The genetic architecture of multimodal human brain age

The complex biological mechanisms underlying human brain aging remain incompletely understood. This study investigated the genetic architecture of three brain age gaps (BAG) derived from gray matter volume (GM-BAG), white matter microstructure (WM-BAG), and functional connectivity (FC-BAG). We identified sixteen genomic loci that reached genome-wide significance (P-value < 5×10-8). A gene-drug-disease network highlighted genes linked to GM-BAG for treating neurodegenerative and neuropsychiatric disorders and WM-BAG genes for cancer therapy. GM-BAG displayed the most pronounced heritability enrichment in genetic variants within conserved regions. Oligodendrocytes and astrocytes, but not neurons, exhibited notable heritability enrichment in WM and FC-BAG, respectively. Mendelian randomization identified potential causal effects of several chronic diseases on brain aging, such as type 2 diabetes on GM-BAG and AD on WM-BAG. Our results provide insights into the genetics of human brain aging, with clinical implications for potential lifestyle and therapeutic interventions. All results are publicly available at https://labs.loni.usc.edu/medicine .

Circulating cytotoxic immune cell composition, activation status and toxins expression associate with white matter microstructure in bipolar disorder

Patients with bipolar disorder (BD) show higher immuno-inflammatory setpoints, with in vivo alterations in white matter (WM) microstructure and post-mortem infiltration of T cells in the brain. Cytotoxic CD8+ T cells can enter and damage the brain in inflammatory disorders, but little is known in BD. Our study aimed to investigate the relationship between cytotoxic T cells and WM alterations in BD. In a sample of 83 inpatients with BD in an active phase of illness (68 depressive, 15 manic), we performed flow cytometry immunophenotyping to investigate frequencies, activation status, and expression of cytotoxic markers in CD8+ and tested for their association with diffusion tensor imaging (DTI) measures of WM microstructure. Frequencies of naïve and activated CD8+ cell populations expressing Perforin, or both Perforin and Granzyme, negatively associated with WM microstructure. CD8+ Naïve cells negative for Granzyme and Perforin positively associates with indexes of WM integrity, while the frequency of CD8+ memory cells negatively associates with index of WM microstructure, irrespective of toxins expression. The resulting associations involve measures representative of orientational coherence and myelination of the fibers (FA and RD), suggesting disrupted oligodendrocyte-mediated myelination. These findings seems to support the hypothesis that immunosenescence (less naïve, more memory T cells) can detrimentally influence WM microstructure in BD and that peripheral CD8+ T cells may participate in inducing an immune-related WM damage in BD mediated by killer proteins.

Histology-informed multiscale modeling of human brain white matter

In this study, we propose a novel micromechanical model for the brain white matter, which is described as a heterogeneous material with a complex network of axon fibers embedded in a soft ground matrix. We developed this model in the framework of RVE-based multiscale theories in combination with the finite element method and the embedded element technique for embedding the fibers. Microstructural features such as axon diameter, orientation and tortuosity are incorporated into the model through distributions derived from histological data. The constitutive law of both the fibers and the matrix is described by isotropic one-term Ogden functions. The hyperelastic response of the tissue is derived by homogenizing the microscopic stress fields with multiscale boundary conditions to ensure kinematic compatibility. The macroscale homogenized stress is employed in an inverse parameter identification procedure to determine the hyperelastic constants of axons and ground matrix, based on experiments on human corpus callosum. Our results demonstrate the fundamental effect of axon tortuosity on the mechanical behavior of the brain's white matter. By combining histological information with the multiscale theory, the proposed framework can substantially contribute to the understanding of mechanotransduction phenomena, shed light on the biomechanics of a healthy brain, and potentially provide insights into neurodegenerative processes.

Whole-brain, gray, and white matter time-locked functional signal changes with simple tasks and model-free analysis

Recent studies have revealed the production of time-locked blood oxygenation level-dependent (BOLD) functional MRI (fMRI) signals throughout the entire brain in response to tasks, challenging the existence of sparse and localized brain functions and highlighting the pervasiveness of potential false negative fMRI findings. "Whole-brain" actually refers to gray matter, the only tissue traditionally studied with fMRI. However, several reports have demonstrated reliable detection of BOLD signals in white matter, which have previously been largely ignored. Using simple tasks and analyses, we demonstrate BOLD signal changes across the whole brain, in both white and gray matters, in similar manner to previous reports of whole brain studies. We investigated whether white matter displays time-locked BOLD signals across multiple structural pathways in response to a stimulus in a similar manner to the cortex. We find that both white and gray matter show time-locked activations across the whole brain, with a majority of both tissue types showing statistically significant signal changes for all task stimuli investigated. We observed a wide range of signal responses to tasks, with different regions showing different BOLD signal changes to the same task. Moreover, we find that each region may display different BOLD responses to different stimuli. Overall, we present compelling evidence that, just like all gray matter, essentially all white matter in the brain shows time-locked BOLD signal changes in response to multiple stimuli, challenging the idea of sparse functional localization and the prevailing wisdom of treating white matter BOLD signals as artifacts to be removed.

Local neuroanatomical and tract-based proxies of optimal subcallosal cingulate deep brain stimulation

BACKGROUND

Deep brain stimulation of the subcallosal cingulate area (SCC-DBS) is a promising neuromodulatory therapy for treatment-resistant depression (TRD). Biomarkers of optimal target engagement are needed to guide surgical targeting and stimulation parameter selection and to reduce variance in clinical outcome.

OBJECTIVE/HYPOTHESIS

We aimed to characterize the relationship between stimulation location, white matter tract engagement, and clinical outcome in a large (n = 60) TRD cohort treated with SCC-DBS. A smaller cohort (n = 22) of SCC-DBS patients with differing primary indications (bipolar disorder/anorexia nervosa) was utilized as an out-of-sample validation cohort.

METHODS

Volumes of tissue activated (VTAs) were constructed in standard space using high-resolution structural MRI and individual stimulation parameters. VTA-based probabilistic stimulation maps (PSMs) were generated to elucidate voxelwise spatial patterns of efficacious stimulation. A whole-brain tractogram derived from Human Connectome Project diffusion-weighted MRI data was seeded with VTA pairs, and white matter streamlines whose overlap with VTAs related to outcome ('discriminative' streamlines; Puncorrected < 0.05) were identified using t-tests. Linear modelling was used to interrogate the potential clinical relevance of VTA overlap with specific structures.

RESULTS

PSMs varied by hemisphere: high-value left-sided voxels were located more anterosuperiorly and squarely in the lateral white matter, while the equivalent right-sided voxels fell more posteroinferiorly and involved a greater proportion of grey matter. Positive discriminative streamlines localized to the bilateral (but primarily left) cingulum bundle, forceps minor/rostrum of corpus callosum, and bilateral uncinate fasciculus. Conversely, negative discriminative streamlines mostly belonged to the right cingulum bundle and bilateral uncinate fasciculus. The best performing linear model, which utilized information about VTA volume overlap with each of the positive discriminative streamline bundles as well as the negative discriminative elements of the right cingulum bundle, explained significant variance in clinical improvement in the primary TRD cohort (R = 0.46, P < 0.001) and survived repeated 10-fold cross-validation (R = 0.50, P = 0.040). This model was also able to predict outcome in the out-of-sample validation cohort (R = 0.43, P = 0.047).

CONCLUSION(S)

These findings reinforce prior indications of the importance of white matter engagement to SCC-DBS treatment success while providing new insights that could inform surgical targeting and stimulation parameter selection decisions.

Aerobic exercise reverses aging-induced depth-dependent decline in cerebral microcirculation

Aging is a major risk factor for cognitive impairment. Aerobic exercise benefits brain function and may promote cognitive health in older adults. However, underlying biological mechanisms across cerebral gray and white matter are poorly understood. Selective vulnerability of the white matter to small vessel disease and a link between white matter health and cognitive function suggests a potential role for responses in deep cerebral microcirculation. Here, we tested whether aerobic exercise modulates cerebral microcirculatory changes induced by aging. To this end, we carried out a comprehensive quantitative examination of changes in cerebral microvascular physiology in cortical gray and subcortical white matter in mice (3-6 vs. 19-21 months old), and asked whether and how exercise may rescue age-induced deficits. In the sedentary group, aging caused a more severe decline in cerebral microvascular perfusion and oxygenation in deep (infragranular) cortical layers and subcortical white matter compared with superficial (supragranular) cortical layers. Five months of voluntary aerobic exercise partly renormalized microvascular perfusion and oxygenation in aged mice in a depth-dependent manner, and brought these spatial distributions closer to those of young adult sedentary mice. These microcirculatory effects were accompanied by an improvement in cognitive function. Our work demonstrates the selective vulnerability of the deep cortex and subcortical white matter to aging-induced decline in microcirculation, as well as the responsiveness of these regions to aerobic exercise.

