Paul's Publications

Journal Articles

  • H. Yamamoto, F.P. Spitzner, T. Takemuro, V. Buendía, H. Murota, C. Morante, T. Konno, S. Sato, A. Hirano-Iwata, A. Levina, V. Priesemann, M.A. Muñoz, J. Zierenberg and J. Soriano
    Modular Architecture Facilitates Noise-Driven Control of Synchrony in Neuronal Networks
    Science Advances 9, eade1755 (2023)
    High-level information processing in the mammalian cortex requires both segregated processing in specialized circuits and integration across multiple circuits. One possible way to implement these seemingly opposing demands is by flexibly switching between states with different levels of synchrony. However, the mechanisms behind the control of complex synchronization patterns in neuronal networks remain elusive. Here, we use precision neuroengineering to manipulate and stimulate networks of cortical neurons in vitro, in combination with an in silico model of spiking neurons and a mesoscopic model of stochastically coupled modules to show that (i) a modular architecture enhances the sensitivity of the network to noise delivered as external asynchronous stimulation and that (ii) the persistent depletion of synaptic resources in stimulated neurons is the underlying mechanism for this effect. Together, our results demonstrate that the inherent dynamical state in structured networks of excitable units is determined by both its modular architecture and the properties of the external inputs.
  • J. Zierenberg, F.P. Spitzner, J. Dehning, V. Priesemann, M. Weigel and M. Wilczek
    How Contact Patterns Destabilize and Modulate Epidemic Outbreaks
    New Journal of Physics 25, 053033 (2023)
    The spread of a contagious disease clearly depends on when infected individuals come into contact with susceptible ones. Such effects, however, have remained largely unexplored in the study of epidemic outbreaks. In particular, it remains unclear how the timing of contacts interacts with the latent and infectious stages of the disease. Here, we use real-world physical proximity data to study this interaction and find that the temporal statistics of actual human contact patterns (i) destabilize epidemic outbreaks and (ii) modulate the basic reproduction number R0. We explain both observations by distinct aspects of the observed contact patterns. On the one hand, we find the destabilization of outbreaks to be caused by the temporal clustering of contacts leading to over-dispersed offspring distributions and increased probabilities of otherwise rare events (zero- and super-spreading). Notably, our analysis enables us to disentangle previously elusive sources of over-dispersion in empirical offspring distributions. On the other hand, we find the modulation of R0 to be caused by a periodically varying contact rate. Both mechanisms are a direct consequence of the memory in contact behavior, and we showcase a generative process that reproduces these non-Markovian statistics. Our results point to the importance of including non-Markovian contact timings into studies of epidemic outbreaks.
  • J.P. Neto, F.P. Spitzner and V. Priesemann
    Sampling Effects and Measurement Overlap Can Bias the Inference of Neuronal Avalanches
    PLoS Computational Biology 18, e1010678 (2022)
    To date, it is still impossible to sample the entire mammalian brain with single-neuron precision. This forces one to either use spikes (focusing on few neurons) or to use coarse-sampled activity (averaging over many neurons, e.g. LFP). Naturally, the sampling technique impacts inference about collective properties. Here, we emulate both sampling techniques on a simple spiking model to quantify how they alter observed correlations and signatures of criticality. We describe a general effect: when the inter-electrode distance is small, electrodes sample overlapping regions in space, which increases the correlation between the signals. For coarse-sampled activity, this can produce power-law distributions even for non-critical systems. In contrast, spike recordings do not suffer this particular bias and underlying dynamics can be identified. This may resolve why coarse measures and spikes have produced contradicting results in the past.
  • A. Hagemann, M.S. Kehl, J. Dehning, F.P. Spitzner, J. Niediek, M. Wibral, F. Mormann and V. Priesemann
    Intrinsic Timescales of Spiking Activity in Humans during Wakefulness and Sleep
    Information processing in the brain requires integration of information over time. Such an integration can be achieved if signals are maintained in the network activity for the required period, as quantified by the intrinsic timescale. While short timescales are considered beneficial for fast responses to stimuli, long timescales facilitate information storage and integration. We quantified intrinsic timescales from spiking activity in the medial temporal lobe of humans. We found extended and highly diverse timescales ranging from tens to hundreds of milliseconds, though with no evidence for differences between subareas. Notably, however, timescales differed between sleep stages and were longest during slow wave sleep. This supports the hypothesis that intrinsic timescales are a central mechanism to tune networks to the requirements of different tasks and cognitive states.
