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Characterizing oscillatory mechanisms of motor control: towards therapeutic closed-loop brain stimulation

Sara J. Hussain, Ph.D.

Human Cortical Physiology and Neurorehabilitation Section National Institutes of Neurological Disorders and Stroke National Institutes of Health

School of Kinesiology University of Minnesota December 2019

Stroke is the leading cause of long-term disability in the United States. Although spontaneous motor recovery often occurs after stroke, this recovery is often incomplete.

Cramer et al. 1997

At the chronic stage, more than 40% of stroke survivors still have hemiparesis.

Transcranial Magnetic Stimulation (TMS)

López-Alonso et al. 2016

“open-loop” brain stimulation ignores brain state “closed-loop” brain stimulation accounts for brain state Which brain state should we target?

The ideal brain state should: 1) be non-invasively detectable 2) be temporally well-defined 3) reflect functional state of the human motor system

Neural oscillations reflect rhythmic electrical activity generated by the central nervous system. Described by: 1) Frequency 2) Power 3) Phase 1 sec

10 Hz 10 Hz high power low power

Cole and Voytek 2017

Oscillations recorded over sensorimotor regions are most dominant between 8-12 Hz (mu).

Rest Movement preparation Movement execution Rest

high power low power low power high power

1. Establish sensorimotor oscillatory contributions to corticospinal motor output. 2. Determine causal contributions of sensorimotor oscillatory brain states to skill learning.

Rec ecen ent work

Haegens et al. 2011;

Do sensorimotor oscillatory phase and power interact to determine human corticospinal output?

90° 90° Hussain et al. 2019

Hussain et al. 2019

power, p=0.513 phase, p=0.950 interaction, p=0.002

peak trough p<0.001 peak trough p<0.001

• Corticospinal motor output is determined by mu power during troughs.
• Mu peaks reflect a neutral output state unaffected by power.
• Phase-power interactions may be a general mechanism of brain function across multiple domains.

Given differences between mu peak and trough phases, these phases may differentially contribute to motor behavior.

Conclusions #1

Hussain et al., in prep

mu mu mu

Do motor cortical contributions to skill learning differ between mu peak and trough phases?

Hussain et al., in prep

270° 270° 270°

Hussain et al., in prep

Closed-loop TMS during mu troughs improved consolidation by 54% (Cohen’s d=0.60, p<0.01). Closed-loop TMS during mu peaks improved consolidation by only 4% (Cohen’s d=0.06, NS). Hussain et al., in prep

• Delivering closed-loop TMS to human motor cortex during mu trough but not mu peak phases facilitated

consolidation of a newly learned motor skill.

• First demonstration of phase-dependent enhancement of human skill memory.
• Motor cortical activity causally contributes to skill consolidation during oscillatory trough phases only.

Neural mechanisms underlying skill consolidation fluctuate coherently with sensorimotor oscillations.

Conclusions #2

Overall conclusions

• Mechanisms of human corticospinal motor output and skill learning fluctuate coherently with sensorimotor
• scillations.
• Rather than being sustained over time, neural mechanisms of motor control are cyclic.
• Delivering brain stimulation interventions during optimal phases may improve descending motor output and

skill learning after stroke.

1. Characterizing cyclic mechanisms of skill learning in the healthy and lesioned brain 2. Synchronizing corticospinal oscillations to enhance human motor function

Fu Future wo work

Day 1

memory acquisition consolidation

This process can repeat indefinitely

Day 2

memory re-activation re-consolidation

Day 3

memory re-activation re-consolidation

• Cyclic mechanisms of skill acquisition and reconsolidation in healthy adults
• Replicate and rescue post-stroke reconsolidation deficits using closed-loop TMS

Research Project Grant (R01, PA-18-345); A0 Sept 2021

5 ms 5 ms 5 ms

A B

12 ms 12 ms 12 ms

A B Entrain spinal motor neurons to oscillate synchronously and in-phase with sensorimotor oscillations.

Womelsdorf et al. 2007

In-phase = effective communication Out-of-phase = ineffective communication

• Enhance effects of existing corticospinal spike timing-dependent plasticity protocols: high versus low synchronization states
• Closed-loop peripheral nerve stimulation to entrain spinal motor neurons to oscillate synchronously with cortical oscillations

NINDS Exploratory Neuroscience Research Grant (R21, PA-18-358); A0 Sept 2022

Seek understanding of the brain oscillatory mechanisms supporting normal and abnormal movement. Develop novel brain stimulation interventions that selectively target these mechanisms. Translate these interventions to restore motor function in patients with residual motor deficits due to neurological damage. Re Research Program Mission Statement

Acknowledgements

Human Cortical Physiology and Neurorehabilitation Section (NINDS at NIH)

Leonardo G Cohen, MD Ethan Buch, PhD Margaret Hayward, CNRP Marta Gozzi, PhD Marlene Bönstrup, MD Farah Fourcand, MD Gabriel Cruciani Ryan Thompson Katie Vollmer Jessica Stimely

Brain Networks and Plasticity Lab (University of Tübingen, Germany)

Ulf Ziemann, MD Christoph Zrenner, MD

Funding

NINDS Intramural Competitive Fellowship program