Evaluating arcuate fasciculus laterality measurements across dataset and tractography pipelines

Tractometry of the Human Connectome Project: resources and insights

Introduction

The Human Connectome Project (HCP) has become a keystone dataset in human neuroscience, with a plethora of important applications in advancing brain imaging methods and an understanding of the human brain. We focused on tractometry of HCP diffusion-weighted MRI (dMRI) data.

Methods

We used an open-source software library (pyAFQ; https://yeatmanlab.github.io/pyAFQ) to perform probabilistic tractography and delineate the major white matter pathways in the HCP subjects that have a complete dMRI acquisition (n = 1,041). We used diffusion kurtosis imaging (DKI) to model white matter microstructure in each voxel of the white matter, and extracted tract profiles of DKI-derived tissue properties along the length of the tracts. We explored the empirical properties of the data: first, we assessed the heritability of DKI tissue properties using the known genetic linkage of the large number of twin pairs sampled in HCP. Second, we tested the ability of tractometry to serve as the basis for predictive models of individual characteristics (e.g., age, crystallized/fluid intelligence, reading ability, etc.), compared to local connectome features. To facilitate the exploration of the dataset we created a new web-based visualization tool and use this tool to visualize the data in the HCP tractometry dataset. Finally, we used the HCP dataset as a test-bed for a new technological innovation: the TRX file-format for representation of dMRI-based streamlines.

Results

We released the processing outputs and tract profiles as a publicly available data resource through the AWS Open Data program's Open Neurodata repository. We found heritability as high as 0.9 for DKI-based metrics in some brain pathways. We also found that tractometry extracts as much useful information about individual differences as the local connectome method. We released a new web-based visualization tool for tractometry-"Tractoscope" (https://nrdg.github.io/tractoscope). We found that the TRX files require considerably less disk space-a crucial attribute for large datasets like HCP. In addition, TRX incorporates a specification for grouping streamlines, further simplifying tractometry analysis.

Microscopic fractional anisotropy outperforms multiple sclerosis lesion assessment and clinical outcome associations over standard fractional anisotropy tensor

We aimed to compare the ability of diffusion tensor imaging and multi-compartment spherical mean technique to detect focal tissue damage and in distinguishing between different connectivity patterns associated with varying clinical outcomes in multiple sclerosis (MS). Seventy-six people diagnosed with MS were scanned using a SIEMENS Prisma Fit 3T magnetic resonance imaging (MRI), employing both conventional (T1w and fluid-attenuated inversion recovery) and advanced diffusion MRI sequences from which fractional anisotropy (FA) and microscopic FA (μFA) maps were generated. Using automated fiber quantification (AFQ), we assessed diffusion profiles across multiple white matter (WM) pathways to measure the sensitivity of anisotropy diffusion metrics in detecting localized tissue damage. In parallel, we analyzed structural brain connectivity in a specific patient cohort to fully grasp its relationships with cognitive and physical clinical outcomes. This evaluation comprehensively considered different patient categories, including cognitively preserved (CP), mild cognitive deficits (MCD), and cognitively impaired (CI) for cognitive assessment, as well as groups distinguished by physical impact: those with mild disability (Expanded Disability Status Scale [EDSS] <=3) and those with moderate-severe disability (EDSS >3). In our initial objective, we employed Ridge regression to forecast the presence of focal MS lesions, comparing the performance of μFA and FA. μFA exhibited a stronger association with tissue damage and a higher predictive precision for focal MS lesions across the tracts, achieving an R-squared value of .57, significantly outperforming the R-squared value of .24 for FA (p-value <.001). In structural connectivity, μFA exhibited more pronounced differences than FA in response to alteration in both cognitive and physical clinical scores in terms of effect size and number of connections. Regarding cognitive groups, FA differences between CP and MCD groups were limited to 0.5% of connections, mainly around the thalamus, while μFA revealed changes in 2.5% of connections. In the CP and CI group comparison, which have noticeable cognitive differences, the disparity was 5.6% for FA values and 32.5% for μFA. Similarly, μFA outperformed FA in detecting WM changes between the MCD and CI groups, with 5% versus 0.3% of connections, respectively. When analyzing structural connectivity between physical disability groups, μFA still demonstrated superior performance over FA, disclosing a 2.1% difference in connectivity between regions closely associated with physical disability in MS. In contrast, FA spotted a few regions, comprising only 0.6% of total connections. In summary, μFA emerged as a more effective tool than FA in predicting MS lesions and identifying structural changes across patients with different degrees of cognitive and global disability, offering deeper insights into the complexities of MS-related impairments.

