Andrea Santoro

Zaffina, L., Diano, M., Petruso, F., Preti, M. G., Amico, E., Morgenroth, E., Petri, G., Van De Ville, D., Vuilleumier, P. O., Santoro, A.

bioRxiv

Emotions are thought to emerge from co-activation among distributed brain systems, yet traditional fMRI analyses typically examine localized responses and pairwise connections, potentially overlooking interactions among groups of regions. Here, we use time-resolved higher-order topology to characterize these group interactions during naturalistic viewing of 14 films totaling over 2.5 h, continuously annotated across 50 affective features. The homological scaffold, representing evolving group-level topology, most closely tracks recurrent emotional states and best predicts fine-grained affective profiles. This sensitivity diminishes when emotion is compressed into dimensions of valence, arousal, and power, where pairwise connectivity captures the dominant arousal signal. Across three independent datasets, arousal predictions transfer most robustly through pairwise connectivity, while the relative geometry of broad affective states remains conserved across film narratives despite poor valence generalization. These findings reveal complementary neural representations of emotion: higher-order topology captures fine-grained affective structure, whereas pairwise connectivity provides a portable readout of broad arousal.

Topological Neuroscience

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

Santoro, A., Nurisso, M., Petri, G.

EUSIPCO

We propose edge-based Laplacian operators for processing brain signals, moving beyond traditional node-centric approaches to capture higher-order topological features of brain functional data.

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

Santoro, A., Battiston, F., Lucas, M., Petri, G., Amico, E.

Nature Communications

Traditional models of human brain activity often represent it as a network of pairwise interactions between brain regions. Going beyond this limitation, recent approaches have been proposed to infer higher-order interactions from temporal brain signals involving three or more regions. However, to this day it remains unclear whether methods based on inferred higher-order interactions outperform traditional pairwise ones for the analysis of fMRI data. To address this question, we conducted a comprehensive analysis using fMRI time series of 100 unrelated subjects from the Human Connectome Project. We show that higher-order approaches greatly enhance our ability to decode dynamically between various tasks, to improve the individual identification of unimodal and transmodal functional subsystems, and to strengthen significantly the associations between brain activity and behavior. Overall, our approach sheds new light on the higher-order organization of fMRI time series, improving the characterization of dynamic group dependencies in rest and tasks, and revealing a vast space of unexplored structures within human functional brain data, which may remain hidden when using traditional pairwise approaches.

Network FoundationsTopological Neuroscience

Santoro, A., Battiston, F., Petri, G., Amico, E.

Nature Physics

Time series analysis has proven to be a powerful method to characterize several phenomena in biology, neuroscience and economics, and to understand some of their underlying dynamical features. Several methods have been proposed for the analysis of multivariate time series, yet most of them neglect the effect of non-pairwise interactions on the emerging dynamics. Here, we propose a framework to characterize the temporal evolution of higher-order dependencies within multivariate time series. Using network analysis and topology, we show that our framework robustly differentiates various spatiotemporal regimes of coupled chaotic maps. This includes chaotic dynamical phases and various types of synchronization. Hence, using the higher-order co-fluctuation patterns in simulated dynamical processes as a guide, we highlight and quantify signatures of higher-order patterns in data from brain functional activity, financial markets and epidemics. Overall, our approach sheds light on the higher-order organization of multivariate time series, allowing a better characterization of dynamical group dependencies inherent to real-world data.

Network Foundations