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The organization of the basal ganglia functional connectivity network is non-linear in Parkinson's disease

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Introduction to Human Neuroimaging

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MRI Study on the Functional and Spatial Consistency of Resting State-Related Independent Components of the Brain Network

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Tensor clustering on outer-product of coefficient and component matrices of independent component analysis for reliable functional magnetic resonance imaging data decomposition

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A study of within-subject reliability of the brain’s default-mode network

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Actividad funcional cerebral en estado de reposo: redes en conexión

Proal, E., Segura, M. Á., de la Iglesia-Vayá, M., Martí‐Bonmatí, L., Castellanos, F. X., & Spanish Resting State Network Spanish Resting State Network (2011) · Revista de Neurología · doi:10.33588/rn.52s01.2010792 · Cited by 12

Consistency of independent component analysis for FMRI

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Amplitudes of resting-state functional networks – investigation into their correlates and biophysical properties

Lee, S., Bijsterbosch, J. D., Alfaro‐Almagro, F., Elliott, L. T., McCarthy, P., Taschler, B., Sala‐Llonch, R., Beckmann, C. F., Duff, E. P., Smith, S. M., et al. (2022) · NeuroImage · doi:10.1016/j.neuroimage.2022.119779 · Cited by 13

Hemodynamic Response Function (HRF) in Epilepsy Patients with Hippocampal Sclerosis and Focal Cortical Dysplasia

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Test-Retest Reliability of Resting Brain Small-World Network Properties across Different Data Processing and Modeling Strategies

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Improved correspondence of resting‐state networks after macroanatomical alignment

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Internal representation of hierarchical sequences involves the default network

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Similarity analysis of functional connectivity with functional near-infrared spectroscopy

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Impact of Independent Component Analysis Dimensionality on the Test–Retest Reliability of Resting-State Functional Connectivity

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Individualized, connectome-based, non-invasive stimulation of OCD deep-brain targets: A proof-of-concept

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Resting‐State Brain Dynamics Unique to Anxiety in Major Depressive Disorder

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Heterogeneous fractionation profiles of meta-analytic coactivation networks

Laird, A. R., Riedel, M. C., Okoe, M., Jianu, R., Ray, K. L., Eickhoff, S. B., Smith, S. M., Fox, P. T., & Sutherland, M. T. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2016.12.037 · Cited by 7

ℛSCZ: A Riemannian schizophrenia diagnosis framework based on the multiplexity of EEG-based dynamic functional connectivity patterns

Dimitriadis, S. I. (2024) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2024.108862 · Cited by 8

Spatiotemporal connectivity maps abnormal communication pathways in major depressive disorder underlying gamma oscillations

Chen, S., Liu, X., Huang, Z., Su, F., Zhang, W., Li, J., Liu, S., & Ming, D. (2023) · Cerebral Cortex · doi:10.1093/cercor/bhad204 · Cited by 6

Resting-state networks in healthy adult subjects: a comparison between a 32-element and an 8-element phased array head coil at 3.0 Tesla

Paolini, M., Keeser, D., Ingrisch, M., Werner, N. S., Kindermann, N. K., Reiser, M. F., & Blautzik, J. (2015) · Acta Radiologica · doi:10.1177/0284185114567703 · Cited by 6

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Correlation between the Functional Connectivity of Brain Areas Active in the Resting State with Behavioral and Psychological Indicators

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Resting-state functional magnetic resonance imaging in a randomized clinical trial for Alzheimer's disease

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Neuroimaging Approaches for Elderly Studies

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An Information System in the Brain: Evidence from fMRI BOLD Responses

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Risk and resilience: A new perspective on Alzheimer's disease

Teipel, S. J. (2013) · Geriatric Mental Health Care · doi:10.1016/j.gmhc.2013.04.003 · Cited by 6

Complementary Methods

de Beeck, H. O., & Nakatani, C. (2019) · Cambridge University Press eBooks · doi:10.1017/9781316847916.017 · Cited by 4

Test-retest reliability of peak location in the sensorimotor network of resting state fMRI for potential rTMS targets

Hu, Y., Yue, J., Ge, Q., Feng, Z., Wang, J., & Zang, Y. (2022) · Frontiers in Neuroinformatics · doi:10.3389/fninf.2022.882126 · Cited by 3

Test-Retest Reliability of Functional Networks for Evaluation of Data-Driven Parcellation

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Evaluating the retest reproducibility of intrinsic connectivity network using multivariate correlation coefficient

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Key Intrinsic Connectivity Networks for Individual Identification With Siamese Long Short-Term Memory

Park, Y.-H., Shin, S. A., Kim, S., & Lee, J. (2021) · Frontiers in Neuroscience · doi:10.3389/fnins.2021.660187 · Cited by 4

Contribution of Nucleus Accumbens Core (AcbC) to Behavior Control during a Learned Resting Period: Introduction of a Novel Task and Lesion Experiments

