Tsinghua University

Researchers from Guangxi University, Wuming Hospital of Guangxi Medical University, Tsinghua University and partner institutions developed a skin-mimetic gradient electrode, softer at the scalp and firmer at the circuit connection, with graded pores for sustained electrolyte release. Two male participants completed an 8-hour daily-activity recording session and a 14-hour session, respectively. In the latter, hourly SSVEP input tasks maintained accuracy above 95%, and mVEP tasks above 90%. Each long-duration session involved one participant; the results do not establish population-wide performance or clinical efficacy.

A review traces implantable BCI substrates from rigid materials such as silicon to bendable but inextensible polymers and then intrinsically stretchable elastomers. It focuses on the mechanical mismatch between microelectrodes and soft brain tissue, which can cause persistent injury and foreign body responses that compromise long-term use. The authors highlight electrospun nanofibrous microelectrodes, which combine stretchability with an interconnected, highly permeable three-dimensional network. They argue that this structure helps address the metabolic limitations of dense films. The review also discusses high-density manufacturing, biochemical modulation, and untethered integration rather than presenting human efficacy testing of a new device.

Training accurate BCI models depends on large, diverse EEG datasets, but that data is usually locked inside individual hospitals and labs, stored in inconsistent formats and restricted by privacy rules, which makes it hard to share. TrustBCI brings three functions into one platform: turning raw BCI datasets into assets that can be exchanged, using incentives to keep institutions contributing data, and letting users run computations without access to the raw records. The platform demonstrates two workflows, controllable data synthesis, which generates new datasets, and privacy-preserving query, which returns only query results. That suggests BCI models could be trained jointly across institutions without first pooling the data in one place.