Band 59, Heft 4 - Special Issue: Neuroprobes / Guest Editor: Thomas Stieglitz, Herc Neves and Patrick Ruther

One of the fundamental challenges in behavioral neurophysiology in awake animals is the steady recording of action potentials of many single neurons for as long as possible. Here, we present single neuron data obtained during acute recordings mainly from premotor cortices of three macaque monkeys using a silicon-based linear multielectrode array. The most important aspect of these probes, compared with similar models commercially available, is that, once inserted into the brain using a dedicated insertion device providing an intermediate probe fixation by means of vacuum, they can be released and left floating in the brain. On the basis of our data, these features appear to provide (i) optimal physiological conditions for extracellular recordings, (ii) good or even excellent signal-to-noise ratio depending on the recorded brain area and cortical layer, and (iii) extreme stability of the signal over relatively long periods. The quality of the recorded signal did not change significantly after several penetrations into the same restricted cortical sector, suggesting limited tissue damage due to probe insertion. These results indicate that these probes offer several advantages for acute neurophysiological experiments in awake monkeys, and suggest the possibility to employ them for semichronic or even chronic studies.

In this article, we evaluated the electrophysiological performance of a novel, high-complexity silicon probe array. This brain-implantable probe implements a dynamically reconfigurable voltage-recording device, coordinating large numbers of electronically switchable recording sites, referred to as electronic depth control (EDC). Our results show the potential of the EDC devices to record good-quality local field potentials, and single- and multiple-unit activities in cortical regions during pharmacologically induced cortical slow wave activity in an animal model.

Intracortical microprobes allow the precise monitoring of electrical and chemical signaling and are widely used in neuroscience. Microelectromechanical system (MEMS) technologies have greatly enhanced the integration of multifunctional probes by facilitating the combination of multiple recording electrodes and drug delivery channels in a single probe. Depending on the neuroscientific application, various assembly strategies are required in addition to the microprobe fabrication itself. This paper summarizes recent advances in the fabrication and assembly of micromachined silicon probes for drug delivery achieved within the EU-funded research project NeuroProbes . The described fabrication process combines a two-wafer silicon bonding process with deep reactive ion etching, wafer grinding, and thin film patterning and offers a maximum in design flexibility. By applying this process, three general comb-like microprobe designs featuring up to four 8-mm-long shafts, cross sections from 150×200 to 250×250 µm², and different electrode and fluidic channel configurations are realized. Furthermore, we discuss the development and application of different probe assemblies for acute, semichronic, and chronic applications, including comb and array assemblies, floating microprobe arrays, as well as the complete drug delivery system NeuroMedicator for small animal research.

A miniature device enabling parallel in vivo detection of the neurotransmitter choline in multiple brain regions of freely behaving rodents is presented. This is achieved by combining a biosensor microprobe array with a custom-developed CMOS chip. Each silicon microprobe comprises multiple platinum electrodes that are coated with an enzymatic membrane and a permselective layer for selective detection of choline. The biosensors, based on the principle of amperometric detection, exhibit a sensitivity of 157±35 µA m M -1 cm -2 , a limit of detection of below 1 µ M, and a response time in the range of 1 s. With on-chip digitalization and multiplexing, parallel recordings can be performed at a high signal-to-noise ratio with minimal space requirements and with substantial reduction of external signal interference. The layout of the integrated circuitry allows for versatile configuration of the current range and can, therefore, also be used for functionalization of the electrodes before use. The result is a compact, highly integrated system, very convenient for on-site measurements.

Neural probes are complex devices consisting of metallic (often Pt based) electrodes, spread over an insolating/dielectric backbone. Their functionality is often limited in time because of the formation of scaring tissues around the implantation tracks. Functionalization of the probes surface can be used to limit the glial scar reaction. This is however challenging, as this treatment has to be equally efficient on all probe surfaces (metallic as well as dielectric) and should not influence the electrodes performances. This paper presents a novel technique to functionalize recording neural probes with hyaluronic acid (HyA), a major component of the extracellular matrix (ECM). HyA and the probe surface are both modified to make the reaction feasible: HyA is chemically functionalized with SS-pyridine groups while the probe surfaces are silanized. The thiol groups thus introduced on the probe surface can then react with the HyA SS-pyridine group, resulting in a covalent bonding of the latter on the former. The electrodes are protected by introducing a pretreatment step, namely an additional hyaluronic acid layer on the platinum electrode, prior to the silanization process, which was found to be effective in reducing electrode impedance under optimized conditions.