  • S. Contreras, J. Dehning, S.B. Mohr, S. Bauer, F.P. Spitzner and V. Priesemann
    Low Case Numbers Enable Long-Term Stable Pandemic Control without Lockdowns
    Science Advances 7, eabg2243 (2021)
    The traditional long-term solutions for epidemic control involve eradication or population immunity. Here, we analytically derive the existence of a third viable solution: a stable equilibrium at low case numbers, where test-trace-and-isolate policies partially compensate for local spreading events and only moderate restrictions remain necessary. In this equilibrium, daily cases stabilize around ten or fewer new infections per million people. However, stability is endangered if restrictions are relaxed or case numbers grow too high. The latter destabilization marks a tipping point beyond which the spread self-accelerates. We show that a lockdown can reestablish control and that recurring lockdowns are not necessary given sustained, moderate contact reduction. We illustrate how this strategy profits from vaccination and helps mitigate variants of concern. This strategy reduces cumulative cases (and fatalities) four times more than strategies that only avoid hospital collapse. In the long term, immunization, large-scale testing, and international coordination will further facilitate control.
  • K. Leite, P. Garg, F.P. Spitzner, S. Guerin Darvas, M. Bähr, V. Priesemann and S. Kügler
    α-Synuclein Impacts on Intrinsic Neuronal Network Activity Through Reduced Levels of Cyclic AMP and Diminished Numbers of Active Presynaptic Terminals
    Frontiers in Molecular Neuroscience 15, 868790 (2022)
    Alpha-synuclein (a-Syn) is intimately linked to synucleinopathies like Parkinson´s disease and dementia with Lewy bodies. However, the pathophysiological mechanisms that are triggered by this protein are still largely enigmatic. a-Syn overabundance may cause neurodegeneration through protein accumulation and mitochondrial deterioration but may also result in pathomechanisms independent from neuronal cell death. One such proposed pathological mechanism is the influence of a-Syn on non-stimulated, intrinsic brain activity. This activity is responsible for more than 90% of the brain's energy consumption, and is thus thought to play an eminent role in basic brain functionality. Here we report that a-Syn substantially disrupts intrinsic neuronal network burst activity in a long-term neuronal cell culture model. Mechanistically, the impairment of network activity originates from reduced levels of cyclic AMP and cyclic AMP-mediated signaling as well as from diminished numbers of active presynaptic terminals. The profound reduction of network activity due to a-Syn was mediated only by intracellularly expressed a-Syn, but not by a-Syn that is naturally released by neurons. Conversely, extracellular pre-formed fibrils of a-Syn mimicked the effect of intracellular a-Syn, suggesting that they trigger an off-target mechanism that is not activated by naturally released a-Syn. A simulation-based model of the network activity in our cultures demonstrated that even subtle effect sizes in reducing outbound connectivity, i.e., loss of active synapses, can cause substantial global reductions in non-stimulated network activity. These results suggest that even low-level loss of synaptic output capabilities caused by a-Syn may result in significant functional impairments in terms of intrinsic neuronal network activity. Provided that our model holds true for the human brain, then a-Syn may cause significant functional lesions independent from neurodegeneration.
  • S. Contreras, J. Dehning, M. Loidolt, J. Zierenberg, F.P. Spitzner, J.H. Urrea-Quintero, S.B. Mohr, M. Wilczek, M. Wibral and V. Priesemann
    The Challenges of Containing SARS-CoV-2 via Test-Trace-and-Isolate
    Nature Communications 12, 378 (2021)
    Without a cure, vaccine, or proven long-term immunity against SARS-CoV-2, test-trace-and-isolate (TTI) strategies present a promising tool to contain its spread. For any TTI strategy, however, mitigation is challenged by pre- and asymptomatic transmission, TTI-avoiders, and undetected spreaders, which strongly contribute to ”hidden' infection chains. Here, we study a semi-analytical model and identify two tipping points between controlled and uncontrolled spread: (1) the behavior-driven reproduction number ${R}_{t}^{H}$ of the hidden chains becomes too large to be compensated by the TTI capabilities, and (2) the number of new infections exceeds the tracing capacity. Both trigger a self-accelerating spread. We investigate how these tipping points depend on challenges like limited cooperation, missing contacts, and imperfect isolation. Our results suggest that TTI alone is insufficient to contain an otherwise unhindered spread of SARS-CoV-2, implying that complementary measures like social distancing and improved hygiene remain necessary.
