RECOGNITION MEMORY STATES BASED ON DISTRIBUTED PATTERNS OF FMRI

这个子项目是许多研究子项目中利用 资源由NIH/NCRR资助的中心拨款提供。子项目和 调查员(PI)可能从NIH的另一个来源获得了主要资金， 并因此可以在其他清晰的条目中表示。列出的机构是 该中心不一定是调查人员的机构。 虽然大脑在经历新的感觉刺激时的反应与之前遇到的刺激不同，但传统的功能磁共振成像(FMRI)数据分析方法利用单变量统计来比较任务条件下的体素活动水平，不能可靠地在单次试验中捕捉到这些助记效应。我们试图利用分布式fMRI活动模式所代表的丰富信息，使用多体素模式分析方法来解码单个刺激的助记状态。在扫描之前，参与者研究了200张人脸的彩色照片。随后，参与者在对200张被研究的面孔和200张新面孔进行识别记忆决定时进行了扫描。对于每一张测试脸，参与者表明他们是否1)回忆起曾经研究过这张脸，2)高度自信地研究过它，3)认为他们研究过它，4)认为他们没有研究过它，或者5)高度自信他们没有研究过它。

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. While the brain responds differently when it experiences a novel sensory stimulus as compared to a previously encountered stimulus, conventional functional magnetic resonance imaging (fMRI) data analysis approaches, utilizing univariate statistics to compare voxel activity levels across task conditions, cannot reliably capture these mnemonic effects on single trials. We sought to exploit the wealth of information represented in distributed fMRI activity patterns, using a multi-voxel pattern analysis approach to decode the mnemonic status of individual stimuli. Prior to scanning, participants studied 200 color photographs of human faces. Subsequently, participants were scanned while they made recognition memory decisions about the 200 studied faces intermixed with 200 novel faces. For each test face, participants indicated whether they 1) recollected having studied the face, 2) were highly confident they studied it, 3) thought they studied it, 4) thought they did not study it, or 5) were highly confident they did not study it.