Recording Of Neuronal Activity Research Articles

Cholinergic modulation of interhemispheric inhibition in the mouse motor cortex.

Interhemispheric inhibition of the homotopic motor cortex is believed to be effective for accurate unilateral motor function. However, the cellular mechanisms underlying interhemispheric inhibition during unilateral motor behavior remain unclear. Furthermore, the impact of the neuromodulator acetylcholine on interhemispheric inhibition and the associated cellular mechanisms are not well understood. To address this knowledge gap, we conducted recordings of neuronal activity from the bilateral motor cortex of mice during the paw-reaching task. Subsequently, we analyzed interhemispheric spike correlation at the cell-pair level, classifying putative cell types to explore the underlying cellular circuitry mechanisms of interhemispheric inhibition. We found a cell-type pair-specific enhancement of the interhemispheric spike correlation when the mice were engaged in the reaching task. We also found that the interhemispheric spike correlation was modulated by pharmacological acetylcholine manipulation. The local field responses to contralateral excitation differed along the cortical depths, and muscarinic receptor antagonism enhanced the inhibitory component of the field response in deep layers. The muscarinic subtype M2 receptor is predominantly expressed in deep cortical neurons, including GABAergic interneurons. These results suggest that GABAergic interneurons expressing muscarinic receptors in deep layers mediate the neuromodulation of interhemispheric inhibition in the homotopic motor cortex.

Fiber-based Probes for Electrophysiology, Photometry, Optical and Electrical Stimulation, Drug Delivery, and Fast-Scan Cyclic Voltammetry In Vivo.

Recording and modulation of neuronal activity enables the study of brain function in health and disease. While translational neuroscience relies on electrical recording and modulation techniques, mechanistic studies in rodent models leverage genetic precision of optical methods, such as optogenetics and imaging of fluorescent indicators. In addition to electrical signal transduction, neurons produce and receive diverse chemical signals which motivate tools to probe and modulate neurochemistry. Although the past decade has delivered a wealth of technologies for electrophysiology, optogenetics, chemical sensing, and optical recording, combining these modalities within a single platform remains challenging. This work leverages materials selection and convergence fiber drawing to permit neural recording, electrical stimulation, optogenetics, fiber photometry, drug and gene delivery, and voltammetric recording of neurotransmitters within individual fibers. Composed of polymers and non-magnetic carbon-based conductors, these fibers are compatible with magnetic resonance imaging, enabling concurrent stimulation and whole-brain monitoring. Their utility is demonstrated in studies of the mesolimbic reward pathway by simultaneously interfacing with the ventral tegmental area and nucleus accumbens in mice and characterizing the neurophysiological effects of a stimulant drug. This study highlights the potential of these fibers to probe electrical, optical, and chemical signaling across multiple brain regions in both mechanistic and translational studies.

Speckle-enabled in vivo demixing of neural activity in the mouse brain.

Functional imaging of neuronal activity in awake animals, using a combination of fluorescent reporters of neuronal activity and various types of microscopy modalities, has become an indispensable tool in neuroscience. While various imaging modalities based on one-photon (1P) excitation and parallel (camera-based) acquisition have been successfully used for imaging more transparent samples, when imaging mammalian brain tissue, due to their scattering properties, two-photon (2P) microscopy systems are necessary. In 2P microscopy, the longer excitation wavelengths reduce the amount of scattering while the diffraction-limited 3D localization of excitation largely eliminates out-of-focus fluorescence. However, this comes at the cost of time-consuming serial scanning of the excitation spot and more complex and expensive instrumentation. Thus, functional 1P imaging modalities that can be used beyond the most transparent specimen are highly desirable. Here, we transform light scattering from an obstacle into a tool. We use speckles with their unique patterns and contrast, formed when fluorescence from individual neurons propagates through rodent cortical tissue, to encode neuronal activity. Spatiotemporal demixing of these patterns then enables functional recording of neuronal activity from a group of discriminable sources. For the first time, we provide an experimental, in vivo characterization of speckle generation, speckle imaging and speckle-assisted demixing of neuronal activity signals in the scattering mammalian brain tissue. We found that despite an initial fast speckle decorrelation, substantial correlation was maintained over minute-long timescales that contributed to our ability to demix temporal activity traces in the mouse brain in vivo. Informed by in vivo quantifications of speckle patterns from single and multiple neurons excited using 2P scanning excitation, we recorded and demixed activity from several sources excited using 1P oblique illumination. In our proof-of-principle experiments, we demonstrate in vivo speckle-assisted demixing of functional signals from groups of sources in a depth range of 220-320 µm in mouse cortex, limited by available speckle contrast. Our results serve as a basis for designing an in vivo functional speckle imaging modality and for maximizing the key resource in any such modality, the speckle contrast. We anticipate that our results will provide critical quantitative guidance to the community for designing techniques that overcome light scattering as a fundamental limitation in bioimaging.

