Stitcher: A Surface Reconstruction Tool for Highly Gyrified Brains DOI Creative Commons
Heitor Mynssen, Kamilla Avelino-de-Souza, Khallil Taverna Chaim

et al.

Neuroinformatics, Journal Year: 2024, Volume and Issue: 22(4), P. 539 - 554

Published: Oct. 10, 2024

Abstract Brain reconstruction, specially of the cerebral cortex, is a challenging task and even more so when it comes to highly gyrified brained animals. Here, we present Stitcher, novel tool capable generating such surfaces utilizing MRI data manual segmentation. Stitcher makes triangulation between consecutive brain slice segmentations by recursively adding edges that minimize total length simultaneously avoid self-intersection. We applied this new method build cortical two dolphins: Guiana dolphin ( Sotalia guianensis ), Franciscana Pontoporia blainvillei ); one pinniped: Steller sea lion Eumetopias jubatus ). Specifically in case P. , reconstructions at different resolutions were made. Additionally, also performed for sub non-cortical structures dolphin. All our mesh results show remarkable resemblance with real anatomy brains, except low-resolution data. Sub meshes properly reconstructed spatial positioning was preserved respect S. cortex. In comparative perspective methods, presents compatible volumetric measurements contrasted other anatomical standard tools. way, seems be viable pipeline neuroanatomical analysis, enhancing visualization descriptions non-primates species, broadening scope compared neuroanatomy.

Language: Английский

Towards a biologically annotated brain connectome DOI
Vincent Bazinet, Justine Y. Hansen, Bratislav Mišić

et al.

Nature reviews. Neuroscience, Journal Year: 2023, Volume and Issue: 24(12), P. 747 - 760

Published: Oct. 17, 2023

Language: Английский

Citations

41
Toward individualized connectomes of brain morphology DOI Open Access
Jinhui Wang, Yong He

Trends in Neurosciences, Journal Year: 2023, Volume and Issue: 47(2), P. 106 - 119

Published: Dec. 22, 2023

Language: Английский

Citations

31
Integrating brainstem and cortical functional architectures DOI Creative Commons
Justine Y. Hansen, Simone Cauzzo, Kavita Singh

et al.

Nature Neuroscience, Journal Year: 2024, Volume and Issue: unknown

Published: Oct. 16, 2024

Abstract The brainstem is a fundamental component of the central nervous system, yet it typically excluded from in vivo human brain mapping efforts, precluding complete understanding how influences cortical function. In this study, we used high-resolution 7-Tesla functional magnetic resonance imaging to derive connectome encompassing cortex and 58 nuclei spanning midbrain, pons medulla. We identified compact set integrative hubs with widespread connectivity cerebral cortex. Patterns between manifest as neurophysiological oscillatory rhythms, patterns cognitive specialization unimodal–transmodal hierarchy. This persistent alignment topographies shaped by spatial arrangement multiple neurotransmitter receptors transporters. replicated all findings using 3-Tesla data same participants. Collectively, work demonstrates that organizational features activity can be traced back brainstem.

Language: Английский

Citations

10
Structural MRI of brain similarity networks DOI
Isaac Sebenius, Lena Dorfschmidt, Jakob Seidlitz

et al.

Nature reviews. Neuroscience, Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 28, 2024

Language: Английский

Citations

8
Morphometric brain organization across the human lifespan reveals increased dispersion linked to cognitive performance DOI Creative Commons
Jiao Li, Chao Zhang, Yao Meng

et al.

PLoS Biology, Journal Year: 2024, Volume and Issue: 22(6), P. e3002647 - e3002647

Published: June 20, 2024

The human brain is organized as segregation and integration units follows complex developmental trajectories throughout life. cortical manifold provides a new means of studying the brain’s organization in multidimensional connectivity gradient space. However, how morphometric changes across lifespan remains unclear. Here, leveraging structural magnetic resonance imaging scans from 1,790 healthy individuals aged 8 to 89 years, we investigated age-related global, within- between-network dispersions reveal networks 3D manifolds based on similarity network (MSN), combining multiple features conceptualized “fingerprint” an individual’s brain. Developmental global dispersion unfolded along patterns molecular organization, such acetylcholine receptor. Communities were increasingly dispersed with age, reflecting more disassortative profiles within community. Increasing within-network primary motor association cortices mediated influence age cognitive flexibility executive functions. We also found that secondary sensory decreasingly rest during aging, possibly indicating shift extreme central position manifolds. Together, our results MSN perspective space, providing insights into brain, well performance.

Language: Английский

Citations

7
Major depressive disorder on a neuromorphic continuum DOI Creative Commons
Jiao Li, Zhiliang Long, Gong‐Jun Ji

et al.

