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Neurobiological research relies heavily on imaging techniques, such as fluorescence microscopy, to understand neurological function and disease processes. However, the number and variety of fluorescent probes available for ex vivo tissue section imaging limits the advance of research in the field. In this review, we outline the current range of fluorescent probes that are available to researchers for ex vivo brain section imaging, including their physical and chemical characteristics, staining targets, and examples of discoveries for which they have been used. This review is organised into sections based on the biological target of the probe, including subcellular organelles, chemical species (e.g., labile metal ions), and pathological phenomenon (e.g., degenerating cells, aggregated proteins). We hope to inspire further development in this field, given the considerable benefits to be gained by the greater availability of suitably sensitive probes that have specificity for important brain tissue targets.

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Episodic memory, the ability to recall specific events and experiences, is a cornerstone of human cognition with profound clinical implications. While animal studies have provided valuable insights into the neuronal underpinnings of episodic memory, research has largely relied on a limited subset of tasks that model only some aspects of episodic memory. In this narrative review, we provide an overview of rodent episodic-like memory tasks that expand the methodological repertoire and diversify the approaches used in episodic-like memory research. These tasks assess various aspects of human episodic memory, such as integrated what-where-when or what-where memory, source memory, free recall, temporal binding, and threshold retrieval dynamics. We review each task's general principle and consider whether alternative non-episodic mechanisms can account for the observed behavior. While our list of tasks is not exhaustive, we hope it will guide researchers in selecting models that align with their specific research objectives, leading to novel advancements and a more comprehensive understanding of mechanisms underlying specific aspects of episodic memory.

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Small extracellular vesicles (sEV) are endogenous lipid-bound membrane vesicles secreted by both prokaryotic and eukaryotic cells into the extracellular environment, performs several biological functions such as cell-cell communication, transfer of proteins, mRNA, and ncRNA to target cells in distant sites. Due to their role in molecular pathogenesis and its potential to deliver biological cargo to target cells, it has become a prominent area of interest in recent research in the field of Neuroscience. However, their role in neurological disorders, like neurodegenerative diseases is more complex and still unaddressed. Thus, this review focuses on the role of sEV in neurodegenerative and neurodevelopmental diseases, including their biogenesis, classification, and pathogenesis, with translational advantages and limitations in the area of neurobiology.

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Magnetoencephalography (MEG) allows the non-invasive measurement of brain activity at millisecond precision combined with localization of the underlying generators. So far, MEG-systems consisted of superconducting quantum interference devices (SQUIDS), which suffer from several limitations. Recent technological advances, however, have enabled the development of novel MEG-systems based on optically pumped magnetometers (OPMs), offering several advantages over conventional SQUID-MEG systems. Considering potential improvements in the measurement of neuronal signals as well as reduced operating costs, the application of OPM-MEG systems for clinical neuroscience and diagnostic settings is highly promising. Here we provide an overview of the current state-of-the art of OPM-MEG and its unique potential for translational neuroscience. First, we discuss the technological features of OPMs and benchmark OPM-MEG against SQUID-MEG and electroencephalography (EEG), followed by a summary of pioneering studies of OPMs in healthy populations. Key applications of OPM-MEG for the investigation of psychiatric and neurological conditions are then reviewed. Specifically, we suggest novel applications of OPM-MEG for the identification of biomarkers and circuit deficits in schizophrenia, dementias, movement disorders, epilepsy, and neurodevelopmental syndromes (autism spectrum disorder and attention deficit hyperactivity disorder). Finally, we give an outlook of OPM-MEG for translational neuroscience with a focus on remaining methodological and technical challenges.

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Monitoring neurochemicals and imaging the molecular content of brain tissues in vitro, ex vivo, and in vivo is essential for enhancing our understanding of neurochemistry and the causes of brain disorders. This review explores the potential applications of surface-enhanced Raman scattering (SERS) nanosensors in neurosciences, where their adoption could lead to significant progress in the field. These applications encompass detecting neurotransmitters or brain disorders biomarkers in biofluids with SERS nanosensors, and imaging normal and pathological brain tissues with SERS labeling. Specific studies highlighting in vitro, ex vivo, and in vivo analysis of brain disorders using fit-for-purpose SERS nanosensors will be detailed, with an emphasis on the ability of SERS to detect clinically pertinent levels of neurochemicals. Recent advancements in designing SERS-active nanomaterials, improving experimentation in biofluids, and increasing the usage of machine learning for interpreting SERS spectra will also be discussed. Furthermore, we will address the tagging of tissues presenting pathologies with nanoparticles for SERS imaging, a burgeoning domain of neuroscience that has been demonstrated to be effective in guiding tumor removal during brain surgery. The review also explores future research applications for SERS nanosensors in neuroscience, including monitoring neurochemistry in vivo with greater penetration using surface-enhanced spatially offset Raman scattering (SESORS), near-infrared lasers, and 2-photon techniques. The article concludes by discussing the potential of SERS for investigating the effectiveness of therapies for brain disorders and for integrating conventional neurochemistry techniques with SERS sensing.

