Yasser Alemán-Gómez

The Human Cerebral Cortex Flattens during Adolescence

The human cerebral cortex appears to shrink during adolescence. To delineate the dynamic morphological changes involved in this process, 52 healthy male and female adolescents (11–17 years old) were neuroimaged twice using magnetic resonance imaging, approximately 2 years apart. Using a novel morphometric analysis procedure combining the FreeSurfer and BrainVisa image software suites, we quantified global and lobar change in cortical thickness, outer surface area, the gyrification index, the average Euclidean distance between opposing sides of the white matter surface (gyral white matter thickness), the convex (“exposed”) part of the outer cortical surface (hull surface area), sulcal length, depth, and width. We found that the cortical surface flattens during adolescence. Flattening was strongest in the frontal and occipital cortices, in which significant sulcal widening and decreased sulcal depth co-occurred. Globally, sulcal widening was associated with cortical thinning and, for the frontal cortex, with loss of surface area. For the other cortical lobes, thinning was related to gyral white matter expansion. The overall flattening of the macrostructural three-dimensional architecture of the human cortex during adolescence thus involves changes in gray matter and effects of the maturation of white matter.

White Matter Microstructure Correlates of Mathematical Giftedness and Intelligence Quotient

Recent functional neuroimaging studies have shown differences in brain activation between mathematically gifted adolescents and controls. The aim of this study was to investigate the relationship between mathematical giftedness, intelligent quotient (IQ), and the microstructure of white matter tracts in a sample composed of math‐gifted adolescents and aged‐matched controls. Math‐gifted subjects were selected through a national program based on detecting enhanced visuospatial abilities and creative thinking. We used diffusion tensor imaging to assess white matter microstructure in neuroanatomical connectivity. The processing included voxel‐wise and region of interest‐based analyses of the fractional anisotropy (FA), a parameter which is purportedly related to white matter microstructure. In a whole‐sample analysis, IQ showed a significant positive correlation with FA, mainly in the corpus callosum, supporting the idea that efficient information transfer between hemispheres is crucial for higher intellectual capabilities. In addition, math‐gifted adolescents showed increased FA (adjusted for IQ) in white matter tracts connecting frontal lobes with basal ganglia and parietal regions. The enhanced anatomical connectivity observed in the forceps minor and splenium may underlie the greater fluid reasoning, visuospatial working memory, and creative capabilities of these children. Hum Brain Mapp 35:2619–2631, 2014.

Cerebral Blood Flow is an Earlier Indicator of Perfusion Abnormalities than Cerebral Blood Volume in Alzheimer's Disease

The purpose of this study was to elucidate whether cerebral blood flow (CBF) can better characterize perfusion abnormalities in predementia stages of Alzheimers disease (AD) than cerebral blood volume (CBV) and whether cortical atrophy is more associated with decreased CBV or with decreased CBF. We compared measurements of CBV, CBF, and mean cortical thickness obtained from magnetic resonance images in a group of healthy controls, patients with mild cognitive impairment (MCI) who converted to AD after 2 years of clinical follow-up (MCI-c), and patients with mild AD. A significant decrease in perfusion was detected in the parietal lobes of the MCI-c patients with CBF parametric maps but not with CBV maps. In the MCI-c group, a negative correlation between CBF values and cortical thickness in the right parahippocampal gyrus suggests an increase in CBF that depends on cortical atrophy in predementia stages of AD. Our study also suggests that CBF deficits appear before CBV deficits in the progression of AD, as CBV abnormalities were only detected at the AD stage, whereas CBF changes were already detected in the MCI stage. These results confirm the hypothesis that CBF is a more sensitive parameter than CBV for perfusion abnormalities in MCI-c patients.

