Eric Yttri
Associate Professor
- Pittsburgh PA UNITED STATES
Eric Yttri's research goal is to establish how neural circuits lead to these action selection decisions.
Biography
Areas of Expertise
Media Appearances
Hesitation is costly in sports but essential to life – neuroscientists identified its brain circuitry
Yahoo! News online
2026-02-12
As a neuroscientist, I have been working to uncover how the brain decides when to act and when to wait. Recent research from my team and me helps explain why this split-second pause happens, offering insight not only into elite athletic performance, but also how people make everyday decisions when the potential outcome isn’t clear.
[...]
Hesitation is not a flaw – it’s a critical feature for navigating an unpredictable world. Whether you’re a figure skater waiting for the perfect moment to launch your jump or just going about your day, the circuitry behind hesitation plays an important role in figuring out the timing to get the action right.
Carnegie Mellon University Hosts Interdisciplinary AI Conference
India Education Diary online
2023-03-04
“It was fascinating to talk to all of the outside speakers that are asking very different questions and using very different models,” Yttri said. “Despite some people looking at proteins, RNA or neuroscience, the methods and thought processes we all use are remarkably similar.”
Gov. Wolf’s Health Department Mandates Masks For Schools, Child Care Facilities
90.5 WESA online
2021-09-01
As part of 90.5 WESA’s Good Question, Kid! Series, Eric Yttri, assistant professor of biological sciences and neuroscience researcher at Carnegie Mellon University, explains why songs get stuck in our heads.
New Algorithm to Revolutionize the Study of Behavior
Carnegie Mellon University online
2021-09-01
Yttri said B-SOiD provides a huge improvement and opens up several avenues for new research.
"It removes user bias and, more importantly, removes the time cost and arduous work," he said. "We can accurately process hours of data in a matter of minutes."
Machine learning algorithm revolutionizes how scientists study behavior
Medical Xpress online
2021-08-31
To Eric Yttri, assistant professor of biological sciences and Neuroscience Institute faculty at Carnegie Mellon University, the best way to understand the brain is to watch how organisms interact with the world.
"Behavior drives everything we do," Yttri said.
The weird Upside Down science behind ‘Stranger Things’
CNN online
2019-07-04
In the lab, they can also create a kind of mind control. It’s not unlike the way the Mindflayer controls Will.
“In neuroscience, we have a much less sinister but similar notion of that control,” Yttri said. “We can record neurons and essentially thoughts in the brain, read those out, decode them and then encode them into actions.”
Media
Social
Industry Expertise
Education
College of William and Mary
B.S.
Neuroscience
Washington University
Ph.D.
Neuroscience
Articles
The striatal indirect pathway mediates hesitation
Nature Neuroscience2025
Hesitation—that is, pausing an action in the face of uncertainty—is ubiquitous in daily life, yet little is known about its underlying neural circuitry. We present a new experimental paradigm that reliably evokes hesitation in mice and find that hesitation is mediated by indirect, but not direct, pathway neurons in the dorsomedial striatum. These data establish a new role for the indirect pathway in suppressing action under uncertainty.
Motor cortex is responsible for motoric dynamics in striatum and the execution of both skilled and unskilled actions
Neuron2024
Striatum and its predominant input, motor cortex, are responsible for the selection and performance of purposive movement, but how their interaction guides these processes is not understood. To establish its neural and behavioral contributions, we bilaterally lesioned motor cortex and recorded striatal activity and reaching performance daily, capturing the lesion’s direct ramifications within hours of the intervention. We observed reaching impairment and an absence of striatal motoric activity following lesion of motor cortex, but not parietal cortex control lesions.
Open-source tools for behavioral video analysis: Setup, methods, and best practices
Elife2023
Recently developed methods for video analysis, especially models for pose estimation and behavior classification, are transforming behavioral quantification to be more precise, scalable, and reproducible in fields such as neuroscience and ethology. These tools overcome long-standing limitations of manual scoring of video frames and traditional ‘center of mass’ tracking algorithms to enable video analysis at scale. The expansion of open-source tools for video acquisition and analysis has led to new experimental approaches to understand behavior. Here, we review currently available open-source tools for video analysis and discuss how to set up these methods for labs new to video recording.
207. Dorsal Striatal Indirect Pathway Neurons Mediate Response Inhibition to Uncertain Cues
Biological Psychiatry2023
Background
The dorsomedial striatum (DMS) is critical for both response inhibition and value-based decision making. Here we assess how the DMS mediates both functions simultaneously.
Methods
Mice (n= 10; 5 female) expressing either channelrhodopsin-2 (ChR2) in either direct or indirect pathway medium spiny neurons (dMSNs or iMSNs) were trained to perform an auditory conditioning task with three cue that predicted reward on 0%, 50% or 100% of trials. To manipulate activity, dMSNs or iMSNs were stimulated during the cue period. In a separate cohort of animals (n= 3; 1 female), MSN activity was recorded using Neuropixel probes, and single units were identified using Kilosort and Phy software.
Mapping the neuroethological signatures of pain, analgesia, and recovery in mice
Neuron2023
Ongoing pain is driven by the activation and modulation of pain-sensing neurons, affecting physiology, motor function, and motivation to engage in certain behaviors. The complexity of the pain state has evaded a comprehensive definition, especially in non-verbal animals. Here, in mice, we used site-specific electrophysiology to define key time points corresponding to peripheral sensitivity in acute paw inflammation and chronic knee pain models. Using supervised and unsupervised machine learning tools, we uncovered sensory-evoked coping postures unique to each model. Through 3D pose analytics, we identified movement sequences that robustly represent different pain states and found that commonly used analgesics do not return an animal's behavior to a pre-injury state.
A-SOiD, an active learning platform for expert-guided, data efficient discovery of behavior
bioRxiv2022
Behavior identification and quantification techniques have undergone rapid development. To this end, supervised or unsupervised methods are chosen based upon their intrinsic strengths and weaknesses (e.g. user bias, training cost, complexity, action discovery). Here, a new active learning platform, A-SOiD, blends these strengths and in doing so, overcomes several of their inherent drawbacks. A-SOiD iteratively learns user-defined groups with a fraction of the usual training data while attaining expansive classification through directed unsupervised classification. In socially-interacting mice, A-SOiD outperformed standard methods despite requiring 85% less training data. Additionally, it isolated two additional ethologically-distinct mouse interactions via unsupervised classification.