Biology subjects

Reillo, I.

Publications and source records attributed to Reillo, I..

3 recordsLinked to original sources

bioRxiv2026

Cortical folding patterns are encoded in the geometry of the unfolded neocortex.

Cortical folding patterns are conserved across individuals of gyrencephalic species and are closely related to cytoarchitectural organisation, connectivity, and function. Early morphogen gradients have been proposed as the molecular source of positional information encoding these patterns - a gyral molecular protomap - but the contribution of neocortical geometry to this encoding has not been examined. Here we show that the geometry of the unfolded ferret brain guides the adult folding pattern before any folding has occurred. Using high-resolution MRI surface reconstructions from postnatal day (P) 0 to adults, we demonstrate that newborn neocortical curvature predicts mature curvature maps, sulcal-gyral fate, and fold orientation. Pre-folding curvature correlates with expression of key patterning genes, and a mediation analysis indicates that geometry at P0 is the principal predictor of sulcal-gyral fate at P6. Mechanical simulations show that regions of high curvature act as autonomous anchors that organise the folding pattern. These results suggest that neocortical geometry constitutes a form of positional information that complements molecular patterns in regulating cortical organisation, and that a complete account of cortical development requires the integration of geometric and mechanical processes alongside molecular signalling.

neuroscience↗

bioRxiv2019

Comparison between diffusion MRI tractography and histological tract-tracing of cortico-cortical structural connectivity in the ferret brain

The anatomical wiring of the brain is a central focus in network neuroscience. Diffusion MRI tractography offers the unique opportunity to investigate the brain fiber architecture in vivo and non invasively. However, its reliability is still highly debated. Here, we explored the ability of diffusion MRI tractography to match invasive anatomical tract-tracing connectivity data of the ferret brain. We also investigated the influence of several state-of-the-art tractography algorithms on this match to ground truth connectivity data. Tract-tracing connectivity data were obtained from retrograde tracer injections into the occipital, parietal and temporal cortices of adult ferrets. We found that the relative densities of projections identified from the anatomical experiments were highly correlated with the estimates from all the studied diffusion tractography algorithms (Spearmans rho ranging from 0.67 to 0.91), while only small, non-significant variations appeared across the tractography algorithms. These results are comparable to findings reported in mouse and monkey, increasing the confidence in diffusion MRI tractography results. Moreover, our results provide insights into the variations of sensitivity and specificity of the tractography algorithms and hence, into the influence of choosing one algorithm over another.

neuroscience↗

bioRxiv2018

A computational approach for characterizing the structural basis of intrinsic coupling modes of the cerebral cortex

Intrinsic coupling modes (ICMs) provide a framework for describing the interactions of ongoing brain activity at multiple spatial and temporal scales. Two families of ICMs can be distinguished: phase and envelope ICMs. The principles that shape these ICMs remain partly elusive, in particular their relation to the underlying brain structure. Here we explored structure-function relationships in the ferret brain between ICMs quantified from ongoing brain activity recorded with chronically implanted ECoG arrays and structural connectivity (SC) obtained from high-resolution diffusion MRI tractography. Large-scale computational models as well as simple topological ingredients of SC were used to explore the ability to predict both types of ICMs. Importantly, all investigations were conducted with ICM measures that are sensitive or insensitive to volume conduction effects. The results show that both types of ICMs are strongly related to SC, except when using ICM measures removing zero-lag synchronizations. Computational models are challenged to predict these ICM patterns consistently, and simple predictions from SC topological features can sometimes outperform them. Overall, the results demonstrate that patterns of cortical functional coupling as reflected in both phase and envelope ICMs bear a substantial relation to the underlying structural connectivity of the cerebral cortex.

neuroscience↗