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

Neuronal and astroglial correlates underlying spatiotemporal Intrinsic Optical Signal in the rat hippocampal slice

Widely used for mapping afferent activated brain areas in vivo, the label-free intrinsic optical signal (IOS) is mainly ascribed to blood volume changes subsequent to glial glutamate uptake. By contrast, IOS imaged in vitro is generally attributed to neuronal and glial cell swelling, however the relative contribution of different cell types and molecular players remained largely unknown. We characterized IOS to Schaffer collateral stimulation in the rat hippocampal slice using a 464-element photodiode-array device that enables IOS monitoring at 0.6 ms time-resolution in combination with simultaneous field potential recordings. We used brief half-maximal stimuli by applying a medium intensity 50 Volt-stimulus train within 50 ms (20 Hz). IOS was primarily observed in the str. pyramidale and proximal region of the str. radiatum of the hippocampus. It was eliminated by tetrodotoxin blockade of voltage-gated Na+ channels and was significantly enhanced by suppressing inhibitory signaling with gamma-aminobutyric acid(A) receptor antagonist picrotoxin. We found that IOS was predominantly initiated by postsynaptic Glu receptor activation and progressed by the activation of astroglial Glu transporters and Mg2+-independent astroglial N-methyl-D-aspartate receptors. Under control conditions, role for neuronal K+/Cl- cotransporter KCC2, but not for glial Na+/K+/Cl- cotransporter NKCC1 was observed. Slight enhancement and inhibition of IOS through non-specific Cl- and volume-regulated anion channels, respectively, were also depicted. High-frequency IOS imaging, evoked by brief afferent stimulation in brain slices provide a new paradigm for studying mechanisms underlying IOS genesis. Major players disclosed this way imply that spatiotemporal IOS reflects glutamatergic neuronal activation and astroglial response, as observed within the hippocampus. Our model may help to better interpret in vivo IOS and support diagnosis in the future

Determining the neurotransmitter concentration profile at active synapses

Establishing the temporal and concentration profiles of neurotransmitters during synaptic release is an essential step towards understanding the basic properties of inter-neuronal communication in the central nervous system. A variety of ingenious attempts has been made to gain insights into this process, but the general inaccessibility of central synapses, intrinsic limitations of the techniques used, and natural variety of different synaptic environments have hindered a comprehensive description of this fundamental phenomenon. Here, we describe a number of experimental and theoretical findings that has been instrumental for advancing our knowledge of various features of neurotransmitter release, as well as newly developed tools that could overcome some limits of traditional pharmacological approaches and bring new impetus to the description of the complex mechanisms of synaptic transmission

Shaping of Spike-Timing-Dependent Plasticity curve using interneuron and calcium dynamics

The field of Computational Neuroscience is where neuroscience and computational modelling merge together. It is an ever-emerging area of research where the level of biological modelling can range from small-scale cellular models, to the larger network scale models. This MSc Thesis will detail the research carried out when looking at a small network of two neurons. These neurons have been modelled with a high level of detail, with the intention of using it to study the phenomenon of Spike-Timing-Dependent Plasticity (or STDP). Spike-Timing-Dependent Plasticity is the occurrence of either a strengthening or weakening in connection between two neurons, depending on the temporal order of stimulation between them. A major part of the work detailed is the focus on what mechanisms are responsible for these changes in plasticity, with the goal of representing the mechanisms in a single learning rule. The results found can be directly compared to data previously seen by scientists who worked on in-vitro experiments. The research then goes on to look at further applications of the model, in particular, looking at certain deficits seen in people with Schizophrenia. We modify the model to include these cellular impairments, then observe how this affects the standard STDP curve and thus affects the strengthening/weakening between the two neurons

Molecular and Cellular Mechanisms Underlying Somatostatin-Based Signaling in Two Model Neural Networks, the Retina and the Hippocampus

Neural inhibition plays a key role in determining the specific computational tasks of different brain circuitries. This functional \u201cbraking\u201d activity is provided by inhibitory interneurons that use different neurochemicals for signaling. One of these substances, somatostatin, is found in several neural networks, raising questions about the significance of its widespread occurrence and usage. Here, we address this issue by analyzing the somatostatinergic system in two regions of the central nervous system, the retina and the hippocampus. By comparing the available information on these structures, we have identified common motifs in the action of somatostatin that may explain its involvement in such diverse circuitries. The emerging concept is that somatostatin-based signaling, through conserved molecular and cellular mechanisms, allows neural networks to operate correctly