Cross-domain Fiber Cluster Shape Analysis for Language Performance Cognitive Score Prediction.

Shape plays an important role in computer graphics, offering informative features to convey an object's morphology and functionality. Shape analysis in brain imaging can help interpret structural and functionality correlations of the human brain. In this work, we investigate the shape of the brain's 3D white matter connections and its potential predictive relationship to human cognitive function. We reconstruct brain connections as sequences of 3D points using diffusion magnetic resonance imaging (dMRI) tractography. To describe each connection, we extract 12 shape descriptors in addition to traditional dMRI connectivity and tissue microstructure features. We introduce a novel framework, Shape--fused Fiber Cluster Transformer (SFFormer), that leverages a multi-head cross-attention feature fusion module to predict subject-specific language performance based on dMRI tractography. We assess the performance of the method on a large dataset including 1065 healthy young adults. The results demonstrate that both the transformer-based SFFormer model and its inter/intra feature fusion with shape, microstructure, and connectivity are informative, and together, they improve the prediction of subject-specific language performance scores. Overall, our results indicate that the shape of the brain's connections is predictive of human language function.

TractGeoNet: A geometric deep learning framework for pointwise analysis of tract microstructure to predict language assessment performance.

We propose a geometric deep-learning-based framework, TractGeoNet, for performing regression using diffusion magnetic resonance imaging (dMRI) tractography and associated pointwise tissue microstructure measurements. By employing a point cloud representation, TractGeoNet can directly utilize tissue microstructure and positional information from all points within a fiber tract without the need to average or bin data along the streamline as traditionally required by dMRI tractometry methods. To improve regression performance, we propose a novel loss function, the Paired-Siamese Regression loss, which encourages the model to focus on accurately predicting the relative differences between regression label scores rather than just their absolute values. In addition, to gain insight into the brain regions that contribute most strongly to the prediction results, we propose a Critical Region Localization algorithm. This algorithm identifies highly predictive anatomical regions within the white matter fiber tracts for the regression task. We evaluate the effectiveness of the proposed method by predicting individual performance on two neuropsychological assessments of language using a dataset of 20 association white matter fiber tracts from 806 subjects from the Human Connectome Project Young Adult dataset. The results demonstrate superior prediction performance of TractGeoNet compared to several popular regression models that have been applied to predict individual cognitive performance based on neuroimaging features. Of the twenty tracts studied, we find that the left arcuate fasciculus tract is the most highly predictive of the two studied language performance assessments. Within each tract, we localize critical regions whose microstructure and point information are highly and consistently predictive of language performance across different subjects and across multiple independently trained models. These critical regions are widespread and distributed across both hemispheres and all cerebral lobes, including areas of the brain considered important for language function such as superior and anterior temporal regions, pars opercularis, and precentral gyrus. Overall, TractGeoNet demonstrates the potential of geometric deep learning to enhance the study of the brain's white matter fiber tracts and to relate their structure to human traits such as language performance.

Harmonized diffusion MRI data and white matter measures from the Adolescent Brain Cognitive Development Study.

The Adolescent Brain Cognitive Development (ABCD) Study® has collected data from over 10,000 children across 21 sites, providing insights into adolescent brain development. However, site-specific scanner variability has made it challenging to use diffusion MRI (dMRI) data from this study. To address this, a dataset of harmonized and processed ABCD dMRI data (from release 3) has been created, comprising quality-controlled imaging data from 9,345 subjects, focusing exclusively on the baseline session, i.e., the first time point of the study. This resource required substantial computational time (approx. 50,000 CPU hours) for harmonization, whole-brain tractography, and white matter parcellation. The dataset includes harmonized dMRI data, 800 white matter clusters, 73 anatomically labeled white matter tracts in full and low resolution, and 804 different dMRI-derived measures per subject (72.3 TB total size). Accessible via the NIMH Data Archive, it offers a large-scale dMRI dataset for studying structural connectivity in child and adolescent neurodevelopment. Additionally, several post-harmonization experiments were conducted to demonstrate the success of the harmonization process on the ABCD dataset.

