Neural and Behavioral Interactions Between Attention, Perception, and Learning
Neural and Behavioral Interactions Between Attention, Perception, and Learning
批准号:
8895328
负责人:
Nicholas Benjamin Turk-Browne
金额:
$34.78万
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 2017-07-31
关键词:
AddressAffectArchitectureAreaAttentionBehavioralBrainBrain InjuriesBrain regionCategoriesCognitionCognitive ScienceDataDevelopmentDiagnosisDiseaseEventExhibitsEye diseasesFaceFunctional Magnetic Resonance ImagingGoalsHippocampus (Brain)HumanIndividualInferiorInjuryKnowledgeLeadLearningLightLinkMachine LearningMapsMedialMemoryMethodsMindModelingNatureNeurosciencesNoiseOccipital lobeParietalParietal LobePerceptionPhysiologicalPositioning AttributeProcessPropertyRecoveryRehabilitation therapyResearchResidual stateResolutionRestRetrievalRoleSensory ProcessShort-Term MemorySignal TransductionSourceStagingStimulusSumSynapsesSystemTemporal LobeTestingTrainingVisionVisualVisual CortexVisual FieldsVisual PerceptionVisual impairmentVisual system structureWorkbasecognitive neurosciencecognitive processcognitive taskexperienceextrastriate visual cortexfrontal lobehippocampal subregionsimprovedinformation processinginnovationmemory retrievalneuroimagingneuromechanismnovel strategiesrelating to nervous systemresponseretinotopicselective attentiontransmission processvisual informationvisual learningvisual memoryvisual processvisual processingvisual stimulus
中文摘要
描述(由申请人提供):本研究的总体目标是描述感知和记忆如何相互作用,包括帮助将视觉经验转化为记忆的学习机制和调节这种转化的意向机制。本提案的具体目标是验证关于视觉统计规律的偶然学习(视觉统计学习)仅限于选择性地参加视觉信息的假设,这种行为相互作用的产生是因为选择性注意如何调节人类视觉和记忆系统之间的神经相互作用。我们提出了一个两阶段的框架,在这个框架中,对高级视觉特征/类别的选择性注意增加了代表低级特征的枕皮质区域和代表被注意的特征/类别的下颞叶皮层(IT)区域之间的神经相互作用,反过来,这个IT区域和参与视觉学习和记忆的内侧颞叶(MTL)亚区域之间的神经相互作用。除了评估基于特征的选择性注意如何在行为水平上影响学习,我们还将使用功能磁共振成像来评估注意如何影响与任务相关的大脑区域的诱发神经反应,以及这些区域之间在正在进行的任务背景下的神经相互作用。我们将开发一种创新的方法来研究神经相互作用,其中从数据中去除诱发反应和全局噪声源,并在残差中评估区域相关性。这种背景连接方法为研究意向目标如何影响感知和学习提供了一种新的途径。目的1检查了我们的框架的第一阶段,测试:选择性注意如何调节IT和枕叶皮层之间的背景连接,这种调制在视网膜异位视觉皮层中发生,以及这些变化是如何由额叶和顶叶皮层控制的。目的2考察了我们框架的第二阶段,首先建立了MTL在视觉统计学习中的作用,然后测试:选择性注意如何调节IT和MTL之间的相互作用,MTL的皮层和海马亚区发生这种调节,以及这些变化如何促进统计规律的偶然学习和随后的知识检索。总之,我们将选择性注意和学习之间的行为相互作用与代表视觉特征的机制和学习它们之间关系的机制之间的神经相互作用联系起来。本研究旨在解决该领域的几个关键问题,包括:注意如何调节MTL,基于特征的注意如何被控制,不同的神经机制是否支持快速和长期视觉学习,任务和目标如何表征,以及注意和记忆检索如何相关。这项研究将提高我们对人类如何从视觉经验中学习,以及视觉处理如何反过来受到学习的影响的理解。这些进展将阐明在眼部疾病、损伤或脑损伤后的发育和视觉功能恢复和康复过程中发生的可塑性。
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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DOI:
10.1126/science.1238409
发表时间:
2013-11-01
期刊:
Science (New York, N.Y.)
影响因子:
--
作者:
[Turk-Browne NB]
通讯作者:
Turk-Browne NB
DOI:
10.1162/jocn_a_00889
发表时间:
2016-01
期刊:
Journal of cognitive neuroscience
影响因子:
3.2
作者:
[Hutchinson JB, Pak SS, Turk-Browne NB]
通讯作者:
Turk-Browne NB
DOI:
10.1162/jocn_a_01284
发表时间:
2018-09
期刊:
Journal of cognitive neuroscience
影响因子:
3.2
作者:
[Tompary A, Al-Aidroos N, Turk-Browne NB]
通讯作者:
Turk-Browne NB
DOI:
10.1371/journal.pcbi.1005674
发表时间:
2017-08
期刊:
PLoS computational biology
影响因子:
4.3
作者:
[Bejjanki VR, da Silveira RA, Cohen JD, Turk-Browne NB]
通讯作者:
Turk-Browne NB
DOI:
10.1038/nn.3331
发表时间:
2013-04
期刊:
NATURE NEUROSCIENCE
影响因子:
25
作者:
[Schapiro, Anna C., Rogers, Timothy T., Cordova, Natalia I., Turk-Browne, Nicholas B., Botvinick, Matthew M.]
通讯作者:
Botvinick, Matthew M.
共 22 条
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:
-
资助金额:$35.56万
-
财政年份:2011
-
负责人:Nicholas Benjamin Turk-Browne
-
依托单位:
Neural and Behavioral Interactions Between Attention, Perception, and Learning
-
批准号:8708870
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项目类别:
-
资助金额:$34.85万
-
财政年份:2011
-
负责人:Nicholas Benjamin Turk-Browne
-
依托单位:
Neural and Behavioral Interactions Between Attention, Perception, and Learning
-
批准号:8515424
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项目类别:
-
资助金额:$33.77万
-
财政年份:2011
-
负责人:Nicholas Benjamin Turk-Browne
-
依托单位:
Neural and Behavioral Interactions Between Attention, Perception, and Learning
-
批准号:8162573
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项目类别:
-
资助金额:$36.22万
-
财政年份:2011
-
负责人:Nicholas Benjamin Turk-Browne
-
依托单位:
海外基金