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For: Gaser C, Dahnke R, Thompson PM, Kurth F, Luders E, Alzheimer’s Disease Neuroimaging Initiative. CAT – A Computational Anatomy Toolbox for the Analysis of Structural MRI Data.. [DOI: 10.1101/2022.06.11.495736] [Cited by in Crossref: 11] [Cited by in F6Publishing: 16] [Article Influence: 11.0] [Reference Citation Analysis]
Number Citing Articles
1 Zhang Y, Li H, Zheng Q. A comprehensive characterization of hippocampal feature ensemble serves as individualized brain signature for Alzheimer's disease: deep learning analysis in 3238 participants worldwide. Eur Radiol 2023. [PMID: 36892643 DOI: 10.1007/s00330-023-09519-x] [Reference Citation Analysis]
2 Grecucci A, Dadomo H, Salvato G, Lapomarda G, Sorella S, Messina I. Abnormal Brain Circuits Characterize Borderline Personality and Mediate the Relationship between Childhood Traumas and Symptoms: A mCCA+jICA and Random Forest Approach. Sensors (Basel) 2023;23. [PMID: 36905064 DOI: 10.3390/s23052862] [Reference Citation Analysis]
3 Petersen M, Hoffstaedter F, Nägele FL, Mayer C, Schell M, Rimmele DL, Zyriax BC, Zeller T, Kühn S, Gallinat J, Fiehler J, Twerenbold R, Omidvarnia A, Patil KR, Eickhoff SB, Thomalla G, Cheng B. A Latent Clinical-anatomical Dimension Relating Metabolic Syndrome to Brain Morphology: Evidence from a Multivariate Imaging Analysis of 40,087 Individuals. bioRxiv 2023:2023. [PMID: 36865285 DOI: 10.1101/2023.02.22.529531] [Reference Citation Analysis]
4 Li R, Miao X, Han B, Li J. Cortical thickness of the left parahippocampal cortex links central hearing and cognitive performance in aging. Ann N Y Acad Sci 2023. [PMID: 36799333 DOI: 10.1111/nyas.14971] [Reference Citation Analysis]
5 Qin Q, Qu J, Yin Y, Liang Y, Wang Y, Xie B, Liu Q, Wang X, Xia X, Wang M, Zhang X, Jia J, Xing Y, Li C, Tang Y. Unsupervised machine learning model to predict cognitive impairment in subcortical ischemic vascular disease. Alzheimers Dement 2023. [PMID: 36786521 DOI: 10.1002/alz.12971] [Reference Citation Analysis]
6 Burles F, Williams R, Berger L, Pike GB, Lebel C, Iaria G. The Unresolved Methodological Challenge of Detecting Neuroplastic Changes in Astronauts. Life (Basel) 2023;13. [PMID: 36836857 DOI: 10.3390/life13020500] [Reference Citation Analysis]
7 Genç B, Şen S, Aslan K, İncesu L. Volumetric changes in hypothalamic subunits in patients with relapsing remitting multiple sclerosis. Neuroradiology 2023. [PMID: 36720749 DOI: 10.1007/s00234-023-03122-z] [Reference Citation Analysis]
8 Stalter J, Yogeswaran V, Vogel W, Sörös P, Mathys C, Witt K. The impact of aging on morphometric changes in the cerebellum: A voxel-based morphometry study. Front Aging Neurosci 2023;15:1078448. [PMID: 36743442 DOI: 10.3389/fnagi.2023.1078448] [Reference Citation Analysis]
9 Brooks JO 3rd, Kruse JL, Kubicki A, Hellemann G, Espinoza RT, Irwin MR, Narr KL. Structural brain plasticity and inflammation are independently related to changes in depressive symptoms six months after an index ECT course. Psychol Med 2023;:1-9. [PMID: 36600668 DOI: 10.1017/S0033291722003555] [Reference Citation Analysis]
10 Baggio T, Grecucci A, Meconi F, Messina I. Anxious Brains: A Combined Data Fusion Machine Learning Approach to Predict Trait Anxiety from Morphometric Features. Sensors (Basel) 2023;23. [PMID: 36679404 DOI: 10.3390/s23020610] [Reference Citation Analysis]
11 Li Q, Wang W, Hu Z. Amygdala's T1-weighted image radiomics outperforms volume for differentiation of anxiety disorder and its subtype. Front Psychiatry 2023;14:1091730. [PMID: 36911127 DOI: 10.3389/fpsyt.2023.1091730] [Reference Citation Analysis]
12 Matziorinis AM, Gaser C, Koelsch S. Is musical engagement enough to keep the brain young? Brain Struct Funct 2023;228:577-88. [PMID: 36574049 DOI: 10.1007/s00429-022-02602-x] [Reference Citation Analysis]
