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Large-scale networks of phase synchronization are considered to regulate the communication between brain regions fundamental to cognitive function, but the mapping to their structural substrates, i.e., the structure-function relationship, remains poorly understood. Biophysical Network Models (BNMs) have demonstrated the influences of local oscillatory activity and inter-regional anatomical connections in generating alpha-band (8–12 Hz) networks of phase synchronization observed with Electroencephalography (EEG) and Magnetoencephalography (MEG). Yet, the influence of inter-regional conduction delays remains unknown. In this study, we compared a BNM with standard “distance-dependent delays”, which assumes constant conduction velocity, to BNMs with delays specified by two alternative methods accounting for spatially varying conduction velocities, “isochronous delays” and “mixed delays”. We followed the Approximate Bayesian Computation (ABC) workflow, i) specifying neurophysiologically informed prior distributions of BNM parameters, ii) verifying the suitability of the prior distributions with Prior Predictive Checks, iii) fitting each of the three BNMs to alpha-band MEG resting-state data (N = 75) with Bayesian optimization for Likelihood-Free Inference (BOLFI), and iv) choosing between the fitted BNMs with ABC model comparison on a separate MEG dataset (N = 30). Prior Predictive Checks revealed the range of dynamics generated by each of the BNMs to encompass those seen in the MEG data, suggesting the suitability of the prior distributions. Fitting the models to MEG data yielded reliable posterior distributions of the parameters of each of the BNMs. Finally, model comparison revealed the BNM with “distance-dependent delays”, as the most probable to describe the generation of alpha-band networks of phase synchronization seen in MEG. These findings suggest that distance-dependent delays might contribute to the neocortical architecture of human alpha-band networks of phase synchronization. Hence, our study illuminates the role of inter-regional delays in generating the large-scale networks of phase synchronization that might subserve the communication between regions vital to cognition.

High-frequency oscillations (HFOs) are common in mammalian brains and have been assumed to be strictly local. Using human intracerebral recordings, the authors find that HFOs can be phase synchronized across long distances between active cortical sites during resting and task states, which may reflect neuronal communication.

Large-scale networks of phase synchronization are considered to regulate the communication between brain regions fundamental to cognitive function, but the mapping to their structural substrates, i.e., the structure-function relationship, remains poorly understood. Biophysical Network Models (BNMs) have demonstrated the influences of local oscillatory activity and inter-regional anatomical connections in generating alpha-band (8-12 Hz) networks of phase synchronization observed with Electroencephalography (EEG) and Magnetoencephalography (MEG). Yet, the influence of inter-regional conduction delays remains unknown. In this study, we compared a BNM with standard "distance-dependent delays", which assumes constant conduction velocity, to BNMs with delays specified by two alternative methods accounting for spatially varying conduction velocities, "isochronous delays" and "mixed delays". We followed the Approximate Bayesian Computation (ABC) workflow, i) specifying neurophysiologically informed prior distributions of BNM parameters, ii) verifying the suitability of the prior distributions with Prior Predictive Checks, iii) fitting each of the three BNMs to alpha-band MEG resting-state data (N = 75) with Bayesian optimization for Likelihood-Free Inference (BOLFI), and iv) choosing between the fitted BNMs with ABC model comparison on a separate MEG dataset (N = 30). Prior Predictive Checks revealed the range of dynamics generated by each of the BNMs to encompass those seen in the MEG data, suggesting the suitability of the prior distributions. Fitting the models to MEG data yielded reliable posterior distributions of the parameters of each of the BNMs. Finally, model comparison revealed the BNM with "distance-dependent delays", as the most probable to describe the generation of alpha-band networks of phase synchronization seen in MEG. These findings suggest that distance-dependent delays might contribute to the neocortical architecture of human alpha-band networks of phase synchronization. Hence, our study illuminates the role of inter-regional delays in generating the large-scale networks of phase synchronization that might subserve the communication between regions vital to cognition., Competing Interests: Declaration of Competing Interest The authors confirm that they have no personal or financial relationship with people or organizations that could inappropriately influence this work., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