Sato, C., Hoshino, M., Ikumi, N., Oba, K., Koike, A., Shouno, O., Sekiguchi, T., Kobayashi, T., Machida, T., Matsumoto, G., et al. (2014) · PLoS ONE · doi:10.1371/journal.pone.0095941 · Cited by 3

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Test–retest reliability and time-of-day variations of perfusion imaging at rest and during a vigilance task

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Advanced Data Analysis

de Beeck, H. O., & Nakatani, C. (2019) · Cambridge University Press eBooks · doi:10.1017/9781316847916.016 · Cited by 2

Network Imaging

Guo, J. N., & Blumenfeld, H. (2014) · Elsevier eBooks · doi:10.1016/b978-0-12-415804-7.00006-x · Cited by 3

Electrophysiological Neuroimaging

de Beeck, H. O., & Nakatani, C. (2019) · Cambridge University Press eBooks · doi:10.1017/9781316847916.012 · Cited by 2

An examination of the reliability of seed-to-seed resting state functional connectivity in tinnitus patients

Schmidt, S. A., Shahsavarani, S., Khan, R. A., Tai, Y., Granato, E. C., Willson, C. M., Ramos, P., Sherman, P. M., Esquivel, C. R., Sutton, B. P., et al. (2023) · Neuroimage Reports · doi:10.1016/j.ynirp.2023.100158 · Cited by 3

Stability of Whole Brain and Regional Network Topology Within and Between Resting and Cognitive States

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Repeatability analysis of ICA-based harmonization for multi-site MRI data using dual projection models

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MRI- and PET-Based Imaging Markers for the Diagnosis of Alzheimer’s Disease

Teipel, S. J., Sperling, R. A., Skudlarski, P., Jack, C. R., Hampel, H. J., Fellgiebel, A., & Herholz, K. (2012) · Advances in biological psychiatry · doi:10.1159/000335393 · Cited by 1

Functional imaging in Huntington disease

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Pain‐free default mode network connectivity contributes to tonic experimental pain intensity beyond the role of negative mood and other pain‐related factors

Alhajri, N., Boudreau, S. A., Mouraux, A., & Graven‐Nielsen, T. (2023) · European Journal of Pain · doi:10.1002/ejp.2141 · Cited by 1

Resting-state fMRI and population neuroscience: Progresses and guidelines for reliability research

Luo, W., Luo, C., Yan, Z., Wang, Y., & Zuo, X. (2024) · Chinese Science Bulletin (Chinese Version) · doi:10.1360/tb-2024-0204 · Cited by 1

Functional and Structural MRI in Alzheimer’s Disease: A Multimodal Approach

Grothe, M. J., Bokde, A. L. W., & Teipel, S. J. (2014) · Springer eBooks · doi:10.1007/978-3-642-54542-9_20 · Cited by 1

Welche bildgebenden Verfahren sind in der Demenzdiagnostik sinnvoll?

Sakretz, M., Kurth, J., Teipel, S., & Krause, B. (2014) · DNP - Der Neurologe und Psychiater · doi:10.1007/s15202-014-0811-0 · Cited by 1

Image Processing

de Beeck, H. O., & Nakatani, C. (2019) · Cambridge University Press eBooks · doi:10.1017/9781316847916.009 · Cited by 1

Big Data und Gesundheit

Ethikrat, D. (2021) · Informationszentrum Lebenswissenschaften (ZB MED) · doi:10.4126/frl01-006428645 · Cited by 1

To select one hand while using both : neural mechanisms supporting flexible hand dominance in bimanual object manipulation

Theorin, A. (2009) · DiVA at Umeå University (Umeå University) · Cited by 1

Application of resting-state fMRI methods to acute ischemic stroke

Lv, Y. (2013) · Qucosa (Saxon State and University Library Dresden) · Cited by 1

Alzheimer’s disease through the MR-eye; novel diagnostic markers and the road to clinical implementation

Clerx, L. (2014) · Research Publications (Maastricht University) · doi:10.26481/dis.20140516lc · Cited by 1

Evaluating the strength of functional connectivity during the resting state

Wang, H., & Lu, Z. (2011) · International Conference on Natural Computation (ICNC) · doi:10.1109/icnc.2011.6022213

Effect of mindfulness meditation on the neural substrates of emotion processing and resting state in experienced and beginner meditators

Taylor, V. A. (2011) · Papyrus : Institutional Repository (Université de Montréal) · doi:10.71781/19025

Resting state functional magnetic resonance imaging analysis by graphical model

Liu, W. (2014) · J. Willard Marriott Library · doi:10.26053/0h-rt2d-w500

DOPAMINE-REGULATING GENES, EXECUTIVE CONTROL, AND THE NETWORK STRUCTURE OF THE HUMAN BRAIN

Gordon, E. M. (2013) · DigitalGeorgetown (Georgetown University Library)

