Exploring spike transfer through the thalamus using hybrid artificial-biological neuronal networks

We use dynamic clamp to construct "hybrid" thalamic circuits by connecting a biological neuron in situ to silicon- or software-generated "neurons" through artificial synapses. The purpose is to explore cellular sensory gating mechanisms that regulate the transfer efficiency of signals during different sleep-wake states. Hybrid technology is applied in vitro to different paradigms such as: (1) simulating interactions between biological thalamocortical neurons, artificial reticular thalamic inhibitory interneurons and a simulated sensory input, (2) grafting an artificial sensory input to a wholly biological thalamic network that generates spontaneous sleep-like oscillations, (3) injecting in thalamocortical neurons a background synaptic bombardment mimicking the activity of corticothalamic inputs. We show that the graded control of the strength of intrathalamic inhibition, combined with the membrane polarization and the fluctuating synaptic noise in thalamocortical neurons, is able to govern functional shifts between different input/output transmission states of the thalamic gate.     

Complex recombination patterns arising during geminivirus coinfections preserve and demarcate biologically important intra-genome interaction networks

Genetic recombination is an important process during the evolution of many virus species and occurs particularly frequently amongst begomoviruses in the single stranded DNA virus family, Geminiviridae. As in many other recombining viruses it is apparent that non-random recombination breakpoint distributions observable within begomovirus genomes sampled from nature are the product of variations both in basal recombination rates across genomes and in the over-all viability of different recombinant genomes. Whereas factors influencing basal recombination rates might include local degrees of sequence similarity between recombining genomes, nucleic acid secondary structures and genomic sensitivity to nuclease attack or breakage, the viability of recombinant genomes could be influenced by the degree to which their co-evolved protein-protein and protein-nucleotide and nucleotide-nucleotide interactions are disreputable by recombination. Here we investigate patterns of recombination that occur over 120 day long experimental infections of tomato plants with the begomoviruses Tomato yellow leaf curl virus and Tomato leaf curl Comoros virus. We show that patterns of sequence exchange between these viruses can be extraordinarily complex and present clear evidence that factors such as local degrees of sequence similarity but not genomic secondary structure strongly influence where recombination breakpoints occur. It is also apparent from our experiment that over-all patterns of recombination are strongly influenced by selection against individual recombinants displaying disrupted intra-genomic interactions such as those required for proper protein and nucleic acid folding. Crucially, we find that selection favoring the preservation of co-evolved longer-range protein-protein and protein DNA interactions is so strong that its imprint can even be used to identify the exact sequence tracts involved in these interactions.     

Viral surface geometry shapes influenza and coronavirus spike evolution through antibody pressure

The evolution of circulating viruses is shaped by their need to evade antibody response, which mainly targets the viral spike. Because of the high density of spikes on the viral surface, not all antigenic sites are targeted equally by antibodies. We offer here a geometry-based approach to predict and rank the probability of surface residues of SARS spike (S protein) and influenza H1N1 spike (hemagglutinin) to acquire antibody-escaping mutations utilizing in-silico models of viral structure. We used coarse-grained MD simulations to estimate the on-rate (targeting) of an antibody model to surface residues of the spike protein. Analyzing publicly available sequences, we found that spike surface sequence diversity of the pre-pandemic seasonal influenza H1N1 and the sarbecovirus subgenus highly correlates with our model prediction of antibody targeting. In particular, we identified an antibody-targeting gradient, which matches a mutability gradient along the main axis of the spike. This identifies the role of viral surface geometry in shaping the evolution of circulating viruses. For the 2009 H1N1 and SARS-CoV-2 pandemics, a mutability gradient along the main axis of the spike was not observed. Our model further allowed us to identify key residues of the SARS-CoV-2 spike at which antibody escape mutations have now occurred. Therefore, it can inform of the likely functional role of observed mutations and predict at which residues antibody-escaping mutation might arise.     

An evaluation of multiple feed-forward networks on GPUs

The Graphics Processing Unit (GPU) originally designed for rendering graphics and which is difficult to program for other tasks, has since evolved into a device suitable for general-purpose computations. As a result graphics hardware has become progressively more attractive yielding unprecedented performance at a relatively low cost. Thus, it is the ideal candidate to accelerate a wide variety of data parallel tasks in many fields such as in Machine Learning (ML). As problems become more and more demanding, parallel implementations of learning algorithms are crucial for a useful application. In particular, the implementation of Neural Networks (NNs) in GPUs can significantly reduce the long training times during the learning process. In this paper we present a GPU parallel implementation of the Back-Propagation (BP) and Multiple Back-Propagation (MBP) algorithms, and describe the GPU kernels needed for this task. The results obtained on well-known benchmarks show faster training times and improved performances as compared to the implementation in traditional hardware, due to maximized floating-point throughput and memory bandwidth. Moreover, a preliminary GPU based Autonomous Training System (ATS) is developed which aims at automatically finding high-quality NNs-based solutions for a given problem.     

