Journal of Avian Biology

Collective movement requires coordination between individuals, yet how this emerges during early interactions remains poorly understood. We investigated how partner familiarity influences coordination, leader-follower dynamics, and learning in homing pigeon pairs navigating from novel sites. Birds were released repeatedly with either familiar or unfamiliar partners, followed by solo releases to assess learning. By quantifying bidirectional information flow, we found familiarity influenced information-transfer dynamics during the first release: familiar pairs exhibited more asymmetric information transfer, likely reflecting established leader-follower relationships, whereas unfamiliar pairs showed more symmetric exchange. These differences disappeared after one release. Conversely, familiarity had little effect on cohesion or navigational performance. There was some evidence for an influence on learning: birds from familiar pairings had higher homing efficiency on a subsequent solo release. Finally, across partnerships, followership was more predictable than leadership with respect to individual identity and flight speed, indicating stable variation in individuals' tendency to follow rather than lead. This suggests that a shift in emphasis from leadership to followership might enhance our understanding of collective decision-making dynamics. Our results demonstrate how flight partners rapidly coordinate, producing limited downstream effects on navigation and learning, with implications for many animals that travel in fission-fusion transitory collectives.

High Pathogenicity Avian Influenza (HPAI) H5N1 clade 2.3.4.4b has spread beyond birds to affect seals across the Southern Ocean and sub-Antarctic region, with southern elephant seals (Mirounga leonina) particularly devastated. The virus, likely introduced via spillover from infected migratory birds, has killed tens of thousands of adult seals and pups throughout most of their range, though Macquarie Island remains unaffected so far. We used twenty years of elephant seal movement data from the southern Indian and Pacific oceans to assess whether seal-to-seal transmission could spread HPAI H5N1 between breeding colonies, despite the vast distances separating them (Marion Island, Iles Crozet, Iles Kerguelen, and Macquarie Island). There was substantial overlap in seals' at-sea distributions during their winter post-moult trips, when seals travel for weeks at average speeds of 3.5 km/h. Two transmission pathways were examined: (1) terrestrial "stepping stone" routes, where infected seals could pass the virus between colonies during short intervals to remain infectious were feasible from Marion Island to Kerguelen but not from Kerguelen to Macquarie Island; and (2) at-sea encounters between seals, which occurred frequently enough to enable transmission. The findings suggest that once established at Macquarie Island, the virus could potentially spread further to New Zealand's sub-Antarctic islands and mainland New Zealand. While seal-to-seal transmission appears possible, we conclude this is unlikely. Nonetheless, understanding at-sea contact rates enhances knowledge of H5N1 epidemiology and demonstrates the value of combining long-term population monitoring with movement data to understand wildlife disease dynamics.

To make adaptive foraging decisions, naive individuals need to gather information about the local prey community. Besides sampling prey personally, the young could gather information about prey profitability by observing the foraging behaviour of other individuals, and parental provisioning provides the first opportunity to acquire this social information. Still, previous research on vertical transmission of prey preferences from parents has provided mixed results that are often confounded with other information sources, such as siblings and peers. It is also not known whether information from parents can change potential innate biases against certain prey types, such as avoidance of warningly coloured insects. Here, we tested whether social information acquired by offspring during parental provisioning influences the development of prey preferences in a generalist predator, the Great Tit (Parus major). We brought 15 great tit broods and their parents into captivity at late nestling stage (14 days old) and divided them into three social information treatments where parents were provided with either brown, red or yellow palatable maggots to feed to their dependent young for 8 days. Once foraging independently from parents, we conducted a preference test where juveniles were offered the full array of coloured maggots. Regardless of palatable exposure to typical warning-coloured maggots (i.e. red and yellow), juveniles consistently preferred yellow over red, and preferred brown maggots the most (i.e. lacking warning coloration). This supports the existence of innate biases against typical warning colours, and that social information from parents is unlikely to override these, at least when alternative prey is easily available.

