Beyond Birth Control: The Neuroscience of Hormonal Contraceptives.

Hormonal contraceptives (HCs) are one of the most highly prescribed classes of drugs in the world used for both contraceptive and noncontraceptive purposes. Despite their prevalent use, the impact of HCs on the brain remains inadequately explored. This review synthesizes recent findings on the neuroscience of HCs, with a focus on human structural neuroimaging as well as translational, nonhuman animal studies investigating the cellular, molecular, and behavioral effects of HCs. Additionally, we consider data linking HCs to mood disorders and dysregulation of the hypothalamic-pituitary-adrenal (HPA) axis and stress response as a potential mediator. The review also addresses the unique sensitivity of the adolescent brain to HCs, noting significant changes in brain structure and function when HCs are used during this developmental period. Finally, we discuss potential effects of HCs in combination with smoking-derived nicotine on outcomes of ischemic brain damage. Methodological challenges, such as the variability in HC formulations and user-specific factors, are acknowledged, emphasizing the need for precise and individualized research approaches. Overall, this review underscores the necessity for continued interdisciplinary research to elucidate the neurobiological mechanisms of HCs, aiming to optimize their use and improve women's health.

Contrastive learning of shared spatiotemporal EEG representations across individuals for naturalistic neuroscience.

Neural representations induced by naturalistic stimuli offer insights into how humans respond to stimuli in daily life. Understanding neural mechanisms underlying naturalistic stimuli processing hinges on the precise identification and extraction of the shared neural patterns that are consistently present across individuals. Targeting the Electroencephalogram (EEG) technique, known for its rich spatial and temporal information, this study presents a framework for Contrastive Learning of Shared SpatioTemporal EEG Representations across individuals (CL-SSTER). CL-SSTER utilizes contrastive learning to maximize the similarity of EEG representations across individuals for identical stimuli, contrasting with those for varied stimuli. The network employs spatial and temporal convolutions to simultaneously learn the spatial and temporal patterns inherent in EEG. The versatility of CL-SSTER was demonstrated on three EEG datasets, including a synthetic dataset, a natural speech comprehension EEG dataset, and an emotional video watching EEG dataset. CL-SSTER attained the highest inter-subject correlation (ISC) values compared to the state-of-the-art ISC methods. The latent representations generated by CL-SSTER exhibited reliable spatiotemporal EEG patterns, which can be explained by properties of the naturalistic stimuli. CL-SSTER serves as an interpretable and scalable framework for the identification of inter-subject shared neural representations in naturalistic neuroscience.

Effectiveness of an interactive online group intervention based on pain neuroscience education and graded exposure to movement in breast cancer survivors with chronic pain: a randomised controlled trial.

PURPOSE: To evaluate the effectiveness, compared with usual care, of an interactive online group programme combining pain neuroscience education (PNE) and graded exposure to movement (GEM) for improving quality of life and pain experience in breast cancer survivors with chronic pain. METHODS: This single-blind randomised controlled trial included a sample of 49 breast cancer survivors who were randomly assigned to two groups (experimental: n = 22 and control: n = 27). The experimental group received a 12-week person-centred online programme based on pain neuroscience education and therapeutic yoga as gradual exposure to movement, while the control group continued with their usual care. The primary outcome was quality of life (FACT-B + 4); the secondary outcomes were related to the experience of chronic pain (pain intensity, pain interference, catastrophizing, pain self-efficacy, kinesiophobia, and fear avoidance behaviours). All variables were assessed at four time points (T0, baseline; T1, after PNE sessions; T2, after yoga sessions; T3, at 3-month follow-up). For data analysis, ANOVA (2 × 4) analysis of variance (95% CI) was used when outcomes were normally distributed. If not, within-group and between-group comparisons were calculated. RESULTS: Thirty-six participants were included in the analysis (control group, 22; experimental group, 14). A significant time * group effect was observed in favour of the experimental group regarding the global quality of life score (p = 0.010, ηp2 = 0.124). Significant differences in favour of the experimental group were observed for pain intensity, pain interference, catastrophizing, and pain self-efficacy. These differences persisted at follow-up. CONCLUSIONS: An online intervention based on PNE and GEM appears to be more effective than usual care for improving quality of life in breast cancer survivors with chronic pain, as a time per group interaction was reported. In addition, the intervention also significantly improved the participants' experience of chronic pain. However, due to the study limitations further research is needed. Trial record: NCT04965909 (26/06/2021).

Harnessing population diversity: in search of tools of the trade.

Big neuroscience datasets are not big small datasets when it comes to quantitative data analysis. Neuroscience has now witnessed the advent of many population cohort studies that deep-profile participants, yielding hundreds of measures, capturing dimensions of each individual's position in the broader society. Indeed, there is a rebalancing from small, strictly selected, and thus homogenized cohorts toward always larger, more representative, and thus diverse cohorts. This shift in cohort composition is prompting the revision of incumbent modeling practices. Major sources of population stratification increasingly overshadow the subtle effects that neuroscientists are typically studying. In our opinion, as we sample individuals from always wider diversity backgrounds, we will require a new stack of quantitative tools to realize diversity-aware modeling. We here take inventory of candidate analytical frameworks. Better incorporating driving factors behind population structure will allow refining our understanding of how brain-behavior relationships depend on human subgroups.

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.

A Perspective on Neuroscience Data Standardization with Neurodata Without Borders.

Neuroscience research has evolved to generate increasingly large and complex experimental data sets, and advanced data science tools are taking on central roles in neuroscience research. Neurodata Without Borders (NWB), a standard language for neurophysiology data, has recently emerged as a powerful solution for data management, analysis, and sharing. We here discuss our labs' efforts to implement NWB data science pipelines. We describe general principles and specific use cases that illustrate successes, challenges, and non-trivial decisions in software engineering. We hope that our experience can provide guidance for the neuroscience community and help bridge the gap between experimental neuroscience and data science. Key takeaways from this article are that (1) standardization with NWB requires non-trivial design choices; (2) the general practice of standardization in the lab promotes data awareness and literacy, and improves transparency, rigor, and reproducibility in our science; (3) we offer several feature suggestions to ease the extensibility, publishing/sharing, and usability for NWB standard and users of NWB data.

Fluorescent probes for neuroscience: imaging ex vivo brain tissue sections.

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.

Rethinking plasticity: Analysing the concept of "destructive plasticity" in the light of neuroscience definitions.

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.

Applications of OPM-MEG for translational neuroscience: a perspective.

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.

Surface-Enhanced Raman Scattering Nanosensing and Imaging in Neuroscience.

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.

Emerging role and translational potential of small extracellular vesicles in neuroscience.

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.

Neuroscientist's Behavioral Toolbox for Studying Episodic-Like Memory.

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.

Neurophysiological measurements of planarian brain activity: a unique model for neuroscience research.

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 control 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.

Behavioral neuroscience's inevitable SABV growing pains.

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.

NANO.PTML model for read-across prediction of nanosystems in neurosciences. computational model and experimental case of study.

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.

Female rodents in behavioral neuroscience: Narrative review on the methodological pitfalls.

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.

Applied human neuroscience: Fostering and designing inclusive environments with the 3E-Cognition perspective.

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.