Temporal oscillations in neuronal nets

Summary A model for the interactions of cortical neurons is derived and analyzed. It is shown that small amplitude spatially inhomogeneous standing oscillations can bifurcate from the rest state. In a periodic domain, traveling wave trains exist. Stability of these patterns is discussed in terms of biological parameters. Homoclinic and heteroclinic orbits are demonstrated for the space-clamped system.The research reported in this paper was supported in part by NIH GM2037     

Spiking regularity in a noisy small-world neuronal network

The regularity of spiking oscillations is studied in the networks with different topological structures. The network is composed of coupled Fitz-Hugh-Nagumo neurons driven by colored noise. The investigation illustrates that the spike train in both the regular and the Watts-Strogatz small-world neuronal networks can show the best regularity at a moderate noise intensity, indicating the existence of coherence resonance. Moreover, the temporal coherence of the spike train in the small-world network is superior to that in a regular network due to the increase of the randomness of the network topology. Besides the noise intensity, the spiking regularity can be optimized by tuning the randomness of the network topological structure or by tuning the correlation time of the colored noise. In particular, under the cooperation of the small-world topology and the correlation time, the spike train with good regularity could sustain a large magnitude of the local noise.     

Robustness of archaeal populations in anaerobic co-digestion of dairy and poultry wastes

The objective of this study is to investigate the responses of methanogen populations to poultry waste addition by comparing the archaeal microbial populations in continuous anaerobic digesters with or without the addition of poultry waste as a co-substrate. Poultry waste was characterized as an organic/nitrogen-rich substrate for anaerobic digestion. Supplementing dilute dairy waste with poultry waste for anaerobic co-digestion to increase organic loading rate by 50% resulted in improved biogas production. Elevated ammonia derived from poultry waste did not lead to process inhibition at the organic loadings tested, demonstrating the feasibility of the anaerobic co-digestion of dairy and poultry wastes for improved treatment efficiency. The stability of the anaerobic co-digestion process was linked to the robust archaeal microbial community, which remained mostly unchanged in community structure following increases in organic loading and ammonia levels. Surprisingly, Crenarchaeota archaeal populations, instead of the Euryarchaeota methanogens, dominated the archaeal communities in the anaerobic digesters. The ecological functions of these abundant non-methanogen archaeal populations in anaerobic digestion remain to be identified.     

Innate synchronous oscillations in freely-organized small neuronal circuits

Background

Information processing in neuronal networks relies on the network''s ability to generate temporal patterns of action potentials. Although the nature of neuronal network activity has been intensively investigated in the past several decades at the individual neuron level, the underlying principles of the collective network activity, such as the synchronization and coordination between neurons, are largely unknown. Here we focus on isolated neuronal clusters in culture and address the following simple, yet fundamental questions: What is the minimal number of cells needed to exhibit collective dynamics? What are the internal temporal characteristics of such dynamics and how do the temporal features of network activity alternate upon crossover from minimal networks to large networks?

Methodology/Principal Findings

We used network engineering techniques to induce self-organization of cultured networks into neuronal clusters of different sizes. We found that small clusters made of as few as 40 cells already exhibit spontaneous collective events characterized by innate synchronous network oscillations in the range of 25 to 100 Hz. The oscillation frequency of each network appeared to be independent of cluster size. The duration and rate of the network events scale with cluster size but converge to that of large uniform networks. Finally, the investigation of two coupled clusters revealed clear activity propagation with master/slave asymmetry.

Conclusions/Significance

The nature of the activity patterns observed in small networks, namely the consistent emergence of similar activity across networks of different size and morphology, suggests that neuronal clusters self-regulate their activity to sustain network bursts with internal oscillatory features. We therefore suggest that clusters of as few as tens of cells can serve as a minimal but sufficient functional network, capable of sustaining oscillatory activity. Interestingly, the frequencies of these oscillations are similar those observed in vivo.     

