Publications

Abstract

Language is supported by a distributed network of brain regions with a particular contribution from the left hemisphere. A multi-level understanding of this network requires studying the genetic architecture of its functional connectivity and hemispheric asymmetry. We used resting state functional imaging data from 29,681 participants from the UK Biobank to measure functional connectivity between 18 left-hemisphere regions implicated in multimodal sentence-level processing, as well as their homotopic regions in the right-hemisphere, and interhemispheric connections. Multivariate genome-wide association analysis of this total network, based on common genetic variants (with population frequencies above 1%), identified 14 loci associated with network functional connectivity. Three of these loci were also associated with hemispheric differences of intrahemispheric connectivity. Polygenic dispositions to lower language-related abilities, dyslexia and left-handedness were associated with generally reduced leftward asymmetry of functional connectivity, but with some trait- and connection-specific exceptions. Exome-wide association analysis based on rare, protein-altering variants (frequencies < 1%) suggested 7 additional genes. These findings shed new light on the genetic contributions to language network connectivity and its asymmetry based on both common and rare genetic variants, and reveal genetic links to language-related traits and hemispheric dominance for hand preference.

Abstract

The aesthetic values that individuals place on visual images are formed and shaped over a lifetime. However, whether the formation of visual aesthetic value is solely influenced by environmental exposure is still a matter of debate. Here, we considered differences in aesthetic value emerging across three visual domains: abstract images, scenes, and faces. We examined variability in two major dimensions of ordinary aesthetic experiences: taste-typicality and evaluation-bias. We build on two samples from the Australian Twin Registry where 1547 and 1231 monozygotic and dizygotic twins originally rated visual images belonging to the three domains. Genetic influences explained 26% to 41% of the variance in taste-typicality and evaluation-bias. Multivariate analyses showed that genetic effects were partially shared across visual domains. Results indicate that the heritability of major dimensions of aesthetic evaluations is comparable to that of other complex social traits, albeit lower than for other complex cognitive traits. The exception was taste-typicality for abstract images, for which we found only shared and unique environmental influences. Our study reveals that diverse sources of genetic and environmental variation influence the formation of aesthetic value across distinct visual domains and provides improved metrics to assess inter-individual differences in aesthetic value.

Abstract

Background

The 1q21.1 distal and 15q11.2 BP1-BP2 CNVs exhibit regional and global brain differences compared to non-carriers. However, interpreting regional differences is challenging if a global difference drives the regional brain differences. Intra-individual variability measures can be used to test for regional differences beyond global differences in brain structure.

Methods

Magnetic resonance imaging data were used to obtain regional brain values for 1q21.1 distal deletion (n=30) and duplication (n=27), and 15q11.2 BP1-BP2 deletion (n=170) and duplication (n=243) carriers and matched non-carriers (n=2,350). Regional intra-deviation (RID) scores i.e., the standardized difference between an individual’s regional difference and global difference, were used to test for regional differences that diverge from the global difference.

Results

For the 1q21.1 distal deletion carriers, cortical surface area for regions in the medial visual cortex, posterior cingulate and temporal pole differed less, and regions in the prefrontal and superior temporal cortex differed more than the global difference in cortical surface area. For the 15q11.2 BP1-BP2 deletion carriers, cortical thickness in regions in the medial visual cortex, auditory cortex and temporal pole differed less, and the prefrontal and somatosensory cortex differed more than the global difference in cortical thickness.

Conclusion

We find evidence for regional effects beyond differences in global brain measures in 1q21.1 distal and 15q11.2 BP1-BP2 CNVs. The results provide new insight into brain profiling of the 1q21.1 distal and 15q11.2 BP1-BP2 CNVs, with the potential to increase our understanding of mechanisms involved in altered neurodevelopment.

