Many grocery shoppers know the routine: bring fruit and vegetables home, rinse them, dry them and hope they stay fresh long enough to be eaten. But fresh produce is delicate. Grapes shrivel, apple sli
A single scoop of water from an Irish river has revealed evidence not only of Ireland's only frog species—as expected—but also signs of the dreaded B. dendrobatidis fungus, marking the first time this
The mountain bongo has become the "ghost of the forest," hard to spot amid the dense shrubs due to its ability to camouflage.
Engineered microorganisms are widely used in industrial biotechnology and biopharmaceutical applications, including the production of biofuels, sustainable chemicals, and therapeutic compounds. Howeve
Scientists from Trinity and Technical University of Denmark have developed a new radar-based technique that could address a critical gap in global conservation efforts, by transforming how we identify
Artificial intelligence can dramatically speed up the painstaking work of tracking wildlife with remote cameras, cutting analysis time from months or even a year to just days while producing nearly th
For more than a decade, conservation biologist Steve Boyes searched for "ghost elephants"—nocturnal giants rumored to roam a remote, high-altitude wetland in eastern Angola. When a motion-sensor camer
Scientists may have found a smarter, safer way to wipe out termites hiding inside homes. A chemical called bistrifluron prevents drywood termites from forming new exoskeletons during molting, killing
Researchers have developed a sensor about the size of a grain of rice that can measure forces and twisting motions in all directions using light instead of traditional electronics. The new sensor coul
Brain-DNN alignment is usually assessed through stimulus-level correspondence or stimulus-set geometry. Inspired by category theory, we operationalize a different question: do brain and model preserve the same candidate transformations among stimuli? We formalize this as approximate naturality: if a
Understanding how neural population responses represent sensory information is a central problem in systems neuroscience. One approach is to define a representational geometry on stimulus space in which distances reflect how reliably stimuli can be distinguished from neural activity. However, differ
Decoding approaches are widely used in neuroscience and machine learning to compare stimulus representations across neural systems, such as different brain regions, organisms, and deep learning models. Popular methods include decoding (perceptual) manifolds and alignment metrics such as Representati
Computational cognitive models discovered using large language models have so far relied solely on behavioral data. However, it is well-known that models produced from the behavioral trajectory alone are typically under-determined. In this work, we explore the use of Think Aloud traces as an additio
Cross-frequency interactions are fundamental brain mechanisms for integrating information across temporal scales. However, accurate identification of these couplings is hindered by complex multi-frequency nonlinearities and by spurious, zero-lag artifacts caused by volume conduction. To our knowledg
Deep convolutional neural networks (DCNNs) have rivaled humans on many visual tasks, yet they remain vulnerable to near-imperceptible perturbations generated by adversarial attacks. Recent work shows that aligning DCNN representations with human visual cortex activity improves adversarial robustness
Cognitive neuroscience is fragmented into specialized models, each tailored to specific experimental paradigms, hence preventing a unified model of cognition in the human brain. Here, we introduce TRIBE v2, a tri-modal (video, audio and language) foundation model capable of predicting human brain ac
The free energy principle casts perception as variational inference, but its biological implementation remains underspecified. In particular, the generalized-coordinate formalism should not be read as a literal claim that neurons compute arbitrary Taylor expansions. This paper argues that generalize