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Cognitive scientist explains how we ‘see’ what isn’t real

Imagine this: A person walks into a room and knocks a ball off a table.

Did you imagine the gender of the person? The color of the ball? The position of the person relative to the ball?

Yes and no, says cognitive scientist Tomer Ullman, the Morris Kahn Associate Professor of Psychology, who with Halely Balaban recently published a paper titled “The Capacity Limits of Moving Objects in the Imagination.” If you’re like most people, you probably thought about some of these things, but not others. People build mental imagery hierarchically, starting with the ideas of “person,” “room,” “ball,” and “table,” then placing them in relation to one another in space, and only later filling in details like color.

“Our imaginations are actually patchwork and fuzzy and not filled in,” he said. His theory: Your mind’s eye might be lazier than you think. But that’s not necessarily a bad thing. “You leave things out until you need them.”

For the latest installment of “One Word Answer,” we asked Ullman to elaborate further on the current scientific thinking behind “imagination.”

Less like a picture, more like a video game? “Our imaginations are actually patchwork and fuzzy and not filled in,” says Tomer Ullman.

Continue reading “Cognitive scientist explains how we ‘see’ what isn’t real” | >

False alarm in newborn screening: How zebrafish can prevent unnecessary spinal muscular atrophy therapies

A positive newborn screening for spinal muscular atrophy (SMA) is currently considered a medical emergency. Without early treatment, severe disability or death in infancy are likely. However, research findings from Germany and Australia now show that in rare cases, a positive screening result can be a genetic false alarm. Researchers have discovered that functional tests in a zebrafish model may enable fast and reliable clinical decision-making in cases of unclear genetic findings.

The study “SMN1 variants identified by false positive SMA newborn screening tests: Therapeutic hurdles, and functional and epidemiological solutions” was published in the American Journal of Human Genetics and another study, “Clinical relevance of zebrafish for gene variants testing. Proof-of-principle with SMN1/SMA,” in EMBO Molecular Medicine. The collaborative research team was led by Professor Dr. Brunhilde Wirth, Director of the University of Cologne’s Institute of Human Genetics and Principal Investigator at the Center for Molecular Medicine Cologne (CMMC) and Dr. Jean Giacomotto from Griffith University’s Institute for Biomedicine and Glycomics, Brisbane, Australia.

The scientists examined two newborns—a girl from Germany and a boy from Australia—in whom routine screening initially failed to detect the SMN1 gene. A missing SMN1 gene is the main genetic trigger of SMA. This diagnosis would normally result in immediate treatment, as it would be assumed that the child’s life is in danger. However, further genetic analysis revealed a surprising finding: both children carried rare SMN1 variants that had not been detected by the screening test. It remains unclear whether these variants cause the disease.

From the lab to the living room: Decoding Parkinson’s patients’ movements in the real world

Scientists have traditionally studied how the brain controls movement by asking patients to perform structured tasks while connected to multiple sensors in a lab. While these studies have provided important insights, these experiments do not fully capture how the brain functions during everyday activities, be it walking to the kitchen for a snack or strolling through a park.

For people living with Parkinson’s disease, this gap between laboratory research and real-world behavior has limited efforts to improve gait symptoms outside of the clinic.

Issues and Challenges in NSCLC Immunotherapy

Immunotherapy has revolutionized lung cancer treatment in the past decade. By reactivating the host’s immune system, immunotherapy significantly prolongs survival in some advanced lung cancer patients. However, resistance to immunotherapy is frequent, which manifests as a lack of initial response or clinical benefit to therapy (primary resistance) or tumor progression after the initial period of response (acquired resistance). Overcoming immunotherapy resistance is challenging owing to the complex and dynamic interplay among malignant cells and the defense system. This review aims to discuss the mechanisms that drive immunotherapy resistance and the innovative strategies implemented to overcome it in lung cancer.

The discovery of the immune checkpoint inhibitors (ICIs), represented by the monoclonal antibodies that block cytotoxic T−lymphocyte−associated protein 4 (CTLA-4), programmed death protein 1 (PD-1), and programmed death protein ligand 1 (PD-L1), has revolutionized the therapeutic landscape of lung cancer. The significant survival benefit derived from ICI-containing treatment has established it as the mainstay first-line therapy in patients with advanced or locally advanced non-small cell lung cancer (NSCLC) and extensive small-cell lung cancer (SCLC). Unprecedented long-term clinical benefit or even, in some cases, a complete recovery has been witnessed in lung cancer, particularly in patients with high PD-L1-expressing tumors (1– 3). Currently, investigations are under way aimed at integrating immunotherapy in the treatment of early-stage lung cancer.

However, most patients with NSCLC develop primary resistance during ICI monotherapy and only 15 to 20% achieve partial or complete response (3). Acquired resistance also occurs in initially responding patients with advanced NSCLC treated with ICIs, after a median progression-free survival (PFS) of 4–10 months (4– 9). The mechanisms of resistance to immunotherapy are not yet fully understood, and methods to overcome them must be developed. Herein, we discuss the pathways driving resistance to immunotherapy in lung cancer to help clinicians in their current practice, as well as identify future research priorities and treatment strategies.

