Converging on consistent functional connectomics DOI Creative Commons
Andrea I. Luppi, Helena M. Gellersen, Zhen-Qi Liu

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2023, Volume and Issue: unknown

Published: June 26, 2023

Abstract Functional interactions between brain regions can be viewed as a network, empowering neuroscientists to leverage network science investigate distributed function. However, obtaining from functional neuroimaging data involves multiple steps of manipulation, which drastically affect the organisation and validity estimated its properties. Here, we provide systematic evaluation 576 unique data-processing pipelines for connectomics resting-state MRI, obtained all possible recombinations popular choices atlas type size, connectivity definition selection, global signal regression. We use portrait divergence, an information-theoretic measure differences in topology across scales, quantify influence analytic on overall derived connectome. evaluate each pipeline entire battery criteria, seeking that (i) minimise spurious test-retest discrepancies topology, while simultaneously (ii) mitigating motion confounds, being sensitive both (iii) inter-subject (iv) experimental effects interest, demonstrated by propofol-induced general anaesthesia. Our findings reveal vast variability pipelines’ suitability connectomics. Choice wrong lead results are not only misleading, but systematically so, distorting connectome more than passage several months. also found majority failed meet at least one our criteria. identified 8 candidates satisfying criteria four independent datasets spanning minutes, weeks, months, ensuring generalisability recommendations. generalise alternative acquisition parameters preprocessing denoising choices. By providing community with full breakdown pipeline’s performance this multi-dataset, multi-criteria, multi-scale multi-step approach, establish comprehensive set benchmarks inform future best practices

Language: Английский

Systematic evaluation of fMRI data-processing pipelines for consistent functional connectomics DOI Creative Commons
Andrea I. Luppi, Helena M. Gellersen, Zhen-Qi Liu

et al.

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

Published: June 4, 2024

Abstract Functional interactions between brain regions can be viewed as a network, enabling neuroscientists to investigate function through network science. Here, we systematically evaluate 768 data-processing pipelines for reconstruction from resting-state functional MRI, evaluating the effect of parcellation, connectivity definition, and global signal regression. Our criteria seek that minimise motion confounds spurious test-retest discrepancies topology, while being sensitive both inter-subject differences experimental effects interest. We reveal vast systematic variability across pipelines’ suitability connectomics. Inappropriate choice pipeline produce results are not only misleading, but so, with majority failing at least one criterion. However, set optimal consistently satisfy all different datasets, spanning minutes, weeks, months. provide full breakdown each pipeline’s performance inform future best practices in

Language: Английский

Citations

22
Structural and functional connectivity reconstruction with CATO - A Connectivity Analysis TOolbox DOI Creative Commons
Siemon C. de Lange,

Koen Helwegen,

Martijn P. van den Heuvel

et al.

NeuroImage, Journal Year: 2023, Volume and Issue: 273, P. 120108 - 120108

Published: April 12, 2023

We describe a Connectivity Analysis TOolbox (CATO) for the reconstruction of structural and functional brain connectivity based on diffusion weighted imaging resting-state MRI data. CATO is multimodal software package that enables researchers to run end-to-end reconstructions from data connectome maps, customize their analyses utilize various packages preprocess Structural maps can be reconstructed with respect user-defined (sub)cortical atlases providing aligned matrices integrative analyses. outline implementation usage processing pipelines in CATO. Performance was calibrated simulated ITC2015 challenge test-retest Human Connectome Project. open-source distributed under MIT License available as MATLAB toolbox stand-alone application at www.dutchconnectomelab.nl/CATO.

Language: Английский

Citations

35
The evolution of Big Data in neuroscience and neurology DOI Creative Commons

Laura Dipietro,

Paola Gonzalez‐Mego, Ciro Ramos‐Estebanez

et al.

