Lab of Rebecca Jordan at the University of Edinburgh
The locus coeruleus projects densely throughout the brain, receives diverse long range and local inputs, and responds to many stimuli, including unexpected sensory input. However, little is known about what this system computes. We aim to understand the computational role of the locus coeruleus in predictive learning, and determine how its circuitry enables its function.
Computation in the locus coeruleus
Mechanisms of learning cortical predictions
Prediction errors represent discrepancies between expected and actual sensory input and are thought to drive learning of predictions. Prediction errors have been found in the activity of cortical neurons and neuromodulatory systems. We aim to test how these signals drive plasticity using virtual reality systems alongside recording and manipulation of neural activity.
Predictive learning in neurodevelopmental disorder models
The sensory symptoms of neurodevelopmental disorders, such as sensory overload, could arise from imbalanced integration of sensory input and predictions. This could arise from improper neuromodulation, excitatory-inhibitory imbalance, or changes to plasticity processes. We aim to assess these ideas in mouse models of neurodevelopmental disorders, such as Fragile X syndrome.