Abstract
Synchronized oscillation is very commonly observed in many neuronal systems and might play an important role in the response properties of the system. We have studied how the spontaneous oscillatory activity affects the responsiveness of a neuronal network, using a neural network model of the visual cortex built from Hodgkin-Huxley type excitatory (E-) and inhibitory (I-) neurons. When the isotropic local E-I and I-E synaptic connections were sufficiently strong, the network commonly generated gamma frequency oscillatory firing patterns in response to random feed-forward (FF) input spikes. This spontaneous oscillatory network activity injects a periodic local current that could amplify a weak synaptic input and enhance the network's responsiveness. When E-E connections were added, we found that the strength of oscillation can be modulated by varying the FF input strength without any changes in single neuron properties or interneuron connectivity. The response modulation is proportional to the oscillation strength, which leads to self-regulation such that the cortical network selectively amplifies various FF inputs according to its strength, without requiring any adaptation mechanism. We show that this selective cortical amplification is controlled by E-E cell interactions. We also found that this response amplification is spatially localized, which suggests that the responsiveness modulation may also be spatially selective. This suggests a generalized mechanism by which neural oscillatory activity can enhance the selectivity of a neural network to FF inputs.
Highlights
Understanding the responsiveness of a cortical neural network is a fundamental requirement for any study of sensory information processing in the brain
We investigated the relationship between the oscillatory activity and the response modulation in neural networks using computational simulation modeling
We conclude that a neural network can dynamically modify its response properties by the selective amplification of sensory signals due to oscillation activity, which may explain some experimental observations and help us to better understand neural systems
Summary
Understanding the responsiveness of a cortical neural network is a fundamental requirement for any study of sensory information processing in the brain. Several experiments show that various factors can affect the neuronal response property and information flow in nervous systems: In the primary visual cortex, spiking responses of neurons can be enhanced by slow cortical oscillation [1]. The spike transfer function of thalamo-cortical neurons is modulated by noisy synaptic background activity [2]. Gain of neuronal responses is modulated by background synaptic input [3]. Even at the single cell level, cellular responsiveness is significantly influenced by the presence of voltage fluctuations [4]. It was shown recently that neuronal oscillations can increase response gain and decrease reaction time as a mechanism of attention selection [5]
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