Abstract
A non-invasive, brain-to-brain interface (BBI) requires precision neuromodulation and high temporal resolution as well as portability to increase accessibility. A BBI is a combination of the brain–computer interface (BCI) and the computer–brain interface (CBI). The optimization of BCI parameters has been extensively researched, but CBI has not. Parameters taken from the BCI and CBI literature were used to simulate a two-class medical monitoring BBI system under a wide range of conditions. BBI function was assessed using the information transfer rate (ITR), measured in bits per trial and bits per minute. The BBI ITR was a function of classifier accuracy, window update rate, system latency, stimulation failure rate (SFR), and timeout threshold. The BCI parameters, including window length, update rate, and classifier accuracy, were kept constant to investigate the effects of varying the CBI parameters, including system latency, SFR, and timeout threshold. Based on passively monitoring BCI parameters, a base ITR of 1 bit/trial was used. The optimal latency was found to be 100 ms or less, with a threshold no more than twice its value. With the optimal latency and timeout parameters, the system was able to maintain near-maximum efficiency, even with a 25% SFR. When the CBI and BCI parameters are compared, the CBI’s system latency and timeout threshold should be reflected in the BCI’s update rate. This would maximize the number of trials, even at a high SFR. These findings suggested that a higher number of trials per minute optimizes the ITR of a non-invasive BBI. The delays innate to each BCI protocol and CBI stimulation method must also be accounted for. The high latencies in each are the primary constraints of non-invasive BBI for the foreseeable future.
Highlights
Non-invasive brain-to-brain interface (BBI) requires precision neuromodulation, device portability, and high temporal resolution to increase accessibility (Rao et al, 2014; Lee et al, 2017; Jiang et al, 2019)
The delays innate to each brain–computer interfaces (BCIs) protocol and computer–brain interface (CBI) stimulation method must be accounted for
As the medical monitoring system showed the highest information transfer rate (ITR) of the typical BCIs, its results were generalized to the other systems
Summary
Non-invasive brain-to-brain interface (BBI) requires precision neuromodulation, device portability, and high temporal resolution to increase accessibility (Rao et al, 2014; Lee et al, 2017; Jiang et al, 2019). Two relevant non-invasive neuromodulation methods include transcranial focused ultrasound (TFUS) and transcranial magnetic stimulation (TMS) (Lee et al, 2018). A non-invasive BBI can potentially operate with limited. Optimizing Non-invasive Brain-to-Brain Interface computational resources, but no work has yet investigated the potential limitations of a general purpose, non-invasive BBI (Lee et al, 2017; Rao, 2019, Toward neural co-processors for the brain: combining decoding and encoding in BCIs 2019). Brain-to-brain interfaces have been demonstrated with both invasive and non-invasive methods in humans and animals. A BBI is a combination of a BCI and a computer–brain interface (CBI)
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