Princeton Neuroscience Institute

Boulanger Lab

• Developing and applying computational strategies to predict protein interactions    
• Proteomic, structural and sequence-based approaches to evaluating selective pressure at  the single-molecule level

•  Building robots to test theories of the brain
•  Spectral analysis of neurophysiological data
•  Examining the functional interactions between brain areas
•  Using artificial life to learn how communication between agents evolves

• Developing mutual information based methods to characterize the flow of verbal information across brains.
• Building set of analysis tools for processing intracranial EEG signal.

• Neuromechanics of insect locomotion
• Modeling of neural dynamics, decision making, and cognitive control

• Building computational models of learning and memory
• Developing methods for decoding cognitive state information from brain imaging data

• Developing MRI/TMS system for interrogating and observing the brain function simultaneously
• Developing Lapped transform based reconstruction algorithm for real-time fMRI with massive parallel receive array

• Designing and simulating computational models of learning and decision-making
• Sophisticated analysis or behavioral and neural (fMRI) data from decision making experiments, using computational methods

• Building computational models of learning and memory
• Developing methods for decoding cognitive state information from brain imaging data

• Building circuit-level computational models of motor guidance
• Developing methods to monitor fine movements during optical imagingexperiments
• Developing methods for segmenting noisy imaging data obtained during optical physiology experiments
• Designing and controlling instrumentation for optical manipulation of neural circuits