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1.
Sci Rep ; 12(1): 18783, 2022 Nov 05.
Artigo em Inglês | MEDLINE | ID: mdl-36335224

RESUMO

Diffuse gliomas are incurable brain tumors, yet there is significant heterogeneity in patient survival. Advanced computational techniques such as radiomics show potential for presurgical prediction of survival and other outcomes from neuroimaging. However, these techniques ignore non-lesioned brain features that could be essential for improving prediction accuracy. Gray matter covariance network (connectome) features were retrospectively identified from the T1-weighted MRIs of 305 adult patients diagnosed with diffuse glioma. These features were entered into a Cox proportional hazards model to predict overall survival with 10-folds cross-validation. The mean time-dependent area under the curve (AUC) of the connectome model was compared with the mean AUCs of clinical and radiomic models using a pairwise t-test with Bonferroni correction. One clinical model included only features that are known presurgery (clinical) and another included an advantaged set of features that are not typically known presurgery (clinical +). The median survival time for all patients was 134.2 months. The connectome model (AUC 0.88 ± 0.01) demonstrated superior performance (P < 0.001, corrected) compared to the clinical (AUC 0.61 ± 0.02), clinical + (AUC 0.79 ± 0.01) and radiomic models (AUC 0.75 ± 0.02). These findings indicate that the connectome is a feasible and reliable early biomarker for predicting survival in patients with diffuse glioma. Connectome and other whole-brain models could be valuable tools for precision medicine by informing patient risk stratification and treatment decision-making.


Assuntos
Neoplasias Encefálicas , Conectoma , Glioma , Adulto , Humanos , Estudos Retrospectivos , Glioma/diagnóstico por imagem , Glioma/cirurgia , Glioma/patologia , Neoplasias Encefálicas/diagnóstico por imagem , Neoplasias Encefálicas/cirurgia , Neoplasias Encefálicas/patologia , Imageamento por Ressonância Magnética/métodos
2.
Science ; 378(6619): 505-510, 2022 11 04.
Artigo em Inglês | MEDLINE | ID: mdl-36378968

RESUMO

There is more to brain connections than the mere transfer of signals between brain regions. Behavior and cognition emerge through cortical area interaction. This requires integration between local and distant areas orchestrated by densely connected networks. Brain connections determine the brain's functional organization. The imaging of connections in the living brain has provided an opportunity to identify the driving factors behind the neurobiology of cognition. Connectivity differences between species and among humans have furthered the understanding of brain evolution and of diverging cognitive profiles. Brain pathologies amplify this variability through disconnections and, consequently, the disintegration of cognitive functions. The prediction of long-term symptoms is now preferentially based on brain disconnections. This paradigm shift will reshape our brain maps and challenge current brain models.


Assuntos
Encéfalo , Cognição , Conectoma , Rede Nervosa , Humanos , Encéfalo/fisiologia , Encéfalo/ultraestrutura , Imageamento por Ressonância Magnética/métodos , Rede Nervosa/ultraestrutura
4.
Transl Psychiatry ; 12(1): 490, 2022 Nov 21.
Artigo em Inglês | MEDLINE | ID: mdl-36411282

