Andrea Perna

IMT School for Advanced Studies · Networks Unit

The size structure of autotroph communities – the relative abundance of small vs. large individuals – shapes the functioning of ecosystems. Whether common mechanisms underpin the size structure of unicellular and multicellular autotrophs is, however, unknown. Using a global data compilation, we show that individual body masses in tree and phytoplan...

Group living animals form aggregations and flocks that remain cohesive in spite of internal movements of individuals. This is possible because individual group members repeatedly adjust their position and motion in response to the position and motion of other group members. Here, we develop a theoretical approach to address the question, what gener...

We present a simple three-dimensional model to describe the autonomous expansion of a substrate whose growth is driven by the local mean curvature of its surface. The model aims to reproduce the nest construction process in arboreal Nasutitermes termites, whose cooperation may similarly be mediated by the shape of the structure they are walking on,...

The survival and reproduction of living organisms depend on their ability to achieve an adequate balance between energy intake and energy expenditure. Multiple quantities contribute to this energetic balance, such as the feeding rate, and the allocation of available energy to growth, maintenance, movement and reproduction. Given that many of these...

Termites build complex nests which are an impressive example of self-organization. We know that the coordinated actions involved in the construction of these nests by multiple individuals are primarily mediated by signals and cues embedded in the structure of the nest itself. However, to date there is still no scientific consensus about the nature...

Termites build complex nests which are an impressive example of self-organization. We know that the coordinated actions involved in the construction of these nests by multiple individuals are primarily mediated by signals and cues embedded in the structure of the nest itself. However, to date there is still no scientific consensus about the nature...

Termites build complex nests which are an impressive example of self-organization. We know that the coordinated actions involved in the construction of these nests by multiple individuals are primarily mediated by signals and cues embedded in the structure of the nest itself. However, to date there is still no scientific consensus about the nature...

Termites build complex nests which are an impressive example of self-organization. We know that the coordinated actions involved in the construction of these nests by multiple individuals are primarily mediated by signals and cues embedded in the structure of the nest itself. However, to date there is still no scientific consensus about the nature...

Nests of social insects are an important area for the exchange of food and information among workers. We investigated how the topology of nest chambers (as opposed to nest size or environmental factors) affects the spatial distribution of nestmates and the foraging behavior of Myrmica rubra ant colonies. Colonies were housed in artificial nests, ea...

We present a simple three-dimensional model to describe the autonomous expansion of a substrate which grows driven by the local mean curvature of its surface. The model aims to reproduce the nest construction process in arboreal Nasutitermes termites, whose cooperation may similarly be mediated by the shape of the structure they are walking on, for...

Analysis of some experimental biology data involves linear regression and interpretation of the resulting slope value. Usually, the x-axis measurements include noise. Noise in the x-variable can create regression dilution, and many biologists are not aware of the implications: regression dilution results in an underestimation of the true slope valu...

We understand little about the energetic costs of flight in free‐ranging birds; in part since current techniques for estimating flight energetics in the wild are limited. Accelerometry is known to estimate energy expenditure through body movement in terrestrial animals, once calibrated using a treadmill with chamber respirometry. The flight equival...

Group living animals form aggregations and flocks that remain cohesive in spite of internal movements of individuals. This is possible because individual group members adjust their position and direction of movement in response to the position and motion of other group members. Recent literature has focused on elucidating these 'interaction rules'...

Collective movement is achieved when individuals adopt local rules to interact with their neighbours. How the brain processes information about neighbours' positions and movements may affect how individuals interact in groups. As brain size can determine such information processing it should impact collective animal movement. Here we investigate wh...

Schools of fish and flocks of birds can move together in synchrony and decide on new directions of movement in a seamless way. This is possible because group members constantly share directional information with their neighbors. Although detecting the directionality of other group members is known to be important to maintain cohesion, it is not cle...

