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Using multimodal spinal cord and brain imaging, this study reveals pronounced age-related changes in the spinal somatosensory pathway and shared central nervous system aging mechanisms, including gray matter loss and decreased functional segregation.

This study comprehensively maps neuropeptide systems in the human brain to elucidate their organizational principles and shows how neuropeptide architecture is linked to behavior and evolution.

Brain network architecture may balance cooperation and competition across circuits. Here the authors use computational whole-brain modeling across three species to show that models with competition are more realistic, more personalized and perform better.

Changes to structural and functional connectivity can give rise to neurodegeneration and neurodevelopmental diseases. Here the authors investigate molecular and connectomic patterns in 13 different neurological, psychiatric and neurodevelopmental diseases from the ENIGMA consortium.

Patterns of gene expression vary across the human cerebral cortex. Here, Misic et al. reveal a ventromedial–dorsolateral gradient of gene assemblies and show that this corresponds to a functional gradient between affective and perceptual domains.

Baracchini et al. reveal that temporal variability in fMRI brain signals encodes biologically meaningful information across spatial and temporal scales, highlighting its role in healthy brain function and systems-level organization.

Despite rapid exploitation of the opportunities that contextualization of brain maps affords, potential limitations have received little attention. In this Roadmap, Royer et al. provide practical guidelines operating at the level of study design, analysis pipelines and interpretation of findings to encourage the development of best practices in data contextualization in neuroscience.

This study proposes an algorithm for generating randomized networks that preserve the weighted degree sequence. The procedure outperforms standard rewiring algorithms and extends to multiple network types, including directed and signed networks.

Hansen et al. used in vivo functional imaging of the human brainstem and cortex to demonstrate how the brainstem shapes cortical functional architecture, including oscillatory dynamics, cognitive specialization and hierarchical organization.

Comparisons of real networks with null models enable researchers to test how statistically unexpected a particular network feature is. In this Review, Váša and Mišić describe different null-model approaches and instantiations, as well as their emerging uses and limitations.

A framework for training artificial neural networks in physical space allows neuroscientists to build networks that look and function like real brains.

neuromaps is a toolbox for accessing, transforming and comparing human neuroimaging data.

We all have the intuition that our brain makes us unique. Here, the authors show that seconds of brain activity are sufficient to differentiate an individual, even when recorded weeks or months apart.

Using multimodal MRI-derived white-matter features combined with BOLD-fMRI and MEG connectivity, Nelson et al. demonstrate that white-matter myelin is a major, frequency-dependent predictor of large-scale functional connectivity across brain networks.

Brain connectivity patterns shape computational capacity of biological neural networks, however mapping empirically measured connectivity to artificial networks remains challenging. The authors present a toolbox for implementing biological neural networks as artificial reservoir networks. The toolbox allows for a variety of empirical/measured connectomes and is equipped with various dynamical systems, and cognitive tasks.

How macroscale connectivity relates to regional micro-architecture is poorly understood. Here, the authors annotate brain networks with microarchitectural attributes, finding that the interplay between connection patterns and biological annotations shape regional functional specialization.

How neurophysiological dynamics are organized across the cortex and their relationship with cortical micro-architecture is not well understood. Here, the authors find the dominant axis of neurophysiological dynamics reflects characteristics of the power spectrum and the linear correlation structure of the signal, and that spatial variation in neurophysiological dynamics is colocalized with multiple micro-architectural features.

Individuals with schizophrenia show reduced structural similarity in temporal, cingulate, and insular lobes, especially those with worse cognition and symptoms, affecting late maturing association areas with low metabolism and high neurotransmission.

HippoMaps provides an open-source resource for studying the human hippocampus at different scales and with different modalities such as histology, fMRI, structural MRI and EEG.

The relationship between brain organization, connectivity and computation is not well understood. The authors construct neuromorphic artificial neural networks endowed with biological connection patterns derived from diffusion-weighted imaging. The neuromorphic networks are trained to perform a memory task, revealing an interaction between network structure and dynamics.

In this Analysis, Liu et al. benchmark more than 200 pairwise statistics for functional brain connectivity in tasks such as hub mapping, distance relationships, structure–function coupling and behavior prediction, revealing varying effectiveness for specific neurophysiological applications.

