Visual perception of highly memorable images is mediated by a distributed network of ventral visual regions that enable a late memorability response

Behavioral and neuroscience studies in humans and primates have shown that memorability is an intrinsic property of an image that predicts its strength of encoding into and retrieval from memory. While previous work has independently probed when or where this memorability effect may occur in the human brain, a description of its spatiotemporal dynamics is missing. Here, we used representational similarity analysis (RSA) to combine functional magnetic resonance imaging (fMRI) with source-estimated magnetoencephalography (MEG) to simultaneously measure when and where the human cortex is sensitive to differences in image memorability. Results reveal that visual perception of High Memorable images, compared to Low Memorable images, recruits a set of regions of interest (ROIs) distributed throughout the ventral visual cortex: a late memorability response (from around 300 ms) in early visual cortex (EVC), inferior temporal cortex, lateral occipital cortex, fusiform gyrus, and banks of the superior temporal sulcus. Image memorability magnitude results are represented after high-level feature processing in visual regions and reflected in classical memory regions in the medial temporal lobe (MTL). Our results present, to our knowledge, the first unified spatiotemporal account of visual memorability effect across the human cortex, further supporting the levels-of-processing theory of perception and memory.

Symmetry Control of Unconventional Spin-Orbit Torques in IrO2

Spin-orbit torques generated by a spin current are key to magnetic switching in spintronic applications. The polarization of the spin current dictates the direction of switching required for energy-efficient devices. Conventionally, the polarizations of these spin currents are restricted to be along a certain direction due to the symmetry of the material allowing only for efficient in-plane magnetic switching. Unconventional spin-orbit torques arising from novel spin current polarizations, however, have the potential to switch other magnetization orientations such as perpendicular magnetic anisotropy, which is desired for higher density spintronic-based memory devices. Here, it is demonstrated that low crystalline symmetry is not required for unconventional spin-orbit torques and can be generated in a nonmagnetic high symmetry material, iridium dioxide (IrO2 ), using epitaxial design. It is shown that by reducing the relative crystalline symmetry with respect to the growth direction large unconventional spin currents can be generated and hence spin-orbit torques. Furthermore, the spin polarizations detected in (001), (110), and (111) oriented IrO2 thin films are compared to show which crystal symmetries restrict unconventional spin transport. Understanding and tuning unconventional spin transport generation in high symmetry materials can provide a new route towards energy-efficient magnetic switching in spintronic devices.

Plasmonic Nanoparticle Lattice Devices for White-Light Lasing

A plasmonic nanolaser architecture that can produce white-light emission is reported. A laser device is designed based on a mixed dye solution used as gain material sandwiched between two aluminum nanoparticle (NP) square lattices of different periodicities. The (±1, 0) and (±1, ±1) band-edge surface lattice resonance (SLR) modes of one NP lattice and the (±1, 0) band-edge mode of the other NP lattice function as nanocavity modes for red, blue, and green lasing respectively. From a single aluminum NP lattice, simultaneous red and blue lasing is realized from a binary dye solution, and the relative intensities of the two colors are controlled by the volume ratio of the dyes. Also, a laser device is constructed by sandwiching dye solutions between two Al NP lattices with different periodicities, which enables red-green and blue-green lasing. With a combination of three dyes as liquid gain, red, green, and blue lasing for a white-light emission profile is realized.

Remote Water-to-Air Eavesdropping with a Phase-Engineered Impedance Matching Metasurface

Efficiently receiving underwater sound remotely from air is a long-standing challenge in acoustics hindered by the large impedance mismatch at the water-air interface. Here, a phase-engineered water-air impedance matching metasurface is proposed and experimentally demonstrated for remote and efficient water-to-air eavesdropping. The judiciously designed metasurface with near-unity transmission efficiency, long monitoring distance, and high mechanical stiffness is capable of making the water-air interface acoustically transparent and, at the same time, freewheelingly patterning the transmitted wavefront. This enables efficient control over the effective spatial location of a distant airborne sensor such that it can measure underwater signals with large signal-to-noise ratios as if placed close to the physical underwater source. Such airborne eavesdropping of underwater sound is experimentally demonstrated with a measured sensitivity enhancement of nearly 10⁴ at 8 kHz, far from achievable with the current state-of-the-art methods. Moreover, the opportunities of using the proposed metasurface for cross-media orbital-angular-momentum-multiplexed communication and underwater acoustic window are also demonstrated. This metasurface opens new avenues for communication and sensing in inhomogeneities with totally reflective interfaces, which may be translated to nano-optics and radio frequencies.