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.

Neurophotonics beyond the surface: unmasking the brain's complexity exploiting optical scattering.

The intricate nature of the brain necessitates the application of advanced probing techniques to comprehensively study and understand its working mechanisms. Neurophotonics offers minimally invasive methods to probe the brain using optics at cellular and even molecular levels. However, multiple challenges persist, especially concerning imaging depth, field of view, speed, and biocompatibility. A major hindrance to solving these challenges in optics is the scattering nature of the brain. This perspective highlights the potential of complex media optics, a specialized area of study focused on light propagation in materials with intricate heterogeneous optical properties, in advancing and improving neuronal readouts for structural imaging and optical recordings of neuronal activity. Key strategies include wavefront shaping techniques and computational imaging and sensing techniques that exploit scattering properties for enhanced performance. We discuss the potential merger of the two fields as well as potential challenges and perspectives toward longer term in vivo applications.

Method for optimizing imaging parameters to record neuronal and cellular activity at depth with bioluminescence.

Optical imaging has accelerated neuroscience in recent years. Genetically encoded fluorescent activity sensors of calcium, neurotransmitters, and voltage are commonly used for optical recording of neuronal activity. However, fluorescence imaging is limited to superficial regions for in vivo activity imaging, due to photon scattering and absorbance. Bioluminescence imaging offers a promising alternative for achieving activity imaging in deeper brain regions without hardware implanted within the brain. Bioluminescent reporters can be genetically encoded and produce photons without external excitation. The use of enzymatic photon production also enables prolonged imaging sessions without the risk of photobleaching or phototoxicity, making bioluminescence suitable for non-invasive imaging of deep neuronal populations. To facilitate the adoption of bioluminescent activity imaging, we sought to develop a low cost, simple in vitro method that simulates in vivo conditions to optimize imaging parameters for determining optimal exposure times and optical hardware configurations to determine what frame rates can be captured with an individual lab's imaging hardware with sufficient signal-to-noise ratios without the use of animals prior to starting an in vivo experiment. We developed an assay for modeling in vivo optical conditions with a brain tissue phantom paired with engineered cells that produce bioluminescence. We then used this assay to limit-test the detection depth versus maximum frame rate for bioluminescence imaging at experimentally relevant tissue depths using off-the-shelf imaging hardware. We developed an assay for modeling in vivo optical conditions with a brain tissue phantom paired with engineered cells that produce bioluminescence. With this method, we demonstrate an effective means for increasing the utility of bioluminescent tools and lowering the barrier to adoption of bioluminescence activity imaging. We demonstrated an improved method for optimizing imaging parameters for activity imaging in vivo with bioluminescent sensors.

Frontostriatal circuit dysfunction leads to cognitive inflexibility in neuroligin-3 R451C knockin mice.

Cognitive and behavioral rigidity are observed in various psychiatric diseases, including in autism spectrum disorder (ASD). However, the underlying mechanism remains to be elucidated. In this study, we found that neuroligin-3 (NL3) R451C knockin mouse model of autism (KI mice) exhibited deficits in behavioral flexibility in choice selection tasks. Single-unit recording of medium spiny neuron (MSN) activity in the nucleus accumbens (NAc) revealed altered encoding of decision-related cue and impaired updating of choice anticipation in KI mice. Additionally, fiber photometry demonstrated significant disruption in dynamic mesolimbic dopamine (DA) signaling for reward prediction errors (RPEs), along with reduced activity in medial prefrontal cortex (mPFC) neurons projecting to the NAc in KI mice. Interestingly, NL3 re-expression in the mPFC, but not in the NAc, rescued the deficit of flexible behaviors and simultaneously restored NAc-MSN encoding, DA dynamics, and mPFC-NAc output in KI mice. Taken together, this study reveals the frontostriatal circuit dysfunction underlying cognitive inflexibility and establishes a critical role of the mPFC NL3 deficiency in this deficit in KI mice. Therefore, these findings provide new insights into the mechanisms of cognitive and behavioral inflexibility and potential intervention strategies.

