On brain folding and fitting 86 billion neurons inside our 1400 cc crania

Brain fold­ing typ­i­cal­ly begins at the end of the. sec­ond trimester of preg­nan­cy and con­tin­ues after birth. Hiroshi Watanabe/DigitalVision via Get­ty Images

The human brain has been called the most com­plex object in the known uni­verse. And with good rea­son: It has around 86 bil­lion neu­rons and sev­er­al hun­dred thou­sand miles of axon fibers con­nect­ing them.

Unsur­pris­ing­ly, the process of brain fold­ing that results in the brain’s char­ac­ter­is­tic bumps and grooves is also high­ly com­plex. Despite decades of spec­u­la­tion and research, the under­ly­ing mech­a­nism behind this process remains poor­ly under­stood. As bio­me­chan­ics and com­put­er sci­ence researchers, we have spent sev­er­al years study­ing the mechan­ics of brain fold­ing and ways to visu­al­ize and map the brain, respectively.

Fig­ur­ing out this com­plex­i­ty may help researchers bet­ter diag­nose and treat devel­op­men­tal brain dis­or­ders such as lissencephaly, or smooth brain, and epilep­sy. Because many neu­ro­log­i­cal dis­or­ders emerge at the ear­ly stages of devel­op­ment, under­stand­ing how brain fold­ing works can pro­vide use­ful insights into nor­mal and patho­log­i­cal brain function.

The mechanics of brain folding

The brain is made of two lay­ers. The out­er lay­er, called the cere­bral cor­tex, is com­posed of fold­ed gray mat­ter made up of small blood ves­sels and the spher­i­cal cell bod­ies of bil­lions of neu­rons. The inner lay­er is com­posed of white mat­ter, con­sist­ing most­ly of the neu­rons’ elon­gat­ed tails, called myeli­nat­ed axons.

The out­er lay­er of the brain is com­posed of gray mat­ter, while the inner lay­er con­tains white mat­ter. The dot­ted lines in this dia­gram show axon­al path­ways leav­ing gray mat­ter and enter­ing white mat­ter as unbro­ken lines. Emma Vought, CC BY

In recent years, researchers have shown that mechan­ics, or the forces that objects exert on one anoth­er, play an impor­tant role in the growth and fold­ing of the brain.

Among the sev­er­al hypothe­ses that sci­en­tists have pro­posed to explain how brain fold­ing works, dif­fer­en­tial tan­gen­tial growth is the most com­mon­ly accept­ed because it’s well-sup­port­ed by exper­i­men­tal obser­va­tions. This the­o­ry assumes that the out­er lay­er of the brain grows at a faster rate than the inner lay­er because of how neu­rons pro­lif­er­ate and migrate dur­ing devel­op­ment. This mis­match in growth rates puts increas­ing amounts of com­pres­sive forces on the out­er lay­er, lead­ing to over­all insta­bil­i­ty of the grow­ing brain struc­ture. Fold­ing these lay­ers, how­ev­er, releas­es this instability.

To bet­ter explain this the­o­ry, Jalil made a mechan­i­cal mod­el of the brain that assigned a greater growth rate to the out­er lay­er than the inner lay­er. As expect­ed, this mis­match in growth rates caused the inner lay­er to block the out­er lay­er from spread­ing out. Because the out­er lay­er can’t expand fur­ther because of this block­age, it has to fold and buck­le inside the inner lay­er to reach a more sta­ble structure.

Anoth­er study using a 3D-print­ed hydro­gel brain mod­el also showed that a mis­match in growth rates results in folding.

This buck­ling hap­pens because fold­ing max­i­mizes the brain’s sur­face-to-vol­ume ratio, or the amount of sur­face area the brain has rel­a­tive to its size. A high­er sur­face-to-vol­ume ratio allows the brain to pack in more neu­rons in a giv­en space while decreas­ing the rel­a­tive dis­tance between them.

Jalil’s research team has also found that oth­er mechan­i­cal fac­tors also affect the even­tu­al shape a devel­op­ing brain will take, includ­ing the brain’s ini­tial out­er lay­er thick­ness and how stiff the two lay­ers are rel­a­tive to each other.

