Tool In Neuroscience Research Research Articles

Animal models in neuroscience with alternative approaches: Evolutionary, biomedical, and ethical perspectives.

Animal models have been a crucial tool in neuroscience research for decades, providing insights into the biomedical and evolutionary mechanisms of the nervous system, disease, and behavior. However, their use has raised concerns on several ethical, clinical, and scientific considerations. The welfare of animals and the 3R principles (replacement, reduction, refinement) are the focus of the ethical concerns, targeting the importance of reducing the stress and suffering of these models. Several laws and guidelines are applied and developed to protect animal rights during experimenting. Concurrently, in the clinic and biomedical fields, discussions on the relevance of animal model findings on human organisms have increased. Latest data suggest that in a considerable amount of time the animal model results are not translatable in humans, costing time and money. Alternative methods, such as invitro (cell culture, microscopy, organoids, and micro physiological systems) techniques and in silico (computational) modeling, have emerged as potential replacements for animal models, providing more accurate data in a minimized cost. By adopting alternative methods and promoting ethical considerations in research practices, we can achieve the 3R goals while upholding our responsibility to both humans and other animals. Our goal is to present a thorough review of animal models used in neuroscience from the biomedical, evolutionary, and ethical perspectives. The novelty of this research lies in integrating diverse points of views to provide an understanding of the advantages and disadvantages of animal models in neuroscience and in discussing potential alternative methods.

Engineered 3D human neurovascular model of Alzheimer's disease to study vascular dysfunction

The blood–brain barrier (BBB) serves as a selective filter that prevents harmful substances from entering the healthy brain. Dysfunction of this barrier is implicated in several neurological diseases. In the context of Alzheimer's disease (AD), BBB breakdown plays a significant role in both the initiation and progression of the disease. This study introduces a three-dimensional (3D) self-assembled in vitro model of the human neurovascular unit to recapitulate some of the complex interactions between the BBB and AD pathologies. It incorporates primary human brain endothelial cells, pericytes and astrocytes, and stem cell-derived neurons and astrocytes harboring Familial AD (FAD) mutations. Over an extended co-culture period, the model demonstrates increased BBB permeability, dysregulation of key endothelial and pericyte markers, and morphological alterations mirroring AD pathologies. The model enables visualization of amyloid-beta (Aβ) accumulation in both neuronal and vascular compartments. This model may serve as a versatile tool for neuroscience research and drug development to provide insights into the dynamic relationship between vascular dysfunction and AD pathogenesis.

Classics in Chemical Neuroscience: Muscimol.

Muscimol (3) is a psychoactive isoxazole present in various Amanita mushrooms, along with ibotenic acid and muscarine. It is structurally related to GABA and acts as a GABAA agonist with great affinity. Muscimol use dates back to Siberian shamanic cultures as an entheogen, where it was ingested orally to exert psychoactive effects. Although not approved for clinical use, its potential and use as a research tool in neuroscience is of immense value, with 3H-muscimol being used as a radioligand in GABA receptor research. Since its discovery in the early 60s, many research groups have worked on the synthesis of the compound. Recent research suggests the potential use of muscimol in neuropathic pain relief and other potential uses are also being studied. In this review, we will cover the history, chemistry, pharmacology and overall importance of the compound.

Miniaturized Head-Mount Doppler Optical Coherence Tomography Scope for Freely Moving Mouse.

This study presents a miniaturized head-mount optical coherence tomography (OCT) system tailored for high-resolution brain imaging in freely moving mice, providing an advanced noninvasive imaging tool in neuroscience research. Leveraging optical coherence tomography technology, the system enables depth-resolved imaging and integrates functional OCT extensions, including angiography and Doppler imaging. Remarkably lightweight at 1.5 g, the device allows for the preservation of natural mouse behavior during imaging sessions. With a maximum 4 × 4 mm field of view and 7.4 μm axial resolution, the system offers reliable imaging capabilities. Noteworthy features include focal adjustability, rotary joint integration for fiber-twist-free operation, and a high-speed swept-source OCT laser at 200 kHz, facilitating real-time imaging. By providing insights into brain mechanisms and neurological disorders without disrupting natural behavior, this innovative system holds promise as a powerful tool in neuroscience research. Its compact design and comprehensive imaging capabilities make it well-suited for studying various brain regions and dynamic processes, contributing significantly to our understanding of brain function and pathology.

