs, and the primary constituents dictating this transfer must be better understood to develop more accurate multi-scale models of injury. Previous studies have characterized axon tortuosity and kinematic behavior in 2-dimensions (2-D), where axons have been modeled to exhibit non-affine (discrete), affine (composite-like), or switching behavior. In this study, we characterize axon tortuosity and model axon kinematic behavior in 3-dimensions (3-D). Embryonic chick spinal cords at different development stages were excised and stretched. Cords were then fixed, transversely sectioned, stained, and imaged. 3-D axon tortuosity was measured from confocal images using a custom-built MATLAB script. 2-D kinematic models previously described in Bain et al. (J Biomech Eng 125(6):798, 2003) were extended, re-derived, and validated for the 3-D case. Results showed that 3-D tortuosity decreased with stretch, exhibiting similar trends with changes in development as observed in the 2-D studies. Kinematic parameters also displayed similar general trends. Axons demonstrated more affine behavior with increasing stretch and development. In comparison with 2-D results, a smaller percentage of the populations of 3-D axons were predicted to follow pure non-affine behavior. The data and kinematic models presented herein can be incorporated into multi-scale CNS injury models, which can advance the accuracy of the models and improve the potential to identify axonal injury thresholds.

Purpose: Perfusion assessment by monitoring the transport of a tracer bolus depends critically on conversion of signal intensity into tracer concentration. Two main assumptions are generally applied for this conversion; (1) contrast agent relaxivity is identical in blood and tissue, (2) change in signal intensity depends only on the primary relaxation effect. The purpose of the study was to assess the validity and influence of these assumptions., Materials and Methods: Blood and cerebral tissue relaxivities r1, r2, and r2* for gadodiamide were measured in four pigs at 1.5 T. Gadolinium concentration was determined by inductively coupled plasma atomic emission spectroscopy. Influence of the relaxivities, secondary relaxation effects and choice of singular value decomposition (SVD) regularization threshold was studied by simulations., Results: In vivo relaxivities relative to blood concentration [in s(-1) mM(-1) for blood, gray matter (GM), white matter (WM)] were for r1 (2.614 ± 1.061, 0.010 ± 0.001, 0.004 ± 0.002), r2 (5.088 ± 0.952, 0.091 ± 0.008, 0.059 ± 0.014), and r2* (13.292 ± 3.928, 1.696 ± 0.157, 0.910 ± 0.139). Although substantial, by a nonparametric test for paired samples, the differences were not statistically significant. The GM to WM blood volume ratio was estimated to 2.6 ± 0.9 by r1, 1.6 ± 0.3 by r2, and 1.9 ± 0.2 by r2*. Secondary relaxation was found to reduce the tissue blood flow, as did the SVD regularization threshold., Conclusion: Contrast agent relaxivity is not identical in blood and tissue leading to substantial errors. Further errors are introduced by secondary relaxation effects and the SVD regularization.

The present study explored multi-scale entropy (MSE) analysis to investigate the entropy of resting state fMRI signals across multiple time scales. MSE analysis was developed to distinguish random noise from complex signals since the entropy of the former decreases with longer time scales while the latter signal maintains its entropy due to a "self-resemblance" across time scales. A long resting state BOLD fMRI (rs-fMRI) scan with 1000 data points was performed on five healthy young volunteers to investigate the spatial and temporal characteristics of entropy across multiple time scales. A shorter rs-fMRI scan with 240 data points was performed on a cohort of subjects consisting of healthy young (age 23 ± 2 years, n = 8) and aged volunteers (age 66 ± 3 years, n = 8) to investigate the effect of healthy aging on the entropy of rs-fMRI. The results showed that MSE of gray matter, rather than white matter, resembles closely that of f (-1) noise over multiple time scales. By filtering out high frequency random fluctuations, MSE analysis is able to reveal enhanced contrast in entropy between gray and white matter, as well as between age groups at longer time scales. Our data support the use of MSE analysis as a validation metric for quantifying the complexity of rs-fMRI signals.