Christopher D Harvey
Harvard University, MA·Neuroscience
How does the brain learn to make good decisions, notice when it is wrong, and change course? Choosing a route, linking what we sense to what we do, and switching rules when outcomes change all depend on brain circuits in the cortex, the brain's outer layer.
- Fields
Neuroscience
Biology
Computer Science
- Topics
decision-making
spatial navigation
cognitive flexibility
- Grants
- 3 known grants, through Mar 2031
What they work on
- Map effective connectivity among functionally identified neurons in the posterior parietal cortex during a virtual-reality navigation decision task, using cellular-resolution optogenetics to stimulate small groups of neurons and testing wiring motifs predicted by decision-making theories.
- Determine the activity patterns, connectivity and causal roles of inhibitory neurons in the posterior parietal cortex during navigational decision-making.
- Identify the molecular plasticity mechanisms activated during navigational learning and test how they reorganize connections within posterior parietal cortex circuits.
- Test whether recurrent connections amplify choice signals through inhibitory competition motifs and create choice-informative activity sequences, by combining optogenetic connectivity measurements with multiple classes of computational models.
- Test whether a subtype of somatostatin inhibitory interneurons carries error-related signals across posterior parietal, retrosplenial and visual cortex, whether it is needed for learning from errors, and how it changes neighboring neurons.
- Test whether the mediodorsal thalamus is a focal point for outcome-error signals, by surveying brain-wide activity, testing whether it is required for rule switching, and measuring how its signals update cortical activity.
More about the research
These abilities are disrupted in many neurological disorders, including Alzheimer's disease. Yet little is known about how specific cell types and the wiring between neurons carry out these computations. The research combines precise light-based control of neurons, recordings of neural activity during decision tasks in virtual reality, and computational models. Its aim is to explain decision-making and learning at the level of connections, cell types and circuits.
Why it matters
Spatial navigation, decision-making and forming accurate expectations are core cognitive abilities that are disrupted in many neurological disorders and diseases, including Alzheimer's disease. By identifying the specific cell types, wiring patterns, plasticity programs and circuits involved, this work could build a foundation for understanding how these abilities fail in disease. It also contributes tools and models for studying cognition more broadly.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Closest labs
Najib Majaj
New York University, NY·Neuroscience
Compare neural computations and behavioral algorithms in macaques foraging head-free in a foraging room with those during head-fixed navigation in virtual reality, to test whether restrained lab conditions differ from naturalistic ones.
David Tank
Princeton University, NJ·Neuroscience
Identify which task features (active navigation, passive navigation, or visual stimulation) produce sequential neural activity, by recording from relevant mouse brain regions during tasks that isolate each feature.
Aaron Kuan
Yale University, CT·Neuroscience·Early-career
Improve the resolution of X-ray nano-holography (XNH), which reconstructs 3D structure from interference patterns of coherent X-rays, at a fourth-generation synchrotron source so that synaptic connections between neurons are directly visible.
The school
Harvard University: 42 labs on PI Pages, $1.5B a year on research, 712 research doctorates a year.
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