Multi-parametric evaluation of the white matter maturation
In vivo evaluation of the brain white matter maturation is still a challenging task with no existing gold standards. In this article we propose an original approach to evaluate the early maturation of the white matter bundles, which is based on comparison of infant and adult groups using the Mahalanobis distance computed from four complementary MRI parameters: quantitative qT1 and qT2 relaxation times, longitudinal λ║ and transverse λ⊥ diffusivities from diffusion tensor imaging. Such multi-parametric approach is expected to better describe maturational asynchrony than conventional univariate approaches because it takes into account complementary dependencies of the parameters on different maturational processes, notably the decrease in water content and the myelination. Our approach was tested on 17 healthy infants (aged 3- to 21-week old) for 18 different bundles. It finely confirmed maturational asynchrony across the bundles: the spino-thalamic tract, the optic radiations, the cortico-spinal tract and the fornix have the most advanced maturation, while the superior longitudinal and arcuate fasciculi, the anterior limb of the internal capsule and the external capsule have the most delayed maturation. Furthermore, this approach was more reliable than univariate approaches as it revealed more maturational relationships between the bundles and did not violate a priori assumptions on the temporal order of the bundle maturation. Mahalanobis distances decreased exponentially with age in all bundles, with the only difference between them explained by different onsets of maturation. Estimation of these relative delays confirmed that the most dramatic changes occur during the first post-natal year.
Studying how the healthy human brain develops is important to understand early pathological mechanisms and to assess the influence of fetal or perinatal events on later life. Brain development relies on complex and intermingled mechanisms especially during gestation and first post-natal months, with intense interactions between genetic, epigenetic and environmental factors. Although the baby's brain is organized early on, it is not a miniature adult brain: regional brain changes are asynchronous and protracted, i.e. sensory-motor regions develop early and quickly, whereas associative regions develop later and slowly over decades. Concurrently, the infant/child gradually achieves new performances, but how brain maturation relates to changes in behavior is poorly understood, requiring non-invasive in vivo imaging studies such as magnetic resonance imaging (MRI). Two main processes of early white matter development are reviewed: (1) establishment of connections between brain regions within functional networks, leading to adult-like organization during the last trimester of gestation, (2) maturation (myelination) of these connections during infancy to provide efficient transfers of information. Current knowledge from post-mortem descriptions and in vivo MRI studies is summed up, focusing on T1- and T2-weighted imaging, diffusion tensor imaging, and quantitative mapping of T1/T2 relaxation times, myelin water fraction and magnetization transfer ratio.
Processing of mathematical operations and solving numerical tasks implicate a distributed set of brain regions. These regions include the superior and inferior parietal lobules that underlie numerical processing such as size judgments, and additional prefrontal regions that are needed for formal mathematical operations such as addition, subtraction and multiplication [Arsalidou, Taylor, 2011]. Critically, little is known about the connectivity between these regions and the association between math performance and the anatomical structure of white matter tracts. The present study investigates connectivity and white matter tracks associated with networks related to math performance: arcuate fasciculus (AF) and superior longitudinal fasciculus (SLF). Participants performed a computerized task with mathematical operations (addition, subtraction, multiplication, and division) with three levels of difficulty; accuracy and reaction time were recorded. Diffusion tensor imagining (DTI) recordings provided indices on fractional anisotropy (FA) — a measure of the direction of white matter tracks in the brain. The relation between FA and math performance scores is reported.
The frontal aslant tract (FAT) is a white-matter tract connecting the inferior frontal gyrus (IFG) and the supplementary motor complex (SMC). Damage to either component of the network causes spontaneous speech dysfluency, indicating its critical role in language production. However, spontaneous speech dysfluency may stem from various lower-level linguistic deficits, precluding inferences about the nature of linguistic processing subserved by the IFG-SMC network. Since the IFG and the SMC are attributed a role in conceptual and lexical selection during language production, we hypothesized that these processes rely on the IFG-SMC connectivity via the FAT. We analysed the effects of FAT volume on conceptual and lexical selection measures following frontal lobe stroke. The measures were obtained from the sentence completion (SC) task, tapping into conceptual and lexical selection, and the picture-word interference (PWI) task, providing a more specific measure of lexical selection. Lower FAT volume was not associated with lower conceptual or lexical selection abilities in our patient cohort. Current findings stand in marked discrepancy with previous lesion and neuroimaging evidence for the joint contribution of the IFG and the SMC to lexical and conceptual selection. A plausible explanation reconciling this discrepancy is that the IFG-SMC connectivity via the FAT does contribute to conceptual and/or lexical selection but its disrupted function undergoes reorganisation over the course of post-stroke recovery. Thus, our negative findings stress the importance of testing the causal role of the FAT in lexical and conceptual selection in patients with more acute frontal lobe lesions.
