Stephanie Jones

Faculty

Stephanie Jones

Author: 
Sara Feijo

Brown University computational neuroscientist Stephanie Jones has received the BIOMAG2020 Mid-Career Award for her transformative contributions to the field of biomagnetism research. 

BIOMAG is a biennial international conference organized by the Biomagnetism Research Community that is focused on latest developments in instrumentation, modeling approaches and basic and clinical biomedical studies of biomagnetism. The interdisciplinary field of biomagnetism includes dynamic and evolving technologies, offering advanced real-time methods for non-invasive assessments of magnetic signals, such as those from the brain, as well as a range of computational methods for localization and interpretation of the signals. 

Jones received the BIOMAG award for her work developing the open-source software Human Neocortical Neurosolver (HNN) to better understand circuit mechanisms of human brain signals with neural modeling, as well as applications leading to novel insights on the mechanisms and functions of human brain rhythms. HNN allows researchers and clinicians to uncover the brain circuits that generate the signals from electroencephalography (EEG) and magnetoencephalography (MEG) brain recordings.

“It is thrilling and motivating to be recognized in this way,” said Jones, an associate professor of neuroscience affiliated with the Carney Institute for Brain Science and the Providence VA Center for Neurorestoration and Neurotechnology. “It’s also extremely humbling as there are many in the field deserving of this award. I, of course, also feel gratitude for all those who have contributed to my career, including many mentors and amazing present and past lab members. This award belongs to all of us.” 

Jones’ cross-disciplinary work links cellular network circuitry models of brain activity and whole-head MEG signals. Olaf Hauk, chair of the BIOMAG2020 Awards Committee, said Jones’ easy-to-use HNN software is a powerful tool to develop and test hypotheses about brain circuit mechanisms.

“Jones’ strongly interdisciplinary research does not only demonstrate how to do EEG/MEG research at the highest standards, but also why we are doing it: namely to reveal the neurophysiological mechanisms that underlie perception, cognition and behavior,” Hauk said. “Her work has produced ground-breaking novel insights into the nature of rhythmic brain activity.”

Jones took a break from computational modeling to discuss the HNN software and how she is expanding the scope of her research to include Transcranial Magnetic Stimulation (TMS), a non-invasive brain stimulation technique. 

Q: Tell us about your work developing computational models to interpret the neural origin of human MEG/EEG signals.

MEG/EEG are incredibly powerful technologies to non-invasively study human brain activity in health and disease. However, it is difficult to interpret the underlying cellular and circuit level generators. This micro-circuit level understanding is critical if we want to use MEG/EEG to understand how the brain works, or to develop new treatments when the brain isn’t working properly. The models we are building are specifically designed to provide the bridge between the extracranially-measured signal and the detailed neural circuit level generation. This bridge also allows us to connect these human signals to the wealth of information being obtained in animal models, where genetic manipulations and detailed circuit recordings are possible. 

With funding from the NIH BRAIN Initiative, we have recently turned our modeling framework into a freely available user-friendly software tool, called Human Neocortical Neurosolver, for the broad MEG/EEG community to use to develop and test predictions on the neural origin of their data. Interest in this tool is growing, and we are helping several groups adapt to their studies. 

Q: How has the Carney Institute community contributed to your cross-disciplinary research program?

Brown and the Carney community have contributed to my research program in profound ways. My lab is situated in the new Carney Institute space on the 4th floor of 164 Angell St. The ecosystem in this space facilitates the interaction of my group with other groups on campus working in the areas of computational neuroscience, engineering and data science. Our research is inherently collaborative, and the integrated Carney environment provides the ideal setting for us to learn from each other and effectively collaborate. 

Q: What's next in your research?

Carney is providing the space and equipment for us to expand our research to include TMS, a non-invasive brain stimulation technique used to perturb brain circuits and behavior. Our TMS work is also supported by Carney’s COBRE Center for Central Nervous System Function and the Carney Institute Salem Postdoctoral Fund.  

We are using insight from our model-derived understanding of the mechanisms of beta rhythms to develop new stimulation paradigms aimed at perturbing these rhythms in a principled way to causally impact somatosensory perception. Ultimately, we hope to expand our studies to improve painful perception. We are also collaborating with colleagues at the Center for Neurorestoration and Neurotechology at Providence VA Medical Center to apply HNN to help develop TMS paradigms for neuropathologies, such as PTSD and depression.

We continue to develop our HNN software into a broadly accessible tool for the MEG and EEG community. We are also furthering research pioneered by my former Brown collaborator, the late Catherine Kerr, to study the impact of a mind-body energy practice called Qigong on physiological measures of improved health. The interaction between the brain and the body is an understudied area of neuroscience, but one where transformative ideas are emerging. We are collaborating with Brown’s Contemplative Studies program to organize an online workshop to discuss the history, clinical benefits and scientific exploration of this Chinese energy practice. We hope to formalize an initiative in Cathy’s honor to continue this timely line of research.