Abstract

Structural neuroimaging data have been used to compute an estimate of the biological age of the brain (brain-age) which has been associated with other biologically and behaviorally meaningful measures of brain development and aging. The ongoing research interest in brain-age has highlighted the need for robust and publicly available brain-age models pre-trained on data from large samples of healthy individuals. To address this need we have previously released a developmental brain-age model. Here we expand this work to develop, empirically validate, and disseminate a pre-trained brain-age model to cover most of the human lifespan. To achieve this, we selected the best-performing model after systematically examining the impact of seven site harmonization strategies, age range, and sample size on brain-age prediction in a discovery sample of brain morphometric measures from 35,683 healthy individuals (age range: 5–90 years; 53.59% female). The pre-trained models were tested for cross-dataset generalizability in an independent sample comprising 2101 healthy individuals (age range: 8–80 years; 55.35% female) and for longitudinal consistency in a further sample comprising 377 healthy individuals (age range: 9–25 years; 49.87% female). This empirical examination yielded the following findings: (1) the accuracy of age prediction from morphometry data was higher when no site harmonization was applied; (2) dividing the discovery sample into two age-bins (5–40 and 40–90 years) provided a better balance between model accuracy and explained age variance than other alternatives; (3) model accuracy for brain-age prediction plateaued at a sample size exceeding 1600 participants. These findings have been incorporated into CentileBrain (https://centilebrain.org/#/brainAGE2), an open-science, web-based platform for individualized neuroimaging metrics.

Abstract

SATB2-associated syndrome (SAS) is caused by pathogenic variants in SATB2, which encodes an evolutionarily conserved transcription factor. Despite the broad range of phenotypic manifestations and variable severity related to this syndrome, haploinsufficiency has been assumed to be the primary molecular explanation.

In this study, we describe eight individuals with SATB2 variants that affect p.Gly392 (four women, age range 2–16 years; p.Gly392Arg, p.Gly392Glu and p.Gly392Val). Of these, individuals with p.Gly392Arg substitutions were found to have more severe neurodevelopmental phenotypes based on an established rubric scoring system when compared with individuals with p.Gly392Glu, p.Gly392Val and other previously reported causative SATB2 missense variants. Consistent with the observations at the phenotypic level, using human cell-based and model organism functional data, we documented that while all three described p.Gly392 variants affect the same residue and seem to all have a partial loss-of-function effect, some effects on SATB2 protein function appear to be variant-specific. Our results indicate that genotype–phenotype correlations in SAS are more complex than originally thought, and variant-specific genotype–phenotype correlations are needed.

Abstract

Genetic investigations of people with speech and language disorders can provide windows into key aspects of human biology. Most genomic research into impaired speech development has so far focused on childhood apraxia of speech (CAS), a rare neurodevelopmental disorder characterized by difficulties with coordinating rapid fine motor sequences that underlie proficient speech. In 2001, pathogenic variants of FOXP2 provided the first molecular genetic accounts of CAS aetiology. Since then, disruptions in several other genes have been implicated in CAS, with a substantial proportion of cases being explained by high-penetrance variants. However, the genetic architecture underlying other speech-related disorders remains less well understood. Thus, in the present study, we used systematic DNA sequencing methods to investigate idiopathic speech delay, as characterized by delayed speech development in the absence of a motor speech diagnosis (such as CAS), a language/reading disorder, or intellectual disability. We performed genome sequencing in a cohort of 23 children with a rigorous diagnosis of idiopathic speech delay. For roughly half of the sample (ten probands), sufficient DNA was also available for genome sequencing in both parents, allowing discovery of de novo variants. In the thirteen singleton probands, we focused on identifying loss-of-function and likely damaging missense variants in genes intolerant to such mutations. We found that one speech delay proband carried a pathogenic frameshift deletion in SETD1A, a gene previously implicated in a broader variable monogenic syndrome characterized by global developmental problems including delayed speech and/or language development, mild intellectual disability, facial dysmorphisms, and behavioural and psychiatric symptoms. Of note, pathogenic SETD1A variants have been independently reported in children with CAS in two separate studies. In other probands in our speech delay cohort, likely pathogenic missense variants were identified affecting highly conserved amino acids in key functional domains of SPTBN1 and ARF3. Overall, this study expands the phenotype spectrum associated with pathogenic SETD1A variants, to also include idiopathic speech delay without CAS or intellectual disability, and suggests additional novel potential candidate genes that may harbour high-penetrance variants that can disrupt speech development.

Abstract

Purpose:
Stuttering is a speech condition that can have a major impact on a person's quality of life. This descriptive study aimed to identify subgroups of people who stutter (PWS) based on stuttering burden and to investigate differences between these subgroups on psychosocial aspects of life.

