Project description:Individual animals are adept at making decisions and have cognitive abilities, such as memory, which allow them to hone their decisions. Social animals can also share information. This allows social animals to make adaptive group-level decisions. Both individual and collective decision-making systems also have drawbacks and limitations, and while both are well studied, the interaction between them is still poorly understood. Here, we study how individual and collective decision-making interact during ant foraging. We first gathered empirical data on memory-based foraging persistence in the ant Lasius niger. We used these data to create an agent-based model where ants may use social information (trail pheromones), private information (memories) or both to make foraging decisions. The combined use of social and private information by individuals results in greater efficiency at the group level than when either information source was used alone. The modelled ants couple consensus decision-making, allowing them to quickly exploit high-quality food sources, and combined decision-making, allowing different individuals to specialize in exploiting different resource patches. Such a composite collective decision-making system reaps the benefits of both its constituent parts. Exploiting such insights into composite collective decision-making may lead to improved decision-making algorithms.
Project description:The Tibetan Plateau and the surrounding (TPS) with its vast land mass and high elevation affects regional climate and weather. The TPS is also the headwater of 9 major Asian rivers that provide fresh water for 1.65 billion people and many ecosystems, with wet season (May-September) precipitation being the critical component of the fresh water. Using station observations, ERA-Interim and MERRA2 reanalysis, we find that wet season precipitation displays vertical gradients (i.e., changes with elevation) that vary within the region on the TPS. The decrease of precipitation with elevation occurs in the interior TPS with elevation larger than 4000 m, little or no change over the southeastern TPS, and increase elsewhere. The increase of precipitation with elevation is caused by increasing convective available potential energy (CAPE) and decreasing lifting condensation level (LCL) with elevation overwhelming the effects of decreasing total column water vapor (TCWV) with elevation. The decreasing precipitation with elevation is due to the combined effects of increasing LCL and decreasing TCWV. LCL and CAPE play a more important role than TCWV in determining the spatial patterns. These findings are important for hydrology study in observation scarce mountainous areas, water resources and ecosystem managements in the region.
Project description:Animals on the move often communicate with each other through some specific postures. Previous studies have shown that social interaction plays a role in communication process. However, it is not clear whether the affinity of group members can affect visual communication. We studied a group of free-ranging Tibetan macaques (Macaca thibetana) at Huangshan Mountain, China, and answered whether and how social centrality or relatives matter in visual signals during group movement using Tobit regression modeling. All individuals emitted the signals of back-glances and pauses in collective movement. The emission of two signals decreased with the number of participants increased. The back-glance and pause signals emitted by the participating individuals were stronger as the position moved backward in the group. Sex, age, and rank had no significant influence on back-glance and pause signals. Individuals with higher social centrality would emit more pause signals, but social centrality had no effect on the back-glance signal. Individuals with more relatives in the group had more back-glance signals, but this had no effect on the pause signal. This study verifies that social centrality and the number of relatives have effects on visual signals in Tibetan macaques. We provide insights into the relationship between communication behaviors and group cooperation in social animals.
Project description:Complex biological systems are increasingly understood in terms of the algorithms that guide the behavior of system components and the information pathways that link them. Much attention has been given to robust algorithms, or those that allow a system to maintain its functions in the face of internal or external perturbations. At the same time, environmental variation imposes a complementary need for algorithm versatility, or the ability to alter system function adaptively as external circumstances change. An important goal of systems biology is thus the identification of biological algorithms that can meet multiple challenges rather than being narrowly specified to particular problems. Here we show that emigrating colonies of the ant Temnothorax curvispinosus tune the parameters of a single decision algorithm to respond adaptively to two distinct problems: rapid abandonment of their old nest in a crisis and deliberative selection of the best available new home when their old nest is still intact. The algorithm uses a stepwise commitment scheme and a quorum rule to integrate information gathered by numerous individual ants visiting several candidate homes. By varying the rates at which they search for and accept these candidates, the ants yield a colony-level response that adaptively emphasizes either speed or accuracy. We propose such general but tunable algorithms as a design feature of complex systems, each algorithm providing elegant solutions to a wide range of problems.
Project description:How social groups and organisms decide between alternative feeding sites or shelters has been extensively studied both experimentally and theoretically. One key result is the existence of a symmetry-breaking bifurcation at a critical system size, where there is a switch from evenly distributed exploitation of all options to a focussed exploitation of just one. Here we present a decision-making model in which symmetry-breaking is followed by a symmetry restoring bifurcation, whereby very large systems return to an even distribution of exploitation amongst options. The model assumes local positive feedback, coupled with a negative feedback regulating the flow toward the feeding sites. We show that the model is consistent with three different strains of the slime mold Physarum polycephalum, choosing between two feeding sites. We argue that this combination of feedbacks could allow collective foraging organisms to react flexibly in a dynamic environment.
