Simone Poetto

Maalouf, A., DelPreto, J., Lucas, M., Poetto, S., Andreas, J., Torralba, A., Gero, S., Petri, G., Rus, D., Gruber, D. F.

Science

We quantitatively document a sperm whale birth event, revealing collective support behaviors across kinship lines. Using high-resolution drone footage, computer vision, and multiscale network analysis, we studied the interactions within a Caribbean sperm whale unit comprising two matrilines. Our results suggest that a female family member led birth assistance and that after delivery, all individuals oriented toward and helped lift the newborn, taking turns in a coordinated, cross-kin effort. Despite historically observed foraging segregation, kinship barriers dissolved as all unit members contributed. These analyses provide evidence of birth attendance, or assistance, in a nonprimate species, a behavior long considered characteristic only of humans and their close relatives.

Project CETIRUNES

Zaffina, L., Monti, C., Poetto, S., Lucas, M., Machado Borges, H. J., Deshpande, R., Tonnesen, P., Gruber, D., Gero, S., Santoro, A., Petri, G.

bioRxiv

Predators searching patchy environments must coordinate movements across scales, yet this behavioural hierarchy is not yet technically possible to observe in the deep ocean. Here we show that sperm-whale foraging is organized across two nested levels: directionally persistent search paths and flexible prey-capture tactics. We combine acoustic recordings with reconstructed three-dimensional trajectories from 34 sensor-tag deployments on 20 individual whales in both the eastern Caribbean and the mid-Atlantic. Complete foraging paths exhibit heavy-tailed step lengths and superdiffusive displacement, consistent with Levy-like search. Within these paths, echolocation buzzes resolve into two recurrent acoustic-kinematic tactics, and every sampled whale used both, switching between them within dives. Together, these results reveal a foraging hierarchy in which flexible capture actions unfold within persistent, deliberate large-scale search.

Project CETIRUNES

Aluma, Y., Baron, Z., Barrett, R., Baumgartner, C., Beguš, G., Bhattacharya, S., Bronstein, M. M., Dahan, S., Davis, O., de Haas, S., Defoe, J., DelPreto, J., Dessi, R., Diamant, R., Gatesy, J., George, K., Gero, S., Gibbons, D., Gibbons, D., Gil, S., Goldwasser, S., Gruber, D. F., Harve, O., Hernandez, A., Ishay, M., Jadhav, N., KC, L., Kenny, A., Leitao, A., Lucas, M., Maalouf, A., Malkin, P., Mevorach, Y., Pagani, S., Paradise, O., Petri, G., Poetto, S., Rossi, E., Rus, D., Salino-Hugg, M., Santoro, A., Sharma, P., Tchernov, D., Torralba, A., Tønnesen, P., Vogt, D. M., Wood, R. J.

Scientific Reports

Wild cetacean birth observations are extremely rare, with observations having been recorded in less than 10% of cetacean species. Here, we describe a detailed accounting of a sperm whale (Physeter macrocephalus) birth off the coast of Dominica within a well-documented social unit and consisted of sperm whales collaboratively lifting the newborn out of the water. We recorded data via multiple concurrent methods: underwater audio, aerial drone video, shipboard photography in addition to behavioral observations spanning before, during and after the whale birth. All 11 members from sperm whale “Unit A” were present and participated in the birth, which lasted 34 min from the time the flukes emerged until the completion of delivery. The sperm whale unit made extensive vocalizations, with statistically significant shifts in coda vocal style corresponding to key events, such as the beginning of the birth and interactions with short-finned pilot whales (Globicephala macrorhynchus) shortly after the birth event. An evolutionary analysis of wild cetacean births suggests that newborns being lifted out of the water dates to before the most recent common ancestor of toothed and baleen whales, >36 million years ago, and that cooperative lifting of the newborn is noted, thus far, only in members of Odontoceti (toothed whales). This study provides the most in-depth observations of a wild cetacean birth.

Project CETIRUNES

Santoro, A., Neri, M., Poetto, S., Orsenigo, D., Diano, M., Gatica, M., Petri, G.

