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Masters Internship: Information processing in a neuronal network model of critical oscillations

Introduction

Information processing in the brain depends on communication between neurons and populations of neurons at different spatial and temporal scales (Varela et al., 2001; Chialvo, 2010). Neuronal oscillations and, more recently, neuronal avalanches have been proposed to play an important role in this communication. Interestingly, both oscillations (Linkenkaer-Hansen et al., 2001) and neuronal avalanches (Beggs and Plenz, 2003) show hallmarks of critical behaviour. Further, theoretical studies have linked criticality in terms of neuronal avalanches to desired information-processing characteristics such as reactivity, adaptability and robustness to input, and the activation of neuronal representations in the form of meta-stable activity patterns (Haldeman and Beggs, 2005; Kinouchi and Copelli, 2006; Shew et al., 2009; Shew et al., 2011). Recently, we developed the critical oscillations (CROS) neuronal network model, which indicated a tight relationship between oscillations that are critical and neuronal avalanches (Poil et al., 2012). We are currently looking for internship students that will join our efforts to elucidate the role of critical-state dynamics in neuronal networks for how information is processed and stored in the brain.

Aim

The aim is to understand the relationship between critical oscillations and information processing. This will be done by investigating the network’s ability to respond to stimuli, to store and recall patterns of activity, and its ability to interact with other networks.

Your profile

• Programming experience and the interest to become proficient in MATLAB.
• Willingness to work considerably independent.
• Good collaboration skills.
• Good writing skills in English.
• Interest in signal processing and how the brain works.

Duration:

A minimum of 5 months

Start date:

Any time

Supervision:

Richard Hardstone and Klaus Linkenkaer-Hansen
Neuronal Oscillations and Cognition, CNCR

For information, please contact: Klaus Linkenkaer-Hansen

E-mail:

Phone:

0031 (020) 5986479

References:

Beggs, J.M., and Plenz, D. (2003). Neuronal avalanches in neocortical circuits. The Journal of Neuroscience 23, 11167-11177.
Chialvo, D.R. (2010). Emergent complex neural dynamics. Nature Physics 6, 744-750.
Haldeman, C., and Beggs, J.M. (2005). Critical branching captures activity in living neural networks and maximizes the number of metastable states. Physical review letters 94, 58101.

Kinouchi, O., and Copelli, M. (2006). Optimal dynamical range of excitable networks at criticality. Nature Physics 2, 348-351.
Linkenkaer-Hansen, K., Nikouline, V.V., Palva, J.M., and Ilmoniemi, R.J. (2001). Long-Range Temporal Correlations and Scaling Behavior in Human Brain Oscillations. The Journal of Neuroscience 21, 1370-1377.

Poil, S.-S., Hardstone, R., Mansvelder, H.D., and Linkenkaer-Hansen, K. (2012). Critical-State Dynamics of Avalanches and Oscillations Jointly Emerge from Balanced Excitation/Inhibition in Neuronal Networks. The Journal of Neuroscience 32, 9817-9823.

Shew, W., Yang, H., Petermann, T., Roy, R., and Plenz, D. (2009). Neuronal avalanches imply maximum dynamic range in cortical networks at criticality. The Journal of neuroscience: the official journal of the Society for Neuroscience 29, 15595.

Shew, W.L., Yang, H., Yu, S., Roy, R., and Plenz, D. (2011). Information Capacity and Transmission Are Maximized in Balanced Cortical Networks with Neuronal Avalanches. The Journal of neuroscience: the official journal of the Society for Neuroscience 31, 55.

Varela, F., Lachaux, J.P., Rodriguez, E., and Martinerie, J. (2001). The brainweb: phase synchronization and large-scale integration. Nature Reviews Neuroscience 2, 229-239.

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