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A preponderance of brain–computer interface (BCI) publications proposing artificial neural networks for motor imagery (MI) electroencephalography (EEG) signal classification utilize one of the BCI Competition datasets. However, these databases encompass MI EEG data from a limited number of subjects, typically less than or equal to 10. Furthermore, the algorithms usually include only bandpass filtering as a means of reducing noise and increasing signal quality. In this study, we conducted a comparative analysis of five renowned neural networks (Shallow ConvNet, Deep ConvNet, EEGNet, EEGNet Fusion, and MI-EEGNet) utilizing open-access databases with a larger subject pool in conjunction with the BCI Competition IV 2a dataset to obtain statistically significant results. We employed the FASTER algorithm to eliminate artifacts from the EEG as a signal processing step and explored the potential for transfer learning to enhance classification results on artifact-filtered data. Our objective was to rank the neural networks; hence, in addition to classification accuracy, we introduced two supplementary metrics: accuracy improvement from chance level and the effect of transfer learning. The former is applicable to databases with varying numbers of classes, while the latter can underscore neural networks with robust generalization capabilities. Our metrics indicated that researchers should not disregard Shallow ConvNet and Deep ConvNet as they can outperform later published members of the EEGNet family.

This paper describes the development of PlatypOUs - an open-source electromyography (EMG)-controlled mobile robot platform that uses the MindRove Brain Computer Interface (BCI) headset as signal acquisition unit, implementing remote control. Simultaneously with the physical mobile robot, simulation environment is also prepared using Gazebo, within the Robot Operating System (ROS) framework, with the same capabilities as the physical device, from the point of view of the ROS. The purpose of the PlatypOUs project is to create a tool for STEM-based education, and it involves two major disciplines: mobile robotics and machine learning, with several sub-areas included in each. The use of the platform and the simulation environment exposes students to hands-on laboratory sessions, which contribute to their progression as engineers. An important feature of our project is that the platform is made up of open-source and easily available commercial hardware and software components. In this paper, an electromyography (EMG) based controller has been developed using support vector machine (SVM) based classification for robot control purposes.

One of the leading tourism products of Hungary is health tourism, where the certain supply segments are influenced by seasonality in different scales. The primary aim of our paper is to survey the seasonality of the 9 spas with the greatest turnover in Hungary with the help of the Gini index. Our research intends to provide an actual picture about the exact measure of seasonality in the highlighted spas of Hungary, due to the overall actuality of the problem and also because no such relevant quantitative research has been dealing with this issue in Hungary yet. The objective reason why these spas were chosen and surveyed is because first of all they are mono profile health tourism centres, where tourists are visiting the settlement exclusively because of the spas, and on the other hand the visitor turnover of the mentioned settlements are significantly higher than the following Hungarian spa towns. We believe that the more we understand seasonality the more we can face with its challenges concerning tourism development. For our seasonality analysis we used the commercial accommodation statistics of the Hungarian Central Statistical Office and to estimate the Gini index we applied the monthly dataset of the guest nights.

Objective. The growing number of recording sites of silicon-based probes means that an increasing amount of neural cell activities can be recorded simultaneously, facilitating the investigation of underlying complex neural dynamics. In order to overcome the challenges generated by the increasing number of channels, highly automated signal processing tools are needed. Our goal was to build a spike sorting model that can perform as well as offline solutions while maintaining high efficiency, enabling high-performance online sorting. Approach. In this paper we present ELVISort, a deep learning method that combines the detection and clustering of different action potentials in an end-to-end fashion. Main results. The performance of ELVISort is comparable with other spike sorting methods that use manual or semi-manual techniques, while exceeding the methods which use an automatic approach: ELVISort has been tested on three independent datasets and yielded average F1 scores of 0.96, 0.82 and 0.81, which comparable with the results of state-of-the-art algorithms on the same data. We show that despite the good performance, ELVISort is capable to process data in real-time: the time it needs to execute the necessary computations for a sample of given length is only 1/15.71 of its actual duration (i.e. the sampling time multiplied by the number of the sampling points). Significance. ELVISort, because of its end-to-end nature, can exploit the massively parallel processing capabilities of GPUs via deep learning frameworks by processing multiple batches in parallel, with the potential to be used on other cutting-edge AI-specific hardware such as TPUs, enabling the development of integrated, portable and real-time spike sorting systems with similar performance to offline sorters.

