Words in sentences that are more predictable are read more quickly and processed more easily. Many lines of research suggest readers are able to activate features of upcoming words before they appear (known as "pre-activation"); however, lots of research has focused on the consequences of predictions being confirmed or violated, rather than how this pre-activation process works. We are interested in identifying and examining neural activity prior to a word's occurrence that is indicative of word pre-activation, and use multiple analysis methods (e.g., time-frequency analyses, multivariate decoding) to pursue this line of research.

Several lines of research have identified changes in behavior or neural activity at the time of a prediction being confirmed or violated, but little work has investigated how cognitive processing or behavior changes following a prediction confirmation or violation. Work in our lab has identified that our memories for words and sentences that we previously read are impacted by the degree to which those words violated our expectations. Additionally, individuals have a tendency to falsely remembering seeing words that they predicted, but never actually read - a "false memory" for predicted words. We are interested in further investigating the factors that contribute to false memories for predicted stimuli, other cognitive or behavioral processes that are impacted by prediction, and the neural mechanisms involved in changing or updating representations based on outcomes of predictions.

A primary mission of cognitive neuroscience is to "map" particular neural responses, or activity in certain brain areas, to cognitive processes (e.g. memory, attention, etc). This is challenging in multiple ways - we must have well-defined cognitive processes to map brain responses onto, but we must also have a thorough understanding of the physiological signals that we measure. A long-standing interest in the lab more on the methodological side of cognitive research has been to better understand these physiological signals (e.g., ERPs, oscillations, pupil dilation) that we measure. We investigate this through the application of more advanced analytic techniques, such as multivariate decoding and source separation, to electrophysiological and pupillometric data.

One of the most rewarding aspects of a career in scientific research is also one of the most important for the integrity and success of the research process - collaboration with fellow researchers. Often times, scientists working in different labs are conducting research on the same mechanism or process without even realizing it, due to a lack of communication or usage of different terminology. Our understanding of this mechanism would likely increase if these scientists worked together! In this career, not only do we have the opportunity to meet and befriend like-minded individuals with similar goals and purposes, but also by working together we bring together novel ideas and scientific viewpoints, as well as ensure that everyone involved in the collaborative work is doing the best work they can and maintaining ethical and responsible research practices. At the HECL, we are ardent proponents of engaging in collaborative cognitive neuroscience, either by sharing data and code, meeting with others and giving talks or workshops, and even working together on research projects. 

Interested in working with us?