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As a multilevel and multidisciplinary field, neuroscience is designed to interact with various branches of natural and applied sciences as well as with humanities and philosophy. The continental tradition in philosophy, particularly over the past 20 years, tended to establish strong connections with biology and neuroscience findings. This cross fertilization can however be impeded by conceptual intricacies, such as those surrounding the concept of plasticity. The use of this concept has broadened as scientists applied it to explore an ever-growing range of biological phenomena. Here, we examine the consequences of this ambiguity in an interdisciplinary context through the analysis of the concept of "destructive plasticity" in the philosophical writings of Catherine Malabou. The term "destructive plasticity" was coined by Malabou in 2009 to refer to all processes leading to psycho-cognitive and emotional alterations following traumatic or nontraumatic brain injuries or resulting from neurodevelopmental disorders. By comparing it with the neuroscientific definitions of plasticity, we discuss the epistemological obstacles and possibilities related to the integration of this concept into neuroscience. Improving interdisciplinary exchanges requires an advanced and sophisticated manipulation of neurobiological concepts. These concepts are not only intended to guide research programmes within neuroscience but also to organize and frame the dialogue between different theoretical backgrounds.

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Neuroimaging data analysis relies on normalization to standard anatomical templates to resolve macroanatomical differences across brains. Existing human cortical surface templates sample locations unevenly because of distortions introduced by inflation of the folded cortex into a standard shape. Here we present the onavg template, which affords uniform sampling of the cortex. We created the onavg template based on openly available high-quality structural scans of 1,031 brains-25 times more than existing cortical templates. We optimized the vertex locations based on cortical anatomy, achieving an even distribution. We observed consistently higher multivariate pattern classification accuracies and representational geometry inter-participant correlations based on onavg than on other templates, and onavg only needs three-quarters as much data to achieve the same performance compared with other templates. The optimized sampling also reduces CPU time across algorithms by 1.3-22.4% due to less variation in the number of vertices in each searchlight.

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The field of rodent behavioral neuroscience is undergoing two major sea changes: an ever-growing technological revolution, and worldwide calls to consider sex as a biological variable (SABV) in experimental design. Both have enormous potential to improve the precision and rigor with which the brain can be studied, but the convergence of these shifts in scientific practice has exposed critical limitations in classic and widely used behavioral paradigms. While our tools have advanced, our behavioral metrics - mostly developed in males and often allowing for only binary outcomes - have not. This opinion article explores how this disconnect has presented challenges for the accurate depiction and interpretation of sex differences in brain function, arguing for the expansion of current behavioral constructs to better account for behavioral diversity.

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Planarians are well-known model organisms for regeneration and developmental biology research due to their remarkable regenerative capacity. Here, we aim to advocate for the use of planaria as a valuable model for neurobiology, as well. Planarians have most of the major qualities of more developed organisms, including a primal brain. These traits combined with their exceptional regeneration capabilities, allow neurobiological experiments not possible in any other model organism, as we demonstrate by electrophysiological recording from planaria with two heads that controlling a shared body. To facilitate planarian neuroscience research, we developed an extracellular multi-unit recording procedure for the planarians fragile brain (Dugesia japonica). We created a semi-intact preparation restrained with fine dissection pins, enabling hours of reliable recording, via a suction electrode. Here, we demonstrate the feasibility and potential of planarian neurophysiological research by characterizing the neuronal activity during simple learning processes and responses to various stimuli. In addition, we examined the use of linalool as anesthetic agent to allows recordings from an intact, large worm and for fine electrophysiological approaches such as intracellular recording. The demonstrated ability for neurophysiological measurements, along with the inherent advantages of planarians, promotes this exceptional model organism for neuroscience research.

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Neuroscience has largely conceptualized inner speech, sometimes called covert speech, as being a part of the language system, namely, a precursor to overt speech and/or speech without the motor component (impoverished motor speech). Yet interdisciplinary work has strongly suggested that inner speech is multidimensional and situated within the language system as well as in more domain general systems. By leveraging evidence from philosophy, linguistics, neuroscience and cognitive science, we argue that neuroscience can gain a more comprehensive understanding of inner speech processes. We will summarize the existing knowledge on the traditional approach to understanding the neuroscience of inner speech, which is squarely through the language system, before discussing interdisciplinary approaches to understanding the cognitive, linguistic and neural substrates/mechanisms that may be involved in inner speech. Given our own interests in inner speech after brain injury, we finish by discussing the theoretical and clinical benefits of researching inner speech in aphasia through an interdisciplinary lens.

