Postsynaptic frequency filters shaped by the interplay of synaptic short-term plasticity and cellular time scales

Temporal filters, the ability of postsynaptic neurons to preferentially select certain presynaptic input patterns over others, have been shown to be associated with the notion of information filtering and coding of sensory inputs. Short-term plasticity (depression and facilitation; STP) has been proposed to be an important player in the generation of temporal filters. We carry out a systematic modeling, analysis and computational study to understand how characteristic postsynaptic (low-, high- and band-pass) temporal filters are generated in response to periodic presynaptic spike trains in the presence STP. We investigate how the dynamic properties of these filters depend on the interplay of a hierarchy of processes, including the arrival of the presynaptic spikes, the activation of STP, its effect on the excitatory synaptic connection efficacy, and the response of the postsynaptic cell. These mechanisms involve the interplay of a collection of time scales that operate at the single-event level (roughly, during each presynaptic interspike-interval) and control the long-term development of the temporal filters over multiple presynaptic events. These time scales are generated at the levels of the presynaptic cell (captured by the presynaptic interspike-intervals), short-term depression and facilitation, synaptic dynamics and the post-synaptic cellular currents. We develop mathematical tools to link the single-event time scales with the time scales governing the long-term dynamics of the resulting temporal filters for a relatively simple model where depression and facilitation interact at the level of the synaptic efficacy change. We extend our results and tools to account for more complex models. These include multiple STP time scales and non-periodic presynaptic inputs. The results and ideas we develop have implications for the understanding of the generation of temporal filters in complex networks for which the simple feedforward network we investigate here is a building block.

Statistical Analysis of Membrane Potential Fluctuations: Relation with Presynaptic Spike Train

The structure and organization of hazard evaluation and toxicity testing protocols are discussed. It was concluded that more expensive, sophisticated tests can be carried out more efficiently if the results from simpler toxicity tests are available when the complex tests are designed. Simultaneous testing at different levels of biological organization is supported. The author believes there is no compelling evidence that single-species tests can be used to predict reliable responses at more complex levels of organization. Although tests at higher levels of organization may be expensive, many are less expensive than or comparable in cost to long-term, continuous-flow exposure tests of single species.

The aim of this study is to investigate students’ meaning–making of multiple visual representations of epigenetics at different levels of biological organisation, and to discern what visual aspects of the multiple visual representations might influence students’ reasoning. Adopting an exploratory approach, we analysed how students made meaning of visually communicated epigenetics phenomena while pointing at and reasoning about the multiple visual representations as part of semi-structured focus groups. We investigated students’ meaning-making of the multiple visual representations by analysing their indications through physical pointing and accompanying verbal utterances. The analysis revealed meaning-making and the nature of linking between levels of organisation in four distinct patterns, namely intra horizontal linking, inter horizontal linking, one level vertical linking and two level vertical linking. In addition, five different visual characteristics of the multiple visual representations emerged as influencing students’ reasoning while linking between different organisation levels: multiple visual representations, salient visual features, analogous visual features, familiar visual elements, and textual adjuncts. The study shows that multiple visual representations at different levels of organisation can support students’ meaning-making of epigenetics, indicating that this way of communicating can be transferable to other biological domains. Potential implications for future research and teaching practice are provided.

Synaptic transmission of chaotic spike trains between primary afferent fiber and spinal dorsal horn neuron in the rat

