Haskins Laboratories
Research
Speech defines us as human beings, while literacy is the foundation of modern civilization. Yet the relationship between speech and literacy is anything but simple. Although talking and understanding what others say comes naturally to every healthy child, many individuals as well as entire societies do not read or write. Disorders, disease, and trauma impair some people’s ability to speak and/or understand the speech of others. Disabilities and inadequate education prevent many more from learning to read or write.
How do we acquire, produce, and understand speech? How do we achieve literacy? How do these fundamental communicative characteristics breakdown? Exploring such questions opens a window on the inner workings of the brain with profound implications for helping those whose speech, language, and reading problems impact their daily lives. The science of the spoken and the written word promises to help these people participate more fully in society. For more than 80 years, Haskins Laboratories has been a leading multidisciplinary community of scientists studying speech, language, and reading and their disorders, and developing practical applications to help improve human communication.
1. TRANSCEND: Transdisciplinary Graduate Training in Educational Neuroscience, Engineering,
and Learning Technologies
Mechanism & Grant #: NSF NRT — 2152202
Summary: This PhD program trains students in neuroscience, education, engineering, CS, and math,
with a focus on neurodiversity and AI. Projects integrate neuroimaging, learning technologies, and
community-based research. Emphasis on bridging science, education, and tech. Over half of trainees self-
identify as neurodivergent.
2. Integrative Sensorimotor Plasticity for Speech Motor Learning and Retention
PI: David J. Ostry | Co-I: Nishant Rao
Mechanism & Grant #: NIH R01 — R01DC017439
Summary: Explores interactions between motor, auditory, and somatosensory systems during speech motor learning. Combines cTBS and fMRI to map neural circuits for speech acquisition and retention,
3. Neural Markers of Phonological-to-Orthographic Transfer in Early Literacy
PI: Erin Isbilen | Mentors: Dick Aslin, Ken Pugh, Jay Rueckl
Mechanism & Grant #: NIH K99/R00 — K99HD113838
Summary: Tracks EEG markers of children's implicit learning of speech sound patterns and their link to
reading and spelling skills. Follows children over time to understand how phonological learning predicts
reading fluency in alphabetic systems.
4. Neurocognitive Predictors of Response to Evidence-Based Reading Instruction
PI: Kenneth R. Pugh
Mechanism & Grant #: NIH R37 (MERIT) — R37HD090153
Summary: Uses fMRI, EEG, and fNIRS to study children (typical and dyslexic) undergoing structured
reading interventions. Identifies neurocognitive traits (e.g., phonological processing, brain plasticity) that
predict who benefits most from instruction.
5. Predicting Intervention Outcomes in Reading Disabled Students Using In-School Neuroscience
PI: Nicole Landi | Yale Sub-PI: Dan Kleinman
Mechanism & Grant #: NIH R01 — R01HD112521
Summary: Implements EEG and behavioral assessments in schools to predict reading intervention
outcomes in students with reading disabilities. Builds predictive models and investigates demographic
and instructional moderators using portable in-school labs.
6. Home-Based Digital Reading Intervention: Efficacy and Individual Predictors
PIs: Nicole Landi, Michael P. Milham (Child Mind Institute)
Mechanism & Grant #: NIH R01 — R01HD101842
Summary: A randomized controlled trial of GraphoLearn for at-home reading intervention. Examines
reading gains, neural and behavioral predictors (e.g., attention, motivation, psychiatric comorbidity), and
parent involvement. Includes remote EEG and usage fidelity tracking.
7. Phenotypic Variability in Word Reading Disability: LD Innovation Hub
PI: Don Compton (FSU) | UConn Sub-PI: Jay Rueckl
Mechanism & Grant #: NIH P20 — P20HD091013
linguistic data with computational modeling.
8. Neural Mechanisms of Compensation in Adult Dyslexia
PI: Fumiko Hoeft | Co-I: Robin Morris (Georgia State)
Mechanism & Grant #: NIH R01 — R01HD096261
Summary: Investigates compensatory brain mechanisms in adults with dyslexia using fMRI, MRS, and
TMS. Focuses on functional reading despite persistent deficits and explores neurochemical markers like
GABA and glutamate.
9. Intergenerational Impacts on Reading & Language Networks Using a Natural Cross-Fostering
Design
PI: Fumiko Hoeft
Mechanism & Grant #: NIH R01 — R01HD094834
Summary: Uses a unique IVF cross-fostering sample to disentangle genetic, prenatal, and postnatal
influences on language and reading brain networks. Includes imaging and behavioral data from both
parents and children.
10. Mechanisms & Outcomes of Emotional Well-Being and Mind-Body Interventions (M3EWB
Network)
PIs: Fumiko Hoeft, Crystal Park, Sandy Chafouleas
Mechanism & Grant #: NIH U24 — U24AT011281
Summary: A national research network studying emotional well-being as both a health outcome and
mechanism. Combines mind-body interventions, imaging, and training infrastructure to advance the
science of emotional well-being.
11. Network-Targeted tDCS Treatment for Laryngeal Dystonia: Mechanisms & Clinical Effects
PI: Vince Gracco | Co-I: Nabin Koirala
Mechanism & Grant #: Dysphonia International (pilot); NIH planned
Summary: Tests targeted transcranial stimulation (tDCS) over speech-motor networks to reduce
laryngeal dystonia symptoms. Measures include voice quality, speech acoustics, and brain imaging to
assess treatment effects and network changes over time.