Lateralization of dorsal fiber tract targeting Broca's area concurs with language skills during development

Language is bounded to the left hemisphere in the adult brain and the functional lateralization can already be observed early during development. Here we investigate whether this is paralleled by a lateralization of the white matter structural language network. We analyze the strength and microstructural properties of language-related fiber tracts connecting temporal and frontal cortices with a separation of two dorsal tracts, one targeting the posterior Broca's area (BA44) and one targeting the precentral gyrus (BA6). In a large sample of young children (3-6 years), we demonstrate that, in contrast to the BA6-targeting tract, the microstructural asymmetry of the BA44-targeting fiber tract significantly correlates locally with different aspects of development. While the asymmetry in its anterior segment reflects age, the asymmetry in its posterior segment is associated with the children's language skills. These findings demonstrate a fine-grained structure-to-function mapping in the lateralized network and go beyond our current view of language-related human brain maturation.

Hemispheric lateralization of language processing: insights from network-based symptom mapping and patient subgroups

The hemispheric laterality of language processing has become a hot topic in modern neuroscience. Although most previous studies have reported left-lateralized language processing, other studies found it to be bilateral. A previous neurocomputational model has proposed a unified framework to explain that the above discrepancy might be from healthy and patient individuals. This model posits an initial symmetry but imbalanced capacity in language processing for healthy individuals, with this imbalance contributing to language recovery disparities following different hemispheric injuries. The present study investigated this model by analyzing the lateralization patterns of language subnetworks across multiple attributes with a group of 99 patients (compared to nonlanguage processing) and examining the lateralization patterns of language subnetworks in subgroups with damage to different hemispheres. Subnetworks were identified using a whole-brain network-based lesion-symptom mapping method, and the lateralization index was quantitatively measured. We found that all the subnetworks in language processing were left-lateralized, while subnetworks in nonlanguage processing had different lateralization patterns. Moreover, diverse hemisphere-injury subgroups exhibited distinct language recovery effects. These findings provide robust support for the proposed neurocomputational model of language processing.

Language lateralization mapping (reversibly) masked by non-dominant focal epilepsy: a case report

Language lateralization in patients with focal epilepsy frequently diverges from the left-lateralized pattern that prevails in healthy right-handed people, but the mechanistic explanations are still a matter of debate. Here, we debate the complex interaction between focal epilepsy, language lateralization, and functional neuroimaging techniques by introducing the case of a right-handed patient with unaware focal seizures preceded by aphasia, in whom video-EEG and PET examination suggested the presence of focal cortical dysplasia in the right superior temporal gyrus, despite a normal structural MRI. The functional MRI for language was inconclusive, and the neuropsychological evaluation showed mild deficits in language functions. A bilateral stereo-EEG was proposed confirming the right superior temporal gyrus origin of seizures, revealing how ictal aphasia emerged only once seizures propagated to the left superior temporal gyrus and confirming, by cortical mapping, the left lateralization of the posterior language region. Stereo-EEG-guided radiofrequency thermocoagulations of the (right) focal cortical dysplasia not only reduced seizure frequency but led to the normalization of the neuropsychological assessment and the "restoring" of a classical left-lateralized functional MRI pattern of language. This representative case demonstrates that epileptiform activity in the superior temporal gyrus can interfere with the functioning of the contralateral homologous cortex and its associated network. In the case of presurgical evaluation in patients with epilepsy, this interference effect must be carefully taken into consideration. The multimodal language lateralization assessment reported for this patient further suggests the sensitivity of different explorations to this interference effect. Finally, the neuropsychological and functional MRI changes after thermocoagulations provide unique cues on the network pathophysiology of focal cortical dysplasia and the role of diverse techniques in indexing language lateralization in complex scenarios.

Functional MRI but not white matter fibre dissection identifies language dominance

OBJECTIVES

Lateralisation of some language pathways has been reported in the literature using diffusion tractography, which is more feasible than functional magnetic resonance imaging (fMRI) in challenging patients. Our retrospective study investigates whether a correlation exists between threshold-independent fMRI language lateralisation and structural lateralisation using tractography in healthy controls and brain tumour patients.

