Tentacle Microelectrode Arrays Uncover Soft Boundary Neurons in Hippocampal CA1.

Hippocampal CA1 neurons show intense firing at specific spatial locations, modulated by isolated landmarks. However, the impact of real-world scene transitions on neuronal activity remains unclear. Moreover, long-term neural recording during movement challenges device stability. Conventional rigid-based electrodes cause inflammatory responses, restricting recording durations. Inspired by the jellyfish tentacles, the multi-conductive layer ultra-flexible microelectrode arrays (MEAs) are developed. The tentacle MEAs ensure stable recordings during movement, thereby enabling the discovery of soft boundary neurons. The soft boundary neurons demonstrate high-frequency firing that aligns with the boundaries of scene transitions. Furthermore, the localization ability of soft boundary neurons improves with more scene transition boundaries, and their activity decreases when these boundaries are removed. The innovation of ultra-flexible, high-biocompatible tentacle MEAs improves the understanding of neural encoding in spatial cognition. They offer the potential for long-term in vivo recording of neural information, facilitating breakthroughs in the understanding and application of brain spatial navigation mehanisms.

Microelectrode Arrays for Detection of Neural Activity in Depressed Rats: Enhanced Theta Activity in the Basolateral Amygdala.

Depression is a common and severely debilitating neuropsychiatric disorder. Multiple studies indicate a strong correlation between the occurrence of immunological inflammation and the presence of depression. The basolateral amygdala (BLA) is crucial in the cognitive and physiological processing and control of emotion. However, due to the lack of detection tools, the neural activity of the BLA during depression is not well understood. In this study, a microelectrode array (MEA) based on the shape and anatomical location of the BLA in the brain was designed and manufactured. Rats were injected with lipopolysaccharide (LPS) for 7 consecutive days to induce depressive behavior. We used the MEA to detect neural activity in the BLA before modeling, during modeling, and after LPS administration on 7 consecutive days. The results showed that after LPS treatment, the spike firing of neurons in the BLA region of rats gradually became more intense, and the local field potential power also increased progressively. Further analysis revealed that after LPS administration, the spike firing of BLA neurons was predominantly in the theta rhythm, with obvious periodic firing characteristics appearing after the 7 d of LPS administration, and the relative power of the local field potential in the theta band also significantly increased. In summary, our results suggest that the enhanced activity of BLA neurons in the theta band is related to the depressive state of rats, providing valuable guidance for research into the neural mechanisms of depression.

High-Throughput Microelectrode Arrays for Precise Functional Localization of the Globus Pallidus Internus.

The globus pallidus internus (GPi) was considered a common target for stimulation in Parkinson's disease (PD). Located deep in the brain and of small size, pinpointing it during surgery is challenging. Multi-channel microelectrode arrays (MEAs) can provide micrometer-level precision functional localization, which can maximize the surgical outcome. In this paper, a 64-channel MEA modified by platinum nanoparticles with a detection site impedance of 61.1 kΩ was designed and prepared, and multiple channels could be synchronized to cover the target brain region and its neighboring regions so that the GPi could be identified quickly and accurately. The results of the implant trajectory indicate that, compared to the control side, there is a reduction in local field potential (LFP) power in multiple subregions of the upper central thalamus on the PD-induced side, while the remaining brain regions exhibit an increasing trend. When the MEA tip was positioned at 8,700 µm deep in the brain, the various characterizations of the spike signals, combined with the electrophysiological characteristics of the ß-segmental oscillations in PD, enabled MEAs to localize the GPi at the single-cell level. More precise localization could be achieved by utilizing the distinct characteristics of the internal capsule (ic), the thalamic reticular nucleus (Rt), and the peduncular part of the lateral hypothalamus (PLH) brain regions, as well as the relative positions of these brain structures. The MEAs designed in this study provide a new detection method and tool for functional localization of PD targets and PD pathogenesis at the cellular level.

Utilizing GO/PEDOT:PSS/PtNPs-enhanced high-stability microelectrode arrays for investigating epilepsy-induced striatal electrophysiology alterations.