Nature Communications, Journal Year: 2025, Volume and Issue: 16(1)

Published: March 11, 2025

The heterogeneity of major depressive disorder (MDD) has hindered clinical translation and neuromarker identification. Biotyping facilitates solving the problems heterogeneity, by dissecting MDD patients into discrete subgroups. However, interindividual variations suggest that depression may be conceptualized as a "continuum," rather than "category." We use Bayesian model to decompose structural MRI features from multisite cross-sectional cohort three latent disease factors (spatial pattern) continuum factor compositions (individual expression). are associated with distinct neurotransmitter receptors/transporters obtained open PET sources. Increases cortical thickness in sensory decreases orbitofrontal cortices (Factor 1) associate norepinephrine 5-HT2A density, cingulo-opercular network subcortex 2) 5-HTT increases social affective brain systems 3) relate density. Disease patterns can also used predict symptom improvement longitudinal cohort. Moreover, individual expressions stable over time cohort, differentially expressed controls transdiagnostic Collectively, our data-driven reveal organize along continuous dimensions affect sets regions. Li et al. identify abnormalities using an unsupervised machine learning technique, quantify their expression level for each patient.

Language: Английский

Citations

1
The Journey of the Default Mode Network: Development, Function, and Impact on Mental Health DOI Creative Commons

Felipe Rici Azarias,

Gustavo Henrique Doná Rodrigues Almeida, Luana Félix de Melo

et al.

Biology, Journal Year: 2025, Volume and Issue: 14(4), P. 395 - 395

Published: April 10, 2025

The Default Mode Network has been extensively studied in recent decades due to its central role higher cognitive processes and relevance for understanding mental disorders. This neural network, characterized by synchronized coherent activity at rest, is intrinsically linked self-reflection, exploration, social interaction, emotional processing. Our of the DMN extends beyond humans non-human animals, where it observed various species, highlighting evolutionary basis adaptive significance throughout phylogenetic history. Additionally, plays a crucial brain development during childhood adolescence, influencing fundamental processes. literature review aims provide comprehensive overview DMN, addressing structural, functional, aspects, as well impact from infancy adulthood. By gaining deeper organization function we can advance our knowledge mechanisms that underlie cognition, behavior, health. This, turn, lead more effective therapeutic strategies range neuropsychiatric conditions.

Language: Английский

Citations

1
Transcriptomic Similarity Informs Neuromorphic Deviations in Depression Biotypes DOI
Jiao Li, Zhiliang Long, Wei Sheng

et al.

Biological Psychiatry, Journal Year: 2023, Volume and Issue: 95(5), P. 414 - 425

Published: Aug. 10, 2023

Language: Английский

Citations

16
Extracting interpretable signatures of whole-brain dynamics through systematic comparison DOI Creative Commons
Annie G. Bryant, Kevin Aquino, Linden Parkes

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: Jan. 12, 2024

The brain's complex distributed dynamics are typically quantified using a limited set of manually selected statistical properties, leaving the possibility that alternative dynamical properties may outperform those reported for given application. Here, we address this limitation by systematically comparing diverse, interpretable features both intra-regional activity and inter-regional functional coupling from resting-state magnetic resonance imaging (rs-fMRI) data, demonstrating our method case-control comparisons four neuropsychiatric disorders. Our findings generally support use linear time-series analysis techniques rs-fMRI analyses, while also identifying new ways to quantify informative fMRI structures. While simple representations performed surprisingly well (e.g., within single brain region), combining with improved performance, underscoring distributed, multifaceted changes in comprehensive, data-driven introduced here enables systematic identification interpretation quantitative signatures multivariate applicability beyond neuroimaging diverse scientific problems involving time-varying systems.

Language: Английский

Citations

5
Benchmarking methods for mapping functional connectivity in the brain DOI Creative Commons
Zhen-Qi Liu, Andrea I. Luppi, Justine Y. Hansen

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: May 8, 2024

The networked architecture of the brain promotes synchrony among neuronal populations and emergence coherent dynamics. These communication patterns can be comprehensively mapped using noninvasive functional imaging, resulting in connectivity (FC) networks. Despite its popularity, FC is a statistical construct operational definition arbitrary. While most studies use zero-lag Pearson's correlations by default, there exist hundreds pairwise interaction statistics broader scientific literature that used to estimate FC. How organization matrix varies with choice statistic fundamental methodological question affects all this rapidly growing field. Here we benchmark topological geometric organization, neurobiological associations, cognitive-behavioral relevance matrices computed large library 239 statistics. We investigate how canonical features networks vary statistic, including (1) hub mapping, (2) weight-distance trade-offs, (3) structure-function coupling, (4) correspondence other neurophysiological networks, (5) individual fingerprinting, (6) brain-behavior prediction. find substantial quantitative qualitative variation across methods. Throughout, observe measures such as covariance (full correlation), precision (partial correlation) distance display multiple desirable properties, close structural connectivity, capacity differentiate individuals predict differences behavior. Using information flow decomposition, methods may arise from differential sensitivity underlying mechanisms inter-regional communication, some more sensitive redundant synergistic flow. In summary, our report highlights importance tailoring specific mechanism research question, providing blueprint for future optimize their method.

Language: Английский

Citations

4