Reliability of spike and burst firing in thalamocortical relay cells

The reliability and precision of the timing of spikes in a spike train is an important aspect of neuronal coding. We investigated reliability in thalamocortical relay (TCR) cells in the acute slice and also in a Morris-Lecar model with several extensions. A frozen Gaussian noise current, superimposed on a DC current, was injected into the TCR cell soma. The neuron responded with spike trains that showed trial-to-trial variability, due to amongst others slow changes in its internal state and the experimental setup. The DC current allowed to bring the neuron in different states, characterized by a well defined membrane voltage (between ?80 and ?50 mV) and by a specific firing regime that on depolarization gradually shifted from a predominantly bursting regime to a tonic spiking regime. The filtered frozen white noise generated a spike pattern output with a broad spike interval distribution. The coincidence factor and the Hunter and Milton measure were used as reliability measures of the output spike train. In the experimental TCR cell as well as the Morris-Lecar model cell the reliability depends on the shape (steepness) of the current input versus spike frequency output curve. The model also allowed to study the contribution of three relevant ionic membrane currents to reliability: a T-type calcium current, a cation selective h-current and a calcium dependent potassium current in order to allow bursting, investigate the consequences of a more complex current-frequency relation and produce realistic firing rates. The reliability of the output of the TCR cell increases with depolarization. In hyperpolarized states bursts are more reliable than single spikes. The analytically derived relations were capable to predict several of the experimentally recorded spike features.     

Environmental selection of the feed-forward loop circuit in gene-regulation networks

Gene-regulation networks contain recurring elementary circuits termed network motifs. It is of interest to understand under which environmental conditions each motif might be selected. To address this, we study one of the most significant network motifs, a three-gene circuit called the coherent feed-forward loop (FFL). The FFL has been demonstrated theoretically and experimentally to perform a basic information-processing function: it shows a delay following ON steps of an input inducer, but not after OFF steps. Here, we ask under what environmental conditions might the FFL be selected over simpler gene circuits, based on this function. We employ a theoretical cost-benefit analysis for the selection of gene circuits in a given environment. We find conditions that the environment must satisfy in order for the FFL to be selected over simpler circuits: the FFL is selected in environments where the distribution of the input pulse duration is sufficiently broad and contains both long and short pulses. Optimal values of the biochemical parameters of the FFL circuit are determined as a function of the environment such that the delay in the FFL blocks deleterious short pulses of induction. This approach can be generally used to study the evolutionary selection of other network motifs.     

Convergent evolution of modularity in metabolic networks through different community structures

ABSTRACT: BACKGROUND: It has been reported that the modularity of metabolic networks of bacteria is closely relatedto the variability of their living habitats. However, given the dependency of the modularityscore on the community structure, it remains unknown whether organisms achieve certainmodularity via similar or different community structures. RESULTS: In this work, we studied the relationship between similarities in modularity scores andsimilarities in community structures of the metabolic networks of 1021 species. Bothsimilarities are then compared against the genetic distances. We revisited the associationbetween modularity and variability of the microbial living environments and extended theanalysis to other aspects of their life style such as temperature and oxygen requirements. Wealso tested both topological and biological intuition of the community structures identifiedand investigated the extent of their conservation with respect to the taxomony. CONCLUSIONS: We find that similar modularities are realized by different community structures. We findthat such convergent evolution of modularity is closely associated with the number of(distinct) enzymes in the organism's metabolome, a consequence of different life styles ofthe species. We find that the order of modularity is the same as the order of the number ofthe enzymes under the classification based on the temperature preference but not on theoxygen requirement. Besides, inspection of modularity-based communities reveals thatthese communities are graph-theoretically meaningful yet not reflective of specificbiological functions. From an evolutionary perspective, we find that the communitystructures are conserved only at the level of kingdoms. Our results call for moreinvestigation into the interplay between evolution and modularity: how evolution shapesmodularity, and how modularity affects evolution (mainly in terms of fitness andevolvability). Further, our results call for exploring new measures of modularity andnetwork communities that better correspond to functional categorizations.     

The biphasic behavior of incoherent feed-forward loops in biomolecular regulatory networks

An incoherent feed-forward loop (FFL) is one of the most-frequently observed motifs in biomolecular regulatory networks. It has been thought that the incoherent FFL is designed simply to induce a transient response shaped by a 'fast activation and delayed inhibition'. We find that the dynamics of various incoherent FFLs can be further classified into two types: time-dependent biphasic responses and dose-dependent biphasic responses. Why do the structurally identical incoherent FFLs play such different dynamical roles? Through computational studies, we show that the dynamics of the two types of incoherent FFLs are mutually exclusive. Following from further computational results and experimental observations, we hypothesize that incoherent FFLs have been optimally designed to achieve distinct biological function arising from different cellular contexts. Additional Supporting Information may be found in the online version of the article.     