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Neurodegenerative diseases involve progressive neuronal death. Traditional treatments often struggle due to solubility, bioavailability, and crossing the Blood-Brain Barrier (BBB). Nanoparticles (NPs) in biomedical field are garnering growing attention as neurodegenerative disease drugs (NDDs) carrier to the central nervous system. Here, we introduced computational and experimental analysis. In the computational study, a specific IFPTML technique was used, which combined Information Fusion (IF) + Perturbation Theory (PT) + Machine Learning (ML) to select the most promising Nanoparticle Neuronal Disease Drug Delivery (N2D3) systems. For the application of IFPTML model in the nanoscience, NANO.PTML is used. IF-process was carried out between 4403 NDDs assays and 260 cytotoxicity NP assays conducting a dataset of 500,000 cases. The optimal IFPTML was the Decision Tree (DT) algorithm which shown satisfactory performance with specificity values of 96.4% and 96.2%, and sensitivity values of 79.3% and 75.7% in the training (375k/75%) and validation (125k/25%) set. Moreover, the DT model obtained Area Under Receiver Operating Characteristic (AUROC) scores of 0.97 and 0.96 in the training and validation series, highlighting its effectiveness in classification tasks. In the experimental part, two samples of NPs (Fe3O4_A and Fe3O4_B) were synthesized by thermal decomposition of an iron(III) oleate (FeOl) precursor and structurally characterized by different methods. Additionally, in order to make the as-synthesized hydrophobic NPs (Fe3O4_A and Fe3O4_B) soluble in water the amphiphilic CTAB (Cetyl Trimethyl Ammonium Bromide) molecule was employed. Therefore, to conduct a study with a wider range of NP system variants, an experimental illustrative simulation experiment was performed using the IFPTML-DT model. For this, a set of 500,000 prediction dataset was created. The outcome of this experiment highlighted certain NANO.PTML systems as promising candidates for further investigation. The NANO.PTML approach holds potential to accelerate experimental investigations and offer initial insights into various NP and NDDs compounds, serving as an efficient alternative to time-consuming trial-and-error procedures.

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The conventional medical paradigm often focuses on deficits and impairments, failing to capture the rich tapestry of experiences and abilities inherent in neurodiversity conditions. In this article, we introduce the 3E-Cognition perspective, offering a paradigm shift by emphasizing the dynamic interplay between the brain, body, and environment in shaping cognitive processes. The perspective fosters a more inclusive and supportive understanding of neurodiversity, with potential applications across various domains such as education, workplace, and healthcare. We begin by introducing the 3E-Cognition principles: embodied, environmentally scaffolded, and enactive. Then, we explore how the 3E-Cognition perspective can be applied to create inclusive environments and experiences for neurodiverse individuals. We provide examples in the realms of education, workplace, and healthcare. In all of these domains, spaces, methodologies, epistemologies, and roles that cater to diverse needs and strengths can be designed using the 3E principles. Finally, we discuss the challenges and benefits of implementing the 3E-Cognition perspective. We focus on the need for technological advancements and research in complex real-world scenarios; we suggest mobile brain/body imaging is a possible solution. We furthermore highlight the importance of recognizing and valuing the diverse manners of experiencing and interacting with the world, the promotion of diverse well-being, and the facilitation of innovation and creativity. Thus, we conclude that the 3E-Cognition perspective offers a groundbreaking approach to understanding and supporting neurodiversity: by embracing the inherent interconnectedness of the brain, body, and environment, we can create a more inclusive and supportive world.

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Since the NIH 'Sex as biological variable' policy, the percentage of studies including female subjects have increased largely. Nonetheless, many researchers fail to adequate their protocols to include females. In this narrative review, we aim to discuss the methodological pitfalls of the inclusion of female rodents in behavioral neuroscience. We address three points to consider in studies: the manipulations conducted only in female animals (such as estrous cycle monitoring, ovariectomy, and hormone replacement), the consideration of males as the standard, and biases related to interpretation and publication of the results. In addition, we suggest guidelines and perspectives for the inclusion of females in preclinical research.

