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FLAP MURI

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    • Sensing Complex Environments
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Techniques, Modeling, and Analysis

In order to discover principles of rapid decision making in complex environments, the FLAP MURI team seeks to develop novel experimental methods, computational models, and data analysis techniques.

Projects

Optimal coding strategies shaped by projection convergence and divergence in feedforward networks

Zach Mobille, Usama bin Sikandar, Simon Sponberg, Hannah Choi

RBM-based cross subject transfer learning

Suya Wu, Marko Angjelichinoski, Haoming Yang, Vahid Torokh, Simon Sponberg

Attentional learning and population structure in AL recordings

Haoming Yang, Pramod KC, Simon Sponberg, Jeff Riffell, Vahid Torokh

Development of new neurogenetic tools in moths

Anandrao Ashok Patil and Jeff Riffell

Identifying age related differences in flight performance

Elina Barredo, Haoming Yang, Suya Wu, Simon Sponberg, Vahid Tarokh, Jamie Theobald

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