Study: Harnessing fMRI neurofeedback to enhance attention and cognitive potential

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Real-time brain feed­back reduces atten­tion laps­es (News at Princeton):

“In an arti­cle pub­lished online Mon­day by the jour­nal Nature Neu­ro­science, researchers at Prince­ton Uni­ver­si­ty describe a study that shows train­ing peo­ple using real-time feed­back from their own brain activ­i­ty can reduce the fre­quen­cy of atten­tion laps­es and improve their abil­i­ty to sus­tain attention.

“Even though we all make a lot of atten­tion­al errors and we have dif­fi­cul­ty focus­ing, there’s some poten­tial for those abil­i­ties to improve,” said Nicholas Turk-Browne…the research offers basic sci­ence insights into how atten­tion works in the brain and how atten­tion-relat­ed men­tal process­es can change. It also opens the door, he said, to poten­tial prac­ti­cal appli­ca­tions for train­ing in occu­pa­tion­al set­tings, such as truck dri­ving and bag­gage screen­ing, where sus­tained atten­tion is required. In addi­tion, the research could prove help­ful in treat­ment of dis­or­ders such as atten­tion deficit hyper­ac­tiv­i­ty dis­or­der and aspects of depres­sion that are relat­ed to attention.

In the study, the researchers used real-time func­tion­al mag­net­ic res­o­nance imag­ing (rtfM­RI) to mon­i­tor the brain activ­i­ty of par­tic­i­pants as they com­plet­ed a task that involved look­ing at an image that blend­ed a face and a scene.

To com­plete the task, the study par­tic­i­pants need­ed to focus their atten­tion on either the face or the scene part of the image. When the rtfM­RI infor­ma­tion indi­cat­ed that their atten­tion was wan­der­ing away from that part of the image, the researchers made the task more dif­fi­cult by fad­ing out that part of the blend­ed image.”

Study: Closed-loop train­ing of atten­tion with real-time brain imag­ing (Nature Neuroscience)

• Abstract: Laps­es of atten­tion can have neg­a­tive con­se­quences, includ­ing acci­dents and lost pro­duc­tiv­i­ty. Here we used closed-loop neu­ro­feed­back to improve sus­tained atten­tion abil­i­ties and reduce the fre­quen­cy of laps­es. Dur­ing a sus­tained atten­tion task, the focus of atten­tion was mon­i­tored in real time with mul­ti­vari­ate pat­tern analy­sis of whole-brain neu­roimag­ing data. When indi­ca­tors of an atten­tion­al lapse were detect­ed in the brain, we gave human par­tic­i­pants feed­back by mak­ing the task more dif­fi­cult. Behav­ioral per­for­mance improved after one train­ing ses­sion, rel­a­tive to con­trol par­tic­i­pants who received feed­back from oth­er par­tic­i­pants’ brains. This improve­ment was largest when feed­back car­ried infor­ma­tion from a fron­topari­etal atten­tion net­work. A neur­al con­se­quence of train­ing was that the basal gan­glia and ven­tral tem­po­ral cor­tex came to rep­re­sent atten­tion­al states more dis­tinc­tive­ly. These find­ings sug­gest that atten­tion­al fail­ures do not reflect an upper lim­it on cog­ni­tive poten­tial and that atten­tion can be trained with appro­pri­ate feed­back about neur­al signals.

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