Presidential Cluster on Breaking the Neural Code
The Presidential Cluster on Breaking the Neural Code supports research and teaching on the neural codes underlying mental states, beliefs, experiences, and behavior. The neural code holds the keys to human flourishing. Understanding it will help us understand the neural bases of feelings, social connections, belief formation and change, mental and brain health, and other fundamental aspects of the human experience.
Doing this requires new, multidisciplinary technologies and approaches that cross traditional boundaries between fields.
Read the Full Mission
Neuroscience Network
Explore an interactive, force-directed map of neuroscience-related labs across Dartmouth. Group it by department, shared technique or shared topic to see how disciplines and methods connect.
Explore the NetworkWhat's happening in the cluster
- Award
Wager wins the 2026 Atkinson Prize
Tor Wager received the National Academy of Sciences' 2026 Atkinson Prize for his research program.
- Funding
R01 converted to an NIH R37 MERIT award
Wager's placebo-effects research earned NIMH's R37 MERIT designation, recognizing sustained scientific impact.
- Infrastructure
Dartmouth gains early tTIS access
Dartmouth is now one of the first universities worldwide with Temporal Interference stimulation access, via the IT'IS Foundation's Early Adopter program.
- Publication
24 papers published in 2026 alone
Including a Science paper on targeted placebo effects and two Nature Communications papers.
- Award
Jim Haxby elected to National Academy of Sciences
Elected in April 2026 as one of 145 new members, recognized for his research on decoding mental content from brain activity, including the Hyperalignment framework and multivoxel pattern analysis.
- Research
Murray lab completes its first human behavioral study at Dartmouth
Eye tracking during a reinforcement-learning task showed how people deploy attention to weigh different features when making decisions, laying the groundwork for the lab’s first neuroimaging experiments.
- Funding
Murray–Stoermer NSF proposal recommended for funding
A joint project between John Murray and Viola Stoermer will investigate the role of attention in learning using choice behavior, eye tracking, and EEG.
- Publication
Murray lab publishes on neurobehavioral biomarkers and cortical dynamics
Papers include “A Framework for Advancing Mechanistic Neurobehavioral Biomarkers in Psychiatry” (Biological Psychiatry) and “Temporal and Spatial Scales of Human Resting-state Cortical Activity Across the Lifespan” (Journal of Neuroscience).
- Collaboration
Murray lab collaborations span UCLA, Yale, and Johns Hopkins
Projects cover learning strategies in autism (UCLA, SFARI-supported), working-memory circuit models (Yale, NSF-supported), and credit assignment in reinforcement learning (Johns Hopkins, NIH R01).
The Committee
Tor WagerChair, Steering CommitteePsychological and Brain Sciences
John MurraySteering CommitteePsychological and Brain Sciences
Jim HaxbySteering CommitteePsychological and Brain Sciences
A Presidential Academic Cluster at Dartmouth College, promoting research and teaching on the neural codes underlying mental states, experiences, and behavior.
Mission and Goals
Why the cluster exists, what it's working toward, and the five goals guiding its work at Dartmouth.
The Presidential Cluster on Breaking the Neural Code supports research and teaching on the neural codes underlying mental states, beliefs, experiences, and behavior. The neural code holds the keys to human flourishing. Understanding it will help us understand the neural bases of feelings, social connections, belief formation and change, mental and brain health, and other fundamental aspects of the human experience.
Cracking the neural code is not a single-lab or single-discipline effort but requires new, multidisciplinary technologies and approaches that cross traditional boundaries between fields of study. Our approach pairs human neuroimaging and physiology with computational models of circuits and behavior across species.
Computational approaches are used to understand brain organization, to develop models of the brain processes underlying human feelings and cognitive performance, and to develop translational applications for clinical use.
The cluster's activities build on existing strengths in neuroscience at Dartmouth College and support a research and teaching community that collaborates across traditional scientific areas.
Five Priorities
- 01
Faculty Hires
Supporting hires who bring cutting-edge multidisciplinary computational and biological techniques to Dartmouth. An active search is underway to fill a third endowed faculty position bridging computational and systems neuroscience, further strengthening ties between human neuroimaging and animal-model circuit research.