Animal vocalisations can convey information about external events, but whether this goes beyond reflecting the emotional state elicited by these events is debated. To explore this, we studied the acoustic structure of common marmoset (Callithrix jacchus) phee (long-distance contact) and ek (alert/mobbing) calls produced in five treatments varying in the emotional valence and arousal they elicit (internal state), as well as food and social context (external events). We measured changes in arousal via nasal temperature and analysed both basic acoustic parameters and Mel-frequency cepstral coefficients (MFCCs) of the calls. Support Vector Machines combined with Linear Mixed effect models revealed that phee calls encode both external events and internal states, while eks reflected predominantly arousal. Notably, an acoustic signature related to food context was present in phees both when provided (positive valence) and teased with highly preferred food items (negative valence), and even when food was not physically present (food call playback treatment). This suggests marmoset long-distant phee calls encode external information beyond emotional arousal and valence, and independently of the presence of an immediately triggering stimulus.

Effective conservation depends on demographic metrics that reliably reflect species status, particularly population abundance. For elusive species occurring at low densities, however, such metrics remain difficult to obtain. Spatial capture-recapture (SCR) models are the standardized approach for estimating density in marked populations, but their data requirements, especially the need for multiple spatial recaptures across individuals, often limit applicability in small or data-poor populations. This constraint has resulted in knowledge gaps for some of the most vulnerable species, undermining evidence-based conservation planning and management. Using camera-trap data and SCR-derived density estimates from data-rich populations, we evaluated alternative, less data-demanding metrics and tested the hypothesis: Space to Event (STE), Mean Local Abundance (MLA), and Relative Abundance Index (RAI) exhibit predictable relationships with SCR-derived density; if supported, these metrics can reliably estimate density in populations where SCR models cannot be implemented. We applied this framework to the European wildcat (Felis silvestris), an elusive small felid with highly fragmented populations across Europe, for which density estimates are largely lacking despite growing conservation concern. Across 21 study areas spanning most of the species' range, our results indicate that European wildcats generally occur at lower densities than previously reported. SCR-derived estimates (n=10) averaged 10.32 {+/-} 11.56 inds/100km2, while STE enabled density estimation in five additional data-poor areas (mean 5.52 {+/-} 5.33 inds/100km2). STE showed a strong linear relationship with SCR-derived density (R2=0.98), supporting its use as a viable alternative when SCR is infeasible, although it tended to underestimate compared to SCR, especially at higher densities. In contrast, MLA and RAI showed weaker and non-linear relationships with SCR-derived density (R2=0.65), indicating substantially lower explanatory power and suggesting their estimates are more strongly influenced by confounding processes. By explicitly calibrating alternative metrics across a wide density gradient throughout most of the species' distribution, this study provides a transferable methodological framework for estimating density in low-density wildlife populations and the first continent-wide, standardized density assessment of a carnivore species. From a management perspective, our findings identify populations that may be most vulnerable, particularly those with the lowest densities, and highlight the need to prioritize absolute abundance monitoring.

Long-distance movement in insects has crucial impacts on agriculture, human health, and biodiversity. Although it was long assumed that only large, specialist insects had the navigation capacity to support long-distance dispersal, recent studies have demonstrated that smaller insects, such as the tiny fruit fly Drosophila melanogaster, can maintain extended, straight paths while flying or walking. This raises the question of whether other Drosophila species possess the navigation capacity to support extended dispersal. Resolving this question is particularly important for Drosophila suzukii(spotted-wing drosophila), a potent pest species that causes enormous damage worldwide to ripe fruit and berries. Spotted-wing drosophila has been thought to lack a capacity for long-distance dispersal, as prior studies have estimated maximal daily dispersal distances of less than 90 m. We developed a system to continuously track the flight trajectories of magnetically tethered D. suzukii relative to a discrete, overhead LED that mimicked the sun. We found that flies maintained remarkably straight flight headings that varied unpredictably across individuals. Male and female D. suzukii exhibited a similar navigation capacity; both sexes responded to rotation of a discrete sun stimulus with compensatory turns to maintain a stable relative heading. Our results suggest that D. suzukiihas an underappreciated capacity for rapid, radial dispersal, which could exceed 250 m in 15 min. This capacity may contribute to the pest species' invasiveness and its reliable, annual re-establishment in seasonally intolerable climates. Our findings highlight the importance of developing area-wide, regional strategies to manage the impacts of D. suzukii.