  • F.P. Spitzner, J. Dehning, J. Wilting, A. Hagemann, J.P. Neto, J. Zierenberg and V. Priesemann
    MR. Estimator, a Toolbox to Determine Intrinsic Timescales from Subsampled Spiking Activity
    PLoS ONE 16, e0249447 (2021)
    Here we present our Python toolbox “MR. Estimator” to reliably estimate the intrinsic timescale from electrophysiologal recordings of heavily subsampled systems. Originally intended for the analysis of time series from neuronal spiking activity, our toolbox is applicable to a wide range of systems where subsampling—the difficulty to observe the whole system in full detail—limits our capability to record. Applications range from epidemic spreading to any system that can be represented by an autoregressive process. In the context of neuroscience, the intrinsic timescale can be thought of as the duration over which any perturbation reverberates within the network; it has been used as a key observable to investigate a functional hierarchy across the primate cortex and serves as a measure of working memory. It is also a proxy for the distance to criticality and quantifies a system's dynamic working point.
  • J. Dehning, J. Zierenberg, F.P. Spitzner, M. Wibral, J.P. Neto, M. Wilczek and V. Priesemann
    Inferring Change Points in the Spread of COVID-19 Reveals the Effectiveness of Interventions
    Science 369 (2020)
    Keeping the lid on infection spread From February to April 2020, many countries introduced variations on social distancing measures to slow the ravages of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Publicly available data show that Germany has been particularly successful in minimizing death rates. Dehning et al. quantified three governmental interventions introduced to control the outbreak. The authors predicted that the third governmental intervention—a strict contact ban since 22 March—switched incidence from growth to decay. They emphasize that relaxation of controls must be done carefully, not only because there is a 2-week lag between a measure being enacted and the effect on case reports but also because the three measures used in Germany only just kept virus spread below the growth threshold.
  • F.P. Spitzner, J. Zierenberg and W. Janke
    The Droplet Formation-Dissolution Transition in Different Ensembles: Finite-size Scaling from Two Perspectives
    SciPost Physics 5, 062 (2018)
    The formation and dissolution of a droplet is an important mechanism related to various nucleation phenomena. Here, we address the droplet formation-dissolution transition in a two-dimensional Lennard-Jones gas to demonstrate a consistent finite-size scaling approach from two perspectives using orthogonal control parameters. For the canonical ensemble, this means that we fix the temperature while varying the density and vice versa. Using specialised parallel multicanonical methods for both cases, we confirm analytical predictions at fixed temperature (rigorously only proven for lattice systems) and corresponding scaling predictions from expansions at fixed density. Importantly, our methodological approach provides us with reference quantities from the grand canonical ensemble that enter the analytical predictions. Our orthogonal finite-size scaling setup can be exploited for theoretical and experimental investigations of general nucleation phenomena—if one identifies the corresponding reference ensemble and adapts the theory accordingly. In this case, our numerical approach can be readily translated to the corresponding ensembles and thereby proves very useful for numerical studies of equilibrium droplet formation, in general.
  • J. Zierenberg, N. Fricke, M. Marenz, F.P. Spitzner, V. Blavatska and W. Janke
    Percolation Thresholds and Fractal Dimensions for Square and Cubic Lattices with Long-Range Correlated Defects
    Physical Review E 96, 062125 (2017)
    We study long-range power-law correlated disorder on square and cubic lattices. In particular, we present high-precision results for the percolation thresholds and the fractal dimension of the largest clusters as a function of the correlation strength. The correlations are generated using a discrete version of the Fourier filtering method. We consider two different metrics to set the length scales over which the correlations decay, showing that the percolation thresholds are highly sensitive to such system details. By contrast, we verify that the fractal dimension df is a universal quantity and unaffected by the choice of metric. We also show that for weak correlations, its value coincides with that for the uncorrelated system. In two dimensions we observe a clear increase of the fractal dimension with increasing correlation strength, approaching df→2. The onset of this change does not seem to be determined by the extended Harris criterion.
  • N. Fricke, J. Zierenberg, M. Marenz, F.P. Spitzner, V. Blavatska and W. Janke
    Scaling Laws for Random Walks in Long-Range Correlated Disordered Media
    Condensed Matter Physics 20, 13004 (2017)
    We study the scaling laws of diffusion in two-dimensional media with long-range correlated disorder through exact enumeration of random walks. The disordered medium is modelled by percolation clusters with correlations decaying with the distance as a power law, $r^{-a}$, generated with the improved Fourier filtering method. To characterize this type of disorder, we determine the percolation threshold $p_c$ by investigating cluster-wrapping probabilities. At $p_c$, we estimate the (sub-diffusive) walk dimension $d_w$ for different correlation exponents $a$. Above $p_c$, our results suggest a normal random walk behavior for weak correlations, whereas anomalous diffusion cannot be ruled out in the strongly correlated case, i.e., for small $a$.


If you wan to create your own publication list like this, check the python script I used to parse my bibtex file!