Biology subjects

Toro, R.

Publications and source records attributed to Toro, R..

At least 19 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↗

bioRxiv2025

Principles of neocortical organisation and behaviour in primates

One sentence summaryThe study of brain MRI from 70 different primate species reveals a fundamental principle of neocortical organisation and behaviour driven by mechanical morphogenesis. The development and evolution of neocortical organisation is typically explained by the interaction of two fundamental factors: genetics and experience-dependent processes. Morphogens and signalling molecules would orchestrate the formation of neocortical areas and connection networks, which are later refined through exposure to environmental stimuli. Evolutionary changes to these genetic programs are thought to account for the diversity of brains and behaviours observed in extant species. However, our phylogenetic comparative study of primate neuroanatomy and behaviour shows this view is incomplete. Using brain MRI from 70 primate species we observed that not only the degree of folding but also the folding pattern changes continuously with brain volume, independently of phylogenetic position. To better understand the consequences of this continuity we focused on New and Old World monkeys which diverged approximately 47 million years ago. Large New World monkeys, such as capuchins, have a significantly larger and more folded neocortex than many of their close phylogenetic relatives, whose brains are barely folded. Notably, in addition to folding, their thickness and connectivity patterns were almost identical to those of phylogenetically distant Old World monkeys. Combined analyses of MRI and endocasts from 105 primate species indicated that the highly folded neocortex of large New World monkeys evolved independently from a common ancestor with a small, unfolded brain. Remarkably, across all 70 species, behavioural similarity correlated substantially more with neuroanatomical similarity than with phylogenetic similarity. Our results challenge the prevailing explanation of the development and evolution of neocortical organisation. We propose that the "capuchin anomaly" can be resolved by incorporating mechanical morphogenesis, alongside genetics and experience, as a third fundamental factor. Growth-driven mechanical instabilities would produce similar neuroanatomical organisation patterns and behaviours, emerging independently of the specific genetic determinants of that growth.

neuroscience↗

bioRxiv2025

Empowering multitrait brain phenotypes GWAS

Brain magnetic resonance imaging (MRI) data are now becoming available in human genetic cohorts including thousands of participants, providing a powerful mean to decipher the genetic architecture of brain phenotypes. Univariates genome-wide association screenings (GWAS) are typically applied as a baseline approach, but there are increasing interest for multitrait approaches to both increase statistical power and uncover shared structure underlying those phenotypes. However, there are limited guidelines on how to select phenotypes to be analyzed jointly and optimize power. Here we investigated factors impacting variant discoverability of state-of-the art multitrait GWAS using 1,010 MRI-derived phenotypes measured in 32,947 participants from the UK Biobank. Our study shows that the expected gain of multitrait approaches over univariate GWAS is highly predictable. We further propose data-driven strategy to define optimize sets and compare its performances with biologically driven approaches.

neuroscience↗

bioRxiv2025

Precon_all: A species-agnostic automated pipeline for non-human cortical surface reconstruction

Cortical surface reconstruction has changed how we study brain morphology and geometry. However, extending these methods to non-human species has been limited by the lack of standardized pipelines, anatomical templates, and variability in imaging protocols. To address these challenges, we present Precon_all, an open-source, species-agnostic pipeline that automates cortical surface reconstruction for non-human neuroimaging. It runs reliably across a wide range of anatomical structures and imaging conditions and has been successfully applied to datasets from primates, carnivores, and artiodactyls. Its modular framework mirrors human neuroimaging workflows, supports manual quality control, and produces outputs compatible with FreeSurfer and Connectome Workbench. In doing so, it substantially reduces technical barriers to non-human neuroimaging. As data-sharing initiatives continue to expand access to non-human imaging datasets, Precon_all provides a scalable and standardized solution that supports the broader adoption of surface-based methods for studying cortical evolution through comparative neuroscience.

