Modulatory effects of pheromone on olfactory learning and memory in moths.

Pheromones are chemical communication signals known to elicit stereotyped behaviours and/or physiological processes in individuals of the same species, generally in relation to a specific function (e.g. mate finding in moths). However, recent research suggests that pheromones can modulate behaviours, which are not directly related to their usual function and thus potentially affect behavioural plasticity. To test this hypothesis, we studied the possible modulatory effects of pheromones on olfactory learning and memory in Agrotis ipsilon moths, which are well-established models to study sex-pheromones. To achieve this, sexually mature male moths were trained to associate an odour with either a reward (appetitive learning) or punishment (aversive learning) and olfactory memory was tested at medium- and long-term (1 h or 1.5 h, and 24 h). Our results show that male moths can learn to associate an odour with a sucrose reward, as well as a mild electric shock, and that olfactory memory persists over medium- and long-term range. Pheromones facilitated both appetitive and aversive olfactory learning: exposure to the conspecific sex-pheromone before conditioning enhanced appetitive but not aversive learning, while exposure to a sex-pheromone component of a heterospecific species (repellent) facilitated aversive but not appetitive learning. However, this effect was short-term, as medium- and long-term memory were not improved. Thus, in moths, pheromones can modulate olfactory learning and memory, indicating that they contribute to behavioural plasticity allowing optimization of the animal's behaviour under natural conditions. This might occur through an alteration of sensitization.

Probabilistic vs linear blending approaches to shared control for wheelchair driving.

Some people with severe mobility impairments are unable to operate powered wheelchairs reliably and effectively, using commercially available interfaces. This has sparked a body of research into "smart wheelchairs", which assist users to drive safely and create opportunities for them to use alternative interfaces. Various "shared control" techniques have been proposed to provide an appropriate level of assistance that is satisfactory and acceptable to the user. Most shared control techniques employ a traditional strategy called linear blending (LB), where the user's commands and wheelchair's autonomous commands are combined in some proportion. In this paper, however, we implement a more generalised form of shared control called probabilistic shared control (PSC). This probabilistic formulation improves the accuracy of modelling the interaction between the user and the wheelchair by taking into account uncertainty in the interaction. In this paper, we demonstrate the practical success of PSC over LB in terms of safety, particularly for novice users.