Classification of electroencephalography (EEG) signals is a fundamental issue of Brain Computer Interface (BCI) systems, and deep learning techniques are still under investigation although they are dominant in other fields like computer vision and natural language processing. In this paper, we introduce the chessboard image transformation method in which the motor imagery EEG signals were transformed into images in order to be classified using a hybrid deep learning model. The EEG motor movement/imagery Physionet dataset was used and the Motor Imagery (MI) signals for two frequency bands (Mu [8–13 Hz] and Beta [13–30 Hz]) were transformed into 2-channel images (one channel for each band). The network model consists of Deep Convolutional Neural Network (DCNN) to extract the spatial and frequency features followed by Long Short Term Memory (LSTM) to extract temporal features and then finally to be classified into 5 different classes (4 motor imagery tasks and one rest). The results were promising with 68.72% classification accuracy for the chessboard approach compared to 68.13% for the azimuthal projection with Clough-Tocher interpolation (2-bands scenario) and to 64.64% average accuracy for a baseline method, i.e., Support Vector Machine (SVM).

The use of SU-8 material in the production of neural sensors has grown recently. Despite its widespread application, a detailed systematic quantitative analysis concerning its biocompatibility in the central nervous system is lacking. In this immunohistochemical study, we quantified the neuronal preservation and the severity of astrogliosis around SU-8 devices implanted in the neocortex of rats, after a 2 months survival. We found that the density of neurons significantly decreased up to a distance of 20 μm from the implant, with an averaged density decrease to 24 ± 28% of the control. At 20 to 40 μm distance from the implant, the majority of the neurons was preserved (74 ± 39% of the control) and starting from 40 μm distance from the implant, the neuron density was control-like. The density of synaptic contacts – examined at the electron microscopic level – decreased in the close vicinity of the implant, but it recovered to the control level as close as 24 μm from the implant track. The intensity of the astroglial staining significantly increased compared to the control region, up to 560 μm and 480 μm distance from the track in the superficial and deep layers of the neocortex, respectively. Electron microscopic examination revealed that the thickness of the glial scar was around 5–10 μm thin, and the ratio of glial processes in the neuropil was not more than 16% up to a distance of 12 μm from the implant. Our data suggest that neuronal survival is affected only in a very small area around the implant. The glial scar surrounding the implant is thin, and the presence of glial elements is low in the neuropil, although the signs of astrogliosis could be observed up to about 500 μm from the track. Subsequently, the biocompatibility of the SU-8 material is high. Due to its low cost fabrication and more flexible nature, SU-8 based devices may offer a promising approach to experimental and clinical applications in the future.

Objective The extraction and identification of single-unit activities in intracortically recorded electric signals have a key role in basic neuroscience, but also in applied fields, like in the development of high-accuracy brain-computer interfaces. The purpose of this paper is to present our current results on the detection, classification and prediction of neural activities based on multichannel action potential recordings. Approach Throughout our investigations, a deep learning approach utilizing convolutional neural networks and a combination of recurrent and convolutional neural networks was applied, with the latter used in case of spike detection and the former used for cases of sorting and predicting spiking activities. Main results In our experience, the algorithms applied prove to be useful in accomplishing the tasks mentioned above: our detector could reach an average recall of 69%, while we achieved an average accuracy of 89% in classifying activities produced by more than 20 distinct neurons. Significance Our findings support the concept of creating real-time, high-accuracy action potential based BCIs in the future, providing a flexible and robust algorithmic background for further development.

The simultaneous utilization of electrophysiological recordings and two-photon imaging allows the observation of neural activity in a high temporal and spatial resolution at the same time. The three dimensional monitoring of morphological features near the microelectrode array makes the observation more precise and complex. In vitro experiments were performed on mice neocortical slices expressing the GCaMP6 genetically encoded calcium indicator for monitoring the neural activity with two-photon microscopy around the implanted microelectrodes. A special filtering algorithm was used for data analysis to eliminate the artefacts caused by the imaging laser. Utilization of a special filtering algorithm allowed us to detect and sort single unit activities from simultaneous two-photon imaging and electrophysiological measurement.

