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Projects of SMARTSTART participants yielded several publications including peer-reviewed articles, preprints and conference papers. In the list below, names of the respective participants are highlighted in bold font.


  • Dehning, J., Zierenberg, J., Spitzner, F.P., Wibral, M., Neto, J.P., Wilczek, M., Priesemann, V., 2020. Inferring change points in the spread of COVID-19 reveals the effectiveness of interventions. Science 369.
  • Goenner, L., Maith, O., Koulouri, I., Baladron, J., Hamker, F.H., n.d. A spiking model of basal ganglia dynamics in stopping behavior supported by Arkypallidal neurons. European Journal of Neuroscience n/a.
  • Maith, O., Escudero, F.V., Dinkelbach, H.Ü., Baladron, J., Horn, A., Irmen, F., Kühn, A.A., Hamker, F.H., 2020. A computational model-based analysis of basal ganglia pathway changes in Parkinson’s disease inferred from resting-state fMRI. European Journal of Neuroscience n/a.
  • Müller, T.T., Lio, P., 2020. PECLIDES Neuro: A Personalisable Clinical Decision Support System for Neurological Diseases. Frontiers in Artificial Intelligence 3.
  • Spitzner, F.P., Dehning, J., Wilting, J., Hagemann, A., Neto, J.P., Zierenberg, J., Priesemann, V., 2020. MR. Estimator, a toolbox to determine intrinsic timescales from subsampled spiking activity. arXiv:2007.03367 [physics, q-bio].
  • Zeraati, R., Engel, T.A., Levina, A., 2020. Estimation of autocorrelation timescales with Approximate Bayesian Computations. bioRxiv 2020.08.11.245944.
  • Zeraati, R., Priesemann, V., Levina, A., 2020. Self-organization toward criticality by synaptic plasticity. arXiv:2010.07888 [cond-mat, physics:physics, q-bio].


  • Fakhar, K., Gonschorek, D., Schmors, L., Bielczyk, N., 2019. Neuronal Causes and Behavioural Effects: a Review on Logical, Methodological, and Technical Issues With Respect to Causal Explanations of Behaviour in Neuroscience.
  • Gutknecht, A.J., Barnett, L., 2019. Sampling distribution for single-regression Granger causality estimators. arXiv:1911.09625 [math, stat].
  • He, X., Liu, T., Fatemeh Hadaeghi, Jäger, H., 2019. Reservoir Transfer on Analog Neuromorphic Hardware. Presented at the IEEE NER19, San Diego.
  • Liu, Y., Schubert, J., Sonnenberg, L., Helbig, K.L., Hoei-Hansen, C.E., Koko, M., Rannap, M., Lauxmann, S., Huq, M., Schneider, M.C., Johannesen, K.M., Kurlemann, G., Gardella, E., Becker, F., Weber, Y.G., Benda, J., Møller, R.S., Lerche, H., 2019. Neuronal mechanisms of mutations in SCN8A causing epilepsy or intellectual disability. Brain 142, 376–390.
  • Pallasdies, F., Goedeke, S., Braun, W., Memmesheimer, R., 2019. From single neurons to behavior in the jellyfish Aurelia aurita. eLife 8, e50084.
  • Román Rosón, M., Bauer, Y., Kotkat, A.H., Berens, P., Euler, T., Busse, L., 2019. Mouse dLGN Receives Functional Input from a Diverse Population of Retinal Ganglion Cells with Limited Convergence. Neuron 102, 462-476.e8.
  • Sikos, L., Tomlinson, S.B., Heins, C., Grodner, D.J., 2019. What do you know? ERP evidence for immediate use of common ground during online reference resolution. Cognition 182, 275–285.
  • State, L., Vilimelis Aceituno, P., 2019. Training Delays in Spiking Neural Networks, in: Tetko, I.V., Kůrková, V., Karpov, P., Theis, F. (Eds.), Artificial Neural Networks and Machine Learning – ICANN 2019: Theoretical Neural Computation, Lecture Notes in Computer Science. Springer International Publishing, Cham, pp. 713–717.
  • Wilting, J., Dehning, J., Pinheiro Neto, J., Rudelt, L., Wibral, M., Zierenberg, J., Priesemann, V., 2018. Operating in a Reverberating Regime Enables Rapid Tuning of Network States to Task Requirements. Front. Syst. Neurosci. 12.
  • Zeraati, R., Engel, T., Levina, A., 2019a. Critical avalanches in a spatially structured model of cortical On-Off dynamics. Presented at the DPG Frühjahrstagung 2019, Regensburg.
  • Zeraati, R., Steinmetz, N., Moore, T., Engel, T., Levina, A., 2019b. Signatures of network structure in timescales of spontaneous activity. Presented at the 28th Annual Computational Neuroscience Meeting, Barcelona.
  • Zeraati, R., Steinmetz, N., Moore, T., Engel, T., Levina, A., 2019c. Timescales of spontaneous cortical dynamics reflect the underlying spatial network structure. Presented at the 15h Bernstein Conference, Berlin.


  • Venniro, M., Zhang, M., Caprioli, D., Hoots, J.K., Golden, S.A., Heins, C., Morales, M., Epstein, D.H., Shaham, Y., 2018. Volitional social interaction prevents drug addiction in rat models. Nat. Neurosci. 21, 1520–1529.


  • Bug, D., Schneider, S., Grote, A., Oswald, E., Feuerhake, F., Schüler, J., Merhof, D., 2017. Context-Based Normalization of Histological Stains Using Deep Convolutional Features, in: Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support, Lecture Notes in Computer Science. Springer, Cham, pp. 135–142.
  • Symvoulidis, P., Lauri, A., Stefanoiu, A., Cappetta, M., Schneider, S., Jia, H., Stelzl, A., Koch, M., Perez, C.C., Myklatun, A., Renninger, S., Chmyrov, A., Lasser, T., Wurst, W., Ntziachristos, V., Westmeyer, G.G., 2017. NeuBtracker—imaging neurobehavioral dynamics in freely behaving fish. Nature Methods 14, 1079–1082.
  • Welke, D., Behncke, J., Hader, M., Schirrmeister, R.T., Schönau, A., Eßmann, B., Müller, O., Burgard, W., Ball, T., 2017. Brain Responses During Robot-Error Observation. arXiv:1708.01465 [cs].


  • Ernst, U.A., Schiffer, A., Persike, M., Meinhardt, G., 2016. Contextual Interactions in Grating Plaid Configurations Are Explained by Natural Image Statistics and Neural Modeling. Front. Syst. Neurosci. 10.