This study shows that brain connectivity changes in Huntington’s disease begin decades before symptoms, shifting from hyper- to hypoconnectivity, with links to specific neurotransmitter systems specially in granular and infragranular cortical layers.

Incorporating spatial information into the optimal control framework makes models of brain state transitions more realistic and leads to reductions in the effort needed to transition from one brain state to another.

Each individual is unique and so is their brain activity. Using brain fingerprinting from functional MRI during anaesthesia, Luppi et al. find that human brains become temporarily more difficult to identify and tell apart when unconscious.

How brain networks process dynamic naturalistic stimuli is not well understood. Here, the authors use machine learning algorithms to show that brain states in the default network capture the semantic aspects of an unfolding narrative during movie watching.

Hansen et al. compile and share an atlas of neurotransmitter receptor/transporter densities in the human cortex and show that receptor achitecture reflects brain structure, function, dynamics, cognitive specialization and disease vulnerability.

Here, the authors use fMRI data to update connectomes with new, asymmetric, and signed weights, leading to an intuitive brain structure that is aligned to functional brain systems, more efficient, subject-specific, state-dependent and varies with age

An analysis of neuroimaging data across mental health, neurodegenerative, psychiatric and neurodevelopmental diagnostic categories highlights how brain network organization and chemoarchitecture interact to shape cognitive topographies.

The neurobiology of human brain development and aging is hard to study in vivo. The authors report on distinct spatial associations between brain morphology and cellular as well as molecular brain properties throughout neurodevelopment and aging.

Brain network structure and local biology jointly shape ALS atrophy. Disease epicenters show transcriptomic enrichment for mitochondrial function, endothelial cells and pericytes. Individual variation in epicenters aligns with clinical symptoms.

How regional anatomy shapes function is not well understood. Here, the authors evaluate the performance of 40 communication models in predicting functional connectivity, and find regional heterogeneity in terms of fit and optimal model, and that regional coupling varies over the human lifespan.

The brain comprises complex structural and functional networks, but much remains to be determined regarding how these networks support the communication processes that underlie neuronal computation. In this Review, Avena-Koenigsberger, Misic and Sporns discuss the network basis of communication dynamics in the brain.

Glioblastoma is thought to arise from neural stem cells. Here, to investigate this, the authors use single-cell RNA-sequencing to compare glioblastoma to the fetal human brain, and find a similarity between glial progenitor cells and a subpopulation of glioblastoma cells.

Humans can quickly learn to efficiently execute tasks yet how the brain activity is dynamically reconfigured during this process remains unknown. Here the authors demonstrate that large-scale functional brain networks are reorganized flexibly to support rapid task automation.

High-resolution maps of biological annotations in the brain are increasingly generated and shared. In this Review, Bazinet and colleagues discuss how brain connectomes can be enriched with biological annotations to address new questions about brain network organization.

Amyloid-β (Aβ) deposition occurs in Alzheimer's disease but its relation to disease features such as local brain hypometabolism or cognitive decline is unclear. Here, the authors show that Aβ aggregation in the brain’s default mode network leads to hypometabolism in distant but functionally connected areas.

Temporal unwrapping analysis of diffusion weighted MRI connectivity and functional MRI scans reveals that the coupling between structure and function in the human brain is regionally heterogeneous and provides a framework to evaluate these relationships from a dynamic perspective.

Guidance is lacking on how to best integrate sex, gender and social and structural determinants of health into neuroscience research on brain resilience in ageing and dementia. In this Roadmap article, Rajah et al. propose a way forward for conducting more inclusive research in this field.

Coletta et al. integrate patient-specific intracranial stimulations in the white matter with normative brain connectivity data. Findings reveal that intracranial driven network mapping is an accurate predictor of both neurological impairments in stroke patients and post-operative language recovery trajectories in glioma patients.

How similar are the behavioural profiles of people with obesity, uncontrolled eating, and addiction? In a meta-analysis of facet-based phenotype profiles, Vainik et al. find that uncontrolled eating and addiction have more similarities than obesity and addiction.

This study reveals that obesity-related brain changes evolve across the lifespan and involve mitochondrial and inflammatory genes, as well as neurochemical and cognitive alterations.