Browsing by Subject "Connectivity"

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  • Roine, Ulrika; Roine, Timo; Salmi, Juha; Nieminen-von Wendt, Taina; Tani, Pekka; Leppämäki, Sami; Rintahaka, Pertti; Caeyenberghs, Karen; Leemans, Alexander; Sams, Mikko (2015)
    Background: Recent brain imaging findings suggest that there are widely distributed abnormalities affecting the brain connectivity in individuals with autism spectrum disorder (ASD). Using graph theoretical analysis, it is possible to investigate both global and local properties of brain's wiring diagram, i.e., the connectome. Methods: We acquired diffusion-weighted magnetic resonance imaging data from 14 adult males with high-functioning ASD and 19 age-, gender-, and IQ-matched controls. As with diffusion tensor imaging-based tractography, it is not possible to detect complex (e.g., crossing) fiber configurations, present in 60-90 % of white matter voxels; we performed constrained spherical deconvolution-based whole brain tractography. Unweighted and weighted structural brain networks were then reconstructed from these tractography data and analyzed with graph theoretical measures. Results: In subjects with ASD, global efficiency was significantly decreased both in the unweighted and the weighted networks, normalized characteristic path length was significantly increased in the unweighted networks, and strength was significantly decreased in the weighted networks. In the local analyses, betweenness centrality of the right caudate was significantly increased in the weighted networks, and the strength of the right superior temporal pole was significantly decreased in the unweighted networks in subjects with ASD. Conclusions: Our findings provide new insights into understanding ASD by showing that the integration of structural brain networks is decreased and that there are abnormalities in the connectivity of the right caudate and right superior temporal pole in subjects with ASD.
  • Tokariev, Anton; Vanhatalo, Sampsa; Palva, J. Matias (2016)
    Objective: To assess how the recording montage in the neonatal EEG influences the detection of cortical source signals and their phase interactions. Methods: Scalp EEG was simulated by forward modeling 20-200 simultaneously active sources covering the cortical surface of a realistic neonatal head model. We assessed systematically how the number of scalp electrodes (11-85), analysis montage, or the size of cortical sources affect the detection of cortical phase synchrony. Statistical metrics were developed for quantifying the resolution and reliability of the montages. Results: The findings converge to show that an increase in the number of recording electrodes leads to a systematic improvement in the detection of true cortical phase synchrony. While there is always a ceiling effect with respect to discernible cortical details, we show that the average and Laplacian montages exhibit superior specificity and sensitivity as compared to other conventional montages. Conclusions: Reliability in assessing true neonatal cortical synchrony is directly related to the choice of EEG recording and analysis configurations. Because of the high conductivity of the neonatal skull, the conventional neonatal EEG recordings are spatially far too sparse for pertinent studies, and this loss of information cannot be recovered by re-montaging during analysis. Significance: Future neonatal EEG studies will need prospective planning of recording configuration to allow analysis of spatial details required by each study question. Our findings also advice about the level of details in brain synchrony that can be studied with existing datasets or by using conventional EEG recordings. (C) 2015 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.
  • Tokariev, Anton; Vanhatalo, Sampsa; Palva, J. Matias (ELSEVIER IRELAND LTD, 2016)
    Objective: To assess how the recording montage in the neonatal EEG influences the detection of cortical source signals and their phase interactions. Methods: Scalp EEG was simulated by forward modeling 20-200 simultaneously active sources covering the cortical surface of a realistic neonatal head model. We assessed systematically how the number of scalp electrodes (11-85), analysis montage, or the size of cortical sources affect the detection of cortical phase synchrony. Statistical metrics were developed for quantifying the resolution and reliability of the montages. Results: The findings converge to show that an increase in the number of recording electrodes leads to a systematic improvement in the detection of true cortical phase synchrony. While there is always a ceiling effect with respect to discernible cortical details, we show that the average and Laplacian montages exhibit superior specificity and sensitivity as compared to other conventional montages. Conclusions: Reliability in assessing true neonatal cortical synchrony is directly related to the choice of EEG recording and analysis configurations. Because of the high conductivity of the neonatal skull, the conventional neonatal EEG recordings are spatially far too sparse for pertinent studies, and this loss of information cannot be recovered by re-montaging during analysis. Significance: Future neonatal EEG studies will need prospective planning of recording configuration to allow analysis of spatial details required by each study question. Our findings also advice about the level of details in brain synchrony that can be studied with existing datasets or by using conventional EEG recordings. (C) 2015 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.
