In our training paradigm, animals learned basic elements of the tasks prior to participating in any BTBI experiments. First, prospective encoder rats were trained to respond to either tactile or visual stimuli until they reached 95% correct trials accuracy. Meanwhile, decoder rats were trained to become proficient while receiving ICMS as a stimulus. A train of ICMS pulses instructed the animal to select one of the levers/nose pokes, whereas a single ICMS pulse instructed a response to the other option. Decoder rats reached a 78.77% ± 2.1 correct trials performance level. After this preliminary training was completed, the animals were run in pairs, each one in a separate operant box.

The next phase of training began with the encoder rat performing ~10 trials of the motor or tactile task, which were used to construct a cortical ensemble template, i.e. the mean cortical neuronal activity for one of the responses. The increased firing rate associated with the right lever press was selected as the parameter extracted from the neuronal ensemble in the motor task. The increased firing rate associated with the “Narrow” trials was selected as the parameter extracted from the neuronal ensemble in the tactile task. A BTBI session followed in which ICMS trains applied to the cortex of the decoder rat reflected the difference between the template and single-trial neuronal ensemble rates produced by a sample of the encoder rat's M1 or S1 activity. ICMS duration (i.e. number of pulses delivered) was proportional to the difference between the sampled neuronal ensemble firing rate recorded during a given trial and the template normalized by the standard deviation. The time window for the analysis of neuronal activity and ICMS parameters was adjusted in each recording session to maximize the directional signal. The decoder rats reacted to ICMS patterns and not any other cues, as was evident from control experiments in which the performance of those rats dropped to chance level after the ICMS cable was disconnected from the stimulator. Furthermore, the encoder rat received feedback information describing the single trial performance of the decoder rat; each time the decoder rat responded correctly to the ICMS cue, the encoder rat received an additional reward (i.e. water).

In experiment 1 (Figure 1), encoder rats (N = 3) pressed one of two levers after an LED on top of the lever was turned on. While the rats did so, M1 neuronal activity was recorded, compared to the template and transformed into ICMS trains applied to M1 of the decoder rats (N = 4) who performed the same lever press task. As would be expected, the encoder rats performed better (95.87% ± 1.83 correct trials) (Figure 2 A) than the decoder rats (64.32 ± 1.1%; range: 60 – 72% correct trials; Binomial test: P < 0.05 in all sessions) (Figure 2 A and B). Yet, the performance of the decoder animals was above chance and highly significant. Indeed, in some experiments the decoder rat's performance using the BTBI was very close to the maximum performance obtained when ICMS was used alone in these animals (72% BTBI vs 78% ICMS alone, see above).

Figure 2 Behavioral performance using a BTBI for transferring cortical motor signals. A) Performance of encoder and decoder animals during transfer of motor information via a BTBI. The performance of the encoder animals was above 90% in all but one session. The BTBI allowed the decoder animals to repeatedly perform significantly above chance. This performance immediately dropped to chance levels when the cable was disconnected but the system remained fully functional. B) The performance of the decoder animals across a session is presented with a moving average of 10 trials. C) The panel depicts the fraction of right lever presses after different microstimulation patterns were delivered to the decoder's M1. As the number of microstimulation pulses increased, a higher fraction of right lever presses occurred. The microstimulation threshold for response in most animals was situated between 41 and 60 pulses. Full size image

The primary factor that influenced the decoder rat's performance was the quality of spatial information extracted from the encoder rat's M1. The performance was high if the chosen neuronal ensemble accurately encoded left versus right presses (Figure 2 C and Figure 3 A–D). The higher the deviation from the template and hence the larger the duration of the ICMS (i.e. number of pulses delivered), the better was the decoder rat's performance (Figure 2 C and 3 B–D). For this first experiment, a total of 538 units and 110 multiunits were recorded from encoder rats. Sessions were comprised of 48.04 ± 1.5 trials. The response latency of the encoder rats was 20.06 ± 1.0 seconds, while decoder animals responded at 13.59 ± 0.5 seconds. Note that this difference reflects only the effect of both rats working as a dyad (see below for comparison of latencies during training and testing).

