White matter brain structure predicts language performance and learning success.

Individual differences in the ability to process language have long been discussed. Much of the neural basis of these, however, is yet unknown. Here we investigated the relationship between long-range white matter connectivity of the brain, as revealed by diffusion tractography, and the ability to process syntactically complex sentences in the participants' native language as well as the improvement thereof by multiday training. We identified specific network motifs by singular value decomposition that indeed related white matter structural connectivity to individual language processing performance. First, for two such motifs, one in the left and one in the right hemisphere, their individual prevalence significantly predicted the individual language performance, suggesting an anatomical predisposition for the individual ability to process syntactically complex sentences. Both motifs comprise a number of cortical regions, but seem to be dominated by areas known for the involvement in working memory rather than the classical language network itself. Second, we identified another left hemispheric network motif, whose change of prevalence over the training period significantly correlated with the individual change in performance, thus reflecting training induced white matter plasticity. This motif comprises diverse cortical areas including regions known for their involvement in language processing, working memory and motor functions. The present findings suggest that individual differences in language processing and learning can be explained, in part, by individual differences in the brain's white matter structure. Brain structure may be a crucial factor to be considered when discussing variations in human cognitive performance, more generally.

Functional brain plasticity during L1 training on complex sentences: Changes in gamma-band oscillatory activity.

The adult human brain remains plastic even after puberty. However, whether first language (L1) training in adults can alter the language network is yet largely unknown. Thus, we conducted a longitudinal training experiment on syntactically complex German sentence comprehension. Sentence complexity was varied by the depth of the center embedded relative clauses (i.e., single or double embedded). Comprehension was tested after each sentence with a question on the thematic role assignment. Thirty adult, native German speakers were recruited for 4 days of training. Magnetoencephalography (MEG) data were recorded and subjected to spectral power analysis covering the classical frequency bands (i.e., theta, alpha, beta, low gamma, and gamma). Normalized spectral power, time-locked to the final closure of the relative clause, was subjected to a two-factor analysis ("sentence complexity" and "training days"). Results showed that for the more complex sentences, the interaction of sentence complexity and training days was observed in Brodmann area 44 (BA 44) as a decrease of gamma power with training. Moreover, in the gamma band (55-95 Hz) functional connectivity between BA 44 and other brain regions such as the inferior frontal sulcus and the inferior parietal cortex were correlated with behavioral performance increase due to training. These results show that even for native speakers, complex L1 sentence training improves language performance and alters neural activities of the left hemispheric language network. Training strengthens the use of the dorsal processing stream with working-memory-related brain regions for syntactically complex sentences, thereby demonstrating the brain's functional plasticity for L1 training.

The emergence of dyslexia in the developing brain.

Developmental dyslexia, a severe deficit in literacy learning, is a neurodevelopmental learning disorder. Yet, it is not clear whether existing neurobiological accounts of dyslexia capture potential predispositions of the deficit or consequences of reduced reading experience. Here, we longitudinally followed 32 children from preliterate to school age using functional and structural magnetic resonance imaging techniques. Based on standardised and age-normed reading and spelling tests administered at school age, children were classified as 16 dyslexic participants and 16 controls. This longitudinal design allowed us to disentangle possible neurobiological predispositions for developing dyslexia from effects of individual differences in literacy experience. In our sample, the disorder can be predicted already before literacy learning from auditory cortex gyrification and aberrant downstream connectivity within the speech processing system. These results provide evidence for the notion that dyslexia may originate from an atypical maturation of the speech network that precedes literacy instruction.

The Concurrence of Cortical Surface Area Expansion and White Matter Myelination in Human Brain Development.

The human brain undergoes dramatic structural changes during childhood that co-occur with behavioral development. These age-related changes are documented for the brain's gray matter and white matter. However, their interrelation is largely unknown. In this study, we investigated age-related effects in cortical thickness (CT) and in cortical surface area (SA) as parts of the gray matter volume as well as age effects in T1 relaxation times in the white matter. Data from N = 170 children between the ages of 3 and 7 years contributed to the sample. We found a high spatial overlap of age-related correlations between SA and T1 relaxation times of the corresponding white matter connections, but no such relation between SA and CT. These results indicate that during childhood the developmental expansion of the cortical surface goes hand-in-hand with age-related increase of white matter fiber connections terminating in the cortical surface.

The emergence of long-range language network structural covariance and language abilities.

