On the Dynamics of the Spontaneous Activity in Neuronal Networks

Abstract

Most neuronal networks, even in the absence of external stimuli, produce spontaneous bursts of spikes separated by periods of reduced activity. The origin and functional role of these neuronal events are still unclear. The present work shows that the spontaneous activity of two very different networks, intact leech ganglia and dissociated cultures of rat hippocampal neurons, share several features. Indeed, in both networks: i) the inter-spike intervals distribution of the spontaneous firing of single neurons is either regular or periodic or bursting, with the fraction of bursting neurons depending on the network activity; ii) bursts of spontaneous spikes have the same broad distributions of size and duration; iii) the degree of correlated activity increases with the bin width, and the power spectrum of the network firing rate has a 1/f behavior at low frequencies, indicating the existence of long-range temporal correlations; iv) the activity of excitatory synaptic pathways mediated by NMDA receptors is necessary for the onset of the long-range correlations and for the presence of large bursts; v) blockage of inhibitory synaptic pathways mediated by GABAA receptors causes instead an increase in the correlation among neurons and leads to a burst distribution composed only of very small and very large bursts. These results suggest that the spontaneous electrical activity in neuronal networks with different architectures and functions can have very similar properties and common dynamics.

Homeostasis of neuronal avalanches during postnatal cortex development in vitro

“…This organization of LFP activity has been demonstrated in the form of 'neuronal avalanches' in mature slice cultures and acute cortex slices taken from adult rats (Beggs and Plenz, 2003;Stewart and Plenz, 2006). A similar organization was demonstrated recently in spontaneous spike bursts of dissociated hippocampus cultures (Mazzoni, Broccard et al, 2007). The presence of power law organization across spatial scales is suggestive of systems in a critical state which optimizes numerous aspects of information processing (for review see: Plenz and Thiagarajan, 2007;Chialvo, 2007).…”

“…Thus, the spatiotemporal organization of synchronized activity as reflected in nLFP clusters, might or might not be identifiable in the spatiotemporal organization of spike clusters. While there has been a recent finding on power laws in spike clusters for hippocampal dissociated cultures (Mazzoni, Broccard et al, 2007), a similar analysis in dissociated cortical cultures resulted in a bimodal distribution of spike cluster sizes (Eytan and Marom, 2006). In the latter study, the branching parameter was estimated using successive spikes and was slightly above 1, compared to the current study, which yielded for most cultures with a clear power law a branching parameter slightly below 1.…”

Neuromorphic behavior in percolating nanoparticle films

“…We speculate that the power law behavior discussed in Sec. III B 1 can be related to experimentally observed power laws for neuronal avalanche size and lifetime [59,60].…”

“…[23] as being consistent with criticality. The expected power law distribution in the size of cortical avalanches and lifetime statistcs [59,60] are not straightforward to simulate in the present simulations, which do not include this dynamical behavior; in addition, further work is required to identify a measure of avalanche size that corresponds to that available from biological systems [59,60]. We speculate that the power law behavior discussed in Sec.…”

Conditional Bursting Enhances Resonant Firing in Neocortical Layer 2–3 Pyramidal Neurons

“…Here, we investigated how frequencydependent gain depends on the stimulus power spectrum, measuring G( f ) in response to 1 ms exponential-filtered noise and 1/f noise, in addition to the 5 ms exponential-filtered noise described above. The 1 ms noise may be thought of as simulating very fast synaptic currents, whereas 1/f noise contains fluctuations spanning multiple timescales, a property that is characteristic of some sensory stimuli (Voss and Clarke, 1975;van Hateren, 1997) and forms of neural activity (Teich et al, 1997;Mazzoni et al, 2007). 1/f noise is also useful as an experimental tool because its substantial power at low frequency allows one to measure gain over a wider frequency range.…”