Princeton's Ph.D. in Neuroscience offers an integrative approach combining biology, psychology, engineering, and computation to explore brain function and dysfunction. These dissertation topics reflect the diverse and impactful areas available for doctoral research.
Neural Encoding of Sensory Stimuli in the Visual Cortex
Functional Brain Connectivity in Cognitive Control Networks
Machine Learning Models for Decoding Motor Intentions
Dopaminergic Signaling and Reward-Based Learning
Optogenetic Manipulation of Memory Circuits
Neuroplasticity in Post-Stroke Motor Recovery
Role of Microglia in Neuroinflammatory Disorders
Computational Models of Decision-Making Under Uncertainty
Neural Oscillations and Sleep-Dependent Memory Consolidation
Emotion Regulation Mechanisms in Prefrontal-Amygdala Circuits
Hippocampal Place Cells in Spatial Navigation Tasks
Brain-Computer Interfaces for Assistive Technologies
Gene Expression Dynamics in Neurodegenerative Disease Progression
Neuroimaging Biomarkers for Early Detection of Alzheimer’s
Synaptic Pruning and Neural Developmental Disorders
Resting-State fMRI Analysis of Attention Networks
Neuroethics and the Use of Neural Implants
Sensorimotor Integration in Reaching and Grasping Tasks
Predictive Coding in Visual Perception Pathways
Plasticity of Auditory Circuits in Language Acquisition
Collexa provides guidance to Princeton Ph.D. students on neuroimaging analysis, lab experiment design, EEG/fMRI datasets, neural simulations, and manuscript preparation in the field of neuroscience.
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