BrainModes: the role of neuronal oscillations in health and disease

The core idea of complexity science--namely how macroscopic phenomena emerge from the interactions between microscopic quantities--is particularly relevant to the study of the human brain. It is in this context that the term "BrainModes" was adopted to explore how cooperative phenomena (or 'modes' of activity) occurring at one spatial or temporal scale give rise to coherent structures at other scales. This Special Issue reports the 2009 BrainModes Workshop, held in Bristol (December 2009) which focussed on the fusion of theoretical, computational, experimental and clinical methods for enhancing our understanding of the role played by neuronal oscillations in healthy and diseased brain states.     

Robustness of linkage maps in natural populations: a simulation study

In a number of long-term individual-based studies of vertebrate populations, the genealogical relationships between individuals have been established with molecular markers. As a result, it is possible to construct genetic linkage maps of these study populations by examining the co-segregation of markers through the pedigree. There are now four free-living vertebrate study populations for whom linkage maps have been built. In this study, simulation was used to investigate whether these linkage maps are likely to be accurate. In all four populations, the probability of assigning markers to the correct chromosome is high and framework maps are generally inferred correctly. However, genotyping error can result in incorrect maps being built with very strong statistical support over the correct order. Future applications of linkage maps of natural populations are discussed.     

Qualitative analysis of oscillations in isolated populations of flies

Populations oscillations in isolated populations of flies are considered. Qualitative methods of analysis are applied to the functional differential equation representing the system and conditions for the occurrence of oscillations are derived. These conditions are readily visualized in terms of parameters which are easily measured and have a straightforward biological interpretation.     

Computer simulation of diffusely-connected neuronal populations

This paper describes computer simulations of diffusely-connected neuronal populations. Main findings are that diffuse monosynaptic linkages between populations are selectively sensitive to synchronized clusters of action potentials in the pre-synaptic population; that diffusely-connected excitatory recurrent collaterals tend to produce rhythmic series of synchronized clusters; and that diffusely-connected inhibition (both recurrent and afferent) tend to reduce the number of cells participating in a given synchronized cluster and thereby the overall transfer rate. However, recurrent inhibition tends to increase the rate at which synchronized clusters are produced by recurrent excitation. These results suggest the speculation that diffusely connected neuronal populations are particularly prone to deal with synchronized clusters of action potentials.This work has been supported by Grant GB 33687 of the National Science Foundation, Grant 1-R01-NS-10781-01 COM of the National Institutes of Health, and by a fellowship from Zonta, International     

Fluctuations in circumpolar seabird populations linked to climate oscillations

We found that synchronous fluctuations of two congeneric seabird species across the entire Arctic and sub-Arctic regions were associated with changes in sea surface temperatures (SST) that were linked to two climate shifts, in 1977 and again in 1989. As the SST changes linked to climate shifts were congruent at the scale of ocean basins, fluctuations of these species occurred similarly at continental or basin scale. Changes in colony sizes were examined for a decade following climate shifts. The magnitude of the SST shift was more important than its direction in determining the subsequent rate of population change. Seabirds declined when the SST shift was large and increased when the shift was small, although the effect differed between the Arctic-breeding species and the more temperate-breeding congener. The Arctic species, Thick-billed Murre ( Uria lomvia ) increased most rapidly when SST warmed slightly, while the temperate species, Common Murre ( Uria aalge ) showed most rapid increase with moderate cooling. Both showed negative trends with large temperature shifts in either direction. This pattern was replicated during both climate oscillations. Negative population trends in seabirds presumably indicate the alteration of underlying food webs. Hence, similar widespread fluctuations in response to climate shifts are likely for other ecosystem components (marine mammals, fish, and invertebrates).     

