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Items: 1 to 20 of 210

1.

Connectome-based predictive modeling of attention: Comparing different functional connectivity features and prediction methods across datasets.

Yoo K, Rosenberg MD, Hsu WT, Zhang S, Li CR, Scheinost D, Constable RT, Chun MM.

Neuroimage. 2018 Feb 15;167:11-22. doi: 10.1016/j.neuroimage.2017.11.010. Epub 2017 Nov 6.

2.

Methylphenidate Modulates Functional Network Connectivity to Enhance Attention.

Rosenberg MD, Zhang S, Hsu WT, Scheinost D, Finn ES, Shen X, Constable RT, Li CS, Chun MM.

J Neurosci. 2016 Sep 14;36(37):9547-57. doi: 10.1523/JNEUROSCI.1746-16.2016.

3.

Connectome-based Models Predict Separable Components of Attention in Novel Individuals.

Rosenberg MD, Hsu WT, Scheinost D, Todd Constable R, Chun MM.

J Cogn Neurosci. 2018 Feb;30(2):160-173. doi: 10.1162/jocn_a_01197. Epub 2017 Oct 17.

PMID:
29040013
4.

An information network flow approach for measuring functional connectivity and predicting behavior.

Kumar S, Yoo K, Rosenberg MD, Scheinost D, Constable RT, Zhang S, Li CR, Chun MM.

Brain Behav. 2019 Jul 9:e01346. doi: 10.1002/brb3.1346. [Epub ahead of print]

5.

Neural circuitry underlying sustained attention in healthy adolescents and in ADHD symptomatology.

O'Halloran L, Cao Z, Ruddy K, Jollans L, Albaugh MD, Aleni A, Potter AS, Vahey N, Banaschewski T, Hohmann S, Bokde ALW, Bromberg U, Büchel C, Quinlan EB, Desrivières S, Flor H, Frouin V, Gowland P, Heinz A, Ittermann B, Nees F, Orfanos DP, Paus T, Smolka MN, Walter H, Schumann G, Garavan H, Kelly C, Whelan R.

Neuroimage. 2018 Apr 1;169:395-406. doi: 10.1016/j.neuroimage.2017.12.030. Epub 2017 Dec 21.

PMID:
29274748
6.

Task modulations and clinical manifestations in the brain functional connectome in 1615 fMRI datasets.

Kaufmann T, Alnæs D, Brandt CL, Doan NT, Kauppi K, Bettella F, Lagerberg TV, Berg AO, Djurovic S, Agartz I, Melle IS, Ueland T, Andreassen OA, Westlye LT.

Neuroimage. 2017 Feb 15;147:243-252. doi: 10.1016/j.neuroimage.2016.11.073. Epub 2016 Dec 1.

PMID:
27916665
7.

Connectome-based models predict attentional control in aging adults.

Fountain-Zaragoza S, Samimy S, Rosenberg MD, Prakash RS.

Neuroimage. 2019 Feb 1;186:1-13. doi: 10.1016/j.neuroimage.2018.10.074. Epub 2018 Oct 28.

PMID:
30394324
8.

Dynamic functional connectivity during task performance and rest predicts individual differences in attention across studies.

Fong AHC, Yoo K, Rosenberg MD, Zhang S, Li CR, Scheinost D, Constable RT, Chun MM.

Neuroimage. 2019 Mar;188:14-25. doi: 10.1016/j.neuroimage.2018.11.057. Epub 2018 Dec 3.

9.

Connectome-based individualized prediction of temperament trait scores.

Jiang R, Calhoun VD, Zuo N, Lin D, Li J, Fan L, Qi S, Sun H, Fu Z, Song M, Jiang T, Sui J.

Neuroimage. 2018 Dec;183:366-374. doi: 10.1016/j.neuroimage.2018.08.038. Epub 2018 Aug 17.

PMID:
30125712
10.

A functional connectivity-based neuromarker of sustained attention generalizes to predict recall in a reading task.