METHODS

Fifteen healthy subjects and 61 patients underwent language fMRI and diffusion-weighted MRI. A regional fMRI laterality index (LI) was calculated. Tracts dissected were the arcuate fasciculus (long direct and short indirect tracts), uncinate fasciculus, inferior longitudinal fasciculus, inferior fronto-occipital fasciculus and frontal aslant tract. An asymmetry index (AI) for each tract was calculated using tract volume analysed with single tensor (ST) and spherical deconvolution (SD) models, as well as hindrance modulated orientational anisotropy (HMOA) for SD tracts. Linear regression assessed the correlation between LI and AI.

RESULTS

In all subjects, there was no significant correlation between LI and AI for any of the dissected tracts. Significant correlations were only found when handedness for controls and tumour volume for patients were included as covariates. In handedness subgroups, the average AI of some tracts showed the same laterality as LI, and some the opposite. Discordant results were observed for ST- and SD-based AIs.

CONCLUSIONS

Our results do not support using tractography in the assessment of language lateralisation. The discordant results between ST and SD indicate that either the structural lateralisation of dissected tracts is less robust than functional lateralisation, or tractography is not sensitive methodology. Other diffusion analysis approaches should be developed.

CLINICAL RELEVANCE STATEMENT

Although diffusion tractography may be more feasible than fMRI in challenging tumour patients and where sedation or anaesthesia is required, our results do not currently recommend replacing fMRI with tractography using volume or HMOA in the assessment of language lateralisation.

KEY POINTS

• No correlation found between fMRI and tractography in language lateralisation. • Discordance between asymmetry indices of different tractography models and metrics. • Tractography not currently recommended in language lateralisation assessment.

Children with Rolandic epilepsy have micro- and macrostructural abnormalities in white matter constituting networks necessary for language function

INTRODUCTION

Self-limited epilepsy with centrotemporal spikes is a transient developmental epilepsy with a seizure onset zone localized to the centrotemporal cortex that commonly impacts aspects of language function. To better understand the relationship between these anatomical findings and symptoms, we characterized the language profile and white matter microstructural and macrostructural features in a cohort of children with SeLECTS.

METHODS

Children with active SeLECTS (n = 13), resolved SeLECTS (n = 12), and controls (n = 17) underwent high-resolution MRIs including diffusion tensor imaging sequences and multiple standardized neuropsychological measures of language function. We identified the superficial white matter abutting the inferior rolandic cortex and superior temporal gyrus using a cortical parcellation atlas and derived the arcuate fasciculus connecting them using probabilistic tractography. We compared white matter microstructural characteristics (axial, radial and mean diffusivity, and fractional anisotropy) between groups in each region, and tested for linear relationships between diffusivity metrics in these regions and language scores on neuropsychological testing.

RESULTS

We found significant differences in several language modalities in children with SeLECTS compared to controls. Children with SeLECTS performed worse on assessments of phonological awareness (p = 0.045) and verbal comprehension (p = 0.050). Reduced performance was more pronounced in children with active SeLECTS compared to controls, namely, phonological awareness (p = 0.028), verbal comprehension (p = 0.028), and verbal category fluency (p = 0.031), with trends toward worse performance also observed in verbal letter fluency (p = 0.052), and the expressive one-word picture vocabulary test (p = 0.068). Children with active SeLECTS perform worse than children with SeLECTS in remission on tests of verbal category fluency (p = 0.009), verbal letter fluency (p = 0.006), and the expressive one-word picture vocabulary test (p = 0.045). We also found abnormal superficial white matter microstructure in centrotemporal ROIs in children with SeLECTS, characterized by increased diffusivity and fractional anisotropy compared to controls (AD p = 0.014, RD p = 0.028, MD p = 0.020, and FA p = 0.024). Structural connectivity of the arcuate fasciculus connecting perisylvian cortical regions was lower in children with SeLECTS (p = 0.045), and in the arcuate fasciculus children with SeLECTS had increased diffusivity (AD p = 0.007, RD p = 0.006, MD p = 0.016), with no difference in fractional anisotropy (p = 0.22). However, linear tests comparing white matter microstructure in areas constituting language networks and language performance did not withstand correction for multiple comparisons in this sample, although a trend was seen between FA in the arcuate fasciculus and verbal category fluency (p = 0.047) and the expressive one-word picture vocabulary test (p = 0.036).

