Qinghao Liang
About
Research
Publications
2025
Trends in self-citation rates in high-impact neurology, neuroscience, and psychiatry journals
Rosenblatt M, Mehta S, Peterson H, Dadashkarimi J, Rodriguez R, Foster M, Adkinson B, Liang Q, Kimble V, Ye J, McCusker M, Farruggia M, Rolison M, Westwater M, Jiang R, Noble S, Scheinost D. Trends in self-citation rates in high-impact neurology, neuroscience, and psychiatry journals. ELife 2025, 12: rp88540. PMID: 40366360, PMCID: PMC12077878, DOI: 10.7554/elife.88540.Peer-Reviewed Original ResearchTrends in self-citation rates in high-impact neurology, neuroscience, and psychiatry journals
Rosenblatt M, Mehta S, Peterson H, Dadashkarimi J, Rodriguez R, Foster M, Adkinson B, Liang Q, Kimble V, Ye J, McCusker M, Farruggia M, Rolison M, Westwater M, Jiang R, Noble S, Scheinost D. Trends in self-citation rates in high-impact neurology, neuroscience, and psychiatry journals. ELife 2025, 12 DOI: 10.7554/elife.88540.4.Peer-Reviewed Original ResearchMeta-Learning for Generalizable Connectome Modeling Across Heterogeneous Atlas Spaces
Liang Q, Adkinson B, Scheinost D. Meta-Learning for Generalizable Connectome Modeling Across Heterogeneous Atlas Spaces. 2025, 00: 1-5. DOI: 10.1109/isbi60581.2025.10981255.Peer-Reviewed Original Research
2024
Overcoming Atlas Heterogeneity in Federated Learning for Cross-Site Connectome-Based Predictive Modeling
Liang Q, Adkinson B, Jiang R, Scheinost D. Overcoming Atlas Heterogeneity in Federated Learning for Cross-Site Connectome-Based Predictive Modeling. Lecture Notes In Computer Science 2024, 15010: 579-588. DOI: 10.1007/978-3-031-72117-5_54.Peer-Reviewed Original ResearchA Flow-based Truncated Denoising Diffusion Model for super-resolution Magnetic Resonance Spectroscopic Imaging
Dong S, Cai Z, Hangel G, Bogner W, Widhalm G, Huang Y, Liang Q, You C, Kumaragamage C, Fulbright R, Mahajan A, Karbasi A, Onofrey J, de Graaf R, Duncan J. A Flow-based Truncated Denoising Diffusion Model for super-resolution Magnetic Resonance Spectroscopic Imaging. Medical Image Analysis 2024, 99: 103358. PMID: 39353335, PMCID: PMC11609020, DOI: 10.1016/j.media.2024.103358.Peer-Reviewed Original ResearchDenoising diffusion modelsDeep learning-based super-resolution methodsLearning-based super-resolution methodsMulti-scale super-resolutionGenerative modelSuper-resolution methodsDeep learning modelsHigh-resolution magnetic resonance spectroscopic imagingHigh-quality imagesPost-processing approachSuper-ResolutionFlow-based networksLearning modelsLow resolutionTruncation stepLow-resolution dataSharpness adjustmentNetworkSensitivity restrictionsUncertainty estimationDiffusion modelImagesCapabilitySampling processSpectroscopic imagingRescuing missing data in connectome-based predictive modeling
Liang Q, Jiang R, Adkinson B, Rosenblatt M, Mehta S, Foster M, Dong S, You C, Negahban S, Zhou H, Chang J, Scheinost D. Rescuing missing data in connectome-based predictive modeling. Imaging Neuroscience 2024, 2: imag-2-00071. PMID: 40800425, PMCID: PMC12224408, DOI: 10.1162/imag_a_00071.Peer-Reviewed Original Research
2022
Machine Learning and Prediction in Fetal, Infant, and Toddler Neuroimaging: A Review and Primer
Scheinost D, Pollatou A, Dufford A, Jiang R, Farruggia M, Rosenblatt M, Peterson H, Rodriguez R, Dadashkarimi J, Liang Q, Dai W, Foster M, Camp C, Tejavibulya L, Adkinson B, Sun H, Ye J, Cheng Q, Spann M, Rolison M, Noble S, Westwater M. Machine Learning and Prediction in Fetal, Infant, and Toddler Neuroimaging: A Review and Primer. Biological Psychiatry 2022, 93: 893-904. PMID: 36759257, PMCID: PMC10259670, DOI: 10.1016/j.biopsych.2022.10.014.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus StatementsA functional connectome signature of blood pressure in >30 000 participants from the UK biobank.
Jiang R, Calhoun VD, Noble S, Sui J, Liang Q, Qi S, Scheinost D. A functional connectome signature of blood pressure in >30 000 participants from the UK biobank. Cardiovascular Research 2022, 119: 1427-1440. PMID: 35875865, PMCID: PMC10262183, DOI: 10.1093/cvr/cvac116.Peer-Reviewed Original ResearchConceptsBlood pressureBP levelsSystolic/diastolic blood pressurePrevalent modifiable risk factorFunctional connectivityMeaningful blood pressureDiastolic blood pressureElevated blood pressureModifiable risk factorsBody mass indexWhole-brain functional connectivityCentral autonomic networkAnterior cingulate cortexAntihypertensive medicationsMass indexMultiple confoundersPulse pressureRisk factorsCardiovascular diseaseIrreversible structural damageMedicated participantsMedication statusCingulate cortexCognitive declineAlzheimer's diseaseA Neuroimaging Signature of Cognitive Aging from Whole‐Brain Functional Connectivity
Jiang R, Scheinost D, Zuo N, Wu J, Qi S, Liang Q, Zhi D, Luo N, Chung Y, Liu S, Xu Y, Sui J, Calhoun V. A Neuroimaging Signature of Cognitive Aging from Whole‐Brain Functional Connectivity. Advanced Science 2022, 9: 2201621. PMID: 35811304, PMCID: PMC9403648, DOI: 10.1002/advs.202201621.Peer-Reviewed Original ResearchConceptsCognitive declineNormal agingFunctional connectivitySimilar neural correlatesWhole-brain functional connectivityDorsal attention networkBrain network organizationNeural dedifferentiationFluid intelligenceCognitive agingCognitive abilitiesNeural correlatesAttention networkCognitive functionNetwork organizationHuman ageNeuroimaging signaturesCognitionUnique patternAgingConnectivityIntelligenceCorrelatesConstructsHealthy cohortPredicting the future of neuroimaging predictive models in mental health
Tejavibulya L, Rolison M, Gao S, Liang Q, Peterson H, Dadashkarimi J, Farruggia MC, Hahn CA, Noble S, Lichenstein SD, Pollatou A, Dufford AJ, Scheinost D. Predicting the future of neuroimaging predictive models in mental health. Molecular Psychiatry 2022, 27: 3129-3137. PMID: 35697759, PMCID: PMC9708554, DOI: 10.1038/s41380-022-01635-2.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus Statements