NeuroHub: Portable and Scalable Time Synchronization Instrument for Brain-Computer Interface and Functional Neuroimaging Research

The advent of new and improved brain imaging tools in recent decades has provided significant progress in understanding the physiological and neural bases of motor and cognitive processes and behavior. As neuroimaging and brain sensing technologies are further developed, they are miniaturized and become portable and wearable, allowing brain activity monitoring in ecologically-valid everyday environments. This introduces the possibility of using multiple systems concurrently on i) the same brain: multimodal/hybrid measurements for better identification of neurophysiological markers, and ii) multiple brains: hyperscanning for novel investigations of brain functions during social interactions. In all of these new directions, seamless integration of various neuroimaging systems is required. More specifically, precise time synchronization of acquired data streams is necessary for proper analysis and interpretation of results. However, there are currently no standards for interoperability and neuroimaging systems have many different designs and interfaces. Experiment setups using multiple systems may require extensive development for a customized solution that would need reconfiguration at the expense of additional time and effort, with the risk of possibly varying precision based on the custom solution. To address these issues, we have developed NeuroHub, a scalable device that can provide plug and play and reliable time synchronization by interfacing with common ports in neuroimaging systems. The device consists of a custom printed circuit board that fits atop an inexpensive and readily available development board for an Atmel ATmega2560 embedded microcontroller. It is housed in a 6 x 11 x 3.5 cm durable plastic casing, smaller than most smart phones, and includes BNC, serial, and parallel communication ports located around its perimeter. The device propagates any synchronization marker it receives from one of the ports and broadcasts it to all systems connected at other ports. The device can be extended as necessary by connecting multiple NeuroHub units. Verification and validation tests indicated reliable byte transmission with 100% accuracy of transmission and a consistent 1.020 millisecond latency in its standard configuration. A program was also developed for automated testing with Monte Carlo simulation, by sending and receiving event markers in various configurations. Through these tests, it became clear how unfit the use of multiple common computer ports is for sub-millisecond precise modality recording, due to their non-embedded nature. This problem is alleviated using NeuroHub as it allows synchronization of each computer through only one port. NeuroHub was implemented in two use cases to demonstrate its potential: i) Multimodal spatial navigation brain computer interface (BCI) that used simultaneous EEG and fNIR for enabling controlling actions within MazeSuite generated virtual environment. ii) Synthetic speech perception study which utilized two different fNIR systems simultaneously to record from a larger area. In the first use case, the naïve P300 response is used as a selection mechanism for a number of options for first-person navigation of a maze. fNIR measurements are used to assess if the person is attentive to the stimuli, which results in higher accuracy scores. For this setup to be successful, markers between the software for stimulation presentation, EEG recording, P300 analysis, maze presentation, and fNIR recording must be synchronized. In the second use case, subjects are presented with audio recordings of 5 sentences over 4 levels of quality of speech signal, ranging from natural speech to low quality synthesized speech, and asked to rate them for naturalness and intelligibility, while fNIR measurements are recorded to provide quantitative data about how cognitively taxing the synthesized speech is that has become common in everyday devices. In this experiment, information must be synchronized between the stimulus computer and the two fNIR recording devices. Both of these use cases demonstrate NeuroHub’s utility in next generation experiment setups with the goal of helping brain computer interface and functional neuroimaging research.M.S., Biomedical Engineering -- Drexel University, 201