RESUMO

Deep brain stimulation (DBS) and non-invasive neuromodulation are currently being investigated for treating network dysfunction in Alzheimer's Disease (AD). However, due to heterogeneity in techniques and targets, the cognitive outcome and brain network connectivity remain unknown. We performed a systematic review, meta-analysis, and normative functional connectivity to determine the cognitive outcome and brain networks of DBS and non-invasive neuromodulation in AD. PubMed, Embase, and Web of Science were searched using three concepts: dementia, brain connectome, and brain stimulation, with filters for English, human studies, and publication dates 1980-2021. Additional records from clinicaltrials.gov were added. Inclusion criteria were AD study with DBS or non-invasive neuromodulation and a cognitive outcome. Exclusion criteria were less than 3-months follow-up, severe dementia, and focused ultrasound intervention. Bias was assessed using Centre for Evidence-Based Medicine levels of evidence. We performed meta-analysis, with subgroup analysis based on type and age at neuromodulation. To determine the patterns of neuromodulation-induced brain network activation, we performed normative functional connectivity using rsfMRI of 1000 healthy subjects. Six studies, with 242 AD patients, met inclusion criteria. On fixed-effect meta-analysis, non-invasive neuromodulation favored baseline, with effect size -0.40(95% [CI], -0.73, -0.06, p = 0.02), while that of DBS was 0.11(95% [CI] -0.34, 0.56, p = 0.63), in favor of DBS. In patients ≥65 years old, DBS improved cognitive outcome, 0.95(95% [CI] 0.31, 1.58, p = 0.004), whereas in patients <65 years old baseline was favored, -0.17(95% [CI] -0.93, 0.58, p = 0.65). Functional connectivity regions were in the default mode (DMN), salience (SN), central executive (CEN) networks, and Papez circuit. The subgenual cingulate and anterior limb of internal capsule (ALIC) showed connectivity to all targets of neuromodulation. This meta-analysis provides level II evidence of a difference in response of AD patients to DBS, based on age at intervention. Brain stimulation in AD may modulate DMN, SN, CEN, and Papez circuit, with the subgenual cingulate and ALIC as potential targets.


Assuntos
Doença de Alzheimer , Conectoma , Estimulação Encefálica Profunda , Demência , Humanos , Idoso , Doença de Alzheimer/diagnóstico por imagem , Doença de Alzheimer/terapia , Encéfalo , Estimulação Encefálica Profunda/métodos
5.
Science ; 378(6619): 500-504, 2022 11 04.
Artigo em Inglês | MEDLINE | ID: mdl-36378967

RESUMO

A comprehensive description of how neurons and entire brain regions are interconnected is fundamental for a mechanistic understanding of brain function and dysfunction. Neuroimaging has shaped the way to approaching the human brain's connectivity on the basis of diffusion magnetic resonance imaging and tractography. At the same time, polarization, fluorescence, and electron microscopy became available, which pushed spatial resolution and sensitivity to the axonal or even to the synaptic level. New methods are mandatory to inform and constrain whole-brain tractography by regional, high-resolution connectivity data and local fiber geometry. Machine learning and simulation can provide predictions where experimental data are missing. Future interoperable atlases require new concepts, including high-resolution templates and directionality, to represent variants of tractography solutions and estimates of their accuracy.


Assuntos
Encéfalo , Conectoma , Neuroimagem , Humanos , Encéfalo/ultraestrutura , Conectoma/métodos , Imagem de Difusão por Ressonância Magnética , Neuroimagem/métodos , Neurônios
6.
Elife ; 112022 11 07.
Artigo em Inglês | MEDLINE | ID: mdl-36342363

RESUMO

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


Assuntos
Conectoma , Animais , Conectoma/métodos , Filogenia , Encéfalo/diagnóstico por imagem , Encéfalo/anatomia & histologia , Imageamento por Ressonância Magnética , Mamíferos
7.
Elife ; 112022 11 18.
Artigo em Inglês | MEDLINE | ID: mdl-36399034

RESUMO

Experience-dependent cortical plasticity is a pivotal process of human brain development and essential for the formation of most cognitive functions. Although studies found that early visual experience could influence the endogenous development of visual cortex in animals, little is known about such impact on human infants. Using the multimodal MRI data from the developing human connectome project, we characterized the early structural and functional maps in the ventral visual cortex and their development during neonatal period. Particularly, we found that postnatal time selectively modulated the cortical thickness in the ventral visual cortex and the functional circuit between bilateral primary visual cortices. But the cortical myelination and functional connections of the high-order visual cortex developed without significant influence of postnatal time in such an early period. The structure-function analysis further revealed that the postnatal time had a direct influence on the development of homotopic connection in area V1, while gestational time had an indirect effect on it through cortical myelination. These findings were further validated in preterm-born infants who had longer postnatal time but shorter gestational time at birth. In short, these data suggested in human newborns that early postnatal time shaped the structural and functional development of the visual cortex in selective and organized patterns.