Inter-areal synchronization of neuronal oscillations at frequencies below ~100 Hz is a pervasive feature of neuronal activity and is thought to regulate communication in neuronal circuits. In contrast, faster activities and oscillations have been considered to be largely local-circuit-level phenomena without large-scale synchronization between brain regions. We show, using human intracerebral recordings, that 100-400 Hz high-frequency oscillations (HFOs) may be synchronized between widely distributed brain regions. HFO synchronization expresses individual frequency peaks and exhibits reliable connectivity patterns that show stable community structuring. HFO synchronization is also characterized by a laminar profile opposite to that of lower frequencies. Importantly, HFO synchronization is both transiently enhanced and suppressed in separate frequency bands during a response-inhibition task. These findings show that HFO synchronization constitutes a functionally significant form of neuronal spike-timing relationships in brain activity and thus a mesoscopic indication of neuronal communication per se.

Objective: To determine whether brain volumetric and white matter microstructural changes are present and correlate with neurological impairment in subjects with alternating hemiplegia of childhood (AHC)., Methods: In this prospective single-center study, 12 AHC subjects (mean age 22.9 years) and 24 controls were studied with 3DT1-weighted MR imaging and high angular resolution diffusion imaging at 3T. Data obtained with voxel-based morphometry and tract-based spatial statistics were correlated with motor impairment using the International Cooperative Ataxia Rating Scale (ICARS) and Movement and Disability sub-scales of Burke-Fahn-Marsden Dystonia Rating Scale (BFMMS and BFMDS)., Results: Compared to healthy controls, AHC subjects showed lower total brain volume (P < 0.001) and white matter volume (P = 0.002), with reduced clusters of white matter in frontal and parietal regions (P < 0.001). No significant regional differences were found in cortical or subcortical grey matter volumes. Lower cerebellar subvolumes correlated with worse ataxic symptoms and global motor impairment in AHC group (P < 0.001). Increased mean and radial diffusivity values were found in the corpus callosum, corticospinal tracts, superior and inferior longitudinal fasciculi, subcortical frontotemporal white matter, internal and external capsules, and optic radiations (P < 0.001). These diffusion scalar changes correlated with higher ICARS and BFMDS scores (P < 0.001)., Interpretation: AHC subjects showed prevalent white matter involvement, with reduced volume in several cerebral and cerebellar regions associated with widespread microstructural changes reflecting secondary myelin injury rather than axonal loss. Conversely, no specific pattern of grey matter atrophy emerged. Lower cerebellar volumes, correlating with severity of neurological manifestations, seems related to disrupted developmental rather than neurodegenerative processes.

Brain Tissue Segmentation (BTS) in young children and neonates is not a trivial task due to peculiar characteristics of the developing brain. The aim of this study is to present the preliminary results of new atlas-free BTS (afBTS) algorithm of MR images for pediatric applications, based on clustering. The algorithm works on axial T1, T2 and FLAIR sequences. First, the Cerebrospinal Fluid (CSF) is identified using the Region Growing algorithm. The remaining voxels are processed with the k-means algorithm in order to separate White Matter (WM) and Grey Matter (GM). The afBTS algorithm was applied to a population of 13 neonates; the segmentations were evaluated by two expert pediatric neuroradiologists and compared with an atlas-based algorithm. The results were promising: afBTS allowed reconstruction of WM and CSF with an image quality comparable to the reference of standard while lower segmentation quality was obtained for the GM segmentation.