Climate change is expected to alter plant populations not only through direct environmental shifts but also via changes in biotic interactions, such as with herbivores and pathogens. As plant species are also expected to differ in their responses to both climate and antagonists, plant responses to both factors are expected to be variable and species-specific. To assess whether interactive effects of climate and antagonists on plant population dynamics are common and whether the strength and direction of plant responses vary across species, we conducted a multi-year field experiment that manipulated realistic climate change and experimentally reduced insect herbivores and fungal pathogens. We measured responses of plant vital rates, such as survivorship, growth, and reproduction across six grassland species. Using Integral Projection Models (IPMs) and Life Table Response Experiments (LTREs), we quantified changes in population growth rate across experimental treatments and the contribution of each vital rate to that observed change. Two of the study species declined so drastically over the course of the experiment that demographic quantification of population growth rates was not possible. From the remaining species, Bromus erectus and Plantago lanceolata show significant interactive responses of climate and antagonist reduction on population growth rates. In contrast, Dianthus carthusianorum and Tragopogon orientalis showed limited responses to experimental treatments. Notably, our results indicate that in some species biotic interactions may amplify the effects of climate change: the presence of plant antagonists exacerbates the negative effects of the future climate treatment on plant population dynamics. Our findings highlight the complexity in predicting plant population responses to climate change and provide insights for grassland management under future environmental conditions.

The rariphotic zone, typically spanning depths of approximately 130 to 300 meters, represents a key transition between light-dependent coral reef ecosystems and the aphotic deep sea. Despite its potential ecological importance, including its proposed role as a refuge for species exposed to climate-driven stress, rariphotic ecosystems remain poorly understood. In this study, we conducted a systematic review and synthesis of the scientific literature on these habitats from 1970 to 2025. Following the PRISMA 2020 protocol, we analyzed 185 studies to characterize the historical development of research, identify geographic and methodological biases, and assess shifts in research priorities over five decades.Our results show a marked increase in research effort over the last decade, driven in part by advances in underwater technologies such as Remotely Operated Vehicles (ROVs), Human Occupied Vehicles (HOVs), and Baited Remote Underwater Video Station (BRUVS). However, this growth remains uneven, with persistent biases toward benthic rather than pelagic studies and a strong concentration of research in geographically accessible regions. Multivariate analyses of research novelty indicate that technological innovation and the formal recognition of the rariphotic zone in 2018 corresponded with major structural shifts in literature. Although the rariphotic zone is now increasingly recognized as an ecologically distinct component of the reef continuum, it remains underrepresented in ecological theory and conservation frameworks. Future research should move beyond descriptive taxonomic mapping toward integrative, data-driven functional ecology, with particular emphasis on long-term monitoring and depth-stratified connectivity.

