Successful MRI-Guided Focused Ultrasound Thalamotomy after Ipsilateral Gamma Knife Radiosurgery for Essential Tremor: A Case Report with Video.

We report the case of a 67-year-old left-handed female patient with disabling medically refractory essential tremor who underwent successful right-sided magnetic resonance-guided focused ultrasound (MRgFUS) of the ventral intermediate nucleus after ipsilateral gamma knife radiosurgery (GKRS) thalamotomy performed 3 years earlier. The GKRS had a partial effect on her postural tremor without side effects, but there was no reduction of her kinetic tremor or improvement in her quality of life (QoL). The patient subsequently underwent a MRgFUS thalamotomy, which induced an immediate and marked reduction in both the postural and kinetic tremor components, with minor complications (left upper lip hypesthesia, dysmetria in her left hand, and slight gait ataxia). The MRgFUS-induced lesion was centered more medially than the GKRS-induced lesion and extended more posteriorly and inferiorly. The MRgFUS-induced lesion interrupted remaining fibers of the dentatorubrothalamic tract (DRTT). The functional improvement 1-year post-MRgFUS was significant due to a marked reduction of the patient's kinetic tremor. The QoL score (Quality of Life in Essential Tremor) improved by 88% and her Clinical Rating Scale for Tremor left hand score by 62%. The side effects persisted but were minor, with no impact on her QoL. The explanation for the superior efficacy of MRgFUS compared to GKRS in our patient could be due to either a poor response to the GKRS or to a better localization of the MRgFUS lesion with a more extensive interruption of DRTT fibers. In conclusion, MRgFUS can be a valuable therapeutic option after unsatisfactory GKRS, especially because MRgFUS has immediate clinical effectiveness, allowing intra-procedural test lesions and possible readjustment of the target if necessary.

Tractostorm: The what, why, and how of tractography dissection reproducibility.

Investigative studies of white matter (WM) brain structures using diffusion MRI (dMRI) tractography frequently require manual WM bundle segmentation, often called "virtual dissection." Human errors and personal decisions make these manual segmentations hard to reproduce, which have not yet been quantified by the dMRI community. It is our opinion that if the field of dMRI tractography wants to be taken seriously as a widespread clinical tool, it is imperative to harmonize WM bundle segmentations and develop protocols aimed to be used in clinical settings. The EADC-ADNI Harmonized Hippocampal Protocol achieved such standardization through a series of steps that must be reproduced for every WM bundle. This article is an observation of the problematic. A specific bundle segmentation protocol was used in order to provide a real-life example, but the contribution of this article is to discuss the need for reproducibility and standardized protocol, as for any measurement tool. This study required the participation of 11 experts and 13 nonexperts in neuroanatomy and "virtual dissection" across various laboratories and hospitals. Intra-rater agreement (Dice score) was approximately 0.77, while inter-rater was approximately 0.65. The protocol provided to participants was not necessarily optimal, but its design mimics, in essence, what will be required in future protocols. Reporting tractometry results such as average fractional anisotropy, volume or streamline count of a particular bundle without a sufficient reproducibility score could make the analysis and interpretations more difficult. Coordinated efforts by the diffusion MRI tractography community are needed to quantify and account for reproducibility of WM bundle extraction protocols in this era of open and collaborative science.

ActiveAxADD : Toward non-parametric and orientationally invariant axon diameter distribution mapping using PGSE.