Assuntos
Conectoma , Córtex Visual , Humanos , Recém-Nascido , Animais , Lactente , Córtex Visual/diagnóstico por imagem , Imageamento por Ressonância Magnética , Recém-Nascido Prematuro , Cognição
8.
PLoS Comput Biol ; 18(11): e1010653, 2022 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-36374908

RESUMO

The representation of the flow of information between neurons in the brain based on their activity is termed the causal functional connectome. Such representation incorporates the dynamic nature of neuronal activity and causal interactions between them. In contrast to connectome, the causal functional connectome is not directly observed and needs to be inferred from neural time series. A popular statistical framework for inferring causal connectivity from observations is the directed probabilistic graphical modeling. Its common formulation is not suitable for neural time series since it was developed for variables with independent and identically distributed static samples. In this work, we propose to model and estimate the causal functional connectivity from neural time series using a novel approach that adapts directed probabilistic graphical modeling to the time series scenario. In particular, we develop the Time-Aware PC (TPC) algorithm for estimating the causal functional connectivity, which adapts the PC algorithm-a state-of-the-art method for statistical causal inference. We show that the model outcome of TPC has the properties of reflecting causality of neural interactions such as being non-parametric, exhibits the directed Markov property in a time-series setting, and is predictive of the consequence of counterfactual interventions on the time series. We demonstrate the utility of the methodology to obtain the causal functional connectome for several datasets including simulations, benchmark datasets, and recent multi-array electro-physiological recordings from the mouse visual cortex.


Assuntos
Conectoma , Animais , Camundongos , Conectoma/métodos , Modelos Neurológicos , Algoritmos , Encéfalo/fisiologia , Causalidade , Imageamento por Ressonância Magnética/métodos , Rede Nervosa/fisiologia
9.
Nat Commun ; 13(1): 7308, 2022 Nov 27.
Artigo em Inglês | MEDLINE | ID: mdl-36437254

RESUMO

We introduce in network geometry a measure of geometrical congruence (GC) to evaluate the extent a network topology follows an underlying geometry. This requires finding all topological shortest-paths for each nonadjacent node pair in the network: a nontrivial computational task. Hence, we propose an optimized algorithm that reduces 26 years of worst scenario computation to one week parallel computing. Analysing artificial networks with patent geometry we discover that, different from current belief, hyperbolic networks do not show in general high GC and efficient greedy navigability (GN) with respect to the geodesics. The myopic transfer which rules GN works best only when degree-distribution power-law exponent is strictly close to two. Analysing real networks-whose geometry is often latent-GC overcomes GN as marker to differentiate phenotypical states in macroscale structural-MRI brain connectomes, suggesting connectomes might have a latent neurobiological geometry accounting for more information than the visible tridimensional Euclidean.


Assuntos
Conectoma , Conectoma/métodos , Encéfalo/diagnóstico por imagem , Algoritmos , Imageamento por Ressonância Magnética
10.
Nat Commun ; 13(1): 6851, 2022 Nov 11.
Artigo em Inglês | MEDLINE | ID: mdl-36369423

RESUMO

Neuropsychiatric disorders are increasingly conceptualized as overlapping spectra sharing multi-level neurobiological alterations. However, whether transdiagnostic cortical alterations covary in a biologically meaningful way is currently unknown. Here, we studied co-alteration networks across six neurodevelopmental and psychiatric disorders, reflecting pathological structural covariance. In 12,024 patients and 18,969 controls from the ENIGMA consortium, we observed that co-alteration patterns followed normative connectome organization and were anchored to prefrontal and temporal disease epicenters. Manifold learning revealed frontal-to-temporal and sensory/limbic-to-occipitoparietal transdiagnostic gradients, differentiating shared illness effects on cortical thickness along these axes. The principal gradient aligned with a normative cortical thickness covariance gradient and established a transcriptomic link to cortico-cerebello-thalamic circuits. Moreover, transdiagnostic gradients segregated functional networks involved in basic sensory, attentional/perceptual, and domain-general cognitive processes, and distinguished between regional cytoarchitectonic profiles. Together, our findings indicate that shared illness effects occur in a synchronized fashion and along multiple levels of hierarchical cortical organization.


