The robust and independent nature of structural STS asymmetries

Bain, Jonathan S.; Filo, Shir; Mezer, Aviv

doi:10.1007/s00429-019-01952-3

Cited by 5 publications

(17 citation statements)

References 65 publications

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“…We measured qT1 data for all subjects. The qT1 data were acquired using the 3T Magnetom Trio scanner (Siemens) with a 32-channel head coil at CiNet, NICT and the protocols described in previous publications (Mezer et al, 2013;Gomez et al, 2017;Bain et al, 2019;Filo et al, 2019). We acquired four fast low-angle shot (FLASH) images with flip angles of 4°, 10°, 20°, and 30°(repetition time, 12 ms; echo time, 2.41 ms) and an isotropic scan resolution of 1 mm.…”

Section: Qt1 Data Acquisitionmentioning

confidence: 99%

Predicting Neural Response Latency of the Human Early Visual Cortex from MRI-Based Tissue Measurements of the Optic Radiation

Takemura

Yuasa

Amano

2020

eNeuro

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Although the non-invasive measurement of visually evoked responses has been extensively studied, the structural basis of variabilities in latency in healthy humans is not well understood. We investigated how tissue properties of optic radiation could predict interindividual variability in the latency of the initial visually evoked component (C1), which may originate from the primary visual cortex (V1). We collected C1 peak latency data using magnetoencephalography (MEG) and checkerboard stimuli, and multiple structural magnetic resonance imaging (MRI) data from 20 healthy subjects. While we varied the contrast and position of the stimuli, the C1 measurement was most reliable when high-contrast stimuli were presented to the lower visual field (LVF). We then attempted to predict interindividual variability in C1 peak latency in this stimulus condition with a multiple regression model using MRI parameters along the optic radiation. We found that this model could predict .20% of variance in C1 latency, when the data were averaged across the hemispheres. The model using the corticospinal tract did not predict variability in C1 latency, suggesting that there is no evidence for generalization to a non-visual tract. In conclusion, our results suggest that the variability in neural latencies in the early visual cortex in healthy subjects can be partly explained by tissue properties along the optic radiation. We discuss the challenges of predicting neural latency using current structural neuroimaging methods and other factors that may explain interindividual variance in neural latency.

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Section: Qt1 Data Acquisitionmentioning

confidence: 99%

Predicting Neural Response Latency of the Human Early Visual Cortex from MRI-Based Tissue Measurements of the Optic Radiation

Takemura

Yuasa

Amano

2020

eNeuro

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“…For SA asymmetry, we uncovered a covariance structure that almost perfectly replicated across datasets. In general, this fit with a multifaceted nature of brain asymmetry 32,43,44 , in which most asymmetries were either not or only weakly correlated, but reliably so. Importantly, however, we identified several regions wherein SA asymmetry reliably correlated within individuals, showing the variance in structural cortical asymmetries is not always dissociable, as is often thought 32,43,109 .…”

Section: Discussionmentioning

confidence: 63%

“…In general, this fit with a multifaceted nature of brain asymmetry 32,43,44 , in which most asymmetries were either not or only weakly correlated, but reliably so. Importantly, however, we identified several regions wherein SA asymmetry reliably correlated within individuals, showing the variance in structural cortical asymmetries is not always dissociable, as is often thought 32,43,109 . The strongest relationships all pertained to asymmetries that were proximal in the cortex but opposite in direction (i.e.…”

Section: Discussionmentioning

confidence: 63%

“…Furthermore, that study applied a relatively course brain atlas, and there is currently no high-resolution complement to describe cortical asymmetries that reliably reproduce across international samples (but see 10,24 ). For areal asymmetry, while results have been broadly more consistent 7,8,14,19,23,26 , there nevertheless remain important discrepancies, such as reports of right- 7,27,28 and left- 14,26 lateralization of superior temporal sulcus (STS).…”

Section: Introductionmentioning

confidence: 99%

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Tracing the development and lifespan change of population-level structural asymmetry in the cerebral cortex