13 Hu Y, Li Q, Qiao K, Zhang X, Chen B, Yang Z. PhiPipe: A multi-modal MRI data processing pipeline with test-retest reliability and predicative validity assessments. Hum Brain Mapp 2023;44:2062-84. [PMID: 36583399 DOI: 10.1002/hbm.26194] [Cited by in Crossref: 1] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
14 Velioglu HA, Ayyildiz B, Ayyildiz S, Sutcubasi B, Hanoglu L, Bayraktaroglu Z, Yulug B. A structural and resting-state functional connectivity investigation of the pulvinar in elderly individuals and Alzheimer's disease patients. Alzheimers Dement 2022. [PMID: 36576157 DOI: 10.1002/alz.12850] [Reference Citation Analysis]
15 Liu J, Xie S, Hu Y, Ding Y, Zhang X, Liu W, Zhang L, Ma C, Kang Y, Jin S, Xia Y, Hu Z, Liu Z, Cheng W, Yang Z. Age-dependent alterations in the coordinated development of subcortical regions in adolescents with social anxiety disorder. Eur Child Adolesc Psychiatry 2022. [PMID: 36542201 DOI: 10.1007/s00787-022-02118-z] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
16 Pastore-Wapp M, Gyurkó DM, Vanbellingen T, Lehnick D, Cazzoli D, Pflugshaupt T, Pflugi S, Nyffeler T, Walther S, Bohlhalter S. Improved gesturing in left-hemispheric stroke by right inferior parietal theta burst stimulation. Front Neurosci 2022;16:998729. [PMID: 36590287 DOI: 10.3389/fnins.2022.998729] [Reference Citation Analysis]
17 Ruzok T, Schmitz-Koep B, Menegaux A, Eves R, Daamen M, Boecker H, Rieger-Fackeldey E, Priller J, Zimmer C, Bartmann P, Wolke D, Sorg C, Hedderich DM. Lower hypothalamus subunit volumes link with impaired long-term body weight gain after preterm birth. Front Endocrinol (Lausanne) 2022;13:1057566. [PMID: 36589836 DOI: 10.3389/fendo.2022.1057566] [Reference Citation Analysis]
18 Hu Z, Wang X, Meng L, Liu W, Wu F, Meng X. Detection of Association Features Based on Gene Eigenvalues and MRI Imaging Using Genetic Weighted Random Forest. Genes (Basel) 2022;13. [PMID: 36553611 DOI: 10.3390/genes13122344] [Reference Citation Analysis]
19 Petersen M, Nägele FL, Mayer C, Schell M, Rimmele DL, Petersen E, Kühn S, Gallinat J, Hanning U, Fiehler J, Twerenbold R, Gerloff C, Thomalla G, Cheng B. Brain network architecture constrains age-related cortical thinning. Neuroimage 2022;264:119721. [PMID: 36341953 DOI: 10.1016/j.neuroimage.2022.119721] [Reference Citation Analysis]
20 Glutig K, Lange L, Krüger PC, Gräger S, de Vries H, Brandl U, Gaser C, Mentzel HJ. Differences in Cerebellar Volume as a Diagnostic and Prognostic Biomarker in Children and Adolescents With Epilepsy of Unknown Etiology. J Child Neurol 2022;37:939-48. [PMID: 36113051 DOI: 10.1177/08830738221114241] [Reference Citation Analysis]
21 Conti M, Stefani A, Bovenzi R, Cerroni R, Garasto E, Placidi F, Liguori C, Schirinzi T, Mercuri NB, Pierantozzi M. STN-DBS Induces Acute Changes in β-Band Cortical Functional Connectivity in Patients with Parkinson's Disease. Brain Sci 2022;12. [PMID: 36552066 DOI: 10.3390/brainsci12121606] [Reference Citation Analysis]
22 Strelnikov D, Alijanpourotaghsara A, Piroska M, Szalontai L, Forgo B, Jokkel Z, Persely A, Hernyes A, Kozak LR, Szabo A, Maurovich-horvat P, Tarnoki DL, Tarnoki AD. Heritability of Subcortical Grey Matter Structures. Medicina 2022;58:1687. [DOI: 10.3390/medicina58111687] [Reference Citation Analysis]
23 Baggio T, Grecucci A, Meconi F, Messina I. Anxious brains: A combined data fusion machine learning approach to predict trait anxiety from gray and white matter features.. [DOI: 10.21203/rs.3.rs-2255161/v1] [Reference Citation Analysis]
24 Ding H, Droby A, Anwar AR, Bange M, Hausdorff JM, Nasseroleslami B, Mirelman A, Maidan I, Groppa S, Muthuraman M. Treadmill training in Parkinson’s disease is underpinned by the interregional connectivity in cortical-subcortical network. npj Parkinsons Dis 2022;8:153. [DOI: 10.1038/s41531-022-00427-3] [Reference Citation Analysis]
25 Van Hoornweder S, A Caulfield K, Nitsche M, Thielscher A, L J Meesen R. Addressing transcranial electrical stimulation variability through prospective individualized dosing of electric field strength in 300 participants across two samples: the 2-SPED approach. J Neural Eng 2022;19. [PMID: 36240729 DOI: 10.1088/1741-2552/ac9a78] [Reference Citation Analysis]
