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Biomimetic microstimulation of the human somatosensory cortex
Sensory feedback based on intracortical microstimulation has been shown to improve subjects’ ability to use brain-controlled bionic hands (Flesher et al., 2021). However, the resulting dexterity is still far from that of natural hands in able-bodied individuals. Efforts to sensitize bionic hands for amputees by electrical stimulation of the nerves have shown that sensory feedback that mimics natural tactile signals (so called biomimetic feedback (Okorokova et al., 2018; Saal and Bensmaia, 2015; Saal et al., 2017) evokes more natural and more intuitive sensations that better support interactions with objects than does non-biomimetic feedback. Despite these successes with amputees, biomimetic feedback has never been applied in the context brain-controlled bionic hands.
Around 169,000 people in the United States live with tetraplegia due to spinal cord injury (SCI). (National Spinal Cord Injury Statistical Center, Facts and Figures at a Glance. Birmingham, AL: University of Alabama at Birmingham, 2018). The resulting paralysis and accompanying loss of independence cause a severe decline in quality of life and necessitate around the clock care. A promising approach to restore independence to individuals with tetraplegia is to equip them with robotic arms that they can control volitionally via signals harnessed directly from the central nervous system. With the development of ever more sophisticated robotic arms and of interface technologies that yield better control signals, the need for the restoration of somatosensory feedback in Brain-Computer Interfaces (BCIs) has come into clearer focus (Bensmaia and Miller, 2014; Bensmaia et al., 2020; Flesher et al., 2016). Indeed, for able-bodied individuals, interactions with objects are critically dependent on signals from the hand that convey information about the objects and our interactions with them. Without these signals, our ability to interact with objects is severely compromised, as visual signals are poor substitutes for their tactile counterparts.
Recent efforts toward developing brain-controlled robotic limbs have thus incorporated artificial sensory feedback by applying intracortical microstimulation (ICMS) to the somatosensory cortex (Flesher et al., 2016, 2021; Salas et al., 2018). ICMS has been shown to evoke stable and nearly natural tactile sensations experienced at specific locations on the (otherwise insensate) hand.
Around 169,000 people in the United States live with tetraplegia due to spinal cord injury (SCI). (National Spinal Cord Injury Statistical Center, Facts and Figures at a Glance. Birmingham, AL: University of Alabama at Birmingham, 2018). The resulting paralysis and accompanying loss of independence cause a severe decline in quality of life and necessitate around the clock care. A promising approach to restore independence to individuals with tetraplegia is to equip them with robotic arms that they can control volitionally via signals harnessed directly from the central nervous system. With the development of ever more sophisticated robotic arms and of interface technologies that yield better control signals, the need for the restoration of somatosensory feedback in Brain-Computer Interfaces (BCIs) has come into clearer focus (Bensmaia and Miller, 2014; Bensmaia et al., 2020; Flesher et al., 2016). Indeed, for able-bodied individuals, interactions with objects are critically dependent on signals from the hand that convey information about the objects and our interactions with them. Without these signals, our ability to interact with objects is severely compromised, as visual signals are poor substitutes for their tactile counterparts. Recent efforts toward developing brain-controlled robotic limbs have thus incorporated artificial sensory feedback by applying intracortical microstimulation (ICMS) to the somatosensory cortex (Flesher et al., 2016, 2021; Salas et al., 2018). ICMS has been shown to evoke stable and nearly natural tactile sensations experienced at specific locations on the (otherwise insensate) hand.
The aim of the project is to develop the first biomimetic approach to restore touch via intracortical microstimulation (ICMS). We will test whether bio-inspired patterns of ICMS are perceived as more natural, yield better prosthetic control, and give rise to greater embodiment of the prosthetic limb, as has been shown to be the case with nerve stimulation. The proposed project leverages the fact that our team is one of the few to have two human participants chronically implanted with arrays of electrodes in both motor and somatosensory cortex.
The major goals (mandatory) for the student will be:
WP1: develop the first biomimetic ICMS encoding algorithm.
WP2: implement the biomimetic encoding algorithm in real-time with the human BCI subjects.
WP3: test the sensory and functional consequences of biomimetic ICMS-based sensory feedback in the human subjects.
Recommendable skills: Signal processing, MATLAB, C++, C, peripheral nervous system neurophysiology and anatomy.
Extra skills: Computational neuroscience, multithread applications, embedded linux system (e.g. raspberry pi).
Time effort required: Master project full time.
The aim of the project is to develop the first biomimetic approach to restore touch via intracortical microstimulation (ICMS). We will test whether bio-inspired patterns of ICMS are perceived as more natural, yield better prosthetic control, and give rise to greater embodiment of the prosthetic limb, as has been shown to be the case with nerve stimulation. The proposed project leverages the fact that our team is one of the few to have two human participants chronically implanted with arrays of electrodes in both motor and somatosensory cortex. The major goals (mandatory) for the student will be: WP1: develop the first biomimetic ICMS encoding algorithm. WP2: implement the biomimetic encoding algorithm in real-time with the human BCI subjects. WP3: test the sensory and functional consequences of biomimetic ICMS-based sensory feedback in the human subjects. Recommendable skills: Signal processing, MATLAB, C++, C, peripheral nervous system neurophysiology and anatomy. Extra skills: Computational neuroscience, multithread applications, embedded linux system (e.g. raspberry pi).
Time effort required: Master project full time.
Dr. Giacomo Valle, Assistant Professor, Head of Neural Bionics laboratory, Chalmers University of Technology, Life Bionics,Goteborg, Sweden
Email: valleg@chalmers.se
Dr. Giacomo Valle, Assistant Professor, Head of Neural Bionics laboratory, Chalmers University of Technology, Life Bionics,Goteborg, Sweden Email: valleg@chalmers.se