Assuntos
Conectoma , Transtornos Mentais , Humanos , Córtex Cerebral/patologia , Cerebelo , Atenção , Imageamento por Ressonância Magnética
11.
Sci Rep ; 12(1): 16793, 2022 Oct 06.
Artigo em Inglês | MEDLINE | ID: mdl-36202837

RESUMO

Functional networks, which typically describe patterns of activity taking place across the cerebral cortex, are widely studied in neuroscience. The dynamical features of these networks, and in particular their deviation from the relatively static structural network, are thought to be key to higher brain function. The interactions between such structural networks and emergent function, and the multimodal neuroimaging approaches and common analysis according to frequency band motivate a multilayer network approach. However, many such investigations rely on arbitrary threshold choices that convert dense, weighted networks to sparse, binary structures. Here, we generalise a measure of multiplex clustering to describe weighted multiplexes with arbitrarily-many layers. Moreover, we extend a recently-developed measure of structure-function clustering (that describes the disparity between anatomical connectivity and functional networks) to the weighted case. To demonstrate its utility we combine human connectome data with simulated neural activity and bifurcation analysis. Our results indicate that this new measure can extract neurologically relevant features not readily apparent in analogous single-layer analyses. In particular, we are able to deduce dynamical regimes under which multistable patterns of neural activity emerge. Importantly, these findings suggest a role for brain operation just beyond criticality to promote cognitive flexibility.


Assuntos
Conectoma , Rede Nervosa , Encéfalo/diagnóstico por imagem , Córtex Cerebral , Análise por Conglomerados , Conectoma/métodos , Humanos , Imageamento por Ressonância Magnética/métodos
12.
Sci Rep ; 12(1): 16543, 2022 Oct 03.
Artigo em Inglês | MEDLINE | ID: mdl-36192582

RESUMO

Understanding the relationship between brain architecture and brain function is a central issue in neuroscience. We modeled realistic spatio-temporal patterns of brain activity on a human connectome with a Boolean networks model with the aim of computationally replicating certain cognitive functions as they emerge from the standardization of many fMRI studies, identified as patterns of human brain activity. Results from the analysis of simulation data, carried out for different parameters and initial conditions identified many possible paths in the space of parameters of these network models, with normal (ordered asymptotically constant patterns), chaotic (oscillating or disordered) but also highly organized configurations, with countless spatial-temporal patterns. We interpreted these results as routes to chaos, permanence of the systems in regimes of complexity, and ordered stationary behavior, associating these dynamics to cognitive processes. The most important result of this work is the study of emergent neural circuits, i.e., configurations of areas that synchronize over time, both locally and globally, determining the emergence of computational analogues of cognitive processes, which may or may not be similar to the functioning of biological brain. Furthermore, results put in evidence the creation of how the brain creates structures of remote communication. These structures have hierarchical organization, where each level allows for the emergence of brain organizations which behave at the next superior level. Taken together these results allow the interplay of dynamical and topological roots of the multifaceted brain dynamics to be understood.


Assuntos
Encéfalo , Conectoma , Simulação por Computador , Conectoma/métodos , Humanos , Imageamento por Ressonância Magnética/métodos , Tempo
13.
Commun Biol ; 5(1): 1056, 2022 Oct 04.
Artigo em Inglês | MEDLINE | ID: mdl-36195744

RESUMO

Human brain connectomes include sets of densely connected hub regions. However, the consistency and reproducibility of functional connectome hubs have not been established to date and the genetic signatures underlying robust hubs remain unknown. Here, we conduct a worldwide harmonized meta-connectomic analysis by pooling resting-state functional MRI data of 5212 healthy young adults across 61 independent cohorts. We identify highly consistent and reproducible connectome hubs in heteromodal and unimodal regions both across cohorts and across individuals, with the greatest effects observed in lateral parietal cortex. These hubs show heterogeneous connectivity profiles and are critical for both intra- and inter-network communications. Using post-mortem transcriptome datasets, we show that as compared to non-hubs, connectome hubs have a spatiotemporally distinctive transcriptomic pattern dominated by genes involved in the neuropeptide signaling pathway, neurodevelopmental processes, and metabolic processes. These results highlight the robustness of macroscopic connectome hubs and their potential cellular and molecular underpinnings, which markedly furthers our understanding of how connectome hubs emerge in development, support complex cognition in health, and are involved in disease.