Intracranial electrophysiological and structural basis of BOLD functional connectivity in human brain white matter

While functional MRI (fMRI) studies have mainly focused on gray matter, recent studies have consistently found that blood-oxygenation-level-dependent (BOLD) signals can be reliably detected in white matter, and functional connectivity (FC) has been organized into distributed networks in white matter. Nevertheless, it remains unclear whether this white matter FC reflects underlying electrophysiological synchronization. To address this question, we employ intracranial stereotactic-electroencephalography (SEEG) and resting-state fMRI data from a group of 16 patients with drug-resistant epilepsy. We find that BOLD FC is correlated with SEEG FC in white matter, and this result is consistent across a wide range of frequency bands for each participant. By including diffusion spectrum imaging data, we also find that white matter FC from both SEEG and fMRI are correlated with white matter structural connectivity, suggesting that anatomical fiber tracts underlie the functional synchronization in white matter. These results provide evidence for the electrophysiological and structural basis of white matter BOLD FC, which could be a potential biomarker for psychiatric and neurological disorders.

Poorer White Matter Microstructure Predicts Slower and More Variable Reaction Time Performance: Evidence for a Neural Noise Hypothesis in a Large Lifespan Cohort

Most prior research has focused on characterizing averages in cognition, brain characteristics, or behavior, and attempting to predict differences in these averages among individuals. However, this overwhelming focus on mean levels may leave us with an incomplete picture of what drives individual differences in behavioral phenotypes by ignoring the variability of behavior around an individual's mean. In particular, enhanced white matter (WM) structural microstructure has been hypothesized to support consistent behavioral performance by decreasing Gaussian noise in signal transfer. Conversely, lower indices of WM microstructure are associated with greater within-subject variance in the ability to deploy performance-related resources, especially in clinical populations. We tested a mechanistic account of the "neural noise" hypothesis in a large adult lifespan cohort (Cambridge Centre for Ageing and Neuroscience) with over 2500 adults (ages 18-102; 1508 female; 1173 male; 2681 behavioral sessions; 708 MRI scans) using WM fractional anisotropy to predict mean levels and variability in reaction time performance on a simple behavioral task using a dynamic structural equation model. By modeling robust and reliable individual differences in within-person variability, we found support for a neural noise hypothesis (Kail, 1997), with lower fractional anisotropy predicted individual differences in separable components of behavioral performance estimated using dynamic structural equation model, including slower mean responses and increased variability. These effects remained when including age, suggesting consistent effects of WM microstructure across the adult lifespan unique from concurrent effects of aging. Crucially, we show that variability can be reliably separated from mean performance using advanced modeling tools, enabling tests of distinct hypotheses for each component of performance.SIGNIFICANCE STATEMENT Human cognitive performance is defined not just by the long-run average, but trial-to-trial variability around that average. However, investigations of cognitive abilities and changes during aging have largely ignored this variability component of behavior. We provide evidence that white matter (WM) microstructure predicts individual differences in mean performance and variability in a sample spanning the adult lifespan (18-102). Unlike prior studies of cognitive performance and variability, we modeled variability directly and distinct from mean performance using a dynamic structural equation model, which allows us to decouple variability from mean performance and other complex features of performance (e.g., autoregression). The effects of WM were robust above the effect of age, highlighting the role of WM in promoting fast and consistent performance.

Hippocampal and motor regions contribute to memory benefits after enacted encoding: cross-sectional and longitudinal evidence

The neurobiological underpinnings of action-related episodic memory and how enactment contributes to efficient memory encoding are not well understood. We examine whether individual differences in level (n = 338) and 5-year change (n = 248) in the ability to benefit from motor involvement during memory encoding are related to gray matter (GM) volume, white matter (WM) integrity, and dopamine-regulating genes in a population-based cohort (age range = 25-80 years). A latent profile analysis identified 2 groups with similar performance on verbal encoding but with marked differences in the ability to benefit from motor involvement during memory encoding. Impaired ability to benefit from enactment was paired with smaller HC, parahippocampal, and putamen volume along with lower WM microstructure in the fornix. Individuals with reduced ability to benefit from encoding enactment over 5 years were characterized by reduced HC and motor cortex GM volume along with reduced WM microstructure in several WM tracts. Moreover, the proportion of catechol-O-methyltransferase-Val-carriers differed significantly between classes identified from the latent-profile analysis. These results provide converging evidence that individuals with low or declining ability to benefit from motor involvement during memory encoding are characterized by low and reduced GM volume in regions critical for memory and motor functions along with altered WM microstructure.

Longitudinal associations between adolescent catch-up sleep, white-matter maturation and internalizing problems

Sleep is an important contributor for neural maturation and emotion regulation during adolescence, with long-term effects on a range of white matter tracts implicated in affective processing in at-risk populations. We investigated the effects of adolescent sleep patterns on longitudinal changes in white matter development and whether this is related to the emergence of emotional (internalizing) problems. Sleep patterns and internalizing problems were assessed using self-report questionnaires in adolescents recruited in the general population followed up from age 14-19 years (N = 111 White matter structure was measured using diffusion tensor imaging (DTI) and estimated using fractional anisotropy (FA). We found that longitudinal increases in time in bed (TIB) on weekends and increases in TIB-variability between weekdays to weekend, were associated with an increase in FA in various interhemispheric and cortico-striatal tracts. Extracted FA values from left superior longitudinal fasciculus mediated the relationship between increases in TIB on weekends and a decrease in internalizing problems. These results imply that while insufficient sleep might have potentially harmful effects on long-term white matter development and internalizing problems, longer sleep duration on weekends (catch-up sleep) might be a natural counteractive and protective strategy.

Maturational Indices of the Cognitive Control Network Are Associated with Inhibitory Control in Early Childhood

Goal-directed behavior crucially relies on our capacity to suppress impulses and predominant behavioral responses. This ability, called inhibitory control, emerges in early childhood with marked improvements between 3 and 4 years. Here, we ask which brain structures are related to the emergence of this critical ability. Using a multimodal approach, we relate the pronounced behavioral improvements in different facets of 3- and 4-year-olds' (N = 37, 20 female) inhibitory control to structural indices of maturation in the developing brain assessed with MRI. Our results show that cortical and subcortical structure of core regions in the adult cognitive control network, including the PFC, thalamus, and the inferior parietal cortices, is associated with early inhibitory functioning in preschool children. Probabilistic tractography revealed an association of frontoparietal (i.e., the superior longitudinal fascicle) and thalamocortical connections with early inhibitory control. Notably, these associations to brain structure were distinct for different facets of early inhibitory control, often referred to as motivational ("hot") and cognitive ("cold") inhibitory control. Our findings thus reveal the structural brain networks and connectivity related to the emergence of this core faculty of human cognition.SIGNIFICANCE STATEMENT The capacity to suppress impulses and behavioral responses is crucial for goal-directed behavior. This ability, called inhibitory control, develops between the ages of 3 and 4 years. The factors behind this developmental milestone have been debated intensely for decades; however, the brain structure that underlies the emergence of inhibitory control in early childhood is largely unknown. Here, we relate the pronounced behavioral improvements in inhibitory control between 3 and 4 years with structural brain markers of gray matter and white matter maturation. Using a multimodal approach that combines analyses of cortical surface structure, subcortical structures, and white matter connectivity, our results reveal the structural brain networks and connectivity related to this core faculty of human cognition.

Imaging versus electrographic connectivity in human mood-related fronto-temporal networks

BACKGROUND

The efficacy of psychiatric DBS is thought to be driven by the connectivity of stimulation targets with mood-relevant fronto-temporal networks, which is typically evaluated using diffusion-weighted tractography.