- 02
Enhance Research on the Neural Code
Providing seed funding for multidisciplinary, exploratory collaborations so they can become externally competitive for larger grants and awards.
- 03
Visitors and Speakers
Bringing cutting-edge researchers to campus to share their work and to facilitate new collaborations beyond Dartmouth.
- 04
Building Community
Enhancing the physical and intellectual environment to foster cross-disciplinary communication among psychology, neuroscience, biology, computer science, engineering, cognitive science, biostatistics, and medicine around computational neuroscience.
- 05
Undergraduate and Graduate Education
Supporting and incentivizing new courses in neuroscience that align with the cluster's mission, at both the undergraduate and graduate level.
Breaking the Neural Code is one of Dartmouth's Presidential Academic Clusters, a College-wide initiative that concentrates strategic investment in faculty hiring and research infrastructure around emerging, cross-disciplinary scientific opportunities. Learn more about the Academic Clusters initiative from Dartmouth's Office of the Provost.
Priority Research Areas
Priority Research Areas
Priority Area 01
Human Computation and Behavior
Human neuroimaging, particularly fMRI and MEG, is used to study human thought, experience, and behavior. This area combines those signals with computational methods, including pattern recognition, dynamic-systems modeling, large-scale data resources, and neuromodulation, to model how the brain gives rise to feelings and cognitive performance.
- fMRI + pattern recognition and dynamic-systems models of brain states
- Big-data resources and large-scale computing
- Advanced modeling of brain–behavior interrelationships
- Neuroimaging combined with neuromodulation and multimodal recording
Priority Area 02
Computational Neuroscience
Computational approaches are used to understand brain organization, to develop models of the brain processes underlying human feelings and cognitive performance, and to develop translational applications for clinical use. This area bridges the cluster's human and circuit-level work through shared models, theory, and large-scale computing.
- Models of the brain processes underlying feelings and cognitive performance
- Machine-learning and AI models that predict feeling states directly from neural data
- Theory linking circuit and population activity to behavior
- Translational applications for clinical use
Priority Area 03
Neural Population Coding and Circuits
This area studies neural circuits and how populations of neurons encode behavior. It develops and applies tools for tagging, imaging, and manipulating neural ensembles tied to behavioral states, along with the theoretical and computational modeling needed to link population activity to cognition and action.
- Tagging, imaging and manipulating neural ensembles (optogenetics, DREADDs, 2-photon/multiphoton, miniscope imaging)
- Theoretical neuroscience: computational modeling of population activity and behavior
Shared Infrastructure
Cross-Cutting Infrastructure
The priority areas draw on the same shared investments in data, compute, and stimulation hardware, built to be useful across the whole cluster, rather than a single lab.
Affective Neuroimaging Consortium
ANIC is a data-sharing consortium spanning 54 collaborating labs worldwide and more than 3,000 participants. It's one of the most comprehensive functional-imaging datasets in existence, covering pain, pleasure, aversive stimuli, and food and drug cues.
Dual-H100 GPU Compute Node
Deployed in partnership with Dartmouth Research Computing, this shared GPU node gives cluster labs the large-scale computing power needed to train AI models that predict feeling states directly from neural data.
Multi-Technique Neurostimulation Facility
Inside the Cognitive and Affective Neuroscience Lab in Moore Hall, researchers combine TMS, tDCS, and Temporal Interference stimulation. Dartmouth is among the first universities worldwide with tTIS access, via the IT'IS Foundation's Early Adopter program.
These investments also feed Dartmouth's emerging, cross-campus integrated Neuroscience Institute initiative, translating neuroscience research into brain-disorder treatments, from fMRI-guided neurostimulation to clinical neuromodulation for epilepsy and serious mental illness.
See how Dartmouth's neuroscience labs connectPriority Area 01
Human Computation and Behavior
Human neuroimaging (particularly fMRI and MEG) offers a unique window into human thought, experience, and behavior. This area asks what it takes to turn that window into a precise, quantitative science.
fMRI and MEG let researchers observe the living human brain as it thinks, feels, and decides, but raw signal alone doesn't explain behavior. This priority area is built around closing that gap: pairing human neuroimaging with the computational tools, data resources, and stimulation technologies needed to develop precise, quantitative models of the brain processes underlying feelings and cognitive performance, and to translate those models toward clinical use.
