ReviewRestoring tactile and proprioceptive sensation through a brain interface
Introduction
One approach to restoring sensorimotor function to amputees or tetraplegic patients is to equip them with robotic prosthetic arms and have them control these limbs using signals from the motor parts of their brain. To date, a number of patients have been able to control anthropomorphic robotic arms to perform simple motor tasks, such as grasping and moving objects (Collinger et al., 2013, Hochberg et al., 2012). As impressive as these feats are from a scientific and technological standpoint, however, movements generated using these prosthetic limbs are slow and relatively inaccurate; their performance still does not warrant the highly invasive surgery that they would require if they were adopted in the clinic. One important reason for the poor performance is the lack of somatosensory feedback. Indeed, our ability to grasp and manipulate objects is critically dependent on the senses of touch and proprioception. Tactile and proprioceptive signals from the hand convey information about the size, shape, and texture of objects, and indicate when objects are slipping from our grasp (Johansson and Flanagan, 2009). Proprioceptive signals also convey information about the state of our limb and are important to plan and guide movements (Sainburg et al., 1993, Sainburg et al., 1995). Vision is a poor substitute for touch and proprioception as evidenced by the fact that patients with intact motor but impaired somatosensory function struggle to perform activities of daily living, like tying a shoelace or turning a doorknob (Marsden et al., 1984). Touch also plays a critical role in emotional and social communication – we touch the people we care about – and in embodiment – the sense that our body is part of us. Given the importance of somatosensation in intact individuals, a key to improving the performance of prosthetic arms is to incorporate this critical sensory feedback. One approach to restoring somatosensation is to electrically stimulate the somatosensory parts of the brain, specifically primary somatosensory cortex (Fig. 1), in the hopes of eliciting meaningful and informative tactile percepts that can then be used not only to improve the dexterity of these limbs, but also to restore the affective component of touch and promote the embodiment of the prosthesis.
Section snippets
Somatosensation and dexterous motor control
When we grasp and manipulate objects, tactile and proprioceptive signals from our hands convey information about the shape, size, and texture of the objects, and signal when they are slipping from our grasp (Johansson and Flanagan, 2009). A variety of different cutaneous receptors convey information about skin deformations (Bensmaia and Tillery, 2013), and different receptors in the joints, muscles, and skin convey information about the conformation and movements of the limb (Edin, 1990, Edin,
Touch and affective communication
The manner in which we touch someone, for example the speed at which we stroke them, can communicate distinct emotions, such as anger, fear, sadness, love and so on, and the accuracy with which this emotional information is transmitted by touch is comparable to that of vocal and facial expression (Hertenstein et al., 2009). At the somatosensory periphery, pleasant touch is in part mediated by a specialized set of afferents, namely C-tactile afferents, that innervate the hairy skin (Löken et
Touch and embodiment
We experience our limbs as being part of our body; in fact, this embodiment does not necessarily disappear when we lose a limb. Indeed, many amputees experience a phantom limb, the sensation that the missing limb is still there (Ramachandran and Hirstein, 1998). Most patients report that the phantom limb is in a static position and immovable. These sensations can gradually fade over a period of weeks but about 30% of those who experience phantom limbs do so for years or even decades after limb
Electrical stimulation of S1 results in somatosensory percepts
Beginning in the 1930s, Wilder Penfield stimulated the surface of the brain in search of the foci of epileptic seizures (Penfield and Boldrey, 1937) and found that stimulating the postcentral gyrus elicited tactile percepts that were localized to specific locations on the body. These electrically-induced percepts usually manifested as numbness or tingling and sometimes pain. The projected location of these sensations varied systematically with the location of S1 stimulation, leading to the
Biomimicry
The most straightforward approach to conveying artificial sensory feedback is to attempt to reproduce naturalistic patterns of neuronal activation through ICMS. Indeed, different neuronal populations in S1 convey different information about the state of the limb and about events impinging on it. Some neurons convey information about the shape of objects grasped in the hand (Bensmaia et al., 2008) (Fig. 1b), others convey information about the motion of objects across the skin (Pei et al., 2010,
Adaptation
The idea behind the biomimetic approach is that reproducing naturalistic patterns of neuronal activity through ICMS will elicit verisimilar percepts that will be intuitive and therefore will not require the patient to learn to interpret the artificial sensations. The problem with the biomimetic approach is that electrical stimulation of neuronal tissue does not produce naturalistic patterns of neuronal activity; in fact, the effects of ICMS on neurons is ill-understood and difficult to predict.
Contributions of biomimicry and adaptation
The biomimetic and adaptation approaches are not mutually exclusive and indeed are complementary. Studies with biomimetic ICMS have demonstrated that, for simple stimulus quantities, like location or pressure, the animals can generalize instantaneously from natural to artificial feedback. However, the evoked sensations are almost certainly not naturalistic and it is not clear whether biomimetic strategies to elicit more complex sensations will be successful. The ability to adapt to novel
Plasticity
Somatosensory cortex has been shown to change adaptively when the pattern of afferentation changes. For example, when a digit is stimulated more than its neighbors, its cortical magnification increases (Elbert et al., 1995, Jenkins et al., 1990). Changes in cortical magnification are also observed in medical conditions when some body parts are overused, such as the writer's cramp and carpal tunnel (Nelson et al., 2009, Tecchio et al., 2002). Similarly, when a digit is severed, the cortical
Reliability and safety
For ICMS to be a viable approach for conveying somatosensory feedback, it must be both reliable and safe. Unfortunately, chronically implanted electrode arrays are not sufficiently robust to last in the brain for decades. Indeed, the electrodes degrade over time (Kane et al., 2013, Prasad et al., 2012) and electrode arrays are susceptible to outright failure, most often due to connector issues (Barrese et al., 2013, Simeral et al., 2011). Given the highly invasive surgery required for
Conclusions
The development of anthropomorphic robotic arms and of algorithms to decode motor intention based on signals from the brain has led to remarkable demonstrations of human patients controlling robotic arms by thought (Collinger et al., 2013, Hochberg et al., 2012). However, this technology will likely not transition into the clinic until somatosensory feedback is incorporated. Indeed, controlling an arm without somatosensation is challenging even with an intact motor system. While patients with
Acknowledgments
This work is supported by the Defense Advanced Research Projects Agency under contract N6601-10-C-4056, by the National Science Foundation grant DGE-0903637, by the National Institutes of Health grant RO1 NS08285, and by the Chicago Biological Consortium grant c-049.
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2022, Cell ReportsCitation Excerpt :Beyond a better understanding of sensory perception, our findings could be key to the efficient delivery of sensory information in the context of sensorimotor neuroprostheses (Chen et al., 2020; Dadarlat et al., 2015; Hartmann et al., 2016; O’Doherty et al., 2011). Recent active neuroprostheses tend to match as closely as possible the spatial and temporal aspects of physiological cortical responses to tactile and proprioceptive inputs (Flesher et al., 2021; Tabot et al., 2015), as well as to visual inputs (Dobelle, 2000; Fernández et al., 2021). However, most studies relied on discrete patterns of stimulation in space and time, whereas everyday prosthesis use is likely to generate complex, continuous sensory feedback.
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