2024
Computational reconstruction of mental representations using human behavior
Caplette L, Turk-Browne N. Computational reconstruction of mental representations using human behavior. Nature Communications 2024, 15: 4183. PMID: 38760341, PMCID: PMC11101448, DOI: 10.1038/s41467-024-48114-6.Peer-Reviewed Original ResearchConceptsMental representationsGoal of cognitive scienceVisual featuresNeural networkMultiple visual conceptsDeep neural networksConceptual representationCognitive scienceVisual conceptsSemantic spaceSemantic featuresHuman behaviorParticipantsNetworkRepresentationStimuliBehaviorFeaturesImagesComputer reconstructionTask
2022
Spatial statistics in perception, learning, and navigation
Graves K, Turk-Browne N. Spatial statistics in perception, learning, and navigation. 2022, 119-133. DOI: 10.4324/9781003158134-8.ChaptersStatistical learningReal-world behaviorNeural mechanismsVisual worldComplex spatial behaviourStatistical perceptionFoundational processGroups of objectsLearningSpatial informationCurrent researchPerceptionSpatial behaviorObjectsDifferent formsMultiple exposuresBehaviorSingle exposureExperienceInterdependenceResearchAbilityGeneral properties
2020
The prevalence and importance of statistical learning in human cognition and behavior
Sherman BE, Graves KN, Turk-Browne NB. The prevalence and importance of statistical learning in human cognition and behavior. Current Opinion In Behavioral Sciences 2020, 32: 15-20. PMID: 32258249, PMCID: PMC7108790, DOI: 10.1016/j.cobeha.2020.01.015.Peer-Reviewed Original ResearchStatistical learningHuman cognitionStatistical learning researchRange of tasksEpisodic memoryLearning phenomenonSpatial navigationHuman behaviorLearning domainsLearning researchCognitionLearningPervasive roleMemoryTaskBehaviorAdulthoodUnrelated processesInfancyContextImportant contributorResearchAbility
2018
Infant fMRI: A Model System for Cognitive Neuroscience
Ellis CT, Turk-Browne NB. Infant fMRI: A Model System for Cognitive Neuroscience. Trends In Cognitive Sciences 2018, 22: 375-387. PMID: 29487030, PMCID: PMC5911209, DOI: 10.1016/j.tics.2018.01.005.Peer-Reviewed Original Research
2014
Pruning of memories by context-based prediction error
Kim G, Lewis-Peacock JA, Norman KA, Turk-Browne NB. Pruning of memories by context-based prediction error. Proceedings Of The National Academy Of Sciences Of The United States Of America 2014, 111: 8997-9002. PMID: 24889631, PMCID: PMC4066528, DOI: 10.1073/pnas.1319438111.Peer-Reviewed Original ResearchConceptsFunctional magnetic resonance imagingPattern similarity analysisLong-term memoryMultivariate pattern classificationContext-based predictionsExperienced contextItem representationsMemoryHuman brainUnreliable memorySimilarity analysisPrediction errorAdaptive processItemsMagnetic resonance imagingRobust supportRepresentationPattern classificationResonance imagingContextBrainMemory banksFindingsSupportBehavior
2007
Age-Related Deficits in Face Recognition are Related to Underlying Changes in Scanning Behavior
Firestone A, Turk-Browne NB, Ryan JD. Age-Related Deficits in Face Recognition are Related to Underlying Changes in Scanning Behavior. Aging Neuropsychology And Cognition 2007, 14: 594-607. PMID: 18038358, DOI: 10.1080/13825580600899717.Peer-Reviewed Original ResearchConceptsRecognition memoryOld facesOlder adultsScanning behaviorWorse recognition memoryAge-related deficitsSocial group statusAge-related differencesAge-related impairmentFace processingYounger groupGroup statusEye movementsMemoryProcessing strategiesYoung adultsFacial featuresFace recognitionMore transitionsAdultsFaceBehaviorDeficitsImpairmentProcessing