Softening neural implants that change their elastic modulus under physiological conditions are promising candidates to mitigate neuroinflammatory response due to the reduced mechanical mismatch between the artificial interface and the brain tissue. Intracortical neural probes have been used to demonstrate the viability of this material engineering approach. In our paper, we present a robust technology of softening neural microelectrode and demonstrate its recording performance in the hippocampus of rat subjects. The 5 mm long, single shank, multi-channel probes are composed of a custom thiol-ene/acrylate thermoset polymer substrate, and were micromachined by standard MEMS processes. A special packaging technique is also developed, which guarantees the stable functionality and longevity of the device, which were tested under in vitro conditions prior to animal studies. The 60 micron thick device was successfully implanted to 4.5 mm deep in the hippocampus without the aid of any insertion shuttle. Spike amplitudes of 84 µV peak-to-peak and signal-to-noise ratio of 6.24 were achieved in acute experiments. Our study demonstrates that softening neural probes may be used to investigate deep layers of the rat brain.

Neural probes designed for extracellular recording of brain electrical activity are traditionally implanted with an insertion speed between 1 µm/s and 1 mm/s into the brain tissue. Although the physical effects of insertion speed on the tissue are well studied, there is a lack of research investigating how the quality of the acquired electrophysiological signal depends on the speed of probe insertion. In this study, we used four different insertion speeds (0.002 mm/s, 0.02 mm/s, 0.1 mm/s, 1 mm/s) to implant high-density silicon probes into deep layers of the somatosensory cortex of ketamine/xylazine anesthetized rats. After implantation, various qualitative and quantitative properties of the recorded cortical activity were compared across different speeds in an acute manner. Our results demonstrate that after the slowest insertion both the signal-to-noise ratio and the number of separable single units were significantly higher compared with those measured after inserting probes at faster speeds. Furthermore, the amplitude of recorded spikes as well as the quality of single unit clusters showed similar speed-dependent differences. Post hoc quantification of the neuronal density around the probe track showed a significantly higher number of NeuN-labelled cells after the slowest insertion compared with the fastest insertion. Our findings suggest that advancing rigid probes slowly (~1 µm/s) into the brain tissue might result in less tissue damage, and thus in neuronal recordings of improved quality compared with measurements obtained after inserting probes with higher speeds.

In neuroscience the use of a microelectrode array allows the detection of neuroelectric signals with high temporal resolution in a confined space within the tissue, while two-photon laser scanning microscopy provides high spatial resolution in a wide region of interest. The combination of these two techniques promises better understanding of the operation of neural pathways. To facilitate this connection, we studied the direct electrochemical deposition of the conductive polymer poly-2,3-ethylenedioxy-thiophene onto different Pt and Pt/Ir electrode surfaces from non-aqueous solvents, such as ionic liquid and propylene carbonate. We show the effects of electrochemical deposition technique (pulsed or continuous), monomer concentration range and solvent electrolyte type on the formation of photoluminescent - conductive films. For these variables we determined the optimal deposition parameters given as 0.025–0.050 M EDOT monomer concentration in BMIMBF4 ionic liquid and the use of pulsed deposition process to form an adherent, uniform functional electrode coating.

This paper presents the results of in vivo local release of a neuronal tracer, biotinylated dextran amine (BDA) in the rat somatosensory cortex using monolithically integrated microfluidic channel of a silicon neural microelectrode. The tracer injection is controlled by iontophoresis using Pt electrodes in the vicinity of the outlet of the microfluidic channel. Using 3–5 μA, 5–7 s on/off cycle and 15–20 min total injection time the localized injection resulted in clear anterograde and retrograde BDA labeling both within the cortex and in subcortical structures. Anterograde and retrograde labeling revealed the fine details of neuronal processes including dendritic spines and axon terminal-like endings. Injection sites appeared clear lacking any strong diffuse background labeling. Electrophysiological recording performed with the same microdevice immediately after the iontophoresis indicated normal cortical functioning. The results prove that the combination of in vivo multichannel neural recording and controlled tracer injection using a single implanted microdevice is feasible, and therefore it can be a powerful tool for studying the connectome of the brain.

