Structural connectivity
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Despite the rising global burden of stroke and its socio-economic implications, the neuroimaging predictors of subsequent cognitive impairment are still poorly understood. We address this issue by studying the relationship of white matter integrity assessed within ten days after stroke and patients' cognitive status one year after the attack. Using diffusion-weighted imaging, we apply the Tract-Based Spatial Statistics analysis and construct individual structural connectivity matrices by employing deterministic tractography. We further quantify the graph-theoretical properties of individual networks. The Tract-Based Spatial Statistic did identify lower fractional anisotropy as a predictor of cognitive status, although this effect was mostly attributable to the age-related white matter integrity decline. We further observed the effect of age propagating into other levels of analysis. Specifically, in the structural connectivity approach we identified pairs of regions significantly correlated with clinical scales, namely memory, attention, and visuospatial functions. However, none of them persisted after the age correction. Finally, the graph-theoretical measures appeared to be more robust towards the effect of age, but still were not sensitive enough to capture a relationship with clinical scales. In conclusion, the effect of age is a dominant confounder especially in older cohorts, and unless appropriately addressed, may falsely drive the results of the predictive modelling.
- MeSH
- bílá hmota * diagnostické zobrazování MeSH
- cévní mozková příhoda * komplikace diagnostické zobrazování MeSH
- difuzní magnetická rezonance MeSH
- kognitivní dysfunkce * diagnostické zobrazování etiologie psychologie MeSH
- lidé MeSH
- senioři MeSH
- stárnutí MeSH
- zobrazování difuzních tenzorů metody MeSH
- Check Tag
- lidé MeSH
- senioři MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
Příspěvek uvádí do souvislosti morfologii úponu bránice v interkostálním prostoru pars costalis diaphragmatis a m. transversus abdominis se začleněním těchto svalů do hlubokého stabilizačního systému (HSS). Na souboru 4 vzorků 3 kadaverů je popsáno anatomické uspořádání inerční oblasti obou svalů, kde v makroskopickém ani mikroskopickém obraze nebyla zjištěna vazivová šlašitá či aponeurotická přechodová oblast a svaly tak jeví vzájemný kontinuální přechod. Je diskutován podíl tohoto morfologického uspořádání na možných zřetězených funkčních patologiích v rámci uzavřených kinetických řetězců (CKC) trupu.
A following report shows a coherence between morphology of ÚPON of diaphragma in intercostalis area of pars costalis diaphragmatis and m.transversus abdominis in the deep stability system. There is described the anatomic arrays inerts areas of both muscles in a group of 4 assays from 3 cadavers. There was not detected macroscopic or microscopic tendinous or aponeurotic transmission area. The muscles show an interaction continual junction. Finally the authors debated about the influence of this morphologic configuration in functional pathologics concatenations of closed cinetics chains in a trunk.
- MeSH
- bránice MeSH
- břicho MeSH
- kosterní svalová vlákna MeSH
- lidé MeSH
- rehabilitace MeSH
- svaly anatomie a histologie MeSH
- Check Tag
- lidé MeSH
The human brain represents a complex computational system, the function and structure of which may be measured using various neuroimaging techniques focusing on separate properties of the brain tissue and activity. We capture the organization of white matter fibers acquired by diffusion-weighted imaging using probabilistic diffusion tractography. By segmenting the results of tractography into larger anatomical units, it is possible to draw inferences about the structural relationships between these parts of the system. This pipeline results in a structural connectivity matrix, which contains an estimate of connection strength among all regions. However, raw data processing is complex, computationally intensive, and requires expert quality control, which may be discouraging for researchers with less experience in the field. We thus provide brain structural connectivity matrices in a form ready for modelling and analysis and thus usable by a wide community of scientists. The presented dataset contains brain structural connectivity matrices together with the underlying raw diffusion and structural data, as well as basic demographic data of 88 healthy subjects.