neuroscience↗

bioRxiv2025

Morphogenesis and morphometry of brain folding patterns across species

Evolutionary adaptations associated with the formation of a folded cortex in many mammalian brains are thought to be a critical specialization associated with higher cognitive function. The dramatic surface expansion and highly convoluted folding of the cortex during early development is a theme with variations that suggest the need for a comparative study of cortical gyrification. Here, we use a combination of physical experiments using gels, computational morphogenesis, and geometric morphometrics to study the folding of brains across different species. Starting with magnetic resonance images of brains of a newborn ferret, a fetal macaque, and a fetal human, we construct two-layer physical gel brain models that swell superficially in a solvent, leading to folding patterns similar to those seen in vivo. We then adopt a three-dimensional continuum model based on differential growth to simulate cortical folding in silico. Finally, we deploy a comparative morphometric analysis of the in vivo, in vitro, and in silico surface buckling patterns across species. Our study shows that a simple mechanical instability driven by differential growth suffices to explain cortical folding and suggests that variations in the tangential growth and different initial geometries are sufficient to explain the differences in cortical folding across species.

neuroscience↗

bioRxiv2023

Linking the genetic structure of neuroanatomical phenotypes with psychiatric disorders

There is increasing evidence of shared genetic factors between psychiatric disorders and brain magnetic resonance imaging (MRI) phenotypes. However, deciphering the joint genetic architecture of these outcomes has proven challenging, and new approaches are needed to infer potential genetic structure underlying those phenotypes. Here, we demonstrate how multivariate analyses can help reveal links between MRI phenotypes and psychiatric disorders missed by univariate approaches. We first conducted univariate and multivariate genome-wide association studies (GWAS) for eight MRI-derived brain volume phenotypes in 20K UK Biobank participants. We performed various enrichment analyses to assess whether and how univariate and multitrait approaches can distinguish disorder-associated and non-disorder-associated variants from six psychiatric disorders: bipolarity, attention-deficit/hyperactivity disorder (ADHD), autism, schizophrenia, obsessive-compulsive disorder, and major depressive disorder. Univariate MRI GWAS displayed only negligible genetic correlation with psychiatric disorders at all the levels we investigated. Multitrait GWAS identified multiple new associations and showed significant enrichment for variants related to both ADHD and schizophrenia. We further clustered top associated variants based on their MRI multitrait association using an optimized k-medoids approach and detected two clusters displaying not only enrichment for association with ADHD and schizophrenia, but also consistent direction of effects. Functional annotation analyses pointed to multiple potential mechanisms, suggesting in particular a role of neurotrophin pathways on both MRI and schizophrenia. Altogether our results show that multitrait association signature can be used to infer genetically-driven latent MRI variables associated with psychiatric disorders, opening paths for future biomarker development.

genetics↗

bioRxiv2023

Primate Cerebellar Scaling in Connection to the Cerebrum: A 34-Species Phylogenetic Comparative Analysis

The cerebellum has increasingly been recognized for its role in diverse functional processes. The reciprocally connected cerebello-cerebral system may scaffold both brain size increase and advanced associative abilities, evolving highly coordinately in primates. In parallel, functional cerebello-cerebral modules have undergone reorganization and cerebellar lobules crura I-II (the ansiform area across mammals) have been reported to be specifically expanded in humans. Here we manually segmented 63 cerebella (34 primate species; 9 infraorders) and 30 crura I-II (13 species; 8 infraorders). We show that both constraints and reorganization may shape the evolution of the primate cerebello-cerebral system. Using phylogenetic generalized least squares, we find that the cerebellum scales isometrically with the cerebral cortex, whereas crura I-II scale hyper-allometrically versus both. Our phylogenetic analyses evidence primate-general crura I-II hyperscaling in contrast to virtually isometric cerebello-cerebral scaling. Crura I-II hyperscaling may be important for associative and cognitive brain functions in an evolutionary context.

evolutionary biology↗

bioRxiv2023

A conserved, non-canonical insert in mitochondrial fission protein 1 (FIS1) is required for DRP1 and TBC1D15 recruitment and fission