Project description:The Schizothoracinae fishes, endemic species in the Tibetan Plateau, are considered as ideal models for highland adaptation and speciation investigation. Despite several transcriptome studies for highland fishes have been reported before, the transcriptome information of Schizothoracinae is still lacking. To obtain comprehensive transcriptome data for Schizothoracinae, the transcriptome of a total of 183 samples from 14 representative Schizothoracinae species, were sequenced and de novo assembled. As a result, about 1,363 Gb transcriptome clean data was obtained. After the assembly, we obtain 76,602-154,860 unigenes for each species with sequence N50 length of 1,564-2,143 bp. More than half of the unigenes were functionally annotated by public databases. The Schizothoracinae fishes in this work exhibited diversified ecological distributions, phenotype characters and feeding habits; therefore, the comprehensive transcriptome data of those species provided valuable information for the environmental adaptation and speciation of Schizothoracinae in the Tibetan Plateau.
Project description:We tend to think that everyone deserves an equal say in a debate. This seemingly innocuous assumption can be damaging when we make decisions together as part of a group. To make optimal decisions, group members should weight their differing opinions according to how competent they are relative to one another; whenever they differ in competence, an equal weighting is suboptimal. Here, we asked how people deal with individual differences in competence in the context of a collective perceptual decision-making task. We developed a metric for estimating how participants weight their partner's opinion relative to their own and compared this weighting to an optimal benchmark. Replicated across three countries (Denmark, Iran, and China), we show that participants assigned nearly equal weights to each other's opinions regardless of true differences in their competence-even when informed by explicit feedback about their competence gap or under monetary incentives to maximize collective accuracy. This equality bias, whereby people behave as if they are as good or as bad as their partner, is particularly costly for a group when a competence gap separates its members.
Project description:Joint action research explores how multiple humans can coordinate their movements to achieve common goals. When there is uncertainty about the joint goal, individuals need to integrate their perceptual information of the environment to collaboratively determine their new goal. To ensure that a group reaches a consensus about the goal, collective decision making among the individuals is required. Collective decision making can be facilitated by nonverbal expressions of opinions and associated confidence levels. Here, we show that confidence sharing in groups of 2, 3, and 4 individuals can be studied using their trajectories when jointly moving toward one of several options. We found that both opinions and confidence levels can be distinguished in individual movement trajectories, and found that movement features can predict an individual's influence. Our results suggest that movement trajectories are a valid way to study confidence sharing in human collective decision making.
Project description:The study of collective decision-making spans various fields such as brain and behavioural sciences, economics, management sciences, and artificial intelligence. Despite these interdisciplinary applications, little is known regarding how a group of simple 'yes/no' units, such as neurons in the brain, can select the best option among multiple options. One prerequisite for achieving such correct choices by the brain is correct evaluation of relative option quality, which enables a collective decision maker to efficiently choose the best option. Here, we applied a sensory discrimination mechanism using yes/no units with differential thresholds to a model for making a collective choice among multiple options. The performance corresponding to the correct choice was shown to be affected by various parameters. High performance can be achieved by tuning the threshold distribution with the options' quality distribution. The number of yes/no units allocated to each option and its variability profoundly affects performance. When this variability is large, a quorum decision becomes superior to a majority decision under some conditions. The general features of this collective decision-making by a group of simple yes/no units revealed in this study suggest that this mechanism may be useful in applications across various fields.
Project description:While collective intelligence (CI) is a powerful approach to increase decision accuracy, few attempts have been made to unlock its potential in medical decision-making. Here we investigated the performance of three well-known collective intelligence rules ("majority", "quorum", and "weighted quorum") when applied to mammography screening. For any particular mammogram, these rules aggregate the independent assessments of multiple radiologists into a single decision (recall the patient for additional workup or not). We found that, compared to single radiologists, any of these CI-rules both increases true positives (i.e., recalls of patients with cancer) and decreases false positives (i.e., recalls of patients without cancer), thereby overcoming one of the fundamental limitations to decision accuracy that individual radiologists face. Importantly, we find that all CI-rules systematically outperform even the best-performing individual radiologist in the respective group. Our findings demonstrate that CI can be employed to improve mammography screening; similarly, CI may have the potential to improve medical decision-making in a much wider range of contexts, including many areas of diagnostic imaging and, more generally, diagnostic decisions that are based on the subjective interpretation of evidence.