OBJECTIVE

Leverage intracranial electrophysiology recordings to better predict the circuit-wide effects of neuromodulation to white matter targets. We hypothesize strong convergence between tractography-predicted structural connectivity and stimulation-induced electrophysiological responses.

METHODS

Evoked potentials were elicited by single-pulse stimulation to two common DBS targets for treatment-resistant depression - the subcallosal cingulate (SCC) and ventral capsule/ventral striatum (VCVS) - in two patients undergoing DBS with stereo-electroencephalographic (sEEG) monitoring. Evoked potentials were compared with predicted structural connectivity between DBS leads and sEEG contacts using probabilistic, patient-specific diffusion-weighted tractography.

RESULTS

Evoked potentials and tractography showed strong convergence in both patients in orbitofrontal, ventromedial prefrontal, and lateral prefrontal cortices for both SCC and VCVS stimulation targets. Low convergence was found in anterior cingulate (ACC), where tractography predicted structural connectivity from SCC targets but produced no evoked potentials during SCC stimulation. Further, tractography predicted no connectivity to ACC from VCVS targets, but VCVS stimulation produced robust evoked potentials.

CONCLUSION

The two connectivity methods showed significant convergence, but important differences emerged with respect to the ability of tractography to predict electrophysiological connectivity between SCC and VCVS to regions of the mood-related network. This multimodal approach raises intriguing implications for the use of tractography in surgical targeting and provides new data to enhance our understanding of the network-wide effects of neuromodulation.

Differences in the gray-to-white matter ratio according to different computed tomography scanners for outcome prediction in post-cardiac arrest patients receiving target temperature management

The gray-to-white matter ratio (GWR) has been used to identify brain damage in comatose patients after cardiac arrest. However, Hounsfield units (HUs), the measurement of brain density on computed tomography (CT) images, may vary depending on the machine type or parameter. Therefore, differences in CT scanners may affect the GWR in post-cardiac arrest patients. We performed a retrospective study on comatose post-cardiac arrest patients who visited the hospital from 2007 to 2017. Two CT, Lightspeed and SOMATOM, scanners were used. Two observers independently measured the HUs of the caudate nucleus, putamen, posterior internal capsule, and corpus callosum using regions of interest. We compared the GWR calculated from the HUs measured at different CT scanners. The analysis of different scanners showed statistically significant differences in the measured HUs and GWR. The HUs and GWR of Lightspeed were measured lower than SOMATOM. The difference between the two CT scanners was also evident in groups divided by neurological prognosis. The area under the curve of the receiver operating characteristic curve to predict poor outcomes of Lightspeed was 0.798, and the cut-off value for 100% specificity was 1.172. The SOMATOM was 0.855, and the cut-off value was 1.269. The difference in scanners affects measurements and performance characteristics of the GWR in post-cardiac arrest patients. Therefore, when applying the results of the GWR study to clinical practice, reference values for each device should be presented, and an integrated plan should be prepared.

Speeding-up while growing-up: Synchronous functional development of motor and non-motor processes across childhood and adolescence

Describing the maturation of information processing in children is fundamental for developmental science. Although non-linear changes in reaction times have been well-documented, direct measurement of the development of the different processing components is lacking. In this study, electromyography was used to quantify the maturation of premotor and motor processes on a sample of 114 children (6–14 years-old) and 15 adults. Using a model-based approach, we show that the development of these two components is well-described by an exponential decrease in duration, with the decay rate being equal for the two components. These findings provide the first unbiased evidence in favour of the common developmental rate of nonmotor and motor processes by directly confronting rates of development of different processing components within the same task. This common developmental rate contrasts with the differential physical maturation of region-specific cerebral gray and white matter. Tentative paths of interpretation are proposed in the discussion.

Functionnectome as a framework to analyse the contribution of brain circuits to fMRI

In recent years, the field of functional neuroimaging has moved away from a pure localisationist approach of isolated functional brain regions to a more integrated view of these regions within functional networks. However, the methods used to investigate functional networks rely on local signals in grey matter and are limited in identifying anatomical circuitries supporting the interaction between brain regions. Mapping the brain circuits mediating the functional signal between brain regions would propel our understanding of the brain's functional signatures and dysfunctions. We developed a method to unravel the relationship between brain circuits and functions: The Functionnectome. The Functionnectome combines the functional signal from fMRI with white matter circuits' anatomy to unlock and chart the first maps of functional white matter. To showcase this method's versatility, we provide the first functional white matter maps revealing the joint contribution of connected areas to motor, working memory, and language functions. The Functionnectome comes with an open-source companion software and opens new avenues into studying functional networks by applying the method to already existing datasets and beyond task fMRI.

The relationship between white matter microstructure, cardiovascular fitness, gross motor skills, and neurocognitive functioning in children

Recent evidence indicates that both cardiovascular fitness and gross motor skill performance are related to enhanced neurocognitive functioning in children by influencing brain structure and functioning. This study investigates the role of white matter microstructure in the relationship of both cardiovascular fitness and gross motor skills with neurocognitive functioning in healthy children. In total 92 children (mean age 9.1 years, range 8.0-10.7) were included in this study. Cardiovascular fitness and gross motor skill performance were assessed using performance-based tests. Neurocognitive functioning was assessed using computerized tests (working memory, inhibition, interference control, information processing, and attention). Diffusion tensor imaging was used in combination with tract-based spatial statistics to assess white matter microstructure as defined by fractional anisotropy (FA), axial and radial diffusivity (AD, RD). The results revealed positive associations of both cardiovascular fitness and gross motor skills with neurocognitive functioning. Information processing and motor response inhibition were associated with FA in a cluster located in the corpus callosum. Within this cluster, higher cardiovascular fitness and better gross motor skills were both associated with greater FA, greater AD, and lower RD. No mediating role was found for FA in the relationship of both cardiovascular fitness and gross motor skills with neurocognitive functioning. The results indicate that cardiovascular fitness and gross motor skills are related to neurocognitive functioning as well as white matter microstructure in children. However, this study provides no evidence for a mediating role of white matter microstructure in these relationships.

Direct Interhemispheric Cortical Communication via Thalamic Commissures: A New White-Matter Pathway in the Rodent Brain

The corpus callosum (CC), the anterior (AC), and the posterior (PC) commissures are the principal axonal fiber bundle pathways that allow bidirectional communication between the brain hemispheres. Here, we used the Allen mouse brain connectivity atlas and high-resolution diffusion-weighted MRI (DWI) to investigate interhemispheric fiber bundles in C57bl6/J mice, the most commonly used wild-type mouse model in biomedical research. We identified 1) commissural projections from the primary motor area through the AC to the contralateral hemisphere; and 2) intrathalamic interhemispheric fiber bundles from multiple regions in the frontal cortex to the contralateral thalamus. This is the first description of direct interhemispheric corticothalamic connectivity from the orbital cortex. We named these newly identified crossing points thalamic commissures. We also analyzed interhemispheric connectivity in the Balb/c mouse model of dysgenesis of the corpus callosum (CCD). Relative to C57bl6/J, Balb/c presented an atypical and smaller AC and weaker interhemispheric corticothalamic communication. These results redefine our understanding of interhemispheric brain communication. Specifically, they establish the thalamus as a regular hub for interhemispheric connectivity and encourage us to reinterpret brain plasticity in CCD as an altered balance between axonal reinforcement and pruning.

Diffusion-informed spatial smoothing of fMRI data in white matter using spectral graph filters

Brain activation mapping using functional magnetic resonance imaging (fMRI) has been extensively studied in brain gray matter (GM), whereas in large disregarded for probing white matter (WM). This unbalanced treatment has been in part due to controversies in relation to the nature of the blood oxygenation level-dependent (BOLD) contrast in WM and its detectability. However, an accumulating body of studies has provided solid evidence of the functional significance of the BOLD signal in WM and has revealed that it exhibits anisotropic spatio-temporal correlations and structure-specific fluctuations concomitant with those of the cortical BOLD signal. In this work, we present an anisotropic spatial filtering scheme for smoothing fMRI data in WM that accounts for known spatial constraints on the BOLD signal in WM. In particular, the spatial correlation structure of the BOLD signal in WM is highly anisotropic and closely linked to local axonal structure in terms of shape and orientation, suggesting that isotropic Gaussian filters conventionally used for smoothing fMRI data are inadequate for denoising the BOLD signal in WM. The fundamental element in the proposed method is a graph-based description of WM that encodes the underlying anisotropy observed across WM, derived from diffusion-weighted MRI data. Based on this representation, and leveraging graph signal processing principles, we design subject-specific spatial filters that adapt to a subject's unique WM structure at each position in the WM that they are applied at. We use the proposed filters to spatially smooth fMRI data in WM, as an alternative to the conventional practice of using isotropic Gaussian filters. We test the proposed filtering approach on two sets of simulated phantoms, showcasing its greater sensitivity and specificity for the detection of slender anisotropic activations, compared to that achieved with isotropic Gaussian filters. We also present WM activation mapping results on the Human Connectome Project's 100-unrelated subject dataset, across seven functional tasks, showing that the proposed method enables the detection of streamline-like activations within axonal bundles.

