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Abstract Task functional magnetic resonance imaging research has generally shielded away from studying individuals due to the low reproducibility. Here, we propose that heterogeneous brain activations across individuals localize to a common network. To test this hypothesis, we use working memory (WM) as our example. First, we showed that discrete-brain-based reproducibility of brain activation during WM across individuals was low. Then, we used activation network mapping (ANM) technique to identify each individual’s brain network of WM and found that network-based reproducibility was rather high. Prediction analyses using machine learning algorithms indicated that individual WM networks identified via ANM can predict WM behavioral performance. This predictive ability even outperformed that of brain activations. Our study provides a new explanation on the low reproducibility of brain activations across individuals. The results suggest that ANM can be used to identify individual brain networks of cognitive processes, thus promising broad potential applications.

BackgroundAsymptomatic chronic cerebrovascular steno-occlusive disease is common, but the cognitive function and alterations in the brain’s structural and functional profiles have not been well studied. This study aimed to reveal whether and how patients with asymptomatic middle cerebral artery (MCA) steno-occlusive disease and normal-appearing white matter differ in brain structural and functional profiles from normal controls and their correlations with cognitive function.MethodsIn all, 26 patients with asymptomatic MCA steno-occlusive disease and 22 healthy controls were compared for neurobehavioral assessments, brain volume, cortical thickness, fiber connectivity density (FiCD) value, and resting-state functional connectivity (FC) using multimodal MRI. We also investigated the associations between abnormal cortical thicknesses, FiCD values, and functional connectivities with the neurobehavioral assessments.ResultsPatients performed worse on memory tasks (Auditory Verbal Learning Test-Huashan version) compared with healthy controls. Patients were divided into two groups: the right group (patients with right MCA steno-occlusive disease) and the left group (patients with left MCA steno-occlusive disease). The left group showed significant cortical thinning in the left superior parietal lobule, while the right group showed significant cortical thinning in the right superior parietal lobule and caudal portion of the right middle frontal gyrus. Increased FiCD values in the superior frontal region of the left hemisphere were observed in the left group. In addition, a set of interhemispheric and intrahemispheric FC showed a significant decrease or increase in both the left and right groups. Many functional connectivity profiles were positively correlated with cognitive scores. No correlation was found between cortical thickness, FiCD values, and cognitive scores.ConclusionEven if the patients with MCA steno-occlusive disease were asymptomatic and had normal-appearing white matter, their cognitive function and structural and functional profiles had changed, especially the FC. Alterations in FC may be an important mechanism underlying the neurodegenerative process in patients with asymptomatic MCA steno-occlusive disease before structural changes occur, so FC assessment may promote the detection of network alterations, which may be used as a biomarker of disease progression and therapeutic efficacy evaluation in these patients.

IntroductionPediatric growth hormone deficiency (GHD) is a disease resulting from impaired growth hormone/insulin-like growth factor-1 (IGF-1) axis but the effects of GHD on children’s cognitive function, brain structure and brain function were not yet fully illustrated.MethodsFull Wechsler Intelligence Scales for Children, structural imaging, diffusion tensor imaging, and resting-state functional magnetic resonance imaging were assessed in 11 children with GHD and 10 matched healthy controls.Results(1) The GHD group showed moderate cognitive impairment, and a positive correlation existed between IGF-1 levels and cognitive indices. (2) Mean diffusivity was significantly increased in both corticospinal tracts in GHD group. (3) There were significant positive correlations between IGF-1 levels and volume metrics of left thalamus, left pallidum and right putamen but a negative correlation between IGF-1 levels and cortical thickness of the occipital lobe. And IGF-1 levels negatively correlated with fractional anisotropy in the superior longitudinal fasciculus and right corticospinal tract. (4) Regional homogeneity (ReHo) in the left hippocampus/parahippocampal gyrus was negatively correlated with IGF-1 levels; the amplitude of low-frequency fluctuation (ALFF) and ReHo in the paracentral lobe, postcentral gyrus and precentral gyrus were also negatively correlated with IGF-1 levels, in which region ALFF fully mediates the effect of IGF-1 on working memory index.ConclusionMultiple subcortical, cortical structures, and regional neural activities might be influenced by serum IGF-1 levels. Thereinto, ALFF in the paracentral lobe, postcentral gyrus and precentral gyrus fully mediates the effect of IGF-1 on the working memory index.