Jangraw DC, Gonzalez-Castillo J, Handwerker DA, Ghane M, Rosenberg MD, Panwar P, Bandettini PA.

Neuroimage. 2018 Feb 1;166:99-109. doi: 10.1016/j.neuroimage.2017.10.019. Epub 2017 Oct 12.

11.

The effect of machine learning regression algorithms and sample size on individualized behavioral prediction with functional connectivity features.

Cui Z, Gong G.

Neuroimage. 2018 Sep;178:622-637. doi: 10.1016/j.neuroimage.2018.06.001. Epub 2018 Jun 2.

PMID:
29870817
12.

A neuromarker of sustained attention from whole-brain functional connectivity.

Rosenberg MD, Finn ES, Scheinost D, Papademetris X, Shen X, Constable RT, Chun MM.

Nat Neurosci. 2016 Jan;19(1):165-71. doi: 10.1038/nn.4179. Epub 2015 Nov 23.

13.

Characterising resting-state functional connectivity in a large sample of adults with ADHD.

Mostert JC, Shumskaya E, Mennes M, Onnink AM, Hoogman M, Kan CC, Arias Vasquez A, Buitelaar J, Franke B, Norris DG.

Prog Neuropsychopharmacol Biol Psychiatry. 2016 Jun 3;67:82-91. doi: 10.1016/j.pnpbp.2016.01.011. Epub 2016 Jan 26.

14.

Quantification of the impact of a confounding variable on functional connectivity confirms anti-correlated networks in the resting-state.

Carbonell F, Bellec P, Shmuel A.

Neuroimage. 2014 Feb 1;86:343-53. doi: 10.1016/j.neuroimage.2013.10.013. Epub 2013 Oct 12.

PMID:
24128734
15.

Increased default-mode variability is related to reduced task-performance and is evident in adults with ADHD.

Mowinckel AM, Alnæs D, Pedersen ML, Ziegler S, Fredriksen M, Kaufmann T, Sonuga-Barke E, Endestad T, Westlye LT, Biele G.

Neuroimage Clin. 2017 Mar 30;16:369-382. doi: 10.1016/j.nicl.2017.03.008. eCollection 2017.

16.

Proportional thresholding in resting-state fMRI functional connectivity networks and consequences for patient-control connectome studies: Issues and recommendations.

van den Heuvel MP, de Lange SC, Zalesky A, Seguin C, Yeo BTT, Schmidt R.

Neuroimage. 2017 May 15;152:437-449. doi: 10.1016/j.neuroimage.2017.02.005. Epub 2017 Feb 3.

17.

Reliability and reproducibility of individual differences in functional connectivity acquired during task and resting state.

Shah LM, Cramer JA, Ferguson MA, Birn RM, Anderson JS.

Brain Behav. 2016 Mar 30;6(5):e00456. doi: 10.1002/brb3.456. eCollection 2016 May.

18.

Connectivity Analysis and Feature Classification in Attention Deficit Hyperactivity Disorder Sub-Types: A Task Functional Magnetic Resonance Imaging Study.

Park BY, Kim M, Seo J, Lee JM, Park H.

Brain Topogr. 2016 May;29(3):429-39. doi: 10.1007/s10548-015-0463-1. Epub 2015 Nov 24.

PMID:
26602102
19.

Predicting individual brain functional connectivity using a Bayesian hierarchical model.

Dai T, Guo Y; Alzheimer's Disease Neuroimaging Initiative.

Neuroimage. 2017 Feb 15;147:772-787. doi: 10.1016/j.neuroimage.2016.11.048. Epub 2016 Dec 1.

20.

Prediction of individualized task activation in sensory modality-selective frontal cortex with 'connectome fingerprinting'.

Tobyne SM, Somers DC, Brissenden JA, Michalka SW, Noyce AL, Osher DE.

Neuroimage. 2018 Dec;183:173-185. doi: 10.1016/j.neuroimage.2018.08.007. Epub 2018 Aug 6.

PMID:
30092348

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