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Perceptual and cortical representations of corporeal touch explored using intracortical microstimulation of primary somatosensory cortex
The somatosensory system is crucial to the formation and maintenance of coherent mental representations of our bodies. Traditional concepts of somatosensation have been shaped by the principles of somatotopic and hierarchical organization of the primary somatosensory cortex (S1). However, emerging psychophysical phenomena have been studied mostly with natural touch only that undergoes extensive processing along the tactile system, and it is unclear at which stages these phenomena arise. Intracortical microstimulation (ICMS) of S1 allows to directly evoke vivid touch sensations on the body, the properties of which can by systematically manipulated by varying the parameters of stimulation. In this work, we use ICMS of human S1 in three implanted participants to define cortical-body maps of the human hand and then to link these mental-body perception maps.
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 student will be guided in understanding the principal causes of lack of sensory feedback, its effects and meaning in terms of artificial perception, the current state of the art of neuroprosthesis with scientific literature readings, and our developed sensory-feedback system. The student will study in detail the mechanisms and principles of direct electrical cortical stimulation for sensory feedback applications. Investigating the functional representations of touch and the relationships between corporeal, cortical and perceptual spaces.
The major goals for the student will be:
1. Spatial acuity of ICMS compared to natural touch
2. Relationships between corporeal – cortical – perceptual spaces
3. Granular representation of human fingers in S1
4. Perceptual biases
5. Array design and bionic hand sensorization
Recommendable skills: Signal processing, MATLAB, central nervous system neurophysiology and anatomy.
Extra skills: Computational neuroscience.
Time effort required: Master project full time.
The student will be guided in understanding the principal causes of lack of sensory feedback, its effects and meaning in terms of artificial perception, the current state of the art of neuroprosthesis with scientific literature readings, and our developed sensory-feedback system. The student will study in detail the mechanisms and principles of direct electrical cortical stimulation for sensory feedback applications. Investigating the functional representations of touch and the relationships between corporeal, cortical and perceptual spaces. The major goals for the student will be: 1. Spatial acuity of ICMS compared to natural touch 2. Relationships between corporeal – cortical – perceptual spaces 3. Granular representation of human fingers in S1 4. Perceptual biases 5. Array design and bionic hand sensorization Recommendable skills: Signal processing, MATLAB, central nervous system neurophysiology and anatomy. Extra skills: Computational neuroscience.
Time effort required: Master project full time.
Dr. Giacomo Valle, Assistant Professor, Head of the Neural Bionics laboratory, Chalmers University of Technology, Life Bionics, Goteborg Sweden
email: valleg@chalmers.se
Dr. Giacomo Valle, Assistant Professor, Head of the Neural Bionics laboratory, Chalmers University of Technology, Life Bionics, Goteborg Sweden email: valleg@chalmers.se