Estimates of brain age for gray matter and white matter in younger and older adults: Insights into human intelligence

Aging entails a multifaceted complex of changes in macro- and micro-structural properties of human brain gray matter (GM) and white matter (WM) tissues, as well as in intellectual abilities. To better capture tissue-specific brain aging, we combined volume and distribution properties of diffusivity indices to derive subject-specific age scores for each tissue. We compared age-related variance between younger and older adults for GM and WM age scores, and tested whether tissue-specific age scores could explain different effects of aging on fluid (Gf) and crystalized (Gc) intelligence in younger and older adults. Chronological age was strongly associated with GM (R2 = 0.73) and WM (R2 = 0.57) age scores. The GM age score accounted for significantly more variance in chronological age in younger relative to older adults (p < 0.001), whereas the WM age score accounted for significantly more variance in chronological age in older compared to younger adults (p < 0.025). Consistent with existing literature, younger adults outperformed older adults in Gf while older adults outperformed younger adults in Gc. The GM age score was negatively associated with Gf in younger adults (p < 0.02), whereas the WM age score was negatively associated with Gc in older adults (p < 0.02). Our results provide evidence for differences in the effects of age on GM and WM in younger versus older adults that may contribute to age-related differences in Gf and Gc.

Difference in distribution functions: A new diffusion weighted imaging metric for estimating white matter integrity

Diffusion weighted imaging (DWI) is a widely recognized neuroimaging technique to evaluate the microstructure of brain white matter. The objective of this study is to establish an improved automated DWI marker for estimating white matter integrity and investigating ageing related cognitive decline. The concept of Wasserstein distance was introduced to help establish a new measure: difference in distribution functions (DDF), which captures the difference of reshaping one's mean diffusivity (MD) distribution to a reference MD distribution. This new DWI measure was developed using a population-based cohort (n=19,369) from the UK Biobank. Validation was conducted using the data drawn from two independent cohorts: the Sydney Memory and Ageing Study, a community-dwelling sample (n=402), and the Renji Cerebral Small Vessel Disease Cohort Study (RCCS), which consisted of cerebral small vessel disease (CSVD) patients (n=171) and cognitively normal controls (NC) (n=43). DDF was associated with age across all three samples and better explained the variance of changes than other established DWI measures, such as fractional anisotropy, mean diffusivity and peak width of skeletonized mean diffusivity (PSMD). Significant correlations between DDF and cognition were found in the UK Biobank cohort and the MAS cohort. Binary logistic analysis and receiver operator characteristic curve analysis of RCCS demonstrated that DDF had higher sensitivity in distinguishing CSVD patients from NC than the other DWI measures. To demonstrate the flexibility of DDF, we calculated regional DDF which also showed significant correlation with age and cognition. DDF can be used as a marker for monitoring the white matter microstructural changes and ageing related cognitive decline in the elderly.

Distinctive responses in anterior temporal lobe and ventrolateral prefrontal cortex during categorization of semantic information

Semantic categorization is a fundamental ability in language as well as in interaction with the environment. However, it is unclear what cognitive and neural basis generates this flexible and context dependent categorization of semantic information. We performed behavioral and fMRI experiments with a semantic priming paradigm to clarify this. Participants conducted semantic decision tasks in which a prime word preceded target words, using names of animals (mammals, birds, or fish). We focused on the categorization of unique marine mammals, having characteristics of both mammals and fish. Behavioral experiments indicated that marine mammals were semantically closer to fish than terrestrial mammals, inconsistent with the category membership. The fMRI results showed that the left anterior temporal lobe was sensitive to the semantic distance between prime and target words rather than category membership, while the left ventrolateral prefrontal cortex was sensitive to the consistency of category membership of word pairs. We interpreted these results as evidence of existence of dual processes for semantic categorization. The combination of bottom-up processing based on semantic characteristics in the left anterior temporal lobe and top-down processing based on task and/or context specific information in the left ventrolateral prefrontal cortex is required for the flexible categorization of semantic information.

Gross anatomy of the longitudinal fascicle of Sapajus sp

Opposing genetic and cultural-social explanations for the origin of language are currently the focus of much discussion. One of the functions linked to the longitudinal fascicle is language, which links Wernicke’s area and Broca’s area in the brain, and its size should indicate the brain increase in the evolution. Sapajus is a New World primate genus with high cognition and advanced tool use similar to that of chimpanzees. A study of the gross anatomy of the longitudinal fascicle of Sapajus using Kingler’s method found it to differ from other studied primates, such as macaques and chimpanzees, mainly because its fibers join the cingulate fascicle. As in other non-human primates, the longitudinal fascicle of Sapajus does not reach the temporal lobe, which could indicate a way of separating these fascicles to increase white matter in relation to individual function. The study of anatomical structures seems very promising for understanding the basis of the origin of language. Indeed, socio-historical-cultural philosophy affirms the socio-cultural origin of speech, although considering the anatomical structures behind it working as a functional system.

Cross-Sectional Volumes and Trajectories of the Human Brain, Gray Matter, White Matter and Cerebrospinal Fluid in 9473 Typically Aging Adults

Accurate knowledge of adult human brain volume (BV) is critical for studies of aging- and disease-related brain alterations, and for monitoring the trajectories of neural and cognitive functions in conditions like Alzheimer's disease and traumatic brain injury. This scoping meta-analysis aggregates normative reference values for BV and three related volumetrics-gray matter volume (GMV), white matter volume (WMV) and cerebrospinal fluid volume (CSFV)-from typically-aging adults studied cross-sectionally using magnetic resonance imaging (MRI). Drawing from an aggregate sample of 9473 adults, this study provides (A) regression coefficients β describing the age-dependent trajectories of volumetric measures by sex within the range from 20 to 70 years based on both linear and quadratic models, and (B) average values for BV, GMV, WMV and CSFV at the representative ages of 20 (young age), 45 (middle age) and 70 (old age). The results provided synthesize ~20 years of brain volumetrics research and allow one to estimate BV at any age between 20 and 70. Importantly, however, such estimates should be used and interpreted with caution because they depend on MRI hardware specifications (e.g. scanner manufacturer, magnetic field strength), data acquisition parameters (e.g. spatial resolution, weighting), and brain segmentation algorithms. Guidelines are proposed to facilitate future meta- and mega-analyses of brain volumetrics.

Tractography Processing with the Sparse Closest Point Transform

We propose a novel approach for processing diffusion MRI tractography datasets using the sparse closest point transform (SCPT). Tractography enables the 3D geometry of white matter pathways to be reconstructed; however, algorithms for processing them are often highly customized, and thus, do not leverage the existing wealth of machine learning (ML) algorithms. We investigated a vector-space tractography representation that aims to bridge this gap by using the SCPT, which consists of two steps: first, extracting sparse and representative landmarks from a tractography dataset, and second transforming curves relative to these landmarks with a closest point transform. We explore its use in three typical tasks: fiber bundle clustering, simplification, and selection across a population. The clustering algorithm groups fibers from single whole-brain datasets using a non-parametric k-means clustering algorithm, with performance compared with three alternative methods and across four datasets. The simplification algorithm removes redundant curves to improve interactive visualization, with performance gauged relative to random subsampling. The selection algorithm extracts bundles across a population using a one-class Gaussian classifier derived from an atlas prototype, with performance gauged by scan-rescan reliability and sensitivity to normal aging, as compared to manual mask-based selection. Our results demonstrate how the SCPT enables the novel application of existing vector-space ML algorithms to create effective and efficient tools for tractography processing. Our experimental data is available online, and our software implementation is available in the Quantitative Imaging Toolkit.

