Felicia Davatolhagh is a postdoctoral researcher at the University of California, Los Angeles in Anne Churchland’s lab, where she studies how cortical circuits are altered during decision-making in a genetic mouse model of autism. She also serves as a member of the neurobiology department’s Justice, Diversity and Inclusion (JEDI) group.
Felicia Davatolhagh
Postdoctoral researcher
University of California, Los Angeles
From this contributor
Women are systematically under-cited in neuroscience. New tools can change that.
An omitted citation in a high-profile paper led us to examine our own practices and to help others adopt tools that promote citation diversity.
Women are systematically under-cited in neuroscience. New tools can change that.
By
Anne Churchland, Felicia Davatolhagh
22 July 2024 | 5 min read
Explore more from The Transmitter
Links between tuberous sclerosis complex and autism, and more
Here is a roundup of autism-related news and research spotted around the web for the week of 17 August.
Links between tuberous sclerosis complex and autism, and more
Here is a roundup of autism-related news and research spotted around the web for the week of 17 August.
By
Jill Adams
18 August 2026 | 1 min read
The fun and flexibility of data science
Taylor Bolt spent his Ph.D. and postdoc digging through brain imaging data for clues to cognition. In industry, the datasets are different but the joy of answering questions with data remains.
The fun and flexibility of data science
Taylor Bolt spent his Ph.D. and postdoc digging through brain imaging data for clues to cognition. In industry, the datasets are different but the joy of answering questions with data remains.
By
Katie Moisse
18 August 2026 | 7 min read
Mind over metrics: How can we tell if two brains (or AI models) are alike?
The ability to record from large populations of neurons has triggered the development of myriad methods for comparing them. But we’re still grappling with how to convert measures of likeness into a better mechanistic understanding.
Mind over metrics: How can we tell if two brains (or AI models) are alike?
The ability to record from large populations of neurons has triggered the development of myriad methods for comparing them. But we’re still grappling with how to convert measures of likeness into a better mechanistic understanding.
By
Alex Williams
17 August 2026 | 7 min read