PURPOSE: Non-invasive axon diameter distribution (ADD) mapping using diffusion MRI is an ill-posed problem. Current ADD mapping methods require knowledge of axon orientation before performing the acquisition. Instead, ActiveAx uses a 3D sampling scheme to estimate the orientation from the signal, providing orientationally invariant estimates. The mean diameter is estimated instead of the distribution for the solution to be tractable. Here, we propose an extension (ActiveAxADD ) that provides non-parametric and orientationally invariant estimates of the whole distribution. THEORY: The accelerated microstructure imaging with convex optimization (AMICO) framework accelerates mean diameter estimation using a linear formulation combined with Tikhonov regularization to stabilize the solution. Here, we implement a new formulation (ActiveAxADD ) that uses Laplacian regularization to provide robust estimates of the whole ADD. METHODS: The performance of ActiveAxADD was evaluated using Monte Carlo simulations on synthetic white matter samples mimicking axon distributions reported in histological studies. RESULTS: ActiveAxADD provided robust ADD reconstructions when considering the isolated intra-axonal signal. However, our formulation inherited some common microstructure imaging limitations. When accounting for the extra axonal compartment, estimated ADDs showed spurious peaks and increased variability because of the difficulty of disentangling intra and extra axonal contributions. CONCLUSION: Laplacian regularization solves the ill-posedness regarding the intra axonal compartment. ActiveAxADD can potentially provide non-parametric and orientationally invariant ADDs from isolated intra-axonal signals. However, further work is required before ActiveAxADD can be applied to real data containing extra-axonal contributions, as disentangling the 2 compartment appears to be an overlooked challenge that affects microstructure imaging methods in general.

Tractography reproducibility challenge with empirical data (TraCED): The 2017 ISMRM diffusion study group challenge.

BACKGROUND: Fiber tracking with diffusion-weighted MRI has become an essential tool for estimating in vivo brain white matter architecture. Fiber tracking results are sensitive to the choice of processing method and tracking criteria. PURPOSE: To assess the variability for an algorithm in group studies reproducibility is of critical context. However, reproducibility does not assess the validity of the brain connections. Phantom studies provide concrete quantitative comparisons of methods relative to absolute ground truths, yet do no capture variabilities because of in vivo physiological factors. The ISMRM 2017 TraCED challenge was created to fulfill the gap. STUDY TYPE: A systematic review of algorithms and tract reproducibility studies. SUBJECTS: Single healthy volunteers. FIELD STRENGTH/SEQUENCE: 3.0T, two different scanners by the same manufacturer. The multishell acquisition included b-values of 1000, 2000, and 3000 s/mm2 with 20, 45, and 64 diffusion gradient directions per shell, respectively. ASSESSMENT: Nine international groups submitted 46 tractography algorithm entries each consisting 16 tracts per scan. The algorithms were assessed using intraclass correlation (ICC) and the Dice similarity measure. STATISTICAL TESTS: Containment analysis was performed to assess if the submitted algorithms had containment within tracts of larger volume submissions. This also serves the purpose to detect if spurious submissions had been made. RESULTS: The top five submissions had high ICC and Dice >0.88. Reproducibility was high within the top five submissions when assessed across sessions or across scanners: 0.87-0.97. Containment analysis shows that the top five submissions are contained within larger volume submissions. From the total of 16 tracts as an outcome relatively the number of tracts with high, moderate, and low reproducibility were 8, 4, and 4. DATA CONCLUSION: The different methods clearly result in fundamentally different tract structures at the more conservative specificity choices. Data and challenge infrastructure remain available for continued analysis and provide a platform for comparison. LEVEL OF EVIDENCE: 5 Technical Efficacy Stage: 1 J. Magn. Reson. Imaging 2020;51:234-249.

Sparse wars: A survey and comparative study of spherical deconvolution algorithms for diffusion MRI.

Spherical deconvolution methods are widely used to estimate the brain's white-matter fiber orientations from diffusion MRI data. In this study, eight spherical deconvolution algorithms were implemented and evaluated. These included two model selection techniques based on the extended Bayesian information criterion (i.e., best subset selection and the least absolute shrinkage and selection operator), iteratively reweighted l2- and l1-norm approaches to approximate the l0-norm, sparse Bayesian learning, Cauchy deconvolution, and two accelerated Richardson-Lucy algorithms. Results from our exhaustive evaluation show that there is no single optimal method for all different fiber configurations, suggesting that further studies should be conducted to find the optimal way of combining solutions from different methods. We found l0-norm regularization algorithms to resolve more accurately fiber crossings with small inter-fiber angles. However, in voxels with very dominant fibers, algorithms promoting more sparsity are less accurate in detecting smaller fibers. In most cases, the best algorithm to reconstruct fiber crossings with two fibers did not perform optimally in voxels with one or three fibers. Therefore, simplified validation systems as employed in a number of previous studies, where only two fibers with similar volume fractions were tested, should be avoided as they provide incomplete information. Future studies proposing new reconstruction methods based on high angular resolution diffusion imaging data should validate their results by considering, at least, voxels with one, two, and three fibers, as well as voxels with dominant fibers and different diffusion anisotropies.