Roe

Vidal-Piñeiro

Amlien

et al. 2021

Preprint

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Cortical asymmetry is a ubiquitous feature of brain organization that is altered in neurodevelopmental disorders and aging. Achieving consensus on cortical asymmetries in humans is necessary to uncover the genetic-developmental mechanisms that shape them and factors moderating cortical lateralization. Here, we delineate population-level asymmetry in cortical thickness and surface area vertex-wise in 7 datasets and chart asymmetry trajectories across life (4-89 years; observations = 3937; 70% longitudinal). We reveal asymmetry interrelationships, heritability, and test associations in UK Biobank (N=∼37,500). Cortical asymmetry was robust across datasets. Whereas areal asymmetry is predominantly stable across life, thickness asymmetry grows in development and declines in aging. Areal asymmetry correlates in specific regions, whereas thickness asymmetry is globally interrelated across cortex and suggests high directional variability in global thickness lateralization. Areal asymmetry is moderately heritable (max h2SNP ∼19%), and phenotypic correlations are reflected by high genetic correlations, whereas heritability of thickness asymmetry is low. Finally, we detected an asymmetry association with cognition and confirm recently-reported handedness links. Results suggest areal asymmetry is developmentally stable and arises in early life, whereas developmental changes in thickness asymmetry may lead to directional variability of global thickness lateralization. Our results bear enough reproducibility to serve as a standard for future brain asymmetry studies.SignificanceCortical asymmetry is reduced in neurodevelopmental disorders, yet we lack knowledge of how cortical asymmetry development proceeds across life in health. We provide a definitive reference for asymmetry in the cerebral cortex. We find areal asymmetry is stable from childhood to old age, and specific areal asymmetries are formed under common genetic-developmental influence. In contrast, thickness asymmetry shows developmental growth, and is globally interrelated in a pattern suggesting highly left-lateralized individuals tend towards left-lateralization also in right-asymmetric regions (and vice versa). Heritability mapping also supported a prenatal-postnatal developmental dichotomy for areal and thickness asymmetry, and we find reduced asymmetry in the most lateralized brain region associates with reduced cognition. Our results provide novel insights into normal brain organization and development.

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“…We analyzed the dMRI and qR1 dataset collected on a 3T General Electric Discovery 750 (General Electric Healthcare, Milwaukee, WI, USA) equipped with a 32-channel head coil (Nova Medical, Wilmington, MA, USA) at the Center for Cognitive and Neurobiological Imaging at Stanford University (www.cni.stanford.edu). This dataset has already been analyzed in previous publications (Bain et al, 2019a(Bain et al, , 2019bErramuzpe et al, 2021;Lerma-Usabiaga et al, 2020;Schurr et al, 2019b;Yeatman et al, 2014).…”

Section: Mri Datasetsmentioning

confidence: 99%

Age dependency and lateralization in the three branches of the human superior longitudinal fasciculus

Amemiya

Naito

Takemura

2021

Preprint

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The superior longitudinal fascicle/fasciculus (SLF) is a major white matter tract connecting the frontal and parietal cortices in humans. Although the SLF has often been analyzed as a single entity, several studies have reported that the SLF is segregated into three distinct branches (SLF I, II, and III). They have also reported the right lateralization of the SLF III volume and discussed its relationship with lateralized cortical functions in the fronto-parietal network. However, to date, the homogeneity or heterogeneity of the age dependency and lateralization properties of SLF branches have not been fully clarified. Through this study, we aimed to clarify the age dependency and lateralization of SLF I-III by analyzing diffusion-weighted MRI (dMRI) and quantitative R1 (qR1) map datasets collected from a wide range of age groups, mostly comprising right-handed children, adolescents, adults, and seniors (6 to 81 years old). The age dependency in dMRI measurement (fractional anisotropy, FA) was heterogeneous among the three SLF branches, suggesting that these branches are regulated by distinct developmental and aging processes. Lateralization analysis on SLF branches revealed that the right SLF III was larger than the left SLF III in adults, replicating previous reports. FA measurement also suggested that, in addition to SLF III, SLF II was lateralized to the right hemisphere in adolescents and adults. We further found a left lateralization of SLF I in qR1 data, a microstructural measurement sensitive to myelin levels, in adults. These findings suggest that the SLF sub-bundles are distinct entities in terms of age dependency and lateralization.

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The robust and independent nature of structural STS asymmetries

Cited by 5 publications

References 65 publications

Predicting Neural Response Latency of the Human Early Visual Cortex from MRI-Based Tissue Measurements of the Optic Radiation

Predicting Neural Response Latency of the Human Early Visual Cortex from MRI-Based Tissue Measurements of the Optic Radiation

Tracing the development and lifespan change of population-level structural asymmetry in the cerebral cortex

Age dependency and lateralization in the three branches of the human superior longitudinal fasciculus

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