Inconsistent language lateralisation – Testing the dissociable language laterality hypothesis using behaviour and lateralised cerebral blood flow

Resting-state functional connectivity correlates of brain structural aging in schizophrenia

A large body of research has shown that schizophrenia patients demonstrate increased brain structural aging. Although this process may be coupled with aberrant changes in intrinsic functional architecture of the brain, they remain understudied. We hypothesized that there are brain regions whose whole-brain functional connectivity at rest is differently associated with brain structural aging in schizophrenia patients compared to healthy controls. Eighty-four male schizophrenia patients and eighty-six male healthy controls underwent structural MRI and resting-state fMRI. The brain-predicted age difference (b-PAD) was a measure of brain structural aging. Resting-state fMRI was applied to obtain global correlation (GCOR) maps comprising voxelwise values of the strength and sign of functional connectivity of a given voxel with the rest of the brain. Schizophrenia patients had higher b-PAD compared to controls (mean between-group difference + 2.9 years). Greater b-PAD in schizophrenia patients, compared to controls, was associated with lower whole-brain functional connectivity of a region in frontal orbital cortex, inferior frontal gyrus, Heschl's Gyrus, plana temporale and polare, insula, and opercular cortices of the right hemisphere (rFTI). According to post hoc seed-based correlation analysis, decrease of functional connectivity with the posterior cingulate gyrus, left superior temporal cortices, as well as right angular gyrus/superior lateral occipital cortex has mainly driven the results. Lower functional connectivity of the rFTI was related to worse verbal working memory and language production. Our findings demonstrate that well-established frontotemporal functional abnormalities in schizophrenia are related to increased brain structural aging.

A meta-analytical account of the functional lateralization of the reading network

The observation that the neural correlates of reading are left-lateralized is ubiquitous in the cognitive neuroscience and neuropsychological literature. Still, reading is served by a constellation of neural units, and the extent to which these units are consistently left-lateralized is unclear. In this regard, the functional lateralization of the fusiform gyrus is of particular interest, by virtue of its hypothesized role as a "visual word form area". A quantitative Activation Likelihood Estimation meta-analysis was conducted on activation foci from 35 experiments investigating silent reading, and both a whole-brain and a bayesian ROI-based approach were used to assess the lateralization of the data submitted to meta-analysis. Perirolandic areas showed the highest level of left-lateralization, the fusiform cortex and the parietal cortex exhibited only a moderate pattern of left-lateralization, while in the occipital, insular cortices and in the cerebellum the lateralization turned out to be the lowest observed. The relatively limited functional lateralization of the fusiform gyrus was further explored in a regression analysis on the lateralization profile of each study. The functional lateralization of the fusiform gyrus during reading was positively associated with the lateralization of the precentral and inferior occipital gyri and negatively associated with the lateralization of the triangular portion of the inferior frontal gyrus and of the temporal pole. Overall, the present data highlight how lateralization patterns differ within the reading network. Furthermore, the present data highlight how the functional lateralization of the fusiform gyrus during reading is related to the degree of functional lateralization of other language brain areas.

Approaches to Measuring Language Lateralisation: An Exploratory Study Comparing Two fMRI Methods and Functional Transcranial Doppler Ultrasound

In this exploratory study we compare and contrast two methods for deriving a laterality index (LI) from functional magnetic resonance imaging (fMRI) data: the weighted bootstrapped mean from the LI Toolbox (toolbox method), and a novel method that uses subtraction of activations from homologous regions in left and right hemispheres to give an array of difference scores (mirror method). Data came from 31 individuals who had been selected to include a high proportion of people with atypical laterality when tested with functional transcranial Doppler ultrasound (fTCD). On two tasks, word generation and semantic matching, the mirror method generally gave better agreement with fTCD laterality than the toolbox method, both for individual regions of interest, and for a large region corresponding to the middle cerebral artery. LI estimates from this method had much smaller confidence intervals (CIs) than those from the toolbox method; with the mirror method, most participants were reliably lateralised to left or right, whereas with the toolbox method, a higher proportion were categorised as bilateral (i.e., the CI for the LI spanned zero). Reasons for discrepancies between fMRI methods are discussed: one issue is that the toolbox method averages the LI across a wide range of thresholds. Furthermore, examination of task-related t-statistic maps from the two hemispheres showed that language lateralisation is evident in regions characterised by deactivation, and so key information may be lost by ignoring voxel activations below zero, as is done with conventional estimates of the LI.

Opposite perceptual biases in analogous auditory and visual tasks are unique to consonant-vowel strings and are unlikely a consequence of repetition

Despite wide reporting of a right ear (RE) advantage on dichotic listening tasks and a right visual field (RVF) advantage on visual half-field tasks, we know very little about the relationship between these perceptual biases. Previous studies that have investigated perceptual asymmetries for analogous auditory and visual consonant-vowel tasks have indicated a serendipitous finding: a RE advantage and a left visual field (LVF) advantage with poor cross-modal correlations. In this study, we examined the possibility that this LVF advantage for visual processing of consonant-vowel strings may be a consequence of repetition by examining perceptual biases in analogous auditory and visual tasks for both consonant-vowel strings and words. We replicated opposite perceptual biases for consonant-vowel strings (RE and LVF advantages). This did not extend to word stimuli where we found RE and RVF advantages. Furthermore, these perceptual biases did not differ across the three experimental blocks. Thus, we can firmly conclude that this LVF advantage is unique to consonant-vowel strings and is not a consequence of the repetition of a relatively limited number of stimuli. Finally, a test of covariances indicated cross-modal relationships between laterality indices suggesting that perceptual biases are dissociable within individuals and cluster on mode of presentation.

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

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

Variability in Hemispheric Functional Segregation Phenotypes: A Review and General Mechanistic Model

Many functions of the human brain are organized asymmetrically and are subject to strong population biases. Some tasks, like speaking and making complex hand movements, exhibit left hemispheric dominance, whereas others, such as spatial processing and recognizing faces, favor the right hemisphere. While pattern of preference implies the existence of a stereotypical way of distributing functions between the hemispheres, an ever-increasing body of evidence indicates that not everyone follows this pattern of hemispheric functional segregation. On the contrary, the review conducted in this article shows that departures from the standard hemispheric division of labor are routinely observed and assume many distinct forms, each having a different prevalence rate. One of the key challenges in human neuroscience is to model this variability. By integrating well-established and recently emerged ideas about the mechanisms that underlie functional lateralization, the current article proposes a general mechanistic model that explains the observed distribution of segregation phenotypes and generates new testable hypotheses.

Testing the relationship between lateralization on sequence-based motor tasks and language laterality using an online battery

ABSTRACTStudies have highlighted an association between motor laterality and speech production laterality. It is thought that common demands for sequential processing may underlie this association. However, most studies in this area have relied on relatively small samples and have infrequently explored the reliability of the tools used to assess lateralization. We, therefore, established the validity and reliability of an online battery measuring sequence-based motor laterality and language laterality before exploring the associations between laterality indices on language and motor tasks. The online battery was completed by 621 participants, 52 of whom returned to complete the battery a second time. The three motor tasks included in the battery showed good between-session reliability (r ≥ .78) and were lateralized in concordance with hand preference. The novel measure of speech production laterality was left lateralized at population level as predicted, but reliability was less satisfactory (r = .62). We found no evidence of an association between sequence-based motor laterality and language laterality. Those with a left-hand preference were more strongly lateralized on motor tasks requiring midline crossing; this effect was not observed in right-handers. We conclude that there is little evidence of the co-lateralization of language and sequence-based motor skill on this battery.