Brain structural plasticity in visual and sensorimotor areas of airline pilots: A voxel-based morphometric study

BACKGROUND AND PURPOSE

Airline pilot is a highly specialized profession that requires to response quickly and accurately in the presence of a wide variety of visual information. Although functional imaging studies have employed virtual simulation to identify brain areas that underlie various flying-related tasks, little is known about the specific patterns of structural plasticity in the airline pilot's brain.

MATERIALS AND METHODS

In this study, we examined differences of gray matter and white matter volumes between 42 airline pilots and 39 non-pilots by using voxel-based morphometry, and further assessed the association between magnitude of structural alterations and flight time in the pilots.

RESULTS

We found significantly increased white matter volume in the cuneus area in the pilot group compared to the non-pilot group (p <  0.05, FWE corrected). Using a relaxed threshold, it was also observed that the pilots had increased gray matter volume in the lingual gyrus, inferior frontal gyrus, supramarginal gyrus, cuneus, and postcentral gyrus, and increased white matter volume in the postcentral area (p <  0.001, uncorrected). Moreover, the pilots' flight time was positively correlated with gray matter volume in the postcentral gyrus and white matter volume in the cuneus area (p <  0.001, uncorrected).

CONCLUSIONS

The morphological changes in specific visual and sensorimotor areas may provide airline pilots with neural efficiency in the visuo-motor processing related to flight.

Functional and diffusion MRI reveal the neurophysiological basis of neonates' noxious-stimulus evoked brain activity

Understanding the neurophysiology underlying neonatal responses to noxious stimulation is central to improving early life pain management. In this neonatal multimodal MRI study, we use resting-state and diffusion MRI to investigate inter-individual variability in noxious-stimulus evoked brain activity. We observe that cerebral haemodynamic responses to experimental noxious stimulation can be predicted from separately acquired resting-state brain activity (n = 18). Applying this prediction model to independent Developing Human Connectome Project data (n = 215), we identify negative associations between predicted noxious-stimulus evoked responses and white matter mean diffusivity. These associations are subsequently confirmed in the original noxious stimulation paradigm dataset, validating the prediction model. Here, we observe that noxious-stimulus evoked brain activity in healthy neonates is coupled to resting-state activity and white matter microstructure, that neural features can be used to predict responses to noxious stimulation, and that the dHCP dataset could be utilised for future exploratory research of early life pain system neurophysiology.

Hearing loss impacts gray and white matter across the lifespan: Systematic review, meta-analysis and meta-regression

Hearing loss is a heterogeneous disorder thought to affect brain reorganization across the lifespan. Here, structural alterations of the brain due to hearing loss are assessed by using unique effect size metrics based on Cohen's d and Hedges' g. These metrics are used to map coordinates of gray matter (GM) and white matter (WM) alterations from bilateral congenital and acquired hearing loss populations. A systematic review and meta-analysis revealed m = 72 studies with structural alterations measured with magnetic resonance imaging (MRI) (bilateral = 64, unilateral = 8). The bilateral studies categorized hearing loss into congenital and acquired cases (n = 7,445) and control cases (n = 2,924), containing 66,545 datapoint metrics. Hearing loss was found to affect GM and underlying WM in nearly every region of the brain. In congenital hearing loss, GM decreased most in the frontal lobe. Similarly, acquired hearing loss had a decrease in frontal lobe GM, albeit the insula was most decreased. In congenital, WM underlying the frontal lobe GM was most decreased. In congenital, the right hemisphere was more negatively impacted than the left hemisphere; however, in acquired, this was the opposite. The WM alterations most frequently underlined GM alterations in congenital hearing loss, while acquired hearing loss studies did not frequently assess the WM metric. Future studies should use the endophenotype of hearing loss as a prognostic template for discerning clinical outcomes.

Differential spatial computations in ventral and lateral face-selective regions are scaffolded by structural connections

Face-processing occurs across ventral and lateral visual streams, which are involved in static and dynamic face perception, respectively. However, the nature of spatial computations across streams is unknown. Using functional MRI and population receptive field (pRF) mapping, we measured pRFs in face-selective regions. Results reveal that spatial computations by pRFs in ventral face-selective regions are concentrated around the center of gaze (fovea), but spatial computations in lateral face-selective regions extend peripherally. Diffusion MRI reveals that these differences are mirrored by a preponderance of white matter connections between ventral face-selective regions and foveal early visual cortex (EVC), while connections with lateral regions are distributed more uniformly across EVC eccentricities. These findings suggest a rethinking of spatial computations in face-selective regions, showing that they vary across ventral and lateral streams, and further propose that spatial computations in high-level regions are scaffolded by the fine-grain pattern of white matter connections from EVC.

Axono-cortical evoked potentials as a new method of IONM for preserving the motor control network: a first study in three cases

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.

Predicting visual working memory with multimodal magnetic resonance imaging

The indispensability of visual working memory (VWM) in human daily life suggests its importance in higher cognitive functions and neurological diseases. However, despite the extensive research efforts, most findings on the neural basis of VWM are limited to a unimodal context (either structure or function) and have low generalization. To address the above issues, this study proposed the usage of multimodal neuroimaging in combination with machine learning to reveal the neural mechanism of VWM across a large cohort (N = 547). Specifically, multimodal magnetic resonance imaging features extracted from voxel-wise amplitude of low-frequency fluctuations, gray matter volume, and fractional anisotropy were used to build an individual VWM capacity prediction model through a machine learning pipeline, including the steps of feature selection, relevance vector regression, cross-validation, and model fusion. The resulting model exhibited promising predictive performance on VWM (r = .402, p < .001), and identified features within the subcortical-cerebellum network, default mode network, motor network, corpus callosum, anterior corona radiata, and external capsule as significant predictors. The main results were then compared with those obtained on emotional regulation and fluid intelligence using the same pipeline, confirming the specificity of our findings. Moreover, the main results maintained well under different cross-validation regimes and preprocess strategies. These findings, while providing richer evidence for the importance of multimodality in understanding cognitive functions, offer a solid and general foundation for comprehensively understanding the VWM process from the top down.

Effects of weather and season on human brain volume

We present an exploratory cross-sectional analysis of the effect of season and weather on Freesurfer-derived brain volumes from a sample of 3,279 healthy individuals collected on two MRI scanners in Hartford, CT, USA over a 15 year period. Weather and seasonal effects were analyzed using a single linear regression model with age, sex, motion, scan sequence, time-of-day, month of the year, and the deviation from average barometric pressure, air temperature, and humidity, as covariates. FDR correction for multiple comparisons was applied to groups of non-overlapping ROIs. Significant negative relationships were found between the left- and right- cerebellum cortex and pressure (t = -2.25, p = 0.049; t = -2.771, p = 0.017). Significant positive relationships were found between left- and right- cerebellum cortex and white matter between the comparisons of January/June and January/September. Significant negative relationships were found between several subcortical ROIs for the summer months compared to January. An opposing effect was observed between the supra- and infra-tentorium, with opposite effect directions in winter and summer. Cohen’s d effect sizes from monthly comparisons were similar to those reported in recent psychiatric big-data publications, raising the possibility that seasonal changes and weather may be confounds in large cohort studies. Additionally, changes in brain volume due to natural environmental variation have not been reported before and may have implications for weather-related and seasonal ailments.

A longitudinal, randomized experimental pilot study to investigate the effects of airborne ultrasound on human mental health, cognition, and brain structure

Ultrasound-(US) emitting sources are highly present in modern human environments (e.g., movement sensors, electric transformers). US affecting humans or even posing a health hazard remains understudied. Hence, ultrasonic (22.4 kHz) vs. sham devices were installed in participants' bedrooms, and active for 28 nights. Somatic and psychiatric symptoms, sound-sensitivity, sleep quality, executive function, and structural MRI were assessed pre-post. Somatization (possible nocebo) and phasic alertness increased significantly in sham, accuracy in a flexibility task decreased significantly in the verum condition (indicating hastier responses). Effects were not sustained after p-level adjustment. Exploratory voxel-based morphometry (VBM) revealed regional grey matter (rGMV) but no regional white matter volume changes in verum (relative to placebo). rGMV increased in bilateral cerebellum VIIb/Crus II and anterior cingulate (BA24). There were rGMV decreases in two bilateral frontal clusters: in the middle frontal gyri/opercular part of inferior frontal gyrus (BA46, 44), and the superior frontal gyri (BA4 ,6, 8). No brain-behavior-links were identified. Given the overall pattern of results, it is suggested that ultrasound may particularly induce regional gray matter decline in frontal areas, however with yet unclear behavioral consequences. Given the localization of clusters, candidate behavioral variables for follow-up investigation are complex motor control/coordination, stress regulation, speech processing, and inhibition tasks.Trial registration: The trial was registered at NIH www.clinicaltrials.gov , trial identifier: NCT03459183, trial name: SonicBrain01, full trial protocol available here: https://clinicaltrials.gov/ct2/show/NCT03459183 .