White matter hyperintensity (WMH) is common in healthy adults in their 60s and can be seen as early as in their 30s and 40s. Alterations in the brain structural and functional profiles in adults with WMH have been repeatedly studied but with a focus on late-stage WMH. To date, structural and functional MRI profiles during the very early stage of WMH remain largely unexplored. To address this, we investigated multimodal MRI (structural, diffusion, and resting-state functional MRI) profiles of community-dwelling asymptomatic adults with very early-stage WMH relative to age-, sex-, and education-matched non-WMH controls. The comparative results showed significant age-related and age-independent changes in structural MRI-based morphometric measures and resting-state fMRI-based measures in a set of specific gray matter (GM) regions but no global white matter changes. The observed structural and functional anomalies in specific GM regions in community-dwelling asymptomatic adults with very early-stage WMH provide novel data regarding very early-stage WMH and enhance understanding of the pathogenesis of WMH.

The inferior parietal lobule (IPL) is one of the most expanded cortical regions in humans relative to other primates. It is also among the most structurally and functionally asymmetric regions in the human cerebral cortex. Whether the structural and connectional asymmetries of IPL subdivisions differ across primate species and how this relates to functional asymmetries remain unclear. We identified IPL subregions that exhibited positive allometric in both hemispheres, scaling across rhesus macaque monkeys, chimpanzees, and humans. The patterns of IPL subregions asymmetry were similar in chimpanzees and humans, but no IPL asymmetries were evident in macaques. Among the comparative sample of primates, humans showed the most widespread asymmetric connections in the frontal, parietal, and temporal cortices, constituting leftward asymmetric networks that may provide an anatomical basis for language and tool use. Unique human asymmetric connectivity between the IPL and primary motor cortex might be related to handedness. These findings suggest that structural and connectional asymmetries may underlie hemispheric specialization of the human brain.

The left and right hemispheres of the human brain are two connected but relatively independent functional modules; they show multidimensional asymmetries ranging from particular local brain unit properties to entire hemispheric connectome topology. To date, however, it remains largely unknown whether and how hemispheric functional hierarchical structures differ between hemispheres. In the present study, we adopted a newly developed resting-state (rs) functional connectivity (FC)-based gradient approach to evaluate hemispheric functional hierarchical structures and their asymmetries in right-handed healthy young adults. Our results showed an overall mirrored principal functional gradient between hemispheres, with the sensory cortex and the default-mode network (DMN) anchored at the two opposite ends of the gradient. Interestingly, the left hemisphere showed a significantly larger full range of the principal gradient in both males and females, with males exhibiting greater leftward asymmetry. Similarly, the principal gradient component scores of two regions around the middle temporal gyrus and posterior orbitofrontal cortex exhibited similar hemisphere × sex interaction effects: a greater degree of leftward asymmetry in males than in females. Moreover, we observed significant main hemisphere and sex effects in distributed regions across the entire hemisphere. All these results are reproducible and robust between test-retest rs-fMRI sessions. Our findings provide evidence of functional gradients that enhance the present understanding of human brain asymmetries in functional organization and highlight the impact of sex on hemispheric functional gradients and their asymmetries.

