Unraveling the mesoscale organization induced by network-driven processes DOI Creative Commons
Giacomo Barzon, Oriol Artime, Samir Suweis

et al.

Proceedings of the National Academy of Sciences, Journal Year: 2024, Volume and Issue: 121(28)

Published: July 5, 2024

Complex systems are characterized by emergent patterns created the nontrivial interplay between dynamical processes and networks of interactions on which these unfold. Topological or descriptors alone not enough to fully embrace this in all its complexity, many times one has resort dynamics-specific approaches that limit a comprehension general principles. To address challenge, we employ metric—that name Jacobian distance—which captures spatiotemporal spreading perturbations, enabling us uncover latent geometry inherent network-driven processes. We compute distance for broad set nonlinear models synthetic real-world high interest applications from biological ecological social contexts. show, analytically computationally, process-driven complex network is sensitive both specific features dynamics topological properties network. This translates into potential mismatches functional mesoscale organization, explain means spectrum matrix. Finally, demonstrate offers clear advantage with respect traditional methods when studying human brain networks. In particular, show it outperforms classical communication explaining communities structural data, therefore highlighting linking structure function brain.

Language: Английский

Mapping neurotransmitter systems to the structural and functional organization of the human neocortex DOI Creative Commons
Justine Y. Hansen, Golia Shafiei, Ross D. Markello

et al.

Nature Neuroscience, Journal Year: 2022, Volume and Issue: 25(11), P. 1569 - 1581

Published: Oct. 27, 2022

Abstract Neurotransmitter receptors support the propagation of signals in human brain. How receptor systems are situated within macro-scale neuroanatomy and how they shape emergent function remain poorly understood, there exists no comprehensive atlas receptors. Here we collate positron emission tomography data from more than 1,200 healthy individuals to construct a whole-brain three-dimensional normative 19 transporters across nine different neurotransmitter systems. We found that profiles align with structural connectivity mediate function, including neurophysiological oscillatory dynamics resting-state hemodynamic functional connectivity. Using Neurosynth cognitive atlas, uncovered topographic gradient overlapping distributions separates extrinsic intrinsic psychological processes. Finally, both expected novel associations between cortical abnormality patterns 13 disorders. replicated all findings an independently collected autoradiography dataset. This work demonstrates chemoarchitecture shapes brain structure providing new direction for studying multi-scale organization.

Language: Английский

Citations

412
Signal propagation in complex networks DOI
Peng Ji, Jiachen Ye, Yu Mu

et al.

Physics Reports, Journal Year: 2023, Volume and Issue: 1017, P. 1 - 96

Published: April 5, 2023

Language: Английский

Citations

180
Brain network communication: concepts, models and applications DOI
Caio Seguin, Olaf Sporns, Andrew Zalesky

et al.

Nature reviews. Neuroscience, Journal Year: 2023, Volume and Issue: 24(9), P. 557 - 574

Published: July 12, 2023

Language: Английский

Citations

129
Communication dynamics in the human connectome shape the cortex-wide propagation of direct electrical stimulation DOI Creative Commons
Caio Seguin, Maciej Jedynak, Olivier David

et al.

Neuron, Journal Year: 2023, Volume and Issue: 111(9), P. 1391 - 1401.e5

Published: March 7, 2023

Language: Английский

Citations

37
A network control theory pipeline for studying the dynamics of the structural connectome DOI
Linden Parkes,

Jason Z. Kim,

Jennifer Stiso

et al.

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

Published: July 29, 2024

Language: Английский

Citations

10
Spatially embedded recurrent neural networks reveal widespread links between structural and functional neuroscience findings DOI Creative Commons
Jascha Achterberg, Danyal Akarca,

Daniel Strouse

et al.

Nature Machine Intelligence, Journal Year: 2023, Volume and Issue: 5(12), P. 1369 - 1381

Published: Nov. 20, 2023

Abstract Brain networks exist within the confines of resource limitations. As a result, brain network must overcome metabolic costs growing and sustaining its physical space, while simultaneously implementing required information processing. Here, to observe effect these processes, we introduce spatially embedded recurrent neural (seRNN). seRNNs learn basic task-related inferences existing three-dimensional Euclidean where communication constituent neurons is constrained by sparse connectome. We find that converge on structural functional features are also commonly found in primate cerebral cortices. Specifically, they solving using modular small-world networks, which functionally similar units configure themselves utilize an energetically efficient mixed-selective code. Because emerge unison, reveal how many common motifs strongly intertwined can be attributed biological optimization processes. incorporate biophysical constraints fully artificial system serve as bridge between research communities move neuroscientific understanding forwards.