Cocaine diminishes functional network robustness and destabilizes the energy landscape of neuronal activity in the medial prefrontal cortex.

We present analysis of neuronal activity recordings from a subset of neurons in the medial prefrontal cortex of rats before and after the administration of cocaine. Using an underlying modern Hopfield model as a description for the neuronal network, combined with a machine learning approach, we compute the underlying functional connectivity of the neuronal network. We find that the functional connectivity changes after the administration of cocaine with both functional-excitatory and functional-inhibitory neurons being affected. Using conventional network analysis, we find that the diameter of the graph, or the shortest length between the two most distant nodes, increases with cocaine, suggesting that the neuronal network is less robust. We also find that the betweenness centrality scores for several of the functional-excitatory and functional-inhibitory neurons decrease significantly, while other scores remain essentially unchanged, to also suggest that the neuronal network is less robust. Finally, we study the distribution of neuronal activity and relate it to energy to find that cocaine drives the neuronal network towards destabilization in the energy landscape of neuronal activation. While this destabilization is presumably temporary given one administration of cocaine, perhaps this initial destabilization indicates a transition towards a new stable state with repeated cocaine administration. However, such analyses are useful more generally to understand how neuronal networks respond to perturbations.

Recording Quality Is Systematically Related to Electrode Impedance.

Extracellular recordings with planar microelectrodes are the gold standard technique for recording the fast action potentials of neurons in the intact brain. The introduction of microfabrication techniques has revolutionized the in vivo recording of neuronal activity and introduced high-density, multi-electrode arrays that increase the spatial resolution of recordings and the number of neurons that can be simultaneously recorded. Despite these innovations, there is still debate about the ideal electrical transfer characteristics of extracellular electrodes. This uncertainty is partly due to the lack of systematic studies comparing electrodes with different characteristics, particularly for chronically implanted arrays over extended time periods. Here a high-density, flexible, and thin-film array is fabricated and tested, containing four distinct electrode types differing in surface material and surface topology and, thus, impedance. It is found that recording quality is strongly related to electrode impedance with signal amplitude and unit yield negatively correlated to impedance. Electrode impedances are stable for the duration of the experiment (up to 12 weeks) and recording quality does not deteriorate. The findings support the expectation from the theory that recording quality will increase as impedance decreases.

Simultaneous recording of neuronal discharge and calcium activity reveals claustrum-cortex neurosynchrony under anesthesia

Neural information transmission between deep brain nuclei and the cortex is essential for brain function. Currently, high-resolution simultaneous detection of neural information between the deep brain nuclei and the large-scale cortex still poses challenges. We have developed the microelectrode arrays based on the Micro-Electro-Mechanical System (MEMS) technology, and modified the electrode surface with nanomaterials to improve the electrode performance. This study combined microelectrode arrays and extended-field-of-view microscopy to achieve simultaneous recording of claustrum (CLA) electrophysiology and wide-field cortical calcium imaging at single-cell resolution. This work investigated the synchronous changes of neural information in CLA and cortex of mice during the whole process from wakefulness to anesthesia and then to wakefulness, and summarized the characteristics of the CLA electrophysiology and cortical calcium signaling under different inhalation anesthesia concentrations. We found the synergy between microscopic spike and local field potential (LFP) of CLA neurons under deep anesthesia, and the law that high inhalation anesthesia concentration enhanced the synchronization between neurons in CLA and cortex. The combination of microelectrode arrays and extended-field-of-view microscopy also gives a new method for synchronous detection of multimodal and multi-brain region neural information.