Figure 3 Trial examples of a BTBI for transferring cortical motor signals. A) Examples of M1 neurons recorded while the encoder rat performed the task. Time = 0 corresponds to the lever press. Very different patterns of increased and decreased activity were observed before and after the lever press, suggesting that multiple task parameters were encoded by this M1 ensemble. B) Sample of trial by trial choices of the rat dyad (encoder and decoder) during execution of the motor task. The encoder's performance is depicted by a blue line, while a red line indicates the decoder's choices in the same trials. In trials 4,7,11 and 13 the behavioral response of the decoder rat did not match the one of the encoder. The overall performance of the decoder rat in this session was 69% correct. C) The bars represent the number of encoder's M1 neuronal spikes recorded during each trial. The neuronal ensemble used in this session encoded very accurately each of the behavioral responses. D) Number of ICMS pulses delivered to the decoder's M1 that resulted from the comparison of each trial in C to the template. Full size image

In addition to the neuronal transfer from the encoder to the decoder rats, feedback information, related to the decoder rats' performance, was sent back to the encoder animal. This feedback provided an additional reward to the encoder rat every time the decoder rat performed a trial correctly. Under these conditions, the encoder rats' response latency decreased after the decoder rat made an error (after correct response: 20.67 ± 1.665 seconds and after an incorrect response = 15.26 ± 2.031 seconds; Mann Whitney U = 13570; P < 0.0001). Furthermore, an analysis of the variation in Z-scores, demonstrated that the signal to noise ratio of the neural activity extracted from the encoder rat's M1 increased after the decoder rat committed an error (Chi Square = 4.08, df = 1; P = 0.0434). Thus, both the behavior and neuronal modulations of the encoder rat became dependent on the trial by trial behavioral performance of its dyad partner, the decoder rat.

In experiment 2, we tested whether a BTBI could enable a real-time transfer of tactile information between a pair of rats' brains (Figure 4). Encoder rats (N = 2) were trained to discriminate the diameter of an aperture width with their whiskers17. If the aperture was narrow, rats were required to nose poke on the left side of the chamber, otherwise they had to poke on the right side of the chamber. Decoder rats (N = 5) were trained to poke on the left water port (narrow aperture) in the presence of ICMS and on the right water port (wide aperture) in the absence of ICMS. Similar to experiment 1, the difference between the S1 neuronal ensemble activity, recorded while the encoder rat examined the aperture with its whiskers in each trial and an average template obtained previously, was utilized to create ICMS patterns applied to the decoder rat's S1. We named these ICMS patterns virtual narrow and virtual wide. A total of 120 units and 223 multiunits were recorded in experiment 2.

Figure 4 Experimental apparatus scheme of a BTBI for transferring cortical tactile information. A) In the tactile discrimination task, the encoder animal was required to sample a variable width aperture using its facial whiskers. The width could be “Narrow” as shown in the left photograph, or “Wide”. After sampling, the encoder animal had to report whether the aperture was narrow or wide by nose poking on a left or right reward port respectively. If correct, the animal received a small water reward. As the encoder explored the aperture, a sample of its S1 activity was recorded, compared with a template trial and then transferred to the decoders' S1 via ICMS. The pattern of microstimulation constantly varied according to the number of spikes recorded from the encoder rat's S1 in each trial. The decoder rat was required to make a response in the reward port corresponding to the width sampled by the encoder, guided only by the microstimulation pattern. If the decoder rat accurately responded in the correct reward port, both rats received a small water reward. Thus, the encoder rat received an additional reward in case both animals of the dyad performed a trial successfully. Full size image

The BTBI accuracy for tactile information transfer was similar to that observed in experiment 1 (Figure 5 A–B). While encoder rats performed at 96.06 ± 1.14% correct, decoder animals performed somewhat worse but significantly above chance (Percent correct: 62.34 ± 0.59%, range 60 – 64.58%; Binomial test: P < 0.05 in all sessions) (Figure 5 A–B and Figure 6 A–D). In this second experiment, the response latency of encoder rats was 2.66 ± 0.1 seconds, while in decoders the latency was 2.68 ± 0.09 seconds.

