Publications

Sense of Okayness (SOK) is an emerging concept that describes a person’s ability to remain stable and unshaken in the face of life transitions and hardships. This quality enables effective stress regulation and heightened tolerance to uncertainty. To investigate the possible role of the parasympathetic nervous system (PNS) in mediating the relationship between SOK and stress regulation among older individuals, an analytical sample of N  =  69 participants (74% women) with a mean age of 78.75 years (SD age  =  6.78) was recruited for a standardized cognitive assessment and stress induction. Baseline heart rate variability (HRV), measured via electrocardiogram (ECG), and SOK assessments were conducted prior to stress induction, along with a baseline cognitive evaluation. Subsequently, participants were subjected to a psychosocial stress paradigm, followed by either a 30-minute SOK elevation intervention (n = 40) or a control condition with nature sounds (n = 29). A second cognitive assessment was administered post-intervention, with continuous HRV measurement through ECG. The results revealed significant HRV changes due to the experimental intervention, though no significant differences were observed between the SOK intervention and control groups. Interestingly, individuals with high trait SOK displayed more stable HRV trajectories, exhibiting a smaller decline during the stress intervention and a milder increase during both the stressor and SOK intervention phases. Overall, these findings do suggest a significant association between SOK, parasympathetic activity, and stress reactivity. These results prompt further investigation into whether personality patterns, such as a strong SOK, may be linked to reduced vagal reactivity and better coping in old age.

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dc.contributor.author: Vinkers, Christiaan H.; Sep, Milou S. C.

Human–wildlife conflict challenges conservation worldwide, which requires innovative management solutions. We developed a prototype Agent-Based Model (ABM) to simulate interactions between humans and solitary bull Asian elephants in the Periyar–Agasthyamalai complex of the Western Ghats in Kerala, India. The main challenges were the complex behavior of elephants and insufficient movement data from the region. Using literature, expert insights, and field surveys, we created a prototype behavior model that incorporates crop habituation, thermoregulation, and aggression. We designed a four-step calibration method to adapt relocation data from radio-tagged elephants in Indonesia to model elephant movements in the model domain. The ABM’s structure, including the assumptions, submodels, and data usage are detailed following the Overview, Design concepts, Details protocol. The ABM simulates various food availability scenarios to study elephant behavior and environmental impact on space use and conflict patterns. The results indicate that the wet months increase conflict and thermoregulation significantly influences elephant movements and crop raiding. Starvation and crop habituation intensify these patterns. This prototype ABM is an initial model that offers information on the development of a decision support system in wildlife management and will be further enhanced with layers of complexity and subtlety across various dimensions. Access the ABM at github.com/quest-lab-iisc/abm-elephant-project

During collective vigilance, it is commonly assumed that individual animals compromise their feeding time to be vigilant against predators, benefiting the entire group. One notable issue with this assumption concerns the unclear nature of predator “detection”, particularly in terms of vision. It remains uncertain how a vigilant individual utilizes its high-acuity vision (such as the fovea) to detect a predator cue and subsequently guide individual and collective escape responses. Using fine-scale motion capture technologies, we tracked the head and body orientations of pigeons (hence reconstructed their visual fields and foveal projections) foraging in a flock during simulated predator attacks. Pigeons used their fovea to inspect predator cues. Earlier foveation on a predator cue was linked to preceding behaviors related to vigilance and feeding, such as head-up or down positions, head-scanning, and food-pecking. Moreover, earlier foveation predicted earlier evasion flights at both the individual and collective levels. However, we also found that relatively long delay between their foveation and escape responses in individuals obscured the relationship between these two responses. While our results largely support the existing assumptions about vigilance, they also underscore the importance of considering vision and addressing the disparity between detection and escape responses in future research.

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Group-living animals sleep together, yet most research treats sleep as an individual process. Here, we argue that social interactions during the sleep period contribute in important, but largely overlooked, ways to animal groups’ social

dynamics, while patterns of social interaction and the structure of social connections within animal groups play important, but poorly understood, roles in shaping sleep behavior. Leveraging field-appropriate methods, such as direct and

video-based observation, and increasingly common on-animal motion sensors (e.g., accelerometers), behavioral indicators can be tracked to measure sleep in multiple individuals in a group of animals simultaneously. Sleep proximity networks and sleep timing networks can then be used to investigate the collective dynamics of sleep in wild group-living animals.

