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Noise-enhanced nonlinear response and the role of modular structure for signal detection in neuronal networks  [PDF]
M. A. Lopes,K. -E. Lee,A. V. Goltsev,J. F. F. Mendes
Quantitative Biology , 2014, DOI: 10.1103/PhysRevE.90.052709
Abstract: We find that sensory noise delivered together with a weak periodic signal not only enhances nonlinear response of neuronal networks, but also improves the synchronization of the response to the signal. We reveal this phenomenon in neuronal networks that are in a dynamical state near a saddle-node bifurcation corresponding to appearance of sustained network oscillations. In this state, even a weak periodic signal can evoke sharp nonlinear oscillations of neuronal activity. These sharp network oscillations have a deterministic form and amplitude determined by nonlinear dynamical equations. The signal-to-noise ratio reaches a maximum at an optimum level of sensory noise, manifesting stochastic resonance (SR) at the population level. We demonstrate SR by use of simulations and numerical integration of rate equations in a cortical model with stochastic neurons. Using this model, we mimic the experiments of Gluckman et al. [B. J. Gluckman et al, Phys. Rev. Lett., v. 77, 4098 (1996)] that have given evidence of SR in mammalian brain. We also study neuronal networks in which neurons are grouped in modules and every module works in the regime of SR. We find that even a few modules can strongly enhance the reliability of signal detection in comparison with the case when a modular organization is absent.
Neuronal Plasticity and Multisensory Integration in Filial Imprinting  [PDF]
Stephen Michael Town,Brian John McCabe
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0017777
Abstract: Many organisms sample their environment through multiple sensory systems and the integration of multisensory information enhances learning. However, the mechanisms underlying multisensory memory formation and their similarity to unisensory mechanisms remain unclear. Filial imprinting is one example in which experience is multisensory, and the mechanisms of unisensory neuronal plasticity are well established. We investigated the storage of audiovisual information through experience by comparing the activity of neurons in the intermediate and medial mesopallium of imprinted and na?ve domestic chicks (Gallus gallus domesticus) in response to an audiovisual imprinting stimulus and novel object and their auditory and visual components. We find that imprinting enhanced the mean response magnitude of neurons to unisensory but not multisensory stimuli. Furthermore, imprinting enhanced responses to incongruent audiovisual stimuli comprised of mismatched auditory and visual components. Our results suggest that the effects of imprinting on the unisensory and multisensory responsiveness of IMM neurons differ and that IMM neurons may function to detect unexpected deviations from the audiovisual imprinting stimulus.
Signal Propagation in Feedforward Neuronal Networks with Unreliable Synapses  [PDF]
Daqing Guo,Chunguang Li
Quantitative Biology , 2011, DOI: 10.1007/s10827-010-0279-7
Abstract: In this paper, we systematically investigate both the synfire propagation and firing rate propagation in feedforward neuronal network coupled in an all-to-all fashion. In contrast to most earlier work, where only reliable synaptic connections are considered, we mainly examine the effects of unreliable synapses on both types of neural activity propagation in this work. We first study networks composed of purely excitatory neurons. Our results show that both the successful transmission probability and excitatory synaptic strength largely influence the propagation of these two types of neural activities, and better tuning of these synaptic parameters makes the considered network support stable signal propagation. It is also found that noise has significant but different impacts on these two types of propagation. The additive Gaussian white noise has the tendency to reduce the precision of the synfire activity, whereas noise with appropriate intensity can enhance the performance of firing rate propagation. Further simulations indicate that the propagation dynamics of the considered neuronal network is not simply determined by the average amount of received neurotransmitter for each neuron in a time instant, but also largely influenced by the stochastic effect of neurotransmitter release. Second, we compare our results with those obtained in corresponding feedforward neuronal networks connected with reliable synapses but in a random coupling fashion. We confirm that some differences can be observed in these two different feedforward neuronal network models. Finally, we study the signal propagation in feedforward neuronal networks consisting of both excitatory and inhibitory neurons, and demonstrate that inhibition also plays an important role in signal propagation in the considered networks.