CONCLUSION

We found impaired language development in children with SeLECTS, particularly in those with active SeLECTS, as well as abnormalities in the superficial centrotemporal white matter as well as the fibers connecting these regions, the arcuate fasciculus. Although relationships between language performance and white matter abnormalities did not pass correction for multiple comparisons, taken together, these results provide evidence of atypical white matter maturation in fibers involved in language processing, which may contribute to the aspects of language function that are commonly affected by the disorder.

A unified global tractography framework for automatic visual pathway reconstruction

The human visual pathway starts from the retina, passes through the retinogeniculate visual pathway, the optic radiation, and finally connects to the primary visual cortex. Diffusion MRI tractography is the only technology that can noninvasively reconstruct the visual pathway. However, complete and accurate visual pathway reconstruction is challenging because of the skull base environment and complex fiber geometries. Specifically, the optic nerve within the complex skull base environment can cause abnormal diffusion signals. The crossing and fanning fibers at the optic chiasm, and a sharp turn of Meyer's loop at the optic radiation, contribute to complex fiber geometries of the visual pathway. A fiber trajectory distribution (FTD) function-based tractography method of our previous work and several high sensitivity tractography methods can reveal these complex fiber geometries, but are accompanied by false-positive fibers. Thus, the related studies of the visual pathway mostly applied the expert region of interest selection strategy. However, interobserver variability is an issue in reconstructing an accurate visual pathway. In this paper, we propose a unified global tractography framework to automatically reconstruct the visual pathway. We first extend the FTD function to a high-order streamline differential equation for global trajectory estimation. At the global level, the tractography process is simplified as the estimation of global trajectory distribution coefficients by minimizing the cost between trajectory distribution and the selected directions under the prior guidance by introducing the tractography template as anatomic priors. Furthermore, we use a deep learning-based method and tractography template prior information to automatically generate the mask for tractography. The experimental results demonstrate that our proposed method can successfully reconstruct the visual pathway with high accuracy.

An atlas of white matter anatomy, its variability, and reproducibility based on constrained spherical deconvolution of diffusion MRI

Virtual dissection of white matter (WM) using diffusion MRI tractography is confounded by its poor reproducibility. Despite the increased adoption of advanced reconstruction models, early region-of-interest driven protocols based on diffusion tensor imaging (DTI) remain the dominant reference for virtual dissection protocols. Here we bridge this gap by providing a comprehensive description of typical WM anatomy reconstructed using a reproducible automated subject-specific parcellation-based approach based on probabilistic constrained-spherical deconvolution (CSD) tractography. We complement this with a WM template in MNI space comprising 68 bundles, including all associated anatomical tract selection labels and associated automated workflows. Additionally, we demonstrate bundle inter- and intra-subject variability using 40 (20 test-retest) datasets from the human connectome project (HCP) and 5 sessions with varying b-values and number of b-shells from the single-subject Multiple Acquisitions for Standardization of Structural Imaging Validation and Evaluation (MASSIVE) dataset. The most reliably reconstructed bundles were the whole pyramidal tracts, primary corticospinal tracts, whole superior longitudinal fasciculi, frontal, parietal and occipital segments of the corpus callosum and middle cerebellar peduncles. More variability was found in less dense bundles, e.g., the fornix, dentato-rubro-thalamic tract (DRTT), and premotor pyramidal tract. Using the DRTT as an example, we show that this variability can be reduced by using a higher number of seeding attempts. Overall inter-session similarity was high for HCP test-retest data (median weighted-dice = 0.963, stdev = 0.201 and IQR = 0.099). Compared to the HCP-template bundles there was a high level of agreement for the HCP test-retest data (median weighted-dice = 0.747, stdev = 0.220 and IQR = 0.277) and for the MASSIVE data (median weighted-dice = 0.767, stdev = 0.255 and IQR = 0.338). In summary, this WM atlas provides an overview of the capabilities and limitations of automated subject-specific probabilistic CSD tractography for mapping white matter fasciculi in healthy adults. It will be most useful in applications requiring a reproducible parcellation-based dissection protocol, and as an educational resource for applied neuroimaging and clinical professionals.

