Understanding the effects of aging and neurodegenerative diseases requires a comprehensive approach that combines behavioral and electrophysiological assessments. In this study, researchers present a protocol for long-term recordings of both muscle activity (EMG) and brain activity (EEG) in mice. By implanting wires in the nuchal muscle and using a skull-surface EEG headcap, the team was able to wirelessly collect data over a period of 9 to 12 months. The beauty of this technique lies in its ability to simultaneously record EEG alongside behavioral tasks, such as locomotion/sleep staging and cognitive testing in the Barnes maze. The collected EEG and EMG data can then be mapped to specific behaviors and neuronal frequencies, providing valuable insights into the relationship between brain function and behavior during the aging process. Through this integrated approach, scientists hope to identify early markers of age-related cognitive decline and gain a deeper understanding of neurodegenerative diseases. This research opens up exciting possibilities for future studies investigating mechanisms underlying brain disorders and developing potential therapeutic interventions.

Electrophysiological and behavioral alterations, including sleep and cognitive impairments, are critical components of age-related decline and neurodegenerative diseases. In preclinical investigation, many refined techniques are employed to probe these phenotypes, but they are often conducted separately. Herein, we provide a protocol for one-time surgical implantation of EMG wires in the nuchal muscle and a skull-surface EEG headcap in mice, capable of 9-to-12-month recording longevity. All data acquisitions are wireless, making them compatible with simultaneous EEG recording coupled to multiple behavioral tasks, as we demonstrate with locomotion/sleep staging during home-cage video assessments, cognitive testing in the Barnes maze, and sleep disruption. Time-course EEG and EMG data can be accurately mapped to the behavioral phenotype and synchronized with neuronal frequencies for movement and the location to target in the Barnes maze. We discuss critical steps for optimizing headcap surgery and alternative approaches, including increasing the number of EEG channels or utilizing depth electrodes with the system. Combining electrophysiological and behavioral measurements in preclinical models of aging and neurodegeneration has great potential for improving mechanistic and therapeutic assessments and determining early markers of brain disorders.

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