My research interests and expertise include constructing and applying novel neuroimaging methods to understand brain development, with a focus on cognitive, neuropsychiatric, and neurodevelopmental disorders, i.e., disorders that affect wide-ranging networks in the brain.

Presently, I am focusing on three areas of investigation that I believe are critical to translating neuroimaging discoveries into effective treatments and interventions for problematic symptoms in autism spectrum disorders: 1) Improving handling of motion-containing MRI data from pediatric clinical populations, 2) Studying other accessible clinical populations with similar symptom burdens to neurodevelopmental disorders to help localize the neuroanatomical basis of specific symptoms in children, and 3) Generating and improving large-scale clinical databases of neurodevelopmental disorder patients with neuroimaging data for hypothesis testing.


I am a physician-scientist specializing in translational neuroimaging dedicated to understanding and treating autism spectrum disorders and other neurodevelopmental conditions. I earned my baccalaureate, medical, and graduate doctoral degrees at Washington University in St. Louis, where I became an expert in using functional neuroimaging to understand brain networks. Following my graduate education, I then went on to complete a combined residency in Pediatrics and Child Neurology at Mayo Clinic where I became interested in childhood conditions affecting cognition including neurodevelopmental disorders.

I came to Boston Children's Hospital in 2016 as a Behavioral Neurology fellow, seeing patients in the Autism Spectrum Center as well as in the Behavioral Neurology Clinic. I am also a Translational Post-Doctoral Neurodevelopment Fellow in the Computational Radiology Laboratory where my research program focuses on improving our ability to study patients with autism spectrum disorders as well as localize the cause of specific symptoms across neurodevelopmental disorders.