Neonatal brain injury influences structural connectivity and childhood functional outcomes

Neonatal brain injury may impact brain development and lead to lifelong functional impairments. Hypoxic-ischemic encephalopathy (HIE) and congenital heart disease (CHD) are two common causes of neonatal brain injury differing in timing and mechanism. Maturation of whole-brain neural networks can be quantified during development using diffusion magnetic resonance imaging (dMRI) in combination with graph theory metrics. DMRI of 35 subjects with CHD and 62 subjects with HIE were compared to understand differences in the effects of HIE and CHD on the development of network topological parameters and functional outcomes. CHD newborns had worse 12–18 month language (P<0.01) and 30 month cognitive (P<0.01), language (P = 0.05), motor outcomes (P = 0.01). Global efficiency, a metric of brain integration, was lower in CHD (P = 0.03) than in HIE, but transitivity, modularity and small-worldness were similar. After controlling for clinical factors known to affect neurodevelopmental outcomes, we observed that global efficiency was highly associated with 30 month motor outcomes (P = 0.02) in both groups. To explore neural correlates of adverse language outcomes in CHD, we used hypothesis-based and data-driven approaches to identify pathways with altered structural connectivity. We found that connectivity strength in the superior longitudinal fasciculus (SLF) tract 2 was inversely associated with expressive language. After false discovery rate correction, a whole connectome edge analysis identified 18 pathways that were hypoconnected in the CHD cohort as compared to HIE. In sum, our study shows that neonatal structural connectivity predicts early motor development after HIE or in subjects with CHD, and regional SLF connectivity is associated with language outcomes. Further research is needed to determine if and how brain networks change over time and whether those changes represent recovery or ongoing dysfunction. This knowledge will directly inform strategies to optimize neurologic functional outcomes after neonatal brain injury.

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.

Broca's area and the search for anatomical asymmetry: commentary and perspectives

We present a brief commentary on the field's search for an anatomical asymmetry between Broca's area and its homologue in the non-dominant hemisphere, focusing on a selection of studies, including research from the last decade. We demonstrate that, several years after the influential review of Keller and colleagues from 2009, and despite recent advances in neuroimaging, the existence of a structural asymmetry of Broca's area is still controversial. This is especially the case for studies of the macroanatomy of this region. We point out the inconsistencies in methodology across studies that could account for the discrepancy in results. Investigations of the microstructure of Broca's area show a trend of a leftward asymmetry, but it is still unclear how these results relate to language dominance. We suggest that it may be necessary to combine multiple metrics in a systematic manner to find robust asymmetries and to expand the regional scope of structural investigations. Finally, based on the current state of the literature, we should not rule out the possibility that language dominance may simply not be reflected in local anatomical differences in the brain.

Structural perisylvian asymmetry in naturally occurring atypical language dominance

Functional and anatomical hemispheric asymmetries abound in the neural language system, yet the relationship between them remains elusive. One attractive proposal is that structural interhemispheric differences reflect or even drive functional language laterality. However, studies on structure-function couplings either find that left and right language dominant individuals display similar leftward structural asymmetry or yield inconsistent results. The current study aimed to replicate and extend prior work by comparing structural asymmetries between neurologically healthy left-handers with right hemispheric language dominance (N = 24) and typically lateralized left-handed controls (N = 39). Based on structural MRI data, anatomical measures of six 'language-related' perisylvian structures were derived, including the surface area of five gray matter regions with known language functions and the FDC (combined fiber density and fiber-bundle cross-sectional area) of the arcuate fasciculus. Only the surface area of the pars triangularis and the anterior insula differed significantly between participant groups, being on average leftward asymmetric in those with typical dominance, but right lateralized in volunteers with atypical language specialization. However, these findings did not survive multiple testing correction and the asymmetry of these structures demonstrated much inter-individual variability in either subgroup. By integrating our findings with those reported previously we conclude that while some perisylvian anatomical asymmetries may differ subtly between typical and atypical speech dominants at the group level, they serve as poor participant-specific predictors of hemispheric language specialization.