Limits to anatomical accuracy of diffusion tractography using modern approaches.

Diffusion MRI fiber tractography is widely used to probe the structural connectivity of the brain, with a range of applications in both clinical and basic neuroscience. Despite widespread use, tractography has well-known pitfalls that limits the anatomical accuracy of this technique. Numerous modern methods have been developed to address these shortcomings through advances in acquisition, modeling, and computation. To test whether these advances improve tractography accuracy, we organized the 3-D Validation of Tractography with Experimental MRI (3D-VoTEM) challenge at the ISBI 2018 conference. We made available three unique independent tractography validation datasets - a physical phantom and two ex vivo brain specimens - resulting in 176 distinct submissions from 9 research groups. By comparing results over a wide range of fiber complexities and algorithmic strategies, this challenge provides a more comprehensive assessment of tractography's inherent limitations than has been reported previously. The central results were consistent across all sub-challenges in that, despite advances in tractography methods, the anatomical accuracy of tractography has not dramatically improved in recent years. Taken together, our results independently confirm findings from decades of tractography validation studies, demonstrate inherent limitations in reconstructing white matter pathways using diffusion MRI data alone, and highlight the need for alternative or combinatorial strategies to accurately map the fiber pathways of the brain.

Central nervous system microbleeds in the acute phase are associated with structural integrity by DTI one year after mild traumatic brain injury: A longitudinal study.

INTRODUCTION: Several imaging modalities are under investigation to unravel the pathophysiological mystery of delayed performance deficits in patients after mild traumatic brain injury (mTBI). Although both imaging and neuropsychological studies have been conducted, only few data on longitudinal correlations of diffusion tensor imaging (DTI), susceptibility weighted imaging (SWI) and extensive neuropsychological testing exist. METHODS: MRI with T1- and T2-weighted, SWI and DTI sequences at baseline and 12 months of 30 mTBI patients were compared with 20 healthy controls. Multiparametric assessment included neuropsychological testing of cognitive performance and post-concussion syndrome (PCS) at baseline, 3 and 12 months post-injury. Data analysis encompassed assessment of cerebral microbleeds (Mb) in SWI, tract-based spatial statistics (TBSS) and voxel-based morphometry (VBM) of DTI (VBM-DTI). Imaging markers were correlated with neuropsychological testing to evaluate sensitivity to cognitive performance and post-concussive symptoms. RESULTS: Patients with Mb in SWI in the acute phase showed worse performance in several cognitive tests at baseline and in the follow-ups during the chronic phase and higher symptom severity in the post concussion symptom scale (PCSS) at twelve months post-injury. In the acute phase there was no statistical difference in structural integrity as measured with DTI between mTBI patients and healthy controls. At twelve months post-injury, loss of structural integrity in mTBI patients was found in nearly all DTI indices compared to healthy controls. CONCLUSIONS: Presence of Mb detected by SWI was associated with worse cognitive outcome and persistent PCS in mTBI patients, while DTI did not prove to predict neuropsychological outcome in the acute phase.

Improved statistical evaluation of group differences in connectomes by screening-filtering strategy with application to study maturation of brain connections between childhood and adolescence.

Detecting local differences between groups of connectomes is a great challenge in neuroimaging, because the large number of tests that have to be performed and the impact on multiplicity correction. Any available information should be exploited to increase the power of detecting true between-group effects. We present an adaptive strategy that exploits the data structure and the prior information concerning positive dependence between nodes and connections, without relying on strong assumptions. As a first step, we decompose the brain network, i.e., the connectome, into subnetworks and we apply a screening at the subnetwork level. The subnetworks are defined either according to prior knowledge or by applying a data driven algorithm. Given the results of the screening step, a filtering is performed to seek real differences at the node/connection level. The proposed strategy could be used to strongly control either the family-wise error rate or the false discovery rate. We show by means of different simulations the benefit of the proposed strategy, and we present a real application of comparing connectomes of preschool children and adolescents.