Characterization of central manifestations in patients with Niemann-Pick disease type C.

PURPOSE: Niemann-Pick disease type C (NPC) is a rare lysosomal storage disease characterized by progressive neurodegeneration and neuropsychiatric symptoms. This study investigated pathophysiological mechanisms underlying motor deficits, particularly speech production, and cognitive impairment. METHODS: We prospectively phenotyped 8 adults with NPC and age-sex-matched healthy controls using a comprehensive assessment battery, encompassing clinical presentation, plasma biomarkers, hand-motor skills, speech production, cognitive tasks, and (micro-)structural and functional central nervous system properties through magnetic resonance imaging. RESULTS: Patients with NPC demonstrated deficits in fine-motor skills, speech production timing and coordination, and cognitive performance. Magnetic resonance imaging revealed reduced cortical thickness and volume in cerebellar subdivisions (lobule VI and crus I), cortical (frontal, temporal, and cingulate gyri) and subcortical (thalamus and basal ganglia) regions, and increased choroid plexus volumes in NPC. White matter fractional anisotropy was reduced in specific pathways (intracerebellar input and Purkinje tracts), whereas diffusion tensor imaging graph theory analysis identified altered structural connectivity. Patients with NPC exhibited altered activity in sensorimotor and cognitive processing hubs during resting-state and speech production. Canonical component analysis highlighted the role of cerebellar-cerebral circuitry in NPC and its integration with behavioral performance and disease severity. CONCLUSION: This deep phenotyping approach offers a comprehensive systems neuroscience understanding of NPC motor and cognitive impairments, identifying potential central nervous system biomarkers.

Harmonized diffusion MRI data and white matter measures from the Adolescent Brain Cognitive Development Study.

The Adolescent Brain Cognitive Development (ABCD) study has collected data from over 10,000 children across 21 sites, providing valuable insights into adolescent brain development. However, site-specific scanner variability has made it challenging to use diffusion MRI (dMRI) data from this study. To address this, a database of harmonized and processed ABCD dMRI data has been created, comprising quality-controlled imaging data from 9345 subjects. This resource required significant computational effort, taking ~50,000 CPU hours to harmonize the data, perform white matter parcellation, and run whole brain tractography. The database includes harmonized dMRI data, 800 white matter clusters, 73 anatomically labeled white matter tracts both in full-resolution (for analysis) and low-resolution (for visualization), and 804 different dMRI-derived measures per subject. It is available via the NIMH Data Archive and offers tremendous potential for scientific discoveries in structural connectivity studies of neurodevelopment in children and adolescents. Additionally, several post-harmonization experiments were conducted to demonstrate the success of the harmonization process on the ABCD dataset.

Directionally encoded color track density imaging in brain tumor patients: A potential application to neuro-oncology surgical planning.