It is an uninformative truism to state that the brain operates at multiple spatial and temporal scales, each with each own set of emergent phenomena. More worthy of attention is the point that our current understanding of it cannot clearly indicate which of these phenomenological scales are the significant contributors to the brain’s function and primary output (i.e. behaviour). Apart from the sheer complexity of the problem, a major contributing factor to this state of affairs is the lack of instrumentation that can simultaneously address these multiple scales without causing function altering damages to the underlying tissue. One important facet of this problem is that standard neural recording devices normally require one output connection per electrode. This limits the number of electrodes that can fit along the thin shafts of implantable probes generating a limiting balance between density and spread. Sharing a single output connection between multiple electrodes relaxes this constraint and permits designs of ultra-high density probes.Here we report the design and in-vivo validation of such a device, a complementary metal-oxide-semiconductor (CMOS) scanning probe with 1344 electrodes; the outcome of the European research project NeuroSeeker. We show that this design targets both local and global spatial scales by allowing the simultaneous recording of more than 1000 neurons spanning 7 functional regions with a single shaft. The neurons show similar recording longevity and signal to noise ratio to passive probes of comparable size and no adverse effects in awake or anesthetized animals. Addressing the data management of this device we also present novel visualization and monitoring methods. Using the probe with freely moving animals we show how accessing a number of cortical and subcortical brain regions offers a novel perspective on how the brain operates around salient behavioural events. Finally, we compare this probe with lower density, non CMOS designs (which have to adhere to the one electrode per output line rule). We show that an increase in density results in capturing neural firing patterns, undetectable by lower density devices, which correlate to self-similar structures inherent in complex naturalistic behaviour.To help design electrode configurations for future, even higher density, CMOS probes, recordings from many different brain regions were obtained with an ultra-dense passive probe.

Objective. Exploring neural activity behind synchronization and time locking in brain circuits is one of the most important tasks in neuroscience. Our goal was to design and characterize a microelectrode array (MEA) system specifically for obtaining in vivo extracellular recordings from three deep-brain areas of freely moving rats, simultaneously. The target areas, the deep mesencephalic reticular-, pedunculopontine tegmental- and pontine reticular nuclei are related to the regulation of sleep-wake cycles. Approach. The three targeted nuclei are collinear, therefore a single-shank MEA was designed in order to contact them. The silicon-based device was equipped with 3*4 recording sites, located according to the geometry of the brain regions. Furthermore, a microdrive was developed to allow fine actuation and post-implantation relocation of the probe. The probe was attached to a rigid printed circuit board, which was fastened to the microdrive. A flexible cable was designed in order to provide not only electronic connection between the probe and the amplifier system, but sufficient freedom for the movements of the probe as well. Main results. The microdrive was stable enough to allow precise electrode targeting into the tissue via a single track. The microelectrodes on the probe were suitable for recording neural activity from the three targeted brainstem areas. Significance. The system offers a robust solution to provide long-term interface between an array of precisely defined microelectrodes and deep-brain areas of a behaving rodent. The microdrive allowed us to fine-tune the probe location and easily scan through the regions of interest.

The advanced technology of microelectromechanical systems (MEMS) makes possible precise and reproducible construction of various microelectrode arrays (MEAs) with patterns of high spatial density. Polymer-based MEMS devices are gaining increasing attention in the field of electrophysiology, since they can be used to form flexible, yet reliable electrical interfaces with the central and the peripheral nervous system. In this paper we present a novel MEA, designed for obtaining neural signals, with a polyimide (PI)--platinum (Pt)--SU-8 layer structure. Electrodes with special, arrow-like shapes were formed in a single row, enabling slight penetration into the tissue. The applied process flow allowed reproducible batch fabrication of the devices with high yield. In vitro characterization of the electrode arrays was performed with electrochemical impedance spectroscopy in lactated Ringer's solution. Functional tests were carried out by performing acute recordings on rat neocortex. The devices have proven to be convenient tools for acute in vivo electrocorticography.