Figure 5 Behavioral performance using a brain-to-brain interface to transfer cortical tactile information. A) Performance of encoder and decoder animals during operation of a BTBI for tactile information sharing. Notice that the performance of the encoder animals was above 85% in all sessions. The performance of the decoder animals was above 60% in all sessions presented and immediately dropped to chance levels when the cable was disconnected but the system remained fully functional. B) Performance of all decoder animals analyzed with a moving average of 10 trials. C) The panel depicts the fraction of the decoder's responses in the Narrow reward port after different patterns of microstimulation were delivered. As the number of microstimulation pulses increased a higher fraction of responses was observed in the Narrow reward port (Virtual Narrow choice), suggesting that the microstimulation threshold of response for decoder animals was situated between 26-40 pulses. Full size image

Figure 6 Trial examples of a BTBI for transferring cortical tactile signals. A) Examples of S1 neurons recorded while an encoder rat performed the aperture discrimination task. Time = 0 corresponds to the moment the animal breaks the photo beam in front of the discrimination bars. B) Blue lines represent the choices of the encoder rat and red line represents the choices of the decoder rat. In trials 8, 15 and 17 the decoder rat selected the incorrect reward port. C) Number of action potentials recorded from 3 S1 neurons in each trial after the whiskers sampled the discriminanda. Typically, a higher spike count was found for narrow trials, when compared to wide trials. D) Number of pulses delivered to the S1 cortex of the decoder rat in each trial. The number of pulses delivered to the S1 cortex of the decoder rat was directly derived from the number of spikes present in the encoder animal in each trial. The overall performance achieved by the rat dyad in this session was 64% correct trials. Full size image

To further demonstrate that the accuracy of the decoder rats' performance was based on the ICMS patterns, which in turn were triggered by larger number of spikes produced by S1 neuronal ensembles, we compared the fraction of Virtual Narrow choices with the number of ICMS pulses delivered to the decoder's S1 cortex. Increases in the number of ICMS pulses delivered to the decoder's S1 were associated with a higher fraction of Virtual Narrow choices (≤ 25 pulses: 0.3966 ± 0.04476 correct; >25 pulses: 0.5433 ± 0.02991 correct; Paired samples t-test = 2.321, df = 16, P = 0.0338) (see Figure 5 C and Figure 6 A–D ). Since ICMS patterns were directly derived, through a transfer function, from the neural ensemble activity recorded from the encoder animal's S1 cortex in each trial, this result demonstrates that the decoder rat's correct choices relied on the accuracy of the ICMS pattern in reproducing the number of action potentials generated by the real tactile stimulus information presented to the encoder rat. Feedback information, providing an additional reward to the encoder rat every time the decoder rat performed a trial correctly, also induced changes in the neural activity of the encoder rat. The encoder's latency of response was similar after correct and incorrect trials (After correct = 2.6 ± 0.1 secs; After incorrect = 2.7 ± 0.2 secs; Mann Whitney U = 19790, P = 0.49). However, similarly to the effects observed in experiment 1, the signal to noise ratio of neural activity in S1 also increased after an incorrect trial (Chi Square = 4.2, df = 1; P = 0.0404).