Publications powered by Harvard Catalyst Profiles

  1. Reducing the Effects of Motion Artifacts in fMRI: A Structured Matrix Completion Approach. IEEE Trans Med Imaging. 2022 01; 41(1):172-185. View abstract
  2. Network Localization of Unconscious Visual Perception in Blindsight. Ann Neurol. 2021 Dec 27. View abstract
  3. Reply: Looking beyond indirect lesion network mapping of prosopagnosia: direct measures required. Brain. 2021 10 22; 144(9):e76. View abstract
  4. A Neural Circuit for Spirituality and Religiosity Derived From Patients With Brain Lesions. Biol Psychiatry. 2021 Jun 29. View abstract
  5. Matched neurofeedback during fMRI differentially activates reward-related circuits in active and sham groups. J Neuroimaging. 2021 09; 31(5):947-955. View abstract
  6. Lesion network mapping predicts post-stroke behavioural deficits and improves localization. Brain. 2021 05 07; 144(4):e35. View abstract
  7. Face-Processing Performance is an Independent Predictor of Social Affect as Measured by the Autism Diagnostic Observation Schedule Across Large-Scale Datasets. J Autism Dev Disord. 2021 Mar 20. View abstract
  8. Tuber Locations Associated with Infantile Spasms Map to a Common Brain Network. Ann Neurol. 2021 04; 89(4):726-739. View abstract
  9. Mapping mania symptoms based on focal brain damage. J Clin Invest. 2020 10 01; 130(10):5209-5222. View abstract
  10. Reply: The influence of sample size and arbitrary statistical thresholds in lesion-network mapping. Brain. 2020 05 01; 143(5):e41. View abstract
  11. Mapping migraine to a common brain network. Brain. 2020 02 01; 143(2):541-553. View abstract
  12. Cortical lesions causing loss of consciousness are anticorrelated with the dorsal brainstem. Hum Brain Mapp. 2020 04 15; 41(6):1520-1531. View abstract
  13. Looking beyond the face area: lesion network mapping of prosopagnosia. Brain. 2019 12 01; 142(12):3975-3990. View abstract
  14. Pediatric postoperative cerebellar cognitive affective syndrome follows outflow pathway lesions. Neurology. 2019 10 15; 93(16):e1561-e1571. View abstract
  15. Response to "smoking, co-morbidities and narcolepsy". Sleep Med. 2018 12; 52:237. View abstract
  16. Response to "High fatigue frequency in narcolepsy type 1 and type 2 in a Brazilian Sleep Center". Sleep Med. 2018 12; 52:235. View abstract
  17. De Novo DNM1L Variant in a Teenager With Progressive Paroxysmal Dystonia and Lethal Super-refractory Myoclonic Status Epilepticus. J Child Neurol. 2018 09; 33(10):651-658. View abstract
  18. Comorbidities in a community sample of narcolepsy. Sleep Med. 2018 03; 43:14-18. View abstract
  19. Intractable Epilepsy and Progressive Cognitive Decline in a Young Man. JAMA Neurol. 2017 06 01; 74(6):737-740. View abstract
  20. BIDS apps: Improving ease of use, accessibility, and reproducibility of neuroimaging data analysis methods. PLoS Comput Biol. 2017 03; 13(3):e1005209. View abstract
  21. NeuroDebian Virtual Machine Deployment Facilitates Trainee-Driven Bedside Neuroimaging Research. J Child Neurol. 2017 01; 32(1):29-34. View abstract
  22. Case of a two-year-old boy with recurrent seizures, abnormal movements, and central hypoventilation. Semin Pediatr Neurol. 2014 Jun; 21(2):114-8. View abstract
  23. Parcellating an individual subject's cortical and subcortical brain structures using snowball sampling of resting-state correlations. Cereb Cortex. 2014 Aug; 24(8):2036-54. View abstract
  24. Functional network organization of the human brain. Neuron. 2011 Nov 17; 72(4):665-78. View abstract
  25. Parcellation in left lateral parietal cortex is similar in adults and children. Cereb Cortex. 2012 May; 22(5):1148-58. View abstract
  26. Prediction of individual brain maturity using fMRI. Science. 2010 Sep 10; 329(5997):1358-61. View abstract
  27. A parcellation scheme for human left lateral parietal cortex. Neuron. 2010 Jul 15; 67(1):156-70. View abstract
  28. Identifying Basal Ganglia divisions in individuals using resting-state functional connectivity MRI. Front Syst Neurosci. 2010; 4:18. View abstract
  29. Role of the anterior insula in task-level control and focal attention. Brain Struct Funct. 2010 Jun; 214(5-6):669-80. View abstract
  30. Functional brain networks develop from a "local to distributed" organization. PLoS Comput Biol. 2009 May; 5(5):e1000381. View abstract
  31. Resting-state functional connectivity in the human brain revealed with diffuse optical tomography. Neuroimage. 2009 Aug 01; 47(1):148-56. View abstract
  32. Mapping the human brain at rest with diffuse optical tomography. Annu Int Conf IEEE Eng Med Biol Soc. 2009; 2009:4070-2. View abstract
  33. Control networks in paediatric Tourette syndrome show immature and anomalous patterns of functional connectivity. Brain. 2009 Jan; 132(Pt 1):225-38. View abstract
  34. Defining functional areas in individual human brains using resting functional connectivity MRI. Neuroimage. 2008 May 15; 41(1):45-57. View abstract
  35. The maturing architecture of the brain's default network. Proc Natl Acad Sci U S A. 2008 Mar 11; 105(10):4028-32. View abstract
  36. A dual-networks architecture of top-down control. Trends Cogn Sci. 2008 Mar; 12(3):99-105. View abstract
  37. Development of distinct control networks through segregation and integration. Proc Natl Acad Sci U S A. 2007 Aug 14; 104(33):13507-12. View abstract
  38. Distinct brain networks for adaptive and stable task control in humans. Proc Natl Acad Sci U S A. 2007 Jun 26; 104(26):11073-8. View abstract
  39. A method for using blocked and event-related fMRI data to study "resting state" functional connectivity. Neuroimage. 2007 Mar; 35(1):396-405. View abstract
  40. Tyrosine-phosphorylated and nonphosphorylated isoforms of alpha-dystrobrevin: roles in skeletal muscle and its neuromuscular and myotendinous junctions. J Cell Biol. 2003 Mar 03; 160(5):741-52. View abstract