Regulation of Irregular Neuronal Firing by Autaptic Transmission

The importance of self-feedback autaptic transmission in modulating spike-time irregularity is still poorly understood. By using a biophysical model that incorporates autaptic coupling, we here show that self-innervation of neurons participates in the modulation of irregular neuronal firing, primarily by regulating the occurrence frequency of burst firing. In particular, we find that both excitatory and electrical autapses increase the occurrence of burst firing, thus reducing neuronal firing regularity. In contrast, inhibitory autapses suppress burst firing and therefore tend to improve the regularity of neuronal firing. Importantly, we show that these findings are independent of the firing properties of individual neurons, and as such can be observed for neurons operating in different modes. Our results provide an insightful mechanistic understanding of how different types of autapses shape irregular firing at the single-neuron level, and they highlight the functional importance of autaptic self-innervation in taming and modulating neurodynamics.Comment: 27 pages, 8 figure

The Effects of Neurosteroids, such as Pregnenolone Sulfate and its receptor, TrpM3 in the Retina.

Pregnenolone sulfate (PregS) is the precursor to all steroid hormones and is produced in neurons in an activity dependent manner. Studies have shown that PregS production is upregulated during certain critical periods of development, such as in the first year of life in humans, during adolescence, and during pregnancy. Conversely, PregS is decreased during aging, as well as in several neurodevelopmental and neurodegenerative conditions. There are several known targets of PregS, such as a positive allosteric modulator NMDA receptors, sigma1 receptor, and as a negative allosteric modulator of GABA-A receptors. Recently a transient receptor potential channel, TrpM3 has been shown to be activated by PregS. TrpM3 is a heat sensitive (between 33-40oC), non-selective cation channel that is outwardly rectifying. PregS has been shown to increase the frequency of post-synaptic currents in the hippocampus and developing cerebellum, induce calcium transients in a subset of retinal ganglion cells, and enhance memory formation in rodents. Furthermore, PregS mediated TrpM3 activation induces calcium dependent transcription of early immediate genes, suggesting that activation of this channel may produce lasting effects on cells and systems in which it is activated. Because PregS is abundant during critical periods of development, we hypothesized that it may play a significant role during development. Furthermore, the role of PregS or its receptor TrpM3, has not previously been well characterized in the retina. To address this question, in this dissertation, we examine the role of the neurosteroid PregS and its receptor, TrpM3, on retinal waves, which are characteristic of specific stages of synaptic development and connectivity. Briefly, we show that PregS induces a TrpM3 dependent prolonged calcium transient, which is absent in the TrpM3-/- animals and increases the correlation of cell participation in waves. We also show that TrpM3 increases the frequency of post-synaptic currents, indicating a mechanism of action presynaptic to retinal ganglion cells, but that TrpM3 is expressed primarily in RGCs and Müller glia. Taken together, our results indicate that both PregS and TrpM3 are important in modulating spontaneous synaptic activity during development

Mammalian Brain As a Network of Networks

Acknowledgements AZ, SG and AL acknowledge support from the Russian Science Foundation (16-12-00077). Authors thank T. Kuznetsova for Fig. 6.Peer reviewedPublisher PD

Probing the dynamics of identified neurons with a data-driven modeling approach

In controlling animal behavior the nervous system has to perform within the operational limits set by the requirements of each specific behavior. The implications for the corresponding range of suitable network, single neuron, and ion channel properties have remained elusive. In this article we approach the question of how well-constrained properties of neuronal systems may be on the neuronal level. We used large data sets of the activity of isolated invertebrate identified cells and built an accurate conductance-based model for this cell type using customized automated parameter estimation techniques. By direct inspection of the data we found that the variability of the neurons is larger when they are isolated from the circuit than when in the intact system. Furthermore, the responses of the neurons to perturbations appear to be more consistent than their autonomous behavior under stationary conditions. In the developed model, the constraints on different parameters that enforce appropriate model dynamics vary widely from some very tightly controlled parameters to others that are almost arbitrary. The model also allows predictions for the effect of blocking selected ionic currents and to prove that the origin of irregular dynamics in the neuron model is proper chaoticity and that this chaoticity is typical in an appropriate sense. Our results indicate that data driven models are useful tools for the in-depth analysis of neuronal dynamics. The better consistency of responses to perturbations, in the real neurons as well as in the model, suggests a paradigm shift away from measuring autonomous dynamics alone towards protocols of controlled perturbations. Our predictions for the impact of channel blockers on the neuronal dynamics and the proof of chaoticity underscore the wide scope of our approach

