Understanding human brain function requires knowledge of its connectivity: how one structure causally influences other components of the network. A wide range of neurological and psychiatric disorders prominently involve dysfunction of connectivity, including neurodegenerative diseases, autism, and mood disorders. Yet current methods provide only indirect measures of connectivity, and none can directly test how one brain structure causally influences another at the level of the whole brain. A unique opportunity to obtain such measures in the human brain comes from using experimental manipulation of activation through direct electrical stimulation, coupled with the whole-brain field-of-view of fMRI (es-fMRI). Our group has obtained IRB approval, and obtained strong initial data of concurrent es-fMRI in a series of 20 neurosurgical patients over the past two years. Here we intend to leverage this unique approach to the application of important open research questions in emotion, and to dissemination of protocols to a wider community of possible performance sites through this U01 mechanism.
Three Aims progress through initial validation and quantification of the approach, mapping of brain networks involved in emotion processing (with a focus on the amygdala and medial prefrontal cortex), and convergent measures with ECoG and rs-fMRI.
These Aims offer a mix of immediate implementation based on strong pilot data, more exploratory implementation during the grant, strong validation components, and future planning. The research focus of all Aims is on how emotion is caused by activity in brain networks. This is the topic with the strongest link to readily accessible brain structures for electrical stimulation in neurosurgical epilepsy patients (amygdala and prefrontal cortex). The work would have immediate implications for deep brain stimulation to treat diseases like depression, and long-term implications for eventually mapping out the effective functional connectome of the human brain. We will aim to provide the research community with short, feasible protocols that could be adopted by many other sites in a concerted effort to map effective connectivity in the human brain, eventually accumulating a database for understanding how individual differences in emotion, in health and disease, arise from differences in network connectivity.

Public Health Relevance

Mood and anxiety disorders are known to arise from abnormal interactions within brain networks, but we know little about how one brain region causes activity in another, and about how such activity generates emotions. We will leverage the rare opportunity to directly electrically stimulate brain regions such as the amygdala in neurosurgical patients, with concurrent fMRI to map the causal networks. The results will provide the first systematic mapping of causal networks in the human brain and directly inform interventions to treat mood disorders through deep-brain stimulation.

National Institute of Health (NIH)
National Institute of Neurological Disorders and Stroke (NINDS)
Research Project--Cooperative Agreements (U01)
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Special Emphasis Panel (ZNS1)
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Gnadt, James W
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California Institute of Technology
Schools of Arts and Sciences
United States
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Dubois, Julien; Galdi, Paola; Han, Yanting et al. (2018) Resting-state functional brain connectivity best predicts the personality dimension of openness to experience. Personal Neurosci 1:
Oya, Hiroyuki; Gander, Phillip E; Petkov, Christopher I et al. (2018) Neural phase locking predicts BOLD response in human auditory cortex. Neuroimage 169:286-301
Dubois, Julien; Galdi, Paola; Paul, Lynn K et al. (2018) A distributed brain network predicts general intelligence from resting-state human neuroimaging data. Philos Trans R Soc Lond B Biol Sci 373:
Dubois, Julien; Oya, Hiroyuki; Tyszka, J Michael et al. (2017) Causal mapping of emotion networks in the human brain: Framework and initial findings. Neuropsychologia :