Jordan, Denis

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Denis
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Denis Jordan

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Gerade angezeigt 1 - 6 von 6
  • Vorschaubild
    Publikation
    Traffic impact of flexibly rented, private parking spaces
    (11.04.2024) Erath, Alexander; Meyer, Adrian; Venuleo, Sara; Jordan, Denis; Büttner, Benjamin; Wulfhorst, Gebhard [in: mobil.TUM 2024]
    04B - Beitrag Konferenzschrift
  • Vorschaubild
    Publikation
    Verkehrliche Wirkung der flexiblen Vermietung privater Parkfelder
    (Fachhochschule Nordwestschweiz FHNW, 27.11.2023) Erath, Alexander; Meyer, Adrian; Venuleo, Sara; Jordan, Denis
    05 - Forschungs- oder Arbeitsbericht
  • 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
    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
    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