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Here Shoham and colleagues use deep learning algorithms to disentangle the contributions of visual, visual–semantic and semantic information in human face and object representations. Visual–semantic and semantic algorithms improve prediction of human representations.
A longitudinal study over 12 weeks used computational models on behavioural data from seven cognitive tasks while tracking participants’ mood, habits and activities to understand individual variability. The findings revealed that practice and emotional states significantly influenced various aspects of computational phenotypes, suggesting that apparent unreliability might actually uncover previously unnoticed patterns, supporting a dynamic perspective on cognitive diversity within individuals.
Using mobility data, the authors quantify usage patterns of so-called ‘15-minute cities’ and uncover a worrying trade-off: increased local usage correlates with higher experienced segregation for low-income residents.
This Article makes the case for moving motor learning research outside the lab. Tsay and colleagues show that a large-scale citizen science approach can replicate established findings, reconcile conflicting ideas and identify key demographic predictors of successful motor learning.
The study of personal ornaments worn by Ice Age European hunter-gatherers between 34,000 and 24,000 years ago identifies nine regional groups, which align with the known genetic diversity of that period.
Although action and motor imagery share similar population-wide neural responses in motor cortex, a subset of those responses exists in orthogonal action-unique and imagery-unique subspaces.
Spens and Burgess develop a computational model that shows how the hippocampus encodes episodic memories and replays them to train generative models of the world. Conceptual and sensory representations of experience can then be recombined for imagination and memory.
This systematic review and meta-analysis examines the evidence for transdiagnostic cognitive behavioural psychotherapy for the treatment of emotional disorders.
This collaborative realist review examines evidence for the use of remote measurement technologies for depression in young people, to inform future research and practice.
Using a unique high-quality dataset of 37,000 parent–offspring trios, the authors probe the mechanisms of the so-called indirect genetic effects on educational attainment. Surprisingly, they find that these effects cannot be explained by processes that operate exclusively within the nuclear family and instead are consistent with dynastic social effects.
Using experimental and archival data, Johnson and Proudfoot show that when an idea is novel, disagreement on how valuable it is grows. People may see the higher variability in value evaluation as a sign of risk and be less willing to invest in such an idea.
Monetary incentives were found to be more motivating than psychological interventions for individuals in the United States and the United Kingdom, compared with individuals in China, India, Mexico and South Africa. Among bilinguals on Facebook, money was more motivating in English compared with in Hindi.
The authors analyse over 12 million Australian job postings and find that since the start of the COVID-19 pandemic, there has been an acceleration in the aggregate demand for interpersonal skills.
The authors conducted a genome-wide association study of educational attainment in an East Asian ancestry cohort, and a cross-ancestry meta-analysis with earlier genome-wide association studies from European ancestry populations, providing new insights into correlations and transferability between ancestries.
A genome-wide association study of the human hypothalamus discovers 23 unique loci and examines genetic associations with neuropsychiatric behaviours and disorders.
The authors conducted a comprehensive exome-wide association analysis on eight sleep-related traits. The researchers identified 22 new genes associated with various aspects of sleep, such as chronotype, daytime sleepiness, daytime napping, snoring and sleep apnoea, highlighting the importance of large-scale genomic studies in unravelling the genetic basis of sleep-related traits.
Tuckute et al. use a machine learning approach to identify sentences that either maximally or minimally activate the human language processing network.
In this Stage 2 Registered Report, Blume et al. report results of a study on the contribution of colour vision mechanisms to circadian modulation by light.
Using eye-tracking and representational geometry analyses, Linde-Domingo and Spitzer find that, even when requested to maintain fixation, humans produce involuntary miniature gaze patterns that encode visuospatial information and change over time to reflect the underlying mental process.