XCP-D: A Robust Pipeline for the Post-Processing of fMRI data

Abstract Functional neuroimaging is an essential tool for neuroscience research. Pre-processing pipelines produce standardized, minimally pre-processed data to support a range of potential analyses. However, post-processing is not similarly standardized. While several options for post-processing exist, they may not support output from different pre-processing pipelines, may have limited documentation, and may not follow generally accepted data organization standards (e.g. BIDS). In response, we present XCP-D: a collaborative effort between PennLINC at the University of Pennsylvania and the DCAN lab at the University of Minnesota. XCP-D uses an open development model on GitHub and incorporates continuous integration testing; it is distributed as a Docker container or Apptainer image. XCP-D generates denoised BOLD images and functional derivatives from resting-state data in either NIfTI or CIFTI files following pre-processing with fMRIPrep, HCP, or ABCD-BIDS pipelines. Even prior to its official release, XCP-D has been downloaded >5,000 times from DockerHub. Together, XCP-D facilitates robust, scalable, and reproducible post-processing of fMRI data.

Engineering viral vectors for acoustically targeted gene delivery

Targeted gene delivery to the brain is a critical tool for neuroscience research and has significant potential to treat human disease. However, the site-specific delivery of common gene vectors such as adeno-associated viruses (AAVs) is typically performed via invasive injections, which limit its applicable scope of research and clinical applications. Alternatively, focused ultrasound blood-brain-barrier opening (FUS-BBBO), performed noninvasively, enables the site-specific entry of AAVs into the brain from systemic circulation. However, when used in conjunction with natural AAV serotypes, this approach has limited transduction efficiency and results in substantial undesirable transduction of peripheral organs. Here, we use high throughput in vivo selection to engineer new AAV vectors specifically designed for local neuronal transduction at the site of FUS-BBBO. The resulting vectors substantially enhance ultrasound-targeted gene delivery and neuronal tropism while reducing peripheral transduction, providing a more than ten-fold improvement in targeting specificity in two tested mouse strains. In addition to enhancing the only known approach to noninvasively target gene delivery to specific brain regions, these results establish the ability of AAV vectors to be evolved for specific physical delivery mechanisms.

Revolutionizing Neurology: The Role of Artificial Intelligence in Advancing Diagnosis and Treatment.

Artificial intelligence (AI) has emerged as a powerful tool in the field of neurology, significantly impacting the diagnosis and treatment of neurological disorders. Recent technological breakthroughs have given us access to a plethora of information relevant to many aspects of neurology. NeuroscienceandAIshare a long history of collaboration.Along with great potential, we encounter obstacles relating to data quality, ethics, and inherent difficulty in applying data science in healthcare. Neurological disorders pose intricate challenges due to their complex manifestations and variability.Automating image interpretation tasks, AI algorithms accurately identify brain structures and detect abnormalities. This accelerates diagnosis and reduces the workload on medical professionals. Treatment optimization benefits from AI simulations that model different scenarios and predict outcomes. These AI systems can currently perform many of the sophisticated perceptual and cognitive capacities of biological systems, such as object identification and decision making. Furthermore, AI is rapidly being used as a tool in neuroscience research, altering our understanding of brain functioning. It has the ability to revolutionize healthcare as we know it into a system in which humans and robots collaborate to deliver better care for our patients.Image analysis activities such as recognizing particular brain regions, calculating changes in brain volume over time, and detecting abnormalities in brain scans can be automated by AI systems. This lessens the strain on radiologists and neurologists while improving diagnostic accuracy and efficiency.It is now obvious that cutting-edge artificial intelligence models combined with high-quality clinical data will lead to enhanced prognostic and diagnostic models in neurological illness, permitting expert-level clinical decision aids across healthcare settings.In conclusion, AI's integration into neurology has revolutionized diagnosis, treatment, and research. As AI technologies advance, they promise to unravel the complexities of neurological disorders further, leading to improved patient care and quality of life. The symbiosis of AI and neurology offers a glimpse into a future where innovation and compassion converge to reshape neurological healthcare. This abstract provides a concise overview of the role of AI in neurology and its transformative potential.

