Imagine your thoughts—your needs, your questions, your feelings—held captive, with no reliable way to be heard. This is the daily reality for many individuals with communication disabilities, and it’s the mission that drives Queen’s PhD candidate and Connected Minds trainee Sonja Bonar in her quest to develop brain-computer interfaces (BCIs) that give voice to silent thoughts. Working at the intersection of neuroscience, engineering and human connection, Sonja is developing BCIs that translate internal speech, also known as covert speech, into meaningful communication. As a researcher in the Building and Designing Assistive Technology Lab supervised by Dr. Claire Davies, she’s taking on one of the most nuanced challenges in neurotechnology: enabling individuals with communication disabilities to communicate using covert speech alone.
Sonja’s path into this research area didn’t follow a straight line. “I was interested in prosthetics at the beginning [of graduate school],” she explained during a recent interview. Early on in her time at Queen’s, she became involved in a side project that would ultimately reshape her research direction: observing focus groups made up of individuals who use augmentative and alternative communication (AAC) devices. These tools help people with motor and communication impairments to express themselves, alongside their caregivers and device manufacturers. “A parent said, ‘I wish we could just have direct thought-to-communication devices.’ And I was like, OK, well, why can’t we?”
That question became the foundation of her doctoral research. Today, Sonja is focused on decoding covert speech from brain signals to build BCIs for individuals who cannot rely on traditional forms of communication.
Rewriting the Rules of Speech Development
Sonja’s work challenges a longstanding psychological theory by Lev Vygotsky, which holds that covert (or inner) speech can only develop from spoken dialogue. “Just by looking at that theory, it excludes populations that have not been able to communicate reliably since development, or individuals with developmental communication impairments,” Sonja said. To explore the assumptions underlying this theory, she conducted a survey with adults who have developmental communication and motor impairments. “What I found from the survey is that this population, who has never been able to reliably speak out loud… actually can develop covert speech.” These findings suggest that inner speech can develop even in the absence of spoken dialogue, calling into question the dominant hypotheses on the form of covert speech. “If this population can use covert speech, this is potentially a more intuitive or natural input for a BCI compared to other input methods,” Sonja explains.
Traditional communication devices often rely on methods like eye-tracking or visually evoked potentials—electrical signals recorded from the brain in response to visual stimuli—where users focus on flashing letters to spell out words. Recently, motor imagery has emerged as a promising BCI input for AAC devices, requiring users to imagine physical movements, such as moving a hand or articulating with the mouth, to trigger a response. But for individuals who have never reliably spoken or performed these movements, this type of imagery can be abstract, cognitively demanding, or difficult to use due to their lack of motor experience and the system’s reliance on consistent, learned patterns. Covert speech, by contrast, may offer a more direct and intuitive path from thought to communication.
In the current phase of her research, Sonja is exploring whether covert speech can be reliably decoded from brain activity. She is currently recording electroencephalography (EEG) data from typically developing adults as they silently respond to simple yes-or-no questions. “They’re asked questions that have obvious yes or no answers,” she explains. “I wanted them to be asked questions audibly because that would be the most realistic in any sort of interaction in real life.”
Her early results are promising. In a pilot study, she was able to distinguish between participants’ internal “yes” and “no” responses with approximately 83% accuracy, suggesting that decoding covert speech may be feasible . Encouraged by these findings, Sonja plans to extend the study to adults with developmental communication and motor impairments, focusing on whether similar neural patterns can be observed across participant populations.
From Academia to Industry: An Internship with Impact
As her research continues to push the boundaries of what’s possible in brain-computer interface design, Sonja is also stepping into the world of industry. This summer, she’s joining VIBRAINT Inc. , a Toronto-based neurotechnology startup, for a Connected Minds-sponsored internship that will immerse her in the applied side of BCI systems.
“VIBRAINT works on motor rehabilitation with brain-computer interface technologies and VR… through decoded motor imagery tasks (with EEG) where a client’s arm is moved by a robotic arm manipulator to match their intended movement,” she explains. While her own research centers on communication rather than movement, Sonja recognizes a valuable connection between the two domains. “This work is very complimentary to my current project… Motor imagery is a common BCI input method for communication devices, so it’s [interesting] to see the process of decoding motor imagery up close.”
The opportunity emerged through a connection made through Connected Minds. “I got my internship through a connection that I made at Connected Minds, Dr. Lauren Sergio from York University,” Sonja says. “I had been interested in VIBRAINT’s work months before I was in contact with them… I remembered Dr. Sergio from the VIBRAINT website… When I reached out to her, she was able to put me in contact with VIBRAINT.”
Looking Ahead
Sonja’s research offers a hopeful glimpse into the future of communication—but it also highlights the practical limitations of current technology. “The device I use takes two hours to set up,” she explains, citing the time-consuming process of adjusting sensors, troubleshooting connections, and managing the bulky equipment. “There are a lot of ways that it’s still impractical as a communication device… it’s definitely not usable [in everyday settings].”
Still, the promise of her research extends beyond proof-of-concept studies. By demonstrating that covert speech can be decoded with accuracy, Sonja’s work lays the foundation for a new class of assistive technologies—tools that are not only scientifically viable but are designed for real-world use. It’s a step toward more portable, accessible BCI systems that could one day offer seamless communication for those who need it most.
