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Background and Hypothesis Although the thalamus has a central role in schizophrenia pathophysiology, contributing to sensory, cognitive, and sleep alterations, the nature and dynamics of the alterations occurring within this structure remain largely elusive. Using a multimodal magnetic resonance imaging (MRI) approach, we examined whether anomalies: (1) differ across thalamic subregions/nuclei, (2) are already present in the early phase of psychosis (EP), and (3) worsen in chronic schizophrenia (SCHZ). Study Design T1-weighted and diffusion-weighted images were analyzed to estimate gray matter concentration (GMC) and microstructural parameters obtained from the spherical mean technique (intra-neurite volume fraction [VFINTRA)], intra-neurite diffusivity [DIFFINTRA], extra-neurite mean diffusivity [MDEXTRA], extra-neurite transversal diffusivity [TDEXTRA]) within 7 thalamic subregions. Results Compared to age-matched controls, the thalamus of EP patients displays previously unreported widespread microstructural alterations (VFINTRA decrease, TDEXTRA increase) that are associated with similar alterations in the whole brain white matter, suggesting altered integrity of white matter fiber tracts in the thalamus. In both patient groups, we also observed more localized and heterogenous changes (either GMC decrease, MDEXTRA increase, or DIFFINTRA decrease) in mediodorsal, posterior, and ventral anterior parts of the thalamus in both patient groups, suggesting that the nature of the alterations varies across subregions. GMC and DIFFINTRA in the whole thalamus correlate with global functioning, while DIFFINTRA in the subregion encompassing the medial pulvinar is significantly associated with negative symptoms in SCHZ. Conclusion Our data reveals both widespread and more localized thalamic anomalies that are already present in the early phase of psychosis.

Given the unpredictable rapid onset and ubiquitous consequences of weight gain induced by antipsychotics (AP), there is a pressing need to get insights into the underlying processes at the brain system level that will allow stratification of “at risk” patients. The pathophysiological hypothesis at hand is focused on brain networks governing impulsivity that are modulated by neuro-inflammatory processes. To this aim, we investigated brain anatomy and functional connectivity in patients with early psychosis (median age: 23 years, IQR = 21–27) using anthropometric data and magnetic resonance imaging acquired one month to one year after initiation of AP medication. Our analyses included 19 patients with high and rapid weight gain (i.e., ≥ 5% from baseline weight after one month) and 23 patients with low weight gain (i.e., P = 0.03). Here, the observed brain differences comprised nodes of impulsivity networks - reduced frontal lobe grey matter volume (Pcorrected=0.007) and higher striatal volume (Pcorrected=0.048) paralleled by disruption of fronto-striatal functional connectivity (R=-0.32; P = 0.04). Weight gain was associated with the inflammatory biomarker plasminogen activator inhibitor-1 (β = 4.9, P = 0.002). There was no significant association between increased BMI or weight gain and brain anatomy characteristics in both cohorts of young and middle-aged healthy individuals. Our findings support the notion of weight gain in treated psychotic patients associated with poor impulse control, impulsivity-related brain networks and chronic inflammation.

Sulcal width, defined as the physical distance between opposing sulcal banks, has shown promise as a biomarker. We present the first method to obtain a vertex-wise representation of this metric directly on the brain’s cortical surface. The algorithm samples the surface at different depths and estimates the distances between the opposing sulcal banks. The method is validated against a simulated sulcus and compared to other sulcal width tools based on regions of interest, showing solid correlations between the proposed algorithm and two widely-used reference methods. A vertex-wise assessment of the sulcal width is carried out by evaluating the correlation between sulcal width and age in a sample of an aging population, revealing clusters in the central, cingulate, and temporal sulcus regions associating wider sulci for older participants. The results confirm that the algorithm is reliable for obtaining sulcal width maps, allowing for vertex-wise analyses, and providing aggregated measures similar to the existing methods. The present algorithm is publicly available viahttps://github.com/HGGM-LIM/SWiM.