Current neuroanatomical models of language processing point to a critical role of white matter tracts in language processing; data on the relation between tracts’ disconnection and the accompanying language deficits are, however, fragmentary. Previous studies show that disconnection of the arcuate fasciculus (AF) impairs language production, whereas damage to the ventral tracts leads to a more specific deficit in lexical-semantic processing (Catani, Mesulam, 2008). The current study aims to systematically reveal a relation between tracts damage and deficits at various aspects of language processing. 35 Russian-speaking right-handed patients (age range: 18–60 years) undergoing brain surgery in the left hemisphere took part in the study. Language assessment was performed before and after surgery using the Russian Aphasia Test (RAT; Ivanova et al., 2013), tapping into all linguistic levels of language processing in both production and comprehension modalities. Patients underwent diffusion-tensor imaging before and after surgery; the data were preprocessed in FSL and ExploreDTI, then TracVis was used to reconstruct AF, frontal aslant tract (FAT), inferior fronto-occipital, inferior longitudinal and uncinate fasciculi (the ventral tracts). We observed a significant correlation (p < 0.007) between smaller postoperative volume of the AF and language production worsening (average production score). Among RAT production subtests analyzed separately, however, only repetition scores demonstrated a significant positive correlation with AF volume. FAT resection was associated with worse discourse production. No correlation between damage to the ventral tracts and comprehension scores was found. The obtained results are in line with the existing data on the role of the white matter tracts in language processing and suggest that the language production impairment following AF disconnection may be driven specifically by a sensory-motor integration deficit. A correlation between FAT volume and discourse production supports its critical role in spontaneous speech production. The study was supported by the Russian Foundation for Basic Research, grant No18-012-00829.
Adequate assessment of individual functional motor potentials is important for developing appropriate rehabilitation strategies in ischemic stroke . Microstructural changes in corticospinal tract (CST) and corpus callosum (CC) were repeatedly correlated to post-stroke outcome [2, 3]. However, relationship between them and functional recovery remains unclear. Here we investigated relationship between integrity of CST and CC assessed with diffusion tensor imaging (DTI) and brain functional state assessed with navigated transcranial magnetic stimulation (nTMS) in chronic ischemic supratentorial stroke.
Age-related changes in language processing have not yet been as well-studied as those in perception, memory, attention or cognition. Specifically with regard to syntactic processing, it is still debatable whether only the processing speed or also accuracy decreases with age. The present study investigated the effect of age and individual differences on syntactic processing in healthy adults. Specifically, we tested the effect of age on the speed of reading syntactically complex sentences and the accuracy of their comprehension, and explored the neural correlates of individual differences in speed and accuracy when taking age into account. The analysis was limited to white matter and used diffusion tensor imaging and tract-based spatial statistics to analyze fractional anisotropy of white-matter tracts. The reading speed was found to become slower with age; however, sentence comprehension accuracy was unaffected by age. Thus, similar to the processing speed decrease in many other cognitive domains, a decrease in sentence processing speed seems to be a compensatory mechanisms that ensures that processing accuracy is maintained. The study did not find any significant correlates of individual differences in syntactic processing accuracy, which is likely due to small sample size.
A model for organizing cargo transportation between two node stations connected by a railway line which contains a certain number of intermediate stations is considered. The movement of cargo is in one direction. Such a situation may occur, for example, if one of the node stations is located in a region which produce raw material for manufacturing industry located in another region, and there is another node station. The organization of freight traﬃc is performed by means of a number of technologies. These technologies determine the rules for taking on cargo at the initial node station, the rules of interaction between neighboring stations, as well as the rule of distribution of cargo to the ﬁnal node stations. The process of cargo transportation is followed by the set rule of control. For such a model, one must determine possible modes of cargo transportation and describe their properties. This model is described by a ﬁnite-dimensional system of diﬀerential equations with nonlocal linear restrictions. The class of the solution satisfying nonlocal linear restrictions is extremely narrow. It results in the need for the “correct” extension of solutions of a system of diﬀerential equations to a class of quasi-solutions having the distinctive feature of gaps in a countable number of points. It was possible numerically using the Runge–Kutta method of the fourth order to build these quasi-solutions and determine their rate of growth. Let us note that in the technical plan the main complexity consisted in obtaining quasi-solutions satisfying the nonlocal linear restrictions. Furthermore, we investigated the dependence of quasi-solutions and, in particular, sizes of gaps (jumps) of solutions on a number of parameters of the model characterizing a rule of control, technologies for transportation of cargo and intensity of giving of cargo on a node station.
Event logs collected by modern information and technical systems usually contain enough data for automated process models discovery. A variety of algorithms was developed for process models discovery, conformance checking, log to model alignment, comparison of process models, etc., nevertheless a quick analysis of ad-hoc selected parts of a journal still have not get a full-fledged implementation. This paper describes an ROLAP-based method of multidimensional event logs storage for process mining. The result of the analysis of the journal is visualized as directed graph representing the union of all possible event sequences, ranked by their occurrence probability. Our implementation allows the analyst to discover process models for sublogs defined by ad-hoc selection of criteria and value of occurrence probability
Existing approaches suggest that IT strategy should be a reflection of business strategy. However, actually organisations do not often follow business strategy even if it is formally declared. In these conditions, IT strategy can be viewed not as a plan, but as an organisational shared view on the role of information systems. This approach generally reflects only a top-down perspective of IT strategy. So, it can be supplemented by a strategic behaviour pattern (i.e., more or less standard response to a changes that is formed as result of previous experience) to implement bottom-up approach. Two components that can help to establish effective reaction regarding new initiatives in IT are proposed here: model of IT-related decision making, and efficiency measurement metric to estimate maturity of business processes and appropriate IT. Usage of proposed tools is demonstrated in practical cases.