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High density electrodes are a new frontier for biomedical implants. Increasing the density and the number of electrodes used for the stimulation of retinal ganglion cells is one possible strategy for enhancing the quality of vision experienced by patients using retinal prostheses. The present work presents an integration strategy for a diamond based, high density, stimulating electrode array with a purpose built application specific integrated circuit (ASIC). The strategy is centered on flip-chip bonding of indium bumps to create high count and density vertical interconnects between the stimulator ASIC and an array of diamond neural stimulating electrodes. The use of polydimethylsiloxane (PDMS) housing prevents cross-contamination of the biocompatible diamond electrode with non-biocompatible materials, such as indium, used in the microfabrication process. Micro-imprint lithography allowed edge-to-edge micro-scale pattering of the indium bumps on non-coplanar substrates that have a form factor that can conform to body organs and thus are ideally suited for biomedical applications. Furthermore, micro-imprint lithography ensures the compatibility of lithography with the silicon ASIC and aluminum contact pads. Although this work focuses on 256 stimulating diamond electrode arrays with a pitch of 150 μm, the use of indium bump bonding technology and vertical interconnects facilitates implants with tens of thousands electrodes with a pitch as low as 10 μm, thus ensuring validity of the strategy for future high acuity retinal prostheses, and bionic implants in general.

Microelectrode arrays and microprobes have been widely utilized to measure neuronal activity, both in vitro and in vivo. The key advantage is the capability to record and stimulate neurons at multiple sites simultaneously. However, unlike the single-cell or single-channel resolution of intracellular recording, microelectrodes detect signals from all possible sources around every sensor. Here, we review the current understanding of microelectrode signals and the techniques for analyzing them. We introduce the ongoing advancements in microelectrode technology, with focus on achieving higher resolution and quality of recordings by means of monolithic integration with on-chip circuitry. We show how recent advanced microelectrode array measurement methods facilitate the understanding of single neurons as well as network function.

Pesticides are unique environmental contaminants that are specifically introduced into the environment to control pests, often by killing them. Although pesticide application serves many important purposes, including protection against crop loss and against vector-borne diseases, there are significant concerns over the potential toxic effects of pesticides to non-target organisms, including humans. In many cases, the molecular target of a pesticide is shared by non-target species, leading to the potential for untoward effects. Here, we review the history of pesticide usage and the neurotoxicity of selected classes of pesticides, including insecticides, herbicides, and fungicides, to humans and experimental animals. Specific emphasis is given to linkages between exposure to pesticides and risk of neurological disease and dysfunction in humans coupled with mechanistic findings in humans and animal models. Finally, we discuss emerging techniques and strategies to improve translation from animal models to humans.

In bottom-up neuroscience, questions on neural information processing are addressed by engineering small but reproducible biological neural networks of defined network topology in vitro. The network topology can be controlled by culturing neurons within polydimethylsiloxane (PDMS) microstructures that are combined with microelectrode arrays (MEAs) for electric access to the network. However, currently used glass MEAs are limited to 256 electrodes and pose a limitation to the spatial resolution as well as the design of more complex microstructures. The use of high density complementary metal-oxide-semiconductor (CMOS) MEAs greatly increases the spatial resolution, enabling sub-cellular readout and stimulation of neurons in defined neural networks. Unfortunately, the non-planar surface of CMOS MEAs complicates the attachment of PDMS microstructures. To overcome the problem of axons escaping the microstructures through the ridges of the CMOS MEA, we stamp-transferred a thin film of hexane-diluted PDMS onto the array such that the PDMS filled the ridges at the contact surface of the microstructures without clogging the axon guidance channels. This method resulted in 23% of structurally fully connected but sealed networks on the CMOS MEA of which about 45% showed spiking activity in all channels. Moreover, we provide an impedance-based method to visualize the exact location of the microstructures on the MEA and show that our method can confine axonal growth within the PDMS microstructures. Finally, the high spatial resolution of the CMOS MEA enabled us to show that action potentials follow the unidirectional topology of our circular multi-node microstructure.

