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Increased Brain Signal Variability Accompanies Lower Behavioral Variability in Development

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  • Anthony Randal McIntosh
  • Natasa Kovacevic
  • Roxane J Itier

Abstract

As the brain matures, its responses become optimized. Behavioral measures show this through improved accuracy and decreased trial-to-trial variability. The question remains whether the supporting brain dynamics show a similar decrease in variability. We examined the relation between variability in single trial evoked electrical activity of the brain (measured with EEG) and performance of a face memory task in children (8–15 y) and young adults (20–33 y). Behaviorally, children showed slower, more variable response times (RT), and less accurate recognition than adults. However, brain signal variability increased with age, and showed strong negative correlations with intrasubject RT variability and positive correlations with accuracy. Thus, maturation appears to lead to a brain with greater functional variability, which is indicative of enhanced neural complexity. This variability may reflect a broader repertoire of metastable brain states and more fluid transitions among them that enable optimum responses. Our results suggest that the moment-to-moment variability in brain activity may be a critical index of the cognitive capacity of the brain.Author Summary: Intuitive notions of brain–behavior relationships would suggest that because children show more variability in behavior, their brains should also be more variable. We demonstrate that this is not the case. In measuring brain signal variability with EEG and behavior in a simple face recognition task, we found that brain signal variability increases in children from 8–15 y and is even higher in young adults. Importantly, we show that this increased brain variability correlates with reduced behavioral variability and more accurate performance. A brain that has more variability also has greater complexity and a greater capacity for information processing. The implication of our findings is that variability in brain signals, or what some would call noise, is actually a critical feature of brain function. For the brain to operate at an optimal level, a certain amount of internal noise is necessary. In a certain way it could be stated that a noisy brain is a healthy brain.

Suggested Citation

  • Anthony Randal McIntosh & Natasa Kovacevic & Roxane J Itier, 2008. "Increased Brain Signal Variability Accompanies Lower Behavioral Variability in Development," PLOS Computational Biology, Public Library of Science, vol. 4(7), pages 1-9, July.
  • Handle: RePEc:plo:pcbi00:1000106
    DOI: 10.1371/journal.pcbi.1000106
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    1. József Fiser & Chiayu Chiu & Michael Weliky, 2004. "Small modulation of ongoing cortical dynamics by sensory input during natural vision," Nature, Nature, vol. 431(7008), pages 573-578, September.
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    1. Macauley Smith Breault & Pierre Sacré & Zachary B. Fitzgerald & John T. Gale & Kathleen E. Cullen & Jorge A. González-Martínez & Sridevi V. Sarma, 2023. "Internal states as a source of subject-dependent movement variability are represented by large-scale brain networks," Nature Communications, Nature, vol. 14(1), pages 1-20, December.
    2. Jessie M H Szostakiwskyj & Stephanie E Willatt & Filomeno Cortese & Andrea B Protzner, 2017. "The modulation of EEG variability between internally- and externally-driven cognitive states varies with maturation and task performance," PLOS ONE, Public Library of Science, vol. 12(7), pages 1-27, July.
    3. Martínez, J.H. & Ariza, P. & Zanin, M. & Papo, D. & Maestú, F. & Pastor, J.M. & Bajo, R. & Boccaletti, S. & Buldú, J.M., 2015. "Anomalous consistency in Mild Cognitive Impairment: A complex networks approach," Chaos, Solitons & Fractals, Elsevier, vol. 70(C), pages 144-155.
    4. Biyu J He & John M Zempel, 2013. "Average Is Optimal: An Inverted-U Relationship between Trial-to-Trial Brain Activity and Behavioral Performance," PLOS Computational Biology, Public Library of Science, vol. 9(11), pages 1-14, November.
    5. Mazen El-Baba & Daniel J Lewis & Zhuo Fang & Adrian M Owen & Stuart M Fogel & J Bruce Morton, 2019. "Functional connectivity dynamics slow with descent from wakefulness to sleep," PLOS ONE, Public Library of Science, vol. 14(12), pages 1-13, December.
    6. Yoshiki Kaneoke & Tomohiro Donishi & Jun Iwatani & Satoshi Ukai & Kazuhiro Shinosaki & Masaki Terada, 2012. "Variance and Autocorrelation of the Spontaneous Slow Brain Activity," PLOS ONE, Public Library of Science, vol. 7(5), pages 1-10, May.
    7. David Florentino Montez & Finnegan J Calabro & Beatriz Luna, 2019. "Working memory improves developmentally as neural processes stabilize," PLOS ONE, Public Library of Science, vol. 14(3), pages 1-15, March.

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