Natural Killer Cell Signal Integration Balances Synapse Symmetry and Migration  [PDF]
Fiona J. Culley,Matthew Johnson,J. Henry Evans,Sunil Kumar,Rupert Crilly,Juan Casasbuenas,Tim Schnyder,Maryam Mehrabi,Mahendra P. Deonarain,Dmitry S. Ushakov,Veronique Braud,Günter Roth,Roland Brock,Karsten K?hler,Daniel M. Davis
PLOS Biology , 2012, DOI: 10.1371/journal.pbio.1000159
Abstract: Natural killer (NK) cells discern the health of other cells by recognising the balance of activating and inhibitory ligands expressed by each target cell. However, how the integration of activating and inhibitory signals relates to formation of the NK cell immune synapse remains a central question in our understanding of NK cell recognition. Here we report that ligation of LFA-1 on NK cells induced asymmetrical cell spreading and migration. In contrast, ligation of the activating receptor NKG2D induced symmetrical spreading of ruffled lamellipodia encompassing a dynamic ring of f-actin, concurrent with polarization towards a target cell and a “stop” signal. Ligation of both LFA-1 and NKG2D together resulted in symmetrical spreading but co-ligation of inhibitory receptors reverted NK cells to an asymmetrical migratory configuration leading to inhibitory synapses being smaller and more rapidly disassembled. Using micropatterned activating and inhibitory ligands, signals were found to be continuously and locally integrated during spreading. Together, these data demonstrate that NK cells spread to form large, stable, symmetrical synapses if activating signals dominate, whereas asymmetrical migratory “kinapses” are favoured if inhibitory signals dominate. This clarifies how the integration of activating and inhibitory receptor signals is translated to an appropriate NK cell response.
Natural Killer Cell Signal Integration Balances Synapse Symmetry and Migration  [PDF]
Fiona J. Culley,Matthew Johnson,J. Henry Evans,Sunil Kumar,Rupert Crilly,Juan Casasbuenas,Tim Schnyder,Maryam Mehrabi,Mahendra P. Deonarain,Dmitry S. Ushakov,Veronique Braud,Günter Roth,Roland Brock,Karsten K?hler,Daniel M. Davis
PLOS Biology , 2009, DOI: 10.1371/journal.pbio.1000159
Abstract: Natural killer (NK) cells discern the health of other cells by recognising the balance of activating and inhibitory ligands expressed by each target cell. However, how the integration of activating and inhibitory signals relates to formation of the NK cell immune synapse remains a central question in our understanding of NK cell recognition. Here we report that ligation of LFA-1 on NK cells induced asymmetrical cell spreading and migration. In contrast, ligation of the activating receptor NKG2D induced symmetrical spreading of ruffled lamellipodia encompassing a dynamic ring of f-actin, concurrent with polarization towards a target cell and a “stop” signal. Ligation of both LFA-1 and NKG2D together resulted in symmetrical spreading but co-ligation of inhibitory receptors reverted NK cells to an asymmetrical migratory configuration leading to inhibitory synapses being smaller and more rapidly disassembled. Using micropatterned activating and inhibitory ligands, signals were found to be continuously and locally integrated during spreading. Together, these data demonstrate that NK cells spread to form large, stable, symmetrical synapses if activating signals dominate, whereas asymmetrical migratory “kinapses” are favoured if inhibitory signals dominate. This clarifies how the integration of activating and inhibitory receptor signals is translated to an appropriate NK cell response.
Signal duration and the time scale dependence of signal integration in biochemical pathways  [PDF]
Jason W. Locasale
Quantitative Biology , 2008,
Abstract: Signal duration (e.g. the time scales over which an active signaling intermediate persists) is a key regulator of biological decisions in myriad contexts such as cell growth, proliferation, and developmental lineage commitments. Accompanying differences in signal duration are numerous downstream biological processes that require multiple steps of biochemical regulation. Here, we present an analysis that investigates how simple biochemical motifs that involve multiple stages of regulation can be constructed to differentially process signals that persist at different time scales. We compute the dynamic gain within these networks and resulting power spectra to better understand how biochemical networks can integrate signals at different time scales. We identify topological features of these networks that allow for different frequency dependent signal processing properties. Our studies suggest design principles for why signal duration in connection with multiple steps of downstream regulation is a ubiquitous control motif in biochemical systems.
Active Dendrites Enhance Neuronal Dynamic Range  [PDF]
Leonardo L. Gollo ,Osame Kinouchi,Mauro Copelli
PLOS Computational Biology , 2009, DOI: 10.1371/journal.pcbi.1000402
Abstract: Since the first experimental evidences of active conductances in dendrites, most neurons have been shown to exhibit dendritic excitability through the expression of a variety of voltage-gated ion channels. However, despite experimental and theoretical efforts undertaken in the past decades, the role of this excitability for some kind of dendritic computation has remained elusive. Here we show that, owing to very general properties of excitable media, the average output of a model of an active dendritic tree is a highly non-linear function of its afferent rate, attaining extremely large dynamic ranges (above 50 dB). Moreover, the model yields double-sigmoid response functions as experimentally observed in retinal ganglion cells. We claim that enhancement of dynamic range is the primary functional role of active dendritic conductances. We predict that neurons with larger dendritic trees should have larger dynamic range and that blocking of active conductances should lead to a decrease in dynamic range.
