Publications by authors named "Isabel D'Alessandro"

Gain control is a process that adjusts a system's sensitivity when input levels change. Neural systems contain multiple mechanisms of gain control, but we do not understand why so many mechanisms are needed or how they interact. Here, we investigate these questions in the Drosophila antennal lobe, where we identify several types of inhibitory interneurons with specialized gain control functions.

View Article and Find Full Text PDF

In neural networks that store information in their connection weights, there is a tradeoff between sensitivity and stability. Connections must be plastic to incorporate new information, but if they are too plastic, stored information can be corrupted. A potential solution is to allow plasticity only during epochs when task-specific information is rich, on the basis of a 'when-to-learn' signal.

View Article and Find Full Text PDF

The degenerin channels, epithelial sodium channels, and acid-sensing ion channels (DEG/ENaC/ASICs) play important roles in sensing mechanical stimuli, regulating salt homeostasis, and responding to acidification in the nervous system. They have two transmembrane domains separated by a large extracellular domain and are believed to assemble as homomeric or heteromeric trimers. Based on studies of selected family members, these channels are assumed to form nonvoltage-gated and sodium-selective channels sensitive to the anti-hypertensive drug amiloride.

View Article and Find Full Text PDF

Spatial maps in the brain are most accurate when they are linked to external sensory cues. Here, we show that the compass in the Drosophila brain is linked to the direction of the wind. Shifting the wind rightward rotates the compass as if the fly were turning leftward, and vice versa.

View Article and Find Full Text PDF

In the Drosophila brain, 'compass' neurons track the orientation of the body and head (the fly's heading) during navigation . In the absence of visual cues, the compass neuron network estimates heading by integrating self-movement signals over time. When a visual cue is present, the estimate of the network is more accurate.

View Article and Find Full Text PDF