12. The MELD Consortium: Longitudinal Multisensory Environments and Development
Summary: Studies how multisensory integration (audio, visual, tactile) develops from infancy through
young adulthood. Uses immersive technologies, longitudinal data, and naturalistic tasks to link sensory
processing with language, cognition, and literacy.
13. Live Social Interaction Brain & Behavior Mapping Suite
PI: Joy Hirsch | Co-Is: Adam Noah, Xian Zhang, David Ostry, Mark Tiede, Vince Gracco
Mechanism & Grant #: NIH R64 Resource Grant
Summary: Builds a multimodal suite (fNIRS, EEG, eye-tracking, pupillometry) to study real-time brain
activity during live social interaction. Includes tools for perturbation (e.g., tDCS) and measures of neural
synchrony, gaze, and socioemotional processing.
14. Reading and Statistical Learning Across Languages: Predictors & Cross-Linguistic
Comparisons
PI: Noam Siegelman (Hebrew University)
Mechanism & Grant #: Azrieli Foundation / Israel Science Foundation
Summary: Investigates how statistical learning of language patterns predicts reading proficiency in
Hebrew and other languages. Focuses on phonotactic and orthographic regularities and examines how
writing system differences shape reading development.
15. Neural Entrainment & Speech Tracking in Developing Brains
PI: Marc Joanisse (Western University, Canada)
Mechanism & Grant #: CIHR Project Grant
Summary: Uses EEG to study neural entrainment to speech rhythms in children, including those with
language and reading disorders. Links phase-locking and signal-to-noise measures to working memory,
speech processing, and reading outcomes.
16. Bilingualism, Language Experience, and Neural Code Development in Reading
PI: Marc Joanisse (Western University, Canada)
Mechanism & Grant #: NSERC Discovery Grant
Summary: Examines how neural representations for reading differ based on bilingual vs. monolingual
language experience. Combines behavioral testing and neuroimaging to understand how exposure, writing
system, and language background shape reading networks.
PI: Urs Maurer (Chinese University of Hong Kong)
Mechanism & Grant #: TRS Grant, Hong Kong RGC — T44-410/21-N (2022–2026)
Summary: Tracks literacy and math development in Hong Kong children using behavioral, genetic, and
EEG data. Includes twins and singletons and builds a large-scale database (~3,000 children) for modeling
academic trajectories in Chinese and English.
18. An Integrative-Interactive Approach to Speech Development
PIs: Aude Noiray (France), Susanne Fuchs (Germany)
Mechanism & Grant #: ANR-DFG — 2025–2028
Summary: Investigates how speech-motor coordination develops in French- and German-speaking
infants. Combines longitudinal and cross-sectional data using audiovisual recordings, eye-tracking,
ultrasound imaging, and respiratory measures.
19. Intensive Speech Motor Chaining Treatment and AI Integration for Residual Speech Sound
Disorders
PI: Jonathan Preston (Syracuse University) | Co-Is: Nina Benway, Ben Munson, Asif Salekin, Dongliang
Wang
Mechanism & Grant #: NIH R01 — R01DC020959
Summary: Aims to optimize and scale Speech Motor Chaining (SMC) therapy for persistent speech
sound disorders (/ɹ/, /s/, /z/). Tests treatment intensity and uses AI to guide practice and detect
misarticulations. Combines RCT, single-subject design, and machine learning.
20. HBCD: Prenatal Experiences and Longitudinal Development (PRELUDE) Consortium
PIs: Laurie Cutting, Osmundson (Vanderbilt)
Mechanism & Grant #: NIH U01 — 5U01DA055347
Summary: A national longitudinal study of brain development in 7,200 mother-infant pairs across 27
U.S. sites. Examines how genetic and environmental exposures (e.g., maternal stress, toxins, substance
use) shape neurodevelopment via imaging, behavioral, and biospecimen data.
PI: Laurie Cutting
Mechanism & Grant #: NIH R37 — 4R37HD095519
Summary: Investigates how executive function (EF) supports reading and math growth in upper
elementary students. Explores the idea that general EF skills become specialized to support academic
22. Neural Correlates of Discourse Processing in Adolescents
PI: Laurie Cutting
Mechanism & Grant #: NIH R01 — 5R01HD109151
Summary: Studies how adolescents build mental models (situation models) while reading narrative vs.
expository texts. Uses neuroimaging and behavioral tools to understand why expository comprehension is
more difficult, and whether embedding emotional content in informational texts boosts comprehension.
Focuses on brain networks supporting socioemotional (NarrT) vs. executive (ExpT) processing in 10–12-
year-olds.
23. The Statistical Reader: Statistical Learning and Reading Proficiency
PIs: Ram Frost, Morten H. Christiansen
Mechanism & Grant #: BSF Research Grant — 2022082
Summary: Investigates how readers learn statistical patterns in writing systems (e.g., word-length
distributions in English vs. Hebrew) and how this shapes eye-movement planning and reading fluency.
Assesses individual differences in implicit learning and links them to reading comprehension efficiency.