Machine learning-based high-frequency neuronal spike reconstruction from low-frequency and low-sampling-rate recordings

Recording neuronal activity using multiple electrodes has been widely used to understand the functional mechanisms of the brain. Increasing the number of electrodes allows us to decode more variety of functionalities. However, handling massive amounts of multichannel electrophysiological data is still challenging due to the limited hardware resources and unavoidable thermal tissue damage. Here, we present machine learning (ML)-based reconstruction of high-frequency neuronal spikes from subsampled low-frequency band signals. Inspired by the equivalence between high-frequency restoration and super-resolution in image processing, we applied a transformer ML model to neuronal data recorded from both in vitro cultures and in vivo male mouse brains. Even with the x8 downsampled datasets, our trained model reasonably estimated high-frequency information of spiking activity, including spike timing, waveform, and network connectivity. With our ML-based data reduction applicable to existing multichannel recording hardware while achieving neuronal signals of broad bandwidths, we expect to enable more comprehensive analysis and control of brain functions.

Methylphenidate (Ritalin) affects serotonin signaling differently in young compared to adults. Concomitant behavioral and neuronal recording from dorsal raphe in freely behaving rats

Currently, methylphenidate (MPD) is one of the most commonly prescribed psychostimulants for management and treatment of attention deficit hyperactivity disorder (ADHD). A rise in the consumption of MPD by “ordinary” youth and adults prompted concern regarding the ontogeny effects of acute and chronic MPD exposure. The objective of this study is to concomitantly record behavioral and neuronal activity from the dorsal raphe (DR) nucleus, a major source of serotonergic innervation in the mammalian brain before and following different doses of acute and chronic administration of MPD in freely behaving adolescent (young) and adult rats previously implanted with electrodes in the DR. A wireless recording system over 10 consecutive experimental days was used. Four experimental groups were used: saline, 0.6, 2.5, and 10.0 mg/kg MPD for young and similar groups for adult rats. Animals received one daily MPD injection on experimental days 1-6, followed by three washout days, and then drug rechallenge on experimental day 10 (ED10). 860 DR units were recorded, 356 from adult rats and 504 from young rats. The study provides experimental evidence that the responses to acute and chronic MPD were significantly different between the two age groups. Moreover, the study implies that it is essential to evaluate the electrophysiological responses to a drug based on the animal’s behavioral response to chronic drug exposure and that the DR and serotonin signaling has a significant role in the response to MPD as well as a different role in young as compared to adult rats.

Keeping time and rhythm by internal simulation of sensory stimuli and behavioral actions.

Effective behavior often requires synchronizing our actions with changes in the environment. Rhythmic changes in the environment are easy to predict, and we can readily time our actions to them. Yet, how the brain encodes and maintains rhythms is not known. Here, we trained primates to internally maintain rhythms of different tempos and performed large-scale recordings of neuronal activity across the sensory-motor hierarchy. Results show that maintaining rhythms engages multiple brain areas, including visual, parietal, premotor, prefrontal, and hippocampal regions. Each recorded area displayed oscillations in firing rates and oscillations in broadband local field potential power that reflected the temporal and spatial characteristics of an internal metronome, which flexibly encoded fast, medium, and slow tempos. The presence of widespread metronome-related activity, in the absence of stimuli and motor activity, suggests that internal simulation of stimuli and actions underlies timekeeping and rhythm maintenance.

Molecular tools to capture active neural circuits.

To understand how neurons and neural circuits function during behaviors, it is essential to record neuronal activity in the brain in vivo. Among the various technologies developed for recording neuronal activity, molecular tools that induce gene expression in an activity-dependent manner have attracted particular attention for their ability to clarify the causal relationships between neuronal activity and behavior. In this review, we summarize recently developed activity-dependent gene expression tools and their potential contributions to the study of neural circuits.

Microfluidic Localized Hydrogel Polymerization Enables Simultaneous Recording of Neural Activity and Behavior in C. elegans.

Monitoring an animal's brain activity during motion provides a means to interpret the brain activity in the context of movement. However, it is challenging to obtain information about the animal's movement during neural imaging in the popular model organism C. elegans due to its small size. Here, we present a microfluidic tool to immobilize only the head region of C. elegans for simultaneous recording of neuronal activity and tail movement. We combine hydrogel photopolymerization and microfluidics to realize controlled head immobilization in a semi-continuous fashion. To optimize the immobilization process, we characterize the hydrogel polymerization under different experimental conditions, including under the effect of fluid flow. We show that the Damköhler number specifically defined for our reactive transport phenomena can predict the success of such photopolymerized hydrogels used for sample immobilization. In addition to simultaneous recording of neural activity and behavior in C. elegans, we demonstrate our method's capability to temporarily reconfigure fluid flow and deliver chemical stimuli to the animal's nose to examine the animal's responses. We envision this approach to be useful for similar recordings for other small motile organisms, as well as scenarios where microfluidics and polymerization are used to control flow and rection.

