Jordan, Denis

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Jordan
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Denis
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Denis Jordan

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2018 - 201942020 - 20225
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Hochschule: Hochschule für Architektur, Bau und Geomatik × Institut: Institut Geomatik ×

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Gerade angezeigt 1 - 9 von 9
  • Vorschaubild
    Publikation
    Silage bale detection for the «Cultivable Area» update of the Cantonal Agricultural Office, Thurgau
    (Institut Geomatik, Hochschule für Architektur, Bau und Geomatik FHNW, 09/2022) Adrian F. Meyer; Jordan, Denis
    In Switzerland direct subsidies are paid to farms for sustainable agricultural practice. The cultivable agricultural area layer (German: Landwirtschaftliche Nutzfläche, LN) serves as an annual basis for the calculation of these contributions at the Swiss cantonal agricultural offices. Material deposits like silage bale stacks are usually excluded from the LN. Therefore, the canton of Thurgau could profit from a spatial vector layer indicating locations and area consumption extent of silage bale stacks intersecting with the LN perimeter.
    05 - Forschungs- oder Arbeitsbericht
  • Vorschaubild
    Publikation
    Brain network integration dynamics are associated with loss and recovery of consciousness induced by sevoflurane
    (Wiley, 2021) Luppi, Andrea I.; Golkowski, Daniel; Ranft, Andreas; Ilg, Rüdiger; Jordan, Denis; Menon, David K.; Stamatakis, Emmanuel A. [in: Human Brain Mapping]
    The dynamic interplay of integration and segregation in the brain is at the core of leading theoretical accounts of consciousness. The human brain dynamically alternates between a sub‐state where integration predominates, and a predominantly segregated sub‐state, with different roles in supporting cognition and behaviour. Here, we combine graph theory and dynamic functional connectivity to compare resting‐state functional MRI data from healthy volunteers before, during, and after loss of responsiveness induced with different concentrations of the inhalational anaesthetic, sevoflurane. We show that dynamic states characterised by high brain integration are especially vulnerable to general anaesthesia, exhibiting attenuated complexity and diminished small‐world character. Crucially, these effects are reversed upon recovery, demonstrating their association with consciousness. Higher doses of sevoflurane (3% vol and burst‐suppression) also compromise the temporal balance of integration and segregation in the human brain. Additionally, we demonstrate that reduced anticorrelations between the brain's default mode and executive control networks dynamically reconfigure depending on the brain's state of integration or segregation. Taken together, our results demonstrate that the integrated sub‐state of brain connectivity is especially vulnerable to anaesthesia, in terms of both its complexity and information capacity, whose breakdown represents a generalisable biomarker of loss of consciousness and its recovery.
    01A - Beitrag in wissenschaftlicher Zeitschrift
  • Vorschaubild
    Publikation
    Dynamic patterns of global brain communication differentiate conscious from unconscious patients after severe brain injury
    (Frontiers Research Foundation, 2021) Golkowski, Daniel; Willnecker, Rebecca; Rösler, Jennifer; Ranft, Andreas; Schneider, Gerhard; Jordan, Denis; Ilg, Rüdiger [in: Frontiers in Systems Neuroscience]
    The neurophysiology of the subjective sensation of being conscious is elusive; therefore, it remains controversial how consciousness can be recognized in patients who are not responsive but seemingly awake. During general anesthesia, a model for the transition between consciousness and unconsciousness, specific covariance matrices between the activity of brain regions that we call patterns of global brain communication reliably disappear when people lose consciousness. This functional magnetic imaging study investigates how patterns of global brain communication relate to consciousness and unconsciousness in a heterogeneous sample during general anesthesia and after brain injury. First, we describe specific patterns of global brain communication during wakefulness that disappear during propofol and sevoflurane general anesthesia. Second, we search for these patterns in a cohort of unresponsive wakeful patients and unmatched healthy controls in order to evaluate their potential use in clinical practice. We found that patterns of global brain communication characterized by high covariance in sensory and motor areas or low overall covariance and their dynamic change were strictly associated with intact consciousness in this cohort. In addition, we show that the occurrence of these two patterns is significantly related to activity within the frontoparietal network of the brain, a network known to play a crucial role in conscious perception. We propose that this approach potentially recognizes consciousness in the clinical routine setting.
