Dataset Information

Dissociation between anterior and posterior cortical regions during self-specificity and familiarity: a combined fMRI-meta-analytic study.

ABSTRACT: The familiarity to the subject of any potential stimuli presents one of the major difficulties for the investigation of the self; the separation of effects resulting from familiarity from self-effects being extremely problematic. The aim of this study was thus to investigate the neural distinction between self and familiarity by combining two sets of fMRI data with a meta-analysis. In the first fMRI experiment, regions responding to self/familiarity were investigated using the subject's own name and names of familiar others. These effects were confirmed and extended in a second fMRI experiment using the subject's own name and a stranger's name, as spoken by familiar and unfamiliar voices. Finally, a meta-analysis of self- and familiarity-related studies was conducted. Neural activity in the anterior brain regions, such as the anterior cingulate (ACC) and anterior insula (AI), was found to be specific for self-specific stimuli. In contrast, posterior brain regions, such as the posterior cingulate, were activated by familiar stimuli. Finally, the distinction between anterior and posterior regions for self and familiarity was confirmed by meta-analytic data. This study demonstrates a clear anterior-posterior cortical partition between self-specificity and familiarity.

SUBMITTER: Qin P

PROVIDER: S-EPMC6869961 | biostudies-literature | 2012 Jan

REPOSITORIES: biostudies-literature

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Dissociation between anterior and posterior cortical regions during self-specificity and familiarity: a combined fMRI-meta-analytic study.

Qin Pengmin P Liu Yijun Y Shi Jinfu J Wang Yuzhi Y Duncan Niall N Gong Qiyong Q Weng Xuchu X Northoff Georg G

Human brain mapping 20110309 1

The familiarity to the subject of any potential stimuli presents one of the major difficulties for the investigation of the self; the separation of effects resulting from familiarity from self-effects being extremely problematic. The aim of this study was thus to investigate the neural distinction between self and familiarity by combining two sets of fMRI data with a meta-analysis. In the first fMRI experiment, regions responding to self/familiarity were investigated using the subject's own name ...[more]

PMID: 21391261

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Project description:Functional brain network studies using the Blood Oxygen-Level Dependent (BOLD) signal from functional Magnetic Resonance Imaging (fMRI) are becoming increasingly prevalent in research on the neural basis of human cognition. An important problem in functional brain network analysis is to understand directed functional interactions between brain regions during cognitive performance. This problem has important implications for understanding top-down influences from frontal and parietal control regions to visual occipital cortex in visuospatial attention, the goal motivating the present study. A common approach to measuring directed functional interactions between two brain regions is to first create nodal signals by averaging the BOLD signals of all the voxels in each region, and to then measure directed functional interactions between the nodal signals. Another approach, that avoids averaging, is to measure directed functional interactions between all pairwise combinations of voxels in the two regions. Here we employ an alternative approach that avoids the drawbacks of both averaging and pairwise voxel measures. In this approach, we first use the Least Absolute Shrinkage Selection Operator (LASSO) to pre-select voxels for analysis, then compute a Multivariate Vector AutoRegressive (MVAR) model from the time series of the selected voxels, and finally compute summary Granger Causality (GC) statistics from the model to represent directed interregional interactions. We demonstrate the effectiveness of this approach on both simulated and empirical fMRI data. We also show that averaging regional BOLD activity to create a nodal signal may lead to biased GC estimation of directed interregional interactions. The approach presented here makes it feasible to compute GC between brain regions without the need for averaging. Our results suggest that in the analysis of functional brain networks, careful consideration must be given to the way that network nodes and edges are defined because those definitions may have important implications for the validity of the analysis.

Dataset Information

Dissociation between anterior and posterior cortical regions during self-specificity and familiarity: a combined fMRI-meta-analytic study.

Publications

Dissociation between anterior and posterior cortical regions during self-specificity and familiarity: a combined fMRI-meta-analytic study.

Similar Datasets

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