Decoding information in the human hippocampus: a user's guide.
Decoding information in the human hippocampus: a user's guide.
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DOI:
10.1016/j.neuropsychologia.2012.07.007
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发表时间:
2012-11
期刊:
影响因子:
2.6
通讯作者:
Maguire EA
中科院分区:
文献类型:
--
作者:
Chadwick MJ;Bonnici HM;Maguire EA
Multi-voxel pattern analysis (MVPA), or ‘decoding’, of fMRI activity has gained popularity in the neuroimaging community in recent years. MVPA differs from standard fMRI analyses by focusing on whether information relating to specific stimuli is encoded in patterns of activity across multiple voxels. If a stimulus can be predicted, or decoded, solely from the pattern of fMRI activity, it must mean there is information about that stimulus represented in the brain region where the pattern across voxels was identified. This ability to examine the representation of information relating to specific stimuli (e.g., memories) in particular brain areas makes MVPA an especially suitable method for investigating memory representations in brain structures such as the hippocampus. This approach could open up new opportunities to examine hippocampal representations in terms of their content, and how they might change over time, with aging, and pathology. Here we consider published MVPA studies that specifically focused on the hippocampus, and use them to illustrate the kinds of novel questions that can be addressed using MVPA. We then discuss some of the conceptual and methodological challenges that can arise when implementing MVPA in this context. Overall, we hope to highlight the potential utility of MVPA, when appropriately deployed, and provide some initial guidance to those considering MVPA as a means to investigate the hippocampus. ► Multi-voxel pattern analysis (MVPA) is increasingly used to analyse fMRI data. ► We review the relatively few studies that have used MVPA to examine the hippocampus. ► We consider methodological challenges related to implementing this approach. ► We conclude that fMRI MVPA can offer new insights into the role of the hippocampus.
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影响因子:
64.8
作者:
Epstein, R;Kanwisher, N
通讯作者:
Kanwisher, N
影响因子:
64.8
作者:
Ekstrom, AD;Kahana, MJ;Fried, I
通讯作者:
Fried, I
DOI:
10.1016/j.cub.2010.01.053
发表时间:
2010-03-23
期刊:
Current biology : CB
影响因子:
--
作者:
Chadwick MJ;Hassabis D;Weiskopf N;Maguire EA
通讯作者:
Maguire EA
影响因子:
5.3
作者:
Graham, Kim S.;Scahill, Victoria L.;Saksida, Lisa M.
通讯作者:
Saksida, Lisa M.
影响因子:
16.2
作者:
Carr, Valerie A.;Rissman, Jesse;Wagner, Anthony D.
通讯作者:
Wagner, Anthony D.