Giovanni Petri

This paper uses higher-order topology to analyze brain activity during naturalistic emotion tasks, finding that it captures fine-grained affective structure while pairwise connectivity captures broad arousal.

The paper examines how preserved cortical hierarchy in blindsight-positive patients explains their ability to detect stimuli without awareness after V1 damage.

This paper analyzes sperm whale foraging behavior using acoustic and movement data to show two distinct prey-capture tactics within persistent search patterns.

The paper evaluates higher-order interaction metrics in brain connectivity using fMRI data, finding topological metrics link brain function to behavior better than pairwise models.

The paper uses topological analysis of fMRI dynamics to show that pairwise co-fluctuations better capture task states and link to personality and symptom dimensions than other interaction representations.

This paper develops a whole-brain model to study how transcranial ultrasound stimulation (TUS) induces functional changes in the brain, identifying two mechanisms that predict plasticity-driven effects.

This study shows that information gain in goal-directed learning is encoded through synergistic and higher-order functional interactions across cortical circuits.

This paper introduces a topological fingerprinting method using homological scaffolds from resting-state fMRI data, achieving near-perfect individual identification accuracy.

This study shows that intrinsic cortical hierarchies constrain experience-dependent plasticity in sensory-deprived humans, preserving functional gradients while allowing adaptive reorganization.

This study compares higher-order and pairwise interaction models for fMRI data, showing that higher-order methods better decode tasks, identify individuals, and link brain activity to behavior.

The paper introduces a homological formalism to analyze higher-order properties of human brain functional sub-circuits and identifies task-specific homological differences in brain connectivity.

The paper models the cost of control in neural networks executing multiple tasks and derives an optimal control policy based on information-theoretic principles.

This paper introduces a high-resolution, fast-sampled fMRI technique for whole-brain BOLD signal measurement, demonstrating improved spatial and temporal resolution in human studies.

This study identifies mesoscopic functional connectivity alterations in ASD by analyzing contrast subgraphs across brain networks of typically developed individuals and ASD patients.

This study shows that perturbing oxytocin neurons during zebrafish development leads to altered social behavior and neural connectivity in adulthood.

This study compares topological and traditional metrics for segmenting brain states from fMRI data, finding topological methods more accurate and generalizable.

This paper shows that topological features of EEG data are reference-invariant, while correlation spaces are not, suggesting topological analysis can capture individual brain dynamics.

The paper shows EEG evidence of topological equivalence between functional network organization during imagery and perception tasks, with variations in functional equivalence linked to cognitive effort and learning effects.

The paper analyzes EEG correlates of head position in individuals with different hypnotizability scores using spectral and topological methods, finding hypnotizability modulates large-scale processing differences.

The paper uses Mapper to create gene co-expression networks that reflect brain anatomy and function, validated with the Allen Human Brain Atlas and dopamine-related gene sets.