Recent advances in calcium imaging, including the development of fast and sensitive genetically encoded indicators, high-resolution camera chips for wide-field imaging, and resonant scanning mirrors in laser scanning microscopy, have notably improved the temporal and spatial resolution of functional imaging analysis. Nonetheless, the variability of imaging approaches and brain structures challenges the development of versatile and reliable segmentation methods. Standard techniques, such as manual selection of regions of interest or machine learning solutions, often fall short due to either user bias, non-transferability among systems, or computational demand. To overcome these issues, we developed CalciSeg, a data-driven and reproducible approach for unsupervised functional calcium imaging data segmentation. CalciSeg addresses the challenges associated with brain structure variability and user bias by offering a computationally efficient solution for automatic image segmentation based on two parameters: regions’ size limits and number of refinement iterations. We evaluated CalciSeg efficacy on datasets of varied complexity, different insect species (locusts, bees, and cockroaches), and imaging systems (wide-field, confocal, and multiphoton), showing the robustness and generality of our approach. Finally, the user-friendly nature and the open-source availability of CalciSeg facilitate the integration of this algorithm into existing analysis pipelines.

Circumnutations are widespread in plants and typically associated with exploratory movements; however, a quantitative understanding of their role remains elusive. In this study we report, for the first time, the role of noisy circumnutations in facilitating an optimal growth pattern within a crowded group of mutually shading plants. We revisit the problem of self-organization observed for sunflowers, mediated by shade response interactions. Our analysis reveals that circumnutation movements conform to a bounded random walk characterized by a remarkably broad distribution of velocities, covering 3 orders of magnitude. In motile animal systems such wide distributions of movement velocities are frequently identified with enhancement of behavioral processes, suggesting that circumnutations may serve as a source of functional noise. To test our hypothesis, we developed a Langevin-type parsimonious model of interacting growing disks, informed by experiments, successfully capturing the characteristic dynamics of individual and multiple interacting plants. Employing our simulation framework we examine the role of circumnutations in the system, and find that the observed breadth of the velocity distribution represents a sharp transition in the force-noise ratio, conferring advantageous effects by facilitating exploration of potential configurations, leading to an optimized arrangement with minimal shading. These findings represent the first report of functional noise in plant movements and establish a theoretical foundation for investigating how plants navigate their environment by employing computational processes such as task-oriented processes, optimization, and active sensing. Since plants move by growing, space and time are coupled, and dynamics of self-organization lead to emergent 3D patterns. As such, this system provides conceptual insight for other interacting growth-driven systems such as fungal hyphae, neurons and self-growing robots, as well as active matter systems where agents interact with past trajectories of their counterparts, such as stigmergy in social insects. This foundational insight has implications in statistical physics, ecological dynamics, agriculture, and even swarm robotics.

The soundscape experienced by animals early in life can affect their behaviour later in life. For birds, sounds experienced in the egg can influence how individuals learn to respond to specific calls post-hatching. However, how early acoustic experiences affect subsequent social behaviour remains unknown. Here, we investigate how exposure to maternal ‘cluck’ calls pre-hatching affects the behaviour of domestic chickens (Gallus gallus domesticus) at 3–5 days and 17–21 days old. We incubated eggs and played cluck calls to half of them. After hatching, we raised chicks in small groups occupying different enclosures. At 3–5 days old, we tested chicks’ responses to three stimuli: (i) background sound, (ii) chick calls and (iii) cluck calls. We found that the pre-hatching experience of cluck calls reduced the likelihood of moving in response to all three stimuli. At 17–21 days old, some chicks explored beyond their own enclosure and ‘visited’ other groups. Chicks exposed to cluck calls before hatching were three times more likely to enter another group’s enclosure than control chicks, and this was unaffected by the chicks’ social connectedness. Our results indicate age- and context-dependent responses of chicks to pre-hatching cluck-call playbacks, with potential long-term effects on individual social behaviour.

Misrepresentation of peer behavior has often been observed in college students and may lead to over‐expression of alcohol consumption and under‐expression of studying. While social norm feedback approaches have had mixed success in addressing these misrepresentations and altering behavior, they may have been too unspecific to be effective and did not directly assess individual perception accuracy. We thus investigated how specific, one‐time feedback on the behavioral distribution of alcohol consumption or study time of a clearly defined, individually‐adjusted social circle would affect the respective norm estimations and behavior of a class of Psychology students ( n  = 89 in January) across their first year of study. Students overestimated alcohol consumption and partially underestimated studying norms. While social circle feedback on alcohol consumption did not clearly affect both individual estimation accuracy and alcohol consumption, feedback on peers' studying time increased studying with no clear effect on estimation accuracy. This indicates that social circle norm feedback may be suitable to evoke behavioral effects. The correction of the detected inaccuracies did not appear to be a precondition for the feedback to be effective.