Size-Induced Ferroelectricity in Antiferroelectric Oxide Membranes

Despite extensive studies on size effects in ferroelectrics, how structures and properties evolve in antiferroelectrics with reduced dimensions still remains elusive. Given the enormous potential of utilizing antiferroelectrics for high-energy-density storage applications, understanding their size effects will provide key information for optimizing device performances at small scales. Here, the fundamental intrinsic size dependence of antiferroelectricity in lead-free NaNbO₃ membranes is investigated. Via a wide range of experimental and theoretical approaches, an intriguing antiferroelectric-to-ferroelectric transition upon reducing membrane thickness is probed. This size effect leads to a ferroelectric single-phase below 40 nm, as well as a mixed-phase state with ferroelectric and antiferroelectric orders coexisting above this critical thickness. Furthermore, it is shown that the antiferroelectric and ferroelectric orders are electrically switchable. First-principle calculations further reveal that the observed transition is driven by the structural distortion arising from the membrane surface. This work provides direct experimental evidence for intrinsic size-driven scaling in antiferroelectrics and demonstrates enormous potential of utilizing size effects to drive emergent properties in environmentally benign lead-free oxides with the membrane platform.

Knots are not for naught: Design, properties, and topology of hierarchical intertwined microarchitected materials

Lightweight and tough engineered materials are often designed with three-dimensional hierarchy and interconnected structural members whose junctions are detrimental to their performance because they serve as stress concentrations for damage accumulation and lower mechanical resilience. We introduce a previously unexplored class of architected materials, whose components are interwoven and contain no junctions, and incorporate micro-knots as building blocks within these hierarchical networks. Tensile experiments, which show close quantitative agreements with an analytical model for overhand knots, reveal that knot topology allows a new regime of deformation capable of shape retention, leading to a ~92% increase in absorbed energy and an up to ~107% increase in failure strain compared to woven structures, along with an up to ~11% increase in specific energy density compared to topologically similar monolithic lattices. Our exploration unlocks knotting and frictional contact to create highly extensible low-density materials with tunable shape reconfiguration and energy absorption capabilities.

Combinatorial characterizations and impossibilities for higher-order homophily

Homophily is the seemingly ubiquitous tendency for people to connect and interact with other individuals who are similar to them. This is a well-documented principle and is fundamental for how society organizes. Although many social interactions occur in groups, homophily has traditionally been measured using a graph model, which only accounts for pairwise interactions involving two individuals. Here, we develop a framework using hypergraphs to quantify homophily from group interactions. This reveals natural patterns of group homophily that appear with gender in scientific collaboration and political affiliation in legislative bill cosponsorship and also reveals distinctive gender distributions in group photographs, all of which cannot be fully captured by pairwise measures. At the same time, we show that seemingly natural ways to define group homophily are combinatorially impossible. This reveals important pitfalls to avoid when defining and interpreting notions of group homophily, as higher-order homophily patterns are governed by combinatorial constraints that are independent of human behavior but are easily overlooked.

Low-voltage magnetoelectric coupling in membrane heterostructures

Strain-mediated magnetoelectric (ME) coupling in ferroelectric (FE)/ferromagnetic (FM) heterostructures offers a unique opportunity for both fundamental scientific research and low-power multifunctional devices. Relaxor-FEs, such as (1 − x)Pb(Mg_1/3Nb_2/3)O₃-(x)PbTiO₃ (PMN-xPT), are ideal FE layer candidates because of their giant piezoelectricity. However, thin films of PMN-PT suffer from substrate clamping, which substantially reduces piezoelectric in-plane strains. Here, we demonstrate low-voltage ME coupling in an all-thin-film heterostructure that uses the anisotropic strains induced by the (011) orientation of PMN-PT. We completely remove PMN-PT films from their substrate and couple with FM Ni overlayers to create membrane PMN-PT/Ni heterostructures showing 90° Ni magnetization rotation with 3 V PMN-PT bias, much less than the bulk PMN-PT ~100-V requirement. Scanning transmission electron microscopy and phase-field simulations clarify the membrane response. These results provide a crucial step toward understanding the microstructural behavior of PMN-PT thin films for use in piezo-driven ME heterostructures.

Origami and materials science

Origami, the ancient art of folding thin sheets, has attracted increasing attention for its practical value in diverse fields: architectural design, therapeutics, deployable space structures, medical stent design, antenna design and robotics. In this survey article, we highlight its suggestive value for the design of materials. At continuum level, the rules for constructing origami have direct analogues in the analysis of the microstructure of materials. At atomistic level, the structure of crystals, nanostructures, viruses and quasi-crystals all link to simplified methods of constructing origami. Underlying these linkages are basic physical scaling laws, the role of isometries, and the simplifying role of group theory. Non-discrete isometry groups suggest an unexpected framework for the design of novel materials. This article is part of the theme issue 'Topics in mathematical design of complex materials'.