Tools for Cre-Mediated Conditional Deletion of Floxed Alleles from Developing Cerebellar Purkinje Cells.

The Cre-lox system is an indispensable tool in neuroscience research for targeting gene deletions to specific cellular populations. Here we assess the utility of several transgenic Cre lines, along with a viral approach, for targeting cerebellar Purkinje cells (PCs) in mice. Using a combination of a fluorescent reporter line (Ai14) to indicate Cre-mediated recombination and a floxed Dystroglycan line (Dag1flox ), we show that reporter expression does not always align precisely with loss of protein. The commonly used Pcp2Cre line exhibits a gradual mosaic pattern of Cre recombination in PCs from Postnatal Day 7 (P7) to P14, while loss of Dag1 protein is not complete until P30. Ptf1aCre drives recombination in precursor cells that give rise to GABAergic neurons in the embryonic cerebellum, including PCs and molecular layer interneurons. However, due to its transient expression in precursors, Ptf1aCre results in stochastic loss of Dag1 protein in these neurons. NestinCre , which is often described as a "pan-neuronal" Cre line for the central nervous system, does not drive Cre-mediated recombination in PCs. We identify a Calb1Cre line that drives efficient and complete recombination in embryonic PCs, resulting in loss of Dag1 protein before the period of synaptogenesis. AAV8-mediated delivery of Cre at P0 results in gradual transduction of PCs during the second postnatal week, with loss of Dag1 protein not reaching appreciable levels until P35. These results characterize several tools for targeting conditional deletions in cerebellar PCs at different developmental stages and illustrate the importance of validating the loss of protein following recombination.

Voxeloc: A time-saving graphical user interface for localizing and visualizing stereo-EEG electrodes

BackgroundThanks to its unrivalled spatial and temporal resolutions and signal-to-noise ratio, intracranial EEG (iEEG) is becoming a valuable tool in neuroscience research. To attribute functional properties to cortical tissue, it is paramount to be able to determine precisely the localization of each electrode with respect to a patient’s brain anatomy. Several software packages or pipelines offer the possibility to localize manually or semi-automatically iEEG electrodes. However, their reliability and ease of use may leave to be desired. New methodVoxeloc (voxel electrode locator) is a Matlab-based graphical user interface to localize and visualize stereo-EEG electrodes. Voxeloc adopts a semi-automated approach to determine the coordinates of each electrode contact, the user only needing to indicate the deep-most contact of each electrode shaft and another point more proximally. ResultsWith a deliberately streamlined functionality and intuitive graphical user interface, the main advantages of Voxeloc are ease of use and inter-user reliability. Additionally, oblique slices along the shaft of each electrode can be generated to facilitate the precise localization of each contact. Voxeloc is open-source software and is compatible with the open iEEG-BIDS (Brain Imaging Data Structure) format. Comparison with existing methodsLocalizing full patients’ iEEG implants was faster using Voxeloc than two comparable software packages, and the inter-user agreement was better. ConclusionsVoxeloc offers an easy-to-use and reliable tool to localize and visualize stereo-EEG electrodes. This will contribute to democratizing neuroscience research using iEEG.

Perturbing cortical networks: in vivo electrophysiological consequences of pan-neuronal chemogenetic manipulations using deschloroclozapine.

