Cognitive Regime Shift I - When the Brain Breaks/Neuronal Avalanches
July 23, 2018
2:20 pm - 3:10 pm
Dietmar Plenz (NIH)
A recent special issue in Frontiers of Systems Neuroscience on criticality and healthy brain states experienced ~70,000 views and 25,000 downloads within the 3 years it was published (<a href="https://www.frontiersin.org/research-topics/1663/criticality-as-a-signature-of-healthy-neural-systems-multi-scale-experimental-and-computational-stud#impact">https://www.frontiersin.org/research-topics/1663/criticality-as-a-signature-of-healthy-neural-systems-multi-scale-experimental-and-computational-stud#impact</a>). As we start to understand the order in ongoing fluctuations of normal healthy brain activity, the promise is that it might get easier to identify early deviations towards pathological brain states. Afew highlights from research groups including ours over the last years that might relevant to the work shop:
- Neuronal avalanches and critical dynamics
- are only found in the awake state and disappear under anesthesia (rodent and humans: (1-4)
- Capture the resting state in nonhuman primates, human MRI, ECoG (3, 5, 6).
- Describe response variability in sensory processing and motor behavior (7).
- Here is a short excerpt MINE of a recent summary on avalanches on criticality optimizing numerous aspects of information procesing in the brain:
“Decades ago, it was suggested that critical dynamics optimize information transfer in gene-regulation networks(8-11). Since then, the criticality hypothesis(12-21) and alternative models for scale-invariant neuronal organization (e.g. refs.(22-26)} have gained much ground in the field of neuroscience. The functional benefits of critical dynamics for brain function include maximization of mutual information between stimulus input and output(27-31), information capacity (i.e. the number of possible internal states a network can establish)(32-34), stimulus discrimination(35, 36), and the ability of neurons to flexibly change synchronization while maintaining an overall robust degree of phase-locking(37-40), all of which are highly desirable aspects of information processing.
- The group might be particularly interested in recent papers from our group and Matias Palva’s group on human disease states and/or behavioral performance demonstrating criticality and deviation from criticality in patients taking anti-epileptic drugs (41, 42), in sleep-deprived normal subjects (43, 44), avalanche scaling exponents in the human brain that correlate with behavioral performance (45, 46) as well as deviations from criticality in animal models of schizophrenia (47).
1. Scott G, et al. (2014) Voltage imaging of waking mouse cortex reveals emergence of critical neuronal dynamics. J. Neurosci. 34(50):16611 - 16620.
2. Bellay T, Klaus A, Seshadri S, & Plenz D (2015) Irregular spiking of pyramidal neurons organizes as scale-invariant neuronal avalanches in the awake state. eLife 4: e07224.
3. Solovey G, et al. (2015) Loss of Consciousness Is Associated with Stabilization of Cortical Activity. J. Neurosci. 35(30):10866-10877.
4. Tagliazucchi E, et al. (2016) Large-scale signatures of unconsciousness are consistent with a departure from critical dynamics. Journal of The Royal Society Interface 13(114).
5. Petermann T, et al. (2009) Spontaneous cortical activity in awake monkeys composed of neuronal avalanches. Proc. Natl. Acad. Sci. U. S. A. 106(37):15921-15926.
6. Tagliazucchi E, Balenzuela P, Fraiman D, & Chialvo DR (2012) Criticality in large-scale brain fMRI dynamics unveiled by a novel point process analysis. Front. Physiol. 3(15).
7. Yu S, et al. (2017) Maintained avalanche dynamics during task-induced changes of neuronal activity in nonhuman primates. eLife 6:e27119.
8. Nykter M, et al. (2008) Critical networks exhibit maximal information diversity in structure-dynamics relationships. Phys. Rev. Lett. 100(5):058702.
9. Rämö P, Kauffman S, Kesselia J, & Yli-Harja O (2007) Measures for information propagation in Boolean networks. Physica D 227:100-104.
10. Sole RV, Manrubia SC, Benton M, Kauffman S, & Bak P (1999) Criticality and scaling in evolutionary ecology. Trends Ecol. Evol. 14(4):156-160.
11. Kauffman SA (1969) Metabolic stability and epigenesis in randomly constructed genetic nets. J. Theor. Biol. 22(3):437-467.
12. Chialvo DR (2010) Emergent complex neural dynamics. Nat. Phys. 6:744-750.
13. Mora T & Bialek W (2011) Are biological systems poised at criticality? JSP 144(2):268-302.
14. Plenz D (2012) Neuronal avalanches and coherence potentials. The European Physical Journal Special Topics 205(1):259-301.
15. Beggs JM & Timme N (2012) Being Critical of Criticality in the Brain. Frontiers in Physiology 3:163.
16. Marković D & Gros C (2014) Power laws and self-organized criticality in theory and nature. PhR 536(2):33.
17. Plenz D & Niebur E (2014) Criticality in Neural Systems (Wiley-VCH, Berlin) p 566.
18. Hesse J & Gross T (2014) Self-organized criticality as a fundamental property of neural systems. Front. Syst. Neurosci. 8.
19. Cocchi L, Gollo LL, Zalesky A, & Breakspear M (2017) Criticality in the brain: A synthesis of neurobiology, models and cognition. Prog. Neurobiol.