Language: Английский

Citations

22
Toward computational neuroconstructivism: a framework for developmental systems neuroscience DOI Creative Commons
Duncan E. Astle, Mark H. Johnson, Danyal Akarca

et al.

Trends in Cognitive Sciences, Journal Year: 2023, Volume and Issue: 27(8), P. 726 - 744

Published: May 31, 2023

Brain development is underpinned by complex interactions between neural assemblies, driving structural and functional change. This neuroconstructivism (the notion that functions are shaped these interactions) core to some developmental theories. However, due their complexity, understanding underlying mechanisms challenging. Elsewhere in neurobiology, a computational revolution has shown mathematical models of hidden biological can bridge observations with theory building. Can we build similar framework yielding mechanistic insights for brain development? Here, outline the conceptual technical challenges addressing this gap, demonstrate there great potential specifying as mathematically defined processes operating within physical constraints. We provide examples, alongside broader ingredients needed, field explores explanations system-wide development.

Language: Английский

Citations

19
Whole-brain structural connectome asymmetry in autism DOI Creative Commons

Seulki Yoo,

Yurim Jang, Seok‐Jun Hong

et al.

NeuroImage, Journal Year: 2024, Volume and Issue: 288, P. 120534 - 120534

Published: Feb. 8, 2024

Autism spectrum disorder is a common neurodevelopmental condition that manifests as disruption in sensory and social skills. Although it has been shown the brain morphology of individuals with autism asymmetric, how this differentially affects structural connectome organization each hemisphere remains under-investigated. We studied whole-brain connectivity-based asymmetry using diffusion magnetic resonance imaging obtained from Brain Imaging Data Exchange initiative. By leveraging dimensionality reduction techniques, we constructed low-dimensional representations connectivity calculated their index. Comparing index between neurotypical controls, found atypical default-mode regions, particularly showing weaker towards right autism. Network communication provided topological underpinnings by demonstrating inferior temporal cortex limbic frontoparietal regions showed reduced global network efficiency decreased send-receive navigation lateral visual cortices Finally, supervised machine learning revealed could be used measure for predicting communication-related autistic symptoms nonverbal intelligence. Our findings provide insights into macroscale alterations underpinnings.

Language: Английский

Citations

7
A multi-modal, asymmetric, weighted, and signed description of anatomical connectivity DOI Creative Commons
Jacob Tanner, Joshua Faskowitz, Andreia Sofia Teixeira

et al.

Nature Communications, Journal Year: 2024, Volume and Issue: 15(1)

Published: July 12, 2024

Abstract The macroscale connectome is the network of physical, white-matter tracts between brain areas. connections are generally weighted and their values interpreted as measures communication efficacy. In most applications, weights either assigned based on imaging features–e.g. diffusion parameters–or inferred using statistical models. reality, ground-truth unknown, motivating exploration alternative edge weighting schemes. Here, we explore a multi-modal, regression-based model that endows reconstructed fiber with directed signed weights. We find fits observed data well, outperforming suite null estimated subject-specific highly reliable, even when fit relatively few training samples, networks maintain number desirable features. summary, offer simple framework for data, demonstrating both its ease implementation while benchmarking utility typical analyses, including graph theoretic modeling brain-behavior associations.

Language: Английский

Citations

7
Relation of connectome topology to brain volume across 103 mammalian species DOI Creative Commons
Maria Grazia Puxeddu, Joshua Faskowitz, Caio Seguin

et al.

PLoS Biology, Journal Year: 2024, Volume and Issue: 22(2), P. e3002489 - e3002489

Published: Feb. 5, 2024

The brain connectome is an embedded network of anatomically interconnected regions, and the study its topological organization in mammals has become paramount importance due to role scaffolding function behavior. Unlike many other observable networks, connections incur material energetic cost, their length density are volumetrically constrained by skull. Thus, open question how differences volume impact topology. We address this issue using MaMI database, a diverse set mammalian connectomes reconstructed from 201 animals, covering 103 species 12 taxonomy orders, whose size varies over more than 4 orders magnitude. Our analyses focus on relationships between modular organization. After having identified modules through multiresolution approach, we observed connectivity features relate structure these relations vary across volume. found that as increases, spatially compact dense, comprising costly connections. Furthermore, investigated spatial embedding shapes communication, finding nodes’ distance progressively impacts communication efficiency. modes variation policies, smaller bigger brains show higher efficiency routing- diffusion-based signaling, respectively. Finally, bridging modularity larger brains, imposes stronger constraints signaling. Altogether, our results systematically related topology tighter restrictions brains.

Language: Английский

Citations

6