The hippocampus region of the brain shows rhythmic neural activities during memory encoding and consolidation, and there is evidence that stimulation of the hippocampus could be a potential treatment for Alzheimer’s disease. However, direct stimulation of the hippocampus can lead to memory disruption. Therefore, modulation of brain regions that input into the hippocampus — such as the medial septum and the entorhinal cortex — could help mitigate such disruptions, but this requires more complex coordination and therefore neural interfaces that can handle multiple feedback loops. Xilin Liu and colleagues have now developed a multi-loop neuromodulation chipset network that supports neuromodulation in multi-loop networks.

Courtesy of ISSCC

The researchers — who are based at the University of Toronto, Ohio State University and the University of Pennsylvania — developed acceleration modules to detect the amplitude and phase of brain rhythms with short latency. Their chipset network consists of three star-connected neural interface nodes surgically implanted near the target brain areas, which are connected to a central node placed under the skin above the skull. The team used the chipsets to study the memory functions of freely behaving monkeys in awake and asleep states. The measured data were transmitted from the chipset network for offline analysis using an ultra-wideband transceiver, with a data rate of 67 Mb s–1 and a bit error rate of 10–5 over a distance of 1.5 m.

Original reference: In Proc. 2024 IEEE Int. Solid-State Circuits Conference (in the press); https://isscc.org