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In the second half of the 20th century, neuroscientists across North America developed automated systems for use in their research laboratories. Their decisions to do so were complex and contingent, partly a result of global reasons, such as the need to increase efficiency and flexibility, and partly a result of local reasons, such as the need to amend perceived biases of earlier research methodologies. Automated methods were advancements but raised several challenges. Transferring a system from one location to another required that certain components of the system be standardized, such as the hardware, software, and programming language. This proved difficult as commercial manufacturers lacked incentives to create standardized products for the few neuroscientists working towards automation. Additionally, investing in automated systems required massive amounts of time, labor, funding, and computer expertise. Moreover, neuroscientists did not agree on the value of automation. My brief history investigates Karl Pribram's decisions to expand his newly created automated system by standardizing equipment, programming, and protocols. Although he was an eminent Stanford neuroscientist with strong institutional support and computer know-how, the development and transfer of his automated behavioral testing system was riddled with challenges. For Pribram and neuroscience more generally, automation was not so automatic.

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Our actions and decisions in everyday life are heavily influenced by social interactions, which are dynamic feedback loops involving actions, reactions, and internal cognitive processes between individual agents. Social interactions induce interpersonal synchrony, which occurs at different biobehavioral levels and comprises behavioral, physiological, and neurological activities. Hyperscanning-a neuroimaging technique that simultaneously measures the activity of multiple brain regions-has provided a powerful second-person neuroscience tool for investigating the phase alignment of neural processes during interactive social behavior. Neural synchronization, revealed by hyperscanning, is a phenomenon called inter-brain synchrony- a process that purportedly facilitates social interactions by prompting appropriate anticipation of and responses to each other's social behaviors during ongoing shared interactions. In this review, I explored the therapeutic dual-brain approach using noninvasive brain stimulation to target inter-brain synchrony based on second-person neuroscience to modulate social interaction. Artificially inducing synchrony between the brains is a potential adjunct technique to physiotherapy, psychotherapy, and pain treatment- which are strongly influenced by the social interaction between the therapist and patient. Dual-brain approaches to personalize stimulation parameters must consider temporal, spatial, and oscillatory factors. Multiple data fusion analysis, the assessment of inter-brain plasticity, a closed-loop system, and a brain-to-brain interface can support personalized stimulation.

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Brain research has progressed with anesthetized animal experiments for a long time. Recent progress in research techniques allows us to measure neuronal activity in awake animals combined with behavioral tasks. The trends became more prominent in the last decade. This new research style triggers the paradigm shift in the research of brain science, and new insights into brain function have been revealed. It is reasonable to consider that awake animal experiments are more ideal for understanding naturalistic brain function than anesthetized ones. However, the anesthetized animal experiment still has advantages in some experiments. To take advantage of the anesthetized animal experiments, it is important to understand the mechanism of anesthesia and carefully handle the obtained data. In this minireview, we will shortly summarize the molecular mechanism of anesthesia in animal experiments, a recent understanding of the neuronal activities in a sensory system in the anesthetized animal brain, and consider the advantages and disadvantages of the anesthetized and awake animal experiments. This discussion will help us to use both research conditions in the proper manner.

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Advances in large-scale single-unit human neurophysiology, single-cell RNA sequencing, spatial transcriptomics and long-term ex vivo tissue culture of surgically resected human brain tissue have provided an unprecedented opportunity to study human neuroscience. In this Perspective, we describe the development of these paradigms, including Neuropixels and recent brain-cell atlas efforts, and discuss how their convergence will further investigations into the cellular underpinnings of network-level activity in the human brain. Specifically, we introduce a workflow in which functionally mapped samples of human brain tissue resected during awake brain surgery can be cultured ex vivo for multi-modal cellular and functional profiling. We then explore how advances in human neuroscience will affect clinical practice, and conclude by discussing societal and ethical implications to consider. Potential findings from the field of human neuroscience will be vast, ranging from insights into human neurodiversity and evolution to providing cell-type-specific access to study and manipulate diseased circuits in pathology. This Perspective aims to provide a unifying framework for the field of human neuroscience as we welcome an exciting era for understanding the functional cytoarchitecture of the human brain.

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We develop a mathematical approach to formally proving that certain neural computations and representations exist based on patterns observed in an organism's behaviour. To illustrate, we provide a simple set of conditions under which an ant's ability to determine how far it is from its nest would logically imply neural structures isomorphic to the natural numbers ℕ . We generalise these results to arbitrary behaviours and representations and show what mathematical characterisation of neural computation and representation is simplest while being maximally predictive of behaviour. We develop this framework in detail using a path integration example, where an organism's ability to search for its nest in the correct location implies representational structures isomorphic to two-dimensional coordinates under addition. We also study a system for processing a n b n strings common in comparative work. Our approach provides an objective way to determine what theory of a physical system is best, addressing a fundamental challenge in neuroscientific inference. These results motivate considering which neurobiological structures have the requisite formal structure and are otherwise physically plausible given relevant physical considerations such as generalisability, information density, thermodynamic stability and energetic cost.

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