The most evident aspect of biodiversity is the variety of complex forms and behaviors among organisms, both living and extinct. Comparative molecular and physiological studies show that the evolution of complex phenotypic traits involves multiple levels of biological organization (i.e. genes, chromosomes, organelles, cells, individual organisms, species, etc.). Regardless of the specific molecular mechanisms and details, the evolution of different complex biological organizations share a commonality: cooperation and conflict among the parts of the biological unit under study. The potential for conflict among parts is abundant. How then do complex systems persist, given the necessity of cooperative behavior for their maintenance, when the potential for conflict occurs across all levels of biological organization? In this Research Topic and eBook we present ideas and work on the question, how coexistence of biological components at different levels of organization persists in the face of antagonistic, conflicting or even exploitative behavior of the parts? The goal of this topic is in presenting examples of cooperation and conflict at different levels of biological organization to discuss the consequences that this “tension” have had in the diversification and emergence of novel phenotypic traits. Exemplary cases are studies investigating: the evolution of genomes, formation of colonial aggregates of cells, biofilms, the origin and maintenance of multicellular organisms, and the stable coexistence of multispecies consortia producing a cooperative product. Altogether, we hope that the contributions to this Research Topic build towards mechanistic knowledge of the biological phenomenon of coexistence in the face of conflict. We believe that knowledge on the mechanisms of the origin and evolutionary maintenance of cooperation has implications beyond evolutionary biology such as novel approaches in controlling microbial infections in medicine and the modes by studies in synthetic biology are conducted when designing economically important microbial consortia.The most evident aspect of biodiversity is the variety of complex forms and behaviors among organisms, both living and extinct. Comparative molecular and physiological studies show that the evolution of complex phenotypic traits involves multiple levels of biological organization (i.e. genes, chromosomes, organelles, cells, individual organisms, species, etc.). Regardless of the specific molecular mechanisms and details, the evolution of different complex biological organizations share a commonality: cooperation and conflict among the parts of the biological unit under study. The potential for conflict among parts is abundant. How then do complex systems persist, given the necessity of cooperative behavior for their maintenance, when the potential for conflict occurs across all levels of biological organization? In this Research Topic and eBook we present ideas and work on the question, how coexistence of biological components at different levels of organization persists in the face of antagonistic, conflicting or even exploitative behavior of the parts? The goal of this topic is in presenting examples of cooperation and conflict at different levels of biological organization to discuss the consequences that this “tension” have had in the diversification and emergence of novel phenotypic traits. Exemplary cases are studies investigating: the evolution of genomes, formation of colonial aggregates of cells, biofilms, the origin and maintenance of multicellular organisms, and the stable coexistence of multispecies consortia producing a cooperative product. Altogether, we hope that the contributions to this Research Topic build towards mechanistic knowledge of the biological phenomenon of coexistence in the face of conflict. We believe that knowledge on the mechanisms of the origin and evolutionary maintenance of cooperation has implications beyond evolutionary biology such as novel approaches in controlling microbial infections in medicine and the modes by studies in synthetic biology are conducted when designing economically important microbial consortia.

The major features of insect societies that fascinate biologists are the self-sacrificing altruism expressed by colony members, the complex division of labor, and the tremendous plasticity demonstrated in the face of changing environments. The social behavior of insects is a result of complex interactions at different levels of biological organization. Genes give rise to proteins and peptides that build the nervous and muscular systems, regulate their own synthesis, interact with each other, and affect the behavior of individuals. Social behavior emerges from the complex interactions of individuals that are themselves far removed from the direct effects of the genes. In order to understand how social organization evolves, we must understand the mechanisms that link the different levels of organization. In this review, we discuss how behavior is influenced by genes and the neural system and how social behavior emerges from the behavioral activities of individuals. We show how different levels of organization share common features and are linked through common mechanisms. We focus on the behavior of the honey bee, the best studied of all social insects.

Integrative biology: linking levels of organization

Resonance is defined as maximal response of a system to periodic inputs in a limited frequency band. Resonance may serve to optimize inter-neuronal communication, and has been observed at multiple levels of neuronal organization. However, it is unknown how neuronal resonance observed at the network level is generated and how network resonance depends on the properties of the network building blocks. Here, we first develop a metric for quantifying spike timing resonance in the presence of background noise, extending the notion of spiking resonance for in vivo experiments. Using conductance-based models, we find that network resonance can be inherited from resonances at other levels of organization, or be intrinsically generated by combining mechanisms across distinct levels. Resonance of membrane potential fluctuations, postsynaptic potentials, and single neuron spiking can each be generated independently of resonance at any other level and be propagated to the network level. At all levels of organization, interactions between processes that give rise to low- and high-pass filters generate the observed resonance. Intrinsic network resonance can be generated by the combination of filters belonging to different levels of organization. Inhibition-induced network resonance can emerge by inheritance from resonance of membrane potential fluctuations, and be sharpened by presynaptic high-pass filtering. Our results demonstrate a multiplicity of qualitatively different mechanisms that can generate resonance in neuronal systems, and provide analysis tools and a conceptual framework for the mechanistic investigation of network resonance in terms of circuit components, across levels of neuronal organization.

