People
Personnel
Marja-Leena Linne
- Senior Research Fellow
- Faculty of Medicine and Health Technology
- Tampere University
- +358503450649
- marja-leena.linne@tuni.fi
Jugoslava Acimovic
- Visiting Researcher
- Faculty of Medicine and Health Technology
- Tampere University
- jugoslava.acimovic@tuni.fi
About me
I am a senior researcher in the Computational Neuroscience group (https://research.tuni.fi/computational-neuroscience/ ) which is part of the Faculty of Medicine and Health Technology at Tampere University. I graduated electrical engineering, focusing on signal processing and communication systems, at University of Belgrade, Serbia. I received a PhD from Ecole Polytechnique Fédérale de Lausanne (EPFL), Switzerland. During doctoral studies, I worked in the group of Nonlinear Dynamical Systems where I was trained in complex networks, machine learning and data analysis. My doctoral work focused on motor control in Parietal area 7a in the primate brain.
I employ computational modeling, experimental data analysis and complex networks theory to explore the impact of cellular and network mechanisms on dynamical regimes and structural organization of cortical neuronal networks. My work explored how the morphometric properties of neurons and neuronal populations constrain their micro-level connectivity. I study how the structured connectivity, the excitation-inhibition balance and other cellular and network mechanisms modulate the global population dynamics. My recent work was a data-driven computational model of dynamical regimes found in dissociated cortical cultures in vitro under several experimental conditions. Currently, I explore the contribution of specific astrocytic mechanisms and astrocyte-neuron interaction in cortical circuits.
Responsibilities
- Research tasks
- Supervision of student projects
- Teaching computational neuroscience and neuroinformatics (as invited lecturer)
Research topics
Computational models of cortical networks, Complex networks
Research unit
Computational Neuroscience Group, Faculty of Medicine and Health Technology
Research fields
Computational neuroscience
H. Teppola, J. Aćimović, M.-L. Linne. Unique Features of Network Bursts Emerge From the Complex Interplay of Excitatory and Inhibitory Receptors in Rat Neocortical Networks. Front Cell Neurosci. 2019;13: 377
https://www.frontiersin.org/articles/10.3389/fncel.2019.00377/full
T. Manninen, J. Aćimović, R. Havela, H. Teppola, M.-L. Linne (2018) Challenges in reproducibility, replicability, and comparability of computational models and tools for neuronal and glial networks, cells, and subcellular structures. Front Neuroinformatics 12: 20, 2018. https://www.frontiersin.org/articles/10.3389/fninf.2018.00020/full
J. Aćimović, T. Mäki-Marttunen, M.-L. Linne (2015) The effects of neuron morphology on graph theoretic measures of network connectivity: Analysis of two-level statistical model. In Front. Neuroanat. 9:76, June 2015 http://journal.frontiersin.org/article/10.3389/fnana.2015.00076/full
T. Mäki-Marttunen, J. Aćimović, M.-L. Linne (2014) Structure-dynamics relationships in bursting neuronal networks revealed using a prediction framework. PLOS One 8(7): e69373, doi:10.1371/journal.pone.006 9373 http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0069373
J. Aćimović, T. Mäki-Marttunen, R. Havela, H. Teppola, M.-L. Linne (2011) Models of neuronal growth in vitro: Comparison of two simulators of growth, Cortex3D and NETMORPH. EURASIP Journal on Bioinformatics and Systems Biology, vol 2011, doi:10.1155/2011/61638
http://bsb.eurasipjournals.springeropen.com/articles/10.1155/2011/616382
T. Mäki-Marttunen, J. Aćimović, M. Nykter, J. Kesseli, O. Yli-Harja, M.-L. Linne (2011) Complexity of Structure and Dynamics in Simulated Neuronal Networks. Front. Comput. Neurosci, 5:26, 2011, doi: 10.3389/fncom.2011.00026 http://journal.frontiersin.org/article/10.3389/fncom.2011.00026/full
Tiina Manninen
- Senior Research Fellow
- Faculty of Medicine and Health Technology
- Tampere University
- tiina.manninen@tuni.fi
About me
I received MSc(Eng) degree in mathematics in September 2003 and DSc(Tech) degree in mathematics in December 2007 from Tampere University of Technology. At the moment I am a Senior Research Fellow in the Computational Neuroscience Group at Tampere University and a Visiting Scientist in Gladstone Institutes.