  • Rikandi, Eva; Mantyla, Teemu; Lindgren, Maija; Kieseppa, Tuula; Suvisaari, Jaana; Raij, Tuukka T. (2018)
    Background: Functional connectivity is altered in psychotic disorders. Multiple findings concentrate on the default mode network, anchored on the precuneus-posterior cingulate cortex (PC-PCC). However, the nature of the alterations varies between studies and connectivity alterations have not been studied during an ecologically valid natural stimulus. In the present study, we investigated the functional and structural connectivity of a PC-PCC region, where functioning differentiated first-episode psychosis patients from control subjects during free viewing of a movie in our earlier study. Methods: 14 first-episode psychosis patients and 12 control subjects were imaged with GE 3T, and 29 patients and 19 control subjects were imaged with a Siemens Skyra 3T scanner while watching scenes from the movie Alice in Wonderland. Group differences in functional connectivity were analysed for both scanners separately and results were compared to identify any overlap. Diffusion tensor measures of 26 patients and 19 control subjects were compared for the related white matter tracts, identified by deterministic tractography. Results: Functional connectivity was increased in patients across scanners between the midline regions of the PC-PCC and the anterior cingulate cortex-medial prefrontal cortex (ACC-mPFC). We found no group differences in any of the diffusion tensor imaging measures. Conclusions: Already in the early stages of psychosis functional connectivity between the midline structures of the PC-PCC and the ACC-mPFC is consistently increased during naturalistic stimulus. (c) 2018 Elsevier B.V. All rights reserved.
  • van Teeffelen, Astrid; Cabeza, Mar; Moilanen, Atte (Springer, 2006)
    Biodiversity and Conservation
    Reserve selection methods are often based on information on species’ occurrence. This can be presence–absence data, or probabilities of occurrence estimated with species distribution models. However, the effect of the choice of distribution model on the outcome of a reserve selection method has been ignored. Here we test a range of species distribution models with three different reserve selection methods. The distribution models had different combinations of variables related to habitat quality and connectivity (which incorporates the effect of spatial habitat configuration on species occurrence). The reserve selection methods included (i) a minimum set approach without spatial considerations; (ii) a clustering reserve selection method; and (iii) a dynamic approach where probabilities of occurrence are re-evaluated according to the spatial pattern of selected sites. The sets of selected reserves were assessed by re-computing species probability of occurrence in reserves using the best probability model and assuming loss of non-selected habitat. The results show that particular choices of distribution model and selection method may lead to reserves that overestimate the achieved target; in other words, species may seem to be represented but the reserve network may actually not be able to support them in the long-term. Instead, the use of models that incorporated connectivity as a variable resulted in the selection of aggregated reserves with higher potential for species long-term persistence. As reserve design aims at the longterm protection of species, it is important to be aware of the uncertainties related to model and method choice and their implications.
  • Lehikoinen, Petteri; Tiusanen, Maria; Santangeli, Andrea; Rajasärkkä, Ari; Jaatinen, Kim; Valkama, Jari; Virkkala, Raimo; Lehikoinen, Aleksi (2021)
    Climate change has ubiquitous impacts on ecosystems and threatens biodiversity globally. One of the most recognized impacts are redistributions of species, a process which can be hindered by habitat degradation. Protected areas (PAs) have been shown to be beneficial for preserving and reallocating species occurrences under climate change. Yet, studies investigating effects of PA networks on species' range shifts under climate change remain scarce. In theory, a well-connected network of PAs should promote population persistence under climate change and habitat degradation. To study this, we evaluated the effects of PA coverage on avian communities in Finland between two study periods of 1980-1999 and 2000-2015. Climate-driven community impacts were investigated by using community temperature index (CTI). We used linear models to study the association of PA coverage and the CTI changes in southern, central and northern Finland. In northern and central Finland, higher PA coverage was associated with lower changes in CTI and 45% PA coverage in northern and 13% in central Finland corresponded with complete mitigation of CTI increase. These results indicate that higher PA coverage strongly increases community resilience to warming climate. However a similar association between PA coverage and changes in CTI was not apparent in southern Finland. The PA coverage in southern Finland was much lower than in the two other sections and thus, may be too sparse to favour community resilience against climate change. The results provide empirical evidence for the international need to rapidly expand PA networks and halt biodiversity loss.