The Microstructural Plasticity of the Arcuate Fasciculus Undergirds Improved Speech in Noise Perception in Musicians

Musical training is thought to be related to improved language skills, for example, understanding speech in background noise. Although studies have found that musicians and nonmusicians differed in morphology of bilateral arcuate fasciculus (AF), none has associated such white matter features with speech-in-noise (SIN) perception. Here, we tested both SIN and the diffusivity of bilateral AF segments in musicians and nonmusicians using diffusion tensor imaging. Compared with nonmusicians, musicians had higher fractional anisotropy (FA) in the right direct AF and lower radial diffusivity in the left anterior AF, which correlated with SIN performance. The FA-based laterality index showed stronger right lateralization of the direct AF and stronger left lateralization of the posterior AF in musicians than nonmusicians, with the posterior AF laterality predicting SIN accuracy. Furthermore, hemodynamic activity in right superior temporal gyrus obtained during a SIN task played a full mediation role in explaining the contribution of the right direct AF diffusivity on SIN performance, which therefore links training-related white matter plasticity, brain hemodynamics, and speech perception ability. Our findings provide direct evidence that differential microstructural plasticity of bilateral AF segments may serve as a neural foundation of the cross-domain transfer effect of musical experience to speech perception amid competing noise.

Negative polarity in quantifiers evokes greater activation in language-related regions compared to negative polarity in adjectives

The processing of sentences with negative quantifiers (e.g., few) is more costly than of sentences that contain their positive counterparts (e.g., many). While this polarity effect is robust and reliably replicable, its neurological bases are not well understood. In this study, we use functional magnetic resonance imaging (fMRI) paradigm for 30 participants to assess the polarity effect in sentences with polar quantifiers, and compare it with the polarity effect of polar adjectives. Both in quantifiers and in adjectives, the polarity effect manifests in the anterior insula bilaterally. The polarity effect in quantifiers, however, shows greater activation in the left hemisphere than it does for adjectives. In particular, left inferior frontal gyrus (IFG) and left superior temporal sulcus (STS) show increased activation for polarity in quantifiers than in adjectives, which is the evidence for the specific involvement of the language network in this type of polarity processing. Using the polarity effect in adjectives as a control, we provide further evidence for the linguistic complexity that negative quantifiers implicate on processing.

Fibre-specific laterality of white matter in left and right language dominant people

Language is the most commonly described lateralised cognitive function, relying more on the left hemisphere compared to the right hemisphere in over 90% of the population. Most research examining the structure-function relationship of language lateralisation only included people showing a left language hemisphere dominance. In this work, we applied a state-of-the-art "fixel-based" analysis approach, allowing statistical analysis of white matter micro- and macrostructure on a fibre-specific level in a sample of participants with left and right language dominance (LLD and RLD). Both groups showed a similar extensive pattern of white matter lateralisation including a comparable leftwards lateralisation of the arcuate fasciculus, regardless of their functional language lateralisation. These results suggest that lateralisation of language functioning and the arcuate fasciculus are driven by independent biases. Finally, a significant group difference of lateralisation was detected in the forceps minor, with a leftwards lateralisation in LLD and rightwards lateralisation for the RLD group.

Converging Evidence for Differential Specialization and Plasticity of Language Systems

Functional specialization and plasticity are fundamental organizing principles of the brain. Since the mid-1800s, certain cognitive functions have been known to be lateralized, but the provenance and flexibility of hemispheric specialization remain open questions. Language is a uniquely human phenomenon that requires a delicate balance between neural specialization and plasticity, and language learning offers the perfect window to study these principles in the human brain. In the current study, we conducted two separate functional MRI experiments with language learners (male and female), one cross-sectional and one longitudinal, involving distinct populations and languages, and examined hemispheric lateralization and learning-dependent plasticity of the following three language systems: reading, speech comprehension, and verbal production. A multipronged analytic approach revealed a highly consistent pattern of results across the two experiments, showing (1) that in both native and non-native languages, while language production was left lateralized, lateralization for language comprehension was highly variable across individuals; and (2) that with increasing non-native language proficiency, reading and speech comprehension displayed substantial changes in hemispheric dominance, with languages tending to lateralize to opposite hemispheres, while production showed negligible change and remained left lateralized. These convergent results shed light on the long-standing debate of neural organization of language by establishing robust principles of lateralization and plasticity of the main language systems. Findings further suggest involvement of the sensorimotor systems in language lateralization and its plasticity.SIGNIFICANCE STATEMENT The human brain exhibits a remarkable ability to support a vast variety of languages that may be acquired at different points in the life span. Language is a complex construct involving linguistic as well as visual, auditory, and motor processes. Using functional MRI, we examined hemispheric specialization and learning-dependent plasticity of three language systems-reading, speech comprehension, and verbal production-in cross-sectional and longitudinal experiments in language learners. A multipronged analytic approach revealed converging evidence for striking differences in hemispheric specialization and plasticity among the language systems. The results have major theoretical and practical implications for our understanding of fundamental principles of neural organization of language, language testing and recovery in patients, and language learning in healthy populations.

