2024
High performers demonstrate greater neural synchrony than low performers across behavioral domains
Chamberlain T, Corriveau A, Song H, Kwon Y, Yoo K, Chun M, Rosenberg M. High performers demonstrate greater neural synchrony than low performers across behavioral domains. Imaging Neuroscience 2024, 2: 1-17. DOI: 10.1162/imag_a_00128.Peer-Reviewed Original ResearchBrain-behavior relationshipsBrain activityBehavioral domainsIntersubject representational similarity analysisPatterns of brain activityRepresentational similarity analysisBehavior scoresNeural similarityBehavior ScaleParticipant sampleNeural synchronyBehavioral similaritiesFMRI datasetsBrainSimilarity analysisLow performanceIndividualsScoresScorersBehaviorTheoretical frameworkParticipantsRelationshipTacit assumptionSynchronyEdge-Based General Linear Models Capture Moment-to-Moment Fluctuations in Attention
Jones H, Yoo K, Chun M, Rosenberg M. Edge-Based General Linear Models Capture Moment-to-Moment Fluctuations in Attention. Journal Of Neuroscience 2024, 44: e1543232024. PMID: 38316565, PMCID: PMC10993033, DOI: 10.1523/jneurosci.1543-23.2024.Peer-Reviewed Original ResearchMoment-to-moment fluctuationsFMRI functional connectivityFMRI analysisProcessing of task-relevant informationSustained attention taskTask-based fMRITask-relevant informationDynamic FC approachParametric fMRI analysisField of network neuroscienceTraditional fMRI analysisNeural underpinningsAttention taskSustained attentionIndividual differencesCognitive processesTask eventsFunctional connectivityNetwork neuroscienceRegions-of-interestGeneralized linear modelAttentional stateFMRI datasetsYoung adultsIndividual's ability
2023
Multiple visual objects are represented differently in the human brain and convolutional neural networks
Mocz V, Jeong S, Chun M, Xu Y. Multiple visual objects are represented differently in the human brain and convolutional neural networks. Scientific Reports 2023, 13: 9088. PMID: 37277406, PMCID: PMC10241785, DOI: 10.1038/s41598-023-36029-z.Peer-Reviewed Original ResearchConceptsObject representationsConvolutional neural networkMultiple visual objectsHuman brainRecurrent processingVisual objectsProcessing regionsSingle-unit levelObject pairsIT neuronsFMRI voxelsSingle objectConstituent objectsPrimate brainBrain dataNeural networkDifferent contextsResponse patternsObject classificationReal worldObjectsRepresentationUnit levelBrainSuch distortionsWhat Moves Us? The Intrinsic Memorability of Dance
Ongchoco J, Chun M, Bainbridge W. What Moves Us? The Intrinsic Memorability of Dance. Journal Of Experimental Psychology Learning Memory And Cognition 2023, 49: 889-899. PMID: 36201801, DOI: 10.1037/xlm0001168.Peer-Reviewed Original ResearchConceptsExpressive actionsIntrinsic memorabilityRobust memorySimple actionsMemorabilityMemoryDynamic experienceObjective measuresStatic imagesAesthetic attributesPerceiversDanceDynamic sequenceIndividual snapshotsPeopleExperienceRemarkable consistencyGesturesLong sequencesPrevious workConsistencyStatic memory
2022
A generalizable connectome-based marker of in-scan sustained attention in neurodiverse youth
Horien C, Greene A, Shen X, Fortes D, Brennan-Wydra E, Banarjee C, Foster R, Donthireddy V, Butler M, Powell K, Vernetti A, Mandino F, O'Connor D, Lake E, McPartland J, Volkmar F, Chun M, Chawarska K, Rosenberg M, Scheinost D, Constable R. A generalizable connectome-based marker of in-scan sustained attention in neurodiverse youth. Cerebral Cortex 2022, 33: 6320-6334. PMID: 36573438, PMCID: PMC10183743, DOI: 10.1093/cercor/bhac506.Peer-Reviewed Original ResearchConceptsAttention taskAttentional stateConnectome-based predictive modelingNeurodiverse conditionsSustained attention taskAttention network modelSample of youthNeurotypical participantsSustained attentionBrain correlatesNeurobiological correlatesAttention networkIndividual participantsSeparate samplesYouthParticipantsHead motionTaskCorrelatesAttentionAutismConfoundsNetwork modelGeneralizesHealthcare settingsDifferences in the functional brain architecture of sustained attention and working memory in youth and adults
Kardan O, Stier A, Cardenas-Iniguez C, Schertz K, Pruin J, Deng Y, Chamberlain T, Meredith W, Zhang X, Bowman J, Lakhtakia T, Tindel L, Avery E, Lin Q, Yoo K, Chun M, Berman M, Rosenberg M. Differences in the functional brain architecture of sustained attention and working memory in youth and adults. PLOS Biology 2022, 20: e3001938. PMID: 36542658, PMCID: PMC9815648, DOI: 10.1371/journal.pbio.3001938.Peer-Reviewed Original ResearchConceptsSustained attentionFunctional brain architectureWM performanceIndividual differencesFunctional connectivityBrain architectureLater recognition memoryRecognition memoryWM modelBrain networksWMMemoryYouthAge groupsFunctional connectionsAdultsChildrenNetwork predictorAttentionPerformancePredictorsDifferencesConnectivityAbilityRepresenting multiple visual objects in the human brain and convolutional neural networks
