OtherJournal of neuroengineering and rehabilitation2019

Control of cortical oscillatory frequency by a closed-loop system.

Mattia D'Andola, Massimiliano Giulioni, Vittorio Dante and 2 others

PMID 30626450

WHAT IT FOUND

In isolated brain tissue, a new device automatically adjusted electrical current to steer slow brain waves to specific frequencies.

It successfully held the target frequency in most cases, though it struggled to reach the very slowest target within the allowed time.

Key findings

01The closed-loop system successfully steered the slow oscillation frequency to the desired target in all five tested cortical slices.

02The system maintained frequencies close to the 0.5 Hz and 0.8 Hz targets, with average deviations of 0.07 Hz and 0.05 Hz respectively.

03The system struggled to reach the 0.1 Hz target within the 120-second limit, often stabilizing at a higher frequency or requiring more time.

STILL TO COME

How it was doneWhat they found

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What it does not show

This is an in vitro study using isolated brain slices from ferrets, not a human or animal in vivo study. The sample size was very small, with only five slices tested in the final protocol. The system could not always reach the lowest target frequency (0.1 Hz) within the time constraints imposed to protect the tissue. The study demonstrates technical control of oscillations but does not test any therapeutic outcome or clinical benefit.

Declared interests

The authors declare no competing interests. The study was supported by non-US government funding.

The easy way to misread this

Do not interpret this as evidence that this device can treat human conditions like sleep disorders or cognitive decline. It is a proof-of-concept engineering study performed on isolated brain tissue in a lab, with no human participants or clinical outcomes measured.

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The study

Participants
5 cortical slices
Certainty of evidence
Low

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    Mattia D'Andola, Massimiliano Giulioni, Vittorio Dante, et al. Control of cortical oscillatory frequency by a closed-loop system. Journal of neuroengineering and rehabilitation. 2019.

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