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Being critical of criticality in the brain.

Beggs JM, Timme N - Front Physiol (2012)

Bottom Line: The hypothesis that the electrical activity of neural networks in the brain is critical is potentially important, as many simulations suggest that information processing functions would be optimized at the critical point.This hypothesis, however, is still controversial.Points and counter points are presented in dialog form.

View Article: PubMed Central - PubMed

Affiliation: Department of Physics, Indiana University Bloomington, IN, USA.

ABSTRACT
Relatively recent work has reported that networks of neurons can produce avalanches of activity whose sizes follow a power law distribution. This suggests that these networks may be operating near a critical point, poised between a phase where activity rapidly dies out and a phase where activity is amplified over time. The hypothesis that the electrical activity of neural networks in the brain is critical is potentially important, as many simulations suggest that information processing functions would be optimized at the critical point. This hypothesis, however, is still controversial. Here we will explain the concept of criticality and review the substantial objections to the criticality hypothesis raised by skeptics. Points and counter points are presented in dialog form.

No MeSH data available.


Rescaled avalanche shapes from Figure 8 (Friedman et al., 2012).
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Figure 9: Rescaled avalanche shapes from Figure 8 (Friedman et al., 2012).

Mentions: Critio: Well, if we divide each curve by its duration, then they will be rescaled to all have the same length. Then if we rescale their heights by their duration raised to an exponent, γ from Eq. 2, that is related to the critical exponents α and β that we discussed earlier, then we get a picture that looks like this. [Critio draws Figure 9.]


Being critical of criticality in the brain.

Beggs JM, Timme N - Front Physiol (2012)

Rescaled avalanche shapes from Figure 8 (Friedman et al., 2012).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3369250&req=5

Figure 9: Rescaled avalanche shapes from Figure 8 (Friedman et al., 2012).
Mentions: Critio: Well, if we divide each curve by its duration, then they will be rescaled to all have the same length. Then if we rescale their heights by their duration raised to an exponent, γ from Eq. 2, that is related to the critical exponents α and β that we discussed earlier, then we get a picture that looks like this. [Critio draws Figure 9.]

Bottom Line: The hypothesis that the electrical activity of neural networks in the brain is critical is potentially important, as many simulations suggest that information processing functions would be optimized at the critical point.This hypothesis, however, is still controversial.Points and counter points are presented in dialog form.

View Article: PubMed Central - PubMed

Affiliation: Department of Physics, Indiana University Bloomington, IN, USA.

ABSTRACT
Relatively recent work has reported that networks of neurons can produce avalanches of activity whose sizes follow a power law distribution. This suggests that these networks may be operating near a critical point, poised between a phase where activity rapidly dies out and a phase where activity is amplified over time. The hypothesis that the electrical activity of neural networks in the brain is critical is potentially important, as many simulations suggest that information processing functions would be optimized at the critical point. This hypothesis, however, is still controversial. Here we will explain the concept of criticality and review the substantial objections to the criticality hypothesis raised by skeptics. Points and counter points are presented in dialog form.

No MeSH data available.