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Partial correlation coefficients approximate the real intrasubject correlation pattern in the analysis of interregional relations of cerebral metabolic activity.

Barry Horwitz, С. И. Рапопорт

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Abstract

Correlation coefficients between pairs of regional glucose metabolic rates have been used to assess patterns of functional associations among brain regions in humans and animals. Partial correlation coefficients (partialing out the global metabolic rate) or correlations between reference ratios (regional to global metabolic rate) have been used to remove the distorting influence of systematic intersubject differences in glucose utilization. Suggesting that partial correlations may not preserve the true (but unknown) intrasubject correlation structure within the brain, others have used a theoretical example to show how an artifactually large negative partial correlation coefficient might arise. Here, we show that such an example is highly unlikely when applied to resting cerebral metabolism, and can be identified in experimental data by testing for a bimodal distribution of partial correlation values. We then show that partial correlations or reference ratio correlations of experimental resting metabolic rates give values which closely approximate the intrasubject correlation coefficients.

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Correlation coefficients between pairs of regional glucose metabolic rates have been used to assess patterns of functional associations among brain regions in humans and animals. Partial correlation coefficients (partialing out the global metabolic rate) or correlations between reference ratios (regional to global metabolic rate) have been used to remove the distorting influence of systematic intersubject differences in glucose utilization. Suggesting that partial correlations may not preserve the true (but unknown) intrasubject correlation structure within the brain, others have used a theoretical example to show how an artifactually large negative partial correlation coefficient might arise. Here, we show that such an example is highly unlikely when applied to resting cerebral metabolism, and can be identified in experimental data by testing for a bimodal distribution of partial correlation values. We then show that partial correlations or reference ratio correlations of experimental resting metabolic rates give values which closely approximate the intrasubject correlation coefficients.

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Available abstract

Correlation coefficients between pairs of regional glucose metabolic rates have been used to assess patterns of functional associations among brain regions in humans and animals. Partial correlation coefficients (partialing out the global metabolic rate) or correlations between reference ratios (regional to global metabolic rate) have been used to remove the distorting influence of systematic intersubject differences in glucose utilization. Suggesting that partial correlations may not preserve the true (but unknown) intrasubject correlation structure within the brain, others have used a theoretical example to show how an artifactually large negative partial correlation coefficient might arise. Here, we show that such an example is highly unlikely when applied to resting cerebral metabolism, and can be identified in experimental data by testing for a bimodal distribution of partial correlation values. We then show that partial correlations or reference ratio correlations of experimental resting metabolic rates give values which closely approximate the intrasubject correlation coefficients.

Key concepts: Partial correlation, Correlation, Correlation coefficient, Metabolic rate, Mathematics, Negative correlation, Positive correlation, Statistics

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Partial correlation coefficients approximate the real intrasubject correlation pattern in the analysis of interregional relations of cerebral metabolic activity. — Research Paper | ScholarLens