The striatum plays a crucial role in studying epilepsy, as it is involved in seizure generation and modulation of brain activity. To explore the complex interplay between the striatum and epilepsy, we engineered advanced microelectrode arrays (MEAs) specifically designed for precise monitoring of striatal electrophysiological activities in rats. These observations were made during and following seizure induction, particularly three and 7 days post-initial modeling. The modification of graphene oxide (GO)/poly (3,4-ethylenedioxythiophene):polystyrene sulfonate (PEDOT:PSS)/platinu-m nanoparticles (PtNPs) demonstrated a marked reduction in impedance (10.5 ± 1.1 kΩ), and maintained exceptional stability, with impedance levels remaining consistently low (23 kΩ) even 14 days post-implantation. As seizure intensity escalated, we observed a corresponding increase in neuronal firing rates and local field potential power, with a notable shift towards higher frequency peaks and augmented inter-channel correlation. Significantly, during the grand mal seizures, theta and alpha bands became the dominant frequencies in the local field potential. Compared to the normal group, the spike firing rates on day 3 and 7 post-modeling were significantly higher, accompanied by a decreased firing interval. Power in both delta and theta bands exhibited an increasing trend, correlating with the duration of epilepsy. These findings offer valuable insights into the dynamic processes of striatal neural activity during the initial and latent phases of temporal lobe epilepsy and contribute to our understanding of the neural mechanisms underpinning epilepsy.

Real-Time Precise Targeting of the Subthalamic Nucleus via Transfer Learning in a Rat Model of Parkinson's Disease Based on Microelectrode Arrays.

In neurodegenerative disorders, neuronal firing patterns and oscillatory activity are remarkably altered in specific brain regions, which can serve as valuable biomarkers for the identification of deep brain regions. The subthalamic nucleus (STN) has been the primary target for DBS in patients with Parkinson's disease (PD). In this study, changes in the spike firing patterns and spectral power of local field potentials (LFPs) in the pre-STN (zona incerta, ZI) and post-STN (cerebral peduncle, cp) regions were investigated in PD rats, providing crucial evidence for the functional localization of the STN. Sixteen-channel microelectrode arrays (MEAs) with sites distributed at different depths and widths were utilized to record neuronal activities. The spikes in the STN exhibited higher firing rates than those in the ZI and cp. Furthermore, the LFP power in the delta band in the STN was the greatest, followed by that in the ZI, and was greater than that in the cp. Additionally, increased LFP power was observed in the beta bands in the STN. To identify the best performing classification model, we applied various convolutional neural networks (CNNs) based on transfer learning to analyze the recorded raw data, which were processed using the Gram matrix of the spikes and the fast Fourier transform of the LFPs. The best transfer learning model achieved an accuracy of 95.16%. After fusing the spike and LFP classification results, the time precision for processing the raw data reached 500 ms. The pretrained model, utilizing raw data, demonstrated the feasibility of employing transfer learning for training models on neural activity. This approach highlights the potential for functional localization within deep brain regions.

Impaired Spatial Firing Representations of Neurons in the Medial Entorhinal Cortex of the Epileptic Rat Using Microelectrode Arrays.

Epilepsy severely impairs the cognitive behavior of patients. It remains unclear whether epilepsy-induced cognitive impairment is associated with neuronal activities in the medial entorhinal cortex (MEC), a region known for its involvement in spatial cognition. To explore this neural mechanism, we recorded the spikes and local field potentials from MEC neurons in lithium-pilocarpine-induced epileptic rats using self-designed microelectrode arrays. Through the open field test, we identified spatial cells exhibiting spatially selective firing properties and assessed their spatial representations in relation to the progression of epilepsy. Meanwhile, we analyzed theta oscillations and theta modulation in both excitatory and inhibitory neurons. Furthermore, we used a novel object recognition test to evaluate changes in spatial cognitive ability of epileptic rats. After the epilepsy modeling, the spatial tuning of various types of spatial cells had suffered a rapid and pronounced damage during the latent period (1 to 5 d). Subsequently, the firing characteristics and theta oscillations were impaired. In the chronic period (>10 d), the performance in the novel object experiment deteriorated. In conclusion, our study demonstrates the detrimental effect on spatial representations and electrophysiological properties of MEC neurons in the epileptic latency, suggesting the potential use of these changes as a "functional biomarker" for predicting cognitive impairment caused by epilepsy.

Highly Activated Neuronal Firings Monitored by Implantable Microelectrode Array in the Paraventricular Thalamus of Insomnia Rats.

Insomnia is a common sleep disorder around the world, which is harmful to people's health, daily life, and work. The paraventricular thalamus (PVT) plays an essential role in the sleep-wake transition. However, high temporal-spatial resolution microdevice technology is lacking for accurate detection and regulation of deep brain nuclei. The means for analyzing sleep-wake mechanisms and treating sleep disorders are limited. To detect the relationship between the PVT and insomnia, we designed and fabricated a special microelectrode array (MEA) to record electrophysiological signals of the PVT for insomnia and control rats. Platinum nanoparticles (PtNPs) were modified onto an MEA, which caused the impedance to decrease and improved the signal-to-noise ratio. We established the model of insomnia in rats and analyzed and compared the neural signals in detail before and after insomnia. In insomnia, the spike firing rate was increased from 5.48 ± 0.28 spike/s to 7.39 ± 0.65 spike/s, and the power of local field potential (LFP) decreased in the delta frequency band and increased in the beta frequency band. Furthermore, the synchronicity between PVT neurons declined, and burst-like firing was observed. Our study found neurons of the PVT were more activated in the insomnia state than in the control state. It also provided an effective MEA to detect the deep brain signals at the cellular level, which conformed with macroscopical LFP and insomnia symptoms. These results laid the foundation for studying PVT and the sleep-wake mechanism and were also helpful for treating sleep disorders.