Method:
The study included 618 adult participants who stutter. They completed a detailed survey examining stuttering symptomatology, impact of stuttering on anxiety, education and employment, experience of stuttering, and levels of depression, anxiety, and stress. A two-step cluster analytic procedure was performed to identify subgroups of PWS, based on self-report of stuttering frequency, severity, affect, and anxiety, four measures that together inform about stuttering burden.

Results:
We identified a high- (n = 230) and a low-burden subgroup (n = 372). The high-burden subgroup reported a significantly higher impact of stuttering on education and employment, and higher levels of general depression, anxiety, stress, and overall impact of stuttering. These participants also reported that they trialed more different stuttering therapies than those with lower burden.

Conclusions:
Our results emphasize the need to be attentive to the diverse experiences and needs of PWS, rather than treating them as a homogeneous group. Our findings also stress the importance of personalized therapeutic strategies for individuals with stuttering, considering all aspects that could influence their stuttering burden. People with high-burden stuttering might, for example, have a higher need for psychological therapy to reduce stuttering-related anxiety. People with less emotional reactions but severe speech distortions may also have a moderate to high burden, but they may have a higher need for speech techniques to communicate with more ease. Future research should give more insights into the therapeutic needs of people highly burdened by their stuttering.

Abstract

The value of normative models in research and clinical practice relies on their robustness and a systematic comparison of different modelling algorithms and parameters; however, this has not been done to date. We aimed to identify the optimal approach for normative modelling of brain morphometric data through systematic empirical benchmarking, by quantifying the accuracy of different algorithms and identifying parameters that optimised model performance. We developed this framework with regional morphometric data from 37 407 healthy individuals (53% female and 47% male; aged 3–90 years) from 87 datasets from Europe, Australia, the USA, South Africa, and east Asia following a comparative evaluation of eight algorithms and multiple covariate combinations pertaining to image acquisition and quality, parcellation software versions, global neuroimaging measures, and longitudinal stability. The multivariate fractional polynomial regression (MFPR) emerged as the preferred algorithm, optimised with non-linear polynomials for age and linear effects of global measures as covariates. The MFPR models showed excellent accuracy across the lifespan and within distinct age-bins and longitudinal stability over a 2-year period. The performance of all MFPR models plateaued at sample sizes exceeding 3000 study participants. This model can inform about the biological and behavioural implications of deviations from typical age-related neuroanatomical changes and support future study designs. The model and scripts described here are freely available through CentileBrain.

Abstract

Subcortical brain structures are involved in developmental, psychiatric and neurological disorders. Here we performed genome-wide association studies meta-analyses of intracranial and nine subcortical brain volumes (brainstem, caudate nucleus, putamen, hippocampus, globus pallidus, thalamus, nucleus accumbens, amygdala and the ventral diencephalon) in 74,898 participants of European ancestry. We identified 254 independent loci associated with these brain volumes, explaining up to 35% of phenotypic variance. We observed gene expression in specific neural cell types across differentiation time points, including genes involved in intracellular signaling and brain aging-related processes. Polygenic scores for brain volumes showed predictive ability when applied to individuals of diverse ancestries. We observed causal genetic effects of brain volumes with Parkinson’s disease and attention-deficit/hyperactivity disorder. Findings implicate specific gene expression patterns in brain development and genetic variants in comorbid neuropsychiatric disorders, which could point to a brain substrate and region of action for risk genes implicated in brain diseases.

Abstract

* Ole Goltermann and Gökberk Alagöz contributed equally.
Primate brain evolution has involved prominent expansions of the cerebral cortex, with largest effects observed in the human lineage. Such expansions were accompanied by fine-grained anatomical alterations, including increased cortical folding. However, the molecular bases of evolutionary alterations in human sulcal organization are not yet well understood. Here, we integrated data from recently completed large-scale neuroimaging genetic analyses with annotations of the human genome relevant to various periods and events in our evolutionary history. These analyses identified single-nucleotide polymorphism (SNP) heritability enrichments in fetal brain human-gained enhancer (HGE) elements for a number of sulcal structures, including the central sulcus, which is implicated in human hand dexterity. We zeroed in on a genomic region that harbors DNA variants associated with left central sulcus shape, an HGE element, and genetic loci involved in neurogenesis including ZIC4, to illustrate the value of this approach for probing the complex factors contributing to human sulcal evolution.