Nepal's rangelands provide multiple benefits, including support for pastoral livelihoods and alpine biodiversity, regulation of water and soil nutrients, and sequestering carbon. Climate change and anthropogenic pressures are altering these rangelands, leading to vegetation and biodiversity change. However, national-scale assessments of rangeland change are limited in Nepal. This study quantified rangeland changes at multiple spatial scales and assessed the climatic and non-climatic drivers of rangeland change. About 80.7% of Nepal's high-altitude rangeland (> 2,000m) outside protected areas showed no significant change. Among areas exhibiting significant annual maximum NDVI trends, 383,281 ha (18.6%) showed positive and 14,702 ha (0.7%) showed negative trends, corresponding the ratio of increase in vegetation greenness and decline in vegetation greenness to 26:1. Climate predicted positive trends covered 627,184 ha (30.5%), whereas residual trends caused by non-climatic drivers covered 94,656 ha (4.6%). Climate induced negative trends covered 47,609 ha (2.3%) while residual trends were observed in 6,260 ha (0.3%). Negative trend pixels were concentrated mainly within the 3,000 to 5,000 m elevation band, with Karnali Province recording the highest proportional climate predicted decline in vegetation greenness (3.4%). At the municipality scale, rangeland change showed no significant relationship with grazing pressure derived from gridded livestock data, suggesting that grazing pressure alone did not explain the non-climatic vegetation signal. These spatially explicit, nationally consistent results identify where rangeland change is occurring and help distinguish climatic and non-climatic drivers of rangeland vegetation change, providing evidence to support targeted rangeland management under Nepal's federal governance structure.

Despite the ecological importance of ungulate migrations, we lack a complete understanding of why some ungulates migrate and others do not. Though progress has been made towards understanding differences across species and between populations, migratory behavior varies even within populations: in many populations, some individuals remain behind as residents (partial migration). Theoretical population-level work has suggested that these different migratory tactics can coexist, but such approaches stop short of providing insights into how individuals make the decision to stay or go each year. Using long-term data from three ungulate populations, we find that individuals probabilities of migrating are highly variable across years, which points to a non-trivial context-dependent decision-making process, whose underlying mechanisms must be probed via individual-level modeling. Drawing on existing knowledge, we propose a decision-making model of ungulate migration onset wherein individuals probabilistically decide to start migrating based on the local intensity of environmental and/or social cues. Residents arise as a robust collective organization phenomenon in our model. At sufficiently large population sizes, the number of residents is invariant with total population size, consistent with empirical patterns. Instead, resident numbers are influenced by the severity of the bad season, by relevant character differences among individuals, and by how individuals contribute and respond to environmental and/or social cues; for instance, when social cues contribute to decision-making in addition to environmental ones, fewer residents result, and migration is more likely to be complete. Overall, our model provides a potential mechanistic explanation for how residents might emerge within migratory ungulate populations.

Aim: To forecast near-future arrivals of non-native terrestrial and freshwater vertebrates at the regional level. Location: Global (geopolitical regions worldwide, including countries and main administrative divisions). Methods: We compiled first regional record data and assembled functional and macroecological variables for 1,931 non-native vertebrate species. For each region, we identified recently arrived non-native species using retrospective windows of thirty and twenty years ending in 2015 (1986-2015; 1996-2015). We then fitted region-specific random-forest models classifying recently arrived species versus those not yet arrived using as predictors: (i) harmonised species traits (e.g., habitat, diet, body size and native-range attributes) and (ii) spread history, capturing time since first record elsewhere. Predictive performance was evaluated using leave-one-out cross-validation, comparing full models with trait-only and spread-only variants. We also assessed relationships between predictive accuracy, predictor importance, and the geographic positioning and trade connectedness of regions. Finally, we predicted region-specific probabilities of arrival for species not yet recorded. Results: Forecasting accuracy was consistently high across regions and taxa, with AUC values above 0.9 in more than half of the focal regions. Full models substantially outperformed models using either predictor set alone, and spread-history-only models typically exceeded trait-only models. Relative importance of spread-history predictors declined with geographic distance to the focal region, whereas predictability was lower in highly trade-connected regions. Predicted near-future high-risk arrivals were dominated by birds and freshwater fishes and showed strong regional structuring. A small set of species ranked highly across many regions (e.g., birds: Phasianus colchicus, Acridotheres tristis, Amandava amandava, Colinus virginianus, Corvus splendens and Lonchura malacca; fishes: Coregonus peled and Oreochromis mossambicus; mammal: Oryctolagus cuniculus), suggesting substantial unrealised spread potential. Main conclusions: Near-future regional arrivals of non-native vertebrates are predictable from spread history and species traits. This enables scalable, updateable regional watchlists to support prevention, early detection and horizon scanning.