It could be argued that the results reported here could have been obtained if prerecorded signals from encoder rats had been used to guide the behavior of the decoder rats. Qualitative and quantitative observation of the behavior of the animals reveals that this is not at all the case. In both motor and tactile BTBI sessions we observed drastic changes in the behavior of encoder and decoder rats as soon as they started to work as part of a dyad. Both encoder and decoder animals either made quick attempts to respond earlier or, conversely, they reduced their response rate or even stopped performing according to the dyad behavior. Thus, response latencies during motor BTBI sessions were largely increased for encoder animals (encoder training: 14.77 ± 0.9 seconds; encoder BTBI session: 20.06 ± 1.0 seconds; t = 3.975, df = 1170, P < 0.0001) and decreased in decoder rats (decoder training: 16.29 ± 0.6 seconds; decoder BTBI sessions: 13.59 ± 0.5 seconds; t = 3.559, df = 1636, P = 0.0004). During the tactile BTBI sessions the responses latency was reduced in both encoder (encoder training: 5.40 ± 0.6 seconds; encoder BTBI sessions: 2.66 ± 0.1 seconds; Mann-Whitney U = 13960, P < 0.0001) and decoder animals (decoder training: 4.632 ± 0.6 seconds; decoder BTBI sessions: 2.68 ± 0.09 seconds; t = 4.638, df = 12, P = 0.0006) as they started to work as a dyad. Therefore, the dyad performance depended on the nature of the task performed jointly by the animal pair. Likely the increased latencies observed in the motor task reflect the fact that pressing a lever is a learned artificial behavior, while the exploratory nose poking necessary for the tactile task is part of the rats' natural behavioral repertoire. These overall changes in the dyad behavior, irrespective of their direction (e.g. increased or decreased latency), are a clear indicator that a fundamentally more complex system emerged from the operation of the BTBI; one which required considerable adaptation from the participant animals so that they could jointly perform the sensorimotor tasks.

As the ICMS cues were delivered to primary cortical areas that are commonly involved in processing motor and somatosensory information in intact animals, we further asked how the decoder rat's S1 cortex represented both real tactile stimuli, generated by mechanical stimulation of its own facial whiskers and ICMS signals representing the encoder rat's whisker stimulation, during operation of a BTBI. To measure this, we tested pairs of encoder and decoder rats during passive transmission of tactile information via a BTBI, while the whiskers of the encoder and decoder rats were mechanically stimulated. This experiment consisted of two parts: first, the encoder animal was lightly anesthetized and head fixed to an automated whisker stimulator that accurately reproduces the movement and speed at which the whiskers interact with the bars in the active tactile discrimination task (see Methods). The animal's S1 neural activity following each movement of the bars was analyzed in real time and delivered, as an ICMS pattern, to the decoder rat's S1. Meanwhile, the decoder rat remained in an open field in a different room while its S1 neural activity was recorded. After this phase was completed, the decoder animal was also lightly anesthetized and placed in the automated whisker stimulator. This allowed us to determine how the decoder rat's S1 neuronal sample, that responded via the BTBI to the tactile stimuli delivered to the encoder's whiskers, responded to tactile stimuli elicited by passive whisker stimulation of their own vibrissae.

Passive whisker stimulation, in either the encoder or decoder rats, induced significant firing modulations in the decoder rat's S1. These were characterized by clear increases of firing activity occurring immediately after the moving bars touched the whiskers of each animal (see Figure 7 A and B). These significant S1 neuronal responses occurred in 70.91% (39/55 multiunits) of the microwires implanted in the decoder rat's S1, which were used to deliver ICMS patterns through the BTBI and in 93.06% (67/72 multiunits) of the microwires from which S1 neuronal activity was recorded from decoder rats (see Figure 7 B and C). The magnitude of the S1 tactile responses elicited by mechanical stimulation of the decoder rat's facial whiskers was 4.82 ± 0.4 spikes/trial and the duration was 111.4 ± 11 ms. During the BTBI transmission, ICMS of the decoder's S1 induced a significant increase of S1 neurons firing activity lasting for 119.7 ± 20 ms. Due to the microstimulation artifact in the recordings, we focused our analysis on the firing activity increases occurring after the last pulse of microstimulation was transmitted (see red traces Figure 7 C).