Research topics
Development of computational models for neuronal and glial cells. See our website Computational Neuroscience Group for model details.
Research unit
Computational Neuroscience Group
Research fields
Computational Neuroscience
L. Keto and T. Manninen. CellRemorph: A toolkit for transforming, selecting, and slicing 3D cell structures on the road to morphologically detailed astrocyte simulations. Neuroinformatics, 2023. https://doi.org/10.1007/s12021-023-09627-5
T. Manninen, J. Aćimović, and M.-L. Linne. Analysis of network models with neuron-astrocyte interactions. Neuroinformatics, 2023. https://doi.org/10.1007/s12021-023-09622-w
M.-L. Linne, J. Aćimović, A. Saudargiene, and T. Manninen. Neuron-glia interactions and brain circuits. Computational Modelling of the Brain, (M. Giugliano, M. Negrello, and D. Linaro eds.), Springer Series in Advances in Experimental Medicine and Biology, vol. 1359, 87-103, 2022. https://doi.org/10.1007/978-3-030-89439-9_4
T. Manninen, A. Saudargiene, and M.-L. Linne. Astrocyte-mediated spike-timing-dependent long-term depression modulates synaptic properties in the developing cortex. PLoS Computational Biology 16(11):e1008360, 2020. https://doi.org/10.1371/journal.pcbi.1008360
H. L. Payne, R. L. French, C. C. Guo, T. D. B. Nguyen-Vu, T. Manninen, and J. L. Raymond. Cerebellar Purkinje cells control eye movements with a rapid rate code that is invariant to spike irregularity. eLife 8:e37102, 2019. https://doi.org/10.7554/eLife.37102
T. Manninen, R. Havela, and M.-L. Linne. Computational models of astrocytes and astrocyte-neuron interactions: Characterization, reproducibility, and future perspectives. Computational Glioscience, (M. De Pittà and H. Berry eds.), Springer Series in Computational Neuroscience, 423 - 454, 2019. https://doi.org/10.1007/978-3-030-00817-8_16
T. Manninen, J. Aćimović, R. Havela, H. Teppola, and M.-L. Linne. Challenges in reproducibility, replicability, and comparability of computational models and tools for neuronal and glial networks, cells, and subcellular structures. Frontiers in Neuroinformatics (Part of Research Topic: Reproducibility and Rigour in Computational Neuroscience) 12:20, 2018. https://doi.org/10.3389/fninf.2018.00020
T. Manninen, R. Havela, and M.-L. Linne. Computational models for calcium-mediated astrocyte functions. Frontiers in Computational Neuroscience 12:14, 2018. https://doi.org/10.3389/fncom.2018.00014
N. P. Rougier, K. Hinsen, F. Alexandre, T. Arildsen, L. A. Barba, F. C. Y. Benureau, C. T. Brown, P. de Buyl, O. Caglayan, A. P. Davison, M.-A. Delsuc, G. Detorakis, A. K. Diem, D. Drix, P. Enel, B. Girard, O. Guest, M. G. Hall, R. N. Henriques, X. Hinaut, K. S. Jaron, M. Khamassi, A. Klein, T. Manninen, P. Marchesi, D. McGlinn, C. Metzner, O. Petchey, H. E. Plesser, T. Poisot, K. Ram, Y. Ram, E. Roesch, C. Rossant, V. Rostami, A. Shifman, J. Stachelek, M. Stimberg, F. Stollmeier, F. Vaggi, G. Viejo, J. Vitay, A. E. Vostinar, R. Yurchak, and T. Zito. Sustainable computational science: the ReScience initiative. PeerJ Computer Science 3:e142, 2017. https://doi.org/10.7717/peerj-cs.142
T. Manninen, R. Havela, and M.-L. Linne. Reproducibility and comparability of computational models for astrocyte calcium excitability. Frontiers in Neuroinformatics 11:11, 2017. https://doi.org/10.3389/fninf.2017.00011
J. Intosalmi, T. Manninen, K. Ruohonen, and M.-L. Linne. Computational study of noise in a large signal transduction network. BMC Bioinformatics 12:252, 2011. https://doi.org/10.1186/1471-2105-12-252
