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Factoring the brain signatures of anesthesia concentration and level of arousal across individuals.

Barttfeld P, Bekinschtein TA, Salles A, Stamatakis EA, Adapa R, Menon DK, Sigman M - Neuroimage Clin (2015)

Bottom Line: Combining resting-state functional magnetic resonance imaging (fMRI) connectivity and behavioral analysis during sedation, we factored out general effects of the anesthetic drug propofol and a specific index of conscious report, participants' level of responsiveness.The factorial analysis shows that increasing concentration of propofol in blood specifically decreases the connectivity strength of fronto-parietal cortical loops.In contrast, loss of responsiveness is indexed by a functional disconnection between the thalamus and the frontal cortex, balanced by an increase in connectivity strength of the thalamus to the occipital and temporal regions of the cortex.

View Article: PubMed Central - PubMed

Affiliation: Universidad Torcuato di Tella, Almirante Juan Saenz Valiente 1010, Buenos Aires C1428BIJ, Argentina ; Cognitive Neuroimaging Unit, CEA DSV/I2BM, INSERM, Université Paris-Sud, Université Paris-Saclay, NeuroSpin center, 91191 Gif/Yvette, France.

ABSTRACT
Combining resting-state functional magnetic resonance imaging (fMRI) connectivity and behavioral analysis during sedation, we factored out general effects of the anesthetic drug propofol and a specific index of conscious report, participants' level of responsiveness. The factorial analysis shows that increasing concentration of propofol in blood specifically decreases the connectivity strength of fronto-parietal cortical loops. In contrast, loss of responsiveness is indexed by a functional disconnection between the thalamus and the frontal cortex, balanced by an increase in connectivity strength of the thalamus to the occipital and temporal regions of the cortex.

No MeSH data available.


MSE maps as a function of β values from x–x, for increasing covariation between regressors. Last panel shows MSE map for the actual data (white dot marks the β value pair calculated for the actual data).
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f0015: MSE maps as a function of β values from x–x, for increasing covariation between regressors. Last panel shows MSE map for the actual data (white dot marks the β value pair calculated for the actual data).

Mentions: We also explored the robustness of our results taking into account random perturbations, through the analysis of the landscape of the mean squared error (MSE) of the regression for a broad range of β values. We found that when covariance between regressors is close to zero, a clear and single minimum exists in the β space (Fig. 3). As the covariance between regressors becomes larger, the valley surrounding this minimum becomes less steep, shifting towards a range of values along the identity line at very high covariance, a case in which many combinations of (interchangeable) β values yield an equally low MSE value (Fig. 3). Fig. 3, lower row and last column shows the β value landscape obtained for the real data whose β values were used to construct the artificial data (the white dot marks the actual β value we empirically obtained, that is, the β value obtained for the non-simulated data). The MSE landscape is quite similar to those with an intermediate r value, in agreement with the calculated value of correlation of 0.33 between our experimental regressors. In this situation a multivariate regression can discriminate between alternative assignments of β values in the presence of a single and very clear minimum (Tabachnick and Fidell, 2013).


Factoring the brain signatures of anesthesia concentration and level of arousal across individuals.

Barttfeld P, Bekinschtein TA, Salles A, Stamatakis EA, Adapa R, Menon DK, Sigman M - Neuroimage Clin (2015)

MSE maps as a function of β values from x–x, for increasing covariation between regressors. Last panel shows MSE map for the actual data (white dot marks the β value pair calculated for the actual data).
© Copyright Policy - CC BY-NC-ND
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4588413&req=5

f0015: MSE maps as a function of β values from x–x, for increasing covariation between regressors. Last panel shows MSE map for the actual data (white dot marks the β value pair calculated for the actual data).
Mentions: We also explored the robustness of our results taking into account random perturbations, through the analysis of the landscape of the mean squared error (MSE) of the regression for a broad range of β values. We found that when covariance between regressors is close to zero, a clear and single minimum exists in the β space (Fig. 3). As the covariance between regressors becomes larger, the valley surrounding this minimum becomes less steep, shifting towards a range of values along the identity line at very high covariance, a case in which many combinations of (interchangeable) β values yield an equally low MSE value (Fig. 3). Fig. 3, lower row and last column shows the β value landscape obtained for the real data whose β values were used to construct the artificial data (the white dot marks the actual β value we empirically obtained, that is, the β value obtained for the non-simulated data). The MSE landscape is quite similar to those with an intermediate r value, in agreement with the calculated value of correlation of 0.33 between our experimental regressors. In this situation a multivariate regression can discriminate between alternative assignments of β values in the presence of a single and very clear minimum (Tabachnick and Fidell, 2013).

Bottom Line: Combining resting-state functional magnetic resonance imaging (fMRI) connectivity and behavioral analysis during sedation, we factored out general effects of the anesthetic drug propofol and a specific index of conscious report, participants' level of responsiveness.The factorial analysis shows that increasing concentration of propofol in blood specifically decreases the connectivity strength of fronto-parietal cortical loops.In contrast, loss of responsiveness is indexed by a functional disconnection between the thalamus and the frontal cortex, balanced by an increase in connectivity strength of the thalamus to the occipital and temporal regions of the cortex.

View Article: PubMed Central - PubMed

Affiliation: Universidad Torcuato di Tella, Almirante Juan Saenz Valiente 1010, Buenos Aires C1428BIJ, Argentina ; Cognitive Neuroimaging Unit, CEA DSV/I2BM, INSERM, Université Paris-Sud, Université Paris-Saclay, NeuroSpin center, 91191 Gif/Yvette, France.

ABSTRACT
Combining resting-state functional magnetic resonance imaging (fMRI) connectivity and behavioral analysis during sedation, we factored out general effects of the anesthetic drug propofol and a specific index of conscious report, participants' level of responsiveness. The factorial analysis shows that increasing concentration of propofol in blood specifically decreases the connectivity strength of fronto-parietal cortical loops. In contrast, loss of responsiveness is indexed by a functional disconnection between the thalamus and the frontal cortex, balanced by an increase in connectivity strength of the thalamus to the occipital and temporal regions of the cortex.

No MeSH data available.