Precision

Although automated systems for rodent behavior annotation exist, specific behaviors are still scored by hand. We introduce a novel AI-assisted annotation tool, SmartAnnotator, which helps the researcher annotate behaviors through active learning. Active learning reduces annotation effort by automatically selecting behavioral events whose annotation will maximally improve classification. Instead of playing a video from start to end and simultaneously scoring behavior, the researcher is presented short video clips, each showing a single behavioral event. The events are derived from clustered low

Many engineered and biological systems must trade off performance and energy use, and the brain is no exception. While there are theories on how activity levels are controlled in biological networks through feedback control (homeostasis), it is not clear what the effects on population coding are, and therefore how performance and energy can be traded off. In this talk we will consider this tradeoff in auto-encoding networks, in which there is a clear definition of performance (the coding loss). We first show how SNNs follow a characteristic trade-off curve between activity levels and coding lo

Rapidly changing inputs such as visual scenes and auditory landscapes are transmitted over several synaptic interfaces and perceived with little loss of detail, but individual neurons are typically “noisy” and cortico-cortical connections are typically “weak”. To understand how information embodied in spike train is transmitted in a lossless manner, we focus on a single synaptic interface: between pyramidal cells and putative interneurons. Using arbitrary white noise patterns injected intra-cortically as photocurrents to freely-moving mice, we find that directly-activated cells exhibit precisi

…and discuss what we can learn about precision, plasticity and possible patterns in mammalian neuronal circuits.