Aerosol Jet-Printed High-Aspect Ratio Micro-Needle Electrode Arrays Applied for Human Cerebral Organoids and 3D Neurospheroid Networks.

The human brain is a complex and poorly accessible organ. Thus, new tools are required for studying the neural function in a controllable environment that preserves multicellular interaction and neuronal wiring. In particular, high-throughput methods that alleviate the need for animal experiments are essential for future studies. Recent developments of induced pluripotent stem cell technologies have enabled in vitro modeling of the human brain by creating three-dimensional brain tissue mimic structures. To leverage these new technologies, a systematic and versatile approach for evaluating neuronal activity at larger tissue depths within the regime of tens to hundreds of micrometers is required. Here, we present an aerosol-jet- and inkjet-printing-based method to fabricate microelectrode arrays, equipped with high-aspect ratio µ-needle electrodes that penetrate 3D neural network assemblies. The arrays have been successfully applied for electrophysiological recordings on interconnected neurospheroids formed on an engineered substrate and on cerebral organoids, both derived from human induced pluripotent stem cells.

4D-Printed Soft and Stretchable Self-Folding Cuff Electrodes for Small-Nerve Interfacing.

Peripheral nerve interfacing (PNI) has a high clinical potential for treating various diseases, such as obesity or diabetes. However, currently existing electrodes present challenges to the interfacing procedure, which limit their clinical application, in particular, when targeting small peripheral nerves (<200 µm). To improve the electrode handling and implantation, a nerve interface that can fold itself to a cuff around a small nerve, triggered by the body moisture during insertion, is fabricated. This folding is achieved by printing a bilayer of a flexible polyurethane printing resin and a highly swelling sodium acrylate hydrogel using photopolymerization. When immersed in an aqueous liquid, the hydrogel swells and folds the electrode softly around the nerve. Furthermore, the electrodes are robust, can be stretched (>20%), and bent to facilitate the implantation due to the use of soft and stretchable printing resins as substrates and a microcracked gold film as conductive layer. The straightforward implantation and extraction of the electrode as well as stimulation and recording capabilities on a small peripheral nerve in vivo are demonstrated. It is believed that such simple and robust to use self-folding electrodes will pave the way for bringing PNI to a broader clinical application.

Influence of Auditory Cues on the Neuronal Response to Naturalistic Visual Stimuli in a Virtual Reality Setting.

Virtual reality environments offer great opportunities to study the performance of brain-computer interfaces (BCIs) in real-world contexts. As real-world stimuli are typically multimodal, their neuronal integration elicits complex response patterns. To investigate the effect of additional auditory cues on the processing of visual information, we used virtual reality to mimic safety-related events in an industrial environment while we concomitantly recorded electroencephalography (EEG) signals. We simulated a box traveling on a conveyor belt system where two types of stimuli - an exploding and a burning box - interrupt regular operation. The recordings from 16 subjects were divided into two subsets, a visual-only and an audio-visual experiment. In the visual-only experiment, the response patterns for both stimuli elicited a similar pattern - a visual evoked potential (VEP) followed by an event-related potential (ERP) over the occipital-parietal lobe. Moreover, we found the perceived severity of the event to be reflected in the signal amplitude. Interestingly, the additional auditory cues had a twofold effect on the previous findings: The P1 component was significantly suppressed in the case of the exploding box stimulus, whereas the N2c showed an enhancement for the burning box stimulus. This result highlights the impact of multisensory integration on the performance of realistic BCI applications. Indeed, we observed alterations in the offline classification accuracy for a detection task based on a mixed feature extraction (variance, power spectral density, and discrete wavelet transform) and a support vector machine classifier. In the case of the explosion, the accuracy slightly decreased by -1.64% p. in an audio-visual experiment compared to the visual-only. Contrarily, the classification accuracy for the burning box increased by 5.58% p. when additional auditory cues were present. Hence, we conclude, that especially in challenging detection tasks, it is favorable to consider the potential of multisensory integration when BCIs are supposed to operate under (multimodal) real-world conditions.