Sample video of an U-turn dynamic in a group of 5 fish. Video showing the velocities of fish and interaction dynamics in the group, corresponding to Fig 4 and S1 Video. (AVI)

Directional correlation Hij(t, τ) between fish Fi and Fj. For i = 2, …, 5 (rows) and j = 1, …, 5, j ≠ i (columns), e.g., first row is for fish F2: (A) H21(t, τ), (B) H23(t, τ), (C) H24(t, τ) and (D) H25(t, τ). (TIF)

Distribution of the average duration (in seconds) of (A) individual and (B) collective U-turns in groups of 2 fish. Collective U-turns last around twice the duration of individual U-turns. (TIF)

Distribution of the average duration (in seconds) of (A) individual and (B) collective U-turns in groups of 5 fish. Collective U-turns last almost four times the duration of individual U-turns. (TIF)

Parameter comparison matrix. Matrix of 40 × 40 square cells, where each cell corresponds to the similarity value SV arising from the comparison of the two parameter combinations shown in the corresponding horizontal and vertical axes. We considered 40 parameter combinations, thus the size of the matrix. The similarity value SV is represented by the...

Available data for different values of the average directional correlation threshold Cmin, in the case of N = 5 fish. Small panels: (there are 10, one per experiment) Number of data points available from the respective experiment for each value of Cmin in [0.5, 1]. The values of Cmin are denoted by small circles. Three specific values are shown by...

Collective U-turns observed in experiments with N = 5 fish. (TIF)

Artificial collective U-turns obtained with the null model. (TIF)

Sample video of an U-turn event in a group of 5 fish. Original video of an U-turn event, corresponding to Fig 4 and S2 Video. (AVI)

Number of available data points for different values of Cmin. Solid black line: Remaining data points for each value of Cmin for N = 2 according to the leftmost panel in S6 Fig. Red line: same thing, for N = 5, according to S7 Fig. Dashed line: highest number of available data points before the sharp fall of the black curve at Cmin = 0.95. (TIF)

Different values of τ* for different subsets of the same data set computed with the method of Nagy et al. [23]. Consider the dataset of U-turns of 2 fish composed by U-turn number 1 to U-turn number 36, coming from the same experiment, and divide it in two subsets SA and SB containing respectively the U-turns [1,…,18] and the U-turns [19,…,36]. (A)...

Homogeneous (isotropic) spatial distribution of “influential neighbors” in collective artificial U-turns. (A) Density map of “influential neighbors” location (blue) and their average relative velocity field (arrows) with respect to the focal fish (red arrow). (B) Average spatial distribution. (TIF)

Available data for different values of the average directional correlation threshold Cmin in the case of N = 2 fish. Small panels: (there are 10, one per experiment) Number of data points available from the respective experiment for each value of Cmin in [0.5, 1]. The values of Cmin are denoted by small circles. Three specific values are shown by a...

Predation is thought to shape the macroscopic properties of animal groups, making moving groups more cohesive and coordinated. Precisely how predation has shaped individuals' fine-scale social interactions in natural populations, however, is unknown. Using high-resolution tracking data of shoaling fish (Poecilia reticulata) from populations differi...

Some organisms, including fungi, ants, and slime molds, explore their environment and forage by forming interconnected networks. The plasmodium of the slime mold Physarum polycephalum is a large unicellular amoeboid organism that grows a tubular spatial network through which nutrients, body mass, and chemical signals are transported. Individual pla...

The nests built by social insects are among the most complex structures produced by animal groups. They reveal the social behaviour of a colony and as such they potentially allow comparative studies. However, for a long time, research on nest architecture was hindered by the lack of technical tools allowing the visualisation of their complex 3D str...

The nests built by termites of the genus Apicotermes present a regular succession of floors interconnected by vertical passages. By scanning these nests with X-ray tomography we observed that two different configurations of vertical passages coexist: ramps and helices. Based on our current knowledge of the mechanisms of nest building behaviour in d...

Significance Social insects build some of the most complex nests found in the animal kingdom. Here, we use experiments and modeling to decipher the mechanisms involved in the coordination of nest building in the ant Lasius niger : we first characterize nest architecture and its growth with 3D imaging techniques; then, we test the building responses...

We present a model for the growth of the transportation network inside nests of the social insect subfamily Termitinae (Isoptera, termitidae). These nests consist of large chambers (nodes) connected by tunnels (edges). The model based on the empirical analysis of the real nest networks combined with pruning (edge removal, either random or weighted...

Many group-living animals construct transportation networks of trails, galleries and burrows by modifying the environment to facilitate faster, safer or more efficient movement. Animal transportation networks can have direct influences on the fitness of individuals, whereas the shape and structure of transportation networks can influence community...

