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Brain-to-Brain Communication Using Non-Invasive Technologies

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A recent development of brain-computer interfaces (BCI) has provided an important element for the creation of brain-to-brain communications.

In a series of experiments, establishment between internet-mediated B2B communication by combining a BCI based on voluntary motor imagery-controlled electroencephalographic (EEG) changes with a CBI inducing the conscious perception of phosphenes through neuronavigated, robotized transcranial magnetic stimulation, with special care taken to block sensory (tactile, visual or auditory) cues.

Four healthy participants (age range 28–50) were tested, one was assigned to the BCI branch (the emitter – Subject 1) and the other three to the CBI branch of the experiments (i.e., as receivers – Subjects 2, 3 and 4).

>The computer-mediated brain-to-brain transmission from Thiruvananthapuram (Kerala state, India) (BCI side) to Strasbourg, France (CBI) was realized using internet-linked EEG and TMS technologies respectively. On the CBI side, three information receiver subjects were stimulated with biphasic TMS pulses at a subject-specific occipital cortex site. The intensity of pulses was adjusted for each subject so that a) one particular orientation of the TMS-induced electric field produced phosphenes [19] (representing the “active direction” and coding the bit value “1”), and b) the orthogonal direction did not produce phosphenes (representing the “silent direction” and coding the bit value “0”). Subjects reported verbally whether or not they perceived phosphenes on stimulation. A fourth subject acted as emitter of information using a BCI system based on motor imagery (of moving feet or hands) to select two kinds of states in EEG spectral power in the motor cortex (coding for the bit values of “0” and “1”). We ensured that receiver subjects were not relying on peripheral nervous system (PNS) cues (visual, tactile and auditory sensations produced by the TMS device) to decode the information by blocking sensory cues: we used a force sensor on the coil to maintain a constant contact pressure on the scalp, implemented a coil rotation information encoding strategy (as opposed to one relying on coil location), and had subjects wear eye mask and earplugs. We verified the effectiveness of these means in series of d-prime control experiments [20]–[22] comparing pairs of stimuli delivered either with the same or different orientations of the coil. Finally, as performance measures for the BCI, CBI and B2B system we analyzed error transmission rates and transmission speed (bits per minute).

Brain-Computer Interface

The BCI communication subsystem used in our experiments converted conscious voluntary motor imagery into brain activity changes that could be captured non-invasively as physical signals conveying information. To monitor EEG activity related with motor imagery tasks we used a wireless (500 S/s, 24 bit) EEG recording system [23] (Starstim tCS/EEG system, by Neuroelectrics,


>The final round of experiments targeted the demonstration of online brain-to-brain transmission of information between remotely located subjects. On March 28th, 2014, 140 bits were encoded by the BCI emitter in Thiruvananthapuram and automatically sent via email to Strasbourg, where the CBI receiver (subject 3) was located. There, a program parsed incoming emails to navigate the robot and deliver TMS pulses precisely over the selected site and with the appropriate coil orientation. A similar transmission with receiver subject 2 took place on April 7th, 2014. In both cases, the transmitted pseudo-random sequences carried encrypted messages encoding a word – “hola” (“hello” in Catalan or Spanish) in the first transmission, “ciao” (“hello” or “goodbye” in Italian) in the second. Words were encoded using a 5-bit Bacon cipher [31] (employing 20 bits) and replicated for redundancy 7 times (for a total of 140 bits). The resulting bit streams were then randomized using random cyphers selected to produce balanced pseudo-random sequences of 0’s and 1’s (for subject blinding and proper statistical analysis purposes in addition to providing word-coding). On reception, de-cyphering and majority voting from the copies of the word were used to decode the message.


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“Brain-to-Brain Communication Using Non-Invasive Technologies”