Abstract
While perception improves with practice, the brain is faced with a Goldilocks challenge in balancing the specificity vs. generality of learning. Learning specificity is classically established (e.g. Karni & Sagi, 1991, PNAS 88, 4966-4970), however, recent work also reveals generalisation that promotes the transfer of training effects (e.g., Xiao et al, 2008, Cur Biol, 18, 1922-26). Here I will discuss how we can understand the neural mechanisms that support these opposing drives for optimising visual processing. I will discuss work that uses perceptual judgments in visual displays where performance is limited by noise added to the stimuli (signal-in-noise tasks) or clearer displays that push observers to make fine differentiation between elements (feature difference tasks). I will review work that suggests different foci of fMRI activity during performance of these types of task (Zhang et al, 2010, J Neurosci, 14127-33), and then describe how we have used psychophysical tests of learning transfer to understand the mechanisms that support learning (Chang et al, 2013, J Neurosci, 10962-71). Finally, I will discuss recent TMS work that implicates a wide high-level network involved in generalisation of training between tasks.