Excitatory and feed-forward inhibitory hippocampal synapses work synergistically as an adaptive filter of natural spike trains

Short-term synaptic plasticity (STP) is an important mechanism for modifying neural circuits during computation. Although STP is much studied, its role in the processing of complex natural spike patterns is unknown. Here we analyze the responses of excitatory and inhibitory hippocampal synapses to natural spike trains at near-physiological temperatures. Our results show that excitatory and inhibitory synapses express complementary sets of STP components that selectively change synaptic strength during epochs of high-frequency discharge associated with hippocampal place fields. In both types of synapses, synaptic strength rapidly alternates between a near-constant level during low activity and another near-constant, but elevated (for excitatory synapses) or reduced (for inhibitory synapses) level during high-frequency epochs. These history-dependent changes in synaptic strength are largely independent of the particular temporal pattern within the discharges, and occur concomitantly in the two types of synapses. When excitatory and feed-forward inhibitory synapses are co-activated within the hippocampal feed-forward circuit unit, the net effect of their complementary STP is an additional increase in the gain of excitatory synapses during high-frequency discharges via selective disinhibition. Thus, excitatory and feed-forward inhibitory hippocampal synapses in vitro act synergistically as an adaptive filter that operates in a switch-like manner and is selective for high-frequency epochs.     

Frequency-domain order parameters for the burst and spike synchronization transitions of bursting neurons

We are interested in characterization of synchronization transitions of bursting neurons in the frequency domain. Instantaneous population firing rate (IPFR) R(t), which is directly obtained from the raster plot of neural spikes, is often used as a realistic collective quantity describing population activities in both the computational and the experimental neuroscience. For the case of spiking neurons, a realistic time-domain order parameter, based on R(t), was introduced in our recent work to characterize the spike synchronization transition. Unlike the case of spiking neurons, the IPFR R(t) of bursting neurons exhibits population behaviors with both the slow bursting and the fast spiking timescales. For our aim, we decompose the IPFR R(t) into the instantaneous population bursting rate R_b(t) (describing the bursting behavior) and the instantaneous population spike rate R_s(t) (describing the spiking behavior) via frequency filtering, and extend the realistic order parameter to the case of bursting neurons. Thus, we develop the frequency-domain bursting and spiking order parameters which are just the bursting and spiking “coherence factors” β_b and β_s of the bursting and spiking peaks in the power spectral densities of R_b and R_s (i.e., “signal to noise” ratio of the spectral peak height and its relative width). Through calculation of β_b and β_s, we obtain the bursting and spiking thresholds beyond which the burst and spike synchronizations break up, respectively. Consequently, it is shown in explicit examples that the frequency-domain bursting and spiking order parameters may be usefully used for characterization of the bursting and the spiking transitions, respectively.     

Dynamic gating of spike propagation in the mitral cell lateral dendrites

A unique feature of the olfactory bulb circuit is the long projection of the mitral cell lateral dendrites. Through dendrodendritic reciprocal synapses, these dendrites connect one olfactory glomerular module to hundreds of others; but the functional principles governing these extensive lateral interactions remain largely unknown. Here we report that the spatial extent of action potential propagation in these dendrites is dynamically regulated by inhibitory synapses distributed along the dendrites. The extent of propagation determines the spatial pattern of Ca(2+) influx and thus the range and number of dendrodendritic synapses to be activated. Accordingly, network control of spike traffic in the mitral cell lateral dendrites can mediate dynamic interaction with different combinations of glomerular modules in response to different odorants.     

Complex patterns of environmental niche evolution in Iberian columbines (genus Aquilegia,Ranunculaceae)

Aims This study explores the patterns of niche differentiation in a group of seven closely related columbines (genus Aquilegia, Ranunculaceae) from the Iberian Peninsula. Populations of these columbines are subject to complex patterns of divergent selection across environments, which partly explain the taxonomic structure of the group. This suggests the hypothesis that niche divergence must have occurred along the process of diversification of the group.Methods We used MaxEnt to build environmental niche models of seven subspecies belonging to the three species of Aquilegia present in the Iberian Peninsula. From these models, we compared the environmental niches through two different approaches: ENMtools and multivariate methods.Important findings MaxEnt distributions conformed closely to the actual distribution of the study taxa. ENMtools methods failed to uncover any clear patterns of niche differentiation or conservatism in Iberian columbines. Multivariate analyses indicate the existence of differentiation along altitudinal gradients and along a gradient of climatic conditions determined by the summer precipitation and temperatures. However, climatic conditions related to winter temperature and precipitation, as well as soil properties, were equally likely to show conservatism or divergence. The complex patterns of niche evolution we found suggest that Iberian Columbines have not been significantly constrained by forces of niche conservatism, so they could respond adaptively to the fast and profound climate changes in the Iberian Peninsula through the glacial cycles of the Pleistocene.     