Assuntos
Conectoma , Neuropeptídeos , Encéfalo/diagnóstico por imagem , Conectoma/métodos , Humanos , Vias Neurais , Reprodutibilidade dos Testes
14.
Neurosci Lett ; 791: 136913, 2022 11 20.
Artigo em Inglês | MEDLINE | ID: mdl-36272557

RESUMO

Determining important vertices in large graphs (e.g., Google's PageRank in the case of the graph of the World Wide Web) facilitated the construction of excellent web search engines, returning the most important hits corresponding to the submitted user queries. Interestingly, finding important edges - instead of vertices - in large graphs has received much less attention until now. Here we examine the human structural braingraph (or connectome), identified by diffusion magnetic resonance imaging (dMRI) methods, with edges connecting cortical and subcortical gray matter areas and weighted by fiber strengths, measured by the number of the discovered fiber tracts along the edge. We identify several "single" important edges in these braingraphs, whose high or low weights imply the sex or the age of the subject observed. We call these edges implicator edges since solely from their weight, one can infer the sex of the subject with more than 67 % accuracy or their age group with more than 62% accuracy. We argue that these brain connections are the most important ones characterizing the sex or the age of the subjects. Surprisingly, the edges implying the male sex are mostly located in the anterior parts of the brain, while those implying the female sex are mostly in the posterior regions. Additionally, most of the inter-hemispheric implicator edges are male ones, while the intra-hemispheric ones are predominantly female edges. Our pioneering method for finding the sex- or age implicator edges can also be applied for characterizing other biological and medical properties, including neurodegenerative- and psychiatric diseases besides the sex or the age of the subject, if large and high-quality neuroimaging datasets become available. We emphasize that our contribution identifies statistically valid single brain connections related to the sex and the age of the subjects in a large and robust dataset. To our knowledge, our results are unprecedented in this aspect.


Assuntos
Conectoma , Masculino , Humanos , Feminino , Conectoma/métodos , Encéfalo/diagnóstico por imagem , Substância Cinzenta/diagnóstico por imagem , Imagem de Difusão por Ressonância Magnética , Neuroimagem , Imageamento por Ressonância Magnética
15.
Nat Rev Neurosci ; 23(12): 725-743, 2022 12.
Artigo em Inglês | MEDLINE | ID: mdl-36289403

RESUMO

The wide variety of animal behaviours that can be observed today arose through the evolution of their underlying neural circuits. Advances in understanding the mechanisms through which neural circuits change over evolutionary timescales have lagged behind our knowledge of circuit function and development. This is particularly true for central neural circuits, which are experimentally less accessible than peripheral circuit elements. However, recent technological developments - including cross-species genetic modifications, connectomics and transcriptomics - have facilitated comparative neuroscience studies with a mechanistic outlook. These advances enable knowledge from two classically separate disciplines - neuroscience and evolutionary biology - to merge, accelerating our understanding of the principles of neural circuit evolution. Here we synthesize progress on this topic, focusing on three aspects of neural circuits that change over evolutionary time: synaptic connectivity, neuromodulation and neurons. By drawing examples from a wide variety of animal phyla, we reveal emerging principles of neural circuit evolution.


Assuntos
Conectoma , Neurociências , Animais , Neurônios/fisiologia , Sistema Nervoso
16.
PLoS Comput Biol ; 18(10): e1010507, 2022 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-36306284

RESUMO

Connectomes represent comprehensive descriptions of neural connections in a nervous system to better understand and model central brain function and peripheral processing of afferent and efferent neural signals. Connectomes can be considered as a distinctive and necessary structural component alongside glial, vascular, neurochemical, and metabolic networks of the nervous systems of higher organisms that are required for the control of body functions and interaction with the environment. They are carriers of functional phenomena such as planning behavior and cognition, which are based on the processing of highly dynamic neural signaling patterns. In this study, we examine more detailed connectomes with edge weighting and orientation properties, in which reciprocal neuronal connections are also considered. Diffusion processes are a further necessary condition for generating dynamic bioelectric patterns in connectomes. Based on our precise connectome data, we investigate different diffusion-reaction models to study the propagation of dynamic concentration patterns in control and lesioned connectomes. Therefore, differential equations for modeling diffusion were combined with well-known reaction terms to allow the use of connection weights, connectivity orientation and spatial distances. Three reaction-diffusion systems Gray-Scott, Gierer-Meinhardt and Mimura-Murray were investigated. For this purpose, implicit solvers were implemented in a numerically stable reaction-diffusion system within the framework of neuroVIISAS. The implemented reaction-diffusion systems were applied to a subconnectome which shapes the mechanosensitive pathway that is strongly affected in the multiple sclerosis demyelination disease. It was found that demyelination modeling by connectivity weight modulation changes the oscillations of the target region, i.e. the primary somatosensory cortex, of the mechanosensitive pathway. In conclusion, a new application of reaction-diffusion systems to weighted and directed connectomes has been realized. Because the implementation was realized in the neuroVIISAS framework many possibilities for the study of dynamic reaction-diffusion processes in empirical connectomes as well as specific randomized network models are available now.