Journal Of Big Data, Journal Year: 2023, Volume and Issue: 10(1)

Published: July 10, 2023

Neurological diseases are on the rise worldwide, leading to increased healthcare costs and diminished quality of life in patients. In recent years, Big Data has started transform fields Neuroscience Neurology. Scientists clinicians collaborating global alliances, combining diverse datasets a massive scale, solving complex computational problems that demand utilization increasingly powerful resources. This revolution is opening new avenues for developing innovative treatments neurological diseases. Our paper surveys Data's impact patient care, as exemplified through work done comprehensive selection areas, including Connectomics, Alzheimer's Disease, Stroke, Depression, Parkinson's Pain, Addiction (e.g., Opioid Use Disorder). We present an overview research methodologies utilizing each area, well their current limitations technical challenges. Despite potential benefits, full these currently remains unrealized. close with recommendations future aimed at optimizing use Neurology improved outcomes.The online version contains supplementary material available 10.1186/s40537-023-00751-2.

Language: Английский

Citations

24
Insomnia Subtypes Have Differentiating Deviations in Brain Structural Connectivity DOI Creative Commons
Tom Bresser, Tessa F. Blanken, Siemon C. de Lange

et al.

Biological Psychiatry, Journal Year: 2024, Volume and Issue: unknown

Published: June 1, 2024

BackgroundInsomnia disorder is the most common sleep disorder. A better understanding of insomnia-related deviations in brain could inspire treatment. Insufficiently recognized heterogeneity within insomnia population obscure detection involved circuits. In current study, we investigated whether structural connectivity differed between recently discovered and validated subtypes.MethodsStructural diffusion-weighted 3T magnetic resonance imaging data from 4 independent studies were harmonized. The sample consisted 73 control participants without complaints 204 with who grouped into 5 subtypes based on their fingerprint mood personality traits assessed Insomnia Type Questionnaire. Linear regression correcting for age sex was used to evaluate group differences strength, indicated by fractional anisotropy, streamline volume density, mean diffusivity evaluated 3 different atlases.ResultsInsomnia showed differentiating profiles deviating that concentrated functional networks. Permutation testing against randomly drawn heterogeneous subsamples significant specificity deviation subtypes: highly distressed, moderately distressed reward sensitive, slightly low reactive, high reactive. Connectivity profile significance ranged p = .001 .049 resolutions parcellation weight.ConclusionsOur results provide an initial indication exhibit distinct connectivity. Subtyping may be essential a mechanisms contribute vulnerability.

Language: Английский

Citations

7
The time-evolving epileptic brain network: concepts, definitions, accomplishments, perspectives DOI Creative Commons
Timo Bröhl, Thorsten Rings, Jan Pukropski

et al.

Frontiers in Network Physiology, Journal Year: 2024, Volume and Issue: 3

Published: Jan. 16, 2024

Epilepsy is now considered a network disease that affects the brain across multiple levels of spatial and temporal scales. The paradigm shift from an epileptic focus—a discrete cortical area which seizures originate—to widespread network—spanning lobes hemispheres—considerably advanced our understanding epilepsy continues to influence both research clinical treatment this multi-faceted high-impact neurological disorder. network, however, not static but evolves in time requires novel approaches for in-depth characterization. In review, we discuss conceptual basics theory critically examine state-of-the-art recording techniques analysis tools used assess characterize time-evolving human network. We give account on current shortcomings highlight potential developments towards improved management epilepsy.

Language: Английский

Citations

6
Optimizing network neuroscience computation of individual differences in human spontaneous brain activity for test-retest reliability DOI Creative Commons
Chao Jiang, Ye He, Richard F. Betzel

et al.

Network Neuroscience, Journal Year: 2023, Volume and Issue: 7(3), P. 1080 - 1108

Published: Jan. 1, 2023

A rapidly emerging application of network neuroscience in neuroimaging studies has provided useful tools to understand individual differences intrinsic brain function by mapping spontaneous activity, namely functional (ifNN). However, the variability methodologies applied across ifNN studies-with respect node definition, edge construction, and graph measurements-makes it difficult directly compare findings also challenging for end users select optimal strategies networks. Here, we aim provide a benchmark best practices systematically comparing measurement reliability under different analytical using test-retest design Human Connectome Project. The results uncovered four essential principles guide studies: (1) use whole parcellation define nodes, including subcortical cerebellar regions; (2) construct networks activity multiple slow bands; (3) optimize topological economy at level; (4) characterize information flow with specific metrics integration segregation. We built an interactive online resource assessments future (https://ibraindata.com/research/ifNN).