    01A - Beitrag in wissenschaftlicher Zeitschrift
  • Vorschaubild
    Publikation
    Criticality creates a functional platform for network transitions between internal and external processing modes in the human brain
    (Frontiers Research Foundation, 2021) Kim, Minkyung; Kim, Hyoungkyu; Huang, Zirui; Mashour, George A.; Jordan, Denis; Ilg, Rüdiger; Lee, UnCheol [in: Frontiers in Systems Neuroscience]
    Continuous switching between internal and external modes in the brain appears important for generating models of the self and the world. However, how the brain transitions between these two modes remains unknown. We propose that a large synchronization fluctuation of brain networks, emerging only near criticality (i.e., a balanced state between order and disorder), spontaneously creates temporal windows with distinct preferences for integrating the network’s internal information or for processing external stimuli. Using a computational model, electroencephalography (EEG) analysis, and functional magnetic resonance imaging (fMRI) analysis during alterations of consciousness in humans, we report that synchronized and incoherent networks, respectively, bias toward internal and external information with specific network configurations. In the brain network model and EEG-based network, the network preferences are the most prominent at criticality and in conscious states associated with the bandwidth 4−12 Hz, with alternating functional network configurations. However, these network configurations are selectively disrupted in different states of consciousness such as general anesthesia, psychedelic states, minimally conscious states, and unresponsive wakefulness syndrome. The network preference for internal information integration is only significant in conscious states and psychedelic states, but not in other unconscious states, suggesting the importance of internal information integration in maintaining consciousness. The fMRI co-activation pattern analysis shows that functional networks that are sensitive to external stimuli–such as default mode, dorsal attentional, and frontoparietal networks–are activated in incoherent states, while insensitive networks, such as global activation and deactivation networks, are dominated in highly synchronized states. We suggest that criticality produces a functional platform for the brain’s capability for continuous switching between two modes, which is crucial for the emergence of consciousness.
    01A - Beitrag in wissenschaftlicher Zeitschrift
  • Vorschaubild
    Publikation
    Criticality creates a functional platform for network transitions between internal and external processing modes in the human brain
    (Frontiers Research Foundation, 2021) Kim, Minkyung; Kim, Hyoungkyu; Huang, Zirui; Mashour, George A.; Jordan, Denis; Ilg, Rüdiger; Lee, UnCheol [in: Frontiers in Systems Neuroscience]
    Continuous switching between internal and external modes in the brain appears important for generating models of the self and the world. However, how the brain transitions between these two modes remains unknown. We propose that a large synchronization fluctuation of brain networks, emerging only near criticality (i.e., a balanced state between order and disorder), spontaneously creates temporal windows with distinct preferences for integrating the network’s internal information or for processing external stimuli. Using a computational model, electroencephalography (EEG) analysis, and functional magnetic resonance imaging (fMRI) analysis during alterations of consciousness in humans, we report that synchronized and incoherent networks, respectively, bias toward internal and external information with specific network configurations. In the brain network model and EEG-based network, the network preferences are the most prominent at criticality and in conscious states associated with the bandwidth 4−12 Hz, with alternating functional network configurations. However, these network configurations are selectively disrupted in different states of consciousness such as general anesthesia, psychedelic states, minimally conscious states, and unresponsive wakefulness syndrome. The network preference for internal information integration is only significant in conscious states and psychedelic states, but not in other unconscious states, suggesting the importance of internal information integration in maintaining consciousness. The fMRI co-activation pattern analysis shows that functional networks that are sensitive to external stimuli–such as default mode, dorsal attentional, and frontoparietal networks–are activated in incoherent states, while insensitive networks, such as global activation and deactivation networks, are dominated in highly synchronized states. We suggest that criticality produces a functional platform for the brain’s capability for continuous switching between two modes, which is crucial for the emergence of consciousness.