E. Toivari, T. Manninen, A. K. Nahata, T. O. Jalonen, and M.-L. Linne. Effects of transmitters and amyloid-beta peptide on calcium signals in rat cortical astrocytes: Fura-2AM measurements and stochastic model simulations. PLoS ONE 6(3): e17914, 2011. https://doi.org/10.1371/journal.pone.0017914
T. Manninen, K. Hituri, E. Toivari, and M.-L. Linne. Modeling signal transduction leading to synaptic plasticity: evaluation and comparison of five models. EURASIP Journal on Bioinformatics and Systems Biology 2011: 797250, 2011. https://bsb-eurasipjournals.springeropen.com/articles/10.1155/2011/797250
T. Manninen, K. Hituri, J. Hellgren Kotaleski, K. T. Blackwell, and M.-L. Linne. Postsynaptic signal transduction models for long-term potentiation and depression. Frontiers in Computational Neuroscience 4:152, 2010. https://doi.org/10.3389/fncom.2010.00152
T. Manninen, M.-L. Linne, and K. Ruohonen. Developing Itô stochastic differential equation models for neuronal signal transduction pathways. Computational Biology and Chemistry 30(4): 280 – 291, 2006. https://doi.org/10.1016/j.compbiolchem.2006.04.002
T. Manninen, M.-L. Linne, and K. Ruohonen. A novel approach to model neuronal signal transduction using stochastic differential equations. Neurocomputing 69(10 – 12): 1066 – 1069, 2006. https://doi.org/10.1016/j.neucom.2005.12.047
A. Pettinen, T. Aho, O.-P. Smolander, T. Manninen, A. Saarinen, K.-L. Taattola, O. Yli-Harja, and M.-L. Linne. Simulation tools for biochemical networks: evaluation of performance and usability. Bioinformatics 21(3): 357 – 363, 2005. https://doi.org/10.1093/bioinformatics/bti018
M.-L. Linne, T. Manninen, and T. O. Jalonen. A model integrating the cerebellar granule neuron excitability and calcium signaling pathways. Neurocomputing 58 – 60: 569 – 574, 2004. https://doi.org/10.1016/j.neucom.2004.01.096
Tuomo Mäki-Marttunen
- Academy Research Fellow
- Faculty of Medicine and Health Technology
- Tampere University
- +358505911491
- tuomo.maki-marttunen@tuni.fi
About me
I am a principal investigator in Computational Neuropsychiatry in Tampere University. My current primary research topic is the disease mechanisms of schizophrenia. I use mathematical modelling of single neurons, neuronal networks as well as intracellular signaling pathways to study the contribution of different schizophrenia-associated genes to cellular and network phenotypes. In particular, I am interested in the cellular and network level mechanisms of EEG-measurable phenotypes of schizophrenia, such as increased delta oscillations and mismatch negativity. My previous research topics revolve around structure and function of neuronal networks and other complex networks, and include topics such as dynamics of Boolean networks, structure and dynamics of dissociated neuronal cultures, measures of complexity, and analysis of network connectivities.
I am leading an Academy of Finland starting grant "ModelPsych: Neural model building for psychiatric diseases - From genes to networks" and an EBRAINS voucher project "Startle-network modelling for Schizophrenia research – Insights from subcellular models of neuromodulation (SubSchiz)".
More about my research (popularized-science blog posts and articles):
Schizophrenia mechanisms can be studied with mathematical modelling
Breaking the code of schizophrenia
Publications: