Critical brain hypothesis
{{Short description|Hypothesis that states certain biological neuronal networks work near phase transitions}}
In neuroscience, the critical brain hypothesis states that certain biological neuronal networks work near phase transitions.{{cite journal | last1 = Chialvo | first1 = D. R. | year = 2010 | title = Emergent complex neural dynamics | journal = Nature Physics | volume = 6 | issue = 10 | pages = 744–750 | doi = 10.1038/nphys1803 | bibcode = 2010NatPh...6..744C | arxiv = 1010.2530 | s2cid = 17584864 }}{{cite journal | last1=Hesse | first1=Janina | last2=Gross | first2=Thilo | title=Self-organized criticality as a fundamental property of neural systems | journal=Frontiers in Systems Neuroscience | volume=8 | date=2014-09-23 | issn=1662-5137 | pmid=25294989 | pmc=4171833 | doi=10.3389/fnsys.2014.00166 | doi-access=free | page=166}}{{Cite journal|last1=Chialvo|first1=D. R.|last2=Bak|first2=P.|date=1999-06-01|title=Learning from mistakes|journal=Neuroscience|volume=90|issue=4|pages=1137–1148|doi=10.1016/S0306-4522(98)00472-2|arxiv=adap-org/9707006|pmid=10338284|s2cid=1304836 }} Experimental recordings from large groups of neurons have shown bursts of activity, so-called neuronal avalanches, with sizes that follow a power law distribution. These results, and subsequent replication on a number of settings, led to the hypothesis that the collective dynamics of large neuronal networks in the brain operates close to the critical point of a phase transition.{{cite journal | doi=10.3389/fphys.2012.00163 | doi-access=free | title=Being Critical of Criticality in the Brain | year=2012 | last1=Beggs | first1=John M. | last2=Timme | first2=Nicholas | journal=Frontiers in Physiology | volume=3 | page=163 | pmid=22701101 | pmc=3369250 }}{{cite journal |last1=di Santo |first1=Serena |last2=Villegas |first2=Pablo |last3=Burioni |first3=Raffaella |last4=Muñoz |first4=Miguel A. |title=Landau–Ginzburg theory of cortex dynamics: Scale-free avalanches emerge at the edge of synchronization |journal=Proceedings of the National Academy of Sciences |date=13 February 2018 |volume=115 |issue=7 |pages=E1356–E1365 |doi=10.1073/pnas.1712989115|pmid=29378970 |pmc=5816155 |arxiv=1801.10356 |bibcode=2018PNAS..115E1356D |doi-access=free }} According to this hypothesis, the activity of the brain would be continuously transitioning between two phases, one in which activity will rapidly reduce and die, and another where activity will build up and amplify over time. In criticality, the brain capacity for information processing is enhanced,{{cite journal | last1 = Kinouchi | first1 = O. | last2 = Copelli | first2 = M. | year = 2006 | title = Optimal dynamical range of excitable networks at criticality | journal = Nature Physics | volume = 2 | issue = 5 | pages = 348–351 | doi = 10.1038/nphys289 | arxiv = q-bio/0601037 | bibcode = 2006NatPh...2..348K | s2cid = 9650581 }}{{cite journal | doi=10.1098/rsta.2007.2092 | title=The criticality hypothesis: How local cortical networks might optimize information processing | year=2008 | last1=Beggs | first1=John M. | journal=Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences | volume=366 | issue=1864 | pages=329–343 | pmid=17673410 | bibcode=2008RSPTA.366..329B | s2cid=9790287 }}{{cite journal | last1 = Shew | first1 = W. L. | last2 = Yang | first2 = H. | last3 = Petermann | first3 = T. | last4 = Roy | first4 = R. | last5 = Plenz | first5 = D. | year = 2009 | title = Neuronal avalanches imply maximum dynamic range in cortical networks at criticality | journal = The Journal of Neuroscience | volume = 29 | issue = 49 | pages = 15595–15600 | pmc=3862241 | doi = 10.1523/jneurosci.3864-09.2009 | pmid = 20007483 | doi-access = free }} so subcritical, critical and slightly supercritical branching process of thoughts could describe how human and animal minds function.
History
Discussion on the brain's criticality have been done since 1950, with the paper on the imitation game for a Turing test.{{cite journal | last1 = Turing | first1 = A. M. | year = 1950 | title = Computing machinery and intelligence | journal = Mind | volume = 59 | issue = 236 | pages = 433–460 | doi = 10.1093/mind/lix.236.433 }} In 1995, Andreas V. Herz and John Hopfield noted that self-organized criticality (SOC) models for earthquakes were mathematically equivalent to networks of integrate-and-fire neurons, and speculated that perhaps SOC would occur in the brain.{{cite journal | last1 = Herz | first1 = A. V. | last2 = Hopfield | first2 = J. J. | year = 1995 | title = Earthquake cycles and neural reverberations: collective oscillations in systems with pulse-coupled threshold elements | journal = Physical Review Letters | volume = 75 | issue = 6 | pages = 1222–1225 | doi = 10.1103/physrevlett.75.1222 | pmid = 10060236 | bibcode = 1995PhRvL..75.1222H }} Simultaneously Dimitris Stassinopoulos and Per Bak proposed a simple neural network model working at criticality{{Cite journal|last1=Stassinopoulos|first1=Dimitris|last2=Bak|first2=Per|date=1995-05-01|title=Democratic reinforcement: A principle for brain function|journal=Physical Review E|volume=51|issue=5|pages=5033–5039|doi=10.1103/PhysRevE.51.5033|pmid=9963215 |bibcode=1995PhRvE..51.5033S}} which was expanded later by Dante R. Chialvo and Bak.{{Cite journal|last1=Chialvo|first1=D.R.|last2=Bak|first2=P.|title=Learning from mistakes|journal=Neuroscience|volume=90|issue=4|pages=1137–1148|doi=10.1016/s0306-4522(98)00472-2|arxiv=adap-org/9707006|year=1999|pmid=10338284|s2cid=1304836 }} In 2003, the hypothesis found experimental support by John M. Beggs and Dietmar Plenz.{{cite journal | last1 = Beggs | first1 = J. M. | last2 = Plenz | first2 = D. | year = 2003 | title = Neuronal avalanches in neocortical circuits | journal = The Journal of Neuroscience | volume = 23 | issue = 35 | pages = 11167–11177 | doi = 10.1523/jneurosci.23-35-11167.2003 | doi-access = free | pmid = 14657176 | pmc = 6741045 }} The critical brain hypothesis is not a consensus among the scientific community. However, there exists more and more support for the hypothesis as more experimenters take to verifying the claims that it makes, particularly in vivo in rats with chronic electrophysiological recordings{{cite journal | last1=Ma | first1=Zhengyu | last2=Turrigiano | first2=Gina G. | last3=Wessel | first3=Ralf | last4=Hengen | first4=Keith B. | title=Cortical Circuit Dynamics Are Homeostatically Tuned to Criticality In Vivo | journal=Neuron | publisher=Elsevier BV | volume=104 | issue=4 | year=2019 | issn=0896-6273 | doi=10.1016/j.neuron.2019.08.031 | pages=655–664.e4 |pmid=31601510| pmc=6934140 }} and mice with high-density electrophysiological recordings.{{cite report | last=Smith | first=Wesley C. | title=In vivo Quantification of Neural Criticality and Complexity in Mouse Cortex and Striatum in a Model of Cocaine Abstinence | date=2022-08-03 | doi=10.1101/2022.08.02.501652 | page=}}