Neuroimaging studies of hippocampal volumes in patients with amyotrophic lateral sclerosis (ALS) have reported inconsistent results. Our aims were to demonstrate that such discrepancies are largely due to atrophy of different regions of the hippocampus that emerge in different disease stages of ALS and to explore the existence of co-pathology in ALS patients. We used the well-validated King’s clinical staging system for ALS to classify patients into different disease stages. We investigated in vivo hippocampal atrophy patterns across subfields and anterior-posterior segments in different King’s stages using structural MRI in 76 ALS patients and 94 health controls (HCs). The thalamus, corticostriatal tract and perforant path were used as structural controls to compare the sequence of alterations between these structures and the hippocampal subfields. Compared with HCs, ALS patients at King’s stage 1 had lower volumes in the bilateral posterior subiculum and presubiculum; ALS patients at King’s stage 2 exhibited lower volumes in the bilateral posterior subiculum, left anterior presubiculum and left global hippocampus; ALS patients at King’s stage 3 showed significantly lower volumes in the bilateral posterior subiculum, dentate gyrus and global hippocampus. Thalamic atrophy emerged at King’s stage 3. White matter tracts remained normal in a subset of ALS patients. Our study demonstrated that the pattern of hippocampal atrophy in ALS patients varies greatly across King’s stages. Future studies in ALS patients that focus on the hippocampus may help to further clarify possible co-pathologies in ALS.

Functional integration among neural units is one of the fundamental principles in brain organization that could be examined using resting-state functional connectivity (rs-FC). Interhemispheric functional integration plays a critical role in human cognition. Homotopic functional connectivity (HoFC) under resting state provide an avenue to investigate functional integration between the two brain hemispheres, which can improve the present understanding of how interhemispheric interactions affect cognitive processing. In this review, we summarize the progress of HoFC studies under resting state and highlight how these findings have enhanced our understanding of interhemispheric functional organization of the human brain. Future studies are encouraged to address particular methodological issues and to further ascertain behavioral correlates, brain disease’s modulation, task influence, and genetic basis of HoFC.

In the present longitudinal study, we investigated the joint effect of early family factors and long-term vocabulary development on the structure of reading-related white matter pathways in adolescents. Seventy-nine children participated in this study. Family environment was measured via parental questionnaire between age 1 and age 3. From age 4 to age 10, children’s vocabulary skills were tested annually. At age 14, diffusion tensor imaging data of the children were collected. Using individual-based tractography, 10 reading-related tracts of the two hemispheres were delineated. Different family factors were found to be correlated with different pathways: Age of literacy exposure was correlated with fractional anisotropy of the direct segment of the left arcuate fasciculus, while an association trend was found between early family socioeconomic status and fractional anisotropy of the left inferior frontal occipital fasciculus. Further regression analyses showed that the age of literacy exposure modulated the relationships between vocabulary development and the structure of the left arcuate fasciculus. Specifically, in the earlier literacy exposure group, no association was found between vocabulary development and the strength of the arcuate fasciculus, whereas in the later literacy exposure group, significant associations were found between vocabulary development and the strength of the arcuate fasciculus.

Chinese is a logographic language that is different from alphabetic languages in visual and semantic complexity. Thus far, it is still unclear whether Chinese children with dyslexia show similar disruption of white matter pathways as in alphabetic languages. The present study focused on the alteration of white matter pathways in Chinese children with dyslexia. Using diffusion tensor imaging tractography, the bilateral arcuate fasciculus (AF-anterior, AF-posterior and AF-direct segments), inferior fronto-occipital fasciculus (IFOF) and inferior longitudinal fasciculus (ILF) were delineated in each individual’s native space. Compared with age-matched controls, Chinese children with dyslexia showed reduced fractional anisotropy in the left AF-direct and the left ILF. Further regression analyses revealed a functional dissociation between the left AF-direct and the left ILF. The AF-direct tract integrity was associated with phonological processing skill, an ability important for reading in all writing systems, while the ILF integrity was associated with morphological processing skill, an ability more strongly recruited for Chinese reading. In conclusion, the double disruption locus in Chinese children with dyslexia, and the functional dissociation between dorsal and ventral pathways reflect both universal and specific properties of reading in Chinese.

