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Human brain atlases have been evolving tremendously, propelled recently by brain big projects, and driven by sophisticated imaging techniques, advanced brain mapping methods, vast data, analytical strategies, and powerful computing. We overview here this evolution in four categories: content, applications, functionality, and availability, in contrast to other works limited mostly to content. Four atlas generations are distinguished: early cortical maps, print stereotactic atlases, early digital atlases, and advanced brain atlas platforms, and 5 avenues in electronic atlases spanning the last two generations. Content-wise, new electronic atlases are categorized into eight groups considering their scope, parcellation, modality, plurality, scale, ethnicity, abnormality, and a mixture of them. Atlas content developments in these groups are heading in 23 various directions. Application-wise, we overview atlases in neuroeducation, research, and clinics, including stereotactic and functional neurosurgery, neuroradiology, neurology, and stroke. Functionality-wise, tools and functionalities are addressed for atlas creation, navigation, individualization, enabling operations, and application-specific. Availability is discussed in media and platforms, ranging from mobile solutions to leading-edge supercomputers, with three accessibility levels. The major application-wise shift has been from research to clinical practice, particularly in stereotactic and functional neurosurgery, although clinical applications are still lagging behind the atlas content progress. Atlas functionality also has been relatively neglected until recently, as the management of brain data explosion requires powerful tools. We suggest that the future human brain atlas-related research and development activities shall be founded on and benefit from a standard framework containing the core virtual brain model cum the brain atlas platform general architecture.

To explore how brains change upon species evolution, we generated single-cell transcriptomic atlases of the central brains of three closely related but ecologically distinct drosophilids: the generalists Drosophila melanogaster and Drosophila simulans , and the noni fruit specialist Drosophila sechellia . The global cellular composition of these species’ brains is well-conserved, but we predicted a few cell types with different frequencies, notably perineurial glia of the blood–brain barrier, which we validate in vivo . Gene expression analysis revealed that distinct cell types evolve at different rates and patterns, with glial populations exhibiting the greatest divergence between species. Compared to the D. melanogaster brain, cellular composition and gene expression patterns are more divergent in D. sechellia than in D. simulans —despite their similar phylogenetic distance from D. melanogaster —indicating that the specialization of D. sechellia is reflected in the structure and function of its brain. Expression changes in D. sechellia include several metabolic signaling genes, suggestive of adaptations to its novel source of nutrition. Additional single-cell transcriptomic analysis on D. sechellia revealed genes and cell types responsive to dietary supplement with noni, pointing to glia as sites for both physiological and genetic adaptation to this fruit. Our atlases represent the first comparative datasets for “whole” central brains and provide a comprehensive foundation for studying the evolvability of nervous systems in a well-defined phylogenetic and ecological framework.

In the last few million years, the hominin brain more than tripled in size. Comparisons across evolutionary lineages suggest that this expansion may be part of a broader trend toward larger, more complex brains in many taxa. Efforts to understand the evolutionary forces driving brain expansion have focused on climatic, ecological, and social factors. Here, building on existing research on learning, we analytically and computationally model the predictions of two closely related hypotheses: The Cultural Brain Hypothesis and the Cumulative Cultural Brain Hypothesis. The Cultural Brain Hypothesis posits that brains have been selected for their ability to store and manage information, acquired through asocial or social learning. The model of the Cultural Brain Hypothesis reveals relationships between brain size, group size, innovation, social learning, mating structures, and the length of the juvenile period that are supported by the existing empirical literature. From this model, we derive a set of predictions-the Cumulative Cultural Brain Hypothesis-for the conditions that favor an autocatalytic take-off characteristic of human evolution. This narrow evolutionary pathway, created by cumulative cultural evolution, may help explain the rapid expansion of human brains and other aspects of our species' life history and psychology.

Despite decades of research, much uncertainty remains regarding the selection pressures responsible for brain size variation. Whilst the influential social brain hypothesis once garnered extensive support, more recent studies have failed to find support for a link between brain size and sociality. Instead, it appears there is now substantial evidence suggesting ecology better predicts brain size in both primates and carnivores. Here, different models of brain evolution were tested, and the relative importance of social, ecological, and life-history traits were assessed on both overall encephalisation and specific brain regions. In primates, evidence is found for consistent associations between brain size and ecological factors, particularly diet; however, evidence was also found advocating sociality as a selection pressure driving brain size. In carnivores, evidence suggests ecological variables, most notably home range size, are influencing brain size; whereas, no support is found for the social brain hypothesis, perhaps reflecting the fact sociality appears to be limited to a select few taxa. Life-history associations reveal complex selection mechanisms to be counterbalancing the costs associated with expensive brain tissue through extended developmental periods, reduced fertility, and extended maximum lifespan. Future studies should give careful consideration of the methods chosen for measuring brain size, investigate both whole brain and specific brain regions where possible, and look to integrate multiple variables, thus fully capturing all of the potential factors influencing brain size.

Background Vertebrate brain structure is characterised not only by relative consistency in scaling between components, but also by many examples of divergence from these general trends.. Alternative hypotheses explain these patterns by emphasising either ‘external’ processes, such as coordinated or divergent selection, or ‘internal’ processes, like developmental coupling among brain regions. Although these hypotheses are not mutually exclusive, there is little agreement over their relative importance across time or how that importance may vary across evolutionary contexts. Results We introduce an agent-based model to simulate brain evolution in a ‘bare-bones’ system and examine dependencies between variables shaping brain evolution. We show that ‘concerted’ patterns of brain evolution do not, in themselves, provide evidence for developmental coupling, despite these terms often being treated as synonymous in the literature. Instead, concerted evolution can reflect either functional or developmental integration. Our model further allows us to clarify conditions under which such developmental coupling, or uncoupling, is potentially adaptive, revealing support for the maintenance of both mechanisms in neural evolution. Critically, we illustrate how the probability of deviation from concerted evolution depends on the cost/benefit ratio of neural tissue, which increases when overall brain size is itself under constraint. Conclusions We conclude that both developmentally coupled and uncoupled brain architectures can provide adaptive mechanisms, depending on the distribution of selection across brain structures, life history and costs of neural tissue. However, when constraints also act on overall brain size, heterogeneity in selection across brain structures will favour region specific, or mosaic, evolution. Regardless, the respective advantages of developmentally coupled and uncoupled brain architectures mean that both may persist in fluctuating environments. This implies that developmental coupling is unlikely to be a persistent constraint, but could evolve as an adaptive outcome to selection to maintain functional integration.

