Towards a biologically annotated brain connectome

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

Published: Oct. 17, 2023

Language: Английский

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Connectome-based reservoir computing with the conn2res toolbox

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

Published: Jan. 22, 2024

Abstract The connection patterns of neural circuits form a complex network. How signaling in these manifests as cognition and adaptive behaviour remains the central question neuroscience. Concomitant advances connectomics artificial intelligence open fundamentally new opportunities to understand how shape computational capacity biological brain networks. Reservoir computing is versatile paradigm that uses high-dimensional, nonlinear dynamical systems perform computations approximate cognitive functions. Here we present : an open-source Python toolbox for implementing networks modular, allowing arbitrary network architecture dynamics be imposed. allows researchers input connectomes reconstructed using multiple techniques, from tract tracing noninvasive diffusion imaging, impose systems, spiking neurons memristive dynamics. versatility us ask questions at confluence neuroscience intelligence. By reconceptualizing function computation, sets stage more mechanistic understanding structure-function relationships

Language: Английский

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Evolution of cortical geometry and its link to function, behaviour and ecology

Nature Communications, Journal Year: 2023, Volume and Issue: 14(1)

Published: April 20, 2023

Abstract Studies in comparative neuroanatomy and of the fossil record demonstrate influence socio-ecological niches on morphology cerebral cortex, but have led to oftentimes conflicting theories about its evolution. Here, we study relationship between shape cortex topography function. We establish a joint geometric representation cortices ninety species extant Euarchontoglires, including commonly used experimental model organisms. show that variability surface geometry relates species’ ecology behaviour, independent overall brain size. Notably, ancestral reconstruction cortical change during evolution enables us trace evolutionary history localised expansions, modal segregation function, their association behaviour cognition. find individual regions follow different sequences area increase adaptations dynamic niches. Anatomical correlates this sequence events are still observable species, relate current ecology. decompose deep human into spatially temporally conscribed components with highly interpretable functional associations, highlighting importance considering when studying anatomy

Language: Английский

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Relation of connectome topology to brain volume across 103 mammalian species

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

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A connectomics-based taxonomy of mammals

eLife, Journal Year: 2022, Volume and Issue: 11

Published: Nov. 7, 2022

Mammalian taxonomies are conventionally defined by morphological traits and genetics. How species differ in terms of neural circuits whether inter-species differences circuit organization conform to these is unknown. The main obstacle the comparison architectures has been network reconstruction techniques, yielding species-specific connectomes that not directly comparable one another. Here, we comprehensively chart connectome across mammalian phylogenetic spectrum using a common protocol. We analyse MRI (MaMI) data set, database encompasses high-resolution ex vivo structural diffusion scans 124 12 taxonomic orders 5 superorders, collected unified assess similarity between two methods: Laplacian eigenspectra multiscale topological features. find greater similarities among within same order, suggesting reflects established relationships morphology While all retain hallmark global features relative proportions connection classes, variation driven local regional connectivity profiles. By encoding into frame reference, findings establish foundation for investigating how change over phylogeny, forging link from genes behaviour.

Language: Английский

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Benchmarking methods for mapping functional connectivity in the brain

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

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Evolution of the Rich Club Properties in Mouse, Macaque, and Human Brain Networks: A Study of Functional Integration, Segregation, and Balance

Neuroscience Bulletin, Journal Year: 2025, Volume and Issue: unknown

Published: April 13, 2025

Language: Английский

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Emergence and maintenance of modularity in neural networks with Hebbian and anti-Hebbian inhibitory STDP

PLoS Computational Biology, Journal Year: 2025, Volume and Issue: 21(4), P. e1012973 - e1012973

Published: April 22, 2025

The modular and hierarchical organization of the brain is believed to support coexistence segregated (specialization) integrated (binding) information processes. A relevant question yet understand how such architecture naturally emerges sustained over time, given plastic nature brain’s wiring. Following evidences that sensory cortices organize into assemblies under selective stimuli, it has been shown stable neuronal can emerge due targeted stimulation, embedding various forms synaptic plasticity in presence homeostatic and/or control mechanisms. Here, we show simple spike-timing-dependent (STDP) rules, based only on pre- post-synaptic spike times, also lead encoding memories absence any mechanism. We develop a model spiking neurons, trained by stimuli targeting different sub-populations. satisfies some biologically plausible features: (i) contains excitatory inhibitory neurons with Hebbian anti-Hebbian STDP; (ii) neither activity nor weights are frozen after learning phase. Instead, allowed fire spontaneously while remains active. find combination two STDP sub-populations allows for formation modules network, each sub-population playing distinctive role. controls firing activity, promote pattern selectivity. After phase, network settles an asynchronous irregular resting-state. This post-learning associated spontaneous memory recalls which turn out be fundamental long-term consolidation learned memories. Due its simplicity, introduced represent test-bed further investigations role played storing maintenance.

Language: Английский

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Translational modelling of low and medium intensity transcranial magnetic stimulation from rodents to humans

Published: April 29, 2024

Abstract Background Rodent models using subthreshold intensities of transcranial magnetic stimulation (TMS) have provided insight into the biological mechanisms TMS but often differ from human studies in intensity electric field (E-field) induced brain. Objective To develop a finite element method model as guide for translation between low and medium rodent high humans. Methods FEM three head (mouse, rat, human), eight coils were developed to simulate flux density (B-field) E-field values by intensities. Results In mouse brain, maximum B-fields ranged 0.00675 T 0.936 0.231 V/m 60.40 E-field. rat brains 0.00696 0.567 E-fields 0.144 97.2 V/m. S90 Standard coil could be used induce B-field 0.643 241 V/m, while MC-B70 0.564 220 Conclusions We novel modelling tool that can help replication commercial coils. Modelling limitations include lack data on dielectric CSF volumes rodents simplification tissue geometry impacting distribution, methods mitigating these issues are discussed. A range additional cross-species factors affecting identified will aid both humans rodents. present describes what extent brain region-specific is possible detail requirements future improvement. graphical abstract translational pipeline this study below (Figure A.1). Highlights Clinical challenging due differences size shape built accurate TMS-derived validated multiple regions This useful designing parameters based studies. critical part evidence TMS.

Language: Английский

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Generative network modeling reveals quantitative definitions of bilateral symmetry exhibited by a whole insect brain connectome

eLife, Journal Year: 2023, Volume and Issue: 12

Published: March 28, 2023

Comparing connectomes can help explain how neural connectivity is related to genetics, disease, development, learning, and behavior. However, making statistical inferences about the significance nature of differences between two networks an open problem, such analysis has not been extensively applied nanoscale connectomes. Here, we investigate this problem via a case study on bilateral symmetry larval

Language: Английский

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