White matter fascicles and cortical microstructure predict reading-related responses in human ventral temporal cortex

Reading-related responses in the lateral ventral temporal cortex (VTC) show a consistent spatial layout across individuals, which is puzzling, since reading skills are acquired during childhood. Here, we tested the hypothesis that white matter fascicles and gray matter microstructure predict the location of reading-related responses in lateral VTC. We obtained functional (fMRI), diffusion (dMRI), and quantitative (qMRI) magnetic resonance imaging data in 30 adults. fMRI was used to map reading-related responses by contrasting responses in a reading task with those in adding and color tasks; dMRI was used to identify the brain's fascicles and to map their endpoint densities in lateral VTC; qMRI was used to measure proton relaxation time (T1), which depends on cortical tissue microstructure. We fit linear models that predict reading-related responses in lateral VTC from endpoint density and T1 and used leave-one-subject-out cross-validation to assess prediction accuracy. Using a subset of our participants (N=10, feature selection set), we find that i) endpoint densities of the arcuate fasciculus (AF), inferior longitudinal fasciculus (ILF), and vertical occipital fasciculus (VOF) are significant predictors of reading-related responses, and ii) cortical T1 of lateral VTC further improves the predictions of the fascicle model. In the remaining participants (N=20, validation set), we show that a linear model that includes T1, AF, ILF and VOF significantly predicts i) the map of reading-related responses across lateral VTC and ii) the location of the visual word form area, a region critical for reading. Overall, our data-driven approach reveals that the AF, ILF, VOF and cortical microstructure have a consistent spatial relationship with an individual's reading-related responses in lateral VTC.

Ephaptic coupling in white matter fibre bundles modulates axonal transmission delays

Axonal connections are widely regarded as faithful transmitters of neuronal signals with fixed delays. The reasoning behind this is that extracellular potentials caused by spikes travelling along axons are too small to have an effect on other axons. Here we devise a computational framework that allows us to study the effect of extracellular potentials generated by spike volleys in axonal fibre bundles on axonal transmission delays. We demonstrate that, although the extracellular potentials generated by single spikes are of the order of microvolts, the collective extracellular potential generated by spike volleys can reach several millivolts. As a consequence, the resulting depolarisation of the axonal membranes increases the velocity of spikes, and therefore reduces axonal delays between brain areas. Driving a neural mass model with such spike volleys, we further demonstrate that only ephaptic coupling can explain the reduction of stimulus latencies with increased stimulus intensities, as observed in many psychological experiments.

Axonal fibre bundles that connect distant cortical areas contain millions of densely packed axons. When synchronous spike volleys travel through such fibre bundles, the extracellular potential within the bundles is perturbed. We use computer simulations to examine the magnitude and shape of this perturbation, and demonstrate that it is sufficiently strong to affect axonal transmission speeds. Since most spikes within a spike volley are positioned in an area where the extracellular potential is negative (relative to a distant reference), the resulting depolarisation of the axonal membranes accelerates the spike volley on average. This finding is in contrast to previous studies of ephaptic coupling effects between axons, where ephaptic coupling was found to slow down spike propagation. Our finding has consequences for information transmission and synchronisation between cortical areas.

Brain biomarkers and neuropsychological outcomes of pediatric posterior fossa brain tumor survivors treated with surgical resection with or without adjuvant chemotherapy

PURPOSE

Children with brain tumors experience cognitive late effects, often related to cranial radiation. We sought to determine differential effects of surgery and chemotherapy on brain structure and neuropsychological outcomes in children who did not receive cranial radiation therapy (CRT).

METHODS

Twenty-eight children with a history of posterior fossa tumor (17 treated with surgery, 11 treated with surgery and chemotherapy) underwent neuroimaging and neuropsychological assessment a mean of 4.5 years (surgery group) to 9 years (surgery + chemotherapy group) posttreatment, along with 18 healthy sibling controls. Psychometric measures assessed IQ, language, executive functions, processing speed, memory, and social-emotional functioning. Group differences and correlations between diffusion tensor imaging findings and psychometric scores were examined.

RESULTS

The z-score mapping demonstrated fractional anisotropy (FA) values were ≥2 standard deviations lower in white matter tracts, prefrontal cortex gray matter, hippocampus, thalamus, basal ganglia, and pons between patient groups, indicating microstructural damage associated with chemotherapy. Patients scored lower than controls on visuoconstructional reasoning and memory (P ≤ .02). Lower FA in the uncinate fasciculus (R = -0.82 to -0.91) and higher FA in the thalamus (R = 0.73-0.91) associated with higher IQ scores, and higher FA in the thalamus associated with higher scores on spatial working memory (R = 0.82).

CONCLUSIONS

Posterior fossa brain tumor treatment with surgery and chemotherapy affects brain microstructure and neuropsychological functioning years into survivorship, with spatial processes the most vulnerable. Biomarkers indicating cellular changes in the thalamus, hippocampus, pons, prefrontal cortex, and white matter tracts associate with lower psychometric scores.

Computing and visualising intra-voxel orientation-specific relaxation-diffusion features in the human brain

Diffusion MRI techniques are used widely to study the characteristics of the human brain connectome in vivo. However, to resolve and characterise white matter (WM) fibres in heterogeneous MRI voxels remains a challenging problem typically approached with signal models that rely on prior information and constraints. We have recently introduced a 5D relaxation-diffusion correlation framework wherein multidimensional diffusion encoding strategies are used to acquire data at multiple echo-times to increase the amount of information encoded into the signal and ease the constraints needed for signal inversion. Nonparametric Monte Carlo inversion of the resulting datasets yields 5D relaxation-diffusion distributions where contributions from different sub-voxel tissue environments are separated with minimal assumptions on their microscopic properties. Here, we build on the 5D correlation approach to derive fibre-specific metrics that can be mapped throughout the imaged brain volume. Distribution components ascribed to fibrous tissues are resolved, and subsequently mapped to a dense mesh of overlapping orientation bins to define a smooth orientation distribution function (ODF). Moreover, relaxation and diffusion measures are correlated to each independent ODF coordinate, thereby allowing the estimation of orientation-specific relaxation rates and diffusivities. The proposed method is tested on a healthy volunteer, where the estimated ODFs were observed to capture major WM tracts, resolve fibre crossings, and, more importantly, inform on the relaxation and diffusion features along with distinct fibre bundles. If combined with fibre-tracking algorithms, the methodology presented in this work has potential for increasing the depth of characterisation of microstructural properties along individual WM pathways.

Arcuate fasciculus architecture is associated with individual differences in pre-attentive detection of unpredicted music changes

The mismatch negativity (MMN) is an event related brain potential (ERP) elicited by unpredicted sounds presented in a sequence of repeated auditory stimuli. The neural sources of the MMN have been previously attributed to a fronto-temporo-parietal network which crucially overlaps with the so-called auditory dorsal stream, involving inferior and middle frontal, inferior parietal, and superior and middle temporal regions. These cortical areas are structurally connected by the arcuate fasciculus (AF), a three-branch pathway supporting the feedback-feedforward loop involved in auditory-motor integration, auditory working memory, storage of acoustic templates, as well as comparison and update of those templates. Here, we characterized the individual differences in the white-matter macrostructural properties of the AF and explored their link to the electrophysiological marker of passive change detection gathered in a melodic multifeature MMN-EEG paradigm in 26 healthy young adults without musical training. Our results show that left fronto-temporal white-matter connectivity plays an important role in the pre-attentive detection of rhythm modulations within a melody. Previous studies have shown that this AF segment is also critical for language processing and learning. This strong coupling between structure and function in auditory change detection might be related to life-time linguistic (and possibly musical) exposure and experiences, as well as to timing processing specialization of the left auditory cortex. To the best of our knowledge, this is the first time in which the relationship between neurophysiological (EEG) and brain white-matter connectivity indexes using DTI-tractography are studied together. Thus, the present results, although still exploratory, add to the existing evidence on the importance of studying the constraints imposed on cognitive functions by the underlying structural connectivity.