Language skills increase as the brain matures. Language processing, especially the comprehension of syntactically complex sentences, is supported by a brain network involving functional interactions between left inferior frontal and left temporal regions in the adult brain, with reduced functional interactions in children. Here, we examined the gray matter covariance of the cortical thickness network relevant for syntactic processing in relation to language abilities in preschool children (i.e., 5-year-olds) and analyzed the developmental changes of the cortical thickness covariance cross-sectionally by comparing preschool children, school age children, and adults. Further, to demonstrate the agreement of cortical thickness covariance and white matter connectivity, tractography analyses were performed. Covariance of language-relevant seeds in preschoolers was strongest in contralateral homologous regions. A more adult-like, significant cortical thickness covariance between left frontal and left temporal regions, however, was observed in preschoolers with advanced syntactic language abilities. By comparing the three age groups, we could show that the cortical thickness covariance pattern from the language-associated seeds develops progressively from restricted in preschoolers to widely-distributed brain regions in adults. In addition, our results suggest that the cortical thickness covariance difference of the left inferior frontal gyrus to superior temporal gyrus/sulcus between preschoolers and adults is accompanied by distinctions in the white matter tracts linking these two areas, with more mature white matter in the arcuate fasciculus in adults compared to preschoolers. These findings provide anatomical evidence for developmental changes in language both from the perspective of gray matter structure co-variation within the language network and white matter maturity as the anatomical substrate for the structural covariance.

Young children's sentence comprehension: Neural correlates of syntax-semantic competition.

Sentence comprehension requires the assignment of thematic relations between the verb and its noun arguments in order to determine who is doing what to whom. In some languages, such as English, word order is the primary syntactic cue. In other languages, such as German, case-marking is additionally used to assign thematic roles. During development children have to acquire the thematic relevance of these syntactic cues and weigh them against semantic cues. Here we investigated the processing of syntactic cues and semantic cues in 2- and 3-year-old children by analyzing their behavioral and neurophysiological responses. Case-marked subject-first and object-first sentences (syntactic cue) including animate and inanimate nouns (semantic cue) were presented auditorily. The semantic animacy cue either conflicted with or supported the thematic roles assigned by syntactic case-marking. In contrast to adults, for whom semantics did not interfere with case-marking, children attended to both syntactic and to semantic cues with a stronger reliance on semantic cues in early development. Children's event-related brain potentials indicated sensitivity to syntactic information but increased processing costs when case-marking and animacy assigned conflicting thematic roles. These results demonstrate an early developmental sensitivity and ongoing shift towards the use of syntactic cues during sentence comprehension.

In-line interferometer for broadband near-field scanning optical spectroscopy.

We present and investigate a novel approach towards broad-bandwidth near-field scanning optical spectroscopy based on an in-line interferometer for homodyne mixing of the near field and a reference field. In scattering-type scanning near-field optical spectroscopy, the near-field signal is usually obscured by a large amount of unwanted background scattering from the probe shaft and the sample. Here we increase the light reflected from the sample by a semi-transparent gold layer and use it as a broad-bandwidth, phase-stable reference field to amplify the near-field signal in the visible and near-infrared spectral range. We experimentally demonstrate that this efficiently suppresses the unwanted background signal in monochromatic near-field measurements. For rapid acquisition of complete broad-bandwidth spectra we employ a monochromator and a fast line camera. Using this fast acquisition of spectra and the in-line interferometer we demonstrate the measurement of pure near-field spectra. The experimental observations are quantitatively explained by analytical expressions for the measured optical signals, based on Fourier decomposition of background and near field. The theoretical model and in-line interferometer together form an important step towards broad-bandwidth near-field scanning optical spectroscopy.

NRSN1 associated grey matter volume of the visual word form area reveals dyslexia before school.

Literacy learning depends on the flexibility of the human brain to reconfigure itself in response to environmental influences. At the same time, literacy and disorders of literacy acquisition are heritable and thus to some degree genetically predetermined. Here we used a multivariate non-parametric genetic model to relate literacy-associated genetic variants to grey and white matter volumes derived by voxel-based morphometry in a cohort of 141 children. Subsequently, a sample of 34 children attending grades 4 to 8, and another sample of 20 children, longitudinally followed from kindergarten to first grade, were classified as dyslexics and controls using linear binary support vector machines. The NRSN1-associated grey matter volume of the 'visual word form area' achieved a classification accuracy of ~ 73% in literacy-experienced students and distinguished between later dyslexic individuals and controls with an accuracy of 75% at kindergarten age. These findings suggest that the cortical plasticity of a region vital for literacy might be genetically modulated, thereby potentially preconstraining literacy outcome. Accordingly, these results could pave the way for identifying and treating the most common learning disorder before it manifests itself in school.