Multicontrast connectometry: a new tool to assess cerebellum alterations in early relapsing-remitting multiple sclerosis.

BACKGROUND: Cerebellar pathology occurs in late multiple sclerosis (MS) but little is known about cerebellar changes during early disease stages. In this study, we propose a new multicontrast "connectometry" approach to assess the structural and functional integrity of cerebellar networks and connectivity in early MS. METHODS: We used diffusion spectrum and resting-state functional MRI (rs-fMRI) to establish the structural and functional cerebellar connectomes in 28 early relapsing-remitting MS patients and 16 healthy controls (HC). We performed multicontrast "connectometry" by quantifying multiple MRI parameters along the structural tracts (generalized fractional anisotropy-GFA, T1/T2 relaxation times and magnetization transfer ratio) and functional connectivity measures. Subsequently, we assessed multivariate differences in local connections and network properties between MS and HC subjects; finally, we correlated detected alterations with lesion load, disease duration, and clinical scores. RESULTS: In MS patients, a subset of structural connections showed quantitative MRI changes suggesting loss of axonal microstructure and integrity (increased T1 and decreased GFA, P < 0.05). These alterations highly correlated with motor, memory and attention in patients, but were independent of cerebellar lesion load and disease duration. Neither network organization nor rs-fMRI abnormalities were observed at this early stage. CONCLUSION: Multicontrast cerebellar connectometry revealed subtle cerebellar alterations in MS patients, which were independent of conventional disease markers and highly correlated with patient function. Future work should assess the prognostic value of the observed damage.

Genomic study of RNA polymerase II and III SNAPc-bound promoters reveals a gene transcribed by both enzymes and a broad use of common activators.

SNAP(c) is one of a few basal transcription factors used by both RNA polymerase (pol) II and pol III. To define the set of active SNAP(c)-dependent promoters in human cells, we have localized genome-wide four SNAP(c) subunits, GTF2B (TFIIB), BRF2, pol II, and pol III. Among some seventy loci occupied by SNAP(c) and other factors, including pol II snRNA genes, pol III genes with type 3 promoters, and a few un-annotated loci, most are primarily occupied by either pol II and GTF2B, or pol III and BRF2. A notable exception is the RPPH1 gene, which is occupied by significant amounts of both polymerases. We show that the large majority of SNAP(c)-dependent promoters recruit POU2F1 and/or ZNF143 on their enhancer region, and a subset also recruits GABP, a factor newly implicated in SNAP(c)-dependent transcription. These activators associate with pol II and III promoters in G1 slightly before the polymerase, and ZNF143 is required for efficient transcription initiation complex assembly. The results characterize a set of genes with unique properties and establish that polymerase specificity is not absolute in vivo.

Structural abnormalities in the thalamus of migraineurs with aura: a multiparametric study at 3 T.

BACKGROUND AND OBJECTIVES: The thalamus exerts a pivotal role in pain processing and cortical excitability control, and migraine is characterized by repeated pain attacks and abnormal cortical habituation to excitatory stimuli. This work aimed at studying the microstructure of the thalamus in migraine patients using an innovative multiparametric approach at high-field magnetic resonance imaging (MRI). DESIGN: We examined 37 migraineurs (22 without aura, MWoA, and 15 with aura, MWA) as well as 20 healthy controls (HC) in a 3-T MRI equipped with a 32-channel coil. We acquired whole-brain T1 relaxation maps and computed magnetization transfer ratio (MTR), generalized fractional anisotropy, and T2* maps to probe microstructural and connectivity integrity and to assess iron deposition. We also correlated the obtained parametric values with the average monthly frequency of migraine attacks and disease duration. RESULTS: T1 relaxation time was significantly shorter in the thalamus of MWA patients compared with MWoA (P < 0.001) and HC (P ≤ 0.01); in addition, MTR was higher and T2* relaxation time was shorter in MWA than in MWoA patients (P < 0.05, respectively). These data reveal broad microstructural alterations in the thalamus of MWA patients compared with MWoA and HC, suggesting increased iron deposition and myelin content/cellularity. However, MWA and MWoA patients did not show any differences in the thalamic nucleus involved in pain processing in migraine. CONCLUSIONS: There are broad microstructural alterations in the thalamus of MWA patients that may underlie abnormal cortical excitability control leading to cortical spreading depression and visual aura.