Mitochondrial fission protein 1 (FIS1) is conserved in all eukaryotes yet its activity in metazoans is thought divergent from lower eukaryotes like fungi. To address this discrepancy, structure-based sequence alignments revealed a conserved but non-canonical, three-residue insert in a turn of FIS1, suggesting conserved activity. In vertebrate FIS1 this insert is serine (S45), lysine (K46), and tyrosine (Y47). To determine the biological role of this "SKY insert", three variants were evaluated for their fold, and tested in HCT116 cells for altered mitochondrial morphology and recruitment of effectors, DRP1 and TBC1D15. Substitution of the SKY insert with three alanine residues (AAA), or deletion of the insert ({Delta}SKY), did not substantially alter the fold or thermal stability of the protein. Replacing SKY with a canonical turn ({Delta}SKYD49G) introduced significant conformational heterogeneity by NMR that was removed upon deletion of a known regulatory region, the FIS1 arm. Expression of AAA fragmented mitochondria into perinuclear clumps associated with increased mitochondrial DRP1 similar to the wild-type protein. In contrast, expression of {Delta}SKY variants elongated mitochondrial networks and reduced mitochondrial DRP1. Co-expression of YFP-TBC1D15 partially rescued mitochondrial morphology and DRP1 recruitment for {Delta}SKY variants, although {Delta}SKY variants were markedly unable to support TBC1D15 assembly into punctate structures found upon co-expression with wildtype FIS1 or the AAA variant. Collectively these results show that FIS1 activity can be modulated by conserved residues supporting a generalized model whereby FIS1 is governed by intramolecular interactions between the regulatory FIS1 arm and SKY insert that may be conserved across species.

cell biology↗

bioRxiv2022

Diversity and evolution of cerebellar folding in mammals

The process of brain folding is thought to play an important role in the development and organisation of the cerebrum and the cerebellum. The study of cerebellar folding is challenging due to the small size and abundance of its folia. In consequence, little is known about its anatomical diversity and evolution. We constituted an open collection of histological data from 56 mammalian species and manually segmented the cerebrum and the cerebellum. We developed methods to measure the geometry of cerebellar folia and to estimate the thickness of the molecular layer. We used phylogenetic comparative methods to study the diversity and evolution of cerebellar folding and its relationship with the anatomy of the cerebrum. Our results show that the evolution of cerebellar and cerebral anatomy follows a stabilising selection process. Ancestral estimations indicate that size and folding of the cerebrum and cerebellum increase and decrease concertedly through evolution. Our analyses confirm the strong correlation between cerebral and cerebellar volumes across species, and show that large cerebella are disproportionately more folded than smaller ones. Compared with the extreme variations in cerebellar surface area, folial wavelength and molecular layer thickness varied only slightly, showing a much smaller increase in the larger cerebella. These findings provide new insights into the diversity and evolution of cerebellar folding and its potential influence on brain organisation across species.

neuroscience↗

bioRxiv2022

Autism excitation-inhibition imbalance linked to brain hyperconnectivity: An analysis based on 657 autistic subjects

The large heterogeneity in autism spectrum disorder (ASD) is a major drawback for the development of therapies. Here, we apply consensus-subtyping strategies based on functional connectivity patterns to a population of N=657 quality-assured autistic subjects. We found two major subtypes (each divided hierarchically into several minor subtypes): Subtype 1 exhibited hypoconnectivity (less average connectivity than typically developing controls) and subtype 2, hyperconnectivity. The two subtypes did not differ in structural imaging metrics in any of the regions analyzed (64 cortical and 14 subcortical), nor in any of the behavioral scores (including Intelligence Quotient, ADI and ADOS). Finally, we used the Allen Human Brain Atlas of gene transcription to show that subtype 2, corresponding with about 42% of all patients, had significant enrichment (after multiple comparisons correction) to excitation-inhibition (E/I) imbalance, a leading reported mechanism in the developmental pathophysiology of ASD. Altogether, our results support a link between E/I imbalance and brain hyperconnectivity in ASD, an association that does not exist in hypoconnected autistic subjects.