A unified neurocomputational bilateral model of spoken language production in healthy participants and recovery in poststroke aphasia

Studies of healthy and impaired language have generated many verbally described hypotheses. While these verbal descriptions have advanced our understanding of language processing, some explanations are mutually incompatible, and it is unclear how they work mechanistically. We constructed a neurocomputational bilateral model of spoken language production to simulate a range of phenomena in healthy participants and patients with aphasia simultaneously, including language lateralization, impaired performance after left but not right damage, and hemispheric involvement in plasticity-dependent recovery. The model demonstrates how seemly contradictory findings can be simulated within a single framework. This provides a coherent mechanistic account of language lateralization and recovery from poststroke aphasia.

Understanding the processes underlying normal, impaired, and recovered language performance has been a long-standing goal for cognitive and clinical neuroscience. Many verbally described hypotheses about language lateralization and recovery have been generated. However, they have not been considered within a single, unified, and implemented computational framework, and the literatures on healthy participants and patients are largely separated. These investigations also span different types of data, including behavioral results and functional MRI brain activations, which augment the challenge for any unified theory. Consequently, many key issues, apparent contradictions, and puzzles remain to be solved. We developed a neurocomputational, bilateral pathway model of spoken language production, designed to provide a unified framework to simulate different types of data from healthy participants and aphasic patients. The model encapsulates key computational principles (differential computational capacity, emergent division of labor across pathways, experience-dependent plasticity-related recovery) and provides an explanation for the bilateral yet asymmetric lateralization of language in healthy participants, chronic aphasia after left rather than right hemisphere lesions, and the basis of partial recovery in patients. The model provides a formal basis for understanding the relationship between behavioral performance and brain activation. The unified model is consistent with the degeneracy and variable neurodisplacement theories of language recovery, and adds computational insights to these hypotheses regarding the neural machinery underlying language processing and plasticity-related recovery following damage.

Structural characterization of the Extended Frontal Aslant Tract trajectory: A ML-validated laterality study in 3T and 7T

The Extended Frontal Aslant Tract (exFAT) is a recently described tractography-based extension of the Frontal Aslant Tract connecting Broca's territory to both supplementary and pre-supplementary motor areas, and more anterior prefrontal regions. In this study, we aim to characterize the microstructural properties of the exFAT trajectories as a means to perform a laterality analysis to detect interhemispheric structural differences along the tracts using the Human Connectome Project (HCP) dataset. To that end, the bilateral exFAT was reconstructed for 3T and 7T HCP acquisitions in 120 randomly selected subjects. As a complementary exploration of the exFAT anatomy, we performed a white matter dissection of the exFAT trajectory of two ex-vivo left hemispheres that provide a qualitative assessment of the tract profiles. We assessed the lateralization structural differences in the exFAT by performing: (i) a laterality comparison between the mean microstructural diffusion-derived parameters for the exFAT trajectories, (ii) a laterality comparison between the tract profiles obtained by applying the Automated Fiber Quantification (AFQ) algorithm, and (iii) a cross-validated Machine Learning (ML) classifier analysis using single and combined tract profiles parameters for single-subject classification. The mean microstructural diffusion-derived parameter comparison showed statistically significant differences in mean FA values between left and right exFATs in the 3T sample. The diffusion parameters studied with the AFQ technique suggest that the inferiormost half of the exFAT trajectory has a hemispheric-dependent fingerprint of microstructural properties, with an increased measure of tissue hindrance in the orthogonal plane and a decreased measure of orientational dispersion along the main tract direction in the left exFAT compared to the right exFAT. The classification accuracy of the ML models showed a high agreement with the magnitude of those differences.