Abstract

Rare disruptions of the transcription factor FOXP1 are implicated in a human neurodevelopmental disorder characterized by autism and/or intellectual disability with prominent problems in speech and language abilities. Avian orthologues of this transcription factor are evolutionarily conserved and highly expressed in specific regions of songbird brains, including areas associated with vocal production learning and auditory perception. Here, we investigated possible contributions of FoxP1 to song discrimination and auditory perception in juvenile and adult female zebra finches. They received lentiviral knockdowns of FoxP1 in one of two brain areas involved in auditory stimulus processing, HVC (proper name) or CMM (caudomedial mesopallium). Ninety-six females, distributed over different experimental and control groups were trained to discriminate between two stimulus songs in an operant Go/Nogo paradigm and subsequently tested with an array of stimuli. This made it possible to assess how well they recognized and categorized altered versions of training stimuli and whether localized FoxP1 knockdowns affected the role of different features during discrimination and categorization of song. Although FoxP1 expression was significantly reduced by the knockdowns, neither discrimination of the stimulus songs nor categorization of songs modified in pitch, sequential order of syllables or by reversed playback were affected. Subsequently, we analyzed the full dataset to assess the impact of the different stimulus manipulations for cue weighing in song discrimination. Our findings show that zebra finches rely on multiple parameters for song discrimination, but with relatively more prominent roles for spectral parameters and syllable sequencing as cues for song discrimination.

NEW & NOTEWORTHY In humans, mutations of the transcription factor FoxP1 are implicated in speech and language problems. In songbirds, FoxP1 has been linked to male song learning and female preference strength. We found that FoxP1 knockdowns in female HVC and caudomedial mesopallium (CMM) did not alter song discrimination or categorization based on spectral and temporal information. However, this large dataset allowed to validate different cue weights for spectral over temporal information for song recognition.

Abstract

Purpose:
To our knowledge, there are no data examining the agreement between self-reported and clinician-rated stuttering severity. In the era of big data, self-reported ratings have great potential utility for large-scale data collection, where cost and time preclude in-depth assessment by a clinician. Equally, there is increasing emphasis on the need to recognize an individual's experience of their own condition. Here, we examined the agreement between self-reported stuttering severity compared to clinician ratings during a speech assessment. As a secondary objective, we determined whether self-reported stuttering severity correlated with an individual's subjective impact of stuttering.

Method:
Speech-language pathologists conducted face-to-face speech assessments with 195 participants (137 males) aged 5–84 years, recruited from a cohort of people with self-reported stuttering. Stuttering severity was rated on a 10-point scale by the participant and by two speech-language pathologists. Participants also completed the Overall Assessment of the Subjective Experience of Stuttering (OASES). Clinician and participant ratings were compared. The association between stuttering severity and the OASES scores was examined.

Results:
There was a strong positive correlation between speech-language pathologist and participant-reported ratings of stuttering severity. Participant-reported stuttering severity correlated weakly with the four OASES domains and with the OASES overall impact score.

Conclusions:
Participants were able to accurately rate their stuttering severity during a speech assessment using a simple one-item question. This finding indicates that self-report stuttering severity is a suitable method for large-scale data collection. Findings also support the collection of self-report subjective experience data using questionnaires, such as the OASES, which add vital information about the participants' experience of stuttering that is not captured by overt speech severity ratings alone.

Abstract

Common genetic variation has been associated with multiple symptoms in Autism Spectrum Disorder (ASD). However, our knowledge of shared genetic factor structures contributing to this highly heterogeneous neurodevelopmental condition is limited. Here, we developed a structural equation modelling framework to directly model genome-wide covariance across core and non-core ASD phenotypes, studying autistic individuals of European descent using a case-only design. We identified three independent genetic factors most strongly linked to language/cognition, behaviour and motor development, respectively, when studying a population-representative sample (N=5,331). These analyses revealed novel associations. For example, developmental delay in acquiring personal-social skills was inversely related to language, while developmental motor delay was linked to self-injurious behaviour. We largely confirmed the three-factorial structure in independent ASD-simplex families (N=1,946), but uncovered simplex-specific genetic overlap between behaviour and language phenotypes. Thus, the common genetic architecture in ASD is multi-dimensional and contributes, in combination with ascertainment-specific patterns, to phenotypic heterogeneity.

