Revolutionizing Motor Hotspot Detection: The Power of Semi-Automated Search (SAMHS)

Discover the cutting-edge of neurosurgical precision with Semi-automated Motor Hotspot Search (SAMHS)—a groundbreaking framework designed to revolutionize the identification of motor hotspots in the brain.
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Note that James is a diligent GPT-based bot and can make mistakes. Consider checking important information (e.g. using the DOI) before completely relying on it.

Semi-automated motor hotspot search (SAMHS): a framework toward an optimised approach for motor hotspot identification.

Agboada et al., Front Hum Neurosci 2023
DOI: 10.3389/fnhum.2023.1228859

What’s New: The study introduces a semi-automated motor hotspot search (SAMHS) technique using a neuronavigated robot-assisted TMS system (TMS-cobot) and compares it with the traditional manual motor hotspot search (MHS).

Importance: The SAMHS technique aims to optimize and streamline the process of motor hotspot identification, which is crucial for setting stimulation intensity in TMS applications.

Contribution to Literature: The study contributes by providing a new method that enhances accuracy in motor hotspot identification and can be used by both experienced and novice TMS researchers.

Results Summary: Involving 32 participants, the study found that the cobot hotspot search (CHS) yielded lower resting motor thresholds (RMT) and stimulus intensity to produce 1 mV (SI1mV) compared to MHS. Additionally, there was a trend towards higher peak-to-peak MEP amplitude with SI1mV using CHS. The CHS took longer (15.60 minutes) than MHS (2.43 minutes on average), but it was more accurate in identifying the motor hotspot.

Conclusion: The SAMHS procedure offers an improved method for motor hotspot determination, balancing accuracy with time efficiency, and is suitable for TMS researchers at all levels of experience.

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