When surgeons perform brain surgery on individuals with brain tumors or epilepsy, it is crucial to remove the tumor or abnormal tissue while preserving parts of the brain that control language and movement.
A new study by Northwestern Medicine may better inform doctors' decisions about which brain areas to preserve, thereby improving patients' language function after surgery. The study expands the understanding of how language is encoded in the brain and identifies key features of critical sites in the cerebral cortex that work together to produce language.
If one considers the brain's language network as a social network, scientists have essentially found the person who links various subnetworks. These "connectors" serve a similar function for language in the brain. If these connector sites were removed, patients would make more language errors post-surgery because the subnetworks could not collaborate effectively.
The study will be published on September 16 in Nature Communications.
Northwestern scientists identified critical language connector sites by recording electrical signals from the cortex of patients with epilepsy or brain tumors while they read words aloud. Investigators then analyzed these signals using graph theory methods and machine learning to predict which sites in the network were critical.
"This discovery could help us be more precise and efficient when we're mapping language sites before surgery," said corresponding author Dr. Marc Slutzky, professor of neurology at Northwestern University Feinberg School of Medicine and a Northwestern Medicine neurologist. "It could help us augment the way surgeons do this mapping, so ultimately it could potentially shorten the time needed for stimulation or possibly eliminate the stimulation and just record electrical signals."
Patients with brain tumors or epilepsy often undergo functional mapping using direct electrical stimulation of the brain to identify critical parts of the cerebral cortex so neurosurgeons know which sites to avoid removing to preserve language. For example, electrical stimulation might temporarily interrupt speech ability or object naming, indicating that area’s importance to speech or language function.
"The way this is done hasn’t changed significantly in over 50 years, yet exactly what is happening during this stimulation is still not well understood," Slutzky said. "It is not clear what is special about the focal sites identified by stimulation as critical to language and speech."
"When someone is speaking, many sites in the brain are active, yet only a handful are identified as critical by being perturbed during stimulation. Answering this question could help us understand how electrical stimulation affects the brain and how it produces spoken language."
Currently, many patients with brain tumors undergo between 20 and 60 minutes of awake surgery for functional mapping via electrical stimulation. This technique can yield false negatives or positives and may cause seizures.
"It’s not fun for the patient," Slutzky said. "When we do it for epilepsy patients, mapping can take a day or sometimes two and is exhausting for them."
Epilepsy patients may need surgery when medications don’t adequately control seizures.
Scientists recorded electrical signals from 16 patients (at Northwestern Memorial Hospital and Johns Hopkins Hospital) with either epilepsy or brain tumors. Electrode arrays were implanted in people with epilepsy as part of their seizure monitoring prior to surgery or placed temporarily on brains during awake surgeries for tumor removal.
Patients read single words aloud from a monitor while investigators recorded their electrocorticography signals. Scientists then analyzed these signals using metrics from graph theory—a branch of mathematics focused on networks—and used machine learning to predict which network sites were critical based solely on these metrics. Critical sites tended to connect across communities within networks.
Other authors include Jason K. Hsieh, Prashanth R. Prakash, Robert D. Flint, Zachary Fitzgerald, Emily Mugler, Jessica W. Templer, Joshua M. Rosenow, and Matthew C. Tate from Northwestern University; Nathan Crone and Yujing Wang from Johns Hopkins University; Richard Betzel from Indiana University.
The research was funded by grants R01NS094748, R01NS099210, R21NS084069, RF1NS125026,R01NS115929 from NIH's National Institute of Neurological Disorders and Stroke; Doris Duke Charitable Foundation; Northwestern Memorial Foundation Dixon Translational Research Grant (partially supported by NIH grant UL1RR025741); and Northwestern Medicine Malnati Brain Tumor Institute at Robert H.Lurie Comprehensive Lurie Cancer Center at Northwestern University.