Bernstein Group for Computational Neuroscience
Home > Projects > Ongoing dynamics of neocortex: modelling amplitude and phase modulations in cortical networks

Ongoing dynamics of neocortex: modelling amplitude and phase modulations in cortical networks 
(Herrmann (leader), Hinrichs, Ohl)

Scientific background and state-of-the-art

In recent years a major goal in neuroscience has been to better understand the neuronal dynamics in cortical networks. A key issue in this topic is how input into cortical networks is processed. It is currently hotly debated how amplitude and phase of ongoing cortical neural activity are generated and modulated by input. Input into a cortical area can in general come from either the periphery (bottomup) or from "higher" cortical areas ("top-down"). The detailed mechanisms for the generation of neocortical oscillations are currently under debate. For example, some models for the generation of gamma oscillations propose an interaction of glutamatergic pyramidal cells with GABAergic interneurons (e.g. Whittington et al. 1995; Haider et al. 2006) while other models emphasize the relevance of thalamocortical loops (e.g. Llinás et al. 2002). The current project aims at resolving this issue. A further presently unresolved issue is how event-related potentials are generated. A debate exists whether the event-related potential is predominantly accounted for by phase-reset of ongoing activity
(e.g. Brandt & Jansen 1991; Makeig et al. 2002; Klimesch et al. 2004) or a stimulus-induced increase in EEG activity (e.g. Schroeder et al. 1995). In order to resolve both issues two approaches have been suggested. The first one is to perform intracranial recordings in animals which allow selective pharmacological (and other) manipulations of the cortical network (Barth & MacDonald 1996). A second approach is the explicit modelling of the amplitude and phase organization of cortical activity by biologically plausible neural networks (Destexhe et al. 1999; Izhikevich 2003). In addition, the combination of both approaches allows investigation of the relationship between microscopic (spike train) and macroscopic levels (LFP, EEG). In the present project we will use both approaches and additionally include intracranial recordings in humans.


References:

Barth DS, MacDonald KD (1996) Thalamic modulation of high-frequency oscillating potentials in auditory cortex. Nature
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Brandt ME , Jansen BH (1991) The relationship between prestimulus-alpha amplitude and visual evoked potential amplitude. Int J Neurosci 6: 261-268.

Destexhe A, Contreras D, Steriade M. (1999) Cortically-induced coherence of a thalamic-generated oscillation. Neuroscience
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Haider B, Duque A, Hasenstaub AR, McCormick DA (2006) Neocortical network activity in vivo is generated through a dynamic balance of excitation and inhibition. J Neurosci 26: 4535-4545.

Izhikevich EM (2003) Simple model of spiking neurons. IEEE Trans Neural Networks 14: 1569-1572.

Klimesch W, Schack B, Schabus M, Doppelmayr M, Gruber W, Sauseng P (2004) Phase-locked alpha and theta oscillations
generate the P1 N1 complex and are related tomemory performance. Cog Brain Res 19: 302-316.

Llinás RR, Leznik E, Urbano FJ (2002) Temporal binding via cortical coincidence detection of specific and non-specific thalamocortical inputs: A voltage-dependent dye-imaging study in mouse brain slices. Proc Natl Acad Sci 99: 449
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Makeig S, Westerfield M, Jung TP, Enghoff S, Townsend J, Courchesne E, Sejnowski TJ (2002) Dynamic brain sources of visual evoked potentials. Science 295: 690-694.

Schroeder CE, Steinschneider M, Javitt DC, Tenke CE, Givre SJ, Mehta AD, Simpson GV, Arezzo JC, Vaughan HG (1995) Localization of ERP generators and identification of underlying neural processes. Electroencephalogr Clin Neurophysiol Suppl 44: 55-75.

Whittington MA, Traub RD, Jefferys JG (1995) Synchronized oscillations in interneuron networks driven by metabotropic glutamate receptor activation. Nature 373: 612-615.

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