Reduced Graphene Oxide and Gold Nanoparticles-Modified Electrochemical Aptasensor for Highly Sensitive Detection of Doxorubicin.

Doxorubicin (DOX) is the most clinically important antibiotic in cancer treatment, but its severe cardiotoxicity and other side effects limit its clinical use. Therefore, monitoring DOX concentrations during therapy is essential to improve efficacy and reduce adverse effects. Here, we fabricated a sensitive electrochemical aptasensor for DOX detection. The sensor used gold wire as the working electrode and was modified with reduced graphene oxide (rGO)/gold nanoparticles (AuNPs) to improve the sensitivity. An aptamer was used as the recognition element for the DOX. The 5' end of the aptamer was modified with a thiol group, and thus immobilized to the AuNPs, and the 3' end was modified with methylene blue, which acts as the electron mediator. The combination between the aptamer and DOX would produce a binding-induced conformation, which changes the electron transfer rate, yielding a current change that correlates with the concentration of DOX. The aptasensor exhibited good linearity in the DOX concentration range of 0.3 µM to 6 µM, with a detection limit of 0.1 µM. In addition, the aptasensor was used for DOX detection in real samples and results, and showed good recovery. The proposed electrochemical aptasensor will provide a sensitive, fast, simple, and reliable new platform for detecting DOX.

Single-neuron detection of place cells remapping in short-term memory using motion microelectrode arrays.

Place cells establish rapid mapping relationships between the external environment and themselves in a new context. However, the mapping relationships of environmental cues to place cells in short-term memory is still completely unknown. In this work, we designed a silicon-based motion microelectrode array (mMEA) and an implantation device to record electrophysiological signals of place cells in CA1, CA3, and DG regions in the hippocampus of ten mice in motion, and investigated the corresponding place fields under distal or local cues in just a few minutes. The mMEA can expand the detection area and greatly lower the motion noise. Finding and recording place cells of moving mice in short-term memory is made possible by the mMEA. The place-related cells were found for the first time. Unlike place cells, which only fire in a particular position of the environment, place-related cells fire in numerous areas of the environment. Furthermore, place cells in the CA1 and CA3 have the most stable place memory for time-preferred single cues, and they fire in concert with place-related cells during short-term memory dynamics, whereas place cells in the DG regions have overlapping and unstable place memory in a multi-cue context. These results demonstrate the consistency of place cells in CA1 and CA3 and reflect their different roles in spatial memory processing during familiarization with new environments. The mMEA provides a platform for studying the place cells of short-term memory.

A Neural Sensor with a Nanocomposite Interface for the Study of Spike Characteristics of Hippocampal Neurons under Learning Training.

Both the cellular- and population-level properties of involved neurons are essential for unveiling the learning and memory functions of the brain. To give equal attention to these two aspects, neural sensors based on microelectrode arrays (MEAs) have been in the limelight due to their noninvasive detection and regulation capabilities. Here, we fabricated a neural sensor using carboxylated graphene/3,4-ethylenedioxythiophene:polystyrenesulfonate (cGO/PEDOT:PSS), which is effective in sensing and monitoring neuronal electrophysiological activity in vitro for a long time. The cGO/PEDOT:PSS-modified microelectrodes exhibited a lower electrochemical impedance (7.26 ± 0.29 kΩ), higher charge storage capacity (7.53 ± 0.34 mC/cm2), and improved charge injection (3.11 ± 0.25 mC/cm2). In addition, their performance was maintained after 2 to 4 weeks of long-term cell culture and 50,000 stimulation pulses. During neural network training, the sensors were able to induce learning function in hippocampal neurons through precise electrical stimulation and simultaneously detect changes in neural activity at multiple levels. At the cellular level, not only were three kinds of transient responses to electrical stimulation sensed, but electrical stimulation was also found to affect inhibitory neurons more than excitatory neurons. As for the population level, changes in connectivity and firing synchrony were identified. The cGO/PEDOT:PSS-based neural sensor offers an excellent tool in brain function development and neurological disease treatment.