neuroscience↗

bioRxiv2021

Comparing Brain Asymmetries Independently of Brain Size

Studies examining cerebral asymmetries typically divide the L-R Measure (e.g., Left- Right Volume) by the L+R Measure to obtain an Asymmetry Index (AI). However, contrary to widespread belief, such a division fails to render the AI independent from the L+R Measure and/or from total brain size. As a result, variations in brain size may bias correlation estimates with the AI or group differences in AI. We investigated how to analyze brain asymmetries in to distinguish global from regional effects, and report unbiased group differences in cerebral asymmetries. We analyzed the extent to which the L+R Measure, Total Cerebral Measure (TCM, e.g., Total Brain Volume), and L-R TCM predict regional asymmetries. As a case study, we assessed the consequences of omitting each of these predictors on the magnitude and significance of sex differences in asymmetries. We found that the L+R Measure, the TCM, and the L-R TCM predicted the AI of more than 89% of regions and that their relationships were generally linear. Removing any of these predictors changed the significance of sex differences in 33% of regions and the magnitude of sex differences across 13-42% of regions. Although we generally report similar sex and age effects on cerebral asymmetries to those of previous large-scale studies, properly adjusting for regional and global brain size revealed additional sex and age effects on brain asymmetry. Highlights- The typical Asymmetry Index (AI) scales with the size of a region and brain size. - Omitting the Left+Right Measure influences reported sex differences in asymmetries. - Omitting brain size or asymmetry influences reported sex differences in asymmetries. - We report sex and age effects on AIs independent of regional and global brain size.

neuroscience↗

bioRxiv2020

Neuroanatomical Norms in the UK Biobank: The Impact of Allometric Scaling, Sex, and Age.

Few neuroimaging studies are sufficiently large to adequately describe population-wide variations. This studys primary aim was to generate neuroanatomical norms and individual markers that consider age, sex, and brain size, from 629 cerebral measures in the UK Biobank (N = 40 028). The secondary aim was to examine the effects and interactions of sex, age, and brain allometry - the non-linear scaling relationship between a region and brain size (e.g., Total Brain Volume) across cerebral measures. Allometry was a common property of brain volumes, thicknesses, and surface areas (83%) and was largely stable across age and sex. Sex differences occurred in 67% of cerebral measures (median |{beta}|= 0.13): 37% of regions were larger in males and 30% in females. Brain measures (49%) generally decreased with age, although aging effects varied across regions and sexes. While models with an allometric or linear covariate adjustment for brain size yielded similar significant effects, omitting brain allometry influenced reported sex differences in variance. This large scale-study advances our understanding of age, sex, and brain allometrys impact on brain structure and provides data for future UK Biobank studies to identify the cerebral regions that covary with specific phenotypes, independently of sex, age, and brain size. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=77 SRC="FIGDIR/small/422684v1_ufig1.gif" ALT="Figure 1"> View larger version (31K): org.highwire.dtl.DTLVardef@405c3borg.highwire.dtl.DTLVardef@1673e3corg.highwire.dtl.DTLVardef@126fee4org.highwire.dtl.DTLVardef@128545b_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIWe created neuroanatomical norms and individual markers for the UK Biobank (N=40 028) C_LIO_LIAllometry was common across 83% of brain volumes, thicknesses, and surface areas C_LIO_LI67% of regions differed between sexes: 37% were larger in males and 30% in females C_LIO_LIOmitting brain allometry influenced reported sex differences in variance C_LIO_LI49% of regions declined with age, with variations across regions and sexes C_LI

neuroscience↗

bioRxiv2020

A collaborative resource platform for non-human primate neuroimaging

Neuroimaging non-human primates (NHPs) is a growing, yet highly specialized field of neuroscience. Resources that were primarily developed for human neuroimaging often need to be significantly adapted for use with NHPs or other animals, which has led to an abundance of custom, in-house solutions. In recent years, the global NHP neuroimaging community has made significant efforts to transform the field towards more open and collaborative practices. Here we present the PRIMatE Resource Exchange (PRIME-RE), a new collaborative online platform for NHP neuroimaging. PRIME-RE is a dynamic community-driven hub for the exchange of practical knowledge, specialized analytical tools, and open data repositories, specifically related to NHP neuroimaging. PRIME-RE caters to both researchers and developers who are either new to the field, looking to stay abreast of the latest developments, or seeking to collaboratively advance the field.

