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Impaired consciousness is linked to changes in effective connectivity of the posterior cingulate cortex within the default mode network.

Crone JS, Schurz M, Höller Y, Bergmann J, Monti M, Schmid E, Trinka E, Kronbichler M - Neuroimage (2015)

Bottom Line: The intrinsic connectivity of the default mode network has been associated with the level of consciousness in patients with severe brain injury.To better understand what aspect of this intrinsic architecture is linked to consciousness, we applied spectral dynamic causal modeling to assess effective connectivity within the default mode network in patients with disorders of consciousness.The resulting regions were then included as nodes in a spectral dynamic causal modeling analysis in order to assess how the causal interactions across these regions as well as the characteristics of neuronal fluctuations change with the level of consciousness.

View Article: PubMed Central - PubMed

Affiliation: Neuroscience Institute & Centre for Cognitive Neuroscience, Christian Doppler Klinik, Paracelsus Medical University, Salzburg, Austria; Centre for Cognitive Neuroscience & Department of Psychology, University of Salzburg, Salzburg, Austria; Department of Neurology, Christian Doppler Klinik, Paracelsus Medical University, Salzburg, Austria; Department of Psychology, University of CA Los Angeles, USA. Electronic address: j.crone@neurocognition.org.

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Results of the post-hoc model selection procedure.The two columns represent the log-posterior and model posterior probabilities of all evaluated models examined for healthy controls (A), patients in minimally conscious state (B), and patients in vegetative state (C). The full model is the winning model in each group with a posterior probability of almost 1.
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f0010: Results of the post-hoc model selection procedure.The two columns represent the log-posterior and model posterior probabilities of all evaluated models examined for healthy controls (A), patients in minimally conscious state (B), and patients in vegetative state (C). The full model is the winning model in each group with a posterior probability of almost 1.

Mentions: Post-hoc model selection compared the evidence of all investigated models for each group. In all three groups, the procedure revealed the fully connected model as the ‘winning’ model with a probability of almost 1 (see Fig. 2). The fully connected model has 16 free parameters describing the intrinsic connections between nodes and the recurrent intrinsic connections within nodes, respectively. In Fig. 2, the profile of model evidences are shown with the posterior probability for each model. In all three groups, the full model (model nr. 256) has a probability of almost 1 and a log-probability of almost 0. The next best model (model nr. 128) has a very low probability with almost 0 for all three groups and a log-probability of − 43.6 for the control group, − 36.2 for the MCS group, and − 57.4 for the VS/UWS group. To estimate the significance of this result, the Bayes factor was calculated by dividing the probability of the ‘winning’ model (almost 1) by the probability of the second most probable model (almost 0) suggesting very strong evidence for the winning model for each group since a Bayes factor of 3:1 is still considered as positive evidence (Kass and Raftery, 1995).


Impaired consciousness is linked to changes in effective connectivity of the posterior cingulate cortex within the default mode network.

Crone JS, Schurz M, Höller Y, Bergmann J, Monti M, Schmid E, Trinka E, Kronbichler M - Neuroimage (2015)

Results of the post-hoc model selection procedure.The two columns represent the log-posterior and model posterior probabilities of all evaluated models examined for healthy controls (A), patients in minimally conscious state (B), and patients in vegetative state (C). The full model is the winning model in each group with a posterior probability of almost 1.
© Copyright Policy - CC BY
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4389831&req=5

f0010: Results of the post-hoc model selection procedure.The two columns represent the log-posterior and model posterior probabilities of all evaluated models examined for healthy controls (A), patients in minimally conscious state (B), and patients in vegetative state (C). The full model is the winning model in each group with a posterior probability of almost 1.
Mentions: Post-hoc model selection compared the evidence of all investigated models for each group. In all three groups, the procedure revealed the fully connected model as the ‘winning’ model with a probability of almost 1 (see Fig. 2). The fully connected model has 16 free parameters describing the intrinsic connections between nodes and the recurrent intrinsic connections within nodes, respectively. In Fig. 2, the profile of model evidences are shown with the posterior probability for each model. In all three groups, the full model (model nr. 256) has a probability of almost 1 and a log-probability of almost 0. The next best model (model nr. 128) has a very low probability with almost 0 for all three groups and a log-probability of − 43.6 for the control group, − 36.2 for the MCS group, and − 57.4 for the VS/UWS group. To estimate the significance of this result, the Bayes factor was calculated by dividing the probability of the ‘winning’ model (almost 1) by the probability of the second most probable model (almost 0) suggesting very strong evidence for the winning model for each group since a Bayes factor of 3:1 is still considered as positive evidence (Kass and Raftery, 1995).

Bottom Line: The intrinsic connectivity of the default mode network has been associated with the level of consciousness in patients with severe brain injury.To better understand what aspect of this intrinsic architecture is linked to consciousness, we applied spectral dynamic causal modeling to assess effective connectivity within the default mode network in patients with disorders of consciousness.The resulting regions were then included as nodes in a spectral dynamic causal modeling analysis in order to assess how the causal interactions across these regions as well as the characteristics of neuronal fluctuations change with the level of consciousness.

View Article: PubMed Central - PubMed

Affiliation: Neuroscience Institute & Centre for Cognitive Neuroscience, Christian Doppler Klinik, Paracelsus Medical University, Salzburg, Austria; Centre for Cognitive Neuroscience & Department of Psychology, University of Salzburg, Salzburg, Austria; Department of Neurology, Christian Doppler Klinik, Paracelsus Medical University, Salzburg, Austria; Department of Psychology, University of CA Los Angeles, USA. Electronic address: j.crone@neurocognition.org.

Show MeSH
Related in: MedlinePlus