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Consistent local activity reductions in autism co-localize with glutamatergic and GABAergic neurotransmission. These patterns resemble brain changes induced by ketamine, highlighting altered excitation-inhibition balance underlying autism’s neurophysiology.

To mark the 20th anniversary of Nature Reviews Neuroscience, in this Viewpoint article we asked some of the researchers who have authored pieces published in the journal in recent years for their views on how the field, and their areas within it, have developed over the past two decades.

Although the number of participants is important for phenotypic prediction accuracy in brain-wide association studies using functional MRI, scanning for at least 30 min offers the greatest cost effectiveness.

Temporal variability of structural-functional coupling (SFC) remains poorly understood. Here, authors show such variability is underpinned by specific transcriptomic and chemoarchitectural signatures, thereby supporting neurocognitive specialization.

Our ability to identify associations between behaviour and brain imaging is important for uncovering markers of cognition and disease. Here, the authors illustrate the importance of the reliability of behavioural measurements to accurately investigate brain-behaviour associations using machine learning.

Here, the authors present the Network Correspondence Toolbox, which enables researchers to examine and report spatial correspondence between their neuroimaging results and widely used brain atlases.

Brain structure scaffolds intrinsic function, supporting cognition and behavioral flexibility. Here, the authors show how macroscale organization of cortical microstructure and resting-state function uncouple in transmodal cortex of humans and macaques.

The default mode network (DMN) is implicated in cognition and behavior. Here, the authors show that the DMN is cytoarchitecturally heterogeneous, it contains regions receptive to input from the sensory cortex and a core relatively insulated from environmental input, and it uniquely balances its output across sensory hierarchies.

The results obtained by seventy different teams analysing the same functional magnetic resonance imaging dataset show substantial variation, highlighting the influence of analytical choices and the importance of sharing workflows publicly and performing multiple analyses.

The human cortex displays an anterior-to-posterior asymmetry, identified via both post-mortem and in vivo microstructural measurements. Microstructural asymmetry is heritable, varies across cortical layers and between sexes, and relates to functional asymmetry and behavior.

Here, the authors use data from the Adolescent Brain Cognitive Development study to show how individual variation in cognition, personality and mental health can be predicted by shared and unique brain network features.

Here, the authors show sex differences in the functional sensory-association axis are associated with differences in functional connectivity profiles and network topology rather than reflecting differences in brain size, microstructural organization, or geodesic distance.

Adolescence is a period of considerable brain remodelling. Here the authors demonstrate that behavioural adaptation to adverse environmental influences links to the microstructural and functional maturation of the adolescent brain.

Here, the authors demonstrate that cortical microstructure in young adults shows marked sex bias, which is most pronounced in paralimbic areas. The effects are put into context with variations in sex hormones and local cytoarchitecture.

By developing the large-scale cortical spatial–rhythmic network analysis, authors identify putative electrophysiological biomarkers for clinical screening of individuals at high familial risk of bipolar disorder onset.

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.

In this paper, the authors present findings demonstrating that variations of the MET gene are associated with specific structural differences in key language regions in individuals with schizophrenia.

An authoritative map of the modules that make up the cerebral cortex of the human brain promises to act as a springboard for greater understanding of brain function and disease. See Article p.171

The brain can be parcellated into areas or networks with different structural or functional properties. Eickhoff, Yeo and Genon describe various imaging-based strategies to parcellate the human brain, including those based on local properties, such as cytoarchitecture, and global properties, such as connectivity.

Individual-level prediction is critical for precision medicine, but many neuroimaging prediction studies are underpowered. Here the authors present a simple yet powerful approach that effectively translates predictive models from big to small data.

The authors study the role of TRIM33 in androgen receptor (AR) transcriptional activity. They show that TRIM33 and AR co-occupy most of their genomic binding sites and TRIM33 loss altered expression of a subset of AR-responsive genes.

Lifestyle factors such as smoking and exercise contribute to the health of the brain during aging, but previous studies have focused on the effects of single lifestyle variables. Here, the authors examine the combined and individual effects of four lifestyle variables on brain structure and function.

While memory is often studied using voluntary recollection, the neural correlates of involuntary memory recall and its effect on cognition are unclear. Here, Ren and colleagues show that the effective connectivity from the anterior hippocampus to the precuneus can predict the strength of involuntary retrieval of episodic memory.

Using meta-analytic techniques, authors report patterns of aberrant functional brain associated with differences in neurophysiology and cognitive and behavioral regulatory mechanisms in men diagnosed with pedophilic disorder to elucidate potential mechanistic and pharmacological interventions.

Cash et al. examined whether coordinates derived from neuroimaging studies might delineate a dysfunctional brain network in unipolar depression rather than isolated neuroanatomical foci. The authors found highly robust distributed brain networks that closely recapitulate clinically meaningful models of depression circuitry.

Responding to widespread concerns about reproducibility, the Organization for Human Brain Mapping created a working group to identify best practices in data analysis, results reporting and data sharing to promote open and reproducible research in neuroimaging. We describe the challenges of open research and the barriers the field faces.

Wu et al. discuss the current and future challenges in the prediction of behavioural traits from brain data.

Individual characteristics tend to over-perform fMRI-based metrics in the prediction of behavioral measures. However, the combination of both metrics can increase predictive accuracy, suggesting that fMRI-based metrics can successfully complement individual characteristics, mainly in large datasets.

The past two decades have witnessed considerable interest in linking interindividual differences in behaviour to differences in brain structure. In this Perspective, Genon et al. examine how the study of brain structure–behaviour associations in healthy populations has developed during this period and the current challenges for this field.

An evolutionary study in 34 primates provides evidence for a primate-general expansion of cerebellar crura I-II. Specifically, common accelerated scaling may directly explain previously reported high volumetric fractions of the human crura I-II.

Andrew Reid et al. use publicly available data to present a method for deriving tract-specific statistics based on diffusion-weighted MRI, based upon arbitrarily-defined regions of interest. Their approach enables them to report both negative and positive associations between age and tract-specific anisotropy along with more moderate sex differences and age-by-sex interactions.

Using machine learning approaches, looking at the predictive utility of functional connectivity estimates show that time points of intermediate co-fluctuation levels have both high subject specificity and predictive capacity.