This K24 grant renewal is requested to support the mentoring activities of Dr. Maria Luisa Gorno Tempini, a behavioral neurologist and cognitive neuroscientist. Dr. Gorno Tempini is a leading researcher and clinician in the fields of neurology and the neuroscience of language, with specific expertise in atypical neurodegenerative diseases that present as speech and language disorders. She mentors a talented group of clinicians and researchers to study and treat Primary Progressive Aphasia (PPA) and investigate the neural basis of language. Dr. Gorno Tempini has a proven track record of success in mentoring both clinicians and scientists in patient- oriented research (POR) related to speech and language disorders. The goals of this proposal are to support time for Dr. Gorno Tempini to mentor a growing number of increasingly diverse clinicians and researchers interested in neurodegenerative language disorders, to extend her impact as a mentor at UCSF, and to pursue novel lines of research in PPA. Leveraging the resources available at the UCSF Memory and Aging Center (MAC), the Global Brain Health Institute, and the UCSF Clinical and Translational Science Institute, she will mentor clinicians, faculty, postdoctoral scholars, and scientists with particular attention to cultivating diversity, equity, and inclusion in her laboratory, the university, and the profession at large. She will sustain her comprehensive mentoring system that features one-on-one mentoring, supervision of clinicians in patient diagnosis and care, and group mentoring activities. She will update and extend that system with opportunities for training with colleagues in speech and data science and a focus on mentoring more advanced junior colleagues as emerging mentors themselves. Dr. Gorno Tempini's experience in basic cognitive neuroscience and neurological methodologies and her increasingly nuanced leadership expertise uniquely position her to benefit a diverse group of trainees. The research project proposed here will develop automatic, efficient, and objective methods to measure speech production in PPA. The study will apply acoustic analysis scripts and automatic speech recognition to five minutes of audio recordings collected from 500 well-characterized PPA patients and employ dynamic speech MRI to identify anatomical biomarkers of vocal tract movements corresponding to speech articulation errors. This will lead to earlier detection of speech deficits; improved characterization of clinical syndromes; and more detailed, objective, and efficient outcome measures to track progression and, in the future, response to treatment. Machine learning analyses of acoustic measures and imaging data collected through other MAC projects will provide novel tools for prediction of post-mortem pathology and new knowledge on the neural basis of speech. This grant will be instrumental in supporting the pursuit of Dr. Gorno Tempini's goals to mentor the next generation of clinician scientists in ...