Modern imaging methods allow a non-invasive assessment of both structural and functional brain connectivity. This has lead to the identification of disease-related alterations affecting functional connectivity. The mechanism of how such alterations in functional connectivity arise in a structured network of interacting neural populations is as yet poorly understood. Here we use a modeling approach to explore the way in which this can arise and to highlight the important role that local population dynamics can have in shaping emergent spatial functional connectivity patterns. The local dynamics for a neural population is taken to be of the Wilson-Cowan type, whilst the structural connectivity patterns used, describing long-range anatomical connections, cover both realistic scenarios (from the CoComac database) and idealized ones that allow for more detailed theoretical study. We have calculated graph-theoretic measures of functional network topology from numerical simulations of model networks. The effect of the form of local dynamics on the observed network state is quantified by examining the correlation between structural and functional connectivity. We document a profound and systematic dependence of the simulated functional connectivity patterns on the parameters controlling the dynamics. Importantly, we show that a weakly coupled oscillator theory explaining these correlations and their variation across parameter space can be developed. This theoretical development provides a novel way to characterize the mechanisms for the breakdown of functional connectivity in diseases through changes in local dynamics.
- MeSH
- lidé MeSH
- modely neurologické MeSH
- mozek fyziologie MeSH
- nervová síť fyziologie MeSH
- výpočetní biologie MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
Many recent studies have explored the effects of present and past landscape structure on species distribution and diversity. However, we know little about the effects of past landscape structure on distribution of genetic diversity within and between populations of a single species. Here we describe the relationship between present and past landscape structure (landscape connectivity and habitat size estimated from historical maps) and current genetic structure in a perennial herb, Succisa pratensis. We used allozymes as co-dominant markers to estimate genetic diversity and deviation from Hardy-Weinberg equilibrium in 31 populations distributed within a 5 km(2) agricultural landscape. The results showed that current genetic diversity of populations was related to habitat suitability, habitat age, habitat size and habitat connectivity in the past. The effects of habitat age and past connectivity on genetic diversity were in most cases also significant after taking the current landscape structure into account. Moreover, current genetic similarity between populations was affected by past connectivity after accounting for current landscape structure. In both cases, the oldest time layer (1850) was the most informative. Most populations showed heterozygote excess, indicating disequilibrium due to recent gene flow or selection against homozygotes. These results suggest that habitat age and past connectivity are important determinants of distribution of genetic diversity between populations at a scale of a few kilometres. Landscape history may significantly contribute to our understanding of distribution of current genetic structure within species and the genetic structure may be used to better understand landscape history, even at a small scale.
- MeSH
- alely MeSH
- Dipsacaceae genetika MeSH
- ekosystém * MeSH
- genetická variace * MeSH
- genetické markery genetika MeSH
- genetické struktury * MeSH
- heterozygot MeSH
- inbreeding MeSH
- izoenzymy genetika MeSH
- populační genetika * MeSH
- regresní analýza MeSH
- rostlinné proteiny genetika MeSH
- selekce (genetika) MeSH
- tok genů MeSH
- životní prostředí MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
The relationship between network structure and dynamics is one of the most extensively investigated problems in the theory of complex systems of recent years. Understanding this relationship is of relevance to a range of disciplines-from neuroscience to geomorphology. A major strategy of investigating this relationship is the quantitative comparison of a representation of network architecture (structural connectivity, SC) with a (network) representation of the dynamics (functional connectivity, FC). Here, we show that one can distinguish two classes of functional connectivity-one based on simultaneous activity (co-activity) of nodes, the other based on sequential activity of nodes. We delineate these two classes in different categories of dynamical processes-excitations, regular and chaotic oscillators-and provide examples for SC/FC correlations of both classes in each of these models. We expand the theoretical view of the SC/FC relationships, with conceptual instances of the SC and the two classes of FC for various application scenarios in geomorphology, ecology, systems biology, neuroscience and socio-ecological systems. Seeing the organisation of dynamical processes in a network either as governed by co-activity or by sequential activity allows us to bring some order in the myriad of observations relating structure and function of complex networks.
