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Updated: Jun 3, 2026
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Assessing Primary Motor Cortex Excitability and Excitability Modulation by Pairing Transcranial Magnetic Stimulation with Electromyography
Published on: October 7, 2025
Cortical excitability distinguishes ALS from mimic disorders
Steve Vucic1, Benjamin C Cheah, Con Yiannikas
1Sydney Medical School Westmead, University of Sydney, Australia. s.vucic@neura.edu.au
Summary
Threshold tracking transcranial magnetic stimulation (TTTMS) identifies cortical hyperexcitability, an early indicator distinguishing amyotrophic lateral sclerosis (ALS) from mimic disorders. This technique shows promise for earlier ALS diagnosis and therapy initiation.
Area of Science:
- Neuroscience
- Neurology
- Biomedical Engineering
Background:
- Amyotrophic lateral sclerosis (ALS) diagnosis relies on strict criteria, often leading to delays in treatment.
- Cortical hyperexcitability is an early, detectable feature in ALS patients.
Purpose of the Study:
- To evaluate the diagnostic value of threshold tracking TMS for ALS.
- To develop algorithms to assist in ALS diagnosis using TTTMS.
Main Methods:
- A prospective study involving 156 patients with neuromuscular symptoms (104 ALS, 52 non-ALS) and 62 healthy controls.
- Assessment of cortical excitability using threshold tracking TMS, measuring parameters like short-interval intracortical inhibition (SICI).
Main Results:
- ALS patients exhibited significantly reduced SICI compared to non-ALS patients and controls (P<0.0001).
- Increased motor evoked potential (MEP) amplitude and intracortical facilitation, along with reduced cortical silent period duration, indicated cortical hyperexcitability in ALS.
- Receiver operating characteristic (ROC) curve analysis showed TTTMS, particularly averaged and peak SICI at 3 ms, effectively distinguished ALS from NALS (AUC 0.76 and 0.73, respectively).
Conclusions:
- Cortical hyperexcitability, detected by TTTMS, differentiates ALS from conditions mimicking the disease.
- TTTMS presents a valuable tool for the diagnostic investigation of ALS, potentially improving early detection.