    01A - Beitrag in wissenschaftlicher Zeitschrift
  • Vorschaubild
    Publikation
    Relationship of critical dynamics, functional connectivity, and states of consciousness in large-scale human brain networks
    (Elsevier, 2019) Lee, Heonsoo; Golkowski, Daniel; Jordan, Denis; Berger, Sebastian; Ilg, Rüdiger; Lee, Joseph; Mashour, George A.; Lee, UnCheol; Avidan, Michael S.; Blain-Moraes, Stefanie; Golmirzaie, Goodarz; Hardie, Randall; Hogg, Rosemary; Janke, Ellen; Kelz, Max B.; Maier, Kaitlyn; Mashour, George A.; Maybrier, Hannah; McKinstry-Wu, Andrew; Muench, Maxwell; Ochroch, Andrew; Palanca, Ben J.A.; Picton, Paul; Schwarz, E. Marlon; Tarnal, Vijay; Vanini, Giancarlo; Vlisides, Phillip E. [in: NeuroImage]
    Recent modeling and empirical studies support the hypothesis that large-scale brain networks function near a critical state. Similar functional connectivity patterns derived from resting state empirical data and brain network models at criticality provide further support. However, despite the strong implication of a relationship, there has been no principled explanation of how criticality shapes the characteristic functional connectivity in large-scale brain networks. Here, we hypothesized that the network science concept of partial phase locking is the underlying mechanism of optimal functional connectivity in the resting state. We further hypothesized that the characteristic connectivity of the critical state provides a theoretical boundary to quantify how far pharmacologically or pathologically perturbed brain connectivity deviates from its critical state, which could enable the differentiation of various states of consciousness with a theory-based metric. To test the hypothesis, we used a neuroanatomically informed brain network model with the resulting source signals projected to electroencephalogram (EEG)-like sensor signals with a forward model. Phase lag entropy (PLE), a measure of phase relation diversity, was estimated and the topography of PLE was analyzed. To measure the distance from criticality, the PLE topography at a critical state was compared with those of the EEG data from baseline consciousness, isoflurane anesthesia, ketamine anesthesia, vegetative state/unresponsive wakefulness syndrome, and minimally conscious state. We demonstrate that the partial phase locking at criticality shapes the functional connectivity and asymmetric anterior-posterior PLE topography, with low (high) PLE for high (low) degree nodes. The topographical similarity and the strength of PLE differentiates various pharmacologic and pathologic states of consciousness. Moreover, this model-based EEG network analysis provides a novel metric to quantify how far a pharmacologically or pathologically perturbed brain network is away from critical state, rather than merely determining whether it is in a critical or non-critical state.
    01A - Beitrag in wissenschaftlicher Zeitschrift
  • Vorschaubild
    Publikation
    Teaching ordinal patterns to a computer. Efficient encoding algorithms based on the Lehmer code
    (MDPI, 2019) Berger, Sebastian; Kravtsiv, Andrii; Schneider, Gerhard; Jordan, Denis [in: Entropy]
    Ordinal patterns are the common basis of various techniques used in the study of dynamical systems and nonlinear time series analysis. The present article focusses on the computational problem of turning time series into sequences of ordinal patterns. In a first step, a numerical encoding scheme for ordinal patterns is proposed. Utilising the classical Lehmer code, it enumerates ordinal patterns by consecutive non-negative integers, starting from zero. This compact representation considerably simplifies working with ordinal patterns in the digital domain. Subsequently, three algorithms for the efficient extraction of ordinal patterns from time series are discussed, including previously published approaches that can be adapted to the Lehmer code. The respective strengths and weaknesses of those algorithms are discussed, and further substantiated by benchmark results. One of the algorithms stands out in terms of scalability: its run-time increases linearly with both the pattern order and the sequence length, while its memory footprint is practically negligible. These properties enable the study of high-dimensional pattern spaces at low computational cost. In summary, the tools described herein may improve the efficiency of virtually any ordinal pattern-based analysis method, among them quantitative measures like permutation entropy and symbolic transfer entropy, but also techniques like forbidden pattern identification. Moreover, the concepts presented may allow for putting ideas into practice that up to now had been hindered by computational burden. To enable smooth evaluation, a function library written in the C programming language, as well as language bindings and native implementations for various numerical computation environments are provided in the supplements.