More recent­ly, our sim­u­la­tion stud­ies have shown that axons, the part of the neu­ron that helps it trans­mit elec­tri­cal sig­nals, play a role in reg­u­lat­ing the brain’s fold­ing process. Our mod­el showed that brain ridges formed in areas with a high num­ber of axons, while val­leys formed in areas of low axon den­si­ty. We con­firmed these find­ings with neu­roimag­ing and tis­sue sam­ples from real human brains. This rein­forces the impor­tance that axon den­si­ty plays in brain devel­op­ment and may speak to the ori­gins of con­di­tions like autism and schiz­o­phre­nia that have irreg­u­lar brain struc­ture and connectivity.

Both of us are now in the process of devel­op­ing more sophis­ti­cat­ed mod­els of the brain based on neu­roimag­ing of real brains that will pro­vide an even more detailed sim­u­la­tion of brain development.

The mechanics of brain disorders

Our brain mod­els pro­vide a poten­tial expla­na­tion for why brains may form abnor­mal­ly dur­ing devel­op­ment, high­light­ing the impor­tant role that the brain’s struc­ture plays in its prop­er functioning.

Brains with abnor­mal fold­ing pat­terns can result in dev­as­tat­ing con­di­tions. For exam­ple, a brain mod­el with a thick­er than usu­al out­er lay­er forms few­er and larg­er ridges and val­leys than one with nor­mal thick­ness. At the extreme, this can result in a con­di­tion called lissencephaly, or smooth brain, that has a com­plete absence of brain folds. Many chil­dren with this con­di­tion have severe­ly stunt­ed devel­op­ment and die before age 10.

On the oth­er hand, polymi­cr­o­gyr­ia has a thin­ner than usu­al out­er lay­er and results in an excess of fold­ing. This con­di­tion has also been repli­cat­ed through mechan­i­cal mod­el­ing. Peo­ple with this con­di­tion can have mild to severe neu­ro­log­i­cal prob­lems, includ­ing seizures, paral­y­sis and devel­op­men­tal delays.

Sci­en­tists have also iden­ti­fied abnor­mal fold­ing pat­terns in brain dis­or­ders such as schiz­o­phre­nia and epilepsy.

Next steps in brain mechanics

Under­stand­ing the mech­a­nisms behind brain fold­ing and con­nec­tiv­i­ty will pro­vide researchers with the knowl­edge foun­da­tion to uncov­er their role in devel­op­men­tal brain dis­or­ders. In the long term, clar­i­fy­ing the con­nec­tion between brain struc­ture and func­tion may lead to ear­ly diag­nos­tic tools for brain diseases.

This 3D scan of nerve tracts shows how dif­fer­ent types of axons are dis­trib­uted across the brain. Axon den­si­ty is one fac­tor that deter­mines where brain folds form. jgmarcelino/flickr, CC BY

In the future, arti­fi­cial intel­li­gence may be able to give even more insight about the nor­mal growth and fold­ing of the human brain. But even with all these advance­ments in neu­ro­science, researchers like us have our work cut out for us as we con­tin­ue try­ing to deci­pher the mys­tery of the most com­plex known struc­ture in the universe.

Mir Jalil Raza­vi is Assis­tant Pro­fes­sor of Mechan­i­cal Engi­neer­ing, Bing­ham­ton Uni­ver­si­ty, State Uni­ver­si­ty of New York, and Weiy­ing Dai is Assis­tant Pro­fes­sor of Com­put­er Sci­ence, Bing­ham­ton Uni­ver­si­ty, State Uni­ver­si­ty of New York, are devel­op­ing sophis­ti­cat­ed mod­els of the brain based on neu­roimag­ing of real brains. This arti­cle was orig­i­nal­ly pub­lished on The Con­ver­sa­tion.

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About SharpBrains

SHARPBRAINS is an independent think-tank and consulting firm providing services at the frontier of applied neuroscience, health, leadership and innovation.
SHARPBRAINS es un think-tank y consultoría independiente proporcionando servicios para la neurociencia aplicada, salud, liderazgo e innovación.

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