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2026-07-18 00:00 China Papers Foundations & Methods Translated from EN

Miniscope Enables Real-Time Neural Decoding

Summary Beijing Normal University researchers developed a low-cost structured-illumination miniscope weighing less than 3 g. The system uses a Ronchi grating and time-multiplexed excitation for HiLo imaging, providing optical sectioning in freely behaving mice. It suppresses out-of-focus background fluorescence while retaining the speed, field of view, and accessibility of widefield miniscopes, and it supports optically sectioned multiplane imaging to increase neuronal yield. In hippocampal recordings, the researchers observed better region-of-interest signal quality and spatial-information readout. They also demonstrated a proof-of-principle closed-loop brain-machine interface supported by rapid online signal extraction and real-time neural decoding. The work is a bioRxiv preprint and has not been peer reviewed.
Why it matters The study integrates affordable optical sectioning, online signal extraction, and closed-loop decoding in a lightweight device, making high-contrast neural feedback experiments more accessible.

BCIwiki (bciwiki.com) — Beijing Normal University posted the study as a preprint on bioRxiv on July 18, 2026. The researchers introduce a low-cost structured-illumination miniscope weighing less than 3 g. It uses a Ronchi grating and time-multiplexed excitation to implement HiLo imaging and achieve optical sectioning in freely behaving mice.

The system strongly suppresses out-of-focus background fluorescence while preserving the speed, field of view, and accessibility of widefield miniscopes. It also supports optically sectioned multiplane imaging to increase neuronal yield. In hippocampal recordings, region-of-interest signal quality and spatial-information readout improved, allowing simple region-averaged signals to approach the performance of offline algorithm-extracted signals. The team also demonstrated a proof-of-principle closed-loop brain-machine interface enabled by rapid online signal extraction and real-time neural decoding. This study is a preprint and has not been peer reviewed.

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biorxiv.org 2026-07-18

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