It draws together investigators across Psychological and Brain Sciences, Thayer School of Engineering, Geisel School of Medicine, and Dartmouth's Cognitive Science program, reflecting the cluster's broader mission to work across the traditional boundaries between those fields.
Sub-Focus Areas
Four ways this area is built
Pattern Recognition and Dynamic-Systems Models
Merging fMRI with pattern-recognition methods and dynamic-systems models of brain states, moving beyond static activation maps toward models of how brain states evolve over time.
Big-Data Resources and Large-Scale Computing
Leveraging large public resources (such as the UK Biobank's combined genetics, imaging, and health dataset) alongside large-scale computing to find patterns that no single-lab dataset could reveal.
Modeling Brain–Behavior Interrelationships
Advanced modeling of brain and behavioral data and how they relate to one another, including dynamic-systems approaches and network-topology models of brain organization.
Neuromodulation and Multimodal Recording
Combining neuroimaging with neuromodulation (TMS and tDCS) and multimodal brain recording such as simultaneous EEG and fMRI, to both measure and causally probe brain activity.
Current Activity
This area in action at Dartmouth
Not an abstract roadmap: active labs, real infrastructure, and work published this year.
Human brain stimulation program (Wager lab)
A collaboration hub with Thayer School of Engineering combining TMS, tDCS, and Temporal Interference stimulation. The program has already produced two papers in the journal Pain, and Dartmouth is among the first universities worldwide with Temporal Interference (tTIS) access, through the IT'IS Foundation's (Zurich) Early Adopter program.
Affective Neuroimaging Consortium (ANIC)
A data-sharing consortium of 54 collaborating labs worldwide and more than 3,000 participants. It's one of the most comprehensive functional-imaging datasets anywhere, covering pain, pleasure, aversive stimuli, and food and drug cues.
New dual-H100 GPU compute
Deployed with Dartmouth Research Computing, this shared compute node now powers AI models that aim to predict feeling states directly from neural data, a core near-term goal for the ANIC dataset.
Murray lab's first Dartmouth neuroimaging experiments
Building on 2024–2025 eye-tracking pilot work, the Murray lab is now running its first EEG and fMRI experiments at Dartmouth, testing models of attention and decision-making, in collaboration with Viola Stoermer of Psychological and Brain Sciences.
Several of these techniques (fMRI, EEG, TMS, tDCS) are shared well beyond this one priority area.
See which Dartmouth labs share these techniques →Priority Area 03
Neural Population Coding and Circuits
Modern neuroscience techniques are revolutionizing our understanding of neural circuits and how populations of neurons encode behavior. This area builds the tools, and the theory, to read that code directly.
Where fMRI and MEG reveal patterns across the whole human brain, this priority area works at the scale of individual neurons and the ensembles they form. New techniques for tagging, imaging, and manipulating neural populations, paired with theoretical models of how population-level activity gives rise to behavior, are opening a second, complementary window onto the same underlying question: how does neural activity encode mental states, decisions, and action?
This area is newer and smaller at Dartmouth than human neuroimaging, and it is deliberately being built out as one of the cluster's active priorities for growth.
Sub-Focus Areas
Two ways this area is built
Tagging, Imaging and Manipulating Neural Ensembles
New techniques for tagging, imaging, and manipulating neural ensembles tied to specific behavioral states, including optogenetics, DREADDs, functional tagging, 2-photon and multiphoton imaging, and miniscope-plus-GRIN-lens imaging in awake, behaving animals.
Theoretical Neuroscience
Computational modeling that links population-level neural ensemble activity to behavior, building the quantitative theory needed to interpret what large-scale recordings actually mean.
Current Activity
This area in action at Dartmouth
Centered today on the Murray lab's computational program and its external collaborations, with room built in to grow.
Computational modeling of neural circuits (Murray lab)
The Murray lab builds computational models of neural circuits and cognitive function, including working memory, thalamocortical organization, and brain-state dynamics, forming the theoretical core of this priority area at Dartmouth today.
Cortical microcircuitry and working-memory modeling
An ongoing collaboration with Yale, supported by an NSF center grant, developing models of how cortical microcircuits sustain working memory.