Functionalconnectivityin BOLDand CBF data: Similarityandreliabilityof resting brain networks

Jann, K., Gee, D. G., Kilroy, E., Schwab, S., Smith, X., & Cannon, T. D. (2015)

Establishing the sensitivity of functional near-infrared spectroscopy to cognitive load and state in healthy adults and children with Autism Spectrum Disorder

Fishburn, F. A. (2017) · DigitalGeorgetown (Georgetown University Library)

Investigating the Neural Networks Involved in Externalizing and Conscientious Behavior

Rueter, A. (2019) · University of Minnesota Digital Conservancy (University of Minnesota)

Electromagnetic Field of the Brain

de Beeck, H. O., & Nakatani, C. (2019) · Cambridge University Press eBooks · doi:10.1017/9781316847916.013

The Physics behind Magnetic Resonance Imaging (MRI)

de Beeck, H. O., & Nakatani, C. (2019) · Cambridge University Press eBooks · doi:10.1017/9781316847916.004

Designing a Hemodynamic Imaging Experiment

de Beeck, H. O., & Nakatani, C. (2019) · Cambridge University Press eBooks · doi:10.1017/9781316847916.008

Causal Methods to Modulate Brain Activity

de Beeck, H. O., & Nakatani, C. (2019) · Cambridge University Press eBooks · doi:10.1017/9781316847916.019

Basic Statistical Analyses

de Beeck, H. O., & Nakatani, C. (2019) · Cambridge University Press eBooks · doi:10.1017/9781316847916.010

Basic Analysis of Electrophysiological Signals

de Beeck, H. O., & Nakatani, C. (2019) · Cambridge University Press eBooks · doi:10.1017/9781316847916.015

Advanced Statistical Analyses

de Beeck, H. O., & Nakatani, C. (2019) · Cambridge University Press eBooks · doi:10.1017/9781316847916.011

Trait-like resting-state brain oscillations predict subsequent problem-solving strategies

Erickson, B. A., & Kounios, J. (2017) · doi:10.17918/etd-7723

Memory, dementia, and the functional role of the parietal cortex

Seibert, T. M. (2011) · eScholarship (California Digital Library)

Funcionamento cerebral de repouso em idosos e recuperação de memória autobiográfica: um estudo de ressonância magnética funcional

Ferreira, L. K. (2015) · doi:10.11606/t.5.2015.tde-13052015-104814

Introduction and Overview

de Beeck, H. O., & Nakatani, C. (2019) · Cambridge University Press eBooks · doi:10.1017/9781316847916.002

Multi-modal Imaging

de Beeck, H. O., & Nakatani, C. (2019) · Cambridge University Press eBooks · doi:10.1017/9781316847916.018

Structural Imaging Methods

de Beeck, H. O., & Nakatani, C. (2019) · Cambridge University Press eBooks · doi:10.1017/9781316847916.005

Hemodynamic Neuroimaging

de Beeck, H. O., & Nakatani, C. (2019) · Cambridge University Press eBooks · doi:10.1017/9781316847916.006

Glossary

de Beeck, H. O., & Nakatani, C. (2019) · Cambridge University Press eBooks · doi:10.1017/9781316847916.020

Neuroimaging Approaches for Elderly Studies

Styliadis, C., Kartsidis, P. E., & Paraskevopoulos, E. (2016) · IGI Global eBooks · doi:10.4018/978-1-5225-0571-6.ch067

Structural Neuroimaging

de Beeck, H. O., & Nakatani, C. (2019) · Cambridge University Press eBooks · doi:10.1017/9781316847916.003

Preface

de Beeck, H. O., & Nakatani, C. (2019) · Cambridge University Press eBooks · doi:10.1017/9781316847916.001

References

de Beeck, H. O., & Nakatani, C. (2019) · Cambridge University Press eBooks · doi:10.1017/9781316847916.021

P2‐007: Longitudinal reproducibility of default‐mode network connectivity in healthy elderly participants: A multicentric resting‐state fMRI study

Jovicich, J., Minati, L., Marizzoni, M., Nobili, F. M., Didic, M., David Bartrés-faz, A., Fiedler, U., Schönknecht, P. O. D., Payoux, P., Beltramello, A., et al. (2015) · Alzheimer s & Dementia · doi:10.1016/j.jalz.2015.06.543

Longitudinal reproducibility of default-mode network connectivity in healthy elderly participants: A multicentric resting-state fMRI study

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Kim, Y., & Lee, J. (2011) · Conference proceedings/Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics · doi:10.1109/icsmc.2011.6084152

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Huang, Y. H., Williams, W., Tomasi, G., Zheng, M., Lin, S.-F., Ropchan, J. R., Labaree, D. C., Olsen, J., Tabriz, M., Planeta‐Wilson, B., et al. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.04.161 · Cited by 1

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Li, K. (2010) · Zhongguo yixue yingxiang jishu