Chemogenetic techniques, specifically the use of Designer Receptors Exclusively Activated by Designer Drugs (DREADDs), have become invaluable tools in neuroscience research. Yet, the understanding of how Gq- and Gicoupled DREADDs alter local field potential (LFP) oscillations in vivo remains incomplete. This study investigates the in vivo electrophysiological effects of DREADD actuation by deschloroclozapine, on spontaneous firing rate and LFP oscillations recorded from the anterior cingulate cortex in lightly anesthetized male rats. Unexpectedly, in response to the administration of deschloroclozapine, we observed inhibitory effects with pan-neuronal hM3D(Gq) stimulation, and excitatory effects with pan-neuronal hM4D(Gi) stimulation in a significant portion of neurons. These results emphasize the need to account for indirect perturbation effects at the local neuronal network level in vivo, particularly when not all neurons express the chemogenetic receptors uniformly. In the current study, for instance, the majority of cells that were transduced with both hM3D(Gq) and hM4D(Gi) were GABAergic. Moreover, we found that panneuronal cortical chemogenetic modulation can profoundly alter oscillatory neuronal activity, presenting a potential research tool or therapeutic strategy in several neuropsychiatric models and diseases. These findings help to optimize the use of chemogenetic techniques in neuroscience research and open new possibilities for novel therapeutic strategies.

Simulation and fabrication of in vitro microfluidic microelectrode array chip for patterned culture and electrophysiological detection of neurons

To enable the detection and modulation of modularized neural networks in vitro, this study proposes a microfluidic microelectrode array chip for the cultivation, compartmentalization, and control of neural cells. The chip was designed based on the specific structure of neurons and the requirements for detection and modulation. Finite-element analysis of the chip’s flow field was conducted using the COMSOL Multiphysics software, and the simulation results show that the liquid within the chip can flow smoothly, ensuring stable flow fields that facilitate the uniform growth of neurons within the microfluidic channels. By employing MEMS technology in combination with nanomaterial modification techniques, the microfluidic microelectrode array chip was fabricated successfully. Primary hippocampal neurons were cultured on the chip, forming a well-defined neural network. Spontaneous electrical activity of the detected neurons was recorded, exhibiting a 23.7% increase in amplitude compared to neuronal discharges detected on an open-field microelectrode array. This study provides a platform for the precise detection and modulation of patterned neuronal growth in vitro, potentially serving as a novel tool in neuroscience research.

Advancing the interfacing performances of chronically implantable neural probes in the era of CMOS neuroelectronics.

Tissue penetrating microelectrode neural probes can record electrophysiological brain signals at resolutions down to single neurons, making them invaluable tools for neuroscience research and Brain-Computer-Interfaces (BCIs). The known gradual decrease of their electrical interfacing performances in chronic settings, however, remains a major challenge. A key factor leading to such decay is Foreign Body Reaction (FBR), which is the cascade of biological responses that occurs in the brain in the presence of a tissue damaging artificial device. Interestingly, the recent adoption of Complementary Metal Oxide Semiconductor (CMOS) technology to realize implantable neural probes capable of monitoring hundreds to thousands of neurons simultaneously, may open new opportunities to face the FBR challenge. Indeed, this shift from passive Micro Electro-Mechanical Systems (MEMS) to active CMOS neural probe technologies creates important, yet unexplored, opportunities to tune probe features such as the mechanical properties of the probe, its layout, size, and surface physicochemical properties, to minimize tissue damage and consequently FBR. Here, we will first review relevant literature on FBR to provide a better understanding of the processes and sources underlying this tissue response. Methods to assess FBR will be described, including conventional approaches based on the imaging of biomarkers, and more recent transcriptomics technologies. Then, we will consider emerging opportunities offered by the features of CMOS probes. Finally, we will describe a prototypical neural probe that may meet the needs for advancing clinical BCIs, and we propose axial insertion force as a potential metric to assess the influence of probe features on acute tissue damage and to control the implantation procedure to minimize iatrogenic injury and subsequent FBR.

Conducting Electroencephalography With Black Individuals: Barriers, Recommendations, and Impact on Generalizability

Electroencephalography (EEG) is a critical tool for neuroscience research on brain functioning, as well as clinical applications in neurological and psychiatric illnesses. Anti-Black racism is a substantial societal problem that affects the validity of EEG assessments, thereby undermining efforts in research and in medical practice. There are several barriers present in the process of recording EEG with Black individuals. This includes the physical qualities of Black hair; as well as the cultural and historical significance of Black hair, the features of Black hairstyles, and the discomfort that many Black individuals feel if their hair is touched. The potential impact of these barriers on the application of EEG is considerable, including concerns of individual discomfort, lack of generalizability, and misdiagnosis. Recommendations are proposed here to combat these barriers, including individual researchers who utilize EEG methods, funding agencies that support EEG research, and journal editors who publish EEG findings.