Frequency of Maternal Touch Predicts Resting Activity and Connectivity of the Developing Social Brain.

Previous behavioral research points to a positive relationship between maternal touch and early social development. Here, we explored the brain correlates of this relationship. The frequency of maternal touch was recorded for 43 five-year-old children during a 10 min standardized play session. Additionally, all children completed a resting-state functional magnetic resonance imaging session. Investigating the default mode network revealed a positive relation between the frequency of maternal touch and activity in the right posterior superior temporal sulcus (pSTS) extending into the temporo-parietal junction. Using this effect as a seed in a functional connectivity analysis identified a network including extended bilateral regions along the temporal lobe, bilateral frontal cortex, and left insula. Compared with children with low maternal touch, children with high maternal touch showed additional connectivity with the right dorso-medial prefrontal cortex. Together these results support the notion that childhood tactile experiences shape the developing "social brain" with a particular emphasis on a network involved in mentalizing.

Brain Functional and Structural Predictors of Language Performance.

The relation between brain function and behavior on the one hand and the relation between structural changes and behavior on the other as well as the link between the 2 aspects are core issues in cognitive neuroscience. It is an open question, however, whether brain function or brain structure is the better predictor for age-specific cognitive performance. Here, in a comprehensive set of analyses, we investigated the direct relation between hemodynamic activity in 2 pairs of frontal and temporal cortical areas, 2 long-distance white matter fiber tracts connecting each pair and sentence comprehension performance of 4 age groups, including 3 groups of children between 3 and 10 years as well as young adults. We show that the increasing accuracy of processing complex sentences throughout development is correlated with the blood-oxygen-level-dependent activation of 2 core language processing regions in Broca's area and the posterior portion of the superior temporal gyrus. Moreover, both accuracy and speed of processing are correlated with the maturational status of the arcuate fasciculus, that is, the dorsal white matter fiber bundle connecting these 2 regions. The present data provide compelling evidence for the view that brain function and white matter structure together best predict developing cognitive performance.

Preschoolers' brains rely on semantic cues prior to the mastery of syntax during sentence comprehension.

Sentence comprehension requires the integration of both syntactic and semantic information, the acquisition of which seems to have different trajectories in the developing brain. Using functional magnetic resonance imaging, we examined the neural correlates underlying syntactic and semantic processing during auditory sentence comprehension as well as its development in preschool children by manipulating case marking and animacy hierarchy cues, respectively. A functional segregation was observed within Broca's area in the left inferior frontal gyrus for adults, where the pars opercularis was involved in syntactic processing and the pars triangularis in semantic processing. By contrast, five-year-old children sensitive to animacy hierarchy cues showed diffuse activation for semantic processing in the left inferior frontal and posterior temporal cortices. While no main effect of case marking was found in the left fronto-temporal language network, children with better syntactic skills showed greater neural responses for syntactically complex sentences, most prominently in the posterior superior temporal cortex. The current study provides both behavioral and neural evidence that five-year-old children compared to adults rely more on semantic information than on syntactic cues during sentence comprehension, but with the development of syntactic abilities, their brain activation in the left fronto-temporal network increases for syntactic processing.

Longitudinal changes in resting-state fMRI from age 5 to age 6years covary with language development.

Resting-state functional magnetic resonance imaging is a powerful technique to study the whole-brain neural connectivity that underlies cognitive systems. The present study aimed to define the changes in neural connectivity in their relation to language development. Longitudinal resting-state functional data were acquired from a cohort of preschool children at age 5 and one year later, and changes in functional connectivity were correlated with language performance in sentence comprehension. For this, degree centrality, a voxel-based network measure, was used to assess age-related differences in connectivity at the whole-brain level. Increases in connectivity with age were found selectively in a cluster within the left posterior superior temporal gyrus and sulcus (STG/STS). In order to further specify the connection changes, a secondary seed-based functional connectivity analysis on this very cluster was performed. The correlations between resting-state functional connectivity (RSFC) and language performance revealed developmental effects with age and, importantly, also dependent on the advancement in sentence comprehension ability over time. In children with greater advancement in language abilities, the behavioral improvement was positively correlated with RSFC increase between left posterior STG/STS and other regions of the language network, i.e., left and right inferior frontal cortex. The age-related changes observed in this study provide evidence for alterations in the language network as language develops and demonstrates the viability of this approach for the investigation of normal and aberrant language development.