- MeSH
- ekologie * MeSH
- ekosystém * MeSH
- mozek MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
Developing sensitive and reliable methods to distinguish normal and abnormal brain states is a key neuroscientific challenge. Topological Data Analysis, despite its relative novelty, already generated many promising applications, including in neuroscience. We conjecture its prominent tool of persistent homology may benefit from going beyond analysing structural and functional connectivity to effective connectivity graphs capturing the direct causal interactions or information flows. Therefore, we assess the potential of persistent homology to directed brain network analysis by testing its discriminatory power in two distinctive examples of disease-related brain connectivity alterations: epilepsy and schizophrenia. We estimate connectivity from functional magnetic resonance imaging and electrophysiology data, employ Persistent Homology and quantify its ability to distinguish healthy from diseased brain states by applying a support vector machine to features quantifying persistent homology structure. We show how this novel approach compares to classification using standard undirected approaches and original connectivity matrices. In the schizophrenia classification, topological data analysis generally performs close to random, while classifications from raw connectivity perform substantially better; potentially due to topographical, rather than topological, specificity of the differences. In the easier task of seizure discrimination from scalp electroencephalography data, classification based on persistent homology features generally reached comparable performance to using raw connectivity, albeit with typically smaller accuracies obtained for the directed (effective) connectivity compared to the undirected (functional) connectivity. Specific applications for topological data analysis may open when direct comparison of connectivity matrices is unsuitable - such as for intracranial electrophysiology with individual number and location of measurements. While standard homology performed overall better than directed homology, this could be due to notorious technical problems of accurate effective connectivity estimation.
- MeSH
- elektroencefalografie MeSH
- epilepsie diagnostické zobrazování patofyziologie MeSH
- konektom * MeSH
- lidé MeSH
- magnetická rezonanční tomografie MeSH
- mapování mozku MeSH
- modely neurologické * MeSH
- mozek diagnostické zobrazování patofyziologie MeSH
- nervová síť diagnostické zobrazování patofyziologie MeSH
- schizofrenie diagnostické zobrazování patofyziologie MeSH
- záchvaty diagnostické zobrazování patofyziologie MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
Brain imaging studies in complex regional pain syndrome (CRPS) have found mixed evidence for functional and structural changes in CRPS. In this cross-sectional study, we evaluated two patient cohorts from different centers and examined functional connectivity (rsFC) in 51 CRPS patients and 50 matched controls. rsFC was compared in predefined ROI pairs, but also in non-hypothesis driven analyses. Resting state (rs)fMRI changes in default mode network (DMN) and the degree rank order disruption index (kD) were additionally evaluated. Finally, imaging parameters were correlated with clinical severity and somatosensory function. Among predefined pairs, we found only weakly to moderately lower functional connectivity between the right nucleus accumbens and bilateral ventromedial prefrontal cortex in the infra-slow oscillations (ISO) band. The unconstrained ROI-to-ROI analysis revealed lower rsFC between the periaqueductal gray matter (PAG) and left anterior insula, and higher rsFC between the right sensorimotor thalamus and nucleus accumbens. In the correlation analysis, pain was positively associated with insulo-prefrontal rsFC, whereas sensorimotor thalamo-cortical rsFC was positively associated with tactile spatial resolution of the affected side. In contrast to previous reports, we found no group differences for kD or rsFC in the DMN, but detected overall lower data quality in patients. In summary, while some of the previous results were not replicated despite the larger sample size, novel findings from two independent cohorts point to potential down-regulated antinociceptive modulation by the PAG and increased connectivity within the reward system as pathophysiological mechanisms in CRPS. However, in light of the detected systematic differences in data quality between patients and healthy subjects, validity of rsFC abnormalities in CRPS should be carefully scrutinized in future replication studies.