Figure 7 Neural activity in the decoder brain discriminates stimuli applied to the encoder's whiskers. PSTHs on the left panels show S1 neuronal responses during the wide tactile stimulus whereas PSTHs on the right panels depict narrow tactile stimulus. The top and middle panels show S1 activity recorded in anesthetized encoder and decoder rats while their facial whiskers were passively stimulated by a set of moving bars. The moving bars generate a tactile stimulus exactly like the one produced during the tactile discrimination task. The lower panels represent the decoder rat's S1 activity while receiving ICMS (red traces) via a BTBI that transmitted tactile information from an anesthetized encoder rat which was having its whiskers passively stimulated. Time zero in all panels corresponds either to the tactile stimulus or the last microstimulation pulse. A) A clear peak of S1 activity can be observed immediately after the encoder's whiskers contacted the bars (other peaks occurred due to rebounding of the moving bars). Increased counts of action potentials were typically associated with the narrow stimulus (compare peaks in left versus right panels). B) Like encoder rats, when the decoder rats' whiskers were passively stimulated by the moving bars, clear peaks of S1 activity with different heights can be observed (see left versus right panels). C) When the encoder rats' whiskers were passively stimulated (shown in A) and the BTBI was used to transfer tactile information in real time (shown in C), clear increases in activity were observed in the decoder's S1 cortex after time 0. These S1 firing modulations were larger when the narrow stimulus was applied to the encoders' whiskers when compared to the wide stimulus (see left versus right panels) and were observed in the same S1 neuronal ensembles that responded to natural whisker stimuli (shown in B). Thus, the S1 neuronal responses observed in the decoder rat demonstrate that it learned to use the BTBI and that a representation of the tactile stimuli applied to the encoders' whiskers could be superimposed on the preexisting representation depicting tactile stimuli applied to its own facial whiskers. Full size image

Analysis of the data obtained during passive BTBI communication further demonstrated that S1 neurons in the decoder's brain responded differently for each of the virtual tactile stimuli. More than half of the S1 multiunits recorded presented differential firing rates for Virtual Wide and Virtual Narrow stimuli (28/44 = 63.64% multiunits). Also, the Virtual Narrow stimulus was characterized by higher neuronal response magnitudes (Virtual Narrow: 3.861 ± 0.6229 spikes/trial; Virtual Wide: 2.200 ± 1.079 spikes/trial; Wilcoxon sum of ranks = 197; P = 0.0182) and durations (Virtual Narrow: 102.7 ± 16.28 ms; Virtual Wide: 31.54 ± 14.85 ms; Wilcoxon sum of ranks = 200; P = 0.0074). To measure whether the differences in firing rates were due to discrimination or due to an ‘upstate' related to the repeated microstimulation, we also compared which S1 multiunits exhibited different firing rates for Virtual Narrow and Virtual Wide. From the total of S1 multiunits that displayed differences in firing rates for the discrimination period, we found that 35.7% (10/28 multiunits) had no significant differences in the baseline firing rate. Thus, more than one third of the S1 multiunits recorded showed no signs of an ‘upstate' in their baseline due to repeated microstimulation. This supports the hypothesis that after the decoder rats learned to use the BTBI, via ICMS cues, their S1 became capable of accurately representing, processing, storing and recalling information about both the tactile stimuli delivered to its own whiskers, as well as mechanical displacements of the encoders' facial vibrissae.

Finally, to further demonstrate the range of potential operation of our BTBI preparation, we tested whether a long-distance communication of a rat dyad, with the encoder rat performing the tactile discrimination task at the ELS-IINN (Natal, Brazil) and the decoder rat receiving patterns of microstimulation and responding at Duke University (Durham, USA), would be capable of performing the same task. For this, neural activity recorded from S1 of the encoder rat performing the tactile discrimination task was sent via an internet connection and delivered, as an ICMS pattern, to the decoder rat S1 (Figure 8). Even under these extreme conditions, the BTBI was also able to transfer in real-time behaviorally meaningful neuronal information. Although the mean time of data transmission observed in this long-distance BTBI was increased from 20 ms (during transmission in our Duke lab) to 232 ± 217.5 ms, a similar number of correct responses was found (short distance transmission: 62.34 ± 0.59%; long distance transmission: 62.25% ± 0.71) in 26.5 ± 0.5 trials in the decoder animals.