Inhibitory transmission, activity-dependent ionic changes and neuronal network oscillations

Oscillatory network activity arises from interactions between synaptic and intrinsic membrane properties of neurons. In this review, we summarize general mechanisms of synchronous neuronal oscillations. In addition, we focus on recent experimental and computational studies which suggest that activity-dependent changes of ionic environment can affect both the synaptic and intrinsic neuronal properties and influence the network behavior. GABA(A) receptor (GABA(A)R)-mediated signaling, that is based on Cl(-) and HCO(3)(-) permeability, is thought to be important for the oscillogenesis and synchronization in cortical networks. A remarkable feature of GABAergic synapses is that prolonged GABA(A)R activation may lead to switching from a hyperpolarizing to a depolarizing response. This is partly due to a positive shift of the GABA(A) R reversal potential (E(GABA)) that is generated by GABA-induced Cl(-) accumulation in neurons. Recent studies suggest that activity-dependent E(GABA) changes may have important implications for the mechanisms of gamma oscillations and seizure-like discharges. Thus, a better understanding of the impact of intracellular Cl(-) dynamics on network behavior may provide insights into the mechanisms of physiological and pathological brain rhythms. Combination of experiments and simulations is a promising approach for elucidating which properties of the time-varying ionic environment can shape the dynamics of a given circuit.     

Gamma oscillations of spiking neural populations enhance signal discrimination

Selective attention is an important filter for complex environments where distractions compete with signals. Attention increases both the gamma-band power of cortical local field potentials and the spike-field coherence within the receptive field of an attended object. However, the mechanisms by which gamma-band activity enhances, if at all, the encoding of input signals are not well understood. We propose that gamma oscillations induce binomial-like spike-count statistics across noisy neural populations. Using simplified models of spiking neurons, we show how the discrimination of static signals based on the population spike-count response is improved with gamma induced binomial statistics. These results give an important mechanistic link between the neural correlates of attention and the discrimination tasks where attention is known to enhance performance. Further, they show how a rhythmicity of spike responses can enhance coding schemes that are not temporally sensitive.     

Computer-aided mapping of specific neuronal populations in the human brain

Antibody-staining methods and computer-aided microscopic systems have been used to generate high-resolution panoramic maps of specific neuronal populations in the human brain (4,6,11). This report focuses on the problems inherent in attempting high-resolution mapping of large brain sections, and describes how they are solved by computer-aided mapping. Further applications of computers to the study of brain structure are considered.     

Spatially structured oscillations in a two-dimensional excitatory neuronal network with synaptic depression

We study the spatiotemporal dynamics of a two-dimensional excitatory neuronal network with synaptic depression. Coupling between populations of neurons is taken to be nonlocal, while depression is taken to be local and presynaptic. We show that the network supports a wide range of spatially structured oscillations, which are suggestive of phenomena seen in cortical slice experiments and in vivo. The particular form of the oscillations depends on initial conditions and the level of background noise. Given an initial, spatially localized stimulus, activity evolves to a spatially localized oscillating core that periodically emits target waves. Low levels of noise can spontaneously generate several pockets of oscillatory activity that interact via their target patterns. Periodic activity in space can also organize into spiral waves, provided that there is some source of rotational symmetry breaking due to external stimuli or noise. In the high gain limit, no oscillatory behavior exists, but a transient stimulus can lead to a single, outward propagating target wave.     

Low-frequency neuronal oscillations as operant processing of integrative mechanisms of conditioning and plasticity

It was found that neuronal activity of the rabbit somatosensory cortex could be operantly conditioned according to the given algorithm of biofeedback control of nociceptive stimulation leading to rising or lowering of firing rate of multiunit activity, or to changes of range of units interspike intervals, or neuronal firing patterns for conditional stimulus, which become operants. Neuronal interactions of its population with feedback and systems of cardiovascular and pain regulation lead to appearance of wave patterns, combining elements to integrative activity by conditioning. Low-frequency oscillations of neuronal assemblies within range of 0.02-0.8 Hz act as operant processing in mechanisms of system plasticity and conditioning.