Nature Communications

We present the first large-scale comparison of higher-order interaction (HOI) metrics — spanning information theory and topology — applied to resting-state and task fMRI data from 100 Human Connectome Project subjects. We identify three distinct classes of HOI metrics: redundant, synergistic, and topological, with the latter bridging the two. Despite their differences, all metrics align with the brain's unimodal-to-transmodal hierarchy and, in some cases, with receptor architecture. HOI metrics outperform classical functional connectivity in fingerprinting and are more predictive of behavior, positioning them as key tools for linking brain architecture and cognition.

Topological NeuroscienceNetwork FoundationsRUNES

Poetto, S., Merritt, H., Santoro, A., Rabuffo, G., Battaglia, D., Vaccarino, F., Saggar, M., Brovelli, A., Petri, G.

bioRxiv

We show that topological fingerprinting, based on homological scaffolds, significantly outperforms FC-based one. We also show that these scaffolds are distributed across functional subnetworks and we link the structure of topological cycles to information synergy.

Topological NeuroscienceNetwork FoundationsRUNES

Leitao, A., Lucas, M., Poetto, S., Hersh, T. A., Gero, S., Gruber, D., Bronstein, M., Petri, G.

eLife

We provide quantitative evidence suggesting social learning in sperm whales across sociocultural boundaries, using acoustic data from the Pacific and Atlantic Oceans. Traditionally, sperm whale populations are categorized into clans based on their vocal repertoire: the rhythmically patterned click sequences (codas) that they use. Among these codas, identity codas function as symbolic markers for each clan, accounting for 35-60% of codas they produce. We introduce a computational method to model whale speech, which encodes rhythmic microvariations within codas, capturing their vocal style. We find that vocal style-clans closely align with repertoire-clans. However, contrary to vocal repertoire, we show that sympatry increases vocal style similarity between clans for non-identity codas, i.e. most codas, suggesting social learning across cultural boundaries. More broadly, this subcoda structure model offers a framework for comparing communication systems in other species, with potential implications for deeper understanding of vocal and cultural transmission within animal societies.

Project CETI

Lucas, M., Townsend-Teague, A., Neri, M., Poetto, S., Morris, A., Habermann, B., Tichit, L.

J. Open Source Softw., 8, 5872

Phasik is a Python library for analyzing the temporal structure of temporal and partially temporal networks. Temporal networks are used to model complex systems that consist of entities with time-varying interactions. This library provides methods for building temporal networks (including from data), visualizing them, and analyzing their structure. In particular, Phasik focuses on the identification of temporal phases, that is, periods of time during which the system is in a given state. The library supports partially temporal networks for which information about only a subset of the edges’ temporal evolution is available. Phasik is implemented in pure Python and integrates with the rest of the Python scientific stack.

Network Foundations

Azeglio, S., Poetto, S., Savant, L., Nurisso, M.

Computational models of vision have traditionally been developed in a bottom-up fashion, by hierarchically composing a series of straightforward operations - i.e. convolution and pooling - with the aim of emulating simple and complex cells in the visual cortex, resulting in the introduction of deep convolutional neural networks (CNNs). Nevertheless, data obtained with recent neuronal recording techniques support that the nature of the computations carried out in the ventral visual stream is not completely captured by current deep CNN models. To fill the gap between the ventral visual stream and deep models, several benchmarks have been designed and organized into the Brain-Score platform, granting a way to perform multi-layer (V1, V2, V4, IT) and behavioral comparisons between the two counterparts. In our work, we aim to shift the focus on architectures that take into account lateral recurrent connections, a ubiquitous feature of the ventral visual stream, to devise adaptive receptive fields. Through recurrent connections, the input s long-range spatial dependencies can be captured in a local multi-step fashion and, as introduced with Gated Recurrent CNNs (GRCNN), the unbounded expansion of the neuron s receptive fields can be modulated through the use of gates. In order to increase the robustness of our approach and the biological fidelity of the activations, we employ specific data augmentation techniques in line with several of the scoring benchmarks. Enforcing some form of invariance, through heuristics, was found to be beneficial for better neural predictivity.

Cognitive and NeuroAI