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Intraoperative neuromonitoring is without doubt important for all surgical interventions, where nerve structures are at risk. Mapping techniques for the identification of motor nerves and cortex are available. They rely on manual identification using an electrical stimulation probe. A landmark-based visualization of the results is currently not possible. To overcome these limitations, we are developing a system for automatic stimulation and display of functional tissue. Infrared neurostimulation (INS) was proposed to be a feasible alternative to electrical stimulation of nerves. It provides contactless and artifact-free activation of nerves. For our preclinical experiments we used an infrared diode laser system with a wavelength of 1470 nm. For automatic screening, we developed a scanning system and suitable scan-algorithms in order to provide optimal scanning parameters. Recording of compound muscle action potentials (CMAP) was performed with a differential amplifier and appropriate neurophysiologic software. Subunits of the system were combined via multiple interfaces. A control-software merges all relevant functions of the individual parts and parallel use. Marking of tissue was realized with a red pilot laser deflected by the same scanning system. With this work we could show, that a system for automatic laser deflection with parallel neurophysiologic recording and subsequent highlighting of irradiated tissue is possible. This system can serve as a tool for further systematic investigations in the field of INS.

Glioblastoma, an aggressive malign tumor of the brain, is one of the most shattering diagnoses due to its very poor prognosis and limited treatment options. These options mainly consist of surgical or radiation therapeutic removal of as much tumor mass as possible, which unfortunately is almost always incomplete. Even worse, chemotherapy is of little use, as the special setup of the brain′s vessels severely limits the transit into the parenchyma of elsewhere efficient cytostatica. This Blood-Brain-Barrier (BBB) is for quite some time the target of sophisticated and nano-particle based transport mechanisms, however it is reported, that a boost of permeability for most of the brain can be achieved based on moderate temperature increase. One means to locally and reversibly increase the brain′s temperature and thus potentially opening the BBB may be achieved by illuminating the skull with infrared laser light, thus causing punctual heating and heat diffusion into the cortex. In extension of the common laser light guiding by glass fibres, we use a micro-positioned simple optics to focus a 1470 nm laser beam of approximately 500 µm in diameter on the skull. The apparent opening of the BBB is evidenced by the localized spread of Evans Blue injected into the tail vein of said rat, binding to Albumin (64,6 kDa) in the body. This marker molecule is usually blocked from passing through the intact BBB, but under IR illumination for half a minute, it appeared in post mortem visible blobs. Temperature profiles and potential tissue damage are now under investigation by high speed thermal camera and post mortem histology.

This work investigates the performance of eventsynchronous noise cancelling algorithms to separate ECG artifacts from thoracic EMG recordings. In focus are the precise detection of heart beats, the exact time alignment of the QRS segments and the construction of a template QRS signal. Among the utilized methods is a modified structural intensity (SI) approach based on the observation of extrema in low pass filtered versions of the second derivative as a detector. An adoption of this approach is also used to obtain the exact time alignment of QRS segments. Artificial test signals are constructed based on addition of ECG and sEMG with different magnitudes. We show that approaches based on the observation of extrema in different scales yield superior results.

Flexible polyimide probes, used for neuronal signal acquisition, are thought to reduce signal deteriorating gliosis, improving the quality of recordings in brain machine interfacing applications. These probes suffer from the disadvantage that they cannot penetrate brain tissue on their own, owing to their limited stiffness and low buckling forces. A microfluidic device as an external micro-drive which aids in the insertion of flexible polyimide neural probes in 0.6% Agarose gel is presented here.

Deep brain stimulation (DBS) is based on the effect of high frequency stimulation (HFS) in neuronal tissue. As a therapy option for patients suffering from e.g. Parkinson’s disease, DBS has been used for decades. Despite the widespread use, the effect of HFS on neurons is not fully investigated. Improving the stimulation efficiency und specificity could increase the efficiency of the INS (internal neuronal stimulator) as well as potentially reduce unwanted side effects. The effect of HFS on the GABAergic system was quantified using whole cell patch clamp electrophysiology during HFS stimulation in cortical human brain slices in vitro. Rectangular, sine, sawtooth and triangular waveforms were applied extracellularly. Since HFS has been hypothesized to increase the activity of the axons of GABAergic interneurons, a decrease in activity can be observed in the pyramidal cells that the interneurons project to. By isolating the incoming non- GABAergic events, we can filter out only the GABAA currents which can be verified using a GABAA antagonist. The results show that all the waveforms effectively increase the GABAA currents. The triangle waveform causes the highest significant increase in the activity which further increases over time after the stimulation was turned off.

Animal models are an essential testbed for new devices on their path from the bench to the patient. Potential impairments by brain stimulation are often investigated in water mazes to study spatial memory and learning. Video camera based tracking systems exist to quantify rodent behaviour, but reflections of ambient lighting on the water surface and artefacts due to the waves caused by the swimming animal cause errors. This often requires tweaking of algorithms and parameters, or even potentially modifying the lab setup. In the following, we provide a simple solution to alleviate these problem using a combination of region based tracking and independent multimodal background subtraction (IMBS) without hav ing to tweak a plethora of parameters.

This study investigated the effects different sampling rates may produce on the quality of muscle fatigue detection algorithms. sEMG signals were obtained from isometric contractions of the arm. Subsampled signals resulting in technically relevant sampling rates were computationally deduced from the original recordings. The spectral based fatigue recognition methods mean and median frequency as well as spectral moment ratio were included in this investigation, as well as the sample and the fuzzy approximate entropy. The resulting fatigue indices were evaluated with respect to noise and separability of different load levels. We concluded that the spectral moment ratio provides the best results in fatigue detection over a wide range of sampling rates.

Near-infrared spectroscopy (NIRS) is a promising research tool that found its way into the field of brain-computer interfacing (BCI). BCI is crucially dependent on maximized usability thus demanding lightweight, compact, and low-cost hardware. We designed, built, and validated a hybrid BCI system incorporating one optical and two electrical modalities ameliorating usability issues. The novel hardware consisted of a NIRS device integrated with an electroencephalography (EEG) system that used two different types of electrodes: Regular gelled gold disk electrodes and tri-polar concentric ring electrodes (TCRE). BCI experiments with 16 volunteers implemented a two-dimensional motor imagery paradigm in off- and online sessions. Various non-canonical signal processing methods were used to extract and classify useful features from EEG, tEEG (EEG through TCRE electrodes), and NIRS. Our analysis demonstrated evidence of improvement in classification accuracy when using the TCRE electrodes compared to disk electrodes and the NIRS system. Based on our synchronous hybrid recording system, we could show that the combination of NIRS-EEG-tEEG performed significantly better than either single modality only. [ABSTRACT FROM AUTHOR]