The coast redwood (Sequoia sempervirens) is a long-lived, hexaploid conifer of high ecological, cultural, and economic value whose range has been greatly reduced by historical logging. Effective restoration and conservation depend on understanding patterns of genetic differentiation across the redwood range to delineate populations for management prioritization. Yet, past range-wide studies provided only a partial picture of population structure in coast redwood as they relied on a limited set of genetic markers or limited sampling, as sequencing was done on the same range-wide provenance collection. Here, we analyze 334,029 SNPs from a new range-wide set of 224 individuals using a dosage-based approach that accounts for polyploidy. Principal coordinates and neighbor-joining analyses reveal clear latitudinal genetic differentiation, with a distinct break south of San Francisco Bay. Outlier SNP analysis indicates new candidate loci involved in salinity tolerance, climate stress response, and nutrient uptake, suggesting potential local adaptation. These results point to the central role of geography in shaping genetic variation in coast redwood and give scientific basis for designing new conservation strategies and future experiments, including assisted migration, provenance trials, and restoration planning aimed at preserving the species into the future.

Primary production in the Southern Ocean (SO) plays a critical role in regulating the global carbon cycle, yet the physiological mechanisms governing phytoplankton responses to iron (Fe) limitation and variable light remain poorly constrained. Using a custom made incubation system that simulated natural diel solar variability, we examined the interactive effects of Fe availability, light intensity, and photoperiod (continuous vs. variable) on three ecologically important SO phytoplankton: Fragilariopsis cylindrus, Phaeocystis antarctica, and Thalassiosira antarctica. Physiological, photophysiological, and proteomic measurements revealed that Fe availability was the dominant factor regulating growth, carbon production, photosynthetic performance and protein expression across all species. Distinct acclimation strategies emerged: F. cylindrus exhibited marked trade-offs between productivity and photoprotection under Fe stress, consistent with adaptation to stable, low-light, Fe-poor environments; P. antarctica maintained growth by flexibly modulating photoprotective and photosynthetic capacity, reflecting high plasticity suited to dynamic, open-ocean conditions; and T. antarctica expressed a balanced strategy, sustaining productivity and photoprotection simultaneously, characteristic of coastal bloom formers with higher Fe demand. Dynamic light regimes produced smaller, species-specific effects, influencing chlorophyll content and carbon storage primarily in T. antarctica. Correlation and z-score analyses demonstrated that Fe-rich photosynthetic proteins co-varied with biomass production, whereas photoprotective traits clustered independently, underscoring divergent energy-allocation strategies. Together, these results reveal how SO phytoplankton partition resources between productivity and photoprotection under shifting Fe-light regimes, providing mechanistic insight into their ecological niches.

Transformer-based deep learning models have shown great potential for decoding visual EEG signals. However, their internal attention mechanisms are often evaluated primarily on optimization objectives, leaving their alignment with biological brain connectivity an open question. This study empirically evaluates how variations in EEG preprocessing strategies affect these attention representations using the Adaptive Thinking Mapper (ATM) model as a framework. We compared a baseline pipeline (MVNN only) against a comprehensive cleaning pipeline integrating ICA and notch filtering. The models were evaluated through cross-generalization, noise robustness, and spectral-temporal ablation analyses. Furthermore, we investigated the structural correspondence between the model's data-driven attention weights and neurophysiological reference networks (GPDC, PDC, and DTF) using Node Strength Correlation and Representational Similarity Analysis (RSA). The results show that the comprehensive preprocessing successfully suppresses non-neural artifacts, such as frontal noise and electrical interference, while maintaining comparable decoding accuracy and baseline robustness. Alignment analyses revealed that the broad spatial organization of the learned attention patterns remains highly stable across pipelines, capturing key directed connectivity dynamics with subtle, metric-dependent variations in global representational geometry. This work provides an empirical exploration into bridging data-driven attention weights with neurophysiological consistency, offering insights toward more transparent brain-computer interfaces.