26 Penhale SH, Picci G, Ott LR, Taylor BK, Frenzel MR, Eastman JA, Wang YP, Calhoun VD, Stephen JM, Wilson TW. Impacts of adrenarcheal DHEA levels on spontaneous cortical activity during development. Dev Cogn Neurosci 2022;57:101153. [PMID: 36174268 DOI: 10.1016/j.dcn.2022.101153] [Reference Citation Analysis]
27 Vickery S, Patil KR, Dahnke R, Hopkins WD, Sherwood CC, Caspers S, Eickhoff SB, Hoffstaedter F. The Uniqueness of Human Vulnerability to Brain Aging in Great Ape Evolution.. [DOI: 10.1101/2022.09.27.509685] [Reference Citation Analysis]
28 Ryan B, O’mara Baker A, Ilse C, Brickell KL, Kersten HM, Williams JM, Addis DR, Tippett LJ, Curtis MA. The New Zealand Genetic Frontotemporal Dementia Study (FTDGeNZ): a longitudinal study of pre-symptomatic biomarkers. Journal of the Royal Society of New Zealand. [DOI: 10.1080/03036758.2022.2101483] [Reference Citation Analysis]
29 Cross-sectional and longitudinal multicentre cohort study, Bernal J, Schreiber S, Ostendorf A, Pfister M, Geisendörfer J, Nemali A, Maass A, Yakupov R, Peters O, Preis L, Schneider L, Herrera AL, Priller J, Spruth EJ, Altenstein S, Schneider A, Fliessbach K, Wiltfang J, Schott BH, Rostamzadeh A, Glanz W, Buerger K, Janowitz D, Ewers M, Perneczky R, Rauchmann B, Teipel S, Kilimann I, Laske C, Munk MH, Spottke A, Roy N, Dobisch L, Dechent P, Scheffler K, Hetzer S, Wolfsgruber S, Kleineidam L, Schmid M, Berger M, Jessen F, Wirth M, Düzel E, Ziegler G. Arterial hypertension and Aβ-amyloid accumulation have spatially overlapping effects on posterior white matter hyperintensity presence and volume.. [DOI: 10.1101/2022.07.19.22277546] [Reference Citation Analysis]
30 Petersen M, Nägele FL, Mayer C, Schell M, Rimmele DL, Petersen E, Kühn S, Gallinat J, Hanning U, Fiehler J, Twerenbold R, Gerloff C, Thomalla G, Cheng B. Brain Network Architecture Constrains Age-related Cortical Thinning.. [DOI: 10.1101/2022.07.08.499363] [Reference Citation Analysis]
31 Petersen M, Nägele FL, Mayer C, Schell M, Petersen E, Kühn S, Gallinat J, Fiehler J, Pasternak O, Matschke J, Glatzel M, Twerenbold R, Gerloff C, Thomalla G, Cheng B. Brain imaging and neuropsychological assessment of individuals recovered from mild COVID-19.. [DOI: 10.1101/2022.07.08.22277420] [Reference Citation Analysis]
32 Long Z. SPAMRI: A MATLAB Toolbox for Surface-Based Processing and Analysis of Magnetic Resonance Imaging. Front Hum Neurosci 2022;16:946156. [DOI: 10.3389/fnhum.2022.946156] [Reference Citation Analysis]
33 Mercier MR, Dubarry A, Tadel F, Avanzini P, Axmacher N, Cellier D, Vecchio MD, Hamilton LS, Hermes D, Kahana MJ, Knight RT, Llorens A, Megevand P, Melloni L, Miller KJ, Piai V, Puce A, Ramsey NF, Schwiedrzik CM, Smith SE, Stolk A, Swann NC, Vansteensel MJ, Voytek B, Wang L, Lachaux J, Oostenveld R. Advances in human intracranial electroencephalography research, guidelines and good practices. NeuroImage 2022. [DOI: 10.1016/j.neuroimage.2022.119438] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 2.0] [Reference Citation Analysis]
34 Hu Y, Li Q, Qiao K, Zhang X, Chen B, Yang Z. PhiPipe: a multi-modal MRI data processing pipeline with test-retest reliability and predicative validity assessments.. [DOI: 10.1101/2022.06.22.497141] [Reference Citation Analysis]
35 Simonsson O, Bouso JC, Kurth F, Araújo DB, Gaser C, Riba J, Luders E. Preliminary evidence of links between ayahuasca use and the corpus callosum. Front Psychiatry 2022;13:1002455. [PMID: 36386967 DOI: 10.3389/fpsyt.2022.1002455] [Reference Citation Analysis]
36 Kurth F, Levitt JG, Gaser C, Alger J, Loo SK, Narr KL, O'Neill J, Luders E. Preliminary evidence for a lower brain age in children with attention-deficit/hyperactivity disorder. Front Psychiatry 2022;13:1019546. [PMID: 36532197 DOI: 10.3389/fpsyt.2022.1019546] [Reference Citation Analysis]