The electrical excitability of neural networks is influenced by different environmental factors. Effective and simple methods are required to objectively and quantitatively evaluate the influence of such factors, including variations in temperature and pharmaceutical dosage. The aim of this paper was to introduce 'the voltage threshold measurement method', which is a new method using microelectrode arrays that can quantitatively evaluate the influence of different factors on the electrical excitability of neural networks. We sought to verify the feasibility and efficacy of the method by studying the effects of acetylcholine, ethanol, and temperature on hippocampal neuronal networks and hippocampal brain slices. First, we determined the voltage of the stimulation pulse signal that elicited action potentials in the two types of neural networks under normal conditions. Second, we obtained the voltage thresholds for the two types of neural networks under different concentrations of acetylcholine, ethanol, and different temperatures. Finally, we obtained the relationship between voltage threshold and the three influential factors. Our results indicated that the normal voltage thresholds of the hippocampal neuronal network and hippocampal slice preparation were 56 and 31 mV, respectively. The voltage thresholds of the two types of neural networks were inversely proportional to acetylcholine concentration, and had an exponential dependency on ethanol concentration. The curves of the voltage threshold and the temperature of the medium for the two types of neural networks were U-shaped. The hippocampal neuronal network and hippocampal slice preparations lost their excitability when the temperature of the medium decreased below 34 and 33°C or increased above 42 and 43°C, respectively. These results demonstrate that the voltage threshold measurement method is effective and simple for examining the performance/excitability of neuronal networks.

Neural probes are sophisticated electrophysiological tools used for intra-cortical recording and stimulation. These microelectrode arrays, designed to penetrate and interface the brain from within, contribute at the forefront of basic and clinical neuroscience. However, one of the challenges and currently most significant limitations is their ‘seamless’ long-term integration into the surrounding brain tissue. Following implantation, which is typically accompanied by bleeding, the tissue responds with a scarring process, resulting in a gliotic region closest to the probe. This glial scarring is often associated with neuroinflammation, neurodegeneration, and a leaky blood–brain interface (BBI). The engineering progress on minimizing this reaction in the form of improved materials, microfabrication, and surgical techniques is summarized in this review. As research over the past decade has progressed towards a more detailed understanding of the nature of this biological response, it is time to pose the question: Are penetrating probes completely free from glial scarring at all possible?

Planar microelectrode arrays (MEAs) for – in vitro or in vivo – neuronal signal recordings lack the spatial resolution and sufficient signal‐to‐noise ratio (SNR) required for a detailed understanding of neural network function and synaptic plasticity. To overcome these limitations, a highly customizable three‐dimensional (3D) printing process is used in combination with thin film technology and a self‐aligned template‐assisted electrochemical deposition process to fabricate 3D‐printed‐based MEAs on stiff or flexible substrates. Devices with design flexibility and physical robustness are shown for recording neural activity in different in vitro and in vivo applications, achieving high‐aspect ratio 3D microelectrodes of up to 33:1. Here, MEAs successfully record neural activity in 3D neuronal cultures, retinal explants, and the cortex of living mice, thereby demonstrating the versatility of the 3D MEA while maintaining high‐quality neural recordings. Customizable 3D MEAs provide unique opportunities to study neural activity under regular or various pathological conditions, both in vitro and in vivo, and contribute to the development of drug screening and neuromodulation systems that can accurately monitor the activity of large neural networks over time. Two‐photon polymerization (2PP) lithography and surface micromachining technology allow the rapid fabrication of polymer templates to guide the growth of electrodes for three‐dimensional microelectrode arrays (3D MEAs), enabling in turn, device customizability, high signal‐to‐noise ratio (SNR) recordings, low bending stiffness, and minimized cross‐sectional footprint for in vitro and in vivo neural applications: from 3D neuronal cell cultures to the cortex of living mice.