neuroscience↗

bioRxiv2019

Increased contrast of the grey-white matter boundary in the motor, visual and auditory areas in Autism Spectrum Disorders

The contrast of the interface between the cortical grey matter and the white matter is emerging as an important neuroimaging biomarker for several brain disorders. Differences in grey to white matter contrast could be related to abnormalities in neuronal migration or in intra-cortical myelination, and are an appealing biomarker for ASD. Two previous studies have reported differences in contrast between patients with autism spectrum disorder and non-autistic controls. We aimed at replicating this finding using open data from the ABIDE initiative, phases 1 and 2, gathering data from 2,148 subjects from 26 different centres and on 764 individuals from the EU-AIMS project (6 different centres). We used multiple linear regression to study the effect of the diagnosis of ASD on contrast, and 3 different strategies for controlling for multiple comparisons. We did not find statistically significant differences in the EU-AIMS dataset, and those that we found in the ABIDE dataset were due to a single centre. All the code necessary to replicate our analyses has been made available open source: https://github.com/neuroanatomy/GWPC.

neuroscience↗

bioRxiv2019

Polygenic architecture of human neuroanatomical diversity

We analysed the genomic architecture of neuroanatomical diversity using magnetic resonance imaging and single nucleotide polymorphism (SNP) data from >26,000 individuals from the UK Biobank project and 5 other projects that had previously participated in the ENIGMA consortium. Our results confirm the polygenic architecture of neuroanatomical diversity, with SNPs capturing from 40% to 54% of regional brain volume variance. Chromosomal length correlated with the amount of phenotypic variance captured, r[~]0.64 on average, suggesting that at a global scale causal variants are homogeneously distributed across the genome. At a local scale, SNPs within genes ([~]51%) captured [~]1.5 times more genetic variance than the rest; and SNPs with low minor allele frequency (MAF) captured less variance than the rest: the 40% of SNPs with MAF<5% captured <1/4th of the genetic variance. We also observed extensive pleiotropy across regions, with an average genetic correlation of rG[~]0.45. Genetic correlations were similar to phenotypic and environmental correlations, however, genetic correlations were often larger than phenotypic correlations for the left/right volumes of the same region. The heritability of differences in left/right volumes was generally not statistically significant, suggesting an important influence of environmental causes in the variability of brain asymmetry. Our code is available at https://github.com/neuroanatomy/genomic-architecture.

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↗

bioRxiv2018

Evolution of neocortical folding: A phylogenetic comparative analysis of MRI from 33 primate species

We conducted a comparative analysis of primate cerebral size and neocortical folding using magnetic resonance imaging data from 65 individuals belonging to 34 different species. We measured several neocortical folding parameters and studied their evolution using phylogenetic comparative methods. Our results suggest that the most likely model for neuroanatomical evolution is one where differences appear randomly (the Brownian Motion model), however, alternative models cannot be completely ruled out. We present estimations of the ancestral primate phenotypes as well as estimations of the rates of phenotypic change. Based on the Brownian Motion model, the common ancestor of primates may have had a folded cerebrum similar to that of a small lemur such as the aye-aye. Finally, we observed a non-linear relationship between fold wavelength and fold depth with cerebral volume. In particular, gyrencephalic primate neocortices across different groups exhibited a strikingly stable fold wavelength of about 12 mm ({+/-} 20%), despite a 20-fold variation in cerebral volume. We discuss our results in the context of current theories of neocortical folding.

neuroscience↗