Imprinting methylation predicts hippocampal volumes and hyperintensities and the change with age in later life

Epigenetic imprinting is important for neurogenesis and brain function. Hippocampal volumes and brain hyperintensities in late life have been associated with early life circumstances. Epigenetic imprinting may underpin these associations. Methylation was measured at 982 sites in 13 imprinted locations in blood samples from a longitudinal cohort by bisulphite amplicon sequencing. Hippocampal volumes and hyperintensities were determined at age 64y and 72y using MRI. Hyperintensities were determined in white matter, grey matter and infratentorial regions. Permutation methods were used to adjust for multiple testing. At 64y, H19/IGF2 and NESPAS methylation predicted hippocampal volumes. PEG3 predicted hyperintensities in hippocampal grey matter, and white matter. GNASXL predicted grey matter hyperintensities. Changes with age were predicted for hippocampal volume (MEST1, KvDMR, L3MBTL, GNASXL), white matter (MEST1, PEG3) and hippocampal grey matter hyperintensities (MCTS2, GNASXL, NESPAS, L3MBTL, MCTS2, SNRPN, MEST1). Including childhood cognitive ability, years in education, or socioeconomic status as additional explanatory variables in regression analyses did not change the overall findings. Imprinting methylation in multiple genes predicts brain structures, and their change over time. These findings are potentially relevant to the development of novel tests of brain structure and function across the life-course, strategies to improve cognitive outcomes, and our understanding of early influences on brain development and function.

Diffusion MRI revealed altered inter-hippocampal projections in the mouse brain after intrauterine inflammation

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 (R² = 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.

Robustness of connectome harmonics to local gray matter and long-range white matter connectivity changes

Recently, it has been proposed that the harmonic patterns emerging from the brain's structural connectivity underlie the resting state networks of the human brain. These harmonic patterns, termed connectome harmonics, are estimated as the Laplace eigenfunctions of the combined gray and white matters connectivity matrices and yield a connectome-specific extension of the well-known Fourier basis. However, it remains unclear how topological properties of the combined connectomes constrain the precise shape of the connectome harmonics and their relationships to the resting state networks. Here, we systematically study how alterations of the local and long-range connectivity matrices affect the spatial patterns of connectome harmonics. Specifically, the proportion of local gray matter homogeneous connectivity versus long-range white-matter heterogeneous connectivity is varied by means of weight-based matrix thresholding, distance-based matrix trimming, and several types of matrix randomizations. We demonstrate that the proportion of local gray matter connections plays a crucial role for the emergence of wide-spread, functionally meaningful, and originally published connectome harmonic patterns. This finding is robust for several different cortical surface templates, mesh resolutions, or widths of the local diffusion kernel. Finally, using the connectome harmonic framework, we also provide a proof-of-concept for how targeted structural changes such as the atrophy of inter-hemispheric callosal fibers and gray matter alterations may predict functional deficits associated with neurodegenerative conditions.

Structural and functional connectivity mapping of the human corpus callosum organization with white-matter functional networks

The corpus callosum serves as a crucial organization for understanding the information integration between the two hemispheres. Our previous study explored the functional connectivity between the corpus callosum and white-matter functional networks (WM-FNs), but the corresponding physical connectivity remains unknown. The current study uses the resting-state fMRI of Human Connectome Project data to identify ten WM-FNs in 108 healthy subjects, and then independently maps the structural and functional connectivity between the corpus callosum and above WM-FNs using the diffusion tensor images (DTI) tractography and resting-state functional connectivity (RSFC). Our results demonstrated that the structural and functional connectivity between the human corpus callosum and WM-FNs have the following high overall correspondence: orbitofrontal WM-FN, DTI map = 89% and RSFC map = 92%; sensorimotor middle WM-FN, DTI map = 47% and RSFC map = 77%; deep WM-FN, DTI map = 50% and RSFC map = 79%; posterior corona radiata WM-FN, DTI map = 82% and RSFC map = 73%. These findings reinforce the notion that the corpus callosum has unique spatial distribution patterns connecting to distinct WM-FNs. However, important differences between the structural and functional connectivity mapping results were also observed, which demonstrated a synergy between DTI tractography and RSFC toward better understanding the information integration of primary and higher-order functional systems in the human brain.

Distribution, number, and certain neurochemical identities of infracortical white matter neurons in the brains of three megachiropteran bat species

A large population of infracortical white matter neurons, or white matter interstitial cells (WMICs), are found within the subcortical white matter of the mammalian telencephalon. We examined WMICs in three species of megachiropterans, Megaloglossus woermanni, Casinycteris argynnis, and Rousettus aegyptiacus, using immunohistochemical and stereological techniques. Immunostaining for neuronal nuclear marker (NeuN) revealed substantial numbers of WMICs in each species-M. woermanni 124,496 WMICs, C. argynnis 138,458 WMICs, and the larger brained R. aegyptiacus having an estimated WMIC population of 360,503. To examine the range of inhibitory neurochemical types we used antibodies against parvalbumin, calbindin, calretinin, and neural nitric oxide synthase (nNOS). The calbindin and nNOS immunostained neurons were the most commonly observed, while those immunoreactive for calretinin and parvalbumin were sparse. The proportion of WMICs exhibiting inhibitory neurochemical profiles was ~26%, similar to that observed in previously studied primates. While for the most part the WMIC population in the megachiropterans studied was similar to that observed in other mammals, the one feature that differed was the high proportion of WMICs immunoreactive to calbindin, whereas in primates (macaque monkey, lar gibbon and human) the highest proportion of inhibitory WMICs contain calretinin. Interestingly, there appears to be an allometric scaling of WMIC numbers with brain mass. Further quantitative comparative work across more mammalian species will reveal the developmental and evolutionary trends associated with this infrequently studied neuronal population.

Nonlinear associations of neurite density and myelin content with age revealed using multicomponent diffusion and relaxometry magnetic resonance imaging

Most magnetic resonance imaging (MRI) studies investigating the relationship between regional brain myelination or axonal density and aging have relied upon nonspecific methods to probe myelin and axonal content, including diffusion tensor imaging and relaxation time mapping. While these studies have provided pivotal insights into changes in cerebral architecture with aging and pathology, details of the underlying microstructural alterations have not been fully elucidated. In the current study, we used the BMC-mcDESPOT analysis, a direct and specific multicomponent relaxometry method for imaging of myelin water fraction (MWF), a marker of myelin content, and NODDI, an emerging multicomponent diffusion technique, for neurite density index (NDI) imaging, a proxy of axonal density. We investigated age-related differences in MWF and NDI in several white matter brain regions in a cohort of cognitively unimpaired participants over a wide age range. Our results indicate a quadratic, inverted U-shape, relationship between MWF and age in all brain regions investigated, suggesting that myelination continues until middle age followed by a decrease at older ages, in agreement with previous work. We found a similarly complex regional association between NDI and age, with several cerebral structures also exhibiting a quadratic, inverted U-shape, relationship. This novel observation suggests an increase in axonal density until the fourth decade of age followed by a rapid loss at older ages. We also observed that these age-related differences in MWF and NDI vary across different brain regions, as expected. Finally, our study indicates no significant association between MWF and NDI in most cerebral structures investigated, although this association approached significance in a limited number of brain regions, indicating the complementary nature of their information and encouraging further investigation. Overall, we find evidence of nonlinear associations between age and myelin or axonal density in a sample of well-characterized adults, using direct myelin and axonal content imaging methods.