Resource quality is an important concept in ecology and evolution that attempts to capture the fitness benefits a resource affords to an organism. Yet “quality” is a multivariate concept, potentially affected by many variables pertaining to the resource, its surroundings, and the resource chooser. Researchers often use a small number of proxy variables to simplify their estimation of resource quality, but without vetting their proxies against a wider set of potential quality estimators this approach risks overlooking potentially important characteristics that can explain patterns of resource use in their study systems. Here we used Neolamprologus multifasciatus , a group‐living cichlid fish that utilizes empty snail shells as shelter resources, to examine how shells were used by, and partitioned among, group members in relation to a range of attributes, including shell size, intactness, texture, spatial position, and usage by heterospecifics. This approach generated a comprehensive picture of what characteristics contribute to the attractiveness and quality of each shell resource, confirming the importance of two previously proposed shell characteristics, size and intactness, but highlighting the influences of other unexplored variables, including shell spatial position and usage by heterospecifics. We also present a generally applicable “resource attractiveness index” as a means to estimate resource quality based on resource choice data. This index incorporates information from any number of resource characteristics and is of particular use when researchers wish to quantify resource value, but many characteristics jointly contribute to the value and attractiveness of the resource.

1. In various animal species conspecifics aggregate at sleeping sites. Such aggregations can act as information centres where individuals acquire up-to-date knowledge about their environment. In some species, communal sleeping sites comprise individuals from multiple groups, where each group maintains stable membership over time.

2. We used GPS tracking to simultaneously record group movement in a population of wild vulturine guineafowl (Acryllium vulturinum) to investigate whether communal sleeping sites can facilitate the transfer of information among individuals across distinct groups. These birds live in large and stable groups that move both together and apart, often forming communal roosts containing up to five groups.

3. We first test whether roosts provide the opportunity for individuals to acquire information from members of other groups by examining the spatial organization at roosts. The GPS data reveal that groups intermix, thereby providing an opportunity for individuals to acquire out-group information.

4. We next conduct a field experiment to test whether naïve groups can locate novel food patches when co-roosting with knowledgeable groups. We find that co-roosting substantially increases the chances for the members of a naïve group to discover a patch known to individuals from other groups at the shared roost. Further, we find that the discovery of food patches by naïve groups subsequently shapes their space use and inter-group associations. We also draw on our long-term tracking to provide examples that demonstrate natural cases where communal roosting has preceded large-scale multi-group collective movements that extend into areas beyond the groups' normal ranges.

5. Our findings support the extension of the information centre hypothesis to communal sleeping sites that consist of distinct social groups.

1. To maximize their fitness, plants have to adjust their allocation strategy according to their abiotic and biotic environments. Plants can use the ratio of red to far-red light (R:FR) to sense neighbours, allowing them to modify their growth in response to aboveground competition.

2. In this study, we used supplemental FR light to artificially lower the R:FR of the lower leaves of common sunflowers (Helianthus annuus) to examine how plants change their growth in response to the threat of neighbours. We combined this treatment with a nitrogen fertilization treatment to investigate how responses to neighbour-detection interact with nitrogen limitation.

3. Plants grown in low R:FR increased in height at the expense of root growth, resulting in nitrogen limitation that restricted leaf growth. However, we found that plants reduced their nitrogen investment into leaves in low R:FR. By weakening the nitrogen sink strength of these lower leaves before they experienced low photosynthetically active radiation, plants were able to preemptively allocate nitrogen to leaves higher in the canopy.

4. Plants responded to the perception of neighbours by simultaneously diverting resources from root growth to stem elongation and from leaves threatened by neighbours to leaves that would pose a threat to neighbours. This whole-plant response to neighbour-detection enables plants to change their allocation in a way that simultaneously manages their limited nitrogen and prepares them for future light competition.

We propose to use optimally ordered orthogonal neighbor-joining (O 3 NJ) trees as a new way to visually explore cluster structures and outliers in multi-dimensional data. Neighbor-joining (NJ) trees are widely used in biology, and their visual representation is similar to that of dendrograms. The core difference to dendrograms, however, is that NJ trees correctly encode distances between data points, resulting in trees with varying edge lengths. We optimize NJ trees for their use in visual analysis in two ways. First, we propose to use a novel leaf sorting algorithm that helps users to better interpret adjacencies and proximities within such a tree. Second, we provide a new method to visually distill the cluster tree from an ordered NJ tree. Numerical evaluation and three case studies illustrate the benefits of this approach for exploring multi-dimensional data in areas such as biology or image analysis.

Animal behaviour is often modelled as networks, where, for example, the nodes are individuals of a group and the edges represent behaviour within this group. Different types of behaviours or behavioural categories are then modelled as different yet connected networks which form a multilayer network. Recent developments show the potential and benefit of multilayer networks for animal behaviour research as well as the potential benefit of stereoscopic 3D immersive environments for the interactive visualisation, exploration and analysis of animal behaviour multilayer networks. However, so far animal behaviour research is mainly supported by libraries or software on 2D desktops. Here, we explore the domain-specific requirements for (stereoscopic) 3D environments. Based on those requirements, we provide a proof of concept to visualise, explore and analyse animal behaviour multilayer networks in immersive environments.