The structural complexity of the thalamus, due to its mixed composition of gray and white matter, make it challenging to disjoint and quantify each tissue contribution to the thalamic anatomy. This work promotes the use of partial‐volume‐based over probabilistic‐based tissue segmentation approaches to better capture thalamic gray matter differences between patients at different stages of psychosis (early and chronic) and healthy controls. The study was performed on a cohort of 23 patients with schizophrenia, 41 with early psychosis and 69 age and sex‐matched healthy subjects. Six tissue segmentation approaches were employed to obtain the gray matter concentration/probability images. The statistical tests were applied at three different anatomical scales: whole thalamus, thalamic subregions and voxel‐wise. The results suggest that the partial volume model estimation of gray matter is more sensitive to detect atrophies within the thalamus of patients with psychosis. However all the methods detected gray matter deficit in the pulvinar, particularly in early stages of psychosis. This study demonstrates also that the gray matter decrease varies nonlinearly with age and between nuclei. While a gray matter loss was found in the pulvinar of patients in both stages of psychosis, reduced gray matter in the mediodorsal was only observed in early psychosis subjects. Finally, our analyses point to alterations in a sub‐region comprising the lateral posterior and ventral posterior nuclei. The obtained results reinforce the hypothesis that thalamic gray matter assessment is more reliable when the tissues segmentation method takes into account the partial volume effect., Three partial‐volume‐based and three probabilistic‐based tissue segmentation approaches were employed to assess thalamic gray matter integrity in patients at different stages of psychosis (early and chronic). This study demonstrates also that the gray matter decrease varies nonlinearly with age and between nuclei. The obtained results reinforce the hypothesis that thalamic gray matter assessment is more reliable when the tissues segmentation method takes into account the partial volume effect.

Functional magnetic resonance imaging (fMRI) is a non-invasive technique that facilitates the study of brain activity by measuring changes in blood flow. Brain activity signals can be recorded during the alternate performance of given tasks, that is, task fMRI (tfMRI), or during resting-state, that is, resting-state fMRI (rsfMRI), as a measure of baseline brain activity. This contributes to the understanding of how the human brain is organized in functionally distinct subdivisions. fMRI experiments from high-resolution scans provide hundred of thousands of longitudinal signals for each individual, corresponding to brain activity measurements over each voxel of the brain along the duration of the experiment. In this context, we propose novel visualization techniques for high-dimensional functional data relying on depth-based notions that enable computationally efficient 2-dim representations of fMRI data, which elucidate sample composition, outlier presence, and individual variability. We believe that this previous step is crucial to any inferential approach willing to identify neuroscientific patterns across individuals, tasks, and brain regions. We present the proposed technique via an extensive simulation study, and demonstrate its application on a motor and language tfMRI experiment. Agencia Estatal de Investigación, Spain, Grant/Award Number: PID2019-109196GB-I00; Ministerio de Economía y Competitividad, Spain, Grant/Award Numbers: ECO2015-66593-P, MTM2014-56535-R. The authors are grateful to Luis Marcos Vidal and Daniel Martín de Blas for their insight on the tfMRI dataset. Sí

Fetal brain diffusion magnetic resonance images are often acquired with a lower through-plane than in-plane resolution. This anisotropy is often overcome by classical upsampling methods such as linear or cubic interpolation. In this work, we employ an unsupervised learning algorithm using an autoencoder neural network to enhance the through-plane resolution by leveraging a large amount of data. Our framework, which can also be used for slice outliers replacement, overperformed conventional interpolations quantitatively and qualitatively on pre-term newborns of the developing Human Connectome Project. The evaluation was performed on both the original diffusion-weighted signal and on the estimated diffusion tensor maps. A byproduct of our autoencoder was its ability to act as a denoiser. The network was able to generalize to fetal data with different levels of motion and we qualitatively showed its consistency, hence supporting the relevance of pre-term datasets to improve the processing of fetal brain images.

Objective: SPG4 is an autosomal dominant pure form of hereditary spastic paraplegia (HSP) caused by mutations in the SPAST gene. HSP is considered an upper motor neuron disorder characterized by progressive retrograde degeneration, or "dying-back" phenomenon, of the corticospinal tract's longest axons. Neuroimaging studies mainly focus on white matter changes and, although previous studies reported cortical thinning in complicated HSP forms, cortical changes remain unclear in SPG4 patients. This work aimed to compare changes in white matter microstructure and cortical thickness between 12 SPG4 patients and 22 healthy age-matched controls. We also explore whether white matter alterations are related to cortical thickness and their correlation with clinical symptoms. Methods: we used fixel-based analysis, an advanced diffusion-weighted imaging technique, and probabilistic tractography of the corticospinal tracts. We also analyzed cortical morphometry using whole-brain surface-based and atlas-based methods in sensorimotor areas. Results: SPG4 patients showed bilateral involvement in the corticospinal tracts; this was more intense in the distal portion than in the upper segments and was associated with the degree of clinical impairment. We found a significant correlation between disease severity and fiber density and cross-section of the corticospinal tracts. Furthermore, corticospinal tract changes were significantly correlated with bilateral cortical thinning in the precentral gyrus in SPG4 patients. Conclusions: Our data point to axonal damage of the corticospinal motor neurons in SPG4 patients might be related to cortical thinning in motor regions.