Predicting early signs of dyslexia at a preliterate age by combining behavioral assessment with structural MRI.

BACKGROUND: Recent studies suggest that neurobiological anomalies are already detectable in pre-school children with a family history of developmental dyslexia (DD). However, there is a lack of longitudinal studies showing a direct link between those differences at a preliterate age and the subsequent literacy difficulties seen in school. It is also not clear whether the prediction of DD in pre-school children can be significantly improved when considering neurobiological predictors, compared to models based on behavioral literacy precursors only. METHODS: We recruited 53 pre-reading children either with (N=25) or without a family risk of DD (N=28). Quantitative T1 MNI data and literacy precursor abilities were assessed at kindergarten age. A subsample of 35 children was tested for literacy skills either one or two years later, that is, either in first or second grade. RESULTS: The group comparison of quantitative T1 measures revealed significantly higher T1 intensities in the left anterior arcuate fascicle (AF), suggesting reduced myelin concentration in preliterate children at risk of DD. A logistic regression showed that DD can be predicted significantly better (p=.024) when neuroanatomical differences between groups are used as predictors (80%) compared to a model based on behavioral predictors only (63%). The Wald statistic confirmed that the T1 intensity of the left AF is a statistically significant predictor of DD (p<.05). CONCLUSIONS: Our longitudinal results provide evidence for the hypothesis that neuroanatomical anomalies in children with a family risk of DD are related to subsequent problems in acquiring literacy. Particularly, solid white matter organization in the left anterior arcuate fascicle seems to play a pivotal role.

Improved prediction of complex diseases by common genetic markers: state of the art and further perspectives.

Reliable risk assessment of frequent, but treatable diseases and disorders has considerable clinical and socio-economic relevance. However, as these conditions usually originate from a complex interplay between genetic and environmental factors, precise prediction remains a considerable challenge. The current progress in genotyping technology has resulted in a substantial increase of knowledge regarding the genetic basis of such diseases and disorders. Consequently, common genetic risk variants are increasingly being included in epidemiological models to improve risk prediction. This work reviews recent high-quality publications targeting the prediction of common complex diseases. To be included in this review, articles had to report both, numerical measures of prediction performance based on traditional (non-genetic) risk factors, as well as measures of prediction performance when adding common genetic variants to the model. Systematic PubMed-based search finally identified 55 eligible studies. These studies were compared with respect to the chosen approach and methodology as well as results and clinical impact. Phenotypes analysed included tumours, diabetes mellitus, and cardiovascular diseases. All studies applied one or more statistical measures reporting on calibration, discrimination, or reclassification to quantify the benefit of including SNPs, but differed substantially regarding the methodological details that were reported. Several examples for improved risk assessments by considering disease-related SNPs were identified. Although the add-on benefit of including SNP genotyping data was mostly moderate, the strategy can be of clinical relevance and may, when being paralleled by an even deeper understanding of disease-related genetics, further explain the development of enhanced predictive and diagnostic strategies for complex diseases.

Genetic dyslexia risk variant is related to neural connectivity patterns underlying phonological awareness in children.

Phonological awareness is the best-validated predictor of reading and spelling skill and therefore highly relevant for developmental dyslexia. Prior imaging genetics studies link several dyslexia risk genes to either brain-functional or brain-structural factors of phonological deficits. However, coherent evidence for genetic associations with both functional and structural neural phenotypes underlying variation in phonological awareness has not yet been provided. Here we demonstrate that rs11100040, a reported modifier of SLC2A3, is related to the functional connectivity of left fronto-temporal phonological processing areas at resting state in a sample of 9- to 12-year-old children. Furthermore, we provide evidence that rs11100040 is related to the fractional anisotropy of the arcuate fasciculus, which forms the structural connection between these areas. This structural connectivity phenotype is associated with phonological awareness, which is in turn associated with the individual retrospective risk scores in an early dyslexia screening as well as to spelling. These results suggest a link between a dyslexia risk genotype and a functional as well as a structural neural phenotype, which is associated with a phonological awareness phenotype. The present study goes beyond previous work by integrating genetic, brain-functional and brain-structural aspects of phonological awareness within a single approach. These combined findings might be another step towards a multimodal biomarker for developmental dyslexia.

Syntax gradually segregates from semantics in the developing brain.

