Zack Williams is an M.D./Ph.D. student at Vanderbilt University, in Nashville, Tennessee, currently pursuing a joint Ph.D. in neuroscience and hearing and speech sciences. His research focuses on the development and evaluation of psychological measures for use in adults on the autism spectrum. He is particularly interested in the assessment of co-occurring psychiatric and psychosomatic disorders in autistic adults and the development of evidence-based treatments for these conditions.
Zachary Williams
M.D./Ph.D. student
Vanderbilt University
From this contributor
Common sensory response scores may miss important variations
A person’s “overall” score on sensory-seeking, hyperreactive or hyporeactive tendencies may obscure nuances in their individual sensory experience.
Common sensory response scores may miss important variations
By
Zachary Williams, Tiffany Woynaroski
22 February 2024 | 5 min read
Explore more from The Transmitter
The term ‘model organism’ should be reserved for biological systems
By referring to artificial neural networks as model organisms, we run the risk of distorting funding priorities and disregard the explanatory power of a shared evolutionary history across biological organisms.
The term ‘model organism’ should be reserved for biological systems
By referring to artificial neural networks as model organisms, we run the risk of distorting funding priorities and disregard the explanatory power of a shared evolutionary history across biological organisms.
By
Marc Coutanche
13 November 2026 | 6 min read
New phase of BRAIN Initiative spawns basal ganglia ‘parts list’
With a standardized cell naming system and infrastructure for data collection and analysis, the basal ganglia project sets the stage for a whole-brain primate atlas.
New phase of BRAIN Initiative spawns basal ganglia ‘parts list’
With a standardized cell naming system and infrastructure for data collection and analysis, the basal ganglia project sets the stage for a whole-brain primate atlas.
By
Claudia López Lloreda
12 November 2026 | 1 min watch
Machine-learning model spots autism-linked variants that scramble splicing
The model provides a way to investigate genetic variation in regions of the genome whose functions have been difficult to interpret.
Machine-learning model spots autism-linked variants that scramble splicing
The model provides a way to investigate genetic variation in regions of the genome whose functions have been difficult to interpret.
By
Giorgia Guglielmi
12 November 2026 | 4 min read