Biology subjects

Ercsey-Ravasz, M.

Publications and source records attributed to Ercsey-Ravasz, M..

3 recordsLinked to original sources

bioRxiv2026

The trade-off between fractal morphology and function of Drosophila neurons

Studying correlation between structure and function in brain networks has long been a central and compelling topic in neuroscience. Using the FlyWire project's fully digitized Drosophila melanogaster brain map, we analyzed a total number of 125330 3D skeletons of neurons from various functional super-classes and classes. By separating axonal and dendritic arbors of individual neurons we compare several morphological and topological properties, including cable length, fractal dimension, number of nodes, maximum width, and tree height. The fractal dimensions of neurons can reach up to 2.4, with dendritic arbors generally more complex than axonal ones, except in the afferent flow, where the situation is reversed. Correlating fractal dimension with cable length reveals that neurons from the same classes cluster in state space. These clusters densify and separate more clearly as we go deeper down the hierarchical annotation schema, indicating that the brain specializes fractal morphology for distinct functional classes.

neuroscience↗

bioRxiv2026

Network reorganization distinguishes vulnerability and resilience to observational fear

Individuals vary widely in their responses to stress and threat, with some developing persistent fear after adverse experiences while others remain resilient. Such variability also extends to social contexts, where individuals can acquire information about danger by observing others in distress through observational fear learning. The neural mechanisms underlying individual differences in responses to socially conveyed threat remain poorly understood. Here, we examined how variability in OFL relates to large-scale brain network organization. Rats observed conspecifics receiving tone-shock pairings and were later tested for fear responses to the conditioned stimulus. Behavioral analysis revealed two phenotypes: observational-susceptible rats displaying robust freezing and observational-resilient rats showing freezing levels comparable to controls. Despite these differences, both groups exhibited elevated corticosterone responses, indicating that socially conveyed threat was detected across animals. Brain-wide c-Fos mapping across 84 regions combined with graph-theoretical analysis revealed distinct network architectures associated with each phenotype. These findings suggest that susceptibility and resilience to socially acquired fear emerge from differences in distributed brain network organization.

neuroscience↗

bioRxiv2020

Predictability of cortical-cortical connections in the mammalian brain

Despite a five-order magnitude range in size, the mammalian brain exhibits many shared anatomical and functional characteristics that should translate into cortical network commonalities. Here we develop a framework employing machine learning to quantify the degree of predictability of the weighted interareal cortical matrix. Data were obtained with retrograde tract-tracing experiments supplemented by projection length measurements. Using this framework with consistent and edge-complete empirical datasets in the macaque and mouse cortex, we show that there is significant amount of predictability embedded in the interareal cortical networks of both species. At the binary level, links are predictable with an Area Under the ROC curve of at least 0.8 for the macaque. At the weighted level, strengths of the medium and strong links are predictable with at least 85-90% accuracy in mouse and 70-80% in macaque, whereas weak links are not predictable in either species. These observations suggest that the formation and evolution of the cortical network at the mesoscale is to a large extent, rule-based, motivating further research on the architectural invariants of the cortical connectome.

neuroscience↗