The incidence of early-onset colorectal cancer (CRC) has risen sharply in recent decades1, yet the biological basis underlying the distinct behavior of tumors arising in young versus aged tissues remains poorly understood. Here we show that aging reprograms the epigenetic landscape of the colon, restricting colon tumor growth through stable silencing of developmental and fetal gene programs. We find that colon tumors arising in aged mice are intrinsically less proliferative than those arising in young animals. Multi-omic profiling of normal colon and colon tumors reveals that aging drives DNA hypermethylation, loss of Polycomb-associated chromatin states, and reduced chromatin accessibility at a defined set of developmental genes that are bivalent (marked by both H3K27me3 and H3K4 methylation), transcriptionally active in colon tumors from young animals and repressed in both tumors and normal tissue from old animals. Among the genes most strongly repressed in old animals is Tacstd2 (Trop2), a regulator of fetal intestinal programs and epithelial stemness. Pharmacologic inhibition of DNA methylation reactivates the aging-silenced gene network in organoids from old animals, whereas genetic disruption of Tacstd2 suppresses growth and developmental transcriptional programs in young tumor organoids. TACSTD2, fetal gene signatures, and the aging-associated bivalent gene program are likewise repressed in late-onset vs. early-onset human colorectal cancers. Collectively, these findings identify age-associated epigenetic silencing of developmental gene programs as a causal mechanism that constrains colorectal tumor growth and provide a mechanistic framework for understanding the distinct biology of early-onset colorectal cancer.

Extrahepatic delivery of lipid nanoparticles (LNPs) to non-phagocytic cells is a major challenge, with the leading strategy involving surface functionalization with target-specific monoclonal antibody (mAb) ligands. We investigate the stability of mAb-conjugated LNPs using two anchoring systems: the commonly used DSPE-PEG2kDa-maleimide and a block copolymer, PCL5kDa-b-PEG2kDa -maleimide, with the hypothesis that conjugation to a 150,000 Da antibody could overwhelm the relatively small ~600 Da aliphatic anchor on the PEG-lipid in vivo. Shedding of the mAB would compromise targeting. Conjugation integrity following IV injection was assessed by tagging LNPs and mAbs with metal ion tracers that could be quantified by ICP-MS. Results show that DSPE-PEG-mAb rapidly (within 1h) dissociates from LNPs in blood, leading to accelerated LNP clearance. In contrast, mAbs conjugated using PCL-b-PEG remained stably associated with the LNP over the 24h circulation and clearance of the construct. Results are connected to a thermodynamic model that reproduces experimental findings for PEG-anchor(-mAb) shedding in vitro and in vivo. This study identifies anchoring strength as a critical, unconsidered parameter for in vivo performance when conjugating mAbs to LNPs for extrahepatic delivery.

Blockade by sedimentary particles, such as mineral crystals, is a continuous risk the kidney tubule faces. To prevent that, kidney resident macrophages form transepithelial protrusions and remove intratubular sedimentary particles, a behavior particularly prevailing in the medulla over the cortex. However, the molecular mechanisms underlying this characteristic behavior of medulla macrophages are incompletely understood. In this study, we identified that the medulla had higher mechanical stiffness than the cortex in steady state, which was further elevated when kidney stone formed. Increased tissue rigidity was sensed by medulla macrophages via mechanoreceptor Piezo1, which promoted macrophage protrusion formation and their ability to clean the tubules. Loss of Piezo1 expression in kidney macrophages predisposed mice to intratubular accumulation of mineral crystal in steady state and accelerated kidney stone formation during oxalate intake challenge. Signaling via Piezo1 mobilized molecules involved in cell adhesion and protrusion assembly, including Talin2 and focal adhesion kinase (FAK). Finally, we developed a first-of-its-kind cell-based therapy for the treatment of experimental nephrolithiasis by exploiting macrophage Piezo1 activity, and this strategy shows great promise for future translational research.