Recently developed CMOS-based microprobes contain hundreds of electrodes on a single shaft with interelectrode distances as small as 30 µm. So far, neuroscientists manually select a subset of those electrodes depending on their appraisal of the “usefulness” of the recorded signals, which makes the process subjective but more importantly too time consuming to be useable in practice. The ever-increasing number of recording electrodes on microelectrode probes calls for an automated selection of electrodes containing “good quality signals” or “signals of interest.” This article reviews the different criteria for electrode selection as well as the basic signal processing steps to prepare the data to compute those criteria. We discuss three of them. The first two select the electrodes based on “signal quality.” The first criterion computes the penalized signal-to-noise ratio (SNR); the second criterion models the neuroscientist’s appraisal of signal quality. Last, our most recent work allows the selection of electrodes that capture particular anatomical cell types. The discussed algorithms perform what is called in the literature “electronic depth control” in contrast to the mechanical repositioning of the electrode shafts in search of “good quality signals” or “signals of interest.”

The proper setting of support ventilation aims to follow the patients’ demands, ensuring adequate assistance to their respiratory effort. Effort assessment is thus necessary. But invasive procedures like measuring transdiaphragmatic pressure (Pdi) are impractical in long-term ventilation. Our purpose was therefore the development of the Occlusion+Delta (O+D) method for non-invasive continuous assessment of effort, quantified by the inspiratory pressure-time-product (PTPinsp), during ventilatory support. Flow and airway pressure were measured from 25 healthy volunteers at three effort levels. For the non-invasive method, short expiratory occlusions were executed each three to seven cycles to estimate resistance and compliance with a fitting algorithm fed with the differences between occluded and undisturbed cycles. Signals and estimates were then used to calculate the effort. For the validation of O+D, its estimations were compared to the results from invasive measurement of Pdi using balloon catheters. The agreement between PTPinsp from the invasive measurement and the proposed alternative was confirmed by regression analysis (PTP O+D =1.13PTP Pdi - 0.85, R²=0.84) and calculation of their differences (mean±SD=1.78±7.18 cm H 2 O s). Repeated execution of the non-invasive O+D method facilitates a safe automatic assessment of respiratory mechanics and breathing effort, promoting the rapid recognition of changes in patient’s demands and the adaptation of support.

An innovative concept for synchronization analysis between heart rate (HR) components and rhythms in EEG envelopes is represented; it applies time-variant analyses to heart rate variability (HRV) and EEG, and it was tested in children with temporal lobe epilepsy (TLE). After a removal of ocular and movement-related artifacts, EEG band activity was computed by means of the frequency-selective Hilbert transform providing envelopes of frequency bands. Synchronization between HRV and EEG envelopes was quantified by Morlet wavelet coherence. A surrogate data approach was adapted to test for statistical significance of time-variant coherences. Using this processing scheme, significant coherence values between a HRV low-frequency sub-band (0.08–0.12 Hz) and the EEG δ envelope (1.5–4 Hz) occurring both in the preictal and early postictal periods of a seizure can be shown. Investigations were performed for all electrodes at 20-s intervals and for selected electrode pairs (T3÷C3, T4÷C4) in a time-variant mode. Synchronization was more pronounced in the group of right hemispheric TLE patients than in the left hemispheric group. Such a group-specific augmentation of synchronization confirms the hypothesis of a right hemispheric lateralization of sympathetic cardiac control of the low-frequency HRV components.

This work presents a new automated system to detect circinate exudates in retina digital images. It operates as follows: the true color image is converted to gray levels, and contrast-limited adaptive histogram equalization (CLAHE) is applied to it before undergoing empirical mode decomposition (EMD) as intrinsic mode functions (IMFs). The entropies and uniformities of the first two IMFs are then computed to form a feature vector that is fed to a support vector machine (SVM) for classification. The experimental results using a set of 45 images (23 normal images and 22 images with circinate exudates taken from the STARE database) and tenfold cross-validation indicate that the proposed approach outperforms previous works found in the literature, with perfect classification. In addition, the image processing time was <4 min, making the presented circinate exudate detection system fit for use in a clinical environment.