Information processing and signal integration in bacterial quorum sensing  [PDF]
Pankaj Mehta,Sidhartha Goyal,Tao Long,Bonnie Bassler,Ned S. Wingreen
Quantitative Biology , 2009,
Abstract: Bacteria communicate using secreted chemical signaling molecules called autoinducers in a process known as quorum sensing. The quorum-sensing network of the marine bacterium {\it Vibrio harveyi} employs three autoinducers, each known to encode distinct ecological information. Yet how cells integrate and interpret the information contained within the three autoinducer signals remains a mystery. Here, we develop a new framework for analyzing signal integration based on Information Theory and use it to analyze quorum sensing in {\it V. harveyi}. We quantify how much the cells can learn about individual autoinducers and explain the experimentally observed input-output relation of the {\it V. harveyi} quorum-sensing circuit. Our results suggest that the need to limit interference between input signals places strong constraints on the architecture of bacterial signal-integration networks, and that bacteria likely have evolved active strategies for minimizing this interference. Here we analyze two such strategies: manipulation of autoinducer production and feedback on receptor number ratios.
Signal duration and the time scale dependence of signal integration in biochemical pathways
Jason W Locasale
BMC Systems Biology , 2008, DOI: 10.1186/1752-0509-2-108
Abstract: Here we present an analysis that investigates how simple biochemical motifs that involve multiple stages of regulation can be constructed to differentially process signals that persist at different time scales. We compute the dynamic, frequency dependent gain within these networks and resulting power spectra to better understand how biochemical networks can integrate signals at different time scales. We identify topological features of these networks that allow for different frequency dependent signal processing properties.We show that multi-staged cascades are effective in integrating signals of long duration whereas multi-staged cascades that operate in the presence of negative feedback are effective in integrating signals of short duration. Our studies suggest principles for why signal duration in connection with multiple steps of downstream regulation is a ubiquitous motif in biochemical systems.Signal duration (e.g. the length of time over which a signaling intermediate is active) is a critical determinant in mediating cell decisions in numerous biological processes including cell growth, proliferation, and developmental lineage commitments (Fig. 1) [1-8]. One fundamental issue in signal transduction and cell decision making then is how differences in signal duration are detected to achieve the appropriate biological response.Accompanying changes in signal duration are multiple stages of biochemical regulation of differing network topology that collectively integrate an incoming signal to deliver a specific biological response. The sequential activation of multiple steps in a biochemical pathway is a ubiquitous regulatory motif involved in many aspects of gene regulation, metabolism, and intracellular signal transduction. Many advantages of having multiple steps of regulation as opposed to having activation occur through a single step have been documented. A signaling cascade can allow for attenuation of noise, incorporation of additional regulatory checkpoints
Neuronal avalanches imply maximum dynamic range in cortical networks at criticality  [PDF]
Woodrow L. Shew,Hongdian Yang,Thomas Petermann,Rajarshi Roy,Dietmar Plenz
Quantitative Biology , 2009,
Abstract: Spontaneous neuronal activity is a ubiquitous feature of cortex. Its spatiotemporal organization reflects past input and modulates future network output. Here we study whether a particular type of spontaneous activity is generated by a network that is optimized for input processing. Neuronal avalanches are a type of spontaneous activity observed in superficial cortical layers in vitro and in vivo with statistical properties expected from a network in a 'critical state'. Theory predicts that the critical state and, therefore, neuronal avalanches are optimal for input processing, but until now, this is untested in experiments. Here, we use cortex slice cultures grown on planar microelectrode arrays to demonstrate that cortical networks which generate neuronal avalanches benefit from maximized dynamic range, i.e. the ability to respond to the greatest range of stimuli. By changing the ratio of excitation and inhibition in the cultures, we derive a network tuning curve for stimulus processing as a function of distance from the critical state in agreement with predictions from our simulations. Our findings suggest that in the cortex, (1) balanced excitation and inhibition establishes the critical state, which maximizes the range of inputs that can be processed and (2) spontaneous activity and input processing are unified in the context of critical phenomena.
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