A simulation model of the locomotion controllers for the nematode Caenorhabditis elegans

This paper presents a simple yet biologicallygrounded model of the C. elegans neural circuit for forward locomotive control. The model considers a limited subset of the C. elegans nervous system, within a minimal two-dimensional environment. Despite its reductionist approach, this model is sufficiently rich to generate patterns of undulations that are reminiscent of the biological worm’s behaviour and qualitatively similar to patterns which have been shown to generate locomotion in a model of a richer physical environment. Interestingly, and contrary to conventional wisdom about neural circuits for motor control, our results are consistent with the conjecture that the worm may be relying on feedback from the shape of its body to generate undulations that propel it forward or backward

Network Dynamics Mediate Circadian Clock Plasticity

A circadian clock governs most aspects of mammalian behavior. Although its properties are in part genetically determined, altered light-dark environment can change circadian period length through a mechanism requiring de novo DNA methylation. We show here that this mechanism is mediated not via cell-autonomous clock properties, but rather through altered networking within the suprachiasmatic nuclei (SCN), the circadian “master clock,” which is DNA methylated in region-specific manner. DNA methylation is necessary to temporally reorganize circadian phasing among SCN neurons, which in turn changes the period length of the network as a whole. Interruption of neural communication by inhibiting neuronal firing or by physical cutting suppresses both SCN reorganization and period changes. Mathematical modeling suggests, and experiments confirm, that this SCN reorganization depends upon GABAergic signaling. Our results therefore show that basic circadian clock properties are governed by dynamic interactions among SCN neurons, with neuroadaptations in network function driven by the environment

A Mathematical model for Astrocytes mediated LTP at Single Hippocampal Synapses

Many contemporary studies have shown that astrocytes play a significant role in modulating both short and long form of synaptic plasticity. There are very few experimental models which elucidate the role of astrocyte over Long-term Potentiation (LTP). Recently, Perea & Araque (2007) demonstrated a role of astrocytes in induction of LTP at single hippocampal synapses. They suggested a purely pre-synaptic basis for induction of this N-methyl-D- Aspartate (NMDA) Receptor-independent LTP. Also, the mechanisms underlying this pre-synaptic induction were not investigated. Here, in this article, we propose a mathematical model for astrocyte modulated LTP which successfully emulates the experimental findings of Perea & Araque (2007). Our study suggests the role of retrograde messengers, possibly Nitric Oxide (NO), for this pre-synaptically modulated LTP.Comment: 51 pages, 15 figures, Journal of Computational Neuroscience (to appear

G protein-coupled receptor signalling in astrocytes in health and disease: A focus on metabotropic glutamate receptors

Work published over the past 10–15 years has caused the neuroscience community to engage in a process of constant re-evaluation of the roles of glial cells in the mammalian central nervous system. Recent emerging evidence suggests that, in addition to carrying out various homeostatic functions within the CNS, astrocytes can also engage in a two-way dialogue with neurons. Astrocytes possess many of the receptors, and some of the ion channels, present in neurons endowing them with an ability to sense and respond to an array of neuronal signals. In addition, an expanding number of small molecules and proteins have been shown to be released by astrocytes in both health and disease. In this commentary we will highlight advances in our understanding of G protein-coupled receptor signalling in astrocytes, with a particular emphasis on metabotropic glutamate (mGlu) receptors. Discussion will focus on the major mGlu receptors expressed in astrocytes, mGlu3 and mGlu5, how these receptors can influence different aspects of astrocyte physiology, and how signalling by these G protein-coupled receptors might change under pathophysiological circumstances