Membrane resonance enables stable and robust gamma oscillations

Neuronal mechanisms underlying beta/gamma oscillations (20-80 Hz) are not completely understood. Here, we show that in vivo beta/gamma oscillations in the cat visual cortex sometimes exhibit remarkably stable frequency even when inputs fluctuate dramatically. Enhanced frequency stability is associated with stronger oscillations measured in individual units and larger power in the local field potential. Simulations of neuronal circuitry demonstrate that membrane properties of inhibitory interneurons strongly determine the characteristics of emergent oscillations. Exploration of networks containing either integrator or resonator inhibitory interneurons revealed that: (i) Resonance, as opposed to integration, promotes robust oscillations with large power and stable frequency via a mechanism called RING (Resonance INduced Gamma); resonance favors synchronization by reducing phase delays between interneurons and imposes bounds on oscillation cycle duration; (ii) Stability of frequency and robustness of the oscillation also depend on the relative timing of excitatory and inhibitory volleys within the oscillation cycle; (iii) RING can reproduce characteristics of both Pyramidal INterneuron Gamma (PING) and INterneuron Gamma (ING), transcending such classifications; (iv) In RING, robust gamma oscillations are promoted by slow but are impaired by fast inputs. Results suggest that interneuronal membrane resonance can be an important ingredient for generation of robust gamma oscillations having stable frequency

Performance of cylindrical converters with preferred-crystal-orientation emitters of chemically vapor deposited tungsten

Design and evaluation of cylindrical out-of-pile thermionic converter test vehicle to determine performance of tungsten emitters with preferred crystal orientatio

Multidimensional patterns of neuronal activity: how do we see them?

Poster presentation: Introduction The brain is a highly interconnected network of constantly interacting units. Understanding the collective behavior of these units requires a multi-dimensional approach. The results of such analyses are hard to visualize and interpret. Hence tools capable of dealing with such tasks become imperative. ...

Effect of pH on fermentative hydrogen production from L-arabinose using mixed cultures

Hydrogen is now considered one of the alternatives to fossil fuels. It is preferred to biogas or methane because hydrogen is not chemically bound to carbon and therefore, combustion does not contribute to green house gases or acid rain [1]. One alternative to sustainable H2 energy production from renewable energy sources is through microbiological fermentation. There have been many studies examining the effect of pH in fermentative hydrogen production from glucose and sucrose using mixed microflora [2,3,4,5,6]. However, fermentative hydrogen production from arabinose, one of the most common pentoses and a component of various biopolymers such as hemicellulose and plant polysaccharides using mixed microflora has not been previously examined. Understanding the influence of pH on biohydrogen production is necessary to develop arabinose-based hydrogen fermentation applications, such as the use of agricultural wastes. Biohydrogen production from arabinose was examined using three different anaerobic sludges with different pHs ranging from 4.5 to 8.0. Arabinose (30 g/L) was used as the substrate for all experiments. Individual cumulative hydrogen production data were used to estimate the three parameters of the modified Gompertz equation. This model has been used for describing the progress of cumulative gas production obtained from the batch experiments. Higher hydrogen production potentials (more than 35 mL) were observed with pH values greater than 6.0 for Unicer (granular sludge) and Choupal (disperse anaerobic digester sludge supplemented with fat) and greater than 6.5 for Freixo (disperse anaerobic digester sludge). Choupal biomass had the largest hydrogen production rate (4.8±1.4 mL/h) at pH 7.5, compared with the other two sludges. Unicer biomass had the shortest lag time (10.6±2.4 h) at pH 8.0. The highest hydrogen yield was observed with Choupal biomass (2.5 mol H2/mol arabinose consumed), with pH 6.0. The granular biomass showed different behaviour than the suspended biomasses. The differences may be explained by smaller lag phases, the percentage of acetate produced, the higher percentage of ethanol produced, and the amount of arabinose consumed. The percentage of n-butyrate was highly correlated with the percentage of acetate (R2 = 0.980) in Freixo biomass. A high correlation (R2 = 0.973) was observed between the percentage of n-butyrate and the percentage of ethanol in Unicer biomass, suggesting that the fermentation is following the butyrate/ethanol pathways which correspond to the lower yields of hydrogen obtained

Inoculum type response to different pHs on bio-hydrogen production from L-arabinose a component of hemicellulosic biopolymers

Biohydrogen production from arabinose was examined using four different anaerobic sludges with different pHs ranging from 4.5 to 8.0. Arabinose (30 g l−1) was used as the substrate for all experiments. Individual cumulative hydrogen production data was used to estimate the three parameters of the modified Gompertz equation. Higher hydrogen production potentials were observed for higher pH values for all the sludges. G2 (acclimated granular sludge) showed the highest hydrogen production potential and percentage of arabinose consumption compared to the other sludges tested. Granular sludges (G1 and G2) showed different behaviour than the suspended sludges (S1 and S2). The differences were observed to be smaller lag phases, the percentage of acetate produced, the higher percentage of ethanol produced, and the amount of arabinose consumed. A high correlation (R2 = 0.973) was observed between the percentage of n-butyrate and the percentage of ethanol in G1 sludge, suggesting that ethanol/butyrate fermentation was the dominant fermentative pathway followed by this sludge. In S1, however, the percentage of n-butyrate was highly correlated with the percentage of acetate (R2 = 0.980). This study indicates that granular sludge can be used for larger pH ranges without reducing its capacity to consume arabinose and achieve higher hydrogen production potentials.Fundação para a Ciência e a Tecnologia (FCT

Gene regulation by CcpA and catabolite repression explored by RNA-Seq in Streptococcus mutans