Abstract

Only a small number of studies have assessed structural differences between the two hemispheres during childhood and adolescence. However, the existing findings lack consistency or are restricted to a particular brain region, a specific brain feature, or a relatively narrow age range. Here, we investigated associations between brain asymmetry and age as well as sex in one of the largest pediatric samples to date (n = 4265), aged 1–18 years, scanned at 69 sites participating in the ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) consortium. Our study revealed that significant brain asymmetries already exist in childhood, but their magnitude and direction depend on the brain region examined and the morphometric measurement used (cortical volume or thickness, regional surface area, or subcortical volume). With respect to effects of age, some asymmetries became weaker over time while others became stronger; sometimes they even reversed direction. With respect to sex differences, the total number of regions exhibiting significant asymmetries was larger in females than in males, while the total number of measurements indicating significant asymmetries was larger in males (as we obtained more than one measurement per cortical region). The magnitude of the significant asymmetries was also greater in males. However, effect sizes for both age effects and sex differences were small. Taken together, these findings suggest that cerebral asymmetries are an inherent organizational pattern of the brain that manifests early in life. Overall, brain asymmetry appears to be relatively stable throughout childhood and adolescence, with some differential effects in males and females.

Abstract

Purpose

The aim of this study is to establish which specific cognitive abilities are phenotypically related to reading skill in adolescence and determine whether this phenotypic correlation is explained by polygenetic overlap.

Method

In an Australian population sample of twins and non-twin siblings of European ancestry (734 ≤ N ≤ 1542 [50.7% < F < 66%], mean age = 16.7, range = 11–28 years) from the Brisbane Adolescent Twin Study, mixed-effects models were used to test the association between a dyslexia polygenic score (based on genome-wide association results from a study of 51,800 dyslexics versus >1 million controls) and quantitative cognitive measures. The variance in the cognitive measure explained by the polygenic score was compared to that explained by a reading difficulties phenotype (scores that were lower than 1.5 SD below the mean reading skill) to derive the proportion of the association due to genetic influences.

Results

The strongest phenotypic correlations were between poor reading and verbal tests (R2 up to 6.2%); visuo-spatial working memory was the only measure that did not show association with poor reading. Dyslexia polygenic scores could completely explain the phenotypic covariance between poor reading and most working memory tasks and were most predictive of performance on a test of arithmetic (R2=2.9%).

Conclusion

Shared genetic pathways are thus highlighted for the commonly found association between reading and mathematics abilities, and for the verbal short-term/working memory deficits often observed in dyslexia.

Abstract

Handedness is a manifestation of brain hemispheric specialization. Left-handedness occurs at increased rates in neurodevelopmental disorders. Genome-wide association studies have identified common genetic effects on handedness or brain asymmetry, which mostly involve variants outside protein-coding regions and may affect gene expression. Implicated genes include several that encode tubulins (microtubule components) or microtubule-associated proteins. Here we examine whether left-handedness is also influenced by rare coding variants (frequencies ≤ 1%), using exome data from 38,043 left-handed and 313,271 right-handed individuals from the UK Biobank. The beta-tubulin gene TUBB4B shows exome-wide significant association, with a rate of rare coding variants 2.7 times higher in left-handers than right-handers. The TUBB4B variants are mostly heterozygous missense changes, but include two frameshifts found only in left-handers. Other TUBB4B variants have been linked to sensorineural and/or ciliopathic disorders, but not the variants found here. Among genes previously implicated in autism or schizophrenia by exome screening, DSCAM and FOXP1 show evidence for rare coding variant association with left-handedness. The exome-wide heritability of left-handedness due to rare coding variants was 0.91%. This study reveals a role for rare, protein-altering variants in left-handedness, providing further evidence for the involvement of microtubules and disorder-relevant genes.

