Brain and Cognition
Seminar Brain and Cognition: Exploring the relations between structure, dynamics and function of biological neural networks
Preparatory meeting
Thursday, 03.11.2011, 17.00 - 18.00 h, Bernstein Center, Hansastr. 9a, Lecture Hall
Date
24.02. and 25.02.2012
Schedule see here
Instructors
Arvind Kumar
Ad Aertsen
Kurzkommentar
Since Euler's treatment of the celebrated "Seven Bridges of Königsberg" math puzzle as a network problem in 1735, graphs and networks have been used as model descriptions in virtually every facet of nature. Networks are particularly prevalent in biological systems. Neuronal network models have been the work horses of theoretical and computational neuroscientists for decades, not only to better understand biological neuronal networks, but also to draw inspiration for the analysis of experimental data and to help understand the function of the brain. Groundbreaking work by Erdós and Rényi laid the foundations to employ random networks as models. This has provided important insight into the dynamics of large networks in the brain. In fact, such models have served as a test bed for a variety of theoretical concepts. With recent advances in experimental techniques, however, it is becoming increasingly clear that the networks of the brain have statistical features that considerably deviate from classical random networks. Thus, the study of structured neuronal networks per se, and of the relations and constraints between structure, dynamics and function of networks, is rapidly developing into a new research paradigm in neuroscience.
A podcast about network structure by the BCF scientists http://podcast2.ruf.uni-freiburg.de/Videodata/rsbccn/podcast/Podcast03.mp3 In this oberseminar we will discuss various recent theoretical publications that have investigate the role of network structure on the dynamics and function of the network. There are paper that discuss the non-randomness of networks in brains [1-5]. How deviations from homogeneous random networks affect the network dynamics is discussed in papers 6-10. Kitsak et al [11] describe how structure affects flow of information in a network and Liu et al. [12] describe how to control the dynamics of a complex network. This collection contains a number of excellent reviews [1-4, 6]. In addition we will also discuss selected recent experimental papers that have provided key evidence for non-classical random networks in the brain [13-16].
Literatur
1. Sporns (2011) The Non-Random Brain: Efficiency, Economy, and Complex Dynamics. Front Comput Neurosci; 5: 5.
2. Bullmore, E.T, Sporns, O. (2009) Complex brain networks: graph-theoretical analysis of structural and functional systems. Nature Reviews Neuroscience 10, 186-198.
3. Meunier (2011) Modular and hierarchically modular organization of brain networks. Front. Neurosci. 4:200. doi: 10.3389/ fnins.2010.00200
4. Newman (2003) The structure and function of complex networks, SIAM Review 45, 167-256.
5. Varshney et al (2011) Stuctural properties of the C. elegans neuronal network. http://openwiki.janelia.org/wiki/download/attachments/12157120VarshneyChenPaniaguaHallChklovskii09.pdf?version=1
6. Arenas et al (2008) Synchronization in complex networks. Physics Reports, 469:93-153.
7. Kriener et al. (2009) Correlations in spiking neuronal networks with distance dependent connections. J Comput Neurosci 27 : 177-200
8. Roxin A (2011) The role of degree distribution in shaping the dynamics in networks of sparsely connected spiking neurons. Front. Comput. Neurosci. 5:8. doi: 10.3389/fncom.2011.00008
9. Zhao L, Beverlin B, Netoff T and Nykamp DQ (2011). Synchronization from second order network connectivity statistics. Front. Comput. Neurosci. 5:28. doi: 10.3389/fncom.2011.00028
10. Pernice et al (2011) How Structure Determines Correlations in Neuronal Networks PLoS Comput Biol 7(5) : e1002059
11. Kitsak et al (2010) Identification of influential spreaders in complex networks. Nature Physics 6, 888-893
12. Liu et al (2011) Controllability of complex networks. Nature 473, 167-173
13. Boucsein et al (2011) Beyond the cortical column: abundance and physiology of horizontal connections imply a strong role for inputs from the surround. Front Neurosci 5 : 32
14. Fino and Yuste (2011) Dense Inhibitory Connectivity in Neocortex. Neuron. 69, 1188-1203.
15. Bonifazi, et al. (2009) GABAergic Hub Neurons Orchestrate Synchrony in Developing Hippocampal Networks P. Science 326, 1419
16. Gerhard F, Pipa G, Lima B, Neuenschwander S and Gerstner W (2011) Extraction of network topology from multi-electrode recordings: is there a small-world effect? Front. Comput. Neurosci. 5:4. doi: 10.3389/fncom.2011.00004
* Some papers will be studies together, that will described in the introduction to the obserseminar.
Zielgruppe
Students in Biology Diploma
M.Sc. Students in Bioinformatics/Systemsbiology
PhD-Students in Computational Neuroscience
PhD-Students in Neuroscience
Important: If we have less that six participants, there will be no Oberseminar.