BACKGROUND: Diffusion magnetic resonance imaging white matter tractography, an increasingly popular preoperative planning modality used for pre-surgical planning in brain tumor patients, is employed with the goal of maximizing tumor resection while sparing postoperative neurological function. Clinical translation of white matter tractography has been limited by several shortcomings of standard diffusion tensor imaging (DTI), including poor modeling of fibers crossing through regions of peritumoral edema and low spatial resolution for typical clinical diffusion MRI (dMRI) sequences. Track density imaging (TDI) is a post-tractography technique that uses the number of tractography streamlines and their long-range continuity to map the white matter connections of the brain with enhanced image resolution relative to the acquired dMRI data, potentially offering improved white matter visualization in patients with brain tumors. The aim of this study was to assess the utility of TDI-based white matter maps in a neurosurgical planning context compared to the current clinical standard of DTI-based white matter maps. METHODS: Fourteen consecutive brain tumor patients from a single institution were retrospectively selected for the study. Each patient underwent 3-Tesla dMRI scanning with 30 gradient directions and a b-value of 1000 s/mm2. For each patient, two directionally encoded color (DEC) maps were produced as follows. DTI-based DEC-fractional anisotropy maps (DEC-FA) were generated on the scanner, while DEC-track density images (DEC-TDI) were generated using constrained spherical deconvolution based tractography. The potential clinical utility of each map was assessed by five practicing neurosurgeons, who rated the maps according to four clinical utility statements regarding different clinical aspects of pre-surgical planning. The neurosurgeons rated each map according to their agreement with four clinical utility statements regarding if the map 1 identified clinically relevant tracts, (2) helped establish a goal resection margin, (3) influenced a planned surgical route, and (4) was useful overall. Cumulative link mixed effect modeling and analysis of variance were performed to test the primary effect of map type (DEC-TDI vs. DEC-FA) on rater score. Pairwise comparisons using estimated marginal means were then calculated to determine the magnitude and directionality of differences in rater scores by map type. RESULTS: A majority of rater responses agreed with the four clinical utility statements, indicating that neurosurgeons found both DEC maps to be useful. Across all four investigated clinical utility statements, the DEC map type significantly influenced rater score. Rater scores were significantly higher for DEC-TDI maps compared to DEC-FA maps. The largest effect size in rater scores in favor of DEC-TDI maps was observed for clinical utility statement 2, which assessed establishing a goal resection margin. CONCLUSION: We observed a significant neurosurgeon preference for DEC-TDI maps, indicating their potential utility for neurosurgical planning.

Language combinations of multilinguals are reflected in their first-language knowledge and processing.

Consequences of multilingualism vary from offering cognitive benefits to poor educational and cognitive outcomes. One aspect of multilingualism that has not been systematically examined is the typology of multilinguals' languages: Do differences and similarities between languages multilinguals are exposed to contribute to the development of their cognition and brain? We investigated n = 162 5-6-year-olds with various language backgrounds on a monolingual-to-quintilingual continuum. Our results show that typological linguistic diversity can be related to expressive vocabulary knowledge in the dominant language. On neural level, it relates to brain activation patterns in (among others) the PGa area in the bilateral IPL, a brain region previously associated with multilingual experience, but never with language typology. We propose an ecologically valid way of describing the continuum of multilingual language experience and provide evidence for both the cognition and the brain of multilingual kindergartners to be related to the typological linguistic diversity of their environment.

Panel composition and disparities in the topics of presentation in vascular surgery conferences.

BACKGROUND: Previous studies identified gender disparities in surgical conference presenters and moderators. We sought to assess disparities in the representation of women in terms of speakers and moderators, but with particular emphasis on panels and topics of discussion at vascular surgery conferences. METHODS: Data regarding presenters and moderators from the Southern Association of Vascular Surgery, Western Vascular Society, Vascular and Endovascular Surgical Society, Society for Clinical Vascular Surgery, and Society for Vascular Surgery conferences was obtained from online meeting archives and via email correspondence. Scientific session speakers, moderators, and panelists were identified by sex. Specific vascular topics for each discussion were also identified. Keynote speakers or special guests were excluded. RESULTS: Compared to men, women were less often presenters (18% versus 82%, p < .002) and moderators (16% versus 84%, p < .001) of conference sessions. Women were most likely to present on dialysis access and least likely to present on venous disease overall. Women were more likely to present on aortic (24% vs 19%; p < .013) and cerebrovascular disease (33% vs 27%; p < .021) at regional compared to national conferences. Of panels assessed, 68% were all-male. Subgroup analysis suggests that some improvements have been made over time. CONCLUSIONS: Significant disparities persist in the topics presented and in panel composition suggesting potential areas for improvement in equity. Further study should focus on evaluating trends in the training level of the presenter and the topics presented, and assessing parity in structural factors that impact research presentation opportunities.

Precision fMRI reveals that the language-selective network supports both phrase-structure building and lexical access during language production.