Cortical thickness and grey-matter volume anomaly detection in individual MRI scans: Comparison of two methods.

Over the past decades, morphometric analysis of brain MRI has contributed substantially to the understanding of healthy brain structure, development and aging as well as to improved characterisation of disease related pathologies. Certified commercial tools based on normative modeling of these metrics are meanwhile available for diagnostic purposes, but they are cost intensive and their clinical evaluation is still in its infancy. Here we have compared the performance of "ScanOMetrics", an open-source research-level tool for detection of statistical anomalies in individual MRI scans, depending on whether it is operated on the output of FreeSurfer or of the deep learning based brain morphometry tool DL + DiReCT. When applied to the public OASIS3 dataset, containing patients with Alzheimer's disease (AD) and healthy controls (HC), cortical thickness anomalies in patient scans were mainly detected in regions that are known as predilection areas of cortical atrophy in AD, regardless of the software used for extraction of the metrics. By contrast, anomaly detections in HCs were up to twenty-fold reduced and spatially unspecific using both DL + DiReCT and FreeSurfer. Progression of the atrophy pattern with clinical dementia rating (CDR) was clearly observable with both methods. DL + DiReCT provided results in less than 25 min, more than 15 times faster than FreeSurfer. This difference in computation time might be relevant when considering application of this or similar methodology as diagnostic decision support for neuroradiologists.

Normative volumes and relaxation times at 3T during brain development.

While research has unveiled and quantified brain markers of abnormal neurodevelopment, clinicians still work with qualitative metrics for MRI brain investigation. The purpose of the current article is to bridge the knowledge gap between case-control cohort studies and individual patient care. Here, we provide a unique dataset of seventy-three 3-to-17 years-old healthy subjects acquired with a 6-minute MRI protocol encompassing T1 and T2 relaxation quantitative sequence that can be readily implemented in the clinical setting; MP2RAGE for T1 mapping and the prototype sequence GRAPPATINI for T2 mapping. White matter and grey matter volumes were automatically quantified. We further provide normative developmental curves based on these two imaging sequences; T1, T2 and volume normative ranges with respect to age were computed, for each ROI of a pediatric brain atlas. This open-source dataset provides normative values allowing to position individual patients acquired with the same protocol on the brain maturation curve and as such provides potentially useful quantitative biomarkers facilitating precise and personalized care.

Pervasive alterations of intra-axonal volume and network organization in young children with a 16p11.2 deletion.

Reciprocal Copy Number Variants (CNVs) at the 16p11.2 locus confer high risk for autism spectrum disorder (ASD) and other neurodevelopmental disorders (NDDs). Morphometric MRI studies have revealed large and pervasive volumetric alterations in carriers of a 16p11.2 deletion. However, the specific neuroanatomical mechanisms underlying such alterations, as well as their developmental trajectory, are still poorly understood. Here we explored differences in microstructural brain connectivity between 24 children carrying a 16p11.2 deletion and 66 typically developing (TD) children between 2 and 8 years of age. We found a large pervasive increase of intra-axonal volume widespread over a high number of white matter tracts. Such microstructural alterations in 16p11.2 deletion children were already present at an early age, and led to significant changes in the global efficiency and integration of brain networks mainly associated to language, motricity and socio-emotional behavior, although the widespread pattern made it unlikely to represent direct functional correlates. Our results shed light on the neuroanatomical basis of the previously reported increase of white matter volume, and align well with analogous evidence of altered axonal diameter and synaptic function in 16p11.2 mice models. We provide evidence of a prevalent mechanistic deviation from typical maturation of brain structural connectivity associated with a specific biological risk to develop ASD. Future work is warranted to determine how this deviation contributes to the emergence of symptoms observed in young children diagnosed with ASD and other NDDs.

Widespread occurrence of non-canonical transcription termination by human RNA polymerase III.

