Summary

Proceedings of the 2012 International Symposium on Nonlinear Theory and its Applications

2012

Session Number:B1L-B

Session:

Number:312

Multi-Scale Causation in Brain Dynamics

Hans Liljenström,  

pp.312-315

Publication Date:

Online ISSN:2188-5079

DOI:10.15248/proc.1.312

PDF download (301KB)

Summary:
For any complex system, consisting of several organizational levels, the problem of causation is profound. Usually, science considers upward causation as fundamental, paying less or no attention to any downward causation. This is also true for the nervous system, where cortical neurodynamics, or even higher mental functions of the brain are normally considered causally dependent on the nerve cell activity, or even the activity at the ion channel level. This study presents both upward and downward causation in cortical neural systems, using computational methods with focus on cortical fluctuations. We have developed models of paleo-and neocortical structures, in order to study their mesoscopic neurodynamics, as a link between the microscopic neuronal and macroscopic mental events and processes. We demonstrate how both noise and chaos may play a role for the functions of cortical structures. While microscopic random noise may trigger meso-or macroscopic states, the nonlinear dynamics at these levels may also affect the activity at the microscopic level.

References:

[1] D. Noble, “A theory of biological relativity: no privileged level of causation,” Interface Focus 2, pp.55-64, 2012.

[2] W. J. Freeman, Neurodynamics: An Exploration in Mesoscopic Brain Dynamics, Berlin: Springer, 2000.

[3] H. Liljenström, “Modeling the dynamics of olfactory cortex using simplified network units and realistic architecture,” Int. J. Neur. Syst. 2, pp.1-15, 1991.

[4] Y. Gu & H. Liljenström, “A neural network model of attention-modulated Neurodynamics,” Cogn. Neurodyn 1, pp.275-285, 2007.

[5] S. Johansson & P. Århem, “Single-channel currents trigger action potentials in small cultured hippocampal neurons,” Proc. Natl. Acad. Sci. 91, pp. 1761-1765, 1994.

[6] H. Liljenström, “Autonomous learning with complex dynamics,” Intl. J. Intell. Syst. 10, pp. 119-153, 1995.

[7] H. Liljenström & X. Wu, “Noise-enhanced performance in a cortical associative memory model,” Int. J. Neur. Syst. 6 pp. 19-29, 1995.

[8] H. Liljenström, ”Inducing phase transitions in mesoscopic brain dynamics”, In: Modeling Phase Transitions in the Brain (Steyn-Ross, D. A. and Steyn-Ross, M. L., eds.), New York: Springer, pp. 147-175, 2010.

[9] H. Liljenström & M. E. Hasselmo, “Cholinergic modulation of cortical oscillatory dynamics,” J. Neurophysiol. 74 pp. 288-297, 1995.

[10] S. Corchs & G. Deco, “Large-scale neural model for visual attention: Integration of experimental single-cell and fMRI data,” Cerebral Cortex, 12 pp. 339-348, 2002.

[11] C. McAdams & J. Maunsell, “Effects of attention on orientation-tuning functions of single neurons in macaque cortical are V4,” J. Neurosci. 19 pp. 431-441, 1999.

[12] P. Fries et al., “Modulation of oscillatory neuronal synchronization by selective visual attention,” Science 291 pp.1560-1563, 2001.

[13] A. von Stein, C. Chiang, & P. König, “Top-down processing mediated by interareal synchronization,” Proc. Natl. Acad. Sci. USA, 97 pp. 14748-14753, 2000.

[14] M. Siegel, K. P. Körding & P. König, “Integrating top-down and bottom-up sensory processing by somato-dendritic interactions,” J. Comp. Neurosci. 8 pp. 161-173, 2000.

[15] C. M. Gray et al., “Oscillatory responses in cat visual cortex exhibit inter-columnar synchronization which reflects global stimulus properties.” Nature 338 pp. 334-337, 1989.

[16] H. Liljenström, “Global effects of fluctuations in neural information processing,” Int. J. Neur. Syst. 7 pp. 497-505, 1996.

[17] H. Liljenström, “Network Effects of Synaptic Modifications,” Pharmacopsychiatry 43 pp. S67-S81, 2010.