Rochester, Minn




Deep brain stimulation (DBS) is an effective electrical stimulation technique for treating patients with certain types of neurological disorders whose symptoms are resistant to pharmacological or other clinical interventions. J. Luis Lujan, M.S., Ph.D., is interested in using DBS and other neuromodulation techniques to restore neural function in patients with neurological injury and disease.

Dr. Lujan develops and applies engineering, mathematical and computational principles and techniques to study, model and control biophysical mechanisms responsible for the motor, cognitive and affective components underlying neural activity in brain injury and disease. Additionally, he applies these models and control strategies to the development of novel clinically effective neural prostheses and brain-machine interfaces.

Focus areas

  • Characterization of neural pathways modulated by DBS and responsible for specific clinical outcomes. Optimal treatment of psychiatric and movement disorders by DBS requires characterization of the neural pathways responsible for specific clinical behaviors. Dr. Lujan's research identifies neural pathways that should be activated or avoided in order to evoke specific clinical outcomes during DBS therapy.
  • Characterization of neurochemical responses evoked by therapeutic DBS. The therapeutic effects of deep brain stimulation have been associated with changes in neurotransmitter release. Dr. Lujan and his group model and parameterize the dynamics of stimulation-evoked neurotransmitter release, detected using in vivo electrochemical monitoring techniques, to develop neurochemical feedback biomarkers to individualize the therapeutic application of DBS.
  • Automated control of DBS for patient-specific treatment of movement and psychiatric disorders. Sustained therapeutic effects in DBS therapy require frequent empiric adjustment to the stimulation parameters based on subjective evaluations of clinical outcomes. Dr. Lujan is developing an automated algorithm that relies on objective biomarkers of therapeutic efficacy to determine stimulation settings that maximize patient-specific therapeutic benefits while minimizing side effects.

    Dr. Lujan's approach involves the development of computational models and control systems based on machine-learning techniques and feedback control strategies that can automatically adjust stimulation parameters in response to real-time changes in clinical symptoms and brain activity.

  • Development of novel brain-machine interfaces for optimal restoration of function following neural injury and disease. Brain-machine interfaces can aid patients with paralysis by bypassing lesions of the nervous system and delivering motor commands directly to target motor centers. Dr. Lujan's aim is to extract command signals from the brain and use these signals to control biophysical systems with multiple and coupled degrees of freedom via electrical stimulation of the central and peripheral nervous system.

Significance to patient care

The clinical success of DBS therapy depends on the careful selection of stimulation targets and stimuli parameters. Because the brain is dynamic, obtaining optimal clinical response requires frequent adjustments to the stimulation parameters.

The translational nature of Dr. Lujan's research has the potential to customize DBS therapy to individual patients, thus reducing under- or over-stimulation and improving neural function in patients with neurological or psychiatric disorders such as Parkinson's disease, essential tremor, depression and obsessive-compulsive disorder.


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Academic Rank

  1. Assistant Professor of Biomedical Engineering
  2. Assistant Professor of Neurosurgery


  1. Post Doctoral Fellowship - Deep Brain Stimulation Cleveland Clinic, Lerner Research Institute, Department of Biomedical Engineering
  2. Ph.D. - Biomedical Engineering Case Western Reserve University
  3. MS - Biomedical Engineering Case Western Reserve University
  4. BS - Computer Engineering and Systems Engineering Universidad Autonoma de Chihuahua

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