BackgroundThe growth hormone (GH)/insulin-like growth factor-1 (IGF-1) axis plays an important role in brain structure and maintenance of brain function. There is a close correlation between serum GH and IGF1 levels and age-related cognitive function. The effects of childhood-onset growth hormone deficiency (GHD)on brain morphology are underestimated so far.MethodsIn this cross-sectional study, T1-weighted magnetic resonance imaging was assessed in 17 adult males with childhood-onset GHD and 17 age and gender-matched healthy controls. The cortical thickness was analyzed and compared between the two groups of subjects. Effects of disease status and hormone levels on cortical thickness were also evaluated.ResultsAlthough there was no difference in whole brain volume or gray matter volume between the two groups, there was decreased cortical thickness in the parahippocampal gyrus, posterior cingulate gyrus and occipital visual syncortex in the adult growth hormone deficiency (AGHD) group, and increased cortical thickness in a partial area of the frontal lobe, parietal lobe and occipital visual syncortex in AGHD group. Cortical thickness of the posterior cingulum gyrus was prominently associated with FT3 serum levels only in control group after adjusting of IGF-1 levels.ConclusionThese results suggest that young adult male patients with childhood-onset GHD have alterations in cortical thickness in different brain lobes/regions.

Accumulating evidence has shown enhanced sensorimotor control of vocal production as a consequence of extensive singing experience. The neural basis of this ability, however, is poorly understood. Given that the insula mediates motor aspects of vocal production, the present study investigated structural plasticity in insula induced by singing experience and its link to auditory feedback control of vocal production. Voxel-based morphometry (VBM) was used to examine the differences in gray matter (GM) volume in the insula of 21 singers and 21 non-singers. An auditory feedback perturbation paradigm was used to examine the differences in auditory-motor control of vocal production between singers and non-singers. Both groups vocalized sustained vowels while hearing their voice unexpectedly pitch-shifted −50 or −200 cents (200 ms duration). VBM analyses showed that singers exhibited significantly lower GM volumes in the bilateral insula than non-singers. When exposed to pitch perturbations in voice auditory feedback, singers involuntarily compensated for pitch perturbations in voice auditory feedback to a significantly lesser degree than non-singers. Moreover, across the two sizes of pitch perturbations, the magnitudes of vocal compensations were positively correlated with the total regional GM volumes in the bilateral insula. These results indicate that extensive singing training leads to decreased GM volumes in insula and suggest that morphometric plasticity in insula contributes to the enhanced sensorimotor control of vocal production observed in singers.

Object conceptual processing has been localized to distributed cortical regions that represent specific attributes. A challenging question is how object semantic space is formed. We tested a novel framework of representing semantic space in the pattern of white matter (WM) connections by extending the representational similarity analysis (RSA) to structural lesion pattern and behavioral data in 80 brain-damaged patients. For each WM connection, a neural representational dissimilarity matrix (RDM) was computed by first building machine-learning models with the voxel-wise WM lesion patterns as features to predict naming performance of a particular item and then computing the correlation between the predicted naming score and the actual naming score of another item in the testing patients. This correlation was used to build the neural RDM based on the assumption that if the connection pattern contains certain aspects of information shared by the naming processes of these two items, models trained with one item should also predict naming accuracy of the other. Correlating the neural RDM with various cognitive RDMs revealed that neural patterns in several WM connections that connect left occipital/middle temporal regions and anterior temporal regions associated with the object semantic space. Such associations were not attributable to modality-specific attributes (shape, manipulation, color, and motion), to peripheral picture-naming processes (picture visual similarity, phonological similarity), to broad semantic categories, or to the properties of the cortical regions that they connected, which tended to represent multiple modality-specific attributes. That is, the semantic space could be represented through WM connection patterns across cortical regions representing modality-specific attributes.

Most research into the neural mechanisms of humor has not explicitly focused on the association between emotion and humor on the brain white matter networks mediating this connection. However, this connection is especially salient in gelotophobia (the fear of being laughed at), which is regarded as the presentation of humorlessness, and two related traits, gelotophilia (the enjoyment of being laughed at) and katagelasticism (the enjoyment of laughing at others). Here, we explored whether the topological properties of white matter networks can account for the individual differences in the laughter-related traits of 31 healthy adults. We observed a significant negative correlation between gelotophobia scores and the clustering coefficient, local efficiency and global efficiency, but a positive association between gelotophobia scores and path length in the brain's white matter network. Moreover, the current study revealed that with increasing individual fear of being laughed at, the linking efficiencies in superior frontal gyrus, anterior cingulate cortex, parahippocampal gyrus, and middle temporal gyrus decreased. However, there were no significant correlations between either gelotophilia or katagelasticism scores or the topological properties of the brain white matter network. These findings suggest that the fear of being laughed at is directly related to the level of local and global information processing of the brain network, which might provide new insights into the neural mechanisms of the humor information processing.