- MeSH
- default mode network diagnostické zobrazování patofyziologie MeSH
- dospělí MeSH
- komplexní regionální syndromy bolesti * patofyziologie diagnostické zobrazování MeSH
- konektom metody MeSH
- lidé středního věku MeSH
- lidé MeSH
- magnetická rezonanční tomografie * MeSH
- mozek patofyziologie diagnostické zobrazování MeSH
- nervová síť patofyziologie diagnostické zobrazování MeSH
- průřezové studie MeSH
- Check Tag
- dospělí MeSH
- lidé středního věku MeSH
- lidé MeSH
- mužské pohlaví MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- multicentrická studie MeSH
Různé vyšetřovací modality magnetické rezonance (MR) prokázaly v mnoha publikovaných studiích morfologické i funkční změny v mozkové tkáni u osob se schizofrenií (SZ). Volumetrickými metodami byly popsány atrofické změny některých oblastí šedé hmoty, pomocí metody zobrazení difuzního tenzoru především pokles hodnot frakční anizotropie bílé hmoty. Tyto změny jsou obecně mírného stupně, široké distribuce a v čase pravděpodobně progredují. Při resting-state funkční magnetické rezonanci byly opakovaně nalezeny významné změny konektivity jednotlivých funkčních center mozku. Vesměs jsou MR nálezy kompatibilní s upřednostňovanou teorií o poruše konektivity mozku u schizofrenie. Mezi výsledky dosud publikovaných studií panuje ovšem velmi značná variabilita, která má více příčin. K těm nejvýznamnějším řadíme nejednotnost v metodice prováděných studií, metodologické a technické limitace MR, malé počty subjektů ve většině publikovaných studií, výraznou heterogenitu psychických a potažmo strukturálních změn u nemocných se schizofrenií, dobu trvání manifestního onemocnění (první ataka versus chronické stadium), možný vliv medikace, toxických a návykových látek na strukturální a funkční změny mozku atd. Má-li magnetická rezonance najít pevné klinické uplatnění v diagnostice schizofrenie, bude potřeba rozsáhlých multicentrických studií s klinicky homogenními skupinami probandů a jednotnou metodikou. V článku jsou shrnuty dosavadní znalosti o strukturálních a funkčních změnách mozku u schizofrenie.
Structural and functional cerebral changes in subjects suffering from schizophrenia (SZ) were proven by means of several modalities of magnetic resonance imaging (MRI) according to the results of numerous studies. Atrophic changes were reported by using volumetric methods, microstructural changes of white matter were described by diffusion tensor imaging. These changes are of mild degree yet likely of widespread distribution and progressing over time. Extensive changes of connectivity were observed by resting-state functional MRI. MRI findings are generally compatible with currently preferred hypothesis of cerebral dysconnectivity in SZ. The published results show considerable degree of variability which can be explained by many reasons. Those of the highest importance are: different methodology, technical MRI limitations, low number of subjects included, high heterogeneity and variability of symptoms of the disease, variable duration of symptoms (first episode versus chronic illness), effects of medication, abuse of toxic substances etc. Before MRI can be utilized for diagnosing SZ in the clinical settings, more comprehensive multi-centric studies of homogenous cohorts with unified methodology are needed. In this review, we summarize the current knowledge of structural and functional cerebral changes in schizophrenia.
- MeSH
- chronická nemoc MeSH
- klinická studie jako téma MeSH
- lidé MeSH
- magnetická rezonanční tomografie * MeSH
- metaanalýza jako téma MeSH
- mozek * patofyziologie MeSH
- neurozobrazování * metody MeSH
- rozpoznávání automatizované MeSH
- schizofrenie * diagnóza patofyziologie MeSH
- šedá hmota patofyziologie MeSH
- zobrazování difuzních tenzorů metody MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- přehledy MeSH
Estimating structural connectivity from diffusion-weighted magnetic resonance imaging is a challenging task, partly due to the presence of false-positive connections and the misestimation of connection weights. Building on previous efforts, the MICCAI-CDMRI Diffusion-Simulated Connectivity (DiSCo) challenge was carried out to evaluate state-of-the-art connectivity methods using novel large-scale numerical phantoms. The diffusion signal for the phantoms was obtained from Monte Carlo simulations. The results of the challenge suggest that methods selected by the 14 teams participating in the challenge can provide high correlations between estimated and ground-truth connectivity weights, in complex numerical environments. Additionally, the methods used by the participating teams were able to accurately identify the binary connectivity of the numerical dataset. However, specific false positive and false negative connections were consistently estimated across all methods. Although the challenge dataset doesn't capture the complexity of a real brain, it provided unique data with known macrostructure and microstructure ground-truth properties to facilitate the development of connectivity estimation methods.
- MeSH
- difuzní magnetická rezonance * metody MeSH
- fantomy radiodiagnostické MeSH
- lidé MeSH
- metoda Monte Carlo MeSH
- mozek diagnostické zobrazování MeSH
- počítačové zpracování obrazu * metody MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- Research Support, N.I.H., Extramural MeSH