Recurrent network dynamics shape direction selectivity in primary auditory cortex

Detecting the direction of frequency modulation (FM) is essential for vocal communication in both animals and humans. Direction-selective firing of neurons in the primary auditory cortex (A1) has been classically attributed to temporal offsets between feedforward excitatory and inhibitory inputs. However, it remains unclear how cortical recurrent circuitry contributes to this computation. Here, we used two-photon calcium imaging and whole-cell recordings in awake mice to demonstrate that direction selectivity is not caused by temporal offsets between synaptic currents, but by an asymmetry in total synaptic charge between preferred and non-preferred directions. Inactivation of cortical somatostatin-expressing interneurons (SOM cells) reduced direction selectivity, revealing its cortical contribution. Our theoretical models showed that charge asymmetry arises due to broad spatial topography of SOM cell-mediated inhibition which regulates signal amplification in strongly recurrent circuitry. Together, our findings reveal a major contribution of recurrent network dynamics in shaping cortical tuning to behaviorally relevant complex sounds.

To Petabytes and beyond: recent advances in probabilistic and signal processing algorithms and their application to metagenomics

As computational biologists continue to be inundated by ever increasing amounts of metagenomic data, the need for data analysis approaches that keep up with the pace of sequence archives has remained a challenge. In recent years, the accelerated pace of genomic data availability has been accompanied by the application of a wide array of highly efficient approaches from other fields to the field of metagenomics. For instance, sketching algorithms such as MinHash have seen a rapid and widespread adoption. These techniques handle increasingly large datasets with minimal sacrifices in quality for tasks such as sequence similarity calculations. Here, we briefly review the fundamentals of the most impactful probabilistic and signal processing algorithms. We also highlight more recent advances to augment previous reviews in these areas that have taken a broader approach. We then explore the application of these techniques to metagenomics, discuss their pros and cons, and speculate on their future directions.

Nucleic-Acid Structures as Intracellular Probes for Live Cells

The chemical composition of cells at the molecular level determines their growth, differentiation, structure, and function. Probing this composition is powerful because it provides invaluable insight into chemical processes inside cells and in certain cases allows disease diagnosis based on molecular profiles. However, many techniques analyze fixed cells or lysates of bulk populations, in which information about dynamics and cellular heterogeneity is lost. Recently, nucleic-acid-based probes have emerged as a promising platform for the detection of a wide variety of intracellular analytes in live cells with single-cell resolution. Recent advances in this field are described and common strategies for probe design, types of targets that can be identified, current limitations, and future directions are discussed.

In situ unsupervised learning using stochastic switching in magneto-electric magnetic tunnel junctions

Spiking neural networks (SNNs) offer a bio-plausible and potentially power-efficient alternative to conventional deep learning. Although there has been progress towards implementing SNN functionalities in custom CMOS-based hardware using beyond Von Neumann architectures, the power-efficiency of the human brain has remained elusive. This has necessitated investigations of novel material systems which can efficiently mimic the functional units of SNNs, such as neurons and synapses. In this paper, we present a magnetoelectric-magnetic tunnel junction (ME-MTJ) device as a synapse. We arrange these synapses in a crossbar fashion and perform in situ unsupervised learning. We leverage the capacitive nature of write-ports in ME-MTJs, wherein by applying appropriately shaped voltage pulses across the write-port, the ME-MTJ can be switched in a probabilistic manner. We further exploit the sigmoidal switching characteristics of ME-MTJ to tune the synapses to follow the well-known spike timing-dependent plasticity (STDP) rule in a stochastic fashion. Finally, we use the stochastic STDP rule in ME-MTJ synapses to simulate a two-layered SNN to perform image classification tasks on a handwritten digit dataset. Thus, the capacitive write-port and the decoupled-nature of read-write path of ME-MTJs allow us to construct a transistor-less crossbar, suitable for energy-efficient implementation of in situ learning in SNNs. This article is part of the theme issue 'Harmonizing energy-autonomous computing and intelligence'.

Atomically thin three-dimensional membranes of van der Waals semiconductors by wafer-scale growth

We report wafer-scale growth of atomically thin, three-dimensional (3D) van der Waals (vdW) semiconductor membranes. By controlling the growth kinetics in the near-equilibrium limit during metal-organic chemical vapor depositions of MoS₂ and WS₂ monolayer (ML) crystals, we have achieved conformal ML coverage on diverse 3D texture substrates, such as periodic arrays of nanoscale needles and trenches on quartz and SiO₂/Si substrates. The ML semiconductor properties, such as channel resistivity and photoluminescence, are verified to be seamlessly uniform over the 3D textures and are scalable to wafer scale. In addition, we demonstrated that these 3D films can be easily delaminated from the growth substrates to form suspended 3D semiconductor membranes. Our work suggests that vdW ML semiconductor films can be useful platforms for patchable membrane electronics with atomic precision, yet large areas, on arbitrary substrates.