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The pedunculopontine nucleus (PPN) and the subthalamic nucleus (STN) are reciprocally connected by excitatory projections. In the 6-hydroxydopamine (6-OHDA) rat model the PPN was found to be hyperactive. Similarly, the STN and the substantia nigra pars reticulata (SNr) showed increased activity in Parkinson's disease (PD) animal models. A lesion of the STN was shown to restore increased activity levels in the SNr of 6-OHDA-treated rats. As the STN and the PPN were reciprocally connected by excitatory projections and both structures were shown to be hyperactive in PD animal models, the present study was performed in order to investigate the changes in neuronal activity of the STN and SNr under urethane anesthesia after unilateral ibotenic acid lesioning of the PPN in animals with previous unilateral 6-OHDA lesions of the substantia nigra pars compacta (SNc). The firing rate of STN neurons significantly increased from 10.3 +/- 0.6 spikes/s (mean +/- SEM) to 17.8 +/- 1.8 spikes/s after SNc lesion and returned to normal levels of 10.8 +/- 0.7 spikes/s after additional lesion of the PPN. Similarly, the firing rate of SNr neurons significantly increased from 19.0 +/- 1.1 to 25.9 +/- 1.4 spikes/s after SNc lesion, the hyperactivity being reversed after additional PPN lesion to 16.8 +/- 1.2 spikes/s. The reversal of STN and SNr hyperactivity of 6-OHDA-treated rats by additional PPN lesion suggests an important modulatory influence of the PPN on STN activity. Moreover, these findings could indicate a new therapeutic strategy in PD by interventional modulation of the PPN.

Nanocrystalline graphite/graphene (NCG) has been studied well before graphene was successfully produced in 2004. Despite the fact that NCG thin films cannot reach the high performance of large‐area graphene in some of its properties, they are able to provide significant benefits for various applications, besides being easier to produce and integrate into devices with current processing technologies. We present here, a comprehensive account of the large variety of synthesis methods, as well as of the already large range of potential applications for NCG thin films.

The inversion procedure presented in this paper is based on the statistical regression of the inverse map between the spaces of ECT scan data, and of crack parameters. The mapping is realized by a combination between a statistical data processing step, i.e., a principal component transformation of the scan data, and an incremental resolution neural network training. Starting from the necessities of improving the detrimental conditioning of the regression and of providing the inversion approach with enhanced potential for automation, a novel "shifting aperture" mapping concept and a data fusion technique are proposed. Supplementing the primary mapping algorithm with these latter processing steps allows one to avoid the usual anomalous-region focusing approach and improves the inversion capabilities by allowing a dynamic reconstruction of the object's profile. Unconnected and multiply connected crack shapes are well estimated, that so far eluded most other inversion methods. For this primary validation of the completed algorithm, only synthetic B-scan data are used, which are collected by an optimized, high performance sensor on the interior of a metal tube.

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