Multimodal brain-age prediction and cardiovascular risk: The Whitehall II MRI sub-study

Brain age is becoming a widely applied imaging-based biomarker of neural aging and potential proxy for brain integrity and health. We estimated multimodal and modality-specific brain age in the Whitehall II (WHII) MRI cohort using machine learning and imaging-derived measures of gray matter (GM) morphology, white matter microstructure (WM), and resting state functional connectivity (FC). The results showed that the prediction accuracy improved when multiple imaging modalities were included in the model (R2 = 0.30, 95% CI [0.24, 0.36]). The modality-specific GM and WM models showed similar performance (R2 = 0.22 [0.16, 0.27] and R2 = 0.24 [0.18, 0.30], respectively), while the FC model showed the lowest prediction accuracy (R2 = 0.002 [-0.005, 0.008]), indicating that the FC features were less related to chronological age compared to structural measures. Follow-up analyses showed that FC predictions were similarly low in a matched sub-sample from UK Biobank, and although FC predictions were consistently lower than GM predictions, the accuracy improved with increasing sample size and age range. Cardiovascular risk factors, including high blood pressure, alcohol intake, and stroke risk score, were each associated with brain aging in the WHII cohort. Blood pressure showed a stronger association with white matter compared to gray matter, while no differences in the associations of alcohol intake and stroke risk with these modalities were observed. In conclusion, machine-learning based brain age prediction can reduce the dimensionality of neuroimaging data to provide meaningful biomarkers of individual brain aging. However, model performance depends on study-specific characteristics including sample size and age range, which may cause discrepancies in findings across studies.

Auditory and Visual System White Matter Is Differentially Impacted by Normative Aging in Macaques

Deficits in auditory and visual processing are commonly encountered by older individuals. In addition to the relatively well described age-associated pathologies that reduce sensory processing at the level of the cochlea and eye, multiple changes occur along the ascending auditory and visual pathways that further reduce sensory function in each domain. One fundamental question that remains to be directly addressed is whether the structure and function of the central auditory and visual systems follow similar trajectories across the lifespan or sustain the impacts of brain aging independently. The present study used diffusion magnetic resonance imaging and electrophysiological assessments of auditory and visual system function in adult and aged macaques to better understand how age-related changes in white matter connectivity at multiple levels of each sensory system might impact auditory and visual function. In particular, the fractional anisotropy (FA) of auditory and visual system thalamocortical and interhemispheric corticocortical connections was estimated using probabilistic tractography analyses. Sensory processing and sensory system FA were both reduced in older animals compared with younger adults. Corticocortical FA was significantly reduced only in white matter of the auditory system of aged monkeys, while thalamocortical FA was lower only in visual system white matter of the same animals. Importantly, these structural alterations were significantly associated with sensory function within each domain. Together, these results indicate that age-associated deficits in auditory and visual processing emerge in part from microstructural alterations to specific sensory white matter tracts, and not from general differences in white matter condition across the aging brain.SIGNIFICANCE STATEMENT Age-associated deficits in sensory processing arise from structural and functional alterations to both peripheral sensory organs and central brain regions. It remains unclear whether different sensory systems undergo similar or distinct trajectories in function across the lifespan. To provide novel insights into this question, this study combines electrophysiological assessments of auditory and visual function with diffusion MRI in aged macaques. The results suggest that age-related sensory processing deficits in part result from factors that impact the condition of specific white matter tracts, and not from general decreases in connectivity between sensory brain regions. Such anatomic specificity argues for a framework aimed at understanding vulnerabilities with relatively local influence and brain region specificity.

Relationship between white matter microstructure and work hours

Human social activities are realized by a synergy of neuronal activity over various regions of the brain, which is supported by their connectivity. In the present study, we examined associations between social activities, represented by work hours, and brain connectivity as quantified using diffusion tensor imaging (DTI). In 483 healthy participants, DTI analysis was performed using 3 T magnetic resonance imaging, and work hours were calculated, considering hours of paid employment (the "Work for Pay" category), hours of housework (the "Work at Home" category), and hours of school-related study (the "Student" category). The correlations between each class of work time and DTI indices were analyzed. The mean diffusivity (MD) values of the anterior limb of the internal capsule (ALIC) and the superior fronto-occipital fasciculus (SFO) were negatively correlated with total work hours (ALIC: r = -0.192, p =  2.3 × 10^-5; SFO: r = -0.161, p =  3.8 × 10^-4). We also found that the MD values of the ALIC and the SFO were correlated with work hours in the Work for Pay category (ALIC: r = -0.211, p =  3.2 × 10^-6; SFO: r = -0.163, p =  3.4 × 10^-4) but not with those in the Work at Home category or the Student category. These results suggest that social activity is associated with the white matter microstructure of the ALIC and the SFO. The main difference between "Work for Pay" and the other two social activities appears to be the type of motivation-for example, external versus internal. Therefore, the white matter microstructure of the ALIC and SFO may be related to externally motivated social activities.

Bundle analytics, a computational framework for investigating the shapes and profiles of brain pathways across populations

Tractography has created new horizons for researchers to study brain connectivity in vivo. However, tractography is an advanced and challenging method that has not been used so far for medical data analysis at a large scale in comparison to other traditional brain imaging methods. This work allows tractography to be used for large scale and high-quality medical analytics. BUndle ANalytics (BUAN) is a fast, robust, and flexible computational framework for real-world tractometric studies. BUAN combines tractography and anatomical information to analyze the challenging datasets and identifies significant group differences in specific locations of the white matter bundles. Additionally, BUAN takes the shape of the bundles into consideration for the analysis. BUAN compares the shapes of the bundles using a metric called bundle adjacency which calculates shape similarity between two given bundles. BUAN builds networks of bundle shape similarities that can be paramount for automating quality control. BUAN is freely available in DIPY. Results are presented using publicly available Parkinson's Progression Markers Initiative data.

Corticocortical and Thalamocortical Changes in Functional Connectivity and White Matter Structural Integrity after Reward-Guided Learning of Visuospatial Discriminations in Rhesus Monkeys

The frontal cortex and temporal lobes together regulate complex learning and memory capabilities. Here, we collected resting-state functional and diffusion-weighted MRI data before and after male rhesus macaque monkeys received extensive training to learn novel visuospatial discriminations (reward-guided learning). We found functional connectivity changes in orbitofrontal, ventromedial prefrontal, inferotemporal, entorhinal, retrosplenial, and anterior cingulate cortices, the subicular complex, and the dorsal, medial thalamus. These corticocortical and thalamocortical changes in functional connectivity were accompanied by related white matter structural alterations in the uncinate fasciculus, fornix, and ventral prefrontal tract: tracts that connect (sub)cortical networks and are implicated in learning and memory processes in monkeys and humans. After the well-trained monkeys received fornix transection, they were impaired in learning new visuospatial discriminations. In addition, the functional connectivity profile that was observed after the training was altered. These changes were accompanied by white matter changes in the ventral prefrontal tract, although the integrity of the uncinate fasciculus remained unchanged. Our experiments highlight the importance of different communication relayed among corticocortical and thalamocortical circuitry for the ability to learn new visuospatial associations (learning-to-learn) and to make reward-guided decisions.SIGNIFICANCE STATEMENT Frontal neural networks and the temporal lobes contribute to reward-guided learning in mammals. Here, we provide novel insight by showing that specific corticocortical and thalamocortical functional connectivity is altered after rhesus monkeys received extensive training to learn novel visuospatial discriminations. Contiguous white matter fiber pathways linking these gray matter structures, namely, the uncinate fasciculus, fornix, and ventral prefrontal tract, showed structural changes after completing training in the visuospatial task. Additionally, different patterns of functional and structural connectivity are reported after removal of subcortical connections within the extended hippocampal system, via fornix transection. These results highlight the importance of both corticocortical and thalamocortical interactions in reward-guided learning in the normal brain and identify brain structures important for memory capabilities after injury.

White matter-Maximien Parchappe and the integration of articulate language

The Imperial Academy of Medicine of Paris met in the spring of 1865 to discuss the localization of speech. One of the participants was Maximien Parchappe (1800-1866), an alienist whose research interests lay in the cerebral cortex. This article addresses Maximien Parchappe's concept that the cognitive elements of language-such as the translation of thoughts into words, the will to express them, and the means to do so-reside within the cortical gray matter, and that they are integrated through white-matter fibers. In so doing, Parchappe anticipated Carl Wernicke's linking of the posterior aspects of the dominant frontal and temporal lobes in verbal expression, and Jules Dejerine's linking of the angular gyrus and Wernicke's area in the understanding of written language. Functional imaging has revived interest in language as a network of neuronal aggregates and has given new relevance to Parchappe's concept of the functional organization of language.