Background: Germinal matrix-intraventricular hemorrhage (GMH-IVH) is a common form of intracranial hemorrhage occurring in preterm neonates that may affect normal brain development. Although the primary lesion is easily identified on MRI by the presence of blood products, its exact extent may not be recognizable with conventional sequences. Quantitative susceptibility mapping (QSM) quantify the spatial distribution of magnetic susceptibility within biological tissues, including blood degradation products., Purpose/hypothesis: To evaluate magnetic susceptibility of normal-appearing white (WM) and gray matter regions in preterm neonates with and without GMH-IVH., Study Type: Retrospective case-control., Population: A total of 127 preterm neonates studied at term equivalent age: 20 had mild GMH-IVH (average gestational age 28.7 ± 2.1 weeks), 15 had severe GMH-IVH (average gestational age 29.3 ± 1.8 weeks), and 92 had normal brain MRI (average gestational age 29.8 ± 1.8 weeks)., Field Strength/sequence: QSM at 1.5 Tesla., Assessment: QSM analysis was performed for each brain hemisphere with a region of interest-based approach including five WM regions (centrum semiovale, frontal, parietal, temporal, and cerebellum), and a subcortical gray matter region (basal ganglia/thalami)., Statistical Tests: Changes in magnetic susceptibility were explored using a one-way analysis of covariance, according to GMH-IVH severity (P < 0.05)., Results: In preterm neonates with normal brain MRI, all white and subcortical gray matter regions had negative magnetic susceptibility values (diamagnetic). Neonates with severe GMH-IVH showed higher positive magnetic susceptibility values (i.e. paramagnetic) in the centrum semiovale (0.0019 versus -0.0014 ppm; P < 0.001), temporal WM (0.0011 versus -0.0012 ppm; P = 0.037), and parietal WM (0.0005 versus -0.0001 ppm; P = 0.002) compared with controls. No differences in magnetic susceptibility were observed between neonates with mild GMH-IVH and controls (P = 0.236)., Data Conclusion: Paramagnetic susceptibility changes occur in several normal-appearing WM regions of neonates with severe GMH-IVH, likely related to the accumulation of hemosiderin/ferritin iron secondary to diffusion of extracellular hemoglobin from the ventricle into the periventricular WM., Level of Evidence: 4 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2018;47:1199-1207., (© 2018 International Society for Magnetic Resonance in Medicine.)

Introduction: Diffusion-weighted magnetic resonance imaging (DW-MRI) allows noninvasive investigation of brain structure in vivo . Diffusion tensor imaging (DTI) is a frequently used application of DW-MRI that assumes a single main diffusion direction per voxel, and is therefore not well suited for reconstructing crossing fiber tracts. Among the solutions developed to overcome this problem, constrained spherical deconvolution with probabilistic tractography (CSD-PT) has provided superior quality results in clinical settings on adult subjects; however, it requires particular acquisition parameters and long sequences, which may limit clinical usage in the pediatric age group. The aim of this work was to compare the results of DTI with those of track density imaging (TDI) maps and CSD-PT on data from neonates and children, acquired with low angular resolution and low b-value diffusion sequences commonly used in pediatric clinical MRI examinations., Materials and Methods: We analyzed DW-MRI studies of 50 children (eight neonates aged 3-28 days, 20 infants aged 1-8 months, and 22 children aged 2-17 years) acquired on a 1.5 T Philips scanner using 34 gradient directions and a b-value of 1,000 s/mm 2 . Other sequence parameters included 60 axial slices; acquisition matrix, 128 × 128; average scan time, 5:34 min; voxel size, 1.75 mm × 1.75 mm × 2 mm; one b = 0 image. For each subject, we computed principal eigenvector (EV) maps and directionally encoded color TDI maps (DEC-TDI maps) from whole-brain tractograms obtained with CSD-PT; the cerebellar-thalamic, corticopontocerebellar, and corticospinal tracts were reconstructed using both CSD-PT and DTI. Results were compared by two neuroradiologists using a 5-point qualitative score., Results: The DEC-TDI maps obtained presented higher anatomical detail than EV maps, as assessed by visual inspection. In all subjects, white matter (WM) tracts were successfully reconstructed using both tractography methodologies. The mean qualitative scores of all tracts obtained with CSD-PT were significantly higher than those obtained with DTI ( p -value < 0.05 for all comparisons)., Conclusion: CSD-PT can be successfully applied to DW-MRI studies acquired at 1.5 T with acquisition parameters adapted for pediatric subjects, thus providing TDI maps with greater anatomical detail. This methodology yields satisfactory results for clinical purposes in the pediatric age group.