Assuntos
Conectoma , Esclerose Múltipla , Humanos , Encéfalo/fisiologia , Imagem de Tensor de Difusão , Vias Neurais
17.
Nat Commun ; 13(1): 6096, 2022 Oct 15.
Artigo em Inglês | MEDLINE | ID: mdl-36243754

RESUMO

Reducing dimension redundancy to find simplifying patterns in high-dimensional datasets and complex networks has become a major endeavor in many scientific fields. However, detecting the dimensionality of their latent space is challenging but necessary to generate efficient embeddings to be used in a multitude of downstream tasks. Here, we propose a method to infer the dimensionality of networks without the need for any a priori spatial embedding. Due to the ability of hyperbolic geometry to capture the complex connectivity of real networks, we detect ultra low dimensionality far below values reported using other approaches. We applied our method to real networks from different domains and found unexpected regularities, including: tissue-specific biomolecular networks being extremely low dimensional; brain connectomes being close to the three dimensions of their anatomical embedding; and social networks and the Internet requiring slightly higher dimensionality. Beyond paving the way towards an ultra efficient dimensional reduction, our findings help address fundamental issues that hinge on dimensionality, such as universality in critical behavior.


Assuntos
Conectoma , Encéfalo
18.
Brain Struct Funct ; 227(9): 3001-3015, 2022 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-36274102

RESUMO

Understanding how few distributed areas can steer large-scale brain activity is a fundamental question that has practical implications, which range from inducing specific patterns of behavior to counteracting disease. Recent endeavors based on network controllability provided fresh insights into the potential ability of single regions to influence whole brain dynamics through the underlying structural connectome. However, controlling the entire brain activity is often unfeasible and might not always be necessary. The question whether single areas can control specific target subsystems remains crucial, albeit still poorly explored. Furthermore, the structure of the brain network exhibits progressive changes across the lifespan, but little is known about the possible consequences in the controllability properties. To address these questions, we adopted a novel target controllability approach that quantifies the centrality of brain nodes in controlling specific target anatomo-functional systems. We then studied such target control centrality in human connectomes obtained from healthy individuals aged from 5 to 85. Main results showed that the sensorimotor system has a high influencing capacity, but it is difficult for other areas to influence it. Furthermore, we reported that target control centrality varies with age and that temporal-parietal regions, whose cortical thinning is crucial in dementia-related diseases, exhibit lower values in older people. By simulating targeted attacks, such as those occurring in focal stroke, we showed that the ipsilesional hemisphere is the most affected one regardless of the damaged area. Notably, such degradation in target control centrality was more evident in younger people, thus supporting early-vulnerability hypotheses after stroke.


Assuntos
Conectoma , Acidente Vascular Cerebral , Humanos , Idoso , Encéfalo , Envelhecimento , Lobo Parietal , Imageamento por Ressonância Magnética/métodos
19.
Trends Cogn Sci ; 26(12): 1066-1067, 2022 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-36207260

RESUMO

Most would agree, the brain is complex. But, beyond metaphor, does the brain's complexity demand a paradigm shift in how we study its structure and function? I argue that complexity manifests in three domains - connectivity, dynamics, and information - and that unlocking their interactions will greatly advance our understanding of brain and cognition.


Assuntos
Conectoma , Humanos , Encéfalo , Cognição , Metáfora , Rede Nervosa , Imageamento por Ressonância Magnética
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