Recent research in animal behaviour has contributed to determine how alignment, turning responses, and changes of speed mediate flocking and schooling interactions in different animal species. Here, we propose a complementary approach to the analysis of flocking phenomena, based on the idea that animals occupy preferential, anysotropic positions wi...

Travelling in groups gives animals opportunities to share route information by following cues from each other's movement. The outcome of group navigation will depend on how individuals respond to each other within a flock, school, swarm or herd. Despite the abundance of modelling studies, only recently have researchers developed techniques to deter...

Simulation results for model Topo. (A) Proportion of six-prawn simulations () with a given number of prawns moving CW over time. (B) Final distribution of simulations by number of CW moving prawns for simulations with three, six and twelve prawns. Error bars represent the mean and standard deviation for each proportion as calculated from the final...

Simulation results for model 0. (A) Proportion of six-prawn simulations () with a given number of prawns moving CW over time. (B) Final distribution of simulations by number of CW moving prawns for simulations with three, six and twelve prawns. Error bars represent the mean and standard deviation for each proportion as calculated from the final ten...

Simulation results for model S1. (A) Proportion of six-prawn simulations () with a given number of prawns moving CW over time. (B) Final distribution of simulations by number of CW moving prawns for simulations with three, six and twelve prawns. Error bars represent the mean and standard deviation for each proportion as calculated from the final te...

Simulation results for model S4. (A) Proportion of six-prawn simulations () with a given number of prawns moving CW over time. (B) Final distribution of simulations by number of CW moving prawns for simulations with three, six and twelve prawns. Error bars represent the mean and standard deviation for each proportion as calculated from the final te...

Simulation results for model D1. (A) Proportion of six-prawn simulations () with a given number of prawns moving CW over time. (B) Final distribution of simulations by number of CW moving prawns for simulations with three, six and twelve prawns. Error bars represent the mean and standard deviation for each proportion as calculated from the final te...

Image of the experimental setup. Prawns moving within an annulus of 200 mm external diameter and 70 mm internal diameter. In this instance the total number of prawns , number of clockwise-moving oriented prawns , the polarisation , and the excess polarisation (TIFF)

Simulation results for model MF. (A) Proportion of six-prawn simulations () with a given number of prawns moving CW over time. (B) Final distribution of simulations by number of CW moving prawns for simulations with three, six and twelve prawns. Error bars represent the mean and standard deviation for each proportion as calculated from the final te...

Simulation results for model S2. (A) Proportion of six-prawn simulations () with a given number of prawns moving CW over time. (B) Final distribution of simulations by number of CW moving prawns for simulations with three, six and twelve prawns. Error bars represent the mean and standard deviation for each proportion as calculated from the final te...

Simulation results for model S3. (A) Proportion of six-prawn simulations () with a given number of prawns moving CW over time. (B) Final distribution of simulations by number of CW moving prawns for simulations with three, six and twelve prawns. Error bars represent the mean and standard deviation for each proportion as calculated from the final te...

Simulation results for model D2. (A) Proportion of six-prawn simulations () with a given number of prawns moving CW over time. (B) Final distribution of simulations by number of CW moving prawns for simulations with three, six and twelve prawns. Error bars represent the mean and standard deviation for each proportion as calculated from the final te...

Simulation results for model D3. (A) Proportion of six-prawn simulations () with a given number of prawns moving CW over time. (B) Final distribution of simulations by number of CW moving prawns for simulations with three, six and twelve prawns. Error bars represent the mean and standard deviation for each proportion as calculated from the final te...

Simulation results for model D4. (A) Proportion of six-prawn simulations () with a given number of prawns moving CW over time. (B) Final distribution of simulations by number of CW moving prawns for simulations with three, six and twelve prawns. Error bars represent the mean and standard deviation for each proportion as calculated from the final te...

A summary of provided supplementary figures and videos. (PDF)

Inference of interaction rules of animals moving in groups usually relies on an analysis of large scale system behaviour. Models are tuned through repeated simulation until they match the observed behaviour. More recent work has used the fine scale motions of animals to validate and fit the rules of interaction of animals in groups. Here, we use a...

Recent experiments by Ward et al. have shown that fish in a moving fish group detects hidden predators faster and more accurately than isolated individuals. The increase in speed, in particular, seems to be a consequence of the movement-mediated nature of the interactions used by fish to share information. The present work aims at investigating the...

