Neural and Behavioral Interactions Between Attention, Perception, and Learning
Neural and Behavioral Interactions Between Attention, Perception, and Learning
批准号:
8515424
负责人:
Nicholas Benjamin Turk-Browne
金额:
$33.77万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2011
资助国家:
美国
项目状态:
已结题
起止时间:
2011-08-01 至 2016-07-31
关键词:
AddressAffectArchitectureAreaAttentionBehavioralBrainBrain InjuriesBrain regionCategoriesCognitionCognitiveCognitive ScienceDataDevelopmentDiagnosisDiseaseEventExhibitsEye diseasesFaceFunctional Magnetic Resonance ImagingGoalsHippocampus (Brain)HumanIndividualInferiorInjuryKnowledgeLeadLearningLightLinkMachine LearningMapsMedialMemoryMethodsMindModelingNatureNeurosciencesNoiseOccipital lobeParietalParietal LobePerceptionPhysiologicalPositioning AttributeProcessPropertyRecoveryRehabilitation therapyResearchResidual stateResolutionRestRetrievalRoleSensory ProcessShort-Term MemorySignal TransductionSourceStagingStimulusSumSynapsesSystemTemporal LobeTestingTrainingVisionVisualVisual CortexVisual FieldsVisual PerceptionVisual impairmentVisual system structureWorkbasecognitive neuroscienceexperienceextrastriate visual cortexfrontal lobehippocampal subregionsimprovedinformation processinginnovationmemory retrievalneuroimagingneuromechanismnovel strategiesrelating to nervous systemresponseretinotopicselective attentiontransmission processvisual informationvisual learningvisual memoryvisual processvisual processingvisual stimulus
中文摘要
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英文摘要
DESCRIPTION (provided by applicant): The overarching goal of this research is to characterize how perception and memory interact, in terms of both the learning mechanisms that help transform visual experience into memory, and the intentional mechanisms that regulate this transformation. The specific goal of this proposal is to test the hypothesis that incidental learning about statistical regularities in vision (visual statistical learning) is limited to selectively attend visual information, and that this behavioral interaction arises because of how selective attention modulates neural interactions between human visual and memory systems. We propose a two-stage framework in which selective attention to a high-level visual feature/category increases neural interactions between regions of occipital cortex that represent low-level features and the region of inferior temporal cortex (IT) that represents the attended feature/category, and in turn between this IT region and medial temporal lobe (MTL) sub regions involved in visual learning and memory. In addition to assessing how feature-based selective attention influences learning at a behavioral level, we will use functional magnetic resonance imaging to assess how attention influences evoked neural responses in task-relevant brain regions, as well as neural interactions between these regions in the background of ongoing tasks. We will develop an innovative approach for studying neural interactions in which evoked responses and global noise sources are scrubbed from the data and regional correlations are assessed in the residuals. This background connectivity approach provides a new way to study how intentional goals affect perception and learning. Aim 1 examines the first stage of our framework, testing: how selective attention modulates background connectivity between IT and occipital cortex, where in retinotopic visual cortex this modulation occurs, and how these changes are controlled by frontal and parietal cortex. Aim 2 examines the second stage of our framework, first establishing the role of the MTL in visual statistical learning, and then testing: how selective attention modulates interactions between IT and the MTL, where in cortical and hippocampal sub regions of the MTL this modulation occurs, and how these changes facilitate incidental learning about statistical regularities and later retrieval of this knowledge. In sum, we relate behavioral interactions between selective attention and learning to neural interactions between the mechanisms that represent visual features and those that learn about their relations. This proposal addresses several key issues in the field, including: how attention modulates the MTL, how feature-based attention is controlled, whether different neural mechanisms support rapid versus long-term visual learning, how tasks and goals are represented, and how attention and memory retrieval are related. This research will improve our understanding of how humans learn from visual experience, and how visual processing is in turn influenced by learning. These advances will shed light on the plasticity that occurs during development and during the recovery and rehabilitation of visual function following eye disease, injury, or brain damage.
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会议论文
Neural and Behavioral Interactions Between Attention, Perception, and Learning
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批准号:8306867
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项目类别:
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资助金额:$35.56万
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财政年份:2011
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负责人:Nicholas Benjamin Turk-Browne
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依托单位:
Neural and Behavioral Interactions Between Attention, Perception, and Learning
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批准号:8708870
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项目类别:
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资助金额:$34.85万
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财政年份:2011
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负责人:Nicholas Benjamin Turk-Browne
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依托单位:
Neural and Behavioral Interactions Between Attention, Perception, and Learning
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批准号:8895328
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项目类别:
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资助金额:$34.78万
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财政年份:2011
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负责人:Nicholas Benjamin Turk-Browne
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依托单位:
Neural and Behavioral Interactions Between Attention, Perception, and Learning
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批准号:8162573
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项目类别:
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资助金额:$36.22万
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财政年份:2011
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负责人:Nicholas Benjamin Turk-Browne
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依托单位:
海外基金