Background and Purpose: Segmental callosal agenesis is characterized by the absence of the intermediate callosal portion. We aimed to evaluate the structural connectivity of segmental callosal agenesis by using constrained spherical deconvolution tractography and connectome analysis., Materials and Methods: We reviewed the clinical-radiologic features of 8 patients (5 males; mean age, 3.9 years). Spherical deconvolution and probabilistic tractography were performed on diffusion data. Structural connectivity analysis, including summary network metrics, modularity analysis, and network consistency measures, was applied in 5 patients and 10 age-/sex-matched controls., Results: We identified 3 subtypes based on the position of the hippocampal commissure: beneath the anterior callosal remnant in 3 patients (type I), beneath the posterior callosal remnant in 3 patients (type II), and between the anterior and posterior callosal remnants in 2 patients (type III). In all patients, the agenetic segment corresponded to fibers projecting to the parietal lobe, and segmental Probst bundles were found at that level. Ectopic callosal bundles were identified in 3 patients. Topology analysis revealed reduced global connectivity in patients compared with controls. The network topology of segmental callosal agenesis was more variable across patients than that of the control connectomes. Modularity analysis revealed disruption of the structural core organization in the patients., Conclusions: Three malformative subtypes of segmental callosal agenesis were identified. Even the absence of a small callosal segment may impact global brain connectivity and modularity organization. The presence of ectopic callosal bundles may explain the greater interindividual variation in the connectomes of patients with segmental callosal agenesis., (© 2017 by American Journal of Neuroradiology.)

Background: In the evaluation of Stereo-Electroencephalography (SEEG) signals, the physicist's workflow involves several operations, including determining the position of individual electrode contacts in terms of both relationship to grey or white matter and location in specific brain regions. These operations are (i) generally carried out manually by experts with limited computer support, (ii) hugely time consuming, and (iii) often inaccurate, incomplete, and prone to errors., Results: In this paper we present SEEG Assistant, a set of tools integrated in a single 3DSlicer extension, which aims to assist neurosurgeons in the analysis of post-implant structural data and hence aid the neurophysiologist in the interpretation of SEEG data. SEEG Assistant consists of (i) a module to localize the electrode contact positions using imaging data from a thresholded post-implant CT, (ii) a module to determine the most probable cerebral location of the recorded activity, and (iii) a module to compute the Grey Matter Proximity Index, i.e. the distance of each contact from the cerebral cortex, in order to discriminate between white and grey matter location of contacts. Finally, exploiting 3DSlicer capabilities, SEEG Assistant offers a Graphical User Interface that simplifies the interaction between the user and the tools. SEEG Assistant has been tested on 40 patients segmenting 555 electrodes, and it has been used to identify the neuroanatomical loci and to compute the distance to the nearest cerebral cortex for 9626 contacts. We also performed manual segmentation and compared the results between the proposed tool and gold-standard clinical practice. As a result, the use of SEEG Assistant decreases the post implant processing time by more than 2 orders of magnitude, improves the quality of results and decreases, if not eliminates, errors in post implant processing., Conclusions: The SEEG Assistant Framework for the first time supports physicists by providing a set of open-source tools for post-implant processing of SEEG data. Furthermore, SEEG Assistant has been integrated into 3D Slicer, a software platform for the analysis and visualization of medical images, overcoming limitations of command-line tools.

An improved spherical deconvolution algorithm to solve fiber crossing in diffusion magnetic resonance imaging is here presented. The introduction of a regularization parameter on the reconstruction of the fibers directions allows to consider the deconvolution as a constrained least squares problem and enforces the normalization of the reconstructed directions. Moreover a new automatic stopping criterion is implemented which allows to push the algorithm to convergence. These modifications improve significantly the performance of the algorithm, decreasing the resolution limit and reconstructing better profiles of the fibers.

In Argentina no historical or present programs exist specifically assessing ecosystem health with respect to photochemical air pollution, although phytotoxic concentrations of near-ground ozone have been documented in recent years. Here we report our preliminary findings on field observations of ozone-like injury found in natural plant populations and agroecosystems late in the 2005 growing season in the Southern Hemisphere. Several possible ozone bioindicator plants which have not been previously documented were observed to exhibit foliar symptoms consistent with ozone-induced injury. Based on these results we intend to expand field surveys and complete the screening process for injury confirmation of the plant species described here. For this and future research we will be using controlled chamber studies based in the US. Continuous monitoring of tropospheric ozone does not currently take place in the region of central Argentina. The combined evidence provided by intermittent air quality sampling and the presence of ozone-like injury to vegetation indicates the need to establish air quality and ozone biomonitoring networks in this region.