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Section: New Results
From the microscopic to the mesoscopic scale
Participants: Laure Buhry, Francesco Giovannini
In collaboration with Beate Knauer and Motoharu Yoshida (Ruhr University) and LieJune Shiau (University of Houston)
Memory and Anaesthesia
The CAN-In model of hippocampal theta oscillations
During working memory tasks, the hippocampus exhibits synchronous theta-band activity, which is thought to be correlated with the short-term memory maintenance of salient stimuli. Recent studies indicate that the hippocampus contains the necessary circuitry allowing it to generate and sustain theta oscillations without the need of extrinsic drive. However, the cellular and network mechanisms supporting synchronous rhythmic activity are far from being fully understood. Based on electrophysiological recordings from hippocampal pyramidal CA1 cells, we have presented a possible mechanism for the maintenance of such rhythmic theta-band activity in the isolated hippocampus [3]. Our model network, based on the Hodgkin-Huxley formalism, comprising pyramidal neurons equipped with calcium-activated non-specific cationic (CAN) ion channels, is able to generate and maintain synchronized theta oscillations (), following a transient stimulation. The synchronous network activity is maintained by an intrinsic CAN current (), in the absence of constant external input. The analysis of the dynamics of model networks of pyramidal-CAN and interneurons (CAN-In) reveals that feedback inhibition improves the robustness of fast theta oscillations, by tightening the synchronisation of the pyramidal CAN neurons. The frequency and power of the theta oscillations are both modulated by the intensity of the , which allows for a wide range of oscillation rates within the theta band.
This biologically plausible mechanism for the maintenance of synchronous theta oscillations in the hippocampus aims at extending the traditional models of septum-driven hippocampal rhythmic activity.
Generation of gamma oscillations in a network of adaptive exponential integrate and fire neurons
Fast neuronal oscillations in the Gamma rhythm (20-80 Hz) are observed in the neocortex and hippocampus during behavioral arousal. Through a conductance-based, four-dimensional Hodgkin-Huxley type neuronal model, Wang and Buzsáki have numerically demonstrated that such rhythmic activity can emerge from a random network of GABAergic interneurons when their intrinsic neuronal characters and network structure act as the main drive of the rhythm. We investigate Gamma oscillations through a randomly connected network model comprising low complexity, two-dimensional adaptive exponential integrate-and-fire (AdEx) neurons that have subthreshold and spike-triggered adaptation mechanisms. Despite the simplicity of our network model, it shares two important results with the previous biophysical model: the minimal number of necessary synaptic inputs to generate coherent Gamma-band rhythms remains the same, and this number is weakly-dependant on the network size. Using AdEx model, we also investigate the necessary neuronal, synaptic and connectivity properties that lead to random network synchrony with Gamma rhythms. These findings suggest a computationally more tractable framework for studying sparse and random networks inducing cortical rhythms in the Gamma band (Laure Buhry submitted an article to Journal of Computational Neuroscience, currently under major revision).