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Northwestern University Feinberg School of Medicine

Faculty Profile: Marc Slutzky, MD, PhD Assistant Professor in the Ken and Ruth Davee Department of Neurology/Physiology and Physical Medicine and Rehabilitation

Marc Slutzky, MD, PhD

Marc Slutzky, MD, PhD, assistant professor in the Ken and Ruth Davee Department of Neurology/Physiology and Physical Medicine and Rehabilitation, recently received the Doris Duke Clinical Scientist Development Award, which provides support for outstanding physician-scientists in the process of establishing their own independent research teams.

Slutzky, a Morton Grove, Ill., native, completed his residency in neurology at Feinberg and became a faculty member in 2006. He received a bachelor’s degree in electrical engineering from the University of Illinois at Urbana-Champaign in 1994, and then earned a doctorate degree in biomedical engineering in 2000 and a Doctor of Medicine degree in 2002 from Northwestern as part of the Medical Scientist Training Program.

Outside of work, Slutzky enjoys spending time with his family, including his wife and two daughters. He also enjoys basketball, golf and playing the piano.

What brought you to the Feinberg School of Medicine?
I completed my residency here at Feinberg in 2006. As my wife and I are both from Chicago, we were fortunate to stay in the area. Northwestern offers a unique combination of outstanding research in neuroscience, in particular neural engineering, as well as clinical prowess in neurology and rehabilitation. Thus, it makes an ideal environment for someone with my research and clinical interests.

You were recently awarded the Doris Duke Clinical Scientist Development Award. Can you explain what this award recognizes?
The award provides additional protected time for clinical research. The selection process has two stages: first at the university level (only two nominees per school), and then 16 out of those 130 university nominees were chosen.

My project for this award aims to create a minimally-invasive brain-machine interface (BMI) using subdural and epidural signals from epilepsy patients who require intracranial placement of electrodes prior to epilepsy surgery. The subjects will attempt to control a virtual hand using a BMI that decodes both their own hand movements and observed hand movements. Since paralyzed patients will not be able to make example movements, the ability to use observed movements to train the BMI “decoder” would be advantageous for an eventual application.

Tell us more about your research.
My research consists of several thrusts in the field of neural prosthetics. My main focus is on BMIs, which record and “decode” brain signals and allow a user to control a device, such as a computer cursor or prosthetic arm, simply by thinking of the desired movement. This could benefit patients with a wide range of neurological disorders, especially those with severe paralysis.

A critical question in BMI research is how best to obtain signals from the brain. Most BMIs have used electrical signals obtained at levels ranging from the scalp (EEG) to individual neuronal action potentials (spikes) inside the cerebral cortex. In general, there is a trade-off between the level of invasiveness and signal quality and recording longevity.

One of my interests lies in determining the optimal signal source for a desired BMI application. Specifically, while intracortical spikes are thought to carry the most information about movement intent, it is difficult to record spikes from many electrodes for more than a few years. Therefore, we are interested in whether field potentials, which are derived from thousands of neurons, can provide enough information to provide good control of a BMI without sacrificing longevity. Moreover, we are investigating whether field potentials obtained in a less-invasive way—i.e., from electrodes placed under or on top of the dura mater—can also provide a high-quality signal source for BMI applications such as robotic arm control. We are investigating this question in rats, monkeys, and humans.

My other main research thrust involves a myoelectric computer interface (MCI), in which a person controls a computer cursor using electrical signals recorded from muscles (surface EMGs) instead of the brain. Each muscle moves the cursor in a different direction; by varying the mapping of muscle to direction, we can train the subject to learn new patterns of muscle activation. This provides a new platform for studying motor learning. Moreover, we aim to apply this technology to stroke rehabilitation. In addition to weakness, co-contraction causes major impairment in stroke subjects. Abnormal co-contraction consists of increased tone in muscles (e.g., agonist-antagonist pairs) during attempted movement by the patient. By using the MCI, we hope to reduce co-contraction and thus improve arm function.

What is the ultimate goal of your research?
The ultimate goal is to restore function to patients paralyzed or weakened from disorders such as stroke, spinal cord injury, and ALS.

BMIs offer the possibility of doing this directly by controlling the functional electrical stimulation (FES) of paralyzed muscles in a natural fashion (i.e., think about closing the hand and the hand closes). They also offer the possibility of pairing brain and muscle activity to potentially increase the brain’s plasticity and help recover motor function after a stroke.

