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A modularized open-source pipeline for invasive brain signal decoding bridges the gap between closed-loop neuromodulation and clinical brain–computer interface approaches in a large patient cohort.

The precise role of the spinal cord in copulatory behavior remains not fully understood. Here, authors identify a population of spinal galanin-expressing neurons that regulate sexual arousal and mating in male mice, revealing a broader role for spinal circuits in copulation than previously acknowledged.

Ca2 + -ATPases in the plasma membrane extrude Ca2+ ions from the cytosol to the extracellular space and thus terminate Ca2 + -signals and control Ca2 + -homeostasis. Here, Constantin et al. show that these pumps operate at rates of more than 5000 cycles/s.

Genome-wide association meta-analyses of attention-deficit/hyperactivity disorder symptom measures and clinical diagnoses identify new risk loci, highlight putative effector genes and yield improved polygenic risk scores.

A coupled-oscillator-based all-to-all-connected Ising machine manufactured using 65-nm complementary metal–oxide–semiconductor (CMOS) technology and operating at room temperature can efficiently solve dense combinatorial optimization problems that cannot be effectively mapped or solved by quantum annealers.

If correlations decay exponentially in a one-dimensional quantum many-body system, then entanglement satisfies an area law. The intuitive explanation for this turns out to be wrong, but the statement is nevertheless true, as demonstrated by a proof based on quantum information theory.

The presence of correlations can strongly affect the evolution of a quantum system. Here, the authors directly observe differences in the dynamics of two spins-1/2 systems in an NMR setup depending on the correlations of the initial state, including differences in energy flow and mutual information.

Neuromorphic hardware has typically focused on accelerating vector–matrix multiplication, but broader and more disruptive approaches will be required to reimagine AI hardware.

The Gaussian minimum entropy conjecture—a long-standing open question—has now been proved for single-mode phase-insensitive bosonic Gaussian channels. This establishes the ultimate achievable bit rate under an energy constraint and provides long-awaited proof that the single-letter classical capacity of these channels is additive.

An artificial intelligence hardware approach that uses the adaptive reservoir computation of biological neural networks in a brain organoid can perform tasks such as speech recognition and nonlinear equation prediction.

Using well-calibrated statistical methods the authors jointly analyze Undiagnosed Diseases Network genomes, identifying known and novel disease genes. Software is publicly available to support future cross-cohort rare disease discovery efforts.

A phenomenon of dynamical Aharonov-Bohm caging arises in a Z2 lattice gauge theory, as a result of vison-like configurations of the gauge-magnetic flux threading elementary plaquettes of the lattice. The authors demonstrate that particles are tightly confined inside the cages, which become mobile in the presence of quantum fluctuations, leading to a Luttinger Liquid or to a Mott insulator of the confined mesons.

Hunter et al. use RNA labelling to investigate RNA transfer between organs in mice. They show that RNA potentially moves en masse from liver to kidney and that this movement is augmented in acute liver injury, although the physiological relevance of the phenomenon is not yet known.

Continuous variable quantum key distribution allows secure communication that is more robust against channel losses than discrete approaches, yet is strongly affected by noise. Madsenet al.devise a continuous scheme for modulated entangled states that is more tolerant to noise and loss than other protocols.

Monolithic 3D integration of electronics based on fully 2D materials is demonstrated in the performance of artificial intelligence tasks.

Continuous-variable remote state preparation in the microwave domain would allow to leverage the superconducting technology for quantum networks applications. Here, the authors show how to deterministically prepare squeezed Gaussian states across 35 cm using previously shared entanglement.

The interaction of waves with periodic structures is a feature central to many areas of physics from quantum mechanics to acoustics. Here, the authors numerically and experimentally demonstrate the presence of Rayleigh-Bloch waves in the regime above the first cut-off using acoustic gratings.

The epigenetic and transcriptional roles of Nucleoporin 98 (NUP98) fusion oncoproteins in driving pediatric acute myeloid leukemia (AML) remain to be explored. Here, the authors identify a core set of genes regulated by NUP98::KDM5A and suggest CDK12 as a potential therapeutic vulnerability.

The wetting on soft surfaces is less understood than that on rigid ones because it is challenging to quantify substrate deformation. Here, the authors monitor the deformation over a large range of droplet velocities, and propose a dynamical model that captures contact line motion and depinning.

Single-cell RNAseq can struggle to capture cellular heterogeneity due to the relatively low expression of biologically meaningful transcripts. Here the authors present an approach called scCLEAN, which uses CRISPR/Cas9 to target and remove certain ubiquitous transcripts, thereby enhancing the detection of low-abundance transcripts.

Ferroelectric domain switching on the surface of a lithium niobate thin film can be induced by the tip of a scanning probe microscope, and gives rise to both regular and chaotic spatiotemporal patterns. Moreover, the long-range interactions that govern these phenomena can be tuned by varying temperature, humidity, domain spacing and tip bias.

Measurement-induced quantum phases provide prime examples of non-trivial many-body dynamics and collective phenomena, but their experimental detection is difficult due to the post-selection barrier. Here, the authors provide a spin-wave-based approach to monitored quantum dynamics in long-range interacting systems, overcoming this challenge.

Glucose uptake in astrocytes is thought to rely on GLUT1. Here, the authors show that adult mice tolerate astrocyte-specific GLUT1 deletion, which increases astrocytic glucose metabolism and confers neuroprotection in a model of stroke.

There are limited in vitro and in vivo models to study human fetal exposure to environmental noise. Here, the authors develop a computational model to quantify fetal exposure to acoustic fields, obtaining acoustic transfer characteristics across the human audio range.

Dopaminergic medication and deep brain stimulation exert a shared therapeutic modulation of cortex-subthalamic nucleus network activity in Parkinson’s disease, through a suppression of high beta synchrony mediated by the hyperdirect pathway.

Device-level complexity represents a big shortcoming for the hardware realization of analogue memory-based deep neural networks. Mackin et al. report a generalized computational framework, translating software-trained weights into analogue hardware weights, to minimise inference accuracy degradation.

Cumulus is a cloud-based framework enabling large-scale single-cell and single-nucleus RNA sequencing data analysis.

A big challenge for artificial intelligence is to gain the ability of learning by experience like biological systems. Here Bianchi et al. propose a hardware neural network based on resistive-switching synaptic arrays which dynamically adapt to the environment for autonomous exploration.

Tuft cells constitutively express IL-25 to sustain ILC2 homeostasis in the intestine, but mechanisms driving IL-25 secretion have been unclear. Here, Feng et al. find that tuft cells express IL-17RB, which is required to regulate the bioavailability of IL-25 and to restrain the activation of ILC2s during homeostasis.

Deep brain stimulation (DBS) is a highly effective treatment option for movement disorders and is also being explored for other brain disorders. This Perspective proposes a unified framework, termed adaptive circuit targeting, which combines adaptive and connectomic DBS to enable decoding of symptom severity from brain signals and activation of relevant symptom-response circuits.