In Vivo Penetrating Microelectrodes for Brain Electrophysiology

Advances in 3D tissue models for neural engineering: self-assembled versus engineered tissue models

Neural tissue engineering has emerged as a promising field that aims to create functional neural tissue for therapeutic applications, drug screening, and disease modelling. It is becoming evident in the literature that this goal requires development of three-dimensional (3D) constructs that can mimic the complex microenvironment of native neural tissue, including its biochemical, mechanical, physical, and electrical properties. These 3D models can be broadly classified as self-assembled models, which include spheroids, organoids, and assembloids, and engineered models, such as those based on decellularized or polymeric scaffolds. Self-assembled models offer advantages such as the ability to recapitulate neural development and disease processes in vitro, and the capacity to study the behaviour and interactions of different cell types in a more realistic environment. However, self-assembled constructs have limitations such as lack of standardised protocols, inability to control the cellular microenvironment, difficulty in controlling structural characteristics, reproducibility, scalability, and lengthy developmental timeframes. Integrating biomimetic materials and advanced manufacturing approaches to present cells with relevant biochemical, mechanical, physical, and electrical cues in a controlled tissue architecture requires alternate engineering approaches. Engineered scaffolds, and specifically 3D hydrogel-based constructs, have desirable properties, lower cost, higher reproducibility, long-term stability, and they can be rapidly tailored to mimic the native microenvironment and structure. This review explores 3D models in neural tissue engineering, with a particular focus on analysing the benefits and limitations of self-assembled organoids compared with hydrogel-based engineered 3D models. Moreover, this paper will focus on hydrogel based engineered models and probe their biomaterial components, tuneable properties, and fabrication techniques that allow them to mimic native neural tissue structures and environment. Finally, the current challenges and future research prospects of 3D neural models for both self-assembled and engineered models in neural tissue engineering will be discussed.

Multi-Sensor Origami Platform: A Customizable System for Obtaining Spatiotemporally Precise Functional Readouts in 3D Models

Bioprinting technology offers unprecedented opportunities to construct in vitro tissue models that recapitulate the 3D morphology and functionality of native tissue. Yet, it remains difficult to obtain adequate functional readouts from such models. In particular, it is challenging to position sensors in desired locations within pre-fabricated 3D bioprinted structures. At the same time, bioprinting tissue directly onto a sensing device is not feasible due to interference with the printer head. As such, a multi-sensing platform inspired by origami that overcomes these challenges by "folding" around a separately fabricated 3D tissue structure is proposed, allowing for the insertion of electrodes into precise locations, which are custom-defined using computer-aided-design software. The multi-sensing origami platform (MSOP) can be connected to a commercial multi-electrode array (MEA) system for data-acquisition and processing. To demonstrate the platform, how integrated 3D MEA electrodes can record neuronal electrical activity in a 3D model of a neurovascular unit is shown. The MSOP also enables a microvascular endothelial network to be cultured separately and integrated with the 3D tissue structure. Accordingly, how impedance-based sensors in the platform can measure endothelial barrier function is shown. It is further demonstrated the device's versatility by using it to measure neuronal activity in brain organoids.

Advances in the Electrophysiological Recordings of Long-Term Potentiation

Understanding neuronal firing patterns and long-term potentiation (LTP) induction in studying learning, memory, and neurological diseases is critical. However, recently, despite the rapid advancement in neuroscience, we are still constrained by the experimental design, detection tools for exploring the mechanisms and pathways involved in LTP induction, and detection ability of neuronal action potentiation signals. This review will reiterate LTP-related electrophysiological recordings in the mammalian brain for nearly 50 years and explain how excitatory and inhibitory neural LTP results have been detected and described by field- and single-cell potentials, respectively. Furthermore, we focus on describing the classic model of LTP of inhibition and discuss the inhibitory neuron activity when excitatory neurons are activated to induce LTP. Finally, we propose recording excitatory and inhibitory neurons under the same experimental conditions by combining various electrophysiological technologies and novel design suggestions for future research. We discussed different types of synaptic plasticity, and the potential of astrocytes to induce LTP also deserves to be explored in the future.