Aims In this study, we introduce an edge-type laminar silicon probe suitable for improved cell accessibility during in vitro brain slice recordings. With protruding contact sites, the spiky probe provides high signal yield and quality while approaching cells located deeper in the tissue. Methods. The spiky probe comprises an angled shank carrying 32 protruding contact sites with three possible spacing of 25 μm, 50 μm and 100 μm. The angled shank makes the probe compatible with large microscope objectives used typically in two-photon imaging, in vitro. Spiky probes were batch manufactured with high precision using the etching before grinding technology and bonded to a custom designed printed circuit board. A quantitative comparison of the performance was made against a commercially available surface probe. To investigate the long-term stability of contact sites, the spiky probe was repeatedly inserted in seven experiments (17 insertions, in total) using Wistar rat hippocampal slices, in vitro. Impedance magnitudes and phase angles were compared before and after the extensive usage. Results Single unit activities were recorded with higher neuronal yield and higher amplitudes compared to the surface probe. Impedances did not increase significantly after reusing the probe in multiple experiments. Furthermore, we were able to detect extracellular action potentials from the same single unit on multiple, adjacent contact sites. Finally, we separated the recorded single units into putative cell types based on their extracellular waveforms. Conclusion and outlook The spiky probes were proved to be optimal solutions to record extracellular spike waveforms, in vitro. The improved signal quality allowed us to distinguish between putative interneurons and principal cells. In future works, integrative experiments using these probes may provide multi-modal data for cellular electrophysiology resulting in a deeper understanding of single cell contributions to mass neural activity.

In this paper, the fabrication method, electrical and fluidic characterization and in vivo testing of the first deep brain silicon multielectrode with monolithically integrated fluidic channel are presented in details. Micromachined silicon probes with monolithically integrated microfluidic channels up to 70 mm length have been realized to perform simultaneous electrical recording and drug delivery in deep brain regions. The achieved cross-sectional dimension of the microchannels is in the range of 5–30 μm, while the length of the channel can be even 70 mm long.Fabrication process and integration of the drug delivery channels and the Pt recording sites are described. Electrical characterization and impedance tuning of the developed probes are also demonstrated. The functionality of the microfluidic channels is verified and the hydrodynamic characteristics (flow rate vs. injection pressure) are measured in the case of several length and cross-sections.Feasibility of our integration concept is proved by locally injected bicuculline in the cortex and in the thalamical regions of rat brain in vivo , while simultaneously recording the electrical signals of the stimulated neurons on four different electrical channels.

Tourism index is an indicator that demonstrates the market positions of settlements, on the basis of aggregating the demand and supply databases of the tourism market. A novelty of this methodology is that it allows the demonstration of the touristic performance of different settlements and regions with the application of one index. The purpose of our study is to demonstrate the theoretical background of the indicator and its application at the settlement and territorial levels of the Hungarian tourism sector. In addition to the index values it is also possible to monitor the further environmental relations system of tourism, including correlations with the settlement network or special geographical areas. The index also allows geographical and spatial development/regional typification and classification.

In this paper, manufacturing and in vivo testing of extreme-long Si-based neural microelectrode arrays are presented. Probes with different shaft lengths (15-70 mm) are formed by deep reactive ion etching and have been equipped with platinum electrodes of various configurations. In vivo measurements on rats indicate good mechanical stability, robust implantation, and targeting capability. High-quality signals have been recorded from different locations of the cerebrum of the rodents. The accompanied tissue damage is characterized by histology.

Recent progress in microtechnology has made room for novel applications in neural stimulation as well as for extending our knowledge on several malfunction of the nerval system such as tremor, epilepsy or Parkinson's disease, which belong to the most serious medical issues in the population of developed countries. Integrated drug delivery function in neural implants can contribute advantageously to the long-term stability of the medical devices in brain tissue. In our work, a hollow silicon microprobe developed for deep-brain application is proposed and tested. The fabrication is based on a novel micromachining technique utilising conventional MEMS technology and integrating both the probe shaft and microchannel system into the same substrate. The integrated microchannels have major influence on the failure properties of the probe, therefore the feasibility of the realised microstructures for deep-brain stimulation is characterised by experimental method and by modeling focusing on the change in mechanical response to axial loading.