Utilizing Cre-lox-based mouse genetic tools in neuroscience research

The Cre-lox approach has become one of the most popular methods to generate mouse strains carrying a designated set of genes. Among a multitude of techniques, targeted recombination in active populations, mosaic analysis with double markers, Brainbow, and intersectional monosynaptic tracing are four of the most unprecedented Cre-lox-based mouse strains designed particularly to specialize in tackling neuroscience-related questions. Despite the ingenuity of these tools, they all have their own caveats and setbacks that should be handled with care and not overlooked. Therefore, the priority while utilizing these mouse genetic tools would be to have a complete understanding of their strengths and weaknesses. In this review, we recount the principles and applications of these techniques included with an incisive overview of the prerequisites, caveats, setbacks, and potential solutions for each, in hope of providing guidance and aid for scientists to find the most suitable technique for their research questions.

Quantitative Classification Model of Composite Product Image Based on Event-Related Potential

As an important research tool in neuroscience, event-related potential (ERP) technology enables in-depth analysis of the consumer’s product image cognition process and complements and verifies the product image cognition model at the ERP level. It provides an important theoretical basis for systematically capturing product image and improvement of the product image cognitive model. In this work, the correlation between ERP data, product image word pairs and the degree of semantic match with the product is investigated, and a support vector machine algorithm is selected to build a classification model with physiological data (behavioral data + ERP data) as the independent variable and the degree of semantic match with the product image as the dependent variable. By adjusting the model parameters, the final classification accuracy reaches 95.667%, which shows that the model has some reliability and is a viable research method for ERP-based product image researchers in the future.

Big Field of View MRI T1w and FLAIR Template - NMRI225

Image templates are a common tool for neuroscience research. Often, they are used for spatial normalization of magnetic resonance imaging (MRI) data, which is a necessary procedure for analyzing brain morphology and function via voxel-based analysis. This allows the researcher to reduce individual shape differences across images and make inferences across multiple subjects. Many templates have a small field-of-view typically focussed on the brain, limiting the use for applications requiring detailed information about other extra-cranial structures in the head and neck area. However, there are several applications where such information is important, for example source reconstruction of electroencephalography (EEG) and/or magnetoencephalography (MEG). We have constructed a new template based on 225 T1w and FLAIR images with a big field-of-view that can serve both as target for across subject spatial normalization as well as a basis to build high-resolution head models. This template is based on and iteratively re-registered to the MNI152 space to provide maximal compatibility with the most commonly used brain MRI template.

Evaluation of Non-invasive Optogenetic Stimulation with Transcranial Functional Ultrasound Imaging.

Optogenetics employs engineered viruses to genetically modify cells to express specific light-sensitive ion channels. The standard method for gene delivery in the brain involves invasive craniotomies that expose the brain and direct injections of viruses that invariably damage neural tissue along the syringe tract. A recently proposed alternative in which non-invasive optogenetics is performed with focused ultrasound (FUS)-mediated blood-brain barrier (BBB) openings has been found to non-invasively facilitate gene delivery for optogenetics in mice. Although gene delivery can be performed non-invasively, validating successful viral transduction and expression of encoded ion channels in target tissue typically involves similar invasive techniques, such as craniotomies in longitudinal studies and/or postmortem histology. Functional ultrasound imaging (fUSi) is an emerging neuroimaging technique that can be used to transcranially detect changes in cerebral blood volume following introduction of a stimulus. In this study, we implemented a fully non-invasive combined FUS-fUSi technique for performing optogenetics in mice. FUS successfully delivered viruses encoding the red-shifted channelrhodopsin variant ChrimsonR in all treated subjects. fUSi successfully identified stimulus-evoked cerebral blood volume changes preferentially in brain regions expressing the light-sensitive ion channels. Improvements in cell-specific targeting of viral vectors and transcranial ultrasound imaging will make the combined technique a useful tool for neuroscience research in small animals.

