In Experiment 1, over an eight-week period, electrical stimuli were tested across a range of current amplitudes between 20–100 µA, with pulse frequency held constant at 150 Hz (see Materials and methods). Stimulation through 46/96 electrodes (48%) prompted at least one response, and there were in total 381 reported sensations out of 1229 non-catch trials (see Materials and methods). There was weak correlation between the number of electrodes that elicited a sensation and the current amplitude (r = 0.34, p=0.42, Pearson linear correlation). Additionally, we found no correlation between electrode impedance and the likelihood of elicited percepts (p=0.80, Pearson linear correlation coefficient), pooling all electrode responses over all days. Furthermore, there was no significant difference in the aggregate impedances of either electrodes that produced or did not produce percepts (p=0.707, Kolmogorov-Smirnov two-sample test). No false positives were reported in any catch trials, and we found no effect of trial history in the proportion of reported sensations during stimulation (see Materials and methods). The stimulation did not trigger any painful sensations, and no adverse events occurred during any of the sessions.

Receptive fields along the upper arm, forearm and hand corresponded to coarse somatotopical organization in the corresponding stimulation sites. Figure 2 shows the most frequently reported receptive field and sensation modality for each electrode across all trials. Of the 46 electrodes with responses, 32 evoked percepts in the upper arm, 18 in the forearm, and two in the hand (palmar surface of digits and a finger pad). In agreement with previous reports, stimulation could produce percepts with variably-sized receptive fields in different electrodes (Flesher et al., 2016). For the majority of electrodes (24/46), receptive fields were reported in the same body region (i.e. upper arm or forearm) or in the same plane (i.e. anterior or posterior) across all tested amplitudes. Coarse somatotopy was present between the medial and lateral arrays (Figure 2B); the medial array was more likely to have reliable receptive fields in the anterior upper arm (46% of medial-array receptive fields), while stimulation on the lateral array induced sensation more frequently on the posterior forearm (51% of lateral-array receptive fields). However, there was no clear somatotopical organization within each array as previously reported (Kim et al., 2015a; Kaas, 1983; Flesher et al., 2016). The coarse somatotopy found across arrays but not within arrays, could be due to the small area of cortex sampled by the implants, and the fact that the implants predominantly covered upper arm and forearm, areas with a less established somatotopic map (Kaas et al., 1979; Kaas, 1983). Another plausible explanation is that the topography in somatosensory cortex has been remapped after injury (Kaas et al., 1983; Florence et al., 1998; Moore et al., 2000)

Figure 2 Download asset Open asset Receptive fields and sensation modality across all amplitude mapping experiments. (A) Receptive field location on anterior (lighter shades) and posterior (darker shades) planes of the right upper arm (green), forearm (pink), and hand (cyan). Grid is the same that the subject referenced during the experiment. (B) Schematic of the two electrode arrays implanted over S1 (Figure 1). Left side panels display the reported receptive fields at each electrode location, and right side panels display the sensation modality (cutaneous - red, proprioceptive - blue). Light gray boxes show electrodes with no reported sensation, while dark gray boxes represent reference channels which are not used in recording. The five electrodes with a thick black outline represent the subset tested in the additional parameter-wide mapping task. Yellow and magenta asterisks mark the inferior-posterior corner of the implants, for the medial and lateral arrays respectively. https://doi.org/10.7554/eLife.32904.004

FG has reported a wealth of qualitative sensations induced by ICMS (Table 1). Unlike paresthetic sensations experienced post-injury, these naturalistic responses were broadly characterized as cutaneous (e.g. squeeze) or proprioceptive (e.g. rightward movement), and as being subjectively similar to sensations experienced prior to injury. At his own discretion, the subject used single-word descriptors to characterize the perceived sensations as accurately as possible. Single-word descriptors have the advantage that they can be compared across large data sets or subjects. However, as experimental advances continue to push the capabilities of ICMS, responses could become more complex and future studies might benefit from more structured descriptors, which take into consideration the complexity of these sensory experiences (Darie et al., 2017).

