Topic: timescales

Claire Adjiman examines artificial intelligence across chemical discovery, product design, process design and process operation. The seminar explains how the appropriate use of AI changes with each activity’s objectives, available data and timescales. Examples across the product lifecycle illustrate potential benefits and unresolved challenges for chemical industries.

Timescales characterize how fast the observables change in time. In neuroscience, they can be estimated from the measured activity and can be used, for example, as a signature of the memory trace in the network. I will first discuss the inference of the timescales from the neuroscience data comprised of the short trials and introduce a new unbiased method. Then, I will apply the method to the data recorded from a local population of cortical neurons from the visual area V4. I will demonstrate that the ongoing spiking activity unfolds across at least two distinct timescales - fast and slow - an