Sensory neuroprostheses and sensory substitution systems for the restoration of hearing [1
] and vision [3
] have been investigated for several decades. Interest in neuroprosthetic devices that combine both motor and sensory components has developed more recently [9
]. One example of a bidirectional neuroprosthesis is a robotic limb controlled by brain activity while sensory information from prosthetic sensors is delivered to somatosensory areas of the brain [15
]. Other possible implementations include sensorized neuroprostheses for the restoration of bipedal walking [17
] and putative systems combining both speech production [18
] and hearing [1
In recent years we have been studying intracortical microstimulation (ICMS) delivered through microelectrode arrays chronically implanted in the primary somatosensory cortex (S1) as a means of adding a somatosensory feedback loop to a brain-machine interface (BMI) [9
]. Taken together with previous work showing that primates [22
] and rodents [25
] can discriminate ICMS patterns, there is growing evidence that ICMS of S1 could equip neuroprosthetic limbs with the sense of touch.
One of the neuroprosthetic devices that we envision in the future is a BMI-operated robotic arm that is equipped with touch sensors [9
]. In such a sensorized neuroprosthesis, the touch sensors would detect instances when the arm interacts with external objects sending signals to the brain in the form of ICMS. We have suggested that long-term operation of such a system, which we call a brain-machine-brain interface (BMBI), could result in the incorporation of the prosthesis into the brain’s representation of the body, so that the artificial limb starts to act and feel as belonging to the subject [15
]. Notwithstanding initial encouraging results [9
], it is unclear whether ICMS would be sufficient to reproduce the rich sensory information of the world of touch [29
In particular, it is not well understood which kinds of ICMS patterns are most useful for virtual active touch. Previously, we have shown that both New World [21
] and Old World monkeys [10
] can discriminate temporal ICMS patterns applied to S1 that consist of short (50–300 ms) high-frequency (100–400 Hz) pulse-trains presented at a lower secondary frequency (2–10 Hz). In these experiments, ICMS served as a cue that instructed the direction of reach. These patterns of ICMS could, in principle, mimic a wide variety of tactile inputs, especially when combined with spatial encoding [21
]. Modulations of sensory inputs in this frequency range correspond to the sensation of flutter [30
]. These timescales are also similar to neuronal modulations involved in texture encoding in the somatosensory system [33
], which makes such ICMS patterns worthy candidates for exploration.
In this study, we examined the ability of rhesus monkeys to discriminate a range of temporal ICMS patterns applied to S1 in the context of an active exploration task in which ICMS mimicked the tactile properties of virtual objects. We manipulated the ICMS patterns in a graded fashion, modulating the degree of periodicity of the pulse-trains while maintaining a constant average pulse rate. We sought to determine the minimal perturbation of the periodic pattern that the monkeys could discriminate. The degree of randomness (as quantified by the coefficient of variation, CV) was varied from trial to trial, which allowed us to quantify the monkeys' sensitivity to ICMS frequency modulations. Concurrently with ICMS delivery, we recorded from large populations of cortical neurons using multielectrode implants. Kinematics of reach movements were extracted from this large-scale activity offline to estimate the accuracy of a BMBI with a somatosensory feedback loop that transmits aperiodic ICMS patterns.
This investigation of sensitivity to ICMS periodicity in S1 was motivated by a possible application in neuroprosthetic limbs. We expect that the patterns of ICMS triggered by the interaction of an upper-limb neuroprosthesis with objects in the environment could be highly irregular. The precise temporal structure of such patterns would depend on the interaction of touch sensors in the robotic prosthesis with the specific surface structure of the manipulated objects and on the specific exploratory movements used by the individual to interact with the objects. Therefore, by knowing the limits of the nervous system in discriminating aperiodic ICMS patterns, we can infer a principled upper bound on the maximum fidelity touch sensor that could be used in a neuroprosthesis, beyond which no additional function would be restored.
This study builds on the results obtained by Romo et al.
about ICMS of S1 [22
] and our own previous work [9
]. One notable difference between the temporal ICMS patterns implemented here and those used by Romo et al
. is that the aperiodic patterns of ICMS that we used had the same mean pulse interpulse intervals as the periodic comparison ICMS pulse trains. Thus the average number of pulses in a pulse train was the same for both periodic and aperiodic patterns. This allowed us to probe S1 sensitivity to the temporal structure of ICMS without the confound of average stimulus intensity. Romo et al
. used periodic pulse trains with different frequencies [22
], which left open the possibility that some of their results could be explained by differences in average ICMS intensity.
Another major difference between this study and previous studies of ICMS-evoked S1 sensations in primates is that the ICMS patterns employed here were used in an active-exploration paradigm in which ICMS was used to simulate the tactile properties of virtual objects. Our monkeys explored the virtual objects, making self-paced exploratory movements, and decided which objects to explore, in what order, and for how long. This is a more realistic model of a clinical somatosensory neuroprosthesis than previous designs.