Visual object naming is a complex cognitive process that engages an interconnected network of cortical regions moving from occipitotemporal to anterior-inferior temporal cortices, and extending into the inferior frontal cortex. Naming can fail for diverse reasons, and different stages of the naming multi-step process appear to be reliant upon the integrity of different neuroanatomical locations. While the neural correlates of semantic errors have been extensively studied, the neural basis of omission errors remains relatively unspecified. Although a strong line of evidence supports an association between anterior temporal lobe damage and semantic errors, there are some studies suggesting that the anterior temporal lobe could be also associated with omissions. However, support for this hypothesis comes from studies with patients in whom damage affected extensive brain regions, sometimes bilaterally. Here, we availed of a group of 12 patients with epilepsy associated with a small lesion at the tip of the left temporal pole. Using an unbiased surface-based morphometry methodology, we correlated two morphological features with errors observed during visual naming. Analyses revealed a correlation between omission errors and reduced local gyrification index in three cortical clusters: one in the left anteromedial temporal lobe region (AMTL) and two in the left anterior cingulate cortex (ACC). Our findings support the view that regions in ACC and AMTL are critical structures within a network engaged in word selection from semantics.

Accurate characterization of in utero human brain maturation is critical as it involves complex interconnected structural and functional processes that may influence health later in life. Magnetic resonance imaging is a powerful tool complementary to the ultrasound gold standard to monitor the development of the fetus, especially in the case of equivocal neurological patterns. However, the number of acquisitions of satisfactory quality available in this cohort of sensitive subjects remains scarce, thus hindering the validation of advanced image processing techniques. Numerical simulations can mitigate these limitations by providing a controlled environment with a known ground truth. In this work, we present a flexible numerical framework for clinical T2-weighted Half-Fourier Acquisition Single-shot Turbo spin Echo of the fetal brain. The realistic setup, including stochastic motion of the fetus as well as intensity non-uniformities, provides images of the fetal brain throughout development that are comparable to real data acquired in clinical routine. A case study on super-resolution reconstruction of the fetal brain from synthetic motion-corrupted 2D low-resolution series further demonstrates the potential of such a simulator to optimize post-processing methods for fetal brain magnetic resonance imaging.

SPG4 is an autosomal dominant pure form of hereditary spastic paraplegia (HSP) caused by mutations in the SPAST gene. HSP is considered an upper motor neuron disorder characterized by progressive spasticity and weakness of the lower limbs caused by degeneration of the corticospinal tract. In other neurodegenerative motor disorders, the thalamus and basal ganglia are affected, with a considerable impact on disease progression. However, only a few works have studied these brain structures in HSP, mainly in complex forms of this disease. Our research aims to detect potential alterations in the volume and shape of the thalamus and various basal ganglia structures by comparing 12 patients with pure HSP and 18 healthy controls. We used two neuroimaging procedures: automated segmentation of the subcortical structures (thalamus, hippocampus, caudate nucleus, globus pallidus, and putamen) in native space and shape analysis of the structures. We found a significant reduction in thalamic volume bilaterally, as well as an inward deformation, mainly in the sensory-motor thalamic regions in patients with pure HSP and a mutation in SPG4. We also observed a significant negative correlation between the shape of the thalamus and clinical scores (the Spastic Paraplegia Rating Scale score and disease duration). Moreover, we found a ‘Group × Age’ interaction that was closely related to the severity of the disease. No differences in volume or in shape were found in the remaining subcortical structures studied. Our results suggest that changes in structure of the thalamus could be an imaging biomarker of disease progression in pHSP.

