Experimental data and code for "Consensus formation and change are enhanced by neutrality"

This dataset contains raw and processed data on a number of experiments on marching locust nymphs in a ring-shaped arena. With sufficiently large densities the locusts exhibit coherent motion and directional switching.
The code accompanying that data is for processing the raw data, analysing the processed data and simulating both spatial and non-spatial models of the data.

This dataset also contains raw and processed data on a number of experiments into consensus formation in which human participants played an iterated voting game.
The code accompanying the data is for processing the raw data, analysing the processed data and simulating mathematical models of the process.

This dataset also contains code to simulate a model of nucleosome modification. The model describes the modifications of nucleosomes by recruitment of modifying and unmodifying enzymes from their neighbours or in a ‘recruitment-independent’ (spontaneous) manner. In the model, nucleosomes can be acetylated (A), unmodified (U) or methylated (M), hence A and M represent active states, while U is a neutral state.

Effective collective decision-making in human and animal groups requires robust mechanisms for consensus formation and change, typically via feedback loops in which individuals adapt their behaviour and opinions based on their perception of others. Such processes have been observed in the onset of motion in insect swarms and is believed to manifest across scales from nucleosomes to entire societies. However, levels of participation can be highly variable over time, with individuals sometimes adopting neutral positions such as moving to the back of a group or abstaining from a vote.

In this work we present a new theoretical and experimental analysis showing that neutrality has two important and hitherto unreported benefits to collective decision making. First, it enables the robust formation of consensus in groups of individuals applying simple linear reasoning, updating their state after consideration of at most one other individual at a time. Second, we find that neutral actors can facilitate efficient consensus change by reducing the effective population size during transitions. These findings are derived from a new general mathematical model of collective binary decision problems, and validated against experiments with insect and human populations. Our results provide a parsimonious explanation of how groups of animals and humans quickly reach and overturn consensus, suggesting efficient solutions to collective decision-making problems.