Moderator: Arjen van Ooyen (Amsterdam)

Abstracts

Role of inhibition in neuronal network oscillations
R.A.J. van Elburg, K. van Aerde, U.D. Reinacher, H. Mansvelder, A.B. Brussaard, A. van Ooyen
Experimentele Neurofysiologie, Vrije Universiteit Amsterdam

In this talk, we explore the role of interneurons in the generation of network oscillations in the prefrontal cortex. The prefrontal cortex is involved in higher cognitive functions such as attention, working memory, and planning. In attention tasks, the prefrontal cortex has been found to show network oscillations of a gamma frequency. This oscillatory activity can be mimicked in vitro by applying muscarinic agonists such as carbachol. Under these in vitro conditions, we recently found that in the infralimbic area of the prefrontal cortex two oscillations of different frequencies can occur simultaneously. Furthermore, pyramidal cells were observed to fire in a phase-locked manner to both oscillations. To study how and under what conditions the prefrontal cortex can generate multiple oscillations of different frequencies, we have developed a computational model of the prefrontal cortex, containing pyramidal cells and interneurons with realistic ion channel compositions. Based on mechanisms previously proposed for network oscillations in single layers, we study network models consisting of multiple layers which can sustain two or more oscillations. We use these computational models to explore the conditions under which the network is able to sustain multiple oscillations and individual cells can phase-lock to more oscillations at the same time. In particular, we study the influence of strength of connectivity between the different layers, synaptic strengths between pyramidal cells and interneurons, and duration and amplitude of the inhibitory postsynaptic current. In addition, we examine the possible functional roles of multiple oscillations for attention and working memory.

Functional role of correlated input on rhythmic neuronal oscillations
M. Zeitler¹, P. Fries^1,2, S. Gielen^1
1Dept Cognitive Neuroscience, Radboud Univ. Nijmegen (Nijmegen); ²F.C. Donders Centre for Cognitive Neuroimaging, Radboud Univ. Nijmegen (Nijmegen)

Visual scenes typically contain multiple stimuli competing for attention and for the control over behaviour. This raises the question how the brain selects a target and prepares responses to that specific target. Experimental findings in visual cortex have shown that if two competing stimuli are inside the receptive field of a neuron, the neuron responds to the attended stimulus as if this is the only stimulus present in the receptive field. A recently proposed hypothetical mechanism for this attention-driven target selection is neuronal synchronization. We will investigate this hypothesis by using synchronization of excitatory and inhibitory input within a simple feedforward neuronal network. Firing rates and coherences between local field potentials (a measure for the common input to a population of neurons) and spike-output will be investigated.

Adaptive scaling of excitability in recurrent neural networks
M. Remme, W. Wadman
Center for NeuroScience, Swammerdam Institute for Life Sciences, Universiteit van Amsterdam (Amsterdam)

Neurons need to match their excitability to the synaptic input in the face of ongoing plasticity in neuronal and synaptic properties. However, many neurons function in recurrent networks that require a delicate balance between excitation and inhibition for maintaining network stability. Here we studied the consequences of homeostatic scaling of excitability for the stability of such recurrent networks. Using a mean field analysis that describes adapting excitatory and inhibitory populations, we show that the stability of the adaptation critically depends on the relation between the adaptation rates of both neuron populations, combined with their respective gains. Simulations with a recurrent network model consisting of excitatory and inhibitory cells that independently control their excitability, confirm that for the adaptation to be stable, the inhibitory neurons need to adapt sufficiently slow compared to the excitatory neurons. Stable cellular adaptation can maintain all neurons in the network in a functional state, controlling activity for varying levels of input and to changes in network connectivity. Altered network connectivity can, however, never be completely compensated for by cellular scaling of excitability; when excitation in the network becomes too strong in relation to inhibition, the network will still become unstable.

Homeostatic synaptic plasticity and epileptogenesis in neocortex
A.R. Houweling^1,2, M. Bazhenov², I. Timofeev³, M. Steriade³, T.J. Sejnowski^2
1Dept Neurosciences, Erasmus MC (Rotterdam); ²The Salk Institute (La Jolla, CA, US); ³Laval University (Quebec, CA)

Chronically isolated neocortex develops chronic hyperexcitability and focal epileptogenesis in a period of days to weeks. The mechanisms operating in this model of post-traumatic epileptogenesis are not well understood. We hypothesized that the spontaneous burst discharges recorded in chronically isolated neocortex result from homeostatic plasticity (a mechanism generally assumed to stabilize neuronal activity) induced by low neuronal activity after deafferentation. To test this hypothesis we constructed computer models of neocortex incorporating a biologically based homeostatic plasticity rule that operates to maintain firing rates. After deafferentation, homeostatic upregulation of excitatory synapses on pyramidal cells, either with or without concurrent downregulation of inhibitory synapses or upregulation of intrinsic excitability, initiated slowly repeating burst discharges that closely resembled the epileptiform burst discharges recorded in chronically isolated neocortex. These burst discharges lasted a few hundred ms, propagated at 1-3 cm/s and consisted of large (10-15 mV) intracellular depolarizations topped by a small number of action potentials. Our results support a role for homeostatic synaptic plasticity as a novel mechanism of post-traumatic epileptogenesis.

Role of excitation and inhibition in the maintenance of working memory states in cortical network models
N. Brunel
Laboratory of Neurophysics and Physiology, UMR 8119, CNRS - Universite Paris 5 (Paris, FR)

Persistent activity of neurons in associative cortex is widely thought to underlie active working memory. Traditional models explain persistent activity through feedback loops between excitatory neurons. I will present an alternative scenario in which multistability arises because of interactions between inhibitory neurons.