A highly sensitive electrochemical sensor is reported for glucose detection using carbon nanotubes grown in situ at low temperatures on photolithographically defined gold microelectrode arrays printed on a glass substrate (CNTs/Au MEA). One of the main advantages of the present design is its potential to monitor 64 samples individually for the detection of glucose. The selectivity of the fabricated MEA towards glucose detection is achieved via modification of CNTs/Au MEA by immobilizing glucose oxidase (GO x ) enzyme in the matrix of poly (paraphenylenediamine) (GO x /poly (p-PDA)/CNTs/Au MEA). The electrocatalytic and electrochemical responses of the proposed sensing platform towards glucose determination were examined via cyclic voltammetry and electrochemical impedance spectroscopy. The developed impedimetric biosensor exhibits a good linear response towards glucose detection, i.e., 0.2–27.5 µM concentration range with sensitivity and detection limits of 168.03 kΩ −1  M −1 and 0.2 ± 0.0014 μM, respectively. The proposed glucose biosensor shows excellent reproducibility, good anti-interference property, and was successfully tested in blood serum samples. Further, the applicability of the proposed sensor was successfully validated through HPLC. These results supported the viability of using such devices for the simultaneous detection of multiple electroactive biomolecules of physiological relevance. Graphical Abstract

Understanding the retinogeniculate pathway in vitro can offer insights into its development and potential for future therapeutic applications. This study presents a Polydimethylsiloxane-based two-chamber system with axon guidance channels, designed to replicate unidirectional retinogeniculate signal transmission in vitro . Using embryonic rat retinas, we developed a model where retinal spheroids innervate thalamic targets through up to 6 mm long microfluidic channels. Using a combination of electrical stimulation and functional calcium imaging we assessed how channel length and electrical stimulation frequency affects thalamic target response. In the presented model we integrated up to 20 identical functional retinothalamic neural networks aligned on a single transparent microelectrode array, enhancing the robustness and quality of recorded functional data. We found that network integrity depends on channel length, with 0.5–2 mm channels maintaining over 90% morphological and 50% functional integrity. A reduced network integrity was recorded in longer channels. The results indicate a notable reduction in forward spike propagation in channels longer than 4 mm. Additionally, spike conduction fidelity decreased with increasing channel length. Yet, stimulation-induced thalamic target activity remained unaffected by channel length. Finally, the study found that a sustained thalamic calcium response could be elicited with stimulation frequencies up to 31 Hz, with higher frequencies leading to transient responses. In conclusion, this study presents a high-throughput platform that demonstrates how channel length affects retina to brain network formation and signal transmission in vitro .

Parkinson’s disease is the second most common neurodegenerative disorder, characterized by the progressive loss of dopaminergic neurons in the substantia nigra and the accumulation of α -synuclein aggregates. While significant progress has been made in understanding the genetic and biological aspects of Parkinson’s disease, its complex pathophysiology remains poorly understood, and current therapeutic approaches are largely symptomatic. Advanced in vitro models have emerged as essential tools for studying Parkinson’s disease related mechanisms and developing new therapeutic strategies. However, the electrophysiological characterization of neurons in these models remains underexplored. This review highlights the importance of employing electrophysiological techniques, such as patch-clamp recordings and microelectrode arrays, in providing critical insights into neuronal dysfunction, synaptic impairments, and network disruptions in Parkinson’s disease. The aim is to summarize the key discoveries in the electrophysiological characterization of the pathology and the related progress made in recent years, underlying the main challenges, including the lack of standardized protocols, and the heterogeneity of cellular sources and culture systems. Addressing these limitations is crucial for improving reproducibility and facilitating cross-study comparisons, allowing for a deeper understanding of Parkinson’s disease pathophysiology. By refining and standardizing electrophysiological approaches, these efforts will enhance our understanding of Parkinson’s disease’s underlying mechanisms, ultimately accelerating the discovery of robust biomarkers and the development of more effective therapeutic strategies.