Language: Английский

Citations

13
Human and chimpanzee shared and divergent neurobiological systems for general and specific cognitive brain functions DOI Creative Commons
Martijn P. van den Heuvel, Dirk Jan Ardesch, Lianne H. Scholtens

et al.

Proceedings of the National Academy of Sciences, Journal Year: 2023, Volume and Issue: 120(22)

Published: May 22, 2023

A long-standing topic of interest in human neurosciences is the understanding neurobiology underlying cognition. Less commonly considered to what extent such systems may be shared with other species. We examined individual variation brain connectivity context cognitive abilities chimpanzees (n = 45) and humans search a conserved link between cognition across two Cognitive scores were assessed on variety behavioral tasks using chimpanzee- human-specific test batteries, measuring aspects related relational reasoning, processing speed, problem solving both show that scoring higher skills display relatively strong among networks also associated comparable group. identified divergence serve specialized functions chimpanzees, as stronger language more prominent regions spatial working memory chimpanzees. Our findings suggest core neural have evolved before humans, along potential differential investments relating specific functional specializations

Language: Английский

Citations

13
Altered functional connectivity in patients with post-stroke fatigue: A resting-state fMRI study DOI
Wenwei Ren,

Mengpu Wang,

Qiongzhang Wang

et al.

Journal of Affective Disorders, Journal Year: 2024, Volume and Issue: 350, P. 468 - 475

Published: Jan. 21, 2024

Language: Английский

Citations

5
The subcortical default mode network and Alzheimer’s disease: a systematic review and meta-analysis DOI Creative Commons
Sara Seoane, Martijn P. van den Heuvel, Ángel Acebes

et al.

Brain Communications, Journal Year: 2024, Volume and Issue: 6(2)

Published: Jan. 1, 2024

Abstract The default mode network is a central cortical brain suggested to play major role in several disorders and be particularly vulnerable the neuropathological hallmarks of Alzheimer’s disease. Subcortical involvement its alteration disease remains largely unknown. We performed systematic review, meta-analysis empirical validation subcortical healthy adults, combined with analysis areas Our results show that, besides well-known regions, consistently includes namely thalamus, lobule vermis IX right Crus I/II cerebellum amygdala. Network also suggests caudate nucleus. In disease, we observed left-lateralized cluster decrease functional connectivity which covered medial temporal lobe amygdala showed overlap portion covering parts left anterior hippocampus found an increase insula. These confirm consistency contributions adults highlight relevance

Language: Английский

Citations

5
The Genetic Architectures of Functional and Structural Connectivity Properties within Cerebral Resting-State Networks DOI Creative Commons
Elleke Tissink, Josefin Werme, Siemon C. de Lange

et al.

eNeuro, Journal Year: 2023, Volume and Issue: 10(4), P. ENEURO.0242 - 22.2023

Published: March 7, 2023

Abstract Functional connectivity within resting-state networks (RSN-FC) is vital for cognitive functioning. RSN-FC heritable and partially translates to the anatomic architecture of white matter, but genetic component structural connections RSNs (RSN-SC) their potential overlap with remain unknown. Here, we perform genome-wide association studies ( N discovery = 24,336; replication 3412) annotation on RSN-SC RSN-FC. We identify genes visual network-SC that are involved in axon guidance synaptic Genetic variation impacts biological processes relevant brain disorders previously were only phenotypically associated alterations. Correlations components mostly observed functional domain, whereas less domain between domains. This study advances understanding complex organization its underpinnings from a genetics viewpoint.

Language: Английский

Citations

12