2024
A 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 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 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 predictions
2022
How Well Do Unsupervised Learning Algorithms Model Human Real-time and Life-long Learning?
Zhuang C, Xiang V, Bai Y, Jia X, Turk-Browne N, Norman K, DiCarlo J, Yamins D. How Well Do Unsupervised Learning Algorithms Model Human Real-time and Life-long Learning? Advances In Neural Information Processing Systems 2022, 35: 22628-22642. PMID: 38435074, PMCID: PMC10906807.Peer-Reviewed Original ResearchSelf-supervised algorithmLearning algorithmsReal-timeStreams of visual inputNeural network modelHuman learning abilitiesMoCo v2Catastrophic forgettingLearning benchmarksLearning capabilityVisual inputReal worldHuman learnersNetwork modelVisual knowledgeLeverage memoryPerformance of modelsAlgorithmHuman performanceBenchmarksNegative samplesContext-sensitiveLearning abilityLearningVision setting
2018
Common Object Representations for Visual Production and Recognition
Fan JE, Yamins DLK, Turk‐Browne N. Common Object Representations for Visual Production and Recognition. Cognitive Science 2018, 42: 2670-2698. PMID: 30125986, PMCID: PMC6497164, DOI: 10.1111/cogs.12676.Peer-Reviewed Original ResearchConceptsVisual object recognitionStudy of visionDeep convolutional neural network modelNatural imagesConvolutional neural network modelAbstract feature representationRecognizable drawingsHuman learningObject representationsVisual productionNeural network modelObject recognitionConceptual knowledgeVisual formVisual conceptsVisual cortexRecognition dataDeep networkFeature representationEnhanced recognitionAbstract featuresComprehensionHigher layersNetwork modelOnline platforms
2017
Complementary learning systems within the hippocampus: a neural network modelling approach to reconciling episodic memory with statistical learning
Schapiro AC, Turk-Browne NB, Botvinick MM, Norman KA. Complementary learning systems within the hippocampus: a neural network modelling approach to reconciling episodic memory with statistical learning. Philosophical Transactions Of The Royal Society B Biological Sciences 2017, 372: 20160049. PMID: 27872368, PMCID: PMC5124075, DOI: 10.1098/rstb.2016.0049.Peer-Reviewed Original ResearchConceptsStatistical learningRapid learningComplementary learning systems theoryComplementary learning systemsSequence of itemsEpisodic memoryIndividual episodesCognitive scienceAssociative reactivationTemporal regularityApparent representationIndividual experiencesNeural network modelling approachNeural network modelLearningLearning systemAnatomical pathwaysHippocampusSystems theoryHippocampal projectionsRegion CA1MemoryNetwork modelMemorizationExperience