Neural mechanisms of relational learning and fast knowledge reassembly in plastic neural networks.

Humans and animals have a striking ability to learn relationships between items in experience (such as stimuli, objects and events), enabling structured generalization and rapid assimilation of new information. A fundamental type of such relational learning is order learning, which enables transitive inference (if A > B and B > C, then A > C) and list linking (A > B > C and D > E > F rapidly 'reassembled' into A > B > C > D > E > F upon learning C > D). Despite longstanding study, a neurobiologically plausible mechanism for transitive inference and rapid reassembly of order knowledge has remained elusive.

Variation in the geometry of concept manifolds across human visual cortex.

Brain activity patterns in high-level visual cortex support accurate linear classification of visual concepts (e.g., objects or scenes).

miR-644a is a tumor cell-intrinsic mediator of sex bias in glioblastoma.

Background: Biological sex is an important risk factor for glioblastoma (GBM), with males having a higher incidence and poorer prognosis. The mechanisms for this sex bias are thought to be both tumor intrinsic and tumor extrinsic. MicroRNAs (miRNAs), key posttranscriptional regulators of gene expression, have been previously linked to sex differences in various cell types and diseases, but their role in the sex bias of GBM remains unknown.

The human social cognitive network contains multiple regions within the amygdala.

Reasoning about someone's thoughts and intentions-i.e., forming a "theory of mind"-is a core aspect of social cognition and relies on association areas of the brain that have expanded disproportionately in the human lineage.

Tumor cell-derived spermidine promotes a protumorigenic immune microenvironment in glioblastoma via CD8+ T cell inhibition.

The glioblastoma (GBM) microenvironment is enriched in immunosuppressive factors that potently interfere with the function of cytotoxic T lymphocytes. Cancer cells can directly affect the immune system, but the mechanisms driving these interactions are not completely clear. Here, we demonstrate that the polyamine metabolite spermidine (SPD) was elevated in the GBM tumor microenvironment.

A large-scale examination of inductive biases shaping high-level visual representation in brains and machines.

The rapid release of high-performing computer vision models offers new potential to study the impact of different inductive biases on the emergent brain alignment of learned representations. Here, we perform controlled comparisons among a curated set of 224 diverse models to test the impact of specific model properties on visual brain predictivity - a process requiring over 1.8 billion regressions and 50.

Principles of intensive human neuroimaging.

The rise of large, publicly shared functional magnetic resonance imaging (fMRI) data sets in human neuroscience has focused on acquiring either a few hours of data on many individuals ('wide' fMRI) or many hours of data on a few individuals ('deep' fMRI). In this opinion article, we highlight an emerging approach within deep fMRI, which we refer to as 'intensive' fMRI: one that strives for extensive sampling of cognitive phenomena to support computational modeling and detailed investigation of brain function at the single voxel level. We discuss the fundamental principles, trade-offs, and practical considerations of intensive fMRI.

Prezygotic barriers effectively limit hybridization in a rapid evolutionary radiation.

Hybridization is increasingly recognized as an important evolutionary process across the tree of life. In many clades, phylogenomic approaches have permitted unparalleled insight into the extent and frequency of hybridization. However, we continue to lack a deep understanding of the factors that limit and shape patterns of hybridization, especially in evolutionary radiations.

"But some were more equal than others:" Exploring inequality at Neolithic Çatalhöyük.

We explore the ways in which residents of Neolithic Çatalhöyük in Anatolia differentiated themselves as well as the ways in which they did not. We integrate numerous data sets in order to assess patterns of inequality (A) across buildings with contemporaneous occupations, (B) between buildings that did or did not burn at abandonment, and (C) through time. We use Gini coefficients so as to maximize comparability with other studies of inequality in the ancient and modern worlds, discussing the underlying data and our results to clarify and enhance the value of the quantitative analyses.

Frontostriatal salience network expansion in individuals in depression.

Decades of neuroimaging studies have shown modest differences in brain structure and connectivity in depression, hindering mechanistic insights or the identification of risk factors for disease onset. Furthermore, whereas depression is episodic, few longitudinal neuroimaging studies exist, limiting understanding of mechanisms that drive mood-state transitions. The emerging field of precision functional mapping has used densely sampled longitudinal neuroimaging data to show behaviourally meaningful differences in brain network topography and connectivity between and in healthy individuals, but this approach has not been applied in depression.

Stacked regressions and structured variance partitioning for interpretable brain maps.

Relating brain activity associated with a complex stimulus to different properties of that stimulus is a powerful approach for constructing functional brain maps. However, when stimuli are naturalistic, their properties are often correlated (e.g.

γ-aminobutyric acid receptor B signaling drives glioblastoma in females in an immune-dependent manner.

Sex differences in immune responses impact cancer outcomes and treatment response, including in glioblastoma (GBM). However, host factors underlying sex specific immune-cancer interactions are poorly understood. Here, we identify the neurotransmitter γ-aminobutyric acid (GABA) as a driver of GBM-promoting immune response in females.