Neural interface technologies including recording and stimulation electrodes are currently in the early phase of clinical trials aiming to help patients with spinal cord injuries, degenerative disorders, strokes interrupting descending motor pathways, or limb amputations. Their lifetime is of key importance; however, it is limited by the foreign body response of the tissue causing the loss of neurons and a reactive astrogliosis around the implant surface. Improving the biocompatibility of implant surfaces, especially promoting neuronal attachment and regeneration is therefore essential. In our work, bioactive properties of implanted black polySi nanostructured surfaces (520–800 nm long nanopillars with a diameter of 150–200 nm) were investigated and compared to microstructured Si surfaces in eight-week-long in vivo experiments. Glial encapsulation and local neuronal cell loss were characterised using GFAP and NeuN immunostaining respectively, followed by systematic image analysis. Regarding the severity of gliosis, no significant difference was observed in the vicinity of the different implant surfaces, however, the number of surviving neurons close to the nanostructured surface was higher than that of the microstructured ones. Our results imply that the functionality of implanted microelectrodes covered by Si nanopillars may lead to improved long-term recordings.

This paper aims the characterization of buried microchannels in silicon realized by deep reactive ion etching. The effects of dry etching parameters on the integrability into hollow microprobes are thoroughly investigated from both technological and functional aspects. Results are supposed to give physiology related probe designers a deeper insight into microfabrication-related issues.

A novel wet chemical etching process has been developed for the construction of multisite silicon-based neural interfaces. The fabricated probe shaft is 280 μm wide, 80 μm thick and 7 mm long. The current probe is equipped with 24 square-shaped platinum recording sites of 30 μm × 30 μm. The applied combination of wet chemical etching steps for the formation of the tip and the shaft allows the manufacturing of this neural interface in a wide variety of widths, thicknesses and lengths. Its sharp tip can easily penetrate both the dura and pia mater in animal experiments. The probe exhibits excellent electrophysiological performance when used for the measurement of local field potential, multiple and single unit activity in the cortex.

The durability of high surface area platinum electrodes during acute intracerebral measurements was investigated. Electrode sites with extremely rough surfaces were realized using electrochemical deposition of platinum onto silicon-based microelectrode arrays from a lead-free platinizing solution. The close to 1000-fold increase in effective surface area lowered impedance, its absolute value at 1 kHz became about 7 and 18 % of the original Pt electrodes in vitro and in vivo, respectively. 24-channel probes were subjected to 12 recording sessions, during which they were implanted into the cerebrum of rats. Our results showed that although on the average the effective surface area of the platinized sites decreased, it remained more than two orders of magnitude higher than the average effective surface area of the original, sputtered thin-film platinum electrodes. Sites with electrochemical deposits proved to be superior, e.g. they provided less thermal and 50 Hz noise, even after 12 penetrations into the intact rat brain.

Extreme-long (up to 70 mm) Si neural multielectrodes are presented for the first time. Probes with different shaft lengths (15–70 mm) were formed by deep reactive ion etching and have been equipped with Pt recording sites of various configurations. In vivo measurements on rodents indicated good mechanical stability, robust implantation and targeting capability, and high quality signals from different locations of the cerebrum have been recorded. The accompanied tissue damage was characterized by histology. With platinum electroplating, electrical impedance reduction was achieved, the improved charge transfer capability was characterized by cyclic voltammetry.

Precise and reproducible construction of microelectrode arrays (MEAs) is possible due to the advanced technology of microelectromechanical systems (MEMS). Polymer-based MEMS devices are gaining increasing attention in the field of experimental electrophysiology, since their mechanical flexibility allows smooth coupling with the soft neural tissue. In this paper we present a novel MEA with a layer structure of polyimide – platinum – SU-8. A single row of electrodes with arrow-like shapes were formed, designed to make possible a slight penetration of the sites into the tissue. Functional tests were performed on rat brain slices (in vitro) and on intact rat neocortex (in vivo).

This paper presents in vivo local iontophoretic release of a neuronal tracer, biotinylated dextran amine (BDA) in the rat brain using monolithically integrated microfluidic channel buried in a neural multielectrode. The tracer injection is controlled by iontophoresis using Pt electrodes in the vicinity of the outlet of the microfluidic channel. The successful injection is evaluated through histological maps of the labelled nerve cells in 3D. Together with previous electrophysiological studies we conclude that the presented device is capable of simultaneous in vivo multichannel neural recording and controlled tracer injection for mapping neuronal pathways of the brain.