Localization of brain stem motoneurons innervating the laryngeal muscles in the rufous horseshoe bat,rhinolophus rouxi

The motoneurons innervating the laryngeal muscles were localized in the rufous horseshoe bat,Rhinolophus rouxi, using the HRP method. HRP was applied to the cricothyroid muscle and to the cut end of the recurrent laryngeal nerve. Labeled motoneurons were found in two completely separated regions of the nucleus ambiguus. The motoneurons innervating the cricothyroid muscle via the superior laryngeal nerve (SLN) are located withinn the ventrolateral portion of the nucleus reaching the caudal pole of the motor nucleus of the facial nerve. The motoneurons innervating the other intrinsic laryngeal muscles via the recurrent laryngeal nerve (RLN) are situated in the caudal half of the nucleus ambiguus. The innervation is strictly homolateral

Multidimensional Characterization and Differentiation of Neurons in the Anteroventral Cochlear Nucleus

Multiple parallel auditory pathways ascend from the cochlear nucleus. It is generally accepted that the origin of these pathways are distinct groups of neurons differing in their anatomical and physiological properties. In extracellular in vivo recordings these neurons are typically classified on the basis of their peri-stimulus time histogram. In the present study we reconsider the question of classification of neurons in the anteroventral cochlear nucleus (AVCN) by taking a wider range of response properties into account. The study aims at a better understanding of the AVCN's functional organization and its significance as the source of different ascending auditory pathways. The analyses were based on 223 neurons recorded in the AVCN of the Mongolian gerbil. The range of analysed parameters encompassed spontaneous activity, frequency coding, sound level coding, as well as temporal coding. In order to categorize the unit sample without any presumptions as to the relevance of certain response parameters, hierarchical cluster analysis and additional principal component analysis were employed which both allow a classification on the basis of a multitude of parameters simultaneously. Even with the presently considered wider range of parameters, high number of neurons and more advanced analytical methods, no clear boundaries emerged which would separate the neurons based on their physiology. At the current resolution of the analysis, we therefore conclude that the AVCN units more likely constitute a multi-dimensional continuum with different physiological characteristics manifested at different poles. However, more complex stimuli could be useful to uncover physiological differences in future studies

Cluster analyses based on a restricted set of parameters.

<p>See text for the reasons of the restriction. The parameter considered are indicated in B. Design of the graphs is the same as in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0029965#pone-0029965-g006" target="_blank">figure 6</a>. <b>A</b>: The present cluster analysis suggests a distinction of four clusters (a–d) with <b>B</b>: specific properties. Note that there is some correspondence between this restricted analysis and the analysis given in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0029965#pone-0029965-g006" target="_blank">figure 6:</a> Cluster ‘a’ relates to cluster V; ‘b’ to I, ‘c’ to II, and ‘d’ to IV. <b>C</b>: The principal component analysis arranges the units in one big coherent cluster. Units establishing different clusters (<b>C1</b>) and different PSTH types (<b>C2</b>) still could not be separated.</p

Physiological response properties of different PSTH groups in AVCN.

<p>abbreviations explained in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0029965#s2" target="_blank">methods</a>.</p><p>categorical values are described in text.</p>a<p>Means ± S.D./Median (25%, 75%).</p>b<p>PSTH groups that do not significantly differ are within one parentheses.</p

Principal component analysis employing three principal components and recheck of PSTH classification.

<p>Same sample of units (n = 174) and analysis as in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0029965#pone-0029965-g007" target="_blank">figure 7</a>. <b>A1</b>: Principal component analysis with assignment of the units to the different clusters gathered from hierarchical cluster analysis. <b>A2</b>: Principal component analysis with assignment of the units to the different PSTH types. Note that even a visualization based on the three dominant principal components does not indicate a clear separation of unit types. <b>B</b>: PSTHs of units in regions of the plot which are mainly occupied by other PSTH types, i.e. a PL_N (<b>B1</b>), a C_S (<b>B2</b>) and a unit which is not unambiguously to classify (<b>B3</b>). This unit was classified as C_T, but it could also be a PL.</p

Physiological response properties of different clusters of AVCN units according to hierarchical cluster analysis using all evaluated properties.

<p>abbreviations explained in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0029965#s2" target="_blank">methods</a>.</p><p>categorical values are described in text.</p>a<p>Means ± S.D./Median (25%, 75%).</p>b<p>cluster that do not significantly differ are within one parentheses.</p

Responses to SAM.

<p>Synchronization indices (left column) and entrainment (right column) as a function of modulation frequency for the different PSTH types. The respective bottommost plots show the average transfer functions for each PSTH type. The horizontal line indicates the 0.3 cut-off criterion that was chosen to classify responses as being phase-locked. Note that C_S units show best and PL units worst ability to comodulate with fast fluctuations in stimulus amplitude.</p

Waveform analysis.

<p><b>A1–A4</b>: Averaged and normalized waveforms of single units sorted according to their PSTH types (numbers of units indicated in the graphs). The inset in A1 shows the mean waveform of the action potentials (black line, grey lines: S.D.) of a PL unit displaying the presynaptic component P and the two postsynaptic components ‘A’ and ‘B’. <b>B1</b>: Normalized average waveforms of all units of the respective PSTH types. <b>C1</b>: Signal-to-noise ratio and <b>C2</b>: duration from the maximum to the minimum of the waveforms of the respective PSTH types. Each symbol represents the value of a single AVCN unit. Significant differences (p≤0.05) between PSTH types are indicated with asterisks.</p

Cluster analyses considering all evaluated response properties.

<p><b>A</b>: Dendrogram illustrating the result of hierarchical cluster analysis. The units (n = 233) are lined up at the bottom of the graph. The analysis suggests five clusters characterized by a specific distribution of parameter values. <b>B</b>: Mean of the respective parameter values for each property in the resulted clusters I–V. The values are standardized and normalized to the respective maxima (for original data and statistical analyses see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0029965#pone-0029965-t002" target="_blank">table 2</a>). Note that for almost all individual properties significant differences exist between the clusters, and some properties also correlated across clusters. <b>C</b>: However, principal component analysis gives no indication for clearly separated groups of units, neither for the different clusters gathered from hierarchical cluster analysis (<b>C1</b>) nor for the different PSTH types (<b>C2</b>). In both cases units establishing different groups tend to accumulate in different regions of the plot. Still, the different groups strongly overlap, especially in the centre of the plot. Thus, with respect to their physiological properties the AVCN neurons form a continuum rather than distinct groups.</p