Abstract

Dyslexia is a common condition that impacts reading ability. Identifying affected brain networks has been hampered by limited sample sizes of imaging case-control studies. We focused instead on brain structural correlates of genetic disposition to dyslexia in large-scale population data. In over 30,000 adults (UK Biobank), higher polygenic disposition to dyslexia was associated with lower head and brain size, and especially reduced volume and/or altered fiber density in networks involved in motor control, language and vision. However, individual genetic variants disposing to dyslexia often had quite distinct patterns of association with brain structural features. Independent component analysis applied to brain-wide association maps for thousands of dyslexia-disposing genetic variants revealed multiple impact modes on the brain, that corresponded to anatomically distinct areas with their own genomic profiles of association. Polygenic scores for dyslexia-related cognitive and educational measures, as well as attention-deficit/hyperactivity disorder, showed similarities to dyslexia polygenic disposition in terms of brain-wide associations, with microstructure of the internal capsule consistently implicated. In contrast, lower volume of the primary motor cortex was only associated with higher dyslexia polygenic disposition among all traits. These findings robustly reveal heterogeneous neurobiological aspects of dyslexia genetic disposition, and whether they are shared or unique with respect to other genetically correlated traits.

Abstract

Background

The number of words children produce (expressive vocabulary) and understand (receptive vocabulary) changes rapidly during early development, partially due to genetic factors. Here, we performed a meta–genome-wide association study of vocabulary acquisition and investigated polygenic overlap with literacy, cognition, developmental phenotypes, and neurodevelopmental conditions, including attention-deficit/hyperactivity disorder (ADHD).

Methods

We studied 37,913 parent-reported vocabulary size measures (English, Dutch, Danish) for 17,298 children of European descent. Meta-analyses were performed for early-phase expressive (infancy, 15–18 months), late-phase expressive (toddlerhood, 24–38 months), and late-phase receptive (toddlerhood, 24–38 months) vocabulary. Subsequently, we estimated single nucleotide polymorphism–based heritability (SNP-h2) and genetic correlations (rg) and modeled underlying factor structures with multivariate models.

Results

Early-life vocabulary size was modestly heritable (SNP-h2 = 0.08–0.24). Genetic overlap between infant expressive and toddler receptive vocabulary was negligible (rg = 0.07), although each measure was moderately related to toddler expressive vocabulary (rg = 0.69 and rg = 0.67, respectively), suggesting a multifactorial genetic architecture. Both infant and toddler expressive vocabulary were genetically linked to literacy (e.g., spelling: rg = 0.58 and rg = 0.79, respectively), underlining genetic similarity. However, a genetic association of early-life vocabulary with educational attainment and intelligence emerged only during toddlerhood (e.g., receptive vocabulary and intelligence: rg = 0.36). Increased ADHD risk was genetically associated with larger infant expressive vocabulary (rg = 0.23). Multivariate genetic models in the ALSPAC (Avon Longitudinal Study of Parents and Children) cohort confirmed this finding for ADHD symptoms (e.g., at age 13; rg = 0.54) but showed that the association effect reversed for toddler receptive vocabulary (rg = −0.74), highlighting developmental heterogeneity.

Conclusions

The genetic architecture of early-life vocabulary changes during development, shaping polygenic association patterns with later-life ADHD, literacy, and cognition-related traits.

Abstract

Rapid advances over the last decade in DNA sequencing and statistical genetics enable us to investigate the genomic makeup of individuals throughout history. In a recent notable study, Begg et al.1 used Ludwig van Beethoven’s hair strands for genome sequencing and explored genetic predispositions for some of his documented medical issues. Given that it was arguably Beethoven’s skills as a musician and composer that made him an iconic figure in Western culture, we here extend the approach and apply it to musicality. We use this as an example to illustrate the broader challenges of individual-level genetic predictions.

Abstract

The language network of the human brain has core components in the inferior frontal cortex and superior/middle temporal cortex, with left-hemisphere dominance in most people. Functional specialization and interconnectivity of these neocortical regions is likely to be reflected in their molecular and cellular profiles. Excitatory connections between cortical regions arise and innervate according to layer-specific patterns. Here we generated a new gene expression dataset from human postmortem cortical tissue samples from core language network regions, using spatial transcriptomics to discriminate gene expression across cortical layers. Integration of these data with existing single-cell expression data identified 56 genes that showed differences in laminar expression profiles between frontal and temporal language cortex together with upregulation in layer II/III and/or layer V/VI excitatory neurons. Based on data from large-scale genome-wide screening in the population, DNA variants within these 56 genes showed set-level associations with inter-individual variation in structural connectivity between left-hemisphere frontal and temporal language cortex, and with predisposition to dyslexia. The axon guidance genes SLIT1 and SLIT2 were consistently implicated. These findings identify region-specific patterns of laminar gene expression as a feature of the brain’s language network.