    01A - Beitrag in wissenschaftlicher Zeitschrift
  • Vorschaubild
    Publikation
    Investigating roundabout properties and bicycle accident occurrence at Swiss roundabouts: A logistic regression approach
    (MDPI, 2019) Hollenstein, Daria; Hess, Martin; Jordan, Denis; Bleisch, Susanne [in: ISPRS International Journal of Geo-Information]
    The positive effects of active mobility on mental and physical health as well as on air quality are widely acknowledged. Increasing the share of active travel is therefore an aim in many countries. Providing bicycle-safe infrastructure is one way to promote cycling. Roundabouts are a common traffic infrastructure and are supposed to facilitate safe and smooth traffic flow. However, data on road traffic accidents indicate an over-proportional involvement of cyclists in accidents at roundabouts. In the present study, the influence of roundabout geometry and traffic flow on bicycle accident occurrence was investigated using a logistic regression approach on twelve parameters of N = 294 mostly small- and mini-sized single-lane roundabouts in the Canton of Berne, Switzerland. Average weekday motorized traffic was identified as a major factor in explaining bicycle accident occurrence at roundabouts. Further, the radius of the central island, the location of the roundabout (in town vs. out of town) and the number of legs were significantly related to bicycle accident occurrence. While these results are in general agreement with findings from similar studies, the findings regarding the central island’s radius and the number of legs underpin the need for roundabout type-specific studies: Some parameters may not prove relevant in intermediate- to large-sized roundabouts, but become critical in small or mini roundabouts, which are common in Switzerland and numerous in the present sample.
    01A - Beitrag in wissenschaftlicher Zeitschrift
  • Vorschaubild
    Publikation
    Spectral dynamics of resting state fMRI within the ventral tegmental area and dorsal raphe nuclei in medication-free major depressive disorder in young adults
    (Frontiers Research Foundation, 2018) Wohlschläger, Afra; Karne, Harish; Jordan, Denis; Lowe, Mark J.; Jones, Stephen E.; Anand, Amit [in: Frontiers in Psychiatry]
    Background: Dorsal raphe nucleus (DRN) and ventral tegmental area (VTA) are major brainstem monamine nuclei consisting of serotonin and dopamine neurons respectively. Animal studies show that firing patterns in both nuclei are altered when animals exhibit depression like behaviors. Functional MRI studies in humans have shown reduced VTA activation and DRN connectivity in depression. This study for the first time aims at investigating the functional integrity of local neuronal firing concurrently in both the VTA and DRN in vivo in humans using spectral analysis of resting state low frequency fluctuation fMRI. Method: A total of 97 medication-free subjects-67 medication-free young patients (ages 18-30) with major depressive disorder and 30 closely matched healthy controls were included in the study to detect aberrant dynamics in DRN and VTA. For the investigation of altered localized dynamics we conducted power spectral analysis and above this spectral cross correlation between the two groups. Complementary to this, spectral dependence of permutation entropy, an information theoretical measure, was compared between groups. Results: Patients displayed significant spectral slowing in VTA vs. controls (p = 0.035, corrected). In DRN, spectral slowing was less pronounced, but the amount of slowing significantly correlated with 17-item Hamilton Depression Rating scores of depression severity (p = 0.038). Signal complexity as assessed via permutation entropy showed spectral alterations inline with the results on spectral slowing. Conclusion: Our results indicate that altered functional dynamics of VTA and DRN in depression can be detected from regional fMRI signal. On this basis, impact of antidepressant treatment and treatment response can be assessed using these markers in future studies.
    01A - Beitrag in wissenschaftlicher Zeitschrift