Table 1 Descriptions of the most prevalent sensations by percentage of total responses. Entries cover 90% of 381 reported sensations, with the final 10% comprising a mixture of other naturalistic cutaneous and proprioceptive descriptors. Each sensation is accompanied by the mode and 25th-75th percentiles in the distribution of amplitudes that elicited each sensation, and by the same quantities for the perceived reported intensities (on a scale of 1 [weak] to 10 [strong]). https://doi.org/10.7554/eLife.32904.005 Description % Total Sensations (381 total) Amplitude μA

(mode) Amplitude μA

(25th, 75th percentile) Intensity

(mode) Intensity

(25th, 75th percentile) Squeeze 24.9 40 40, 87.5 7 4, 7 Tap 17.3 70 40, 80 1 1, 4 Right movement 9.7 90 55, 90 1 1, 3 Vibration 8.1 40 40, 90 2 2, 3 Blowing 6.6 60 30, 80 1 1, 2 Forward Movement 5.8 70 40, 80 1 1, 4 Pinch 5.5 40 40, 90 3 3, 6 Press 5.0 40 40, 70 7 4, 7 Upward Movement 3.9 70 70, 85 1 1.25, 4 Goosebumps 3.1 100 60, 90 5 2, 5

We found that 18 electrodes had cutaneous-only responses across all tested current amplitudes, while six electrodes had proprioceptive-only responses; the rest of the electrodes (22/46) had mixed responses, where the perceived modality (cutaneous or proprioceptive) varied as stimulus parameters changed. Of these mixed-response electrodes, 45% evoked mostly cutaneous sensations, 32% evoked mostly proprioceptive sensations, and 23% had an equal number of cutaneous and proprioceptive sensations (Figure 2B). This pattern of cutaneous and proprioceptive evoked sensations complements recent reports of multimodal (i.e. cutaneous and proprioceptive) neurons throughout S1 (Yau et al., 2016; Kim et al., 2015b). While prior single-unit experiments have defined maps from single neurons to specific unimodal receptive fields (Kaas et al., 1979; Kaas, 1983; Friedman et al., 2004; Romo et al., 2000), the above results suggest that more than one variable may be represented when mapping with ICMS. This finding may be the product of different mechanisms by which receptive fields are observed through recording versus stimulation, and could be an important topic for future work. We found a significant difference between the amplitudes that elicited cutaneous or proprioceptive responses, with the distribution of proprioceptive responses skewed towards higher amplitudes (Figure 3A), when pooling across all electrodes and amplitudes that produced a sensation (p=0.039, Kruskal-Wallis nonparametric ANOVA, χ2(1,378)=4.41, proprioceptive responses N = 79, cutaneous responses N = 302). To assess consistent current delivery across all electrodes, we measured electrode impedance at the beginning of every session and found no significant difference when comparing proprioceptive or cutaneous responses (p=0.237, χ2(1,378)=1.39) and, furthermore, we found no significant difference between the impedance of proprioceptive- and cutaneous-only (p=0.922, χ2(1,155)=0.01) or mixed-response electrodes (p=0.372, χ2(1,221)=0.8). To account for potential bias from an uneven distribution of responses across amplitudes, we compared the proportion of proprioceptive and cutaneous responses in a bootstrapped resampling (N = 10000), in which each repetition drew 15 responses at each amplitude from all data pooled across days (Figure 3B). We observed a clear relationship between the number of proprioceptive and cutaneous responses and stimulation amplitudes, measured through overall positive slopes in the 1st-order polynomial fit at each iteration for proprioceptive responses, and negative slopes for cutaneous responses (Figure 3C).

Figure 3 Download asset Open asset Proprioceptive and cutaneous responses. (A) Kernel density estimate and box plot showing the difference in the distribution of amplitudes associated with each report of proprioceptive (blue) or cutaneous (red) responses. (B) The median percentage of responses in the bootstrapped sample (solid line) for proprioceptive and cutaneous responses at each amplitude tested. Dashed line shows 1st-order polynomial fit. (C) Kernel density estimates of the distribution of slopes from 1st-order polynomial fits in each bootstrap iteration. (D) Pie charts show the percentage of total stimulations of responses for the subset of electrodes tested over a range of both current amplitudes and pulse frequencies. The left panel shows an individual example electrode (six trials per combination of amplitude and frequency) and the right panel shows data pooled over all five electrodes (30 total stimulations per combination). The percentage of no response (white), proprioceptive (blue) or cutaneous (red) are shown. (E) A normalized histogram of proprioceptive (blue) and cutaneous (red) responses at each of the amplitudes tested in experiment 2. https://doi.org/10.7554/eLife.32904.006