Credit assignment in reinforcement learning
A collaboration with Johns Hopkins, funded by an NIH R01, using monkey neuronal recordings to study how the brain assigns credit for outcomes during learning.
Autism and learning heterogeneity
A collaboration with UCLA Psychiatry, supported by a SFARI grant, studying heterogeneity in learning processes relevant to autism.
A growing area, and an active search
Neural population coding and circuits research is newer at Dartmouth than the cluster's human-neuroimaging work, and it is a deliberate growth priority. The cluster is actively searching for a third endowed faculty member whose work will bridge computational and systems neuroscience, further strengthening ties between human neuroimaging and animal-model circuit research.
Curious which Dartmouth labs already work in circuit-level and computational neuroscience?
Explore the Lab Network →Directory
The Dartmouth Neuroscience Lab Network
A directory of neuroscience-related labs across Dartmouth, from Psychological and Brain Sciences to Thayer Engineering to Geisel Medicine. Group labs by department, shared technique or shared topic.
Our Community
The People Behind the Cluster
Leadership
Steering Committee
The faculty and administrative leaders who set the cluster's scientific direction and stewardship priorities.
Tor Wager
Chair, Steering Committee
Dept. of Psychological and Brain Sciences
Leads the cluster's human brain stimulation and neuroimaging program, with a research focus on pain, placebo effects, and brain stimulation.
John Murray
Steering Committee
Dept. of Psychological and Brain Sciences
Builds computational models of neural circuits and cognitive function, with a focus on decision-making, working memory, and thalamocortical organization.
Jim Haxby
Steering Committee
Dept. of Psychological and Brain Sciences
A founding figure in multivariate pattern analysis of fMRI data, pioneering techniques for decoding fine-grained patterns of brain activity.
Working Across Campus
Affiliated Departments and Partners
The cluster's research spans several Dartmouth schools, departments, and shared facilities.
Cluster Timeline
Past and Upcoming Events
This timeline draws from the cluster's recent activity (publications, infrastructure, and public talks) and from what's ahead. It starts with what's coming next, then traces the record back to the cluster's earliest years.
What's Next
On the Horizon
Directions the cluster is actively pursuing. Dates aren't fixed, so each entry is framed as a near-term goal rather than a firm calendar date.
2026–2027Upcoming
A New Clinical Trial for Cancer Pain
Through the Dartmouth Innovation Accelerator for Cancer, the team is translating its tDCS neurostimulation advances into a clinical trial for oncology patients living with cancer pain.
2026–2027Upcoming
Growing ANIC with GPU-Powered AI Models
The Affective Neuroimaging Consortium (ANIC) continues to expand, and the cluster's new dual-H100 GPU compute node will power AI models aimed at predicting feeling states directly from neural data.
Coming this yearUpcoming
Murray Lab's First EEG + fMRI Experiments
Building on the lab's 2026 eye-tracking pilot work, the Murray lab plans its first combined EEG and fMRI experiments at Dartmouth, testing models of attention and decision-making.
OngoingUpcoming
Searching for a Third Endowed Faculty Member
The cluster is actively searching for a third endowed faculty member whose work will bridge computational and systems neuroscience, further strengthening ties between human neuroimaging and animal-model circuit research.
2026–2027Upcoming
Supporting a Campus-Wide Neuroscience Institute
The cluster is lending its expertise to Dartmouth's emerging, cross-campus integrated Neuroscience Institute initiative, which aims to translate neuroscience research into treatments for brain disorders: from fMRI-guided neurostimulation to clinical neuromodulation for epilepsy and serious mental illness.
The Record
Past Events
Publications and infrastructure milestones since the cluster's earliest years, most recent first.
2026
2026
New Book: Elements of fMRI Imaging
Tor Wager's book, Elements of fMRI Imaging, entered production at MIT Press.
2026
On the Road with President Beilock
Tor Wager and undergraduate researcher Jason Davis were interviewed by Dartmouth President Sian Leah Beilock as part of her “On the Road” series, hosted by the Dartmouth Club of New York.
2026
New Findings on Brain Stimulation for Pain
The human brain stimulation program, run in collaboration with Thayer School of Engineering, published two papers in the journal Pain. A related randomized clinical trial, under review at Science Translational Medicine, found that precentral gyrus stimulation produced substantial pain reductions.
