When conducting brain surgery on patients with brain tumors or epilepsy, surgeons must remove the abnormal tissue or tumor while ensuring that important areas responsible for language and movement remain intact. A recent study offers insights that could assist doctors in deciding which brain regions to safeguard, ultimately enhancing language functions in patients following surgery. This research broadens our comprehension of how language is processed in the brain and pinpoints essential features of specific areas in the cerebral cortex involved in language production.
When conducting brain surgery on patients with brain tumors or epilepsy, surgeons must carefully remove the abnormal tissue or tumor while protecting vital areas of the brain responsible for language and movement.
A new study from Northwestern Medicine may enhance medical professionals’ choices about which brain regions to spare, leading to better language outcomes for patients post-surgery. The findings deepen our knowledge of the brain’s language processing and highlight crucial elements of specific cerebral cortex regions that collaborate to facilitate language.
Think of the brain’s language network as a social network; scientists have discovered a key “connector” similar to a person who links numerous sub-networks. This connector allows various subnetworks to interact, and eliminating such sites could lead to increased language errors after surgery, like struggles with naming objects, as the subnetworks would fail to coordinate.
The study is set to appear in Nature Communications on September 16.
Investigating brain signals in patients with brain tumors and epilepsy
Researchers at Northwestern identified these critical language connector areas by monitoring electrical signals from patients’ brain cortices as they read words aloud. They then analyzed the data using graph theory and machine learning to determine which network sites were essential.
“This discovery could lead to more precise and efficient methods for mapping language areas before surgery,” stated Dr. Marc Slutzky, the study’s main author and a professor of neurology at Northwestern University Feinberg School of Medicine. “It could augment the ways surgeons perform this mapping, potentially reducing the time needed for stimulation or even eliminating it altogether in favor of just recording electrical signals.”
Patients undergoing surgery due to brain tumors or epilepsy typically experience functional mapping, which involves directly stimulating the brain electrically to identify critical regions (especially in the cerebral cortex). This helps neurosurgeons avoid removing vital areas related to language. For instance, if stimulation temporarily disrupts a patient’s speech or their ability to name objects, it indicates that the stimulated area is important for these functions.
Limitations of current stimulation techniques
“This method has remained largely unchanged for over 50 years, and we still don’t fully understand what happens during the stimulation,” Slutzky mentioned. “It’s unclear why only certain sites identified through stimulation are considered critical for language and speech.”
“While speaking, multiple brain areas show activity, yet only a few are recognized as essential based on how they respond during stimulation. Addressing this question could illuminate how electrical stimulation impacts the brain and aids in speech production.”
Approximately 1.2 million people in the U.S. are living with brain tumors
Currently, many patients with brain tumors endure 20 to 60 minutes of electrical stimulation while awake during surgery. However, this technique is not foolproof for pinpointing language areas; it can yield false positives or negatives and even lead to seizures.
“It’s not an enjoyable experience for the patient,” Slutzky explained. “Mapping for epilepsy patients can take one or two days and is taxing for them.”
Patients with epilepsy may require surgery when their seizures aren’t well managed by medication, added Slutzky.
Study methodology
Researchers recorded electrical signals from the cortex surface of 16 patients (from Northwestern Memorial Hospital and Johns Hopkins Hospital) diagnosed with brain tumors or epilepsy. The electrode arrays were either previously implanted in epilepsy patients for monitoring or placed temporarily during awake brain surgery for tumor patients undergoing mapping.
The patients read words displayed on a monitor as their brain signals were captured (a technique known as electrocorticography). The scientists analyzed these signals through graph theory metrics that describe network connectivity—how sites interacted functionally, either locally, globally, or across sub-networks. They employed machine learning to identify key sites in the network using these metrics, focusing on those connecting across different communities.
Additional authors from Northwestern include Jason K. Hsieh, Prashanth R. Prakash, Robert D. Flint, Zachary Fitzgerald, Emily Mugler, Jessica W. Templer, Joshua M. Rosenow, and Matthew C. Tate.
This Northwestern study involved collaboration with Nathan Crone and Yujing Wang from Johns Hopkins University’s neurology department and Richard Betzel from Indiana University’s psychological and brain sciences department.
