Caroline Haimerl is a postdoctoral fellow at the Champalimaud Foundation in Lisbon, Portugal, where she works with Joseph Paton and Christian Machens.
Haimerl has a bachelor of science in statistics and psychology, both from the University of Vienna, and obtained her Ph.D. in computational neuroscience from New York University. Under the supervision of Eero Simoncelli and Cristina Savin, she constructed a theory for task-dependent visual information routing in hierarchical brain networks and proposed a new functional role for shared fluctuations in neural activity.
In her current postdoctoral research, Haimerl investigates how complex, flexible behavior is enabled by hierarchical representations and parallel learning in corticostriatal circuitry. She uses reinforcement learning and modular neural network models and collaborates with experimentalists to complement her theory-driven models with neural and behavioral data analysis.
In her future work, Haimerl plans to study how sensory information bottlenecks, task rules and behavioral repertoires jointly shape neural representations across multiple brain areas, allowing action control that spans multiple spatiotemporal scales.
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