2026
Dartmouth Gains Early Access to Temporal Interference Stimulation
Dartmouth became one of the first universities worldwide with Temporal Interference stimulation (tTIS) access, through the IT’IS Foundation's (Zurich) Early Adopter program.
2026
Murray Lab's First Human Study at Dartmouth
The Murray lab conducted its first human behavioral study at Dartmouth, using eye tracking to study reinforcement learning and attention allocation. A related NSF grant with Viola Stoermer (PBS), on attention in learning, was recommended for funding.
2026
24 Peer-Reviewed Papers So Far in 2026
The Wager lab published 24 peer-reviewed papers in 2026 alone, among them the three publications below.
2026
Targeted Placebo Effects Mapped in Science
A Science paper from the Wager lab identified targeted placebo effects in specific brainstem body sites, evidence that placebo responses are organized with far more anatomical precision than previously understood.
2026
Insula Mapped Across 540 Participants in Nature Communications
A Nature Communications paper mapped the insula's functional organization using fMRI data from 540 participants across 36 cohorts, one of the largest studies of this brain region to date.
2026
A Meta-Analysis of Placebo Effects in Nature Communications
A second Nature Communications paper presented a meta-analysis of placebo effects across studies, consolidating evidence on how and when placebo responses occur.
2026
Moore Hall Neurostimulation Facility Opens
A new multi-technique neurostimulation facility (supporting TMS, tDCS, and Temporal Interference stimulation) opened inside the Cognitive and Affective Neuroscience Lab in Moore Hall.
2026
New Courses for a New Generation
John Murray launched a new graduate course, “Neural Computation.” Tor Wager taught “Mind, Brain, and Health,” a culminating-experience course on brain–body medicine.
2026
Dual-H100 GPU Compute Node Deployed
The cluster partnered with Dartmouth Research Computing to deploy a dual-H100 GPU compute node, expanding capacity for large-scale modeling of neural and behavioral data.
2026
Affective Neuroimaging Consortium Reaches 54 Labs Worldwide
The Affective Neuroimaging Consortium (ANIC), which the cluster helps lead, has grown to 54 collaborating laboratories worldwide and more than 3,000 research participants. It's one of the most comprehensive functional-imaging datasets of its kind, spanning pain, pleasure, aversive stimuli, and food and drug cues.
2025
2025
Five-Year Follow-Up Published in JAMA Psychiatry
A five-year follow-up study on Pain Reprocessing Therapy for chronic back pain was published in JAMA Psychiatry, extending the lab's original 2021 trial.
2023
2023
A Banner Year for Publications
The Wager lab published 21 peer-reviewed papers in 2022, with 9 more out by mid-2023.
2023
First Neuroimaging Signature for Drug Craving
The lab published the first neuroimaging-based signature for drug craving, an objective marker of the neural patterns underlying persistent drug use and relapse risk.
2023
Large Trial Nearly Eliminates Chronic Back Pain
In a large clinical trial, a four-week psychological and behavioral treatment eliminated or nearly eliminated chronic back pain in roughly two-thirds of patients, with gains maintained at one-year follow-up.
2023
The Most Comprehensive Analysis of Placebo Mechanisms to Date
The lab published its most comprehensive analysis yet of the brain mechanisms behind placebo effects in pain, showing that placebos engage active healing processes.
2021
2021
15 Papers in Neuron, Nature Communications, and More
The Wager lab published 15 peer-reviewed papers in journals including Neuron, Nature Communications, Nature Reviews Neuroscience, Nature Medicine, and JAMA Psychiatry.
2021
A Landmark 150-Patient Pain Trial
In a landmark chronic-pain clinical trial of 150 patients, a novel psychological and behavioral treatment eliminated or nearly eliminated pain in about 75% of participants, with gains lasting a year or more.
2021
tDCS Arrives at Dartmouth
The Wager lab brought Transcranial Direct Current Stimulation (tDCS) to Dartmouth, in collaboration with Thayer School of Engineering.
2021
Faculty Search Launched
The cluster launched an active search for an additional tenured or tenure-track professor and a staff research scientist, to expand its computational capacity.