SPG4 is an autosomal dominant pure form of hereditary spastic paraplegia (HSP) caused by mutations in the SPAST gene. HSP is considered an upper motor neuron disorder characterized by progressive spasticity and weakness of the lower limbs caused by degeneration of the corticospinal tract. In other neurodegenerative motor disorders, the thalamus and basal ganglia are affected, with a considerable impact on disease progression. However, only a few works have studied these brain structures in HSP, mainly in complex forms of this disease. Our research aims to detect potential alterations in the volume and shape of the thalamus and various basal ganglia structures by comparing 12 patients with pure HSP and 18 healthy controls. We used two neuroimaging procedures: automated segmentation of the subcortical structures (thalamus, hippocampus, caudate nucleus, globus pallidus, and putamen) in native space and shape analysis of the structures. We found a significant reduction in thalamic volume bilaterally, as well as an inward deformation, mainly in the sensory-motor thalamic regions in patients with pure HSP and a mutation in SPG4. We also observed a significant negative correlation between the shape of the thalamus and clinical scores (the Spastic Paraplegia Rating Scale score and disease duration). Moreover, we found a 'Group × Age' interaction that was closely related to the severity of the disease. No differences in volume or in shape were found in the remaining subcortical structures studied. Our results suggest that changes in structure of the thalamus could be an imaging biomarker of disease progression in pHSP.

Structural connectivity in the brain is typically studied by reducing its observation to a single spatial resolution. However, the brain possesses a rich architecture organized over multiple scales linked to one another. We explored the multiscale organization of human connectomes using datasets of healthy subjects reconstructed at five different resolutions. We found that the structure of the human brain remains self-similar when the resolution of observation is progressively decreased by hierarchical coarse-graining of the anatomical regions. Strikingly, a geometric network model, where distances are not Euclidean, predicts the multiscale properties of connectomes, including self-similarity. The model relies on the application of a geometric renormalization protocol which decreases the resolution by coarse-graining and averaging over short similarity distances. Our results suggest that simple organizing principles underlie the multiscale architecture of human structural brain networks, where the same connectivity law dictates short- and long-range connections between different brain regions over many resolutions. The implications are varied and can be substantial for fundamental debates, such as whether the brain is working near a critical point, as well as for applications including advanced tools to simplify the digital reconstruction and simulation of the brain.

Autism spectrum disorders (ASD) and early‐onset psychosis (EOP) are neurodevelopmental disorders that share genetic, clinical and cognitive facets; it is unclear if these disorders also share spatially overlapping cortical thickness (CT) and surface area (SA) abnormalities. MRI scans of 30 ASD, 29 patients with early‐onset first‐episode psychosis (EO‐FEP) and 26 typically developing controls (TD) (age range 10–18 years) were analyzed by the FreeSurfer suite to calculate vertex‐wise estimates of CT, SA, and cortical volume. Two publicly available datasets of ASD and EOP (age range 7–18 years and 5–17 years, respectively) were used for replication analysis. ASD and EO‐FEP had spatially overlapping areas of cortical thinning and reduced SA in the bilateral insula (all p’s

A commonly adopted approach to carry out detection tasks in medical imaging is to rely on an initial segmentation. However, this approach strongly depends on voxel-wise annotations which are repetitive and time-consuming to draw for medical experts. An interesting alternative to voxel-wise masks are so-called “weak” labels: these can either be coarse or oversized annotations that are less precise, but noticeably faster to create. In this work, we address the task of brain aneurysm detection as a patch-wise binary classification with weak labels, in contrast to related studies that rather use supervised segmentation methods and voxel-wise delineations. Our approach comes with the non-trivial challenge of the data set creation: as for most focal diseases, anomalous patches (with aneurysm) are outnumbered by those showing no anomaly, and the two classes usually have different spatial distributions. To tackle this frequent scenario of inherently imbalanced, spatially skewed data sets, we propose a novel, anatomically-driven approach by using a multi-scale and multi-input 3D Convolutional Neural Network (CNN). We apply our model to 214 subjects (83 patients, 131 controls) who underwent Time-Of-Flight Magnetic Resonance Angiography (TOF-MRA) and presented a total of 111 unruptured cerebral aneurysms. We compare two strategies for negative patch sampling that have an increasing level of difficulty for the network and we show how this choice can strongly affect the results. To assess whether the added spatial information helps improving performances, we compare our anatomically-informed CNN with a baseline, spatially-agnostic CNN. When considering the more realistic and challenging scenario including vessel-like negative patches, the former model attains the highest classification results (accuracy\(\simeq \)95%, AUROC\(\simeq \)0.95, AUPR\(\simeq \)0.71), thus outperforming the baseline.