A bacterial transcriptome of the primary etiological agent of human dental caries, Streptococcus mutans, is described here using deep RNA sequencing. Differential expression profiles of the transcriptome in the context of carbohydrate source, and of the presence or absence of the catabolite control protein CcpA, revealed good agreement with previously-published DNA microarrays. In addition, RNA-seq considerably expanded the repertoire of DNA sequences that showed statistically-significant changes in expression as a function of the presence of CcpA and growth carbohydrate. Novel mRNAs and small RNAs were identified, some of which were differentially expressed in conditions tested in this study, suggesting that the function of the S. mutans CcpA protein and the influence of carbohydrate sources has a more substantial impact on gene regulation than previously appreciated. Likewise, the data reveal that the mechanisms underlying prioritization of carbohydrate utilization are more diverse than what is currently understood. Collectively, this study demonstrates the validity of RNA-seq as a potentially more-powerful alternative to DNA microarrays in studying gene regulation in S. mutans because of the capacity of this approach to yield a more precise landscape of transcriptomic changes in response to specific mutations and growth conditions

Land use changes in the Douro Valley and carbon emissions

Deforestation for economic development and urbanisation or urban sprawl as a result of human population growth is a common feature of land-use change and is an important source of increased atmospheric CO2. At the global level, carbon emissions from burning fossil fuels are two to three times higher than carbon sequestration by land systems, mainly forests and woody vegetation. The work presented herein focuses on the identification of carbon balance shifts due to land use changes in a group of municipalities located in the Douro River Valley in northern Portugal, where the dominance of vineyards and forestry uses over urban occupation is the norm. However, when urban sprawl occurs through the replacement of forested areas by urban uses, the ability to sequester carbon dioxide is reduced while its production rates increase. A thorough study (Lourenço et al., 2008) of land uses evolution between 1990 and 2000 shows that urban uses have been growing near Vila Real as well as vineyard plantations. Forest fires and a complex topography are major causes for the growth of abandonment, which make these areas more prone to erosion and desertification.Portuguese Foundation for Science and Technology in the scope of the research project PTDC/ECM/73069/200

Synchronization hubs may arise from strong rhythmic inhibition during gamma oscillations in primary visual cortex

Poster presentation from Twentieth Annual Computational Neuroscience Meeting: CNS*2011 Stockholm, Sweden. 23-28 July 2011. Parallel multiunit recordings from V1 in anesthetized cat were collected during the presentation of random sequences of drifting sinusoidal gratings at 12 fixed orientations while gamma oscillations were present. In agreement with the seminal work [1], most units were orientation selective to varying degrees and synchronization was evident in spike train crosscorrelograms computed between units with similar preferred orientations, particularly during the presentation of optimal stimuli. Interestingly, a subset of units, which we refer to as synchronization hubs, were additionally found to synchronize with units having differing preferred orientations which was consistent with a previous study [2]. Moreover, oscillatory patterning in spike train autocorrelograms was also found to be strongest in units denoted as synchronization hubs, and synchronization hubs also tended to have narrower tuning curves relative to other units. We used simplified computational models of small networks of V1 neurons to demonstrate that neurons subject to a sufficiently strong level of inhibitory input can function as synchronization hubs. Neurons were endowed either with integrate-and-fire or conductance-based dynamics and each neuron received a combination of excitatory (AMPA) synaptic inputs that were Poisson-distributed and inhibitory (GABA) inputs that were coherent at a gamma-frequency range. If the strength of rhythmic inhibition was increased for a subset of neurons in the network, and excitation was increased simultaneously to maintain a fixed firing rate, then these neurons produced stronger oscillatory patterning in their discharge probabilities. The oscillations in turn synchronized these neurons with other neurons in the network. Importantly, the strength of synchronization increased with neurons of differing orientation preferences even though no direct synaptic coupling existed between the hubs and the other neurons. Enhanced levels of inhibition account for the emergence of synchronization hubs in the following way: Inhibitory inputs exhibiting a gamma rhythm determine a time window within which a cell is likely to discharge. Increased levels of inhibition narrow down this window further simultaneously leading to (i) even stronger oscillatory patterning of the neuron's activity and (ii) enhanced synchronization with other neurons. This enables synchronization even between cells with differing orientation preferences. Additionally, the same increased levels of inhibition may be responsible for the narrow tuning curves of hub neurons. In conclusion, synchronization hubs may be the cells that interact most strongly with the network of inhibitory interneurons during gamma oscillations in primary visual cortex

Hold Your Methods! How Multineuronal Firing Ensembles Can Be Studied Using Classical Spike-Train Analysis Techniques

Responses of neuronal populations play an important role in the encoding of stimulus related information. However, the inherent multidimensionality required to describe population activity has imposed significant challenges and has limited the applicability of classical spike train analysis techniques. Here, we show that these limitations can be overcome. We first quantify the collective activity of neurons as multidimensional vectors (patterns). Then we characterize the behavior of these patterns by applying classical spike train analysis techniques: peri-stimulus time histograms, tuning curves and auto- and cross-correlation histograms. We find that patterns can exhibit a broad spectrum of properties, some resembling and others substantially differing from those of their component neurons. We show that in some cases pattern behavior cannot be intuitively inferred from the activity of component neurons. Importantly, silent neurons play a critical role in shaping pattern expression. By correlating pattern timing with local-field potentials, we show that the method can reveal fine temporal coordination of cortical circuits at the mesoscale. Because of its simplicity and reliance on well understood classical analysis methods the proposed approach is valuable for the study of neuronal population dynamics