Chemical Reaction Pattern Shines Like the Sun

For a phenomenon like a wildfire burning through a forest or a disease moving through a population, the resulting patterns can sometimes be modeled using a so-called reaction–diffusion system—an experiment where a chemical reaction front moves through a region full of reactants. Now Anne De Wit of the Université Libre de Bruxelles and her colleagues have demonstrated that new patterns can be revealed when the reactants flow against the direction of the front’s propagation, causing it to freeze in place [1]. Their “sun-ray” pattern is the first one discovered this way, but the technique could generate other patterns that might replicate behavior in forest fires or epidemics.

Two years ago, De Wit and her colleagues brought a propagating reaction front to a standstill by slowly and continually injecting a reactant into the center of a disk-shaped chamber filled with the other reactant, against the front’s inward propagation [2]. The stopping occurred when the outward flow matched the rate at which the inner reactant was consumed. De Wit says that a stationary front allows more control and thus more careful study of patterns than a propagating front.

As a demonstration of this control, the researchers have now used reactants with different diffusion rates in the same outward-flow setup. In this case, the stationary front developed ripples—an effect previously seen in propagating fronts. The researchers also observed radial “rays”—narrow regions of higher concentration of one of the reactants. They showed in simulations and experiments that properties of the front can be precisely controlled by varying the flow rate.

Time crystals could become accurate and efficient timekeepers

Time crystals could one day provide a reliable foundation for ultra-precise quantum clocks, new mathematical analysis has revealed. Published in Physical Review Letters, the research was led by Ludmila Viotti at the Abdus Salam International Center for Theoretical Physics in Italy. The team shows that these exotic systems could, in principle, offer higher timekeeping precision than more conventional designs, which rely on external excitations to generate reliably repeating oscillations.

In physics, a crystal can be defined as any system that hosts a repeating pattern in its microscopic structure. In conventional crystals, this pattern repeats in space—but more exotic behavior can emerge in materials whose configurations repeat over time. Known as “time crystals,” these systems were first demonstrated experimentally in 2016. Since then, researchers have been working to understand the full extent of their possible applications.

The IceCube experiment is ready to uncover more secrets of the universe

The name “IceCube” not only serves as the title of the experiment, but also describes its appearance. Embedded in the transparent ice of the South Pole, a three-dimensional grid of more than 5,000 extremely sensitive light sensors forms a giant cube with a volume of one cubic kilometer. This unique arrangement serves as an observatory for detecting neutrinos, the most difficult elementary particles to detect.

In order to detect neutrinos, they must interact with matter, creating charged particles whose light can be measured. These light measurements can be used to determine information about the properties of neutrinos. However, the probability of neutrinos interacting with matter is extremely low, so they usually pass through it without leaving a trace, which makes their detection considerably more difficult.

For this reason, a large detector volume is required to increase the probability of interaction, and state-of-the-art technology is crucial for detecting such rare interactions.

How a key receptor tells apart two nearly identical drug molecules

G-protein-coupled receptors (GPCRs) are one of the largest families of cell surface proteins in the human body that recognize hormones, neurotransmitters, and drugs. These receptors regulate a wide range of physiological processes and are the targets of more than 30% of currently marketed drugs. The histamine H1 receptor (H1R) is one such GPCR subtype that plays a key role in mediating allergic reactions, inflammation, vascular permeability, airway constriction, wakefulness, and cognitive functions in the human body. While antihistamines primarily target H1R, current drugs can exhibit limited therapeutic efficacy, prompting researchers to look at H1R ligands from new perspectives.

Recently, the importance of drug design based not only on the affinity or binding energy between a compound and its target protein, but also on its components, enthalpy, and entropy, has been recognized as crucial for rational drug design. In particular, enthalpy–entropy compensation has emerged as a key concept for understanding ligand selectivity and isomer specificity. However, direct experimental measurement of these thermodynamic parameters has been limited to cell surface proteins, such as GPCRs.

Addressing this gap, a research team led by Professor Mitsunori Shiroishi from the Department of Life System Engineering, Tokyo University of Science (TUS), Japan, systematically investigated the binding thermodynamics of the H1R. The team included Mr. Hiroto Kaneko (first-year doctoral student) and Associate Professor Tadashi Ando from TUS, among others. Their study was published online in ACS Medicinal Chemistry Letters on January 26, 2026.

Why you hardly notice your blind spot: New tests pit three theories of consciousness

Although humans’ visual perception of the world appears complete, our eyes contain a visual blind spot where the optic nerve connects to the retina. Scientists are still uncertain whether the brain fully compensates for the blind spot or if it causes perceptual distortions in spatial experience. A new study protocol, published in PLOS One, seeks to compare different theoretical predictions on how we perceive space from three leading theories of consciousness using carefully controlled experiments.

The new protocol focuses on three contrasting theories of consciousness: Integrated Information Theory (IIT), Predictive Processing Active Inference (AI), and Predictive Processing Neurorepresentationalism (NREP). Each of the theories have different predictions about the effects that the blind spot’s structural features have on the conscious perception of space, compared to non-blind spot regions.

IIT argues that the quality of spatial consciousness is determined by the composition of a cause-effect structure, and that the perception of space involving the blind spot is altered. On the other hand, AI and NREP argue that perception relies on internal models that reduce prediction errors and that these models adapt to accommodate for the structural deviations resulting from the blind spot. Essentially, this means that perceptual distortions should either appear small or nonexistent in both theories. However, AI and NREP differ in some ways.

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