Previous findings suggest that the Papez Circuit may have a role in major depressive disorders. We used atlas-based tract-specific quantification analysis and voxel-based analysis to examine the integrity of white matter tracts involved in mood regulation (including tracts in the Papez Circuit). Diffusion tensor imaging acquired from 35 first-episode, treatment-naive adults with major depressive disorders and 34 healthy adult controls were compared. Our statistical approach compared structural integrity of 11 major white matter tracts between the major depressive disorder and adult controls, as well as illness duration influence in patients. Fractional anisotropy was decreased in the hippocampal cingulum and in the anterior thalamic radiation according to both analytical approaches, all of which were important tracts included in the Papez Circuit. Our results support the role of the Papez Circuit in major depressive disorders with the minimal probability of false positive due to similar findings in both analyses that have complementary advantages. Dysfunction of the Papez Circuit may be a potential marker for studying the pathogenesis of major depressive disorders.

Diffusion-weighted MRI (DW-MRI), the only non-invasive technique for probing human brain white matter structures in vivo, has been widely used in both fundamental studies and clinical applications. Many studies have utilized diffusion tensor imaging (DTI) and tractography approaches to explore the topological properties of human brain anatomical networks by using the single tensor model, the basic model to quantify DTI indices and tractography. However, the conventional DTI technique does not take into account contamination by the cerebrospinal fluid (CSF), which has been known to affect the estimated DTI measures and tractography in the single tensor model. Previous studies have shown that the Fluid-Attenuated Inversion Recovery (FLAIR) technique can suppress the contribution of the CSF to the DW-MRI signal. We acquired DTI datasets from twenty-two subjects using both FLAIR-DTI and conventional DTI (non-FLAIR-DTI) techniques, constructed brain anatomical networks using deterministic tractography, and compared the topological properties of the anatomical networks derived from the two types of DTI techniques. Although the brain anatomical networks derived from both types of DTI datasets showed small-world properties, we found that the brain anatomical networks derived from the FLAIR-DTI showed significantly increased global and local network efficiency compared with those derived from the conventional DTI. The increases in the network regional topological properties derived from the FLAIR-DTI technique were observed in CSF-filled regions, including the postcentral gyrus, periventricular regions, inferior frontal and temporal gyri, and regions in the visual cortex. Because brain anatomical networks derived from conventional DTI datasets with tractography have been widely used in many studies, our findings may have important implications for studying human brain anatomical networks derived from DW-MRI data and tractography.

Recently, a combination of non-invasive neuroimaging techniques and graph theoretical approaches has provided a unique opportunity for understanding the patterns of the structural and functional connectivity of the human brain (referred to as the human brain connectome). Currently, there is a very large amount of brain imaging data that have been collected, and there are very high requirements for the computational capabilities that are used in high-resolution connectome research. In this paper, we propose a hybrid CPU-GPU framework to accelerate the computation of the human brain connectome. We applied this framework to a publicly available resting-state functional MRI dataset from 197 participants. For each subject, we first computed Pearson's Correlation coefficient between any pairs of the time series of gray-matter voxels, and then we constructed unweighted undirected brain networks with 58 k nodes and a sparsity range from 0.02% to 0.17%. Next, graphic properties of the functional brain networks were quantified, analyzed and compared with those of 15 corresponding random networks. With our proposed accelerating framework, the above process for each network cost 80∼150 minutes, depending on the network sparsity. Further analyses revealed that high-resolution functional brain networks have efficient small-world properties, significant modular structure, a power law degree distribution and highly connected nodes in the medial frontal and parietal cortical regions. These results are largely compatible with previous human brain network studies. Taken together, our proposed framework can substantially enhance the applicability and efficacy of high-resolution (voxel-based) brain network analysis, and have the potential to accelerate the mapping of the human brain connectome in normal and disease states.