UWB technology started to become an attraction in the field of research since the Federal Communications Commission (FCC) allowing this communication is used for commercial communications at a frequency (3.1 GHz - 10.6 GHz). UWB has a very wide frequency range so that in practice there is often interference due to signal interference. Therefore in UWB system filter design is required to maintain UWB device. In telecommunications, filter is a transmission device that has the function to pass the desired frequency. In this paper designed bandpass filter which is applied for UWB technology. The designed bandpass filter is a combination of a lowpass filter (LPF) and a highpass filter (HPF). The lowpass filter has the characteristic of passing a frequency lower than its cut-off frequency. The highpass filter has the characteristic passing a frequency higher than its cut-off frequency. Considering the characteristics of both filters, the bandpass filter (BPF) is a combination of lowpass and highpass filters. In this research designed lowpass filter in microstrip technology with step-impedance method, that is by combining high impedance microstrip and low impedance microstrip with a certain length. As for designing HPF using the distribution method of short circuit stubs by adding via ground on each stub. The design of this filter uses Roger substrate RT 5880 with dielectric constant er = 2,2 with thickness (h) = 0.508 mm. In this research it can be concluded that bandpass filter can be designed with lowpass and highpass filter incorporation method, although at the merging of highpass and lowpass structures is disturbed by each other, but overall design shows matching bandpass.
 Keywords—Microstrip, Lowpass Filter, Highpass Filter, Bandpass Filter.

Comparative Plant Ecology as a Tool for Integrating Across Scales

Dual intracellular recordings and computational models of slow inhibitory postsynaptic potentials in rat neocortical and hippocampal slices

Three kinds of the periodical structures are designed as low-pass, high-pass, and band-pass filters for elastic wave. The theoretical simulations have proved that the periodical surface slots can act as a low-pass filter for elastic wave. With increasing depth of the surface periodical structure in the sample, the cutoff frequency of the low-pass filter is decreased. Unlike the surface periodical structure, the periodical subsurface structure can work as a high-pass filter for elastic wave. The cutoff frequency of the high-pass filter is suppressed by the increase of the subsurface structure thickness. When the two periodical structures are combined together, the band-pass filter is obtained, in which the pass band is determined by the cutoff frequencies of the low-pass and high-pass filters.

This paper presents a study based on changes in the cut-off frequency and sharpness of different types of filter by loading with glass and graphene–glass superstrate. Design and fabrication of four basic types of microwave filter – low-pass, high-pass, band pass, and band stop filter are presented and S-parameters are measured with superstrate. The impact of superstrate on the filter characteristics such as cut-off frequency, bandwidth, and sharpness are analyzed experimentally by comparing these characteristics for without superstrate and with superstrate. The superstrate loading resulted in the decrease of cut-off frequency for low-pass and high-pass filter, whereas the bandwidth is decreased for band pass filter and band stop filter with larger shift in high cut-off frequency. Such effects have been confirmed by the simulation of low-pass filter and band pass filter on placing a glass. It is estimated from the filter responses that graphene–glass has conducting as well as dielectric nature compared to glass in the frequency range of study. It has been shown that the cut-off frequency and bandwidth can be tuned by dielectric kind of superstrate without varying the physical dimension of filter.

Neuronal variability plays a central role in neural coding and impacts the dynamics of neuronal networks. Unreliability of synaptic transmission is a major source of neural variability: synaptic neurotransmitter vesicles are released probabilistically in response to presynaptic action potentials and are recovered stochastically in time. The dynamics of this process of vesicle release and recovery interacts with variability in the arrival times of presynaptic spikes to shape the variability of the postsynaptic response. We use continuous time Markov chain methods to analyze a model of short term synaptic depression with stochastic vesicle dynamics coupled with three different models of presynaptic spiking: one model in which the timing of presynaptic action potentials are modeled as a Poisson process, one in which action potentials occur more regularly than a Poisson process (sub-Poisson) and one in which action potentials occur more irregularly (super-Poisson). We use this analysis to investigate how variability in a presynaptic spike train is transformed by short term depression and stochastic vesicle dynamics to determine the variability of the postsynaptic response. We find that sub-Poisson presynaptic spiking increases the average rate at which vesicles are released, that the number of vesicles released over a time window is more variable for smaller time windows than larger time windows and that fast presynaptic spiking gives rise to Poisson-like variability of the postsynaptic response even when presynaptic spike times are non-Poisson. Our results complement and extend previously reported theoretical results and provide possible explanations for some trends observed in recorded data.