News & Comment

The study of the female brain during pregnancy and motherhood is gaining traction, and holds the potential to address the unmet needs of millions of women worldwide. Here we highlight the most pressing gaps in this field. Filling these knowledge gaps will require two paths forward: focused longitudinal studies that deeply characterize individuals, and collaborative initiatives that build large-scale international databases.

Neuroscience research is affected by a substantial racial bias, but there are major challenges involved in minimizing this bias. Here we discuss these challenges and call for a global discussion that develops answers to these challenges and defines best practices for how researchers can better represent human diversity and work against medical racism. This global discussion should involve researchers from medicine, life sciences, social sciences, and humanities, as well as people with lived experience and health equity activists, to improve racial and ethnic equity in neuroscience research and beyond.

The neuroscience of hormonal contraceptives is a vital but relatively new field. Existing studies are limited in size and scope, but they nonetheless highlight that the effects of hormonal contraceptives on the nervous system are complex and can vary because of individual differences, contraceptive type and formulation, and timing of use, among other factors. Neuroscientists can empower individuals with information about the biopsychological effects of hormonal contraceptives by delving more deeply into these effects in rigorous randomized controlled trials, large-scale studies that examine population-level trends, and dense imaging or intensive longitudinal studies that examine individual-level effects.

In the case that led the Supreme Court to overturn Roe vs Wade, the State of Mississippi made the strong claim that fetuses can feel pain. We argue that critical biological evidence used to support this claim was misinterpreted and that the State’s argument conflated pain and nociception. Abortion policy has profound moral and ethical consequences and therefore needs to be grounded in the most accurate scientific arguments, as well as a clear understanding of what we mean when we use the term pain.

By integrating ongoing bioethical collaboration, neuroscientists can create a positive effect on their research and the knowledge it produces. To this end, we offer our experiences with an interdisciplinary model for the ethical advancement of a promising area of neuroscience — human neural organoid research.

Although issues surrounding diversity and inclusion in science are global, distinctive region-specific socioeconomic factors and operational biases interact to widen the opportunity gap and exacerbate the isolation of specific groups of disadvantaged scientists on the global stage. This commentary reviews the issues currently faced by the Latin American (neuro)science community and outlines key actions on multiple fronts to overcome the barriers impeding their global inclusion, visibility and success.

Can studying individual differences in brain structure and function reveal individual differences in behavior? Analyses of MRI data from nearly 50,000 individuals may suggest that the possibility is fleeting. Although sample size is important for brain-based prediction, researchers can take other steps to build better biomarkers. These include testing model generalizability across people, datasets, and time points and maximizing model robustness by optimizing brain data acquisition, behavioral measures, and prediction approaches.

Science engagement can be a daunting prospect. This is especially true for scientists whose work involves animal models, and particularly nonhuman primates. Here, we show that openly explaining our rationale for our neuroscience work involving nonhuman primates — and the legal and ethical regulations that govern animal experimentation — increased public support and understanding, which is crucial for this essential research to continue.

The death of George Floyd in 2020 sparked intense emotion, and increased recognition of the need to take active measures in matters of race within science and academia. This piece considers the field’s immediate actions with regard to Black representation at neuroscience conferences, and whether we are rising to the occasion in an area under our control.

Academics are not immune to the biases contributing to persistent inequalities in society. We face an urgent need to overhaul and dismantle current evaluation practices that uphold inequities at multiple points along the academic pipeline. Graduate admissions and faculty advancement are two arenas of gatekeeping in which a reimagining and redistribution of weighting of commonly used evaluation metrics are warranted. We define and promote the use of dynamic, flexible holistic evaluation models that can be implemented by first recognizing and acknowledging the biases that contribute to racial and ethnic disparities in academia. Leaders of academic institutions must step up to drive adoption of these revised evaluation metrics.

To understand the function of cortical circuits, it is necessary to catalog their cellular diversity. Past attempts to do so using anatomical, physiological or molecular features of cortical cells have not resulted in a unified taxonomy of neuronal or glial cell types, partly due to limited data. Single-cell transcriptomics is enabling, for the first time, systematic high-throughput measurements of cortical cells and generation of datasets that hold the promise of being complete, accurate and permanent. Statistical analyses of these data reveal clusters that often correspond to cell types previously defined by morphological or physiological criteria and that appear conserved across cortical areas and species. To capitalize on these new methods, we propose the adoption of a transcriptome-based taxonomy of cell types for mammalian neocortex. This classification should be hierarchical and use a standardized nomenclature. It should be based on a probabilistic definition of a cell type and incorporate data from different approaches, developmental stages and species. A community-based classification and data aggregation model, such as a knowledge graph, could provide a common foundation for the study of cortical circuits. This community-based classification, nomenclature and data aggregation could serve as an example for cell type atlases in other parts of the body.