Collective animal behaviour is the study of how interactions between individuals produce group level patterns, and why these interactions have evolved. This study has proved itself uniquely interdisciplinary, involving physicists, mathematicians, engineers as well as biologists. Almost all experimental work in this area is related directly or indir...

Inference of interaction rules of animals moving in groups usually relies on an analysis of large scale system behaviour. Models are tuned through repeated simulation until they match the observed behaviour. More recent work has used the fine scale motions of animals to validate and fit the rules of interaction of animals in groups. Here, we use a...

Video illustrating how the pheromone maps are inferred from the movement of the ants. Whenever a portion of the arena is covered by one ant for one frame, the pheromone map at that location is incremented by a constant amount. Notice that the video is made for illustrative purposes: real experiments involved filming a larger portion of the arena fr...

Video illustrating how the movement of the ants is analysed and correlated to the pheromone maps. Every twenty frames (0.4 s) each ant present under the field of view of the camcorder is detected and its position marked. The ant is followed over two intervals of 10 frames each and its path is described by two paths of ten frames each and a turning...

We studied the formation of trail patterns by Argentine ants exploring an empty arena. Using a novel imaging and analysis technique we estimated pheromone concentrations at all spatial positions in the experimental arena and at different times. Then we derived the response function of individual ants to pheromone concentrations by looking at correl...

Collective motion, where large numbers of individuals move synchronously together, is achieved when individuals adopt interaction rules that determine how they respond to their neighbors' movements and positions. These rules determine how group-living animals move, make decisions, and transmit information between individuals. Nonetheless, few studi...

We will deonstrate the use of (more or less!) Bayesian methods for inferring interaction rules between individuals in a system of collective animal motion. We examine a group of prawns moving in an effectively one-dimensional environment, which we reduce to a binary classification problem, aiming to infer the factors that predict whether an individ...

We propose a method for quantitative characterization of spatial networklike patterns with loops, such as surface fracture patterns, leaf vein networks, and patterns of urban streets. Such patterns are not well characterized by purely topological estimators: also patterns that both look different and result from different morphogenetic processes ca...

We propose a new method for quantitative characterization of spatial network-like patterns with loops, such as surface fracture patterns, leaf vein networks and patterns of urban streets. Such patterns are not well characterized by purely topological estimators: also patterns that both look different and result from different morphogenetic processe...

free download at https://mitpress.mit.edu/sites/default/files/titles/alife/0262297140chap61.pdf

Social insect colonies build large net-like systems: gallery and trail networks. Many such networks appear to show near-optimal performance. Focusing on the network system inside termite nests we address the question how simple agents with probabilistic behaviour can control and optimize the growth of a structure with size several magnitude orders...

Optimization has been shown to be a driving force for the evolution of some biological structures, such as neural maps in the brain or transport networks. Here we show that insect networks also display characteristic traits of optimality. By using a graph representation of the chamber organization of termite nests and a disordered lattice model, it...

Transport networks are a key component of human and natural societies that enable efficient communication at a low cost. Here, we study the topological efficiency of the three-dimensional networks of galleries in termite nests and how spatial constraints affect the organisation of these networks. Cubitermes termite nests have far better than random...

Recent studies have introduced computer tomography (CT) as a tool for the visualisation and characterisation of insect architectures. Here, we use CT to map the three-dimensional networks of galleries inside Cubitermes nests in order to analyse them with tools from graph theory. The structure of these networks indicates that connections inside the...

Human psychophysical observations, computational models, and the selectivity of neurons in primary visual cortex all suggest that an early step in visual processing is the detection of features such as lines and edges. However, previous fMRI experiments investigating the responses of early visual areas to phase coherence have led to apparently disc...

Transportation networks are a key component of human societies that enable efficient communication at a low cost. Like humans, also most animal species build transportation networks. However, the topology of animal built transportation networks only results from the interactions between animals and the environment, in a completely unplanned and sel...

This study investigates the role played by individual spatial scales in determining the apparent brightness of greyscale patterns. We measured the perceived difference in brightness across an edge in the presence of notch filtering and high-pass filtering for two stimulus configurations, one that elicits the perception of transparency and one that...