Science Daily: Certain brain wave patterns that occur while an individual sleeps may be assessed by clinicians to help them diagnose dementia and other conditions related to memory, language, and thinking.
A new study published in Sleep that was led by investigators at Massachusetts General Hospital (MGH) and Beth Israel Deaconess Medical Center (BIDMC) could help improve automated methods for detecting these brain wave patterns, or sleep spindles, and for correlating them with cognitive function.
Sleep spindles are bursts of brain activity that occur during non-REM sleep and can be assessed through electroencephalograms (EECs) involving non-invasive electrodes placed on the scalp. Spindles are considered a “fingerprint” that vary among individuals, are highly heritable, and tend to be consistent from night to night.
“With the rising burden of neurodegenerative disease, there is a pressing need for a sensitive biomarker of cognition. This has led to a surge of research examining sleep spindles, an oscillatory pattern of brain activity observed during sleep, and their role in various neuropsychiatric conditions and cognitive performance,” says lead author Noor Adra, a clinical research coordinator at MGH.
Although sleep spindles and other brain features represent promising potential electrophysiologic markers of neurodegenerative and psychiatric diseases, detecting and assessing sleep spindles is not straightforward. “People have already known that these transient high frequency events during sleep in the brain are closely linked to cognition, especially to learning and memory. But when you try to detect spindles among more than 100 sleep recordings, things become less clear — such as what is the best threshold, what is the best minimum duration, etc.,” says co-author Haoqi Sun, PhD, an investigator in the department of Neurology at MGH.
