25 research outputs found

    Neuronal Oscillations Enhance Stimulus Discrimination by Ensuring Action Potential Precision

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    Although oscillations in membrane potential are a prominent feature of sensory, motor, and cognitive function, their precise role in signal processing remains elusive. Here we show, using a combination of in vivo, in vitro, and theoretical approaches, that both synaptically and intrinsically generated membrane potential oscillations dramatically improve action potential (AP) precision by removing the membrane potential variance associated with jitter-accumulating trains of APs. This increased AP precision occurred irrespective of cell type and—at oscillation frequencies ranging from 3 to 65 Hz—permitted accurate discernment of up to 1,000 different stimuli. At low oscillation frequencies, stimulus discrimination showed a clear phase dependence whereby inputs arriving during the trough and the early rising phase of an oscillation cycle were most robustly discriminated. Thus, by ensuring AP precision, membrane potential oscillations dramatically enhance the discriminatory capabilities of individual neurons and networks of cells and provide one attractive explanation for their abundance in neurophysiological systems

    Spatio- temporal dynamics of odor representations in the mammalian olfactory bulb

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    We explored the spatio-temporal dynamics of odor-evoked activity in the rat and mouse main olfactory bulb (MOB) using voltage-sensitive dye imaging (VSDI) with a new probe. The high temporal resolution of VSDI revealed odor-specific sequences of glomerular activation. Increasing odor concentrations reduced response latencies, increased response amplitudes, and recruited new glomerular units. However, the sequence of glomerular activation was maintained. Furthermore, we found distributed MOB activity locked to the nasal respiration cycle. The spatial distribution of its amplitude and phase was heterogeneous and changed by sensory input in an odor-specific manner. Our data show that in the mammalian olfactory bulb, odor identity and concentration are represented by spatio-temporal patterns, rather than spatial patterns alone

    Topographic embedding of MOR18-2 in the mouse olfactory bulb

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    Poster presentation at 1st International Workshop on Odor Spaces. Mice are exceptional in their ability to capture their chemical environment, mapping the olfactory world into a basic sensory representation with over one thousand different types of chemical sensors, that is, olfactory sensory neurons (OSNs). OSNs of each type converge in the olfactory bulb onto exclusive distinct physiological areas called glomeruli. The glomeruli constitute the first relay station of olfactory stimulus representation in the mouse brain. Thus, the stimulus induced glomerular input pattern spatially embodies an important part of the sensory representation in the olfactory bulb. Still, topographic organization principles (chemotopy, tunotopy) are under debate. One reason might be that investigation are, due to experimental limitations, only performed on stimuli sets in the size of one hundred odors. But this represents only a tiny snapshot of the vast amount of molecules in the olfactory world and topographic relationships might be disguised in the incomplete representation of molecular receptive ranges (MRR). Therefore we investigated the problem with the MOR18-2 glomerulus as point of reference: First we determined it's MRR. Then, based on a measurement set covering this MRR, we elucidated the topographic embedding. It shows that MOR18-2 is embedded in a hierarchy of patchy tunotopic domains

    Hyperpolarizations Maintain AP Precision by Minimizing Membrane Potential Variance

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    <div><p>(A1) Schematic showing the experimental configuration and analysis parameters of the mitral cell membrane voltage recorded while varying the hyperpolarization period (Δt; 2 to 400 ms). AP jitter was created by injecting a depolarizing current pulse (150 to 250 pA for 100 ms) and estimated by calculating the standard deviation of the pre-AP time. The effect of the hyperpolarizing pulse on precision recovery was measured by determining the jitter of the AP immediately following the hyperpolarization pulse (post-AP) and comparing it to the control AP. The relationship between membrane potential at the beginning (Vm<sub>pre</sub>) and at the end (Vm<sub>post</sub>) was determined by calculating the mean voltage over the first 250 μs and the last 100 μs of the nonspiking interval. </p> <p>(A2) Two example traces of a 2-ms hyperpolarizing pulse with post-APs showing that depolarized (−48 mV) and hyperpolarized (−58 mV) potentials evoked early and late post-APs, respectively. The red ellipse highlights the variable membrane potential at the end of the hyperpolarizing pulse; red lines indicate the variable AP times of the post-AP that reflect post-AP jitter.</p> <p>(A3) Representative voltage traces of APs for hyperpolarization intervals of 2, 6, 24, and 80 ms show a large variation in Vm<sub>pre</sub> (see also C); traces with the earliest and the latest prehyperpolarization AP are highlighted in black. Ten overlaid traces show the reduction in the variable membrane potential across the recovery period. The associated reduction in post-AP jitter is indicated by the red bars above the clipped APs. </p> <p>(A4) Post-AP jitter as a function of the recovery interval (mean ± SEM, <i>n</i> = 4 cells). The data points were fitted with a single exponential (τ = 6.8 ms). The precision of the control AP is indicated by the dashed line. Inset: Correlation between the post-AP jitter and membrane potential variance at Vm<sub>post</sub> ( <i>R</i><sup>2</sup> = 0.86). </p> <p>(B) The correlation between Vm<sub>pre</sub> and Vm<sub>post</sub> plotted as a function of the recovery interval ( <i>n</i> = 4). The graph is overlaid by the single exponential fit shown in A4 (red line). Inset: The Vm<sub>pre</sub> and Vm<sub>post</sub> values are plotted for a 2-ms interval (filled circles) and compared to that for a 120-ms interval (open circles). </p> <p>(C) (Top) Example traces showing the relationship between the pre-AP time (relative to the pulse onset) and Vm<sub>pre</sub>. (Below) A plot of Vm<sub>pre</sub> against pre-AP time for a single cell. A single AHP trace is superimposed on the graph. </p> <p>(D1) Five consecutive traces from a mitral cell show spontaneous AP jitter relative to the same randomly chosen point in time (black) and the jitter of the AP (red) immediately following a precise AP (left). Cells were held at threshold by injecting constant current and the precise AP (pAP) was elicited by brief current injection (1,000 pA for 2 ms).</p> <p>(D2) Population data from mitral cells ( <i>n</i> = 6), pyramidal neurons ( <i>n</i> = 5), and Purkinje neurons ( <i>n</i> = 3) showing the normalized jitter of ongoing APs and the AP immediately following the injected pAP (mean ± SEM, <i>p</i> < 0.001 in all cell types). Precision recovery is similar in the three cell types. </p></div
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