Experiment 2 tested a subset of 5 electrodes with robust responses across all tested amplitudes in Experiment 1 (Figure 2B, Figure 3D). In a pseudorandomly-interleaved fashion, we stimulated each electrode with five amplitudes (range 20 to 100 μA) at six different frequencies (range 50 to 300 Hz) over the course of three consecutive days (see Materials and methods). We reproduced the effect of amplitude on sensation modality, either proprioceptive or cutaneous, when pooling across all responses (p=2×10−5, χ2(1323)= 18.17, Figure 3E). Similar to the main mapping task, we did not find any significant effect on modality due to electrode impedance (p=0.305, χ2(1323)=0.8). Furthermore, there was no significance when testing the effect of frequency in eliciting proprioceptive or cutaneous responses (p=0.22, χ2(1323)= 1.48).

This amplitude-specific effect on sensation modality is perhaps surprising given the more commonly observed effect of frequency and pulse-width modulation on sensation in the periphery (Graczyk et al., 2016). Although there is evidence of tactile and proprioceptive inputs co-modulating S1 firing activity (Kim et al., 2015b), we are unaware of any reported effect of amplitude or frequency thresholding for different sensory modalities in the CNS. Proprioceptive sensations are commonly thought to derive from activity in areas 2 or 3a, while cutaneous sensations more likely correspond to activity in areas 3b and 1. From topographical features, we estimate our implants lie in area 1; however, with evidence of interindividual variability in the microstructural organization within S1 (Geyer et al., 1999), and the potential for functional reorganization after injury (Kaas et al., 1983; Florence et al., 1998), it is possible that higher current amplitudes could increase the effective range of stimulation to include sensory areas 3a or 2. Moreover, given the receptive fields activated during stimulation, the two implants are well within the arm and forearm regions of S1, which might receive a larger ratio of proprioceptive-to-cutaneous signals than hand regions (McKenna et al., 1982), making it more likely to activate these different modalities with ICMS.

FG also provided subjective measures of sensation intensity and duration. Sensation intensity was ranked from 1 to 10 (weakest to strongest). In Experiment 1, we found a strong positive correlation between intensity and amplitude (r = 0.2, p=2.1×10−5, Pearson linear correlation coefficient), with an intensity of 2.4 ± 1.9 a.u. (mean ±s.d.) for 20 μA and 4.0 ± 2.1 a.u. for 100 μA, with a slope of 0.02 (1st-order polynomial, least squares fitting). As subjective measures of intensity are most likely sensitive to day-to-day variability, in post-hoc analysis we also normalized intensity values within each session (see Materials and methods). We measured a negative correlation between the current amplitude and the standard deviation of the intensity (r = −0.6, p=0.12). Duration of the percept was recorded for each response as either short (sensation lasts only briefly at the onset of stimulation), medium (sensation persists throughout the stimulation but not for the full length of the stimulation) or long (sensation lasts the full duration of the stimulation). The majority of responses were short (N = 225), followed by medium (N = 122) with very few long responses (N = 12). Stimulus duration was not recorded for 22 responses of the 381 responses. For Experiment 2 this trend was replicated (N = 268, 55 and 1. Short, medium and long, respectively). There was no relationship between duration of the sensation and either amplitude of stimulation (p=0.1, χ2(1323)=4.53) or frequency of stimulation (p=0.2, χ2(1323)=2.83).

To our knowledge, this is the first report in human of replicable, purely naturalistic proprioceptive and cutaneous sensations induced through ICMS. Stimulation over a wide range of amplitudes and frequencies generated qualitatively diverse sensations, although percept modality was strongly linked to variations in amplitude. Pairing these natural sensations with BMIs create a unique opportunity to explore how effectively they can be incorporated in a closed-loop BMI system. For example, the ability to evoke proprioceptive sensations could allow the subject to interpret position- or movement-related information, as previously reported in primate studies (Tomlinson and Miller, 2016; Dadarlat et al., 2015), while eliciting cutaneous sensations could improve our ability to deliver richer somatosensory feedback for object manipulation. Together these somatosensory signals have the potential to improve performance and embodiment when using a BMI-controlled external device.