Abnormal patterns of activity within the human default network (DN), which is a constellation of functionally connected brain regions that is engaged during introspective thought and suppressed during sensorimotor processing, has been linked to the cognitive and behavioral impairments associated with host of neuropsychiatric disorders such as schizophrenia, depression, autism spectrum disorder or ADHD. For instance, functional magnetic resonance imaging (fMRI) studies have revealed that aberrant patterns of DN activity may in part orchestrate disordered-thinking characteristic to schizophrenia. DN dysfunction, as illuminated with fMRI, across various neuropsychiatric disease states is likely not a consequence of a shared pathophysiologic process. Despite this assumption, remarkably little is known about the electrophysiological dynamics of the DN, information that is crucial to a mechanistic understanding of abnormal function at a systems level. The overall goal of the experiments outlined in this proposal is to define the electrophysiological dynamics of the DN using two techniques: 1, electrocortiography (ECoG), capitalizing on the standard-of-care implantation of subdural ECoG electrodes in the presurgical evaluation of individuals with intractable epilepsy and 2, high frequency scalp-based electroencephalography (EEG).
Specific Aim 1 will use ECoG to determine the rapid and dynamic timing of neural responses within the DN during an evoked event-related introspective, 'self-referential'task and during DN suppression engendered by a linguistic task.
In Specific Aim 2, we will use ECoG to characterize the interactions between the DN and a language or task positive network to elucidate the neuronal mechanisms underlying DN interference on task performance. However, use of ECoG is limited to populations requiring craniotomies for surgical exposure. Therefore, in Specific Aim 3 we will capitalize on new approaches in EEG methodology and examine the ability of EEG to localize electrical activity to the deep cortical regions of the DN, using ECoG as the gold standard. Building upon his background in functional imaging, a training program has been designed and a distinguished team of neurosurgeons, neurologists and electrophysiologists has been assembled to provide the candidate with the knowledge necessary to incorporate electrophysiology into his research activities. The future application of a multimodal approach, employing both functional imaging and electrophysiology to the pursuits of DN function in psychiatric populations provides an exquisitely sensitive means of profiling the range and contributions of DN dysfunction to the biological basis of mental health.

Public Health Relevance

The anticipated results from these experiments will precisely characterize the neurophysiological dynamics of the default network in humans. They will contribute to our understanding of the biological utility, relevance and function of the default network and provide greater insight into how reported network abnormalities occurring in various mental disorders such as Schizophrenia, Autism, depression and ADHD contribute to underlying pathology.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Research Scientist Development Award - Research & Training (K01)
Project #
5K01MH086118-04
Application #
8521381
Study Section
Cognitive Neuroscience Study Section (COG)
Program Officer
Rosemond, Erica K
Project Start
2010-08-10
Project End
2015-07-31
Budget Start
2013-08-01
Budget End
2014-07-31
Support Year
4
Fiscal Year
2013
Total Cost
$136,841
Indirect Cost
$10,136
Name
University of Washington
Department
Radiation-Diagnostic/Oncology
Type
Schools of Medicine
DUNS #
605799469
City
Seattle
State
WA
Country
United States
Zip Code
98195
Ko, Andrew L; Weaver, Kurt E; Hakimian, Shahin et al. (2013) Identifying functional networks using endogenous connectivity in gamma band electrocorticography. Brain Connect 3:491-502
Wander, Jeremiah D; Blakely, Timothy; Miller, Kai J et al. (2013) Distributed cortical adaptation during learning of a brain-computer interface task. Proc Natl Acad Sci U S A 110:10818-23
Weaver, K E; Chaovalitwongse, W A; Novotny, E J et al. (2013) Local functional connectivity as a pre-surgical tool for seizure focus identification in non-lesion, focal epilepsy. Front Neurol 4:43