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Predictable internal brain dynamics in EEG and its relation to conscious states.

Yoo J, Kwon J, Choe Y - Front Neurorobot (2014)

Bottom Line: Our results show that EEG signals from awake or rapid eye movement (REM) sleep states have more predictable dynamics compared to those from slow-wave sleep (SWS).Since awakeness and REM sleep are associated with conscious states and SWS with unconscious or less consciousness states, these results support our hypothesis.The results suggest an intricate relationship among prediction, consciousness, and time, with potential applications to time perception and neurorobotics.

View Article: PubMed Central - PubMed

Affiliation: Department of Computer Science and Engineering, Texas A&M University College Station, TX, USA.

ABSTRACT
Consciousness is a complex and multi-faceted phenomenon defying scientific explanation. Part of the reason why this is the case is due to its subjective nature. In our previous computational experiments, to avoid such a subjective trap, we took a strategy to investigate objective necessary conditions of consciousness. Our basic hypothesis was that predictive internal dynamics serves as such a condition. This is in line with theories of consciousness that treat retention (memory), protention (anticipation), and primary impression as the tripartite temporal structure of consciousness. To test our hypothesis, we analyzed publicly available sleep and awake electroencephalogram (EEG) data. Our results show that EEG signals from awake or rapid eye movement (REM) sleep states have more predictable dynamics compared to those from slow-wave sleep (SWS). Since awakeness and REM sleep are associated with conscious states and SWS with unconscious or less consciousness states, these results support our hypothesis. The results suggest an intricate relationship among prediction, consciousness, and time, with potential applications to time perception and neurorobotics.

No MeSH data available.


Related in: MedlinePlus

Summary of EEG IPI prediction error results (mean and standard deviation). Mean and standard deviation of IPI prediction error are shown for all four subjects, for all three conditions (awake, REM, and SWS). The unit for the y-axis was 10 ms. For all subjects, awake and REM conditions resulted in lower IPI prediction error than SWS, showing that predictive dynamics may be more prominent during conscious states. All differences were significant (t-test, p < 10−6), except for REM vs. AWAKE for subject 4. See text for details. Awake state having higher IPI prediction error than REM state is somewhat unexpected, which we will discuss further in the Discussion section. (A) Subject 1, (B) subject 2, (C) subject 3, (D) subject 4.
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Figure 3: Summary of EEG IPI prediction error results (mean and standard deviation). Mean and standard deviation of IPI prediction error are shown for all four subjects, for all three conditions (awake, REM, and SWS). The unit for the y-axis was 10 ms. For all subjects, awake and REM conditions resulted in lower IPI prediction error than SWS, showing that predictive dynamics may be more prominent during conscious states. All differences were significant (t-test, p < 10−6), except for REM vs. AWAKE for subject 4. See text for details. Awake state having higher IPI prediction error than REM state is somewhat unexpected, which we will discuss further in the Discussion section. (A) Subject 1, (B) subject 2, (C) subject 3, (D) subject 4.

Mentions: The IPI prediction error on novel data (not used during training or validation) are summarized in Figure 3 and the error distributions shown in Figure 4.


Predictable internal brain dynamics in EEG and its relation to conscious states.

Yoo J, Kwon J, Choe Y - Front Neurorobot (2014)

Summary of EEG IPI prediction error results (mean and standard deviation). Mean and standard deviation of IPI prediction error are shown for all four subjects, for all three conditions (awake, REM, and SWS). The unit for the y-axis was 10 ms. For all subjects, awake and REM conditions resulted in lower IPI prediction error than SWS, showing that predictive dynamics may be more prominent during conscious states. All differences were significant (t-test, p < 10−6), except for REM vs. AWAKE for subject 4. See text for details. Awake state having higher IPI prediction error than REM state is somewhat unexpected, which we will discuss further in the Discussion section. (A) Subject 1, (B) subject 2, (C) subject 3, (D) subject 4.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4043151&req=5

Figure 3: Summary of EEG IPI prediction error results (mean and standard deviation). Mean and standard deviation of IPI prediction error are shown for all four subjects, for all three conditions (awake, REM, and SWS). The unit for the y-axis was 10 ms. For all subjects, awake and REM conditions resulted in lower IPI prediction error than SWS, showing that predictive dynamics may be more prominent during conscious states. All differences were significant (t-test, p < 10−6), except for REM vs. AWAKE for subject 4. See text for details. Awake state having higher IPI prediction error than REM state is somewhat unexpected, which we will discuss further in the Discussion section. (A) Subject 1, (B) subject 2, (C) subject 3, (D) subject 4.
Mentions: The IPI prediction error on novel data (not used during training or validation) are summarized in Figure 3 and the error distributions shown in Figure 4.

Bottom Line: Our results show that EEG signals from awake or rapid eye movement (REM) sleep states have more predictable dynamics compared to those from slow-wave sleep (SWS).Since awakeness and REM sleep are associated with conscious states and SWS with unconscious or less consciousness states, these results support our hypothesis.The results suggest an intricate relationship among prediction, consciousness, and time, with potential applications to time perception and neurorobotics.

View Article: PubMed Central - PubMed

Affiliation: Department of Computer Science and Engineering, Texas A&M University College Station, TX, USA.

ABSTRACT
Consciousness is a complex and multi-faceted phenomenon defying scientific explanation. Part of the reason why this is the case is due to its subjective nature. In our previous computational experiments, to avoid such a subjective trap, we took a strategy to investigate objective necessary conditions of consciousness. Our basic hypothesis was that predictive internal dynamics serves as such a condition. This is in line with theories of consciousness that treat retention (memory), protention (anticipation), and primary impression as the tripartite temporal structure of consciousness. To test our hypothesis, we analyzed publicly available sleep and awake electroencephalogram (EEG) data. Our results show that EEG signals from awake or rapid eye movement (REM) sleep states have more predictable dynamics compared to those from slow-wave sleep (SWS). Since awakeness and REM sleep are associated with conscious states and SWS with unconscious or less consciousness states, these results support our hypothesis. The results suggest an intricate relationship among prediction, consciousness, and time, with potential applications to time perception and neurorobotics.

No MeSH data available.


Related in: MedlinePlus