Integration–segregation dynamics in functional networks of individuals diagnosed with schizophrenia

Schizophrenia has been associated with dysfunction in information integration/ segregation dynamics. One of the neural networks whose role has been most investigated in schizophrenia is the default mode network (DMN). In this study, we have explored the possible alteration of integration and segregation dynamics in individuals diagnosed with schizophrenia with respect to healthy controls, based on the study of the topological properties of the graphs derived from the functional connectivity between the nodes of the DMN in the resting state. Our results indicate that the patients show a diminution of the modularity of the DMN and a higher global efficiency, in sparse graphs. Our data emphasise the interest in studying temporal changes in network measures and are compatible with the hypothesis of randomization of functional networks in schizophrenia.Agencia Estatal de Investigacion, AEI PID2019-105145RB-I0

Fractal dimension analysis of grey matter in multiple sclerosis

The fractal dimension (FD) is a quantitative parameter that characterizes the morphometric variability of a complex object. Among other applications, FD has been used to identify abnormalities of the human brain in conventional magnetic resonance imaging (MRI), including white matter abnormalities in patients with Multiple Sclerosis (MS). Extensive grey matter (GM) pathology has been recently identified in MS and it appears to be a key factor in long-term disability. The aim of the present work was to assess whether FD measurement of GM in T1 MRI sequences can identify GM abnormalities in patients with MS in the early phase of the disease. A voxel-based morphometry approach optimized for MS was used to obtain the segmented brain, where we later calculated the three-dimensional FD of the GM in MS patients and healthy controls.We found that patients with MS had a significant increase in the FD of the GM compared to controls. Such differences were present even in patients with short disease durations, including patients with first attacks of MS. In addition, the FD of the GM correlated with T1 and T2 lesion load, but not with GM atrophy or disability. The FD abnormalities of the GM here detected differed from the previously published FD of the white matter in MS, suggesting that different pathological processes were taking place in each structure. These results indicate that GM morphology is abnormal in patients with MS and that this alteration appears early in the course of the disease

Fractal dimension analysis of resting state functional networks in schizophrenia from EEG signals

Fractal dimension (FD) has been revealed as a very useful tool in analyzing the changes in brain dynamics present in many neurological disorders. The fractal dimension index (FDI) is a measure of the spatiotemporal complexity of brain activations extracted from EEG signals induced by transcranial magnetic stimulation. In this study, we assess whether the FDI methodology can be also useful for analyzing resting state EEG signals, by characterizing the brain dynamic changes in different functional networks affected by schizophrenia, a mental disorder associated with dysfunction in the information flow dynamics in the spontaneous brain networks. We analyzed 31 resting-state EEG records of 150 s belonging to 20 healthy subjects (HC group) and 11 schizophrenia patients (SCZ group). Brain activations at each time sample were established by a thresholding process applied on the 15,002 sources modeled from the EEG signal. FDI was then computed individually in each resting-state functional network, averaging all the FDI values obtained using a sliding window of 1 s in the epoch. Compared to the HC group, significant lower values of FDI were obtained in the SCZ group for the auditory network (p < 0.05), the dorsal attention network (p < 0.05), and the salience network (p < 0.05). We found strong negative correlations (p < 0.01) between psychopathological scores and FDI in all resting-state networks analyzed, except the visual network. A receiver operating characteristic curve analysis also revealed that the FDI of the salience network performed very well as a potential feature for classifiers of schizophrenia, obtaining an area under curve value of 0.83. These results suggest that FDI is a promising method for assessing the complexity of the brain dynamics in different regions of interest, and from long resting-state EEG signals. Regarding the specific changes associated with schizophrenia in the dynamics of the spontaneous brain networks, FDI distinguished between patients and healthy subjects, and correlated to clinical variables

Non-evaluated manipulation of complex CSG solids

One of the most important problems to solve in Solid Modeling is computing boolean operations for solids (union, intersection and difference). In this paper we present a method to obtain the boolean operators based on covering the solids by simplices without evaluating the boundary. The representation of the obtained solid does not correspond with the minimal boundary of the solid, but using the appropriate algorithms it is possible to calculate some properties of the final solid, such as point-in-polyhedron test, visualization, volume or octree generation. The proposed method is also suitable for complex solids bounded by triangular meshes or CSG with polyhedral primitives

Voxelization of solids using simplicial coverings

Rasterization of polygons in 2D is a well known problem, existing several optimal solutions to solve it. The extension of this problem to 3D is more difficult and most existing solutions are designed to obtain a voxelization of the solid. In this paper a new approach to rasterize and voxelize solids in 3D is presented. The described algorithms are very simple, general and robust. The 3D algorithm is valid to be used in the new 3D displays, and it can also be used to voxelize solids delimited by planar faces (with or without holes, manifold or non-manifold). The proposed methods are very suitable for an implementation in graphic hardware rendering system, because it does not use any additional data structure or complex operation

Fractal-dimension analysis detects cerebral changes in preterm infants with and without intrauterine growth restriction

In the search for a useful parameter to detect and quantify subtle brain abnormalities in infants with intrauterine growth restriction (IUGR), we hypothesised that the analysis of the structural complexity of grey matter (GM) and white matter (WM) using the fractal dimension (FD), a measurement of the topological complexity of an object, could be established as a useful tool for quantitative studies of infant brain morphology. We studied a sample of 18 singleton IUGR premature infants, (12.72 months corrected age (CA), range: 12 months-14 months), 15 preterm infants matched one-to-one for gestational age (GA) at delivery (12.6 months; range: 12 months-14 months), and 15 neonates born at term (12.4 months; range: 11 months-14 months). The neurodevelopmental outcome was assessed in all subjects at 18 months CA according to the Bayley Scale for Infant and Toddler Development - Third edition (BSID-III). For MRI acquisition and processing, the infants were scanned at 12 months CA, in a TIM TRIO 3T scanner, sleeping naturally. Images were pre-processed using the SPM5 toolbox, the GM and WM segmented under the VBM5 toolbox, and the box-counting method was applied for FD calculation of normal and skeletonised segmented images. The results showed a significant decrease of the FD of the brain GM and WM in the IUGR group when compared to the preterm or at-term controls. We also identified a significant linear tendency of both GM and WM FD from IUGR to preterm and term groups. Finally, multiple linear analyses between the FD of the GM or WM and the neurodevelopmental scales showed a significant regression of the language and motor scales with the FD of the GM. In conclusion, a decreased FD of the GM and WM in IUGR infants could be a sensitive indicator for the investigation of structural brain abnormalities in the IUGR population at 12 months of age, which can also be related to functional disorders. © 2010 Elsevier Inc.This work was supported by grants: University of Jaén (UJA2009/13/04) to J.R.dM. and F.J.E.; Spanish Government (TIN2007-67474-C03-03) to J.R.dM.; Junta de Andalucía (BIO-302) to F.J.E.; and to N.P., M.S.C. and E.G. by grants from The Cerebra Foundation for the Brain Injured Child (Carmarthen, Wales, UK), The Thrasher Research Fund (Salt Lake City, USA), Marie Curie Host Fellowships for Early Stage Researchers (FETAL-MED-019707-2) and the Spanish Fondo de Investigaciones Sanitarias (FIS 06/0347). N.P. was also supported by a Sara Borrell post-doctoral fellowship (CD09/00263), ISCIII-MICINN, Spain.Peer Reviewe