The goal of our MCI research is twofold: to help restore function to patients with motor impairment, and to uncover mechanisms of neural interface learning that may inform our BMI research.

How does your research advance medical science and knowledge?
Neural interfaces offer the exciting potential to restore function to paralyzed patients who currently have very little options. While the field of BMIs has exploded with rapid growth in laboratories, it is still very much in its infancy. Our research aims to elucidate ways to obtain high-quality, long-lasting signals for BMIs while minimizing potential adverse effects. Our work thus far demonstrates that epidural signals may provide similar information to subdural signals, and that intracortical field potentials convey almost as much information as spikes.

Subdural electrode monitoring allows us to record from multiple brain areas simultaneously with high temporal resolution. However, most electrode arrays used in clinical epilepsy monitoring have coarse spatial resolution. Our work suggests that we could obtain much more information simply by increasing the density of the electrodes used. This could improve not only BMIs, but also our understanding of human physiology and pathophysiology.

BMIs also provide a uniquely powerful platform to study brain physiology. For example, monkeys learn to control a cursor using decoded signals from motor cortex that are highly correlated with arm movements, yet they learn to move the cursor without moving their arms. I am very interested in the mechanism for phenomena like this, and what it can teach us about normal and abnormal brain physiology. MCIs likewise provide a new paradigm for studying adaptation to neural interfaces.

What types of collaborations are you engaged in across campus (and beyond)?
I am fortunate to be involved with several different collaborations. I work very closely with Lee Miller, PhD in the Department of Physiology, and through him I am involved in collaborations with several other faculty including Sara Solla, PhD and Konrad Kording, PhD, also from the Department of Physiology; Nicholas Hatsopoulos, PhD at the University of Chicago, and Andrew Fagg, PhD at the University of Oklahoma.

My desire to advance my BMI research into human subjects led me to form a collaboration with Joshua Rosenow, MD, Director of Functional Neurosurgery at Northwestern Memorial Hospital (NMH), and Stephan Schuele, MD, Director of the Clinical Epilepsy Center at NMH. This collaboration further involves Jun Yao, PhD and Julius Dewald, DPT, PhD, Department of Physical Therapy. Together we have recorded from five epilepsy subjects while they perform hand grasping movements. I also collaborate with the laboratory of Jim Patton, PhD to examine decoding speech from human brain surface signals. To broaden our patient recruitment efforts, I have established a collaborative agreement to perform similar experiments with James Tao, MD and David Frim, MD, Departments of Neurology and Neurosurgery, respectively, at the University of Chicago Medical Center. The Doris Duke project includes a collaboration with and mentorship from Todd Kuiken, MD, PhD, Director, Neural Engineering Center for Artificial Limbs at the Shirley Ryan AbilityLab, as well as a collaboration with Gerwin Schalk, PhD, Wadsworth Center at Albany Medical College.

Zev Rymer, MD, PhD, Vice President for Research, Shirley Ryan AbilityLab, has been my co-mentor on my K08 award, and is a co-investigator on my MCI research project.

Finally, I am a Co-PI in a multi-institutional DARPA project to design reliable CNS BMIs with investigators at NU, University of Chicago, University of Oklahoma, and Michigan State University. This project aspires to have monkeys control a robotic arm and hand using a BMI.

How did you become interested in this area of research?
As an undergraduate at UIUC, I worked with Bruce Wheeler for an honors thesis project working on decoding some of the data for one of the first BMIs, based on P300 waves recorded from the scalp. While this project was ultimately unsuccessful, it opened my mind to the BMI field. My graduate work aspired toward refining another form of brain machine interfacing—control of epileptic seizures using precisely-timed electrical stimulation at the seizure focus. Later, I read about the work of Lee Miller, PhD in BMIs and decided to switch my focus from epilepsy to motor BMIs.

How is your research funded?
My main source of funding has been an NIH K08 award for the past 4 years. During that time I have also received funding from several private foundations, including the Brain Research Foundation and Northwestern Memorial Foundation Dixon Translational research awards, that helped start my independent research in humans. More recently, I have been awarded funding for my human BMI work from the Paralyzed Veterans of America and the Doris Duke Charitable Foundation. I also received a Neilsen Foundation Research Grant for the human BMI work which I had to decline due to overlap with the Duke award.