Human RNA polymerase (Pol) III-transcribed genes are thought to share a simple termination signal constituted by four or more consecutive thymidine residues in the coding DNA strand, just downstream of the RNA 3'-end sequence. We found that a large set of human tRNA genes (tDNAs) do not display any T(≥4) stretch within 50 bp of 3'-flanking region. In vitro analysis of tDNAs with a distanced T(≥4) revealed the existence of non-canonical terminators resembling degenerate T(≥5) elements, which ensure significant termination but at the same time allow for the production of Pol III read-through pre-tRNAs with unusually long 3' trailers. A panel of such non-canonical signals was found to direct transcription termination of unusual Pol III-synthesized viral pre-miRNA transcripts in gammaherpesvirus 68-infected cells. Genome-wide location analysis revealed that human Pol III tends to trespass into the 3'-flanking regions of tDNAs, as expected from extensive terminator read-through. The widespread occurrence of partial termination suggests that the Pol III primary transcriptome in mammals is unexpectedly enriched in 3'-trailer sequences with the potential to contribute novel functional ncRNAs.

Learning by Heart or with Heart: Brain Asymmetry Reflects Pedagogical Practices.

Brain hemispheres develop rather symmetrically, except in the case of pathology or intense training. As school experience is a form of training, the current study tested the influence of pedagogy on morphological development through the cortical thickness (CTh) asymmetry index (AI). First, we compared the CTh AI of 111 students aged 4 to 18 with 77 adults aged > 20. Second, we investigated the CTh AI of the students as a function of schooling background (Montessori or traditional). At the whole-brain level, CTh AI was not different between the adult and student groups, even when controlling for age. However, pedagogical experience was found to impact CTh AI in the temporal lobe, within the parahippocampal (PHC) region. The PHC region has a functional lateralization, with the right PHC region having a stronger involvement in spatiotemporal context encoding, while the left PHC region is involved in semantic encoding. We observed CTh asymmetry toward the left PHC region for participants enrolled in Montessori schools and toward the right for participants enrolled in traditional schools. As these participants were matched on age, intelligence, home-life and socioeconomic conditions, we interpret this effect found in memory-related brain regions to reflect differences in learning strategies. Pedagogy modulates how new concepts are encoded, with possible long-term effects on knowledge transfer.

Bundle-Specific Axon Diameter Index as a New Contrast to Differentiate White Matter Tracts.

In the central nervous system of primates, several pathways are characterized by different spectra of axon diameters. In vivo methods, based on diffusion-weighted magnetic resonance imaging, can provide axon diameter index estimates non-invasively. However, such methods report voxel-wise estimates, which vary from voxel-to-voxel for the same white matter bundle due to partial volume contributions from other pathways having different microstructure properties. Here, we propose a novel microstructure-informed tractography approach, COMMITAxSize, to resolve axon diameter index estimates at the streamline level, thus making the estimates invariant along trajectories. Compared to previously proposed voxel-wise methods, our formulation allows the estimation of a distinct axon diameter index value for each streamline, directly, furnishing a complementary measure to the existing calculation of the mean value along the bundle. We demonstrate the favourable performance of our approach comparing our estimates with existing histologically-derived measurements performed in the corpus callosum and the posterior limb of the internal capsule. Overall, our method provides a more robust estimation of the axon diameter index of pathways by jointly estimating the microstructure properties of the tissue and the macroscopic organisation of the white matter connectivity.

Sex differences in sensory processing in children with autism spectrum disorder.

