Enduring Borderlands: the Marches of Ireland and Wales in the Early Modern Period

This joint chapter explores similarities and differences between two borderlands within the early modern ‘British’ state – the marches of Ireland and Wales. In some respects, the two regions were very different, most fundamentally because the Irish march remained militarised throughout the Tudor period, while Welsh society was markedly more peaceful. However, there was also much in common. In the later middle ages both marches were frontiers between the expanding Anglo-Normans and native Celtic society. The notion that the march separated ‘civility’ from ‘savagery’ was an enduring one: despite the efforts of the Tudors to impose centralisation and uniformity throughout its territories, there remained institutions, structures of power, and mentalities which ensured that both sets of marches were still in existence by the end of the 16th century. This chapter explores the reasons for the endurance of these borderlands, and indicates how political reforms of the 16th century caused the perception – and sometimes the very location – of the marches to alter.

Temporal difference models describe higher-order learning in humans.

The ability to use environmental stimuli to predict impending harm is critical for survival. Such predictions should be available as early as they are reliable. In pavlovian conditioning, chains of successively earlier predictors are studied in terms of higher-order relationships, and have inspired computational theories such as temporal difference learning. However, there is at present no adequate neurobiological account of how this learning occurs. Here, in a functional magnetic resonance imaging (fMRI) study of higher-order aversive conditioning, we describe a key computational strategy that humans use to learn predictions about pain. We show that neural activity in the ventral striatum and the anterior insula displays a marked correspondence to the signals for sequential learning predicted by temporal difference models. This result reveals a flexible aversive learning process ideally suited to the changing and uncertain nature of real-world environments. Taken with existing data on reward learning, our results suggest a critical role for the ventral striatum in integrating complex appetitive and aversive predictions to coordinate behaviour.