Development and validation of an advanced ex vivo brain slice invasion assay to model glioblastoma cell invasion into the complex brain microenvironment.

Organotypic cultures of murine brain slices are well-established tools in neuroscience research, including electrophysiology studies, modeling neurodegeneration, and cancer research. Here, we present an optimized ex vivo brain slice invasion assay that models glioblastoma multiforme (GBM) cell invasion into organotypic brain slices. Using this model, human GBM spheroids can be implanted with precision onto murine brain slices and cultured ex vivo to allow tumour cell invasion into the brain tissue. Traditional top-down confocal microscopy allows for imaging of GBM cell migration along the top of the brain slice, but there is limited resolution of tumour cell invasion into the slice. Our novel imaging and quantification technique involves embedding stained brain slices into an agar block, re-sectioning the slice in the Z-direction onto slides, and then using confocal microscopy to image cellular invasion into the brain tissue. This imaging technique allows for the visualization of invasive structures beneath the spheroid that would otherwise go undetected using traditional microscopy approaches. Our ImageJ macro (BraInZ) allows for the quantification of GBM brain slice invasion in the Z-direction. Importantly, we note striking differences in the modes of motility observed when GBM cells invade into Matrigel in vitro versus into brain tissue ex vivo highlighting the importance of incorporating the brain microenvironment when studying GBM invasion. In summary, our version of the ex vivo brain slice invasion assay improves upon previously published models by more clearly differentiating between migration along the top of the brain slice versus invasion into the slice.

Neurophilic herpesvirus: a powerful tool for neuroscience research

Viruses are powerful tools for the study of modern neurosciences. Most of the research on the connection and function of neurons were done by using recombinant viruses, among which neurotropic herpesvirus is one of the most important tools. With the continuous development of genetic engineering and molecular biology techniques, several recombinant neurophilic herpesviruses have been engineered into different viral tools for neuroscience research. This review describes and discusses several common and widely used neurophilic herpesviruses as nerve conduction tracers, viral vectors for neurological diseases, and lytic viruses for neuro-oncology applications, which provides a reference for further exploring the function of neurophilic herpesviruses.

Graphene- and MXene-based materials for neuroscience: diagnostic and therapeutic applications.

MXenes and graphene are two-dimensional materials that have gained increasing attention in neuroscience, particularly in sensing, theranostics, and biomedical engineering. Various composites of graphene and MXenes with fascinating thermal, optical, magnetic, mechanical, and electrical properties have been introduced to develop advanced nanosystems for diagnostic and therapeutic applications, as exemplified in the case of biosensors for neurotransmitter detection. These biosensors display high sensitivity, selectivity, and stability, making them promising tools for neuroscience research. MXenes have been employed to create high-resolution neural interfaces for neuroelectronic devices, develop neuro-receptor-mediated synapse devices, and stimulate the electrophysiological maturation of neural circuits. On the other hand, graphene/derivatives exhibit therapeutic applicability in neuroscience, as exemplified in the case of graphene oxide for targeted delivery of therapeutic agents to the brain. While MXenes and graphene have potential benefits in neuroscience, there are also challenges/limitations associated with their use, such as toxicity, environmental impacts, and limited understanding of their properties. In addition, large-scale production and commercialization as well as optimization of reaction/synthesis conditions and clinical translation studies are very important aspects. Thus, it is important to consider the use of these materials in neuroscience research and conduct further research to obtain an in-depth understanding of their properties and potential applications. By addressing issues related to biocompatibility, long-term stability, targeted delivery, electrical interfaces, scalability, and cost-effectiveness, MXenes and graphene have the potential to greatly advance the field of neuroscience and pave the way for innovative diagnostic and therapeutic approaches for neurological disorders. Herein, recent advances in therapeutic and diagnostic applications of graphene- and MXene-based materials in neuroscience are discussed, focusing on important challenges and future prospects.