2024
Inducing representational change in the hippocampus through real-time neurofeedback
Peng K, Wammes J, Nguyen A, Iordan C, Norman K, Turk-Browne N. Inducing representational change in the hippocampus through real-time neurofeedback. Philosophical Transactions Of The Royal Society B Biological Sciences 2024, 379: 20230091. PMID: 39428880, PMCID: PMC11491844, DOI: 10.1098/rstb.2023.0091.Peer-Reviewed Original ResearchConceptsFunctional magnetic resonance imagingReal-time functional magnetic resonance imagingPatterns of fMRI activityCategorical perception taskReal-time neurofeedbackNeurocognitive mechanismsFMRI sessionStimulus similarityFMRI activationTask demandsBehavioral consequencesUntrained objectsNeural representationPerception taskMemory integrationRepresentational changeEndogenous neuromodulatorNeurofeedbackHippocampusCortical representationIncreased coactivationMagnetic resonance imagingVisual cortexMemoryMultiple theoriesA neural network model of differentiation and integration of competing memories
Ritvo V, Nguyen A, Turk-Browne N, Norman K. A neural network model of differentiation and integration of competing memories. ELife 2024, 12 DOI: 10.7554/elife.88608.3.Peer-Reviewed Original ResearchNeural network modelUnsupervised neural network modelUnsupervised learning mechanismLearning mechanismLearning modelsNetwork modelComputational explanationInactive memoryNeural representationActive competitorsDiverse setRepresentationMemoryRepresentation of memoryMemory literatureBrain regionsNovel predictionsA neural network model of differentiation and integration of competing memories
Ritvo V, Nguyen A, Turk-Browne N, Norman K. A neural network model of differentiation and integration of competing memories. ELife 2024, 12: rp88608. PMID: 39319791, PMCID: PMC11424095, DOI: 10.7554/elife.88608.Peer-Reviewed Original ResearchConceptsNeural network modelUnsupervised neural network modelUnsupervised learning mechanismLearning mechanismLearning modelsNetwork modelComputational explanationInactive memoryNeural representationActive competitorsDiverse setRepresentationMemoryRepresentation of memoryMemory literatureBrain regionsNovel predictions
2021
Learning hierarchical sequence representations across human cortex and hippocampus
Henin S, Turk-Browne NB, Friedman D, Liu A, Dugan P, Flinker A, Doyle W, Devinsky O, Melloni L. Learning hierarchical sequence representations across human cortex and hippocampus. Science Advances 2021, 7: eabc4530. PMID: 33608265, PMCID: PMC7895424, DOI: 10.1126/sciadv.abc4530.Peer-Reviewed Original ResearchConceptsOrdinal positionTransitional probabilitiesBrain areasEarliest brain areasGradient of complexityVisual sequencesCortico-hippocampal circuitsNeural representationNeural trackingEarly processingBrain's abilityTemporal regularityStatistical learningAssociative regionsSensory inputLow-level featuresHuman cortexSequence representationParallel computational systemsMultiple levelsComputational systemsIntracranial electrodesCortexHippocampusProcessing
2019
Relating Visual Production and Recognition of Objects in Human Visual Cortex
Fan JE, Wammes JD, Gunn JB, Yamins DLK, Norman KA, Turk-Browne NB. Relating Visual Production and Recognition of Objects in Human Visual Cortex. Journal Of Neuroscience 2019, 40: 1710-1721. PMID: 31871278, PMCID: PMC7046321, DOI: 10.1523/jneurosci.1843-19.2019.Peer-Reviewed Original ResearchConceptsNeural representationVisual cortexRich perceptual informationPotential neural substratesHuman visual cortexRecognition of objectsSimple line drawingsVisual productionPerceptual representationsPerceptual discriminabilityObject cuesPerceptual experienceRecognizable drawingsPerceptual informationNeural substratesNeural mechanismsRepresentational actionsTraining studiesHuman participantsCortex participatesParietal cortexProduction of drawingsEnhanced decodingExperience influencePatterns of connectivityNonmonotonic Plasticity: How Memory Retrieval Drives Learning
Ritvo VJH, Turk-Browne NB, Norman KA. Nonmonotonic Plasticity: How Memory Retrieval Drives Learning. Trends In Cognitive Sciences 2019, 23: 726-742. PMID: 31358438, PMCID: PMC6698209, DOI: 10.1016/j.tics.2019.06.007.Peer-Reviewed Original ResearchConceptsRecent fMRI studiesFunction of learningMemory retrievalMemory causesNeural representationFMRI studyInactive memorySame associatesSupervised learning modelDifferent stimuliLearningLearning modelStimuliNumerous findingsSame outcomeUnsupervised learningMemoryFindingsRetrievalOutcomesRepresentationIntegrationActivation causes
2018
Neural Overlap in Item Representations Across Episodes Impairs Context Memory
Kim G, Norman KA, Turk-Browne NB. Neural Overlap in Item Representations Across Episodes Impairs Context Memory. Cerebral Cortex 2018, 29: 2682-2693. PMID: 29897407, PMCID: PMC6519698, DOI: 10.1093/cercor/bhy137.Peer-Reviewed Original ResearchConceptsSubsequent source memorySource memoryContext memoryInitial contextBetter source memoryNovel contextual informationLateral occipital cortexNeural overlapRepresentational similarityNeural representationNeural patternsFMRI studyItem representationsSecond presentationLater retrievalDifferent tasksMemorySame itemsOccipital cortexInitial taskPattern similaritySuch reactivationInitial itemsNovel experienceContextual information
2017
Neural Differentiation of Incorrectly Predicted Memories
Kim G, Norman KA, Turk-Browne NB. Neural Differentiation of Incorrectly Predicted Memories. Journal Of Neuroscience 2017, 37: 2022-2031. PMID: 28115478, PMCID: PMC5338753, DOI: 10.1523/jneurosci.3272-16.2017.Peer-Reviewed Original ResearchConceptsNeural representationPrevious contextTarget memoryBOLD activity patternsGreater neural differentiationMemory representationsHuman fMRIMemory weakeningTrial fashionSubsequent restudySuch memoriesIndividual memoryNeural network simulationMemoryControl conditionFMRIComputational modelItemsPrediction strengthRestudyNeural connectionsPrediction errorMore differentiationParticular contextRepresentation
2013
Neural representations of events arise from temporal community structure
Schapiro AC, Rogers TT, Cordova NI, Turk-Browne NB, Botvinick MM. Neural representations of events arise from temporal community structure. Nature Neuroscience 2013, 16: 486-492. PMID: 23416451, PMCID: PMC3749823, DOI: 10.1038/nn.3331.Peer-Reviewed Original Research
2008
Spatiotemporal object continuity in human ventral visual cortex
Yi DJ, Turk-Browne NB, Flombaum JI, Kim MS, Scholl BJ, Chun MM. Spatiotemporal object continuity in human ventral visual cortex. Proceedings Of The National Academy Of Sciences Of The United States Of America 2008, 105: 8840-8845. PMID: 18591658, PMCID: PMC2442124, DOI: 10.1073/pnas.0802525105.Peer-Reviewed Original ResearchConceptsVentral visual cortexHuman ventral visual cortexNeural representationVisual cortexFace-selective cortical regionsSpatiotemporal continuityCoherent visual experienceSame persisting individualsCognitive science researchPerceptual representationsObject identityObject continuityIdentical objectsLess activationVisual experienceApparent motionObject persistenceVisual featuresCortical regionsSuch processingCortexDifferent individualsObjectsRepresentationPowerful principle