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.

Development of a microelectrode for simultaneous <i>in vivo</i> calcium and electrophysiological recording of hippocampal neuronal activity

Calcium (Ca2+) imaging is a commonly utilized neuroscience technique for in vivo recording of neuronal activity. It involves the optical measurement of calcium concentration using genetically encoded calcium indicators (GECI) [1]. However, the kinetics of changes in the fluorescence of GECI are relatively slow and limited by the biophysics of the calcium binding [2]. In response to single action potentials (APs) in pyramidal neurons, most of the widely used GECI have a fluorescence half-life of approximately 100 ms [3]. As a result, GECI cannot provide complete information about the dynamics of neural ensembles. To address this issue, new variants of GECI, such as jGCaMP7 [3], and jGCaMP8 [4], have been developed, or genetically encoded voltage indicators (GEVI), such as JEDI-2P [5], have been utilized. However, the speed of GECI or GEVI is still lower than that of electrophysiological registration methods. Thus, we have designed a microelectrode that can be utilized with a gradient lens for in vivo calcium imaging with a miniscope. The miniscope is a miniature microscope for single photon epifluorescence Ca2+ imaging, which enables recording of neuronal activity in freely moving laboratory animals, unlike the traditionally used two-photon imaging technique. The miniscope utilizes gradient-index (GRIN) lenses that are implanted directly into the brain of a laboratory animal, instead of a conventional lens. The gradient lens is a transparent cylinder with a diameter of 1.8 mm and a length of 3.8 mm. To facilitate electrophysiological recording, we developed a microelectrode that can be aligned with a GRIN lens. The microelectrode is a three-layer structure consisting of: 1) a polyimide film, 2) conductive copper tracks deposited through thermoforming, and 3) a polyimide film with cutouts for pads. On one side of the microelectrode, there are 12 gold-plated conductive contacts for registering local field potentials, while on the other side, a similar number of conductive tracks are present for connecting to a connector that transmits data to the processing board. The flexible microelectrode is wrapped around a gradient lens and fixed using thermoforming, after which it is implanted in the animal's brain. Using the developed microelectrode, our aim is to perform a comparative analysis of the calcium and electrophysiological activity of hippocampal neurons in freely moving wild-type mice and in a mouse model of Alzheimer's disease. This study will enable the identification of any abnormalities in Alzheimer's disease at the level of neural ensembles and may suggest new treatment approaches or mechanisms for the development of the progressive memory loss pathology associated with this disease. We would like to express our gratitude to Anastasia Viktorovna Bolshakova for her administrative assistance, and to the staff of the Laboratory of Molecular Neurodegeneration for their invaluable help and advices.

Subthalamic nucleus neuronal activity entropy in the effective stimulation area in patients with Parkinson’s disease