Converging Evidence for Differential Specialization and Plasticity of Language Systems

Functional specialization and plasticity are fundamental organizing principles of the brain. Since the mid-1800s, certain cognitive functions have been known to be lateralized, but the provenance and flexibility of hemispheric specialization remain open questions. Language is a uniquely human phenomenon that requires a delicate balance between neural specialization and plasticity, and language learning offers the perfect window to study these principles in the human brain. In the current study, we conducted two separate functional MRI experiments with language learners (male and female), one cross-sectional and one longitudinal, involving distinct populations and languages, and examined hemispheric lateralization and learning-dependent plasticity of the following three language systems: reading, speech comprehension, and verbal production. A multipronged analytic approach revealed a highly consistent pattern of results across the two experiments, showing (1) that in both native and non-native languages, while language production was left lateralized, lateralization for language comprehension was highly variable across individuals; and (2) that with increasing non-native language proficiency, reading and speech comprehension displayed substantial changes in hemispheric dominance, with languages tending to lateralize to opposite hemispheres, while production showed negligible change and remained left lateralized. These convergent results shed light on the long-standing debate of neural organization of language by establishing robust principles of lateralization and plasticity of the main language systems. Findings further suggest involvement of the sensorimotor systems in language lateralization and its plasticity.

SIGNIFICANCE STATEMENT The human brain exhibits a remarkable ability to support a vast variety of languages that may be acquired at different points in the life span. Language is a complex construct involving linguistic as well as visual, auditory, and motor processes. Using functional MRI, we examined hemispheric specialization and learning-dependent plasticity of three language systems—reading, speech comprehension, and verbal production—in cross-sectional and longitudinal experiments in language learners. A multipronged analytic approach revealed converging evidence for striking differences in hemispheric specialization and plasticity among the language systems. The results have major theoretical and practical implications for our understanding of fundamental principles of neural organization of language, language testing and recovery in patients, and language learning in healthy populations.

Dissociating the white matter tracts connecting the temporo-parietal cortical region with frontal cortex using diffusion tractography

Three major white matter pathways connect the posterior temporal region and the adjacent inferior parietal lobule with the lateral frontal cortex: the arcuate fasciculus (AF), and the second and third branches of the superior longitudinal fasciculus (SLF II and SLF III). These pathways are found also in nonhuman primate brains where they play specific roles in auditory and spatial processing. The precise origin, course, and termination of these pathways has been examined in invasive tract tracing studies in macaque monkeys. Here we use this prior knowledge to improve dissections of these pathways in vivo in the human brain using diffusion Magnetic Resonance Imaging (MRI) tractography. In this study, the AF, originating from the posterior temporal cortex, has been successfully separated from the SLF II and SLF III tracts originating from the angular and supramarginal gyri of the inferior parietal lobule, respectively. The latter two pathways, i.e. SLF II and SLF III, have also been clearly separated from each other. Furthermore, we report for the first time in the human brain the dorsal branch of the AF that targets the posterior dorsolateral frontal region. These improved dissection protocols provide a solid basis for exploring the respective functional roles of these major fasciculi.

Evaluating arcuate fasciculus laterality measurements across dataset and tractography pipelines

The arcuate fasciculi are white-matter pathways that connect frontal and temporal lobes in each hemisphere. The arcuate plays a key role in the language network and is believed to be left-lateralized, in line with left hemisphere dominance for language. Measuring the arcuate in vivo requires diffusion magnetic resonance imaging-based tractography, but asymmetry of the in vivo arcuate is not always reliably detected in previous studies. It is unknown how the choice of tractography algorithm, with each method's freedoms, constraints, and vulnerabilities to false-positive and -negative errors, impacts findings of arcuate asymmetry. Here, we identify the arcuate in two independent datasets using a number of tractography strategies and methodological constraints, and assess their impact on estimates of arcuate laterality. We test three tractography methods: a deterministic, a probabilistic, and a tractography-evaluation (LiFE) algorithm. We extract the arcuate from the whole-brain tractogram, and compare it to an arcuate bundle constrained even further by selecting only those streamlines that connect to anatomically relevant cortical regions. We test arcuate macrostructure laterality, and also evaluate microstructure profiles for properties such as fractional anisotropy and quantitative R1. We find that both tractography choice and implementing the cortical constraints substantially impact estimates of all indices of arcuate laterality. Together, these results emphasize the effect of the tractography pipeline on estimates of arcuate laterality in both macrostructure and microstructure.