The long-term objective of this Career Development Award to Promote Diversity in Neuroscience Research is to develop the candidate's skills in applying novel brain network approaches to the study of neurodevelopmental disorders, and in conducting clinical assessments, so that she can become an independent investigator in the fields of neuroimaging and autism research. Specifically, the candidate will develop expertise in using diffusion tensor imaging (DTI) data in conjunction with recently developed multivariate pattern classification and effective connectivity analyses of functional magnetic resonance imaging (fMRI) data to examine structural and intrinsic functional brain connectivity underlying atypical behavior and cognition in children with autism spectrum disorders (ASD). To this end, the candidate will be mentored and trained by experts in the fields of neuroimaging, engineering, clinical psychology, neurology and psychiatry. The candidate will also gain critical experience in clinical assessments necessary for successfully working with children with ASD. In addition, the candidate will undertake formal coursework and attend seminars in functional neuroimaging, clinical psychology, and computer programming to achieve this goal. The research project proposed by the candidate will enable the acquisition of the skills required to become a successful independent investigator in the field of developmental cognitive neuroscience. ASD is a complex neurodevelopmental disorder of largely unknown etiology, characterized by social communicative impairments, restricted interests, and repetitive and stereotyped behaviors. The main goal of the proposed research is to examine aberrant structural and functional brain connectivity underlying atypical cognition and behavior in children with ASD. The candidate proposes to probe large-scale brain networks using DTI and fMRI to examine possible aberrant cortical connectivity and compromises in dynamic interactions between networks in children with ASD. She will specifically test a novel systems-level hypothesis she has put forth, synthesizing recent advances in brain network connectivity with converging evidence from neuroimaging studies in autism. The hypothesis is that hypoactivity of the anterior insula during processing of social stimuli results in reduced salience detection in individuals with ASD, which impairs dynamic switching between other large-scale brain networks important for cognition. Additionally, she will explore methods to establish brain-based biomarkers to distinguish children with ASD from typically developing children using a combination of brain connectivity measures and cognitive and behavioral measures. Completion of this research project and training plan will enable Dr. Uddin to gain proficiency relevant to her goal of becoming an independent investigator in the fields of autism and neuroimaging research, and will also facilitate the principled development of biomarkers of brain network dysfunction in ASD. This Career Development Award is consistent with the NIH goals to promote diversity in neuroscience research. )

Public Health Relevance

Autism spectrum disorders (ASD) affect 1:150 individuals, and the incidence continues to rise steadily, making the disorder an urgent public health concern. ASD results in lifelong difficulties for afflicted individuals and their families, and there is no known cure. Recently developed analytic tools have enabled the study of brain connectivity in vivo, revealing important principles of brain organization in individuals with ASD. Characterization of the integrity and functional roles of brain networks, as well as interactions between them, will help us to understand the underlying brain differences in individuals with ASD and eventually lead to the development of more effective treatments and therapies. )

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Research Scientist Development Award - Research & Training (K01)
Project #
5K01MH092288-04
Application #
8485679
Study Section
NST-2 Subcommittee (NST)
Program Officer
Gilotty, Lisa
Project Start
2010-04-01
Project End
2015-06-30
Budget Start
2013-07-01
Budget End
2014-06-30
Support Year
4
Fiscal Year
2013
Total Cost
$168,978
Indirect Cost
$12,517
Name
Stanford University
Department
Psychiatry
Type
Schools of Medicine
DUNS #
009214214
City
Stanford
State
CA
Country
United States
Zip Code
94305
Di Martino, A; Yan, C-G; Li, Q et al. (2014) The autism brain imaging data exchange: towards a large-scale evaluation of the intrinsic brain architecture in autism. Mol Psychiatry 19:659-67
Uddin, Lucina Q; Kinnison, Joshua; Pessoa, Luiz et al. (2014) Beyond the tripartite cognition-emotion-interoception model of the human insular cortex. J Cogn Neurosci 26:16-27
Iuculano, Teresa; Rosenberg-Lee, Miriam; Supekar, Kaustubh et al. (2014) Brain organization underlying superior mathematical abilities in children with autism. Biol Psychiatry 75:223-30
Schreiner, Matthew J; Karlsgodt, Katherine H; Uddin, Lucina Q et al. (2014) Default mode network connectivity and reciprocal social behavior in 22q11.2 deletion syndrome. Soc Cogn Affect Neurosci 9:1261-7
Uddin, Lucina Q (2014) Dynamic connectivity and dynamic affiliation. Comment on "Understanding brain networks and brain organization" by L. Pessoa. Phys Life Rev 11:460-1
Uddin, Lucina Q (2013) Complex relationships between structural and functional brain connectivity. Trends Cogn Sci 17:600-2
Yamada, Makiko; Uddin, Lucina Q; Takahashi, Hidehiko et al. (2013) Superiority illusion arises from resting-state brain networks modulated by dopamine. Proc Natl Acad Sci U S A 110:4363-7
Molnar-Szakacs, Istvan; Uddin, Lucina Q (2013) Self-processing and the default mode network: interactions with the mirror neuron system. Front Hum Neurosci 7:571
Uddin, Lucina Q; Supekar, Kaustubh; Menon, Vinod (2013) Reconceptualizing functional brain connectivity in autism from a developmental perspective. Front Hum Neurosci 7:458
Uddin, Lucina Q; Supekar, Kaustubh; Lynch, Charles J et al. (2013) Salience network-based classification and prediction of symptom severity in children with autism. JAMA Psychiatry 70:869-79

Showing the most recent 10 out of 22 publications