A new study from researchers at Prince­ton Uni­ver­sity pro­vides evi­dence for how the brain per­forms this feat. The study, pub­lished in the jour­nal Nature, indi­cates that cer­tain position-tracking neu­rons -- called grid cells -- ramp their activ­ity up and down by work­ing together in a col­lec­tive way to deter­mine loca­tion, rather than each cell act­ing on its own as was pro­posed by a com­pet­ing theory.

Grid cells are neu­rons that become elec­tri­cally active, or "fire," as ani­mals travel in an envi­ron­ment. First dis­cov­ered in the mid-2000s, each cell fires when the body moves to spe­cific loca­tions, for exam­ple in a room. Amaz­ingly, these loca­tions are arranged in a hexag­o­nal pat­tern like spaces on a Chi­nese checker board.

"Together, the grid cells form a rep­re­sen­ta­tion of space," said David Tank, Princeton's Henry L. Hill­man Pro­fes­sor in Mol­e­c­u­lar Biol­ogy and leader of the study. "Our research focused on the mech­a­nisms at work in the neural sys­tem that forms these hexag­o­nal pat­terns," he said. The first author on the paper was grad­u­ate stu­dent Cristina Dom­nisoru, who con­ducted the exper­i­ments together with post­doc­toral researcher Amina Kinkhabwala.

Dom­nisoru mea­sured the elec­tri­cal sig­nals inside indi­vid­ual grid cells in mouse brains while the ani­mals tra­versed a computer-generated vir­tual envi­ron­ment, devel­oped pre­vi­ously in the Tank lab. The ani­mals moved on a mouse-sized tread­mill while watch­ing a video screen in a set-up that is sim­i­lar to video-game vir­tual real­ity sys­tems used by humans.

She found that the cell's elec­tri­cal activ­ity, mea­sured as the dif­fer­ence in volt­age between the inside and out­side of the cell, started low and then ramped up, grow­ing larger as the mouse reached each point on the hexag­o­nal grid and then falling off as the mouse moved away from that point.

This ramp­ing pat­tern cor­re­sponded with a pro­posed mech­a­nism of neural com­pu­ta­tion called an attrac­tor net­work. The brain is made up of vast num­bers of neu­rons con­nected together into net­works, and the attrac­tor net­work is a the­o­ret­i­cal model of how pat­terns of con­nected neu­rons can give rise to brain activ­ity by col­lec­tively work­ing together. The attrac­tor net­work the­ory was first pro­posed 30 years ago by John Hop­field, Princeton's Howard A. Prior Pro­fes­sor in the Life Sci­ences, Emeritus.

The team found that their mea­sure­ments of grid cell activ­ity cor­re­sponded with the attrac­tor net­work model but not a com­pet­ing the­ory, the oscil­la­tory inter­fer­ence model. This com­pet­ing the­ory pro­posed that grid cells use rhyth­mic activ­ity pat­terns, or oscil­la­tions, which can be thought of as many fast clocks tick­ing in syn­chrony, to cal­cu­late where ani­mals are located. Although the Prince­ton researchers detected rhyth­mic activ­ity inside most neu­rons, the activ­ity pat­terns did not appear to par­tic­i­pate in posi­tion calculations.

Note: If no author is given, the source is cited instead.

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