  • Hakulinen, Christian; Fried, Eiko; Pulkki-Råback, Laura; Virtanen, Marianna; Suvisaari, Jaana; Elovainio, Marko (2020)
    Purpose Putative causal relations among depressive symptoms in forms of network structures have been of recent interest, with prior studies suggesting that high connectivity of the symptom network may drive the disease process. We examined in detail the network structure of depressive symptoms among participants with and without depressive disorders (DD; consisting of major depressive disorder (MDD) and dysthymia) at two time points. Methods Participants were from the nationally representative Health 2000 and Health 2011 surveys. In 2000 and 2011, there were 5998 healthy participants (DD-) and 595 participants with DD diagnosis (DD+). Depressive symptoms were measured using the 13-item version of the Beck Depression Inventory (BDI). Fused Graphical Lasso was used to estimate network structures, and mixed graphical models were used to assess network connectivity and symptom centrality. Network community structure was examined using the walktrap-algorithm and minimum spanning trees (MST). Symptom centrality was evaluated with expected influence and participation coefficients. Results Overall connectivity did not differ between networks from participants with and without DD, but more simple community structure was observed among those with DD compared to those without DD. Exploratory analyses revealed small differences between the samples in the order of one centrality estimate participation coefficient. Conclusions Community structure, but not overall connectivity of the symptom network, may be different for people with DD compared to people without DD. This difference may be of importance when estimating the overall connectivity differences between groups with and without mental disorders.
  • Popov, S.; Milicic, M.; Diti, I.; Marko, O.; Sommaggio, D.; Markov, Z.; Vujic, A. (2017)
    Spatial and temporal differences in landscape patterns are of considerable interest for understanding ecological processes. In this study, we assessed habitat quality by using the Syrph The Net database and data on decreasing species richness over a 25-year period for the two largest phytophagous hoverfly genera (Merodon and Cheilosia). Furthermore, within this time frame, we explored congruence between ecological responses (species richness and Biodiversity Maintenance Function for these two genera) and landscape structural changes through correlation analysis. Our results indicate that landscapes have experienced changes in aggregation, isolation/connectivity and landscape diversity, with these parameters being significantly correlated with Cheilosia species richness loss and habitat quality. We conclude that the genus Cheilosia is a good bioindicator that can highlight not only the current quality of an area but also temporal changes in landscape patterns.
  • Yli-Kauhaluoma, Sari Susanna; Pantzar, Mika (2018)
    Objective Self-tracking technologies have created high hopes, even hype, for aiding people to govern their own health risks and promote optimal wellness. High expectations do not, however, necessarily materialize due to connective gaps between personal experiences and self-tracking data. This study examines situations when self-trackers face difficulties in engaging with, and reflecting on, their data with the aim of identifying the specificities and consequences of such connective gaps in self-tracking contexts. Methods The study is based on empirical analyses of interviews of inexperienced, experienced and extreme self-trackers (in total 27), who participated in a pilot study aiming at promoting health and wellness. Results The study shows that people using self-tracking devices actively search for constant connectivity to their everyday experiences and particularly health and wellness through personal data but often become disappointed. The results suggest that in connective gaps the personal data remains invisible or inaccurate, generating feelings of confusion and doubt in the users of the self-tracking devices. These are alarming symptoms that may lead to indifference when disconnectivity becomes solidified and data ends up becoming dead, providing nothing useful for the users of self-tracking technologies. Conclusions High expectations which are put on wearables to advance health and wellness may remain unmaterialised due to connective gaps. This is problematic if individuals are increasingly expected to be active in personal data collection and interpretation regarding their own health and wellness.