An essential computational component of the human language faculty is syntax as it regulates how words are combined into sentences. Although its neuroanatomical basis is well-specified in adults, its emergence in the maturing brain is not yet understood. Using event-related functional magnetic resonance imaging (fMRI) in a cross-sectional design, we discovered, that in contrast to what is known about adults 3-to-4- and 6-to-7-year-old children do not process syntax independently from semantics at the neural level already before these two types of information are integrated for the interpretation of a sentence. It is not until the end of the 10th year of life that children show a neural selectivity for syntax, segregated and gradually independent from semantics, in the left inferior frontal cortex as in the adult brain. Our results indicate that it takes until early adolescence for the domain-specific selectivity of syntax within the language network to develop.

Developmental changes in organization of structural brain networks.

Recent findings from developmental neuroimaging studies suggest that the enhancement of cognitive processes during development may be the result of a fine-tuning of the structural and functional organization of brain with maturation. However, the details regarding the developmental trajectory of large-scale structural brain networks are not yet understood. Here, we used graph theory to examine developmental changes in the organization of structural brain networks in 203 normally growing children and adolescents. Structural brain networks were constructed using interregional correlations in cortical thickness for 4 age groups (early childhood: 4.8-8.4 year; late childhood: 8.5-11.3 year; early adolescence: 11.4-14.7 year; late adolescence: 14.8-18.3 year). Late childhood showed prominent changes in topological properties, specifically a significant reduction in local efficiency, modularity, and increased global efficiency, suggesting a shift of topological organization toward a more random configuration. An increase in number and span of distribution of connector hubs was found in this age group. Finally, inter-regional connectivity analysis and graph-theoretic measures indicated early maturation of primary sensorimotor regions and protracted development of higher order association and paralimbic regions. Our finding reveals a time window of plasticity occurring during late childhood which may accommodate crucial changes during puberty and the new developmental tasks that an adolescent faces.

Functional and structural syntax networks in aging.

Language abilities are known to deteriorate in aging, possibly related to decreased functional and structural connectivity within specialized brain networks. Here, we investigated syntactic ability in healthy young and older adults using a comprehensive assessment of behavioral performance, task-independent functional (FC) and structural brain connectivity (SC). Seed-based FC originating from left pars opercularis (part of Broca's area) known to support syntactic processes was assessed using resting-state functional magnetic resonance imaging, and SC using fractional anisotropy from diffusion weighted imaging, in the dorsally located superior longitudinal and the ventrally located uncinate fasciculi (SLF, UF) and forceps minor. Young compared to older adults exhibited superior syntactic performance and stronger FC within the mainly left-lateralized syntax network, which was beneficial for performance. In contrast, in older adults, FC within the mainly left-lateralized syntax network was reduced and did not correlate with performance; inter-hemispheric FC to right inferior frontal and angular gyri was detrimental for performance. In both groups, performance was positively correlated with inter-hemispheric SC. For intra-hemispheric SC, performance correlated with structural integrity of SLF in young adults and with integrity of UF in older adults. Our data show that reduced syntactic ability in older adults is associated with decreased FC within dedicated syntax networks. Moreover, young adults showed an association of syntactic ability with structural integrity of the dorsal tract, while older adults rely more on ventral fibers. In sum, our study provided novel insight into the relationship between connectivity and syntactic performance in young and older adults. In addition to elucidating age-related changes in syntax networks and their behavioral relevance, our results contribute to a better understanding of age-related changes in functional and structural brain organization in general, an important prerequisite for developing novel strategies to counteract age-related cognitive decline.

Neuroanatomical prerequisites for language functions in the maturing brain.

The 2 major language-relevant cortical regions in the human brain, Broca's area and Wernicke's area, are connected via the fibers of the arcuate fasciculus/superior longitudinal fasciculus (AF/SLF). Here, we compared this pathway in adults and children and its relation to language processing during development. Comparison of fiber properties demonstrated lower anisotropy in children's AF/SLF, arguing for an immature status of this particular pathway with conceivably a lower degree of myelination. Combined diffusion tensor imaging (DTI) data and functional magnetic resonance imaging (fMRI) data indicated that in adults the termination of the AF/SLF fiber projection is compatible with functional activation in Broca's area, that is pars opercularis. In children, activation in Broca's area extended from the pars opercularis into the pars triangularis revealing an alternative connection to the temporal lobe (Wernicke's area) via the ventrally projecting extreme capsule fiber system. fMRI and DTI data converge to indicate that adults make use of a more confined language network than children based on ongoing maturation of the structural network. Our data suggest relations between language development and brain maturation and, moreover, indicate the brain's plasticity to adjust its function to available structural prerequisites.