Single-nucleus transcriptomic atlases offer an unprecedented opportunity to connect cellular molecular states with Alzheimer's disease (AD) neuropathology, but whether these profiles encode reproducible, predictive information about pathological burden remains unclear. We present the SEA-AD DREAM Challenge, an open, international, model-to-data competition built on the Seattle Alzheimer's Disease Brain Cell Atlas to predict Alzheimer's disease neuropathological severity from single-nucleus RNA-sequencing data. Participants developed containerized models to predict categorical neuropathological staging, including overall Alzheimer's disease neuropathologic change, Braak stage, Thal phase, and CERAD score, as well as quantitative amyloid-{beta} and phospho-tau burden measured by 6E10 and AT8 immunohistochemistry. Across 17 eligible teams from 15 countries, the crowdsourcing framework enabled systematic comparison of diverse computational approaches and surfaced a broad landscape of modeling strategies and candidate predictive features. Top-performing methods achieved near-perfect prediction of categorical staging, with the best submission reaching a quadratic weighted kappa of 1.0 for the Overall AD Neuropathological Change score (ADNC), and competitive prediction of quantitative pathological burden in held-out data, with a best concordance correlation coefficient of 0.48. Post hoc perturbation analyses revealed that top categorical-stage predictions relied heavily on donor-level metadata-driven signals rather than transcriptomic features, whereas quantitative pathology prediction was more robust and supported by transcriptomic and cell-type-associated features with potential biological relevance to AD progression. The challenge also introduced the first AI Agent Track in a DREAM Challenge, providing an early benchmark for autonomous and human-guided agentic model development in single-cell neuroscience. This work demonstrates that single-nucleus transcriptomes encode substantial information about Alzheimer's disease pathology, establishes a reproducible benchmark for molecular neuropathology prediction, and highlights critical principles for designing privacy-preserving, leakage-aware community challenges using deeply phenotyped human brain data.

Joint music making offers an ecologically powerful framework for investigating human social interaction and synchronization. Yet, experimental paradigms often rely on traditional instruments that limit accessibility, reproducibility, and experimental control. In parallel, the use of music for therapy and rehabilitation is expanding, motivating the development of digital musical instruments that can serve research, educational, and clinical purposes. Here, we introduce the e-Music Box Roma (eMB Roma), an open, reproducible digital musical instrument designed to study music making behavior regardless of musical training. The eMB Roma plays preregistered music with tempo controlled by hand rotary movements. Building on the original e-Music Box (Novembre et al., 2015), the eMB Roma retains its intuitive rotary hand control while introducing major innovations: a fully open and 3D-printable design, modular hardware with integrated slider and button controls, polyphonic output with multiple simultaneous instruments, and MIDI compatibility. Additionally, a dedicated graphical user interface allows real-time monitoring, experiment control, device synchronization (like neuroimaging or motion capture devices), and both solo and joint music-making paradigms. The eMB Roma provides a flexible and accessible platform for research contexts, allowing experimental control, reproducibility, and future extensions. Its open design and modularity make it suitable not only for research but also for therapeutic, rehabilitation, and educational applications, where it can support personalized interventions and quantitative assessment of motor performance.

Brain areas differ in their inherent susceptibility to focal seizures, but the principles governing this risk remain unclear. While prior work has focused on anatomical and physiological factors, here we observed a fundamental contribution from the computations performed by the underlying neural network. Handcrafted and trained recurrent neural networks supporting continuous representations respond to seizure perturbations with higher activity and earlier performance decline relative to matched networks stabilizing discrete, well-separated states. Consistent with this prediction, in vivo recordings revealed that medial entorhinal cortex, whose grid cells exhibit continuous attractor dynamics, drives acute epileptiform discharges with stronger involvement and smoother state trajectories compared to CA3, a hippocampal subfield associated with discrete memory storage. Moreover, selective synaptic silencing demonstrated that this difference in seizure responses depends on intact entorhinal connectivity. Thus, the computations that enable neural networks to process information also influence their vulnerability to pathological transitions.