Many diffusion parameters and indices (e.g., fractional anisotropy [FA] and mean diffusivity [MD]) have been derived from diffusion magnetic resonance imaging (MRI) data. These parameters have been extensively applied as imaging markers for localizing white matter (WM) changes under various conditions (e.g., development, degeneration and disease). However, the vast majority of the existing parameters is derived from intra-voxel analyses and represents the diffusion properties solely within the voxel unit. Other types of parameters that characterize inter-voxel relationships have been largely overlooked. In the present study, we propose a novel inter-voxel metric referred to as the local diffusion homogeneity (LDH). This metric quantifies the local coherence of water molecule diffusion in a model-free manner. It can serve as an additional marker for evaluating the WM microstructural properties of the brain. To assess the distinguishing features between LDH and FA/MD, the metrics were systematically compared across space and subjects. As an example, both the LDH and FA/MD metrics were applied to measure age-related WM changes. The results indicate that LDH reveals unique inter-subject variability in specific WM regions (e.g., cerebral peduncle, internal capsule and splenium). Furthermore, there are regions in which measurements of age-related WM alterations with the LDH and FA/MD metrics yield discrepant results. These findings suggest that LDH and FA/MD have different sensitivities to specific WM microstructural properties. Taken together, the present study shows that LDH is complementary to the conventional diffusion-MRI markers and may provide additional insights into inter-subject WM variability. Further studies, however, are needed to uncover the neuronal mechanisms underlying the LDH.

Graph theoretical analysis of brain networks based on resting-state functional MRI (R-fMRI) has attracted a great deal of attention in recent years. These analyses often involve the selection of correlation metrics and specific preprocessing steps. However, the influence of these factors on the topological properties of functional brain networks has not been systematically examined. Here, we investigated the influences of correlation metric choice (Pearson's correlation versus partial correlation), global signal presence (regressed or not) and frequency band selection [slow-5 (0.01-0.027 Hz) versus slow-4 (0.027-0.073 Hz)] on the topological properties of both binary and weighted brain networks derived from them, and we employed test-retest (TRT) analyses for further guidance on how to choose the "best" network modeling strategy from the reliability perspective. Our results show significant differences in global network metrics associated with both correlation metrics and global signals. Analysis of nodal degree revealed differing hub distributions for brain networks derived from Pearson's correlation versus partial correlation. TRT analysis revealed that the reliability of both global and local topological properties are modulated by correlation metrics and the global signal, with the highest reliability observed for Pearson's-correlation-based brain networks without global signal removal (WOGR-PEAR). The nodal reliability exhibited a spatially heterogeneous distribution wherein regions in association and limbic/paralimbic cortices showed moderate TRT reliability in Pearson's-correlation-based brain networks. Moreover, we found that there were significant frequency-related differences in topological properties of WOGR-PEAR networks, and brain networks derived in the 0.027-0.073 Hz band exhibited greater reliability than those in the 0.01-0.027 Hz band. Taken together, our results provide direct evidence regarding the influences of correlation metrics and specific preprocessing choices on both the global and nodal topological properties of functional brain networks. This study also has important implications for how to choose reliable analytical schemes in brain network studies.

Previous neuroimaging studies have suggested a role of amygdala in trait anxiety level, in which amygdala was typically treated as a whole. To date, it remains unknown whether the morphology of specific subregions of amygdala are associated with trait anxiety. Here, we employed a shape analysis approach to locate the association between its morphology and trait anxiety on the surface of amygdala. 24 healthy young participants were included. The boundary of amygdala for each subject was first manually outlined using high-resolution magnetic resonance (MR) image, followed by 3D surface reconstruction and parameterization using spherical harmonic description. Two point-wise metrics, direct displacement between the individual surface and atlas surface and its normal projection, were used to quantify the surface morphology of amygdala. Statistical analysis revealed significant correlations between the two surface metrics and trait anxiety levels, which were located around the lateral and central nucleus of right amygdala. Our results provided localized information for the association between amygdala and trait anxiety, and suggested a central role of the lateral and central nucleus of right amygdala on trait anxiety.