Cortical morphology of adolescents with bipolar disorder and with schizophrenia

INTRODUCTION Recent evidence points to overlapping decreases in cortical thickness and gyrification in the frontal lobe of patients with adult-onset schizophrenia and bipolar disorder with psychotic symptoms, but it is not clear if these findings generalize to patients with a disease onset during adolescence and what may be the mechanisms underlying a decrease in gyrification. METHOD This study analyzed cortical morphology using surface-based morphometry in 92 subjects (age range 11-18 years, 52 healthy controls and 40 adolescents with early-onset first-episode psychosis diagnosed with schizophrenia (n=20) or bipolar disorder with psychotic symptoms (n=20) based on a two year clinical follow up). Average lobar cortical thickness, surface area, gyrification index (GI) and sulcal width were compared between groups, and the relationship between the GI and sulcal width was assessed in the patient group. RESULTS Both patients groups showed decreased cortical thickness and increased sulcal width in the frontal cortex when compared to healthy controls. The schizophrenia subgroup also had increased sulcal width in all other lobes. In the frontal cortex of the combined patient group sulcal width was negatively correlated (r=-0.58, p<0.001) with the GI. CONCLUSIONS In adolescents with schizophrenia and bipolar disorder with psychotic symptoms there is cortical thinning, decreased GI and increased sulcal width of the frontal cortex present at the time of the first psychotic episode. Decreased frontal GI is associated with the widening of the frontal sulci which may reduce sulcal surface area. These results suggest that abnormal growth (or more pronounced shrinkage during adolescence) of the frontal cortex represents a shared endophenotype for psychosis.

Deconvolution in diffusion spectrum imaging

Diffusion spectrum magnetic resonance imaging (DSI) allows the estimation of the displacement probability density function (pdf) of water molecules, which contain valuable information about the microgeometry of the medium where the diffusion process occurs. It provides a more general approach to disentangle complex fiber structures in biological tissues because it does not assume any particular model of diffusion; even so, it has a number of limitations that remain unstudied. For instance, the theoretical model used to compute the displacement pdf is based on a Fourier transformation defined in the whole measurement space; however, in practice, it is computed using discrete signals with a finite support. As a consequence, the displacement pdf obtained from the experiments is the convolution between the true pdf and a point spread function (PSF) that completely depends on the experimental sampling scheme. In this work, a general framework to rectify and decontaminate the displacement pdf reconstructed from DSI is introduced. This framework is based on model-free deconvolution techniques that allow obtaining clearer and sharper DSI estimates. The method was tested in synthetic data as well as in real data measured from a healthy human volunteer. The results demonstrated that the angular resolution of DSI can be increased, potentially revealing new real fiber components and reducing both the artefactual peaks and the uncertainty of the local diffusion orientational distribution. Furthermore, the deconvolution process provides scalar maps of quantities derived from the propagator, such as the zero displacement probability, with higher tissue contrast.

Spherical Deconvolution of Multichannel Diffusion MRI Data with Non-Gaussian Noise Models and Spatial Regularization

Spherical deconvolution (SD) methods are widely used to estimate the intra-voxel white-matter fiber orientations from diffusion MRI data. However, while some of these methods assume a zero-mean Gaussian distribution for the underlying noise, its real distribution is known to be non-Gaussian and to depend on many factors such as the number of coils and the methodology used to combine multichannel MRI signals. Indeed, the two prevailing methods for multichannel signal combination lead to noise patterns better described by Rician and noncentral Chi distributions. Here we develop a Robust and Unbiased Model-BAsed Spherical Deconvolution (RUMBA-SD) technique, intended to deal with realistic MRI noise, based on a Richardson-Lucy (RL) algorithm adapted to Rician and noncentral Chi likelihood models. To quantify the benefits of using proper noise models, RUMBA-SD was compared with dRL-SD, a well-established method based on the RL algorithm for Gaussian noise. Another aim of the study was to quantify the impact of including a total variation (TV) spatial regularization term in the estimation framework. To do this, we developed TV spatially-regularized versions of both RUMBA-SD and dRL-SD algorithms. The evaluation was performed by comparing various quality metrics on 132 three-dimensional synthetic phantoms involving different inter-fiber angles and volume fractions, which were contaminated with noise mimicking patterns generated by data processing in multichannel scanners. The results demonstrate that the inclusion of proper likelihood models leads to an increased ability to resolve fiber crossings with smaller inter-fiber angles and to better detect non-dominant fibers. The inclusion of TV regularization dramatically improved the resolution power of both techniques. The above findings were also verified in human brain data.

