Emily S. Finn is assistant professor of psychological and brain sciences at Dartmouth College, where she directs the Functional Imaging and Naturalistic Neuroscience (FINN) Lab. Finn has pioneered techniques such as functional connectome fingerprinting and connectome-based predictive modeling for predicting individual behaviors from functional brain connectivity. Her current work is focused on how within- and between-individual variability in brain activity relates to appraisal of ambiguous information under naturalistic conditions such as watching movies or listening to stories.
Emily S. Finn
Assistant professor of psychological and brain sciences
Dartmouth College
From this contributor
To improve big data, we need small-scale human imaging studies
By insisting that every brain-behavior association study include hundreds or even thousands of participants, we risk stifling innovation. Smaller studies are essential to test new scanning paradigms.
To improve big data, we need small-scale human imaging studies
Explore more from The Transmitter
Fruit flies use memory to track odors
When flies encounter a tasty smell, they stroll in and out of the odor plume—a process that depends on encoding a memory of the angle needed to travel back to the plume, according to a new study.
Fruit flies use memory to track odors
When flies encounter a tasty smell, they stroll in and out of the odor plume—a process that depends on encoding a memory of the angle needed to travel back to the plume, according to a new study.
New methods to contextualize autism-linked genes, and more
Here is a roundup of autism-related news and research spotted around the web for the week of 7 September.
New methods to contextualize autism-linked genes, and more
Here is a roundup of autism-related news and research spotted around the web for the week of 7 September.
Dimensionality—neuroscience’s red herring?
Placing too much emphasis on a specific interpretation of dimensionality, or treating it as an end-all quantification of some aspect of neural computation, may hinder progress in understanding the brain.
Dimensionality—neuroscience’s red herring?
Placing too much emphasis on a specific interpretation of dimensionality, or treating it as an end-all quantification of some aspect of neural computation, may hinder progress in understanding the brain.