Our brains are highly active when we are up and about doing things, such as, cooking, eating, dancing, or when we are sitting quietly solving mathematical equations, or thinking about our past memories and future dreams. Only recently, scientists learned that a set of brain structures, known as the default mode network (DMN), show reduced activity during the performance of many tasks but increased activity when we are at rest or remembering what happened in the past. This is the opposite of what scientists have seen in many other areas of the brain. To date, almost the entire literature about the DMN function is based on neuroimaging methods (e.g. fMRI) that follow the changes of blood flow in the brain, and thus have limited temporal resolution. With support from the National Science Foundation, Drs. Parvizi and Wagner of Stanford University will combine functional imaging (fMRI), direct electrophysiological recordings from the surface of the human cerebral cortex (ECoG), and electrical brain stimulation (EBS) to measure the activity of DMN structures during rest, attention, and recall conditions and determine their interactions with brain areas involved in attention and memory functions. This study will provide unprecedented information about the modes of our brain function when we switch from rest to solving difficult tasks and vice versa.

Pathological changes in the DMN are known to hallmark the onset of disorders such as Alzheimer's disease and attention-deficit disorder and autism all of which represent a pervasive public health issue. This project will lead to knowledge about the working of DMN and may one day contribute to development of intervention and treatment methods. Findings from this research will have significant societal impact. This collaborative research will also offer unique training opportunities for students and fellows to learn the multimodal approach with fMRI, ECoG, and EBS.

National Science Foundation (NSF)
Division of Behavioral and Cognitive Sciences (BCS)
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Alumit Ishai
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Stanford University
Palo Alto
United States
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