Wireless Cortical Brain-Machine Interface for Whole-Body Navigation in Primates

Abstract

Several groups have developed brain-machine-interfaces (BMIs) that allow primates to use cortical activity to control artificial limbs. Yet, it remains unknown whether cortical ensembles could represent the kinematics of whole-body navigation and be used to operate a BMI that moves a wheelchair continuously in space. Here we show that rhesus monkeys can learn to navigate a robotic wheelchair, using their cortical activity as the main control signal. Two monkeys were chronically implanted with multichannel microelectrode arrays that allowed wireless recordings from ensembles of premotor and sensorimotor cortical neurons. Initially, while monkeys remained seated in the robotic wheelchair, passive navigation was employed to train a linear decoder to extract 2D wheelchair kinematics from cortical activity. Next, monkeys employed the wireless BMI to translate their cortical activity into the robotic wheelchair’s translational and rotational velocities. Over time, monkeys improved their ability to navigate the wheelchair toward the location of a grape reward. The navigation was enacted by populations of cortical neurons tuned to whole-body displacement. During practice with the apparatus, we also noticed the presence of a cortical representation of the distance to reward location. These results demonstrate that intracranial BMIs could restore whole-body mobility to severely paralyzed patients in the future.

Enhancing Nervous System Recovery through Neurobiologics, Neural Interface Training, and Neurorehabilitation

“…These have been developed to bypass motor lesions (assistive BMIs) (Wolpaw and McFarland, 1994; Kennedy and Bakay, 1998; Leuthardt et al, 2004; Moritz et al, 2008; Ethier et al, 2012; Collinger et al, 2013; Memberg et al, 2014; Jarosiewicz et al, 2015; Bouton et al, 2016; Capogrosso et al, 2016; Hotson et al, 2016; Rajangam et al, 2016; Vansteensel et al, 2016; reviewed in Lobel and Lee, 2014) and, more recently, to facilitate neural plasticity and motor learning to enhance recovery after injury (rehabilitative BMIs) (Carhart et al, 2004; Buch et al, 2008; van den Brand et al, 2012; Ang et al, 2013; Ramos-Murguialday et al, 2013; Wahl et al, 2014; Gharabaghi et al, 2014a,b,c; Gerasimenko et al, 2015b; Donati et al, 2016; reviewed in Ethier et al, 2015; Jackson and Zimmermann, 2012). …”

“…Means of extracting nervous system signals range from invasive [intracortical microelectrodes (APs, or spikes) and larger scale sub- or epidural electrodes (electrocorticography, ECoG)] to non-invasive [electroencephalography (EEG) or electromyography (EMG)]. Targeted outputs have included cursors on a screen (Wolpaw and McFarland, 1994; Kennedy and Bakay, 1998; Leuthardt et al, 2004; McFarland et al, 2010), virtual typing (Jarosiewicz et al, 2015), robotic or prosthetic arms (Collinger et al, 2013; Hotson et al, 2016), wheelchairs (Rajangam et al, 2016), exoskeletons (Donati et al, 2016), the spinal cord (Zimmermann and Jackson, 2014; Capogrosso et al, 2016), and a patient's own extremities (Ethier et al, 2012; Memberg et al, 2014; King et al, 2015; Bouton et al, 2016; Vidaurre et al, 2016). …”

“…Researchers have been dedicated to improving the quality of life for these patients in several ways, e.g., (1) biological manipulation of the cellular milieu to encourage neuronal repair and regeneration (Magavi et al, 2000; Chen et al, 2002; Lee et al, 2004; Freund et al, 2006; Benowitz and Yin, 2007; Park et al, 2008; Maier et al, 2009; de Lima et al, 2012b; Dachir et al, 2014; Li et al, 2015; Omura et al, 2015), (2) creation of neural- or brain-machine interfaces designed to circumvent lesions and restore functionality (Wolpaw and McFarland, 1994; Kennedy and Bakay, 1998; Leuthardt et al, 2004; Monfils et al, 2004; Hochberg et al, 2006, 2012; Moritz et al, 2008; O'Doherty et al, 2009; Ethier et al, 2012; Collinger et al, 2013; Guggenmos et al, 2013; Ifft et al, 2013; Memberg et al, 2014; Zimmermann and Jackson, 2014; Grahn et al, 2015; Jarosiewicz et al, 2015; Soekadar et al, 2015; Bouton et al, 2016; Capogrosso et al, 2016; Donati et al, 2016; Hotson et al, 2016; Rajangam et al, 2016; Vansteensel et al, 2016), and (3) new rehabilitation techniques that include electrical stimulation and pharmacological enhancement of spinal circuitry to stimulate recovery (Carhart et al, 2004; Levy et al, 2008, 2016; Dy et al, 2010; Harkema et al, 2011, 2012; Dominici et al, 2012; van den Brand et al, 2012; Gad et al, 2013b, 2015; Angeli et al, 2014; Gharabaghi et al, 2014a,c; Wahl et al, 2014; Gerasimenko et al, 2015b). Unfortunately, the path to clinical relevance for these individual approaches remains long, and each field tends to operate largely in its own sphere of influence.…”

Wireless recording from unrestrained monkeys reveals motor goal encoding beyond immediate reach in frontoparietal cortex

“…Those studies focused on locomotion (Capogrosso et al, 2016;Foster et al, 2014;Yin et al, 2014), vocalization (Hage & Jurgens, 2006;Roy & Wang, 2012), or showed proof-of-concept data of sleep (Yin et al, 2014) or basic uninstructed behavior (Fernandez-Leon et al, 2015;Gilja et al, 2010;Schwarz et al, 2014). One study used a wireless brain-machine-interface to let monkeys control a robotic wheelchair in which they sat (Rajangam et al, 2016). Other studies used tethered recordings to investigate primates freely exploring the environment while being attached to a pole (Sun et al, 2006), to a cable assembly (Ludvig et al, 2004) or seated in a chair they could move (Rolls, Robertson, & Georges-François, 1997).…”

Brain-machine interfaces: assistive, thought-controlled devices

“…2) 7 . Using their neural activity as a control signal, the monkeys learned to drive the chairs and navigate towards fruit rewards.…”