The curious case of rapid entrainment after jet lag and how to get a single neuron to remember
This talk will cover two stories involving mathematical modelling (and some experiments) in neural systems.
In the first, we will discuss the re-entrainment problem of how our bodies synchronise with the external environment following travel across time zones or shift work. To do so, we analyse a two-dimensional variant of the Forgers-Jewett-Kronauer model, which describes changes in core body temperature and neural activity in the brain region responsible for circadian rhythms, forced by a 24-hour light/dark cycle. This model, which has previously been used to explain the East-West asymmetry in jet lag severity after travel, predicts a counter-intuitive rapid re-entrainment for sufficiently bright daylight. We explain this phenomenon via continuation of invariant manifolds of fixed points of a 24-hour stroboscopic map and explore the consequence of the arrangement of such manifolds on re-entrainment in a variety of scenarios.
In the second story, we will explore the capability of a neuron that is synaptically coupled to itself, to store and repeat patterns of precisely timed spikes, which we regard as single cell 'memories'. Drawing on analogies from semiconductor lasers, we append a delayed self-coupling term to the oft studied Morris-Lecar model of neuronal excitability and use bifurcation analysis to predict the number and type of memories the neuron can store. These results highlight the delay period as an important period parameter controlling the storage capacity of the cell. Finally, we use the dynamic clamp protocol to introduce self-coupling to a mammalian cell and confirm the existence of the spiking patterns predicted by the model analysis.
Speaker
Kyle Wedgwood, Univesity of Exeter
How to attend
If not a member of the Dept. Mathematical Science at the University of Essex, you can register your interest in attending the seminar and request the Zoom's meeting password by emailing Dr Jesus Martinez-Garcia (jesus.martinez-garcia@essex.ac.uk)