In the past few decades, hundreds of hominin fossils have been recovered from well-dated sites in East Africa. In addition, early representatives from far outside Africa have been found in Asia and Europe. Recently, discoveries at Malapa in South Africa and at Dmanisi in western Asia have brought important new fossils and archaeological residues to light. Analyses of local stratigraphy, windblown dust, sea and lake cores, and stable isotopic analyses have improved the reconstruction of ancient environments inhabited by early humans. Antón et al. review recent evidence and arguments about the evolution of early Homo , arguing that habitat instability and fragmentation imposed an important selective force. Science , this issue p. 10.1126/science.1236828 Integration of evidence over the past decade has revised understandings about the major adaptations underlying the origin and early evolution of the genus Homo . Many features associated with Homo sapiens , including our large linear bodies, elongated hind limbs, large energy-expensive brains, reduced sexual dimorphism, increased carnivory, and unique life history traits, were once thought to have evolved near the origin of the genus in response to heightened aridity and open habitats in Africa. However, recent analyses of fossil, archaeological, and environmental data indicate that such traits did not arise as a single package. Instead, some arose substantially earlier and some later than previously thought. From ~2.5 to 1.5 million years ago, three lineages of early Homo evolved in a context of habitat instability and fragmentation on seasonal, intergenerational, and evolutionary time scales. These contexts gave a selective advantage to traits, such as dietary flexibility and larger body size, that facilitated survival in shifting environments.

Human visual cortex is organized with striking consistency across individuals. While recent findings demonstrate an unexpected coupling between functional and cytoarchitectonic regions relative to the folding of human visual cortex, a unifying principle linking these anatomical and functional features of the cortex remains elusive. To fill this gap in knowledge, we combined independent and ground truth measurements of cytoarchitectonic regions and genetic tissue characterization within human occipitotemporal cortex. Using a data-driven approach, we examined whether differential gene expression among cytoarchitectonic areas could contribute to the arealization of occipitotemporal cortex into a hierarchy based on transcriptomics. This approach revealed two opposing gene expression gradients: one that contains a series of genes with expression magnitudes that ascend from posterior (e.g., areas human occipital [hOc]1, hOc2, hOc3, etc.) to anterior cytoarchitectonic areas (e.g., areas fusiform gyrus [FG]1-FG4) and another that contains a separate series of genes that show a descending gradient from posterior to anterior areas. Using data from the living human brain, we show that each of these gradients correlates strongly with variations in measures related to either thickness or myelination of cortex, respectively. We further reveal that these genetic gradients emerge along unique trajectories in human development: the ascending gradient is present at 10-12 gestational weeks, while the descending gradient emerges later (19-24 gestational weeks). Interestingly, it is not until early childhood (before 5 years of age) that the two expression gradients achieve their adult-like mean expression values. Additional analyses in nonhuman primates (NHPs) reveal that homologous genes do not generate the same ascending and descending expression gradients as in humans. We discuss these findings relative to previously proposed hierarchies based on functional and cytoarchitectonic features of visual cortex. Altogether, these findings bridge macroscopic features of human cytoarchitectonic areas in visual cortex with microscopic features of cellular organization and genetic expression, which, despite the complexity of this multiscale correspondence, can be described by a sparse subset (approximately 200) of genes. These findings help pinpoint the genes contributing to healthy cortical development and explicate the cortical biology distinguishing humans from other primates, as well as establishing essential groundwork for understanding future work linking genetic mutations with the function and development of the human brain.

How animal brains evolve to support ecological specialization is poorly understood. A recent PLOS Biology study reveals that glial cells show the most dramatic molecular and cellular changes in the brains of fruit flies adapted to a toxic niche, highlighting their underappreciated role in brain evolution.

Alzheimer’s disease (AD) pathology develops many years before the onset of cognitive symptoms. Two pathological processes—aggregation of the amyloid-β (Aβ) peptide into plaques and the microtubule protein tau into neurofibrillary tangles (NFTs)—are hallmarks of the disease. However, other pathological brain processes are thought to be key disease mediators of Aβ plaque and NFT pathology. How these additional pathologies evolve over the course of the disease is currently unknown. Here we show that proteomic measurements in autosomal dominant AD cerebrospinal fluid (CSF) linked to brain protein coexpression can be used to characterize the evolution of AD pathology over a timescale spanning six decades. SMOC1 and SPON1 proteins associated with Aβ plaques were elevated in AD CSF nearly 30 years before the onset of symptoms, followed by changes in synaptic proteins, metabolic proteins, axonal proteins, inflammatory proteins and finally decreases in neurosecretory proteins. The proteome discriminated mutation carriers from noncarriers before symptom onset as well or better than Aβ and tau measures. Our results highlight the multifaceted landscape of AD pathophysiology and its temporal evolution. Such knowledge will be critical for developing precision therapeutic interventions and biomarkers for AD beyond those associated with Aβ and tau. Proteomic analysis of cerebrospinal fluid from individuals with autosomal dominant Alzheimer’s disease reveals how this complex and chronic disease evolves over many decades.