Temporal asymmetry of neural representations predicts memory decisions.

A stimulus can be familiar for multiple reasons. It might have been recently encountered, or is similar to recent experience, or is similar to 'typical' experience. Understanding how the brain translates these sources of similarity into memory decisions is a fundamental, but challenging goal.

Modeling short visual events through the BOLD moments video fMRI dataset and metadata.

Studying the neural basis of human dynamic visual perception requires extensive experimental data to evaluate the large swathes of functionally diverse brain neural networks driven by perceiving visual events. Here, we introduce the BOLD Moments Dataset (BMD), a repository of whole-brain fMRI responses to over 1000 short (3 s) naturalistic video clips of visual events across ten human subjects. We use the videos' extensive metadata to show how the brain represents word- and sentence-level descriptions of visual events and identify correlates of video memorability scores extending into the parietal cortex.

Improved quantitative parameter estimation for prostate T relaxometry using convolutional neural networks.

Objective: Quantitative parameter mapping conventionally relies on curve fitting techniques to estimate parameters from magnetic resonance image series. This study compares conventional curve fitting techniques to methods using neural networks (NN) for measuring T in the prostate.

Materials And Methods: Large physics-based synthetic datasets simulating T mapping acquisitions were generated for training NNs and for quantitative performance comparisons.

What Do We Know About Nurse Practitioner/Physician Care Models in Long-Term Care: Results of a Scoping Review.

Objectives: Due to the rise of the nurse practitioner (NP) role in long-term care settings, it is important to understand the underlying structures and processes that influence NP and physician care models. This scoping review aims to answer the question, "What are the structures, processes, and outcomes of care models involving NPs and physicians in long-term care (LTC) homes?" A secondary aim was to describe the structural enablers and barriers across care models.

Research Design And Methods: Seven databases were searched.

A mathematical theory of relational generalization in transitive inference.

Humans and animals routinely infer relations between different items or events and generalize these relations to novel combinations of items. This allows them to respond appropriately to radically novel circumstances and is fundamental to advanced cognition. However, how learning systems (including the brain) can implement the necessary inductive biases has been unclear.

Growth-defense trade-offs promote habitat isolation between recently-diverged species.

Trade-offs are crucial for species divergence and reproductive isolation. Trade-offs between investment in growth versus defense against herbivores are implicated in tropical forest diversity. Empirically exploring the role of growth-defense trade-offs in closely related species' reproductive isolation can clarify the eco-evolutionary dynamics through which growth-defense trade-offs contribute to diversity.

Disentangling signal and noise in neural responses through generative modeling.

Measurements of neural responses to identically repeated experimental events often exhibit large amounts of variability. This is distinct from , operationally defined as the average expected response across repeated trials for each given event. Accurately distinguishing signal from noise is important, as each is a target that is worthy of study (many believe noise reflects important aspects of brain function) and it is important not to confuse one for the other.

Emergent neural dynamics and geometry for generalization in a transitive inference task.

Relational cognition-the ability to infer relationships that generalize to novel combinations of objects-is fundamental to human and animal intelligence. Despite this importance, it remains unclear how relational cognition is implemented in the brain due in part to a lack of hypotheses and predictions at the levels of collective neural activity and behavior. Here we discovered, analyzed, and experimentally tested neural networks (NNs) that perform transitive inference (TI), a classic relational task (if A > B and B > C, then A > C).

Androgen loss weakens anti-tumor immunity and accelerates brain tumor growth.

Many cancers, including glioblastoma (GBM), have a male-biased sex difference in incidence and outcome. The underlying reasons for this sex bias are unclear but likely involve differences in tumor cell state and immune response. This effect is further amplified by sex hormones, including androgens, which have been shown to inhibit anti-tumor T cell immunity.

miR-644a is a tumor cell-intrinsic mediator of sex bias in glioblastoma.

Background: Biological sex is an important risk factor for glioblastoma (GBM), with males having a higher incidence and poorer prognosis. The mechanisms for this sex bias are thought to be both tumor intrinsic and tumor extrinsic. MicroRNAs (miRNAs), key post-transcriptional regulators of gene expression, have been previously linked to sex differences in various cell types and diseases, but their role in the sex bias of GBM remains unknown.

Programmed spontaneously beating cardiomyocytes in regenerative cardiology.

Stem cells have gained attention as a promising therapeutic approach for damaged myocardium, and there have been efforts to develop a protocol for regenerating cardiomyocytes (CMs). Certain cells have showed a greater aptitude for yielding beating CMs, such as induced pluripotent stem cells, embryonic stem cells, adipose-derived stromal vascular fraction cells and extended pluripotent stem cells. The approach for generating CMs from stem cells differs across studies, although there is evidence that Wnt signaling, chemical additives, electrical stimulation, co-culture, biomaterials and transcription factors triggers CM differentiation.