Ed Bartlett

Title:

Professor

PhD Granting Institution:

University of Wisconsin-Madison

Contact:

Email Address: ebartle@purdue.edu
Office Phone: 765-496-1425
Lab Website Link: https://engineering.purdue.edu/CAPLab

Primary Training Group:

Integrative Neuroscience

Secondary Training Groups:

Computational and Systems Biology, Membrane Biology

Research Areas:

neuroscience, neurobiology, sensory systems, electrophysiology, hearing, neurodegeneration, aging

Current Projects:

1) We are testing how different types of noise exposure differing in intensity and duration affect hearing and recovery from exposure over time. Noise exposure affects millions of Americans, both civilians and military service members, and we are testing how brief noise exposures such as those due to blast (Race et al. 2017, Han et al. 2020) or gunshot exposure may differ from continuous noise such as that experienced in many workplaces (e.g. construction, manufacturing). We correlate recorded neural activities with changes in neuroanatomy. These projects are funded or have been funded by the Department of Defense and the Indiana CTSI. 2)Age-related hearing loss (ARHL) affects tens of millions of people in the United States alone, and left untreated, it is a major risk factor for poor outcomes in aging (Helfer et al. 2020). We are currently working on diagnostics of auditory system function, behavioral and electrophysiological, that are non-invasive and can be used in rodents and humans (Parthasarathy and Bartlett 2012, Parthasarathy et al. 2014, 2016, 2019, Lai et al. 2017, 2018). In addition, we record from neurons in the inferior colliculus (IC), auditory thalamus, and auditory cortex in order to track age-related changes in neural representations of sound features (Rabang et al. 2012, Herrmann et al. 2017). These projects are funded or have been funded by the Department of Defense and the National Institutes of Health. 3) Infrared neural stimulation (INS) offers a novel mode of neuroprosthetic substitution (Coventry et. al 2020) that may be more selective than electrical stimulation and that does not require genetic modification of neurons, making INS more easily suitable and a powerful technology for humans. Moreover, we have developed a powerful algorithm called Spiker-Net for learning and modifying neural stimulation parameters in real-time. These projects are funded or have been funded by the National Institutes of Health .