Error monitoring allows us to adapt to an inherently dynamic environment. Error monitoring relies mainly on the anterior cingulate cortex (ACC). Its protracted maturation suggests a window for experience-dependent plasticity. To investigate this possibility, we measured error-related response-locked potentials components with morphometric magnetic resonance imaging (MRI) measures of the ACC in twenty-six schoolchildren, aged 6-12 years, enrolled in either a Montessori or a traditional curriculum. We show that the caudal ACC undergoes significant morphometric changes during this age range that relate to error detection ERP activity. Furthermore, pedagogy modulates source localization activity related to error detection within the caudal ACC amongst others. We provide early evidence for a window of opportunity regarding the acquisition of error monitoring skills, with implications for educational practices.

[Image: see text] COVER ILLUSTRATION This image aims to reflect the parallelism that exists between the morphometric brain changes that occur during pregnancy and those that take place during adolescence. The image has no copyright and the neurons were inspired in one of the Ramon y Cajal drawings.

Decades of research have increased the understanding of the contribution of the anterior temporal lobes (ATLs) to semantic cognition. Nonetheless, whether semantic processing of different types of information show a selective relationship with left and right ATLs, or whether semantic processing in the ATLs is independent of the modality of the input is currently unknown. There exists evidence supporting each of these alternatives. A fundamental objection to these findings is that they were obtained from studies with patients with brain damage affecting extensive regions, sometimes bilaterally. In the current study, we assessed a group of 38 temporal lobe epilepsy (TLE) patients with either left or right small epileptogenic lesions with a battery of commonly used semantic tasks that tested verbal and non-verbal semantic processing. We found that left TLE patients exhibited worse performance than controls on the verbal semantic tasks, as expected, but also on the non-verbal semantic task. On the other hand, performance of the right TLE group did not differ from controls on the non-verbal task, but was worse on a semantic fluency task. When performance between patient groups was compared, we found that left TLE not only did worse than right TLE on the naming task, but also on the non-verbal associative memory task. When considered together, current data do not support a strong view of input modality differences between left and right ATLs. Additionally, they provide evidence indicating that the left and right ATLs do not make similar contributions to a singular functional system for semantic representation.

Math-gifted subjects are characterized by above-age performance in intelligence tests, exceptional creativity, and high task commitment. Neuroimaging studies reveal enhanced functional brain organization and white matter microstructure in the frontoparietal executive network of math-gifted individuals. However, the cortical morphometry of these subjects remains largely unknown. The main goal of this study was to compare the cortical morphometry of math-gifted adolescents with that of an age- and IQ-matched control group. We used surface-based methods to perform a vertex-wise analysis of cortical thickness and surface area. Our results show that math-gifted adolescents present a thinner cortex and a larger surface area in key regions of the frontoparietal and default mode networks, which are involved in executive processing and creative thinking, respectively. The combination of reduced cortical thickness and larger surface area suggests above-age neural maturation of these networks in math-gifted individuals. Hum Brain Mapp 37:1893-1902, 2016. © 2016 Wiley Periodicals, Inc.

According to the so-called disconnection hypothesis, the loss of synaptic inputs from the medial temporal lobes (MTL) in Alzheimer's disease (AD) may lead to reduced activity of target neurons in cortical areas and, consequently, to decreased cerebral blood flow (CBF) in those areas. The aim of this study was to assess whether hypoperfusion in parietotemporal and frontal cortices of patients with mild cognitive impairment who converted to AD (MCI-c) and patients with mild AD is associated with atrophy in the MTL and/or microstructural changes in the white matter (WM) tracts connecting these areas. We assessed these relationships by investigating correlations between CBF in hypoperfused areas, mean cortical thickness in atrophied regions of the MTL, and fractional anisotropy (FA) in WM tracts. In the MCI-c group, a strong correlation was observed between CBF of the superior parietal gyri and FA in the parahippocampal tracts (left: r = 0.90, p < 0.0001; right: r = 0.597, p = 0.024), and between FA in the right parahippocampal tract and the right precuneus (r = 0.551, p = 0.041). No significant correlations between CBF in hypoperfused regions and FA in the WM tract were observed in the AD group. These results suggest an association between perfusion deficits and altered WM tracts in prodromal AD, while microvasculature impairments may have a greater influence in more advanced stages. We did not find correlations between cortical thinning in the medial temporal lobes and decreased FA in the WM tracts of the limbic system in either group.