\n<\/p>\n
Does string theory\u2014the controversial \u201ctheory of everything\u201d from physics\u2014tell us anything about consciousness and the human brain?<\/p>\n
Outside of the theory itself being devised by conscious humans using their brains, there\u2019s scant reason to think so. In a nutshell, string theory is a sprawling realm of theoretical physics that assumes that tiny vibrating strings are the fundamental basis of reality. If valid, it offers ways for unifying the quantum mechanics that govern the universe on small scales with the gravitational force that shapes the cosmos at larger scales. But the proposed strings are so unimaginably minuscule, and their associated math is so difficult and diverse, that the theory is widely considered to be experimentally unverifiable. Consciousness, meanwhile, is a notoriously slippery and ill-defined thing, but it generally seems to be an emergent property of biology, such as assemblages of neurons within our brains.<\/p>\n
No meaningful overlap exists between these vastly disparate domains. Or does it? A new paper, published last week in Nature, posits that some of the arcane math of string theory actually helps explain the wiring of a brain\u2019s neurons\u2014as well as the branching of other \u201cphysical networks\u201d such as tree limbs, blood vessels and anthills. \u201cThe work,\u201d trumpets one institutional press release, \u201crepresents the first time string theory … has successfully described real biological structures.\u201d<\/p>\n
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Senior author Albert-L\u00e1szl\u00f3 Barab\u00e1si, a distinguished professor and network scientist at Northeastern University, emphasizes that the paper isn\u2019t claiming any profound, direct relationship between string theory and neuroscience. Rather it\u2019s showing how mathematical techniques that have been developed in string theory can be used to better describe how physical networks organize themselves. But even so, using string theory\u2019s math to understand neural wiring would be a surprisingly practical feat, given that the theory is so tenuously tethered to physical reality that skeptical physicists have called it \u201cnot even wrong.\u201d<\/p>\n
The potential linkage, Barab\u00e1si says, springs from the fact that \u201cphysical networks are physically costly and thus try to optimize themselves,\u201d even if we don\u2019t yet know what exactly they optimize. The simplest approach would be a \u201cwiring diagram\u201d following the shortest routes between any two nodes to minimize length\u2014but detailed three-dimensional scans and maps of physical networks have revealed more complex branching geometries and connections that show that some different optimization must be occurring. So instead Barab\u00e1si and his team sought to explain how the structure of physical networks optimizes for minimal surface area rather than other factors such as length or volume.<\/p>\n
\u201cFor many of these networks, like the vascular system that carries blood or the neurons that use ion channels to pump out neurotransmitters, you\u2019re really talking about a tube, and the greatest cost is to build the surface,\u201d he says. \u201cBut modeling surface minimization is a hell of a mathematical problem because you need to create locally smooth surfaces that patch into each other in a continuous way.\u201d<\/p>\n
Barab\u00e1si\u2019s former postdoc and the study\u2019s first author Xiangyi Meng, now an assistant professor at Rensselaer Polytechnic Institute, realized that the seemingly intractable calculation was essentially identical to one for which string theorists had already developed sophisticated tools.<\/p>\n
\u201cWhile the mathematics of minimal surfaces has deep historical roots, our work relies on a specific advancement that classical geometry does not offer,\u201d Meng says\u2014namely a subtype of string theory called \u201ccovariant closed string field theory,\u201d which was developed by Massachusetts Institute of Technology physicist Barton Zwiebach and others in the 1980s.<\/p>\n
Covariant closed string field theory allows physicists to compute the smoothest, most efficient interactions\u2014akin to minimal surfaces\u2014between certain types of strings by treating them as vertices (corners) and edges; this approach is important for string-theory-based attempts to unify gravity and quantum mechanics. In the case of physical networks, Meng says, it offers a way to represent their growth as a series of sleevelike surfaces that are smoothly sewn together. \u201cCrucially, classical minimization tends to collapse sleevelike surfaces into trivial wires,\u201d he says. \u201cZwiebach\u2019s formulation prevents this, maintaining a finite thickness for every link. This fundamental insight is what allows us to model the three-dimensional reality of physical networks, such as of neurons or veins, which must retain volume to function.\u201d<\/p>\n
The team then tested its approach against high-resolution 3D scans of physical networks, including those of neurons, blood vessels, tree branches and corals. In each case, they found that the string theory model produced a closer match than simpler classical predictions. In particular, the team\u2019s model more accurately replicated the observed numbers and alignments of branches. \u201cSo what we were seeing is a behavior that\u2019s not specific to the brain but universal across physical networks,\u201d Barab\u00e1si says. \u201cIt\u2019s a very important step, I think, in understanding the mechanisms of how brains and other physical networks wire themselves and why they\u2019re unusual.\u201d<\/p>\n
\u201cThis paper nicely shows that if you think [of physical networks] in terms of surface-area costs rather than wire length, things start to make more sense,\u201d says Michael Winding, a systems neuroscientist at the Francis Crick Institute in England, who was not involved with the work. \u201cThat\u2019s genuinely interesting. People usually think about surface area in terms of its effect on electrical properties\u2014like how fast signals move within a neuron rather than as a construction cost to build a neuron.\u201d<\/p>\n
As for whether comprehending the wiring of the brain really demands techniques from the frontiers of theoretical physics, questions remain. Bona fide experts in both domains are few and far between. But one, Vijay Balasubramanian, a string theorist and brain-focused biophysicist at the University of Pennsylvania, is skeptical.<\/p>\n
\u201cI\u2019m not sure that this study marks a critical breakthrough in our understanding of physical networks, and many experts may find the claimed relationship to string theory unconvincing,\u201d he says. \u201cSo any assertion of revolutionary importance here seems premature. That said, this effort to apply physical principles to understanding biological networks makes a welcome addition to the scholarship in biophysics and neuroscience and will hopefully inspire further investigations.\u201d<\/p>\n","protected":false},"excerpt":{"rendered":"
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