Matthew Lehet

Matthew Lehet serves as Assistant Professor of Psychology in the Department of Psychology at Chatham University's College of Arts and Sciences, joining the institution in 2024. His research bridges cognitive neuroscience, clinical psychology, and linguistic theory with a focus on schizophrenia and speech processing mechanisms.

His academic credentials include:

• Ph.D. in Cognitive Psychology from Carnegie Mellon University (2017)
• B.A. in Psychology from Reed College (2008)

Dr. Lehet's research investigates language-thought interactions, mental health correlates of inner speech, corollary discharge mechanisms in perception, and human neuroscience applications. His work employs neuroimaging and behavioral paradigms to examine how predictive neural processes influence perception, particularly in schizophrenia spectrum disorders. Key methodologies include fMRI connectivity analyses and speech perception experiments exploring statistical learning.

Analysis of his 2017-2025 publications reveals three convergent research trajectories: (1) schizophrenia-related neural connectivity abnormalities in thalamocortical and oculomotor networks, (2) corollary discharge mechanisms in perceptual prediction, and (3) dimension-based statistical learning in speech processing. These strands demonstrate consistent integration of cognitive theory with clinical neuroscience.

His scholarly contributions have been recognized through prestigious awards:

• Acoustical Society of America Stetson Fellowship
• Multimodal Neuroimaging Training Program
• Behavioral Brain Research Training Program
• Presidential Fellowship at Carnegie Mellon University
• University of Pennsylvania Cognitive Neuroscience Summer Program
• Veteran’s Administration Summer Fellowship
• Reed College Miller Grant

Dr. Lehet has secured significant research funding through competitive fellowships and training grants supporting his neuroimaging and behavioral studies. While no formal advisees are documented, his training program affiliations indicate mentorship experience in multimodal neuroscience methodology. His work continues to advance understanding of predictive coding mechanisms in both typical and clinical populations.