Mocz V, Jeong S, Chun M, Xu Y. Representing multiple visual objects in the human brain and convolutional neural networks. Journal Of Vision 2022, 22: 3665. DOI: 10.1167/jov.22.14.3665.Peer-Reviewed Original ResearchFunctional connectome stability and optimality are markers of cognitive performance
Corriveau A, Yoo K, Kwon Y, Chun M, Rosenberg M. Functional connectome stability and optimality are markers of cognitive performance. Cerebral Cortex 2022, 33: 5025-5041. PMID: 36408606, PMCID: PMC10110430, DOI: 10.1093/cercor/bhac396.Peer-Reviewed Original ResearchConceptsFunctional connectivityAspects of attentionConnectivity patternsFunctional connectivity patternsAttentional abilitiesMemory taskCognitive tasksIndividual differencesCognitive performanceInitial evidenceCognitionIndependent samplesTaskFunctional connectionsConnectomeIndividualsConnectivityAttentionDistinctive patternsOptimal patternAbilityPrevious workPatternsPredicting Identity-Preserving Object Transformations in Human Posterior Parietal Cortex and Convolutional Neural Networks
Mocz V, Vaziri-Pashkam M, Chun M, Xu Y. Predicting Identity-Preserving Object Transformations in Human Posterior Parietal Cortex and Convolutional Neural Networks. Journal Of Cognitive Neuroscience 2022, 34: 2406-2435. PMID: 36122358, PMCID: PMC9988239, DOI: 10.1162/jocn_a_01916.Peer-Reviewed Original ResearchConceptsOccipito-temporal cortexPosterior parietal cortexHuman posterior parietal cortexHuman occipito-temporal cortexNon-Euclidean featuresObject identityParietal cortexConvolutional neural networkPrimate ventral visual systemSuperior intraparietal sulcusVisual object informationVentral visual systemFeature changesObject responsesIntraparietal sulcusCurrent best modelVisual systemEuclidean featuresObject informationResponse of objectsPrevious researchNeural networkObject transformationCortexObject classification
2021
Predicting Identity-Preserving Object Transformations across the Human Ventral Visual Stream
Mocz V, Vaziri-Pashkam M, Chun M, Xu Y. Predicting Identity-Preserving Object Transformations across the Human Ventral Visual Stream. Journal Of Neuroscience 2021, 41: 7403-7419. PMID: 34253629, PMCID: PMC8412993, DOI: 10.1523/jneurosci.2137-20.2021.Peer-Reviewed Original Research
2020
Transformations of Object Representations Across the Human Visual Processing Hierarchy
Mocz V, Vaziri-Pashkam M, Chun M, Xu Y. Transformations of Object Representations Across the Human Visual Processing Hierarchy. Journal Of Vision 2020, 20: 1262. DOI: 10.1167/jov.20.11.1262.Peer-Reviewed Original Research
2019
Deep learning fMRI classification of temporal codes during naturalistic movie viewing and memory recall
Johnson M, O’Connell T, Chun M, Johnson M. Deep learning fMRI classification of temporal codes during naturalistic movie viewing and memory recall. Journal Of Vision 2019, 19: 203a. DOI: 10.1167/19.10.203a.Peer-Reviewed Original ResearchZero-shot neural decoding from rhesus macaque inferior temporal cortex using deep convolutional neural networks
O’Connell T, Chun M, Kreiman G. Zero-shot neural decoding from rhesus macaque inferior temporal cortex using deep convolutional neural networks. Journal Of Vision 2019, 19: 209a. DOI: 10.1167/19.10.209a.Peer-Reviewed Original ResearchImage memorability is driven by visual and conceptual distinctivenes
Lin Q, Yousif S, Scholl B, Chun M. Image memorability is driven by visual and conceptual distinctivenes. Journal Of Vision 2019, 19: 290c. DOI: 10.1167/19.10.290c.Peer-Reviewed Original Research
2018
Visual memorability in the absence of semantic content
Lin Q, Yousif S, Scholl B, Chun M. Visual memorability in the absence of semantic content. Journal Of Vision 2018, 18: 1302. DOI: 10.1167/18.10.1302.Peer-Reviewed Original ResearchMemory and Attention
Long N, Kuhl B, Chun M. Memory and Attention. 2018, 1-37. DOI: 10.1002/9781119170174.epcn109.Peer-Reviewed Original Research
2017
Studying Consciousness Through Inattentional Blindness, Change Blindness, and the Attentional Blink
Cohen M, Chun M. Studying Consciousness Through Inattentional Blindness, Change Blindness, and the Attentional Blink. 2017, 537-550. DOI: 10.1002/9781119132363.ch38.Peer-Reviewed Original Research
2016
Statistical learning of movement
Ongchoco J, Uddenberg S, Chun M. Statistical learning of movement. Journal Of Vision 2016, 16: 1079. DOI: 10.1167/16.12.1079.Peer-Reviewed Original Research
2015
A neuromarker of sustained attention from whole-brain functional connectivity
Rosenberg MD, Finn ES, Scheinost D, Papademetris X, Shen X, Constable RT, Chun MM. A neuromarker of sustained attention from whole-brain functional connectivity. Nature Neuroscience 2015, 19: 165-171. PMID: 26595653, PMCID: PMC4696892, DOI: 10.1038/nn.4179.Peer-Reviewed Original ResearchFunctional connectome fingerprinting: identifying individuals using patterns of brain connectivity
Finn ES, Shen X, Scheinost D, Rosenberg MD, Huang J, Chun MM, Papademetris X, Constable RT. Functional connectome fingerprinting: identifying individuals using patterns of brain connectivity. Nature Neuroscience 2015, 18: 1664-1671. PMID: 26457551, PMCID: PMC5008686, DOI: 10.1038/nn.4135.Peer-Reviewed Original Research