2023
Connectome-based machine learning models are vulnerable to subtle data manipulations
Rosenblatt M, Rodriguez R, Westwater M, Dai W, Horien C, Greene A, Constable R, Noble S, Scheinost D. Connectome-based machine learning models are vulnerable to subtle data manipulations. Patterns 2023, 4: 100756. PMID: 37521052, PMCID: PMC10382940, DOI: 10.1016/j.patter.2023.100756.Peer-Reviewed Original ResearchData manipulationNoise attacksPrediction performanceMachine learning modelsManipulated dataLearning modelHigh trustworthinessConnectome dataTrustworthinessAttacksModel performancePredictive modelDownstream analysisPerformanceAcademic researchMachineRobustnessModelConnectomeConnectome-based modelsFunctional connectomeManipulationPredicting depressed and elevated mood symptomatology in bipolar disorder using brain functional connectomes
Sankar A, Shen X, Colic L, Goldman D, Villa L, Kim J, Pittman B, Scheinost D, Constable R, Blumberg H. Predicting depressed and elevated mood symptomatology in bipolar disorder using brain functional connectomes. Psychological Medicine 2023, 53: 6656-6665. PMID: 36891769, PMCID: PMC10491744, DOI: 10.1017/s003329172300003x.Peer-Reviewed Original ResearchBipolar disorderYoung Mania Rating ScaleMania Rating ScaleFunctional connectomeBrain functional connectomeSymptom scoresHamilton DepressionMagnetic resonance imaging dataEmotion processing taskMood symptomatologyRating ScaleFunctional magnetic resonance imaging (fMRI) dataConnectomeAdultsImaging dataIndependent samplesPredictive abilitySymptomatology
2019
The individual functional connectome is unique and stable over months to years
Horien C, Shen X, Scheinost D, Constable RT. The individual functional connectome is unique and stable over months to years. NeuroImage 2019, 189: 676-687. PMID: 30721751, PMCID: PMC6422733, DOI: 10.1016/j.neuroimage.2019.02.002.Peer-Reviewed Original ResearchConceptsHigh ID ratesIndividual differencesFunctional connectomeIndividual functional connectomesStable individual differencesID rateResting-state fMRI datasetsFrontoparietal networkFunctional connectivityParietal cortexFMRI datasetsIdiosyncratic aspectsConnectomeHead motionEntire brainFMRIBrainCortexSpecific datasetDifferencesConnectivityChapter 4 The uniqueness of the individual functional connectome
Horien C, Scheinost D, Constable R. Chapter 4 The uniqueness of the individual functional connectome. 2019, 63-81. DOI: 10.1016/b978-0-12-813838-0.00004-2.Peer-Reviewed Original ResearchFunctional magnetic resonance imagingIndividual differencesIndividual functional connectomesBrain functionConnectivity dataGroup-level differencesFunctional connectivity dataHuman neuroimagingBehavioral measuresFunctional connectomeMagnetic resonance imagingResonance imagingInterindividual heterogeneityNext turnConnectomeCognitionBest predictive modelNeuroimagingDifferencesParticipantsDisease
2018
79. Transdiagnostic Prediction of Memory and Cognitive Abilities From Functional Connectivity Data: A Multidimensional Connectome-Based Predictive Modeling Study
Scheinost D, Gao S, Greene A, Constable R. 79. Transdiagnostic Prediction of Memory and Cognitive Abilities From Functional Connectivity Data: A Multidimensional Connectome-Based Predictive Modeling Study. Biological Psychiatry 2018, 83: s33. DOI: 10.1016/j.biopsych.2018.02.096.Peer-Reviewed Original Research