One of the most successful and promising treatments for Parkinson’s disease today is deep brain stimulation (DBS). Accurate localization of the stimulation area is critical for the outcome of surgical DBS electrode implantation in the subthalamic nucleus (STN). To achieve this, microelectrode recording is used during surgery to precisely locate the STN borders [1], while test stimulations with a macroelectrode are widely employed to enhance DBS electrode placement accuracy. Thus, through testing multiple trajectories, the most clinically effective one can be selected. However, a comprehensive and reliable description of the specific single neuron activity associated with successful DBS electrode implantation is currently lacking. A study was conducted using microelectrode recordings (MER) of single neuron activity in the STN of 21 Parkinson’s disease patients (UPDRS III off/on=46.9/12.8) to identify the neuronal activity features associated with the most favorable clinical outcome of test stimulation. A comparative analysis of 29 activity parameters, such as firing rate, oscillatory activity intensity in different frequency ranges (Oscores), coefficient of variation, burst, pause index, among others [2], was conducted for 618 identified neurons. In addition, the approach of computing the entropy of the change in interspike intervals (ISI) of the pulse sequence [3] and the process of identifying patterns of neural activity using hierarchical clustering [4] were implemented. A comparative analysis of single neuron activity indicated notable (p 0.05) variations between disregarded and selected paths for the ultimate implantation of DBS electrode, solely relying on entropy parameters. Trajectories that delivered optimal test stimulation outcomes demonstrated reduced entropy of interspike intervals. Only the patterns of neuronal activity characterized by extended periods of steady firing and brief pauses, referred to as tonic and pause activity, respectively, were found to contribute to the difference in entropy between trajectories. In contrast, there were no statistically significant differences detected in entropy values associated with neurons demonstrating burst activity. Furthermore, we observed a positive and significant correlation between entropy values and the degree of improvement in disease presentation before and after administration of medication. A comparative analysis was conducted on the activity of single neurons along different trajectories with varied test stimulation responses. The results showed a weak effectiveness of linear parameters in determining the optimal electrode insertion path for improved clinical outcomes. However, the use of non-linear activity parameters, specifically entropy, in single neurons effectively differentiated trajectories with significant versus absent/insignificant test stimulation results. Furthermore, the significance of entropy in establishing the basal ganglia functions and describing information transfer processes in movement control is emphasized by interpreting this parameter as a measure of uncertainty or unpredictability of the information system in relation to the findings of other studies [5].

Analysis of the hippocampal neural network activity <i>in vivo</i> by miniature fluorescence microscopy in neurological pathologies

Miniature fluorescent microscopy is a method that enables neurobiologists to visualize and record neuronal activity of a specific brain region in vivo in freely moving mice [1]. The use of miniscope presents a novel approach for acquiring extensive data on the structure, function, and organization of the neuronal network in the region of interest at the in vivo level [2, 3]. In this way, the use of miniscope could also identify changes caused by pathological conditions, such as seizures, neurodegenerative diseases, and neurological complications resulting from past viral infections, like influenza virus. Data obtained through miniature fluorescent microscopy contains information on the functioning properties and original connections of hundreds of simultaneously recorded neurons. Our group developed an open-source toolbox to move from qualitative to quantitative analysis of recorded data, providing neurobiologists with statistical metrics from miniscope processed recordings through “Minian” [4]. Neuronal network state was defined in open-field test conditions under normal circumstances using a self-developed toolbox in the current study. In this study, 5-month-old wild B6SJL mice were injected with AAV-GCaMP6f virus in the hippocampus. After 3 weeks, a gradient lens was implanted over the hippocampus with baseplate fixation. Changes in calcium levels were measured using Miniscope v3 in the “open field” test. A software package was created for quantitative analysis of the neuron activity data. As a result, the study concluded that the most consistent data over the course of five days were the Pearson correlation coefficient for the active spike method (based on binary results from active phase segmentation) and the network degree level (the ratio of interconnected neurons depending on the presence of a connection). These measures displayed a high level of stability throughout the recordings. Furthermore, the PCA method applied to the calculated statistics indicated a close relationship between the coordinates that described the activity of the hippocampal neuronal network during the five-day testing period. The miniscope technique appears to be an effective tool for identifying shifts in neuronal networks during the progression of neurodegenerative diseases, such as Alzheimer’s disease [5]. It may also aid in detecting possible changes following neurological complications related to viral infections.

An Open-Source Wireless Electrophysiology System for In Vivo Neuronal Activity Recording in the Rodent Brain: 2.0.

Current trends in neurobiological research focus on analyzing complex interactions within brain structures. To conduct relevant experiments, it is often essential to employ animals with unhampered mobility and utilize electrophysiological equipment capable of wirelessly transmitting data. In prior research, we introduced an open-source wireless electrophysiology system to surmount these challenges. Nonetheless, this prototype exhibited several limitations, such as a hefty weight for the wireless module, redundant system components, a diminished sampling rate, and limited battery longevity. In this study, we unveil an enhanced version of the open-source wireless electrophysiology system, tailored for in vivo monitoring of neural activity in rodent brains. This new system has been successfully tested in real-time recordings of in vivo neural activity. Consequently, our development offers researchers a cost-effective and proficient tool for studying complex brain functions.