Decoding Neural Activity from an Intracortical Implant in Humans with Tetraplegia Chad E. Bouton Battelle Health and Lif

1. Decoding Neural Activity from an Intracortical Implant in Humans with TetraplegiaChad E. BoutonBattelleHealth and Life Sciences Division

2. Background • Cyberkinetics (founded in 2001) developed a Brain-Computer Interface (BCI) system called BrainGate • At the core of the system was the Utah Electrode Array (brain implant) • Implanted in the Primary Motor Cortex (M1), hand/arm area • Purpose was to allow severely disabled individuals to communicate, use their PC’s, and even control a wheelchair by decoding their thoughts

3. Background • Battelle developed user training methods and NeuralDecoding Algorithms • Processed signals from the electrode array (96 channels) • Goal: isolate and predict arm/hand movements the patient is thinking about Time Domain Signals from Electrode Array Neural Decoding Shoulder Abduction Elbow Extension Wrist Flexion

4. Patients • 54 year old female stroke victim (“SCI 3”), quadriplegic and unable to speak • 36 year old male, diagnosed with ALS, quadriplegic and unable to speak • Conducted an intended motion survey to look at neural modulation (change in neuronal firing patterns) for various visually cued movements • Shoulder Flexion and Extension • Shoulder Abduction and Adduction • Elbow Flexion and Extension • Wrist Flexion and Hyperextension • Wrist Radial and Ulnar Deviation • Wrist Pronation and Supination • Hand Open and Close

5. Initial Motion Survey with SCI3 Flexion/extension mixed (dark/med blue) Zero Units (Neurons) Exhibited Differing Firing Patterns (Axes are unit-less and represent the first three principal components from a principal components / eigenvector analysis.)

6. Thought-Driven Cursor • Previous decoding methods (from non-human primate work) • Position based (assumed neural patterns correlated to position in space) • Early demonstration in a human subject: BG SCI P003 - Center Out - 2006.01.23.wmv • Marginally stable results - proprioceptive feedback is disrupted in a disabled user • Introduced user training methods - used motion demonstration (mirror neuron activation) and ‘coaching’ periods • Moved away from position-based decoding and utilized model-based approaches along with support vector machine methods • Results for Battelle decoding algorithm - stabilized cursor motion by isolating 6 intended motions: rest, four wrist motions, and close hand: • SCI P003 8-23-06 Great - excellent motion and diagonal.mov

7. Increasing Degrees-of-Freedom -12 Motions (6 DOF) Recognized by Algorithm

8. Adaptive Algorithm • Subject ALS1 exhibited decreased and inconsistent performance • Incorporated performance feedback during training (“dots/masses on springs”) • Adapted decoding algorithm after each training block • Demonstration: ALS1_4DOF_matlab_screen.wmv

9. Communicating to Others • Locked-in syndrome • 5 imagined movements to move and ‘click’ cursor over virtual keyboard: Aug_Communications_Wonderful_high_quality.wmv

10. Wheelchair Control • Mobility extremely important and can be difficult/impossible for certain patients with existing interfaces • As aired on 60 Minutes (Nov. 2, 2008), Cathy Hutchinson became the world’s first person to control a wheelchair with a brain implant (using the Battelle training and decoding methods) • Stroke Patient - Controlling Wheelchair.wmv

11. Acknowledgements • Cyberkinetics, Inc. • Dr. John Donoghue • Dr. Leigh Hochberg • Mike Fritz • Almut Branner • Abe Caplan • Ammar Shaikhouni • Oystein Johnsen (Eagle)