A fronto-temporal brain network has long been implicated in language comprehension. However, this network's role in language production remains debated. In particular, it remains unclear whether all or only some language regions contribute to production, and which aspects of production these regions support. Across 3 functional magnetic resonance imaging experiments that rely on robust individual-subject analyses, we characterize the language network's response to high-level production demands. We report 3 novel results. First, sentence production, spoken or typed, elicits a strong response throughout the language network. Second, the language network responds to both phrase-structure building and lexical access demands, although the response to phrase-structure building is stronger and more spatially extensive, present in every language region. Finally, contra some proposals, we find no evidence of brain regions-within or outside the language network-that selectively support phrase-structure building in production relative to comprehension. Instead, all language regions respond more strongly during production than comprehension, suggesting that production incurs a greater cost for the language network. Together, these results align with the idea that language comprehension and production draw on the same knowledge representations, which are stored in a distributed manner within the language-selective network and are used to both interpret and generate linguistic utterances.

White matter association tracts underlying language and theory of mind: An investigation of 809 brains from the Human Connectome Project.

Language and theory of mind (ToM) are the cognitive capacities that allow for the successful interpretation and expression of meaning. While functional MRI investigations are able to consistently localize language and ToM to specific cortical regions, diffusion MRI investigations point to an inconsistent and sometimes overlapping set of white matter tracts associated with these two cognitive domains. To further examine the white matter tracts that may underlie these domains, we use a two-tensor tractography method to investigate the white matter microstructure of 809 participants from the Human Connectome Project. 20 association white matter tracts (10 in each hemisphere) are uniquely identified by leveraging a neuroanatomist-curated automated white matter tract atlas. The fractional anisotropy (FA), mean diffusivity (MD), and number of streamlines (NoS) are measured for each white matter tract. Performance on neuropsychological assessments of semantic memory (NIH Toolbox Picture Vocabulary Test, TPVT) and emotion perception (Penn Emotion Recognition Test, PERT) are used to measure critical subcomponents of the language and ToM networks, respectively. Regression models are constructed to examine how structural measurements of left and right white matter tracts influence performance across these two assessments. We find that semantic memory performance is influenced by the number of streamlines of the left superior longitudinal fasciculus III (SLF-III), and emotion perception performance is influenced by the number of streamlines of the right SLF-III. Additionally, we find that performance on both semantic memory & emotion perception is influenced by the FA of the left arcuate fasciculus (AF). The results point to multiple, overlapping white matter tracts that underlie the cognitive domains of language and ToM. Results are discussed in terms of hemispheric dominance and concordance with prior investigations.

Auditory Processing of Non-speech Stimuli by Children in Dual-Language Immersion Programs.

Perception of low-level auditory cues such as frequency modulation (FM) and rise time (RT) is crucial for development of phonemic representations, segmentation of word boundaries, and attunement to prosodic patterns in language. While learning an additional language, children may develop an increased sensitivity to these cues to extract relevant information from multiple types of linguistic input. Performance on these auditory processing tasks such as FM and RT by children learning another language is, however, unknown. Here we examine 92 English-speaking 7-8-year-olds in the U.S. and their performance in FM and RT perceptual tasks at the end of their second year in Cantonese or Spanish dual-language immersion compared to children in general English education programs. Results demonstrate that children in immersion programs have greater sensitivity to FM, but not RT, controlling for various factors. The immersion program students were also observed to have better phonological awareness performance. However, individual differences in FM sensitivity were not associated with phonological awareness, a pattern typically observed in monolinguals. These preliminary findings suggest a possible impact of formal language immersion on low-level auditory processing. Additional research is warranted to understand causal relationships and ultimate impact on language skills in multilinguals.

Decoding the role of the cerebellum in the early stages of reading acquisition.

Numerous studies have consistently reported functional activation of the cerebellum during reading tasks, especially in the right cerebellar hemisphere. However, it remains unclear whether this region is also involved in reading during the earliest stages of reading acquisition. Here, we investigated whether and how the cerebellum contributes to reading acquisition. We tested 80 5-6-year-old kindergarteners, who performed a visual word matching task during which functional MRI (fMRI) data were collected. We found that bilateral cerebellar hemispheres were significantly activated during visual word processing. Moreover, activation of left cerebellar lobule VII extending to lobule VIII negatively and significantly correlated with current reading ability, whereas activation of right cerebellar lobule VII extending to lobule VIII significantly and positively correlated with future reading ability. Functional decoding via functional connectivity patterns further revealed that left and right cerebellar lobules connected with different cerebral cortex regions. Our results suggest a division of labor between the left and right cerebellar lobules in beginning readers.