Regional specificity of thalamic volume deficits in male adolescents with early-onset psychosis

BACKGROUND Thalamic volume deficits are associated with psychosis but it is unclear whether the volume reduction is uniformly distributed or whether it is more severe in particular thalamic regions. AIMS To quantify whole and regional thalamic volume in males with early-onset psychosis and healthy male controls. METHOD Brain scans were obtained for 80 adolescents: 46 individuals with early-onset psychosis with a duration of positive symptoms less than 6 months and 34 healthy controls. All participants were younger than 19 years. Total thalamic volumes were assessed using FreeSurfer and FSL-FIRST, group comparisons of regional thalamic volumes were studied with a surface-based approach. RESULTS Total thalamic volume was smaller in participants with early-onset psychosis relative to controls. Regional thalamic volume reduction was most significant in the right anterior mediodorsal area and pulvinar. CONCLUSIONS In males with minimally treated early-onset psychosis, thalamic volume deficits may be most pronounced in the anterior mediodorsal and posterior pulvinar regions, adding strength to findings from post-mortem studies in adults with psychosis.

Statistical analysis of brain tissue images in the wavelet domain: wavelet-based morphometry.

Wavelet-based methods have been developed for statistical analysis of functional MRI and PET data, where the wavelet transformation is employed as a tool for efficient signal representation. A number of studies using these approaches have reported better estimation capabilities, in terms of increased sensitivity and specificity, than the standard statistical analyses in the spatial domain. In line with these previous studies, the present report proposes a statistical analysis in the wavelet domain for the estimation of inter-group differences from structural MRI data. The procedure, called wavelet-based morphometry (WBM), was implemented under a voxel-based morphometry (VBM) style analysis. It was evaluated by comparing the gray-matter images of a group of 32 healthy subjects whose images were artificially altered to induce thinning of the cortex, with a different group of 32 healthy subjects whose images were unaltered. In order to quantify the performance of the reconstruction from a practical perspective, the same comparison was also conducted with standard VBM using SPMs Gaussian random fields and FSLs cluster-based statistics, family-wise error corrected, for datasets spatially-normalized via two different registration methods (i.e., SyN and FNIRT). The effect of using different amounts of smoothing, Battle-Lemarié filters and resolution levels in the wavelet transform was also investigated. Results support the proposed approach as a different and promising methodology to assess the structural morphometric differences between different populations of subjects.

Brain morphometry of Dravet syndrome.

The aim of this study was to identify differential global and local brain structural patterns in Dravet Syndrome (DS) patients as compared with a control subject group, using brain morphometry techniques which provide a quantitative whole-brain structural analysis that allows for specific patterns to be generalized across series of individuals. Nine patients with the diagnosis of DS that tested positive for mutation in the SCN1A gene and nine well-matched healthy controls were investigated using voxel brain morphometry (VBM), cortical thickness and cortical gyrification measurements. Global volume reductions of gray matter (GM) and white matter (WM) were related to DS. Local volume reductions corresponding to several white matter regions in brainstem, cerebellum, corpus callosum, corticospinal tracts and association fibers (left inferior fronto-occipital fasciculus and left uncinate fasciculus) were also found. Furthermore, DS showed a reduced cortical folding in the right precentral gyrus. The present findings describe DS-related brain structure abnormalities probably linked to the expression of the SCN1A mutation.

The Disconnection Hypothesis in Alzheimer's Disease Studied Through Multimodal Magnetic Resonance Imaging: Structural, Perfusion, and Diffusion Tensor Imaging

According to the so-called disconnection hypothesis, the loss of synaptic inputs from the medial temporal lobes (MTL) in Alzheimers 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.