Our Mission

Our lab focuses on identifying the neuroanatomical substrate for symptoms common in autism and other neurodevelopmental conditions with a goal of direct translation into possible targets for noninvasive treatment modalities, e.g., TMS and/or fMRI-based neurofeedback.

This entails three interactive research arms:

  1. Generation of circuit-based hypotheses for specific symptoms from cohorts with lesions, tubers, tumor resections, etc.

  2. Validation of these localizations through prospective neuroimaging study of patients with neurodevelopmental disorders with similar symptoms, and

  3. Testing whether this circuit can be modulated through non-invasive therapy, e.g., behavioral, fMRI-neurofeedback, or potentially TMS-based interventions.

Projects

  • This project seeks to understand whether there are particular networks of regions impacted by lesions that are associated with particular symptoms that are also seen in Autism Spectrum Disorders. We have begun several projects to help answer this question, starting with the symptom of face processing difficulties:

    1. Studying Face Processing in children with Tuberous Sclerosis Complex:
      • This study investigates whether the pattern of cortical tubers in children with Tuberous Sclerosis Complex predicts their face processing ability. If this is true, it would indicate which networks are causally involved in face processing difficulties.

    2. Studying Face Processing in adolescents with Autism Spectrum Disorder:
      • This study investigates whether face processing difficulties in adolescents with ASD is correlated with specific brain network differences, a hypothesis generated from patients with acquired prosopagnosia, i.e., face blindness after brain injury. If this is true, it would mean that the same brain regions are causally involved in face processing difficulties in patients without brain injury.

    3. Studying the correlation between Face Processing and Social Affect:
      • This study leverages large-scale existing datasets to quantify the relationship between face recognition ability and social affect.

Moving forward, we have already started to investigate additional symptoms and are happy to collaborate with researchers interested in applying lesion network mapping to their data.

Generating Developmental Atlases of Brain Connectivity (2018 - present)

  • This project utilizes publicly available brain connectivity data, currently from more than 20,000 children and adolescents, into single consistently processed and quality-controlled datasets that can be used by medical researchers as a ‘gold-standard’ reference of typical development.

    1. The GSP1000 Processed Connectome is derived from data acquired by the Brain Genomics Superstruct Project (GSP), which contained 1570 subjects in total (ages 18-36). From this dataset, 1000 subjects (1:1 M/F) were chosen and processed using publicly available tools to generate a normative functional connectivity dataset. Click this link to download:‘https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/ILXIKS'

Participate

  • Impact of Stimulants and In-Scanner Motion on fMRI Neurofeedback and Task Performance in ADHD

  • We are currently seeking participants with and without attention deficit hyperactivity disorder for a study investigating whether people can improve their attention by viewing their brain signals in real time.


    If you are interested in any of our studies, please email us at Cohenlab@childrens.harvard.edu

    Meet the Team

    Faculty

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    Alexander Cohen, MD, PhD

    Principal Investigator

    The Brain, Playing Sitar

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    Jurriaan M. Peters, MD, PhD

    Investigator

    Epilepsy, Triathlon

    Researchers

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    Gillian Miller, BA

    Clinical Research Specialist

    Knitting, Crochet, Cats

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    Clara Steeby, BS

    Clinical Research Specialist

    Reading fiction, Baking, Silk screen printing

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    Jiaqi Zhao, BS

    Clinical Research Assistant

    Pet Blogging, Movies, Playing Piano

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    Zexia Lu, MS, BA

    Clinical Research Assistant

    Movies, Ski

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    Meghan Walsh, BA

    Clinical Research Assistant

    Skateboarding, Dogs

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    Wendy Xiao Herman, MD, PhD

    Child Neurology Resident

    Travel, Food

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    Shaoling Peng, PhD

    Postdoctoral Fellow

    Travel, Cooking, Running

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    Nasim Sheikhi

    Co-Op Student

    Traveling, Crocheting, Pets

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    Shreya Tripathy, BA

    Medical Student

    Cooking, Traveling, Watching movies

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    Sofia Heras, BS

    Clinical Research Assistant

    Cooking, Movies and TV, Traveling

    Alumni

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    Arina Ovchinnikova

    Undergraduate Research Assistant

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    Ayesha Imran

    Undergraduate Research Assistant

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    Brechtje Mulder

    Medical Student

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    Chariton Moschopoulos

    Child Neurology Resident

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    Eva Leikikh

    High School Research Intern

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    Faiza Yasin

    Undergraduate COACH Intern

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    Ivry Zagurly-Orly

    Medical Student

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    Louis Soussand

    Data Scientist

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    Keturah Warner

    Undergraduate COACH Intern

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    Mallory Kroeck

    Research Specialist

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    Pauline Brandon Bravo Bruinsma

    Graduate Research Intern

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    Peter McManus

    Clinical Research Assistant

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    Roshan Mathur

    Undergraduate Research Intern

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    Tabitha Hacker

    Clinical Research Assistant

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    Alyssa Edwards

    Medical Student

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    Juliana Wall

    Clinical Research Assistant

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    Meera Basu

    Neurology Resident

    Recent Publications

    (Draft List, refer to Google Scholar)

    Quickly discover relevant content by filtering publications.
    (2021). Tuber Locations Associated with Infantile Spasms Map to a Common Brain Network. ANNALS OF NEUROLOGY.

    (2020). Mapping migraine to a common brain network. Brain.

    (2020). Cortical lesions causing loss of consciousness are anticorrelated with the dorsal brainstem. Human Brain Mapping.

    (2019). Tubers Associated with Infantile Spasms Impact a Common Brain Network in Tuberous Sclerosis Complex. ANNALS OF NEUROLOGY.

    Educational Resources

    Quick tutorials for scientific computing

    Learn to use Markdown to make ‘modern’ text files (10 minutes):

    The ‘command line’ and writing shell scripts (~1 hour each):

    An introduction to pandas (an alternative to excel):

    An introduction to R (an alternative to SPSS/STATA):

    Jupyter Notebooks, a great way to organize your python, matlab, and R code:

    Git, a way to keep track of versions of your code and share files:

    Good articles to read:

    Introduction to MRI-fMRI

    Useful Courses (free):

    Contact