20. Muñoz MA (2017) Colloquium: Criticality and dynamical scaling in living systems. Review of Modern Physics (in press).
21. Bettinger JS (2017) Comparative approximations of criticality in a neural and quantum regime. Prog. Biophys. Mol. Biol. 131:445-462.
22. Ioffe ML & Berry II MJ (2017) The structured ‘low temperature’phase of the retinal population code. PLoS Comput. Biol. 13(10):e1005792.
23. Aitchison L, Corradi N, & Latham PE (2016) Zipf’s Law Arises Naturally When There Are Underlying, Unobserved Variables. PLoS Comput. Biol. 12(12):e1005110.
24. Touboul J & Destexhe A (2017) Power-law statistics and universal scaling in the absence of criticality. Phys. Rev. E. 95(012413).
25. Martinello M, et al. (2017) Neutral Theory and Scale-Free Neural Dynamics. Phys. Rev. X 7(4):041071.
26. Williams-García RV, Moore M, Beggs JM, & Ortiz G (2014) Quasicritical brain dynamics on a nonequilibrium Widom line. Phys. Rev. E 90(6):062714.
27. Kinouchi O & Copelli M (2006) Optimal dynamical range of excitable networks at criticality. Nat. Phys. 2 348-351.
28. Shew WL, Yang H, Petermann T, Roy R, & Plenz D (2009) Neuronal avalanches imply maximum dynamic range in cortical networks at criticality. J. Neurosci. 29(49):15595-15600.
29. Shew WL & Plenz D (2013) The functional benefits of criticality in the cortex. Neuroscientist. 19(1):88-100.
30. Gautam H, Hoang TT, McClanahan K, Grady SK, & Shew WL (2015) Maximizing sensory dynamic range by tuning the cortical state to criticality. PLoS Comput. Biol. 11(12):e1004576.
31. Bortolotto GS, Girardi-Schappo M, Gonsalves JJ, Pinto LT, & Tragtenberg MHR (2016) Information processing occurs via critical avalanches in a model of the primary visual cortex. Journal of Physics: Conference Series 686(1):012008.
32. Tkačik G, et al. (2015) Thermodynamics and signatures of criticality in a network of neurons. Proc. Natl. Acad. Sci. U. S. A.:201514188.
33. Shew WL, Yang H, Yu S, Roy R, & Plenz D (2011) Information capacity is maximized in balanced cortical networks with neuronal avalanches. J. Neurosci. 5:55-63.
34. Haldeman C & Beggs JM (2005) Critical branching captures activity in living neural networks and maximizes the number of metastable States. Phys Rev.Lett 94(5):058101.
35. Clawson WP, Wright NC, Wessel R, & Shew WL (2017) Adaptation towards scale-free dynamics improves cortical stimulus discrimination at the cost of reduced detection. PLoS Comput. Biol. 13(5):e1005574.
36. Shriki O & Yellin D (2016) Optimal Information Representation and Criticality in an Adaptive Sensory Recurrent Neuronal Network. PLoS Comput. Biol. 12(2):e1004698.
37. Kelso JA, Dumas G, & Tognoli E (2013) Outline of a general theory of behavior and brain coordination. Neural networks : the official journal of the International Neural Network Society 37:120-131.
38. Yang H, Shew WL, Roy R, & Plenz D (2012) Maximal variability of phase synchrony in cortical networks with neuronal avalanches. J. Neurosci. 32(3):1061-1072.
39. Kirst C, Modes CD, & Magnasco MO (2017) Shifting attention to dynamics: Self-reconfiguration of neural networks. Current Opinion in Systems Biology 3:132-140.
40. Jantzen KJ, Steinberg FL, & Kelso JA (2009) Coordination dynamics of large-scale neural circuitry underlying rhythmic sensorimotor behavior. J. Cogn. Neurosci. 21(12):2420-2433.
41. Meisel C, Plenz D, Schulze-Bonhage A, & Reichmann H (2016) Quantifying antiepileptic drug effects using intrinsic excitability measures. Epilepsia 57(11):e210-e215.
42. Meisel C, et al. (2015) Intrinsic excitability measures track antiepileptic drug action and uncover increasing/decreasing excitability over the wake/sleep cycle. Proc. Natl. Acad. Sci. U. S. A. 112(47):14694-14699.
43. Meisel C, Bailey K, Achermann P, & Plenz D (2017) Decline of long-range temporal correlations in the human brain during sustained wakefulness. Scientific Reports 7(1):11825.
44. Meisel C, Olbrich E, Shriki O, & Achermann P (2013) Fading signatures of critical brain dynamics during sustained wakefulness in humans. J. Neurosci. 33(44):17363-17372.
45. Zhigalov A, Kaplan A, & Palva JM (2016) Modulation of critical brain dynamics using closed-loop neurofeedback stimulation. Clin. Neurophysiol. 127(8):2882-2889.
46. Palva JM, et al. (2013) Neuronal long-range temporal correlations and avalanche dynamics are correlated with behavioral scaling laws. Proc. Natl. Acad. Sci. U. S. A. 110(9):3585-3590.
47. Seshadri S, Klaus A, Winkowski DE, Kanold PO, & Plenz D (2018) Altered avalanche dynamics in a developmental NMDAR hypofunction model of cognitive impairment. Translational Psychiatry 8(1):3.
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