Imaging-based parcellations of the human brain

Nature reviews. Neuroscience, Год журнала: 2018, Номер 19(11), С. 672 - 686

Опубликована: Окт. 9, 2018

Язык: Английский

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An improved neuroanatomical model of the default-mode network reconciles previous neuroimaging and neuropathological findings

Communications Biology, Год журнала: 2019, Номер 2(1)

Опубликована: Окт. 10, 2019

Abstract The brain is constituted of multiple networks functionally correlated areas, out which the default-mode network (DMN) largest. Most existing research into DMN has taken a corticocentric approach. Despite its resemblance with unitary model limbic system, contribution subcortical structures to may be underappreciated. Here, we propose more comprehensive neuroanatomical including such as basal forebrain, cholinergic nuclei, anterior and mediodorsal thalamic nuclei. Additionally, tractography diffusion-weighted imaging was employed explore structural connectivity, revealed that thalamus forebrain are central importance for functioning DMN. these neurochemically diverse nuclei reconciles previous neuroimaging neuropathological findings in diseased brains offers potential identifying conserved homologue other mammalian species.

Язык: Английский

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General functional connectivity: Shared features of resting-state and task fMRI drive reliable and heritable individual differences in functional brain networks

NeuroImage, Год журнала: 2019, Номер 189, С. 516 - 532

Опубликована: Янв. 30, 2019

Intrinsic connectivity, measured using resting-state fMRI, has emerged as a fundamental tool in the study of human brain. However, due to practical limitations, many studies do not collect enough data generate reliable measures intrinsic connectivity necessary for studying individual differences. Here we present general functional (GFC) method leveraging shared features across and task fMRI demonstrate Human Connectome Project Dunedin Study that GFC offers better test-retest reliability than estimated from same amount alone. Furthermore, at equivalent scan lengths, displayed higher estimates heritability connectivity. We also found predictions cognitive ability generalized datasets, performing well or Collectively, our work suggests can improve existing datasets and, subsequently, opportunity identify meaningful correlates differences behavior. Given are often collected together, researchers immediately derive more through adoption rather solely data. Moreover, by capturing heritable variation represents novel endophenotype with broad applications clinical neuroscience biomarker discovery.

Язык: Английский

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Spatial and Temporal Organization of the Individual Human Cerebellum

Neuron, Год журнала: 2018, Номер 100(4), С. 977 - 993.e7

Опубликована: Окт. 25, 2018

Язык: Английский

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20 years of the default mode network: A review and synthesis

Neuron, Год журнала: 2023, Номер 111(16), С. 2469 - 2487

Опубликована: Май 10, 2023

Язык: Английский

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Using Brain Imaging to Improve Spatial Targeting of Transcranial Magnetic Stimulation for Depression

Biological Psychiatry, Год журнала: 2020, Номер 90(10), С. 689 - 700

Опубликована: Июнь 7, 2020

Язык: Английский

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Interpreting temporal fluctuations in resting-state functional connectivity MRI

NeuroImage, Год журнала: 2017, Номер 163, С. 437 - 455

Опубликована: Сен. 12, 2017

Язык: Английский

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The relationship between spatial configuration and functional connectivity of brain regions

eLife, Год журнала: 2018, Номер 7

Опубликована: Фев. 16, 2018

Brain connectivity is often considered in terms of the communication between functionally distinct brain regions. Many studies have investigated extent to which patterns coupling strength multiple neural populations relates behaviour. For example, used ‘functional fingerprints’ characterise individuals' activity. Here, we investigate exact spatial arrangement cortical regions interacts with measures connectivity. We find that shape and location interact strongly modelling connectivity, present evidence functional predictive non-imaging behaviour lifestyle. believe that, many cases, cross-subject variations configuration are being interpreted as changes Therefore, a better understanding these effects important when interpreting relationship imaging data cognitive traits.

Язык: Английский

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Individual Variation in Functional Topography of Association Networks in Youth

Neuron, Год журнала: 2020, Номер 106(2), С. 340 - 353.e8

Опубликована: Фев. 19, 2020

Язык: Английский

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Different scaling of linear models and deep learning in UKBiobank brain images versus machine-learning datasets

Nature Communications, Год журнала: 2020, Номер 11(1)

Опубликована: Авг. 25, 2020

Recently, deep learning has unlocked unprecedented success in various domains, especially using images, text, and speech. However, is only beneficial if the data have nonlinear relationships they are exploitable at available sample sizes. We systematically profiled performance of deep, kernel, linear models as a function size on UKBiobank brain images against established machine references. On MNIST Zalando Fashion, prediction accuracy consistently improves when escalating from to shallow-nonlinear models, further with deep-nonlinear models. In contrast, structural or functional scans, simple perform par more complex, highly parameterized age/sex across increasing sum, keep improving approaches ~10,000 subjects. Yet, nonlinearities for predicting common phenotypes typical scans remain largely inaccessible examined kernel methods.

Язык: Английский

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