Noise-induced burst and spike synchronizations in an inhibitory small-world network of subthreshold bursting neurons

We are interested in noise-induced firings of subthreshold neurons which may be used for encoding environmental stimuli. Noise-induced population synchronization was previously studied only for the case of global coupling, unlike the case of subthreshold spiking neurons. Hence, we investigate the effect of complex network architecture on noise-induced synchronization in an inhibitory population of subthreshold bursting Hindmarsh–Rose neurons. For modeling complex synaptic connectivity, we consider the Watts–Strogatz small-world network which interpolates between regular lattice and random network via rewiring, and investigate the effect of small-world connectivity on emergence of noise-induced population synchronization. Thus, noise-induced burst synchronization (synchrony on the slow bursting time scale) and spike synchronization (synchrony on the fast spike time scale) are found to appear in a synchronized region of the J–D plane (J: synaptic inhibition strength and D: noise intensity). As the rewiring probability p is decreased from 1 (random network) to 0 (regular lattice), the region of spike synchronization shrinks rapidly in the J–D plane, while the region of the burst synchronization decreases slowly. We separate the slow bursting and the fast spiking time scales via frequency filtering, and characterize the noise-induced burst and spike synchronizations by employing realistic order parameters and statistical-mechanical measures introduced in our recent work. Thus, the bursting and spiking thresholds for the burst and spike synchronization transitions are determined in terms of the bursting and spiking order parameters, respectively. Furthermore, we also measure the degrees of burst and spike synchronizations in terms of the statistical-mechanical bursting and spiking measures, respectively.     

Serial evolutionary networks of within-patient HIV-1 sequences reveal patterns of evolution of X4 strains

Background  

The HIV virus is known for its ability to exploit numerous genetic and evolutionary mechanisms to ensure its proliferation, among them, high replication, mutation and recombination rates. Sliding MinPD, a recently introduced computational method [1], was used to investigate the patterns of evolution of serially-sampled HIV-1 sequence data from eight patients with a special focus on the emergence of X4 strains. Unlike other phylogenetic methods, Sliding MinPD combines distance-based inference with a nonparametric bootstrap procedure and automated recombination detection to reconstruct the evolutionary history of longitudinal sequence data. We present serial evolutionary networks as a longitudinal representation of the mutational pathways of a viral population in a within-host environment. The longitudinal representation of the evolutionary networks was complemented with charts of clinical markers to facilitate correlation analysis between pertinent clinical information and the evolutionary relationships.     

Complex patterns predicted in an in vitro experimental model system for the evolution of molecular cooperation

An isothermal biochemical in vitro amplification system with two trans-cooperatively coupled amplifying DNA molecules was investigated homogeneously using a hierarchy of kinetic models and as a simplified reaction-diffusion system. In our model of this recently developed experimental system, no reaction mechanism higher than second order occurs, yet numerical simulations show a variety of complex spatiotemporal patterns which arise in response to finite amplitude perturbations in a flow reactor. In a certain domain of the kinetic parameters the system shows self-replicating spots. These spots can stabilize the cooperative amplification in such evolving systems against emerging parasites. The results are of high relevance for experimental studies on these functional in vitro ecosystems in spatially resolved microstructured reactors.     

3D propagation of the shock-induced vibrations through the whole lower-limb during running

Shock-induced vibrations to the feet have been related to the feel of comfort, the biomechanical control of performance, and the risk of fatigue or injury. Up to recently, the complexity of measuring the human biodynamic response to vibration exposure implied to focus most of the research on the axial acceleration at the tibia. Using wireless three-dimensional accelerometers, this paper investigates the propagation of shock-induced vibrations through the whole lower-limb during running in the temporal and the spectral domains. Results indicated that the vibrations were not consistent across the lower-limb, showing various spatial and spectral distributions of energy. The amount of energy was not constantly decreasing from the distal to the proximal extremity of the runner’s lower-limb, especially regarding the lateral epicondyle of the femur. Vibrations in the transversal plane of the segments were substantial compared to the longitudinal axis regarding the distal extremity of the tibia, and the lateral epicondyle of the femur. Further, the spectral content was wider at the distal than at the proximal end of the lower-limb. Finally, to get a thorough understanding of the risks incurred by the runners, the need to account for shock-induced vibrations up to 50 Hz has been stressed when investigating three-dimensional vibrations. The overall study raises attention on the substantial importance of the transverse components of the acceleration, and their potential relation to shear fatigue and injury during running.