Predictors of postoperative biochemical remission in acromegaly.

PURPOSE: Acromegaly is a rare neuroendocrine condition that can lead to significant morbidity. Despite China's vast population size, studies on acromegaly remain sparse. This study aimed to investigate the clinical characteristics and predictors of biochemical remission after surgery for acromegaly using the China Acromegaly Patient Association (CAPA) database. METHODS: A retrospective nationwide study was conducted using patient-reported data from CAPA database between 1998 and 2018. The principal component analysis (PCA) and logistic regression analysis were employed to determine independent predictors of biochemical remission at 3 months in patients after surgery. RESULTS: Of the 546 surgical cases (mean age: 36.8 years; 59.5% females), macroadenomas and invasive tumors (Knosp score 3-4) were 83.9% and 64.1%, respectively. Ninety-five percent of patients were treated with endonasal surgery and 36.8% exhibited biochemical remission at 3-months postoperatively. The following independent predictors of biochemical remission were identified: preoperative growth hormone (GH) levels between 12 and 28 µg/L [odds ratio (OR) = 0.58; 95% confidence interval (CI), 0.37-0.92; p = 0.021], preoperative GH levels > 28 µg/L (OR = 0.55; 95% CI, 0.34-0.88; p = 0.013), macroadenoma (OR = 0.56; 95% CI, 0.32-0.96; p = 0.034), giant adenomas (OR = 0.14; 95% CI, 0.05-0.38; p < 0.001), Knosp score 3-4 (OR = 0.37; 95% CI, 0.24-0.57; p < 0.001), and preoperative medication usage (OR = 2.32; 95% CI, 1.46-3.70; p < 0.001). CONCLUSIONS: In this nationwide study spanning over two decades, we highlight that higher preoperative GH levels, large tumor size, and greater extent of tumor invasiveness are associated with a lower likelihood of biochemical remission at 3-months after surgery, while preoperative medical therapy increases the chance of remission.

Spoken language proficiency predicts print-speech convergence in beginning readers.

Learning to read transforms the brain, building on children's existing capacities for language and visuospatial processing. In particular, the development of print-speech convergence, or the spatial overlap of neural regions necessary for both auditory and visual language processing, is critical for literacy acquisition. Print-speech convergence is a universal signature of proficient reading, yet the antecedents of this convergence remain unknown. Here we examine the relationship between spoken language proficiency and the emergence of the print-speech network in beginning readers (ages 5-6). Results demonstrate that children's language proficiency, but not their early literacy skill, explains variance in their print-speech neural convergence in kindergarten. Furthermore, print-speech convergence in kindergarten predicts reading abilities one year later. These findings suggest that children's language ability is a core mechanism guiding the neural plasticity for learning to read, and extend theoretical perspectives on language and literacy acquisition across the lifespan.

Direct and Indirect Contributions of Executive Function to Word Decoding and Reading Comprehension in Kindergarten.

Extant research is increasingly recognizing the contribution of executive function (EF) to reading comprehension alongside established predictors like word decoding and oral language. The nature of the association between EF and reading comprehension is commonly investigated in older children and in those with reading impairments. However, less is known about this relationship in emerging readers in kindergarten, where word decoding and reading comprehension are highly intertwined. Moreover, a better understanding of the mechanisms by which EF influences reading comprehension is needed. The present study investigated direct contributions of EF to reading comprehension, as well as indirect contributions via word decoding in 97 kindergarteners. Results indicated that there was a significant indirect effect of EF on reading comprehension, with word decoding mediating this association. The direct contribution of EF to reading comprehension was not significant. Implications for reading instruction and intervention for early readers are discussed.