Caviness John

Professor,Neurology,Mayo Clinic 

Location: United States

Consulting Services


Areas Of Interest

Myoclonus Essential Tremor Tremor Dementia Lewy Bodies Synucleinopathies Synucleins Huntington Disease

Professional Narrative

The clinical practice of John N. Caviness, M.D., involves movement disorders, electrophysiology of movement disorders and interpretation of electroencephalography. His main research interest is cortical function in Parkinson's disease and its role in cognitive deterioration and dementia.

Focus areas

Dr. Caviness' lab is interested in developing and validating electrophysiological biomarkers for the cognitive decline in Parkinson's disease.

Among the electrophysiological biomarkers that Dr. Caviness has studied are electroencephalography (EEG) spectral features and small-amplitude myoclonus in Parkinson's disease, for which he established its cortical origin.

Also, with colleagues, Dr. Caviness has proposed a definition for mild cognitive impairment in Parkinson's disease. He is also interested in premotor Parkinson's disease.

Other research interests are:

  • Movement disorders
  • Myoclonus, particularly the myoclonus associated with neurodegenerative disease
  • Electrophysiology of movement disorders, particularly myoclonus
  • Huntington's disease
  • Clinical neurophysiology of EEG
  • Basic movement physiology
  • Cellular neurophysiology and neurochemistry
  • Neurochemistry
  • Clinical-pathological correlation of neurodegenerative disease

Significance to patient care

There is a great need for measuring the effects of new and experimental treatments in Parkinson's disease and related diseases. Sensitive and precise measurement allows treatment trials to be done faster and more accurately.

Dr. Caviness and his colleagues have shown that electrophysiological biomarkers will effectively fulfill this role. For example, quantitative EEG will help distinguish the more-effective treatments for cognitive decline in Parkinson's disease.

These biomarkers have also shown that electromyography and EEG can also have predictive value for the development of early Parkinson's disease and some of its complications. This discovery will be used to help identify individuals for the earliest therapies to prevent Parkinson's disease progression.


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