Early neural dynamics of visual word recognition

For a skilled reader, visual word recognition can be completed within several hundred milliseconds. There is evidence that the left inferior frontal cortex is activated by visual words in the first 300 ms after stimulus onset; additionally, there is evidence for early top-down feedback from this frontal region to ventral occipito-temporal cortex during visual word recognition. Using magnetoencephalography (MEG), this thesis sought to examine early neural dynamics of visual word recognition by examining the early stage inter-regional connectivity and time course of visual word recognition. In Chapter 1, I review studies of the neural correlates and relevant neural models of visual word recognition; in particular, two models on the ventral occipito-temporal cortex in visual word recognition with contrasting views on the role of top-down feedback are examined. I then introduce dynamic causal modeling (DCM), a crucial neuroimaging method for examining directional influences of one brain area to another. Next I review the neuroimaging studies of visual word recognition focusing on its time course and also highlight the importance of examining early brain activity of visual word recognition. Finally, I propose the research questions to be addressed in this thesis: What is the nature of early top-down feedback from frontal to ventral occipito-temporal cortex during visual word recognition? How task goals modulate the early top-down feedback? How task goals modulate the time course of visual word recognition? These questions are examined in three empirical chapters. Using a semantic categorisation task, Chapter 2 examines the nature of top-down feedback from the left inferior frontal gyrus (LIFG) to the left ventral occipito-temporal cortex (LvOT) during the first 200 ms visual word recognition. The results revealed that the LIFG-to-LvOT connection was stronger for real words than for pseudowords, and stronger for false fonts than for consonant strings in both 1-150 ms and 1-200 ms time-windows, indicating that both lexical-semantic and surface letter information influence early top-down feedback. Furthermore, the LIFG-to-LvOT connection was stronger for pseudowords than for consonant strings in the 1-200 ms time-window, indicating that compared with lexical-semantic and surface letter information, the influences of phonological information occur later. By comparing a non-linguistic visual discrimination task (is it a hash string?) with the semantic categorisation task (is it an animal word?) used in Chapter 2, Chapter 3 examines how task goals modulate the early LIFG-to-LvOT feedback during the first 200 ms visual word recognition. The results revealed that the LIFG-to-LvOT connection was stronger for real words than for pseudowords in both 1-150 ms and 1-200 ms time-windows in the discrimination task, and this was similar to that in the semantic task, indicating that the influences of lexical-semantic information on this feedback are independent of task goals. However, in the discrimination task the LIFG-to-LvOT connection was stronger for consonant strings than for pseudowords in the 1-200 ms time-window and was stronger for consonant strings than for false fonts in the 1-150 ms time-window, and this was opposite to that in the semantic task, indicating that the influences of letter and phonological information on the early feedback are dependent on task goals. Using the data from the previous two chapters, Chapter 4 examines how task goals modulate the on-line time course of visual word recognition by examining the first 500 ms time course data during the linguistic semantic task and the non-linguistic discrimination task. A behavioural version of each MEG experiment with one task is also reported on. The MEG and behavioural results established that an emphasis on high-level linguistic information in a linguistic task sensitise early neural responses to linguistic properties, whereas an emphasis on low-level visual feature detection in a non-linguistic task sensitise early neural responses to physical appearance. This thesis has established that lexical-semantic, phonological, and letter properties all can trigger early top-down feedback during visual word recognition, but occur differently across time. Task goals with different emphases strongly bias early top-down feedback and also modulate the time course of visual word recognition.