Despite the high prevalence of sensory processing difficulties in children with autism spectrum disorder (ASD), little research has focused on the sex differences in sensory processing. Furthermore, there is a lack of knowledge on the female-specific symptoms of ASD, contributing to later referral, diagnosis and intervention. In this study, we examined the sex differences in sensory processing symptoms in large cohorts of ASD children (N = 168; 26 females, 142 males) and typically developing (TD) children (N = 439; 209 females, 230 males). For this, we translated the sensory processing measure (SPM) and SPM - Preschool (SPM-P) Home Forms to French. The SPM/SPM-P are parent/caregiver questionnaires that assess typical behavioral responses to sensory stimuli. Overall, our results showed that the magnitude of the differences in sensory processing between males and females is larger in ASD children relative to TD children, with females showing more severe symptoms in Hearing, as well as Balance and Motion subscales. Additionally, linear discriminant analysis showed that the SPM/SPM-P are good at discriminating TD children from ASD, children with higher accuracy rates for females than for males. These findings are discussed in light of the heterogeneity of sensory processing difficulties present in ASD. Overall, our results suggest that there seem to be female-specific profiles in sensory processing difficulties in ASD. Implications of findings concerning sex differences in sensory processing and their potential for improving identification and diagnosis of ASD females are discussed. LAY SUMMARY: The present study examined sex differences in behavioral responses to sensory stimuli in children with autism spectrum disorder (ASD), and typically developing (TD) children. While there is a small trend for TD males to show more sensory processing atypicalities, female ASD children show significantly more atypical responses compared to their male counterparts. This has important implications for characterizing female autism profiles, and ultimately improving the chance for earlier detection, diagnosis and treatment.

Touch and olfaction/taste differentiate children carrying a 16p11.2 deletion from children with ASD.

BACKGROUND: Sensory processing atypicalities are frequent in Autism Spectrum Disorder (ASD) and neurodevelopmental disorders (NDD). Different domains of sensory processing appear to be differentially altered in these disorders. In this study, we explored the sensory profile of two clinical cohorts, in comparison with a sample of typically developing children. METHODS: Behavioral responses to sensory stimuli were assessed using the Sensory Processing Measure (parent-report questionnaire). We included 121 ASD children, 17 carriers of the 16p11.2 deletion (Del 16p11.2) and 45 typically developing (TD) children. All participants were aged between 2 and 12 years. Additional measures included the Tactile Defensiveness and Discrimination Test-Revised, Wechsler Intelligence Scales and Autism Diagnostic Observation Schedule (ADOS-2). Statistical analyses included MANCOVA and regression analyses. RESULTS: ASD children score significantly higher on all SPM subscales compared to TD. Del16p11.2 also scored higher than TD on all subscales except for tactile and olfactory/taste processing, in which they score similarly to TD. When assessing sensory modulation patterns (hyper-, hypo-responsiveness and seeking), ASD did not significantly differ from del16p11.2. Both groups had significantly higher scores across all patterns than the TD group. There was no significant association between the SPM Touch subscale and the TDDT-R. LIMITATIONS: Sensory processing was assessed using a parent-report questionnaire. Even though it captures observable behavior, a questionnaire does not assess sensory processing in all its complexity. The sample size of the genetic cohort and the small subset of ASD children with TDDT-R data render some of our results exploratory. Divergence between SPM Touch and TDDT-R raises important questions about the nature of the process that is assessed. CONCLUSIONS: Touch and olfaction/taste seem to be particularly affected in ASD children compared to del16p11.2. These results indicate that parent report measures can provide a useful perspective on behavioral expression. Sensory phenotyping, when combined with neurobiological and psychophysical methods, might have the potential to provide a better understanding of the sensory processing in ASD and in other NDD.

Robust Monte-Carlo Simulations in Diffusion-MRI: Effect of the Substrate Complexity and Parameter Choice on the Reproducibility of Results.

Monte-Carlo Diffusion Simulations (MCDS) have been used extensively as a ground truth tool for the validation of microstructure models for Diffusion-Weighted MRI. However, methodological pitfalls in the design of the biomimicking geometrical configurations and the simulation parameters can lead to approximation biases. Such pitfalls affect the reliability of the estimated signal, as well as its validity and reproducibility as ground truth data. In this work, we first present a set of experiments in order to study three critical pitfalls encountered in the design of MCDS in the literature, namely, the number of simulated particles and time steps, simplifications in the intra-axonal substrate representation, and the impact of the substrate's size on the signal stemming from the extra-axonal space. The results obtained show important changes in the simulated signals and the recovered microstructure features when changes in those parameters are introduced. Thereupon, driven by our findings from the first studies, we outline a general framework able to generate complex substrates. We show the framework's capability to overcome the aforementioned simplifications by generating a complex crossing substrate, which preserves the volume in the crossing area and achieves a high packing density. The results presented in this work, along with the simulator developed, pave the way toward more realistic and reproducible Monte-Carlo simulations for Diffusion-Weighted MRI.