Central alexia (CA) is an acquired reading disorder co-occurring with a generalised language deficit (aphasia). In my thesis, through a series of three experiments, I aim to explore the reading network of 23 patients with CA and how it responds to a training application (app) called iReadMore. It is hoped that improving our understanding of the mechanisms of neural plasticity following therapy for post-stroke CA will lead to the development of more effectively targeted therapies. The introduction outlines models of reading and our current understanding of neuroplasticity in post-stroke aphasia. Of particular importance is the view of aphasia as a network disorder. Accordingly, this thesis investigates the effective connectivity observed when reading, rather than activation within individual regions. In the first results chapter, I compare the reading networks of CA and control participants using dynamic causal modelling (DCM) for magnetoencephalography (MEG) data. This analysis aims to identify potentially damaged and adapted connections within the reading network of CA participants. I then report the results of a clinical trial investigating the effects of iReadMore training, paired with anodal transcranial Direct Current Stimulation (A-tDCS). This chapter aims to identify if iReadMore training improves single word reading aloud, and if A-tDCS provides an additive effect on training. In the final results chapter, I use DCM for MEG to explore training induced changes in the reading network of CA patients. This chapter aims to identify the neural mechanisms by which iReadMore training is effective. In chapter six, I take each of the results chapters in turn and discuss the main findings, limitations and potential future research directions. I also discuss reading therapy for CA and the clinical use of DCM as two broader topics touched upon by this thesis
