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The Texting Rhythm: A Novel EEG Waveform Using Smartphones.
William O Tatum1, Benedetto DiCiaccio, Joseph A Kipta
1*Department of Neurology, Mayo Clinic College of Medicine, Mayo Clinic in Florida, Jacksonville, Florida, U.S.A.; †University of Florida, Gainesville, Florida, U.S.A.; and ‡Department of Neurological Sciences, Rush University Medical Center, Chicago, Illinois, U.S.A.
Summary
A unique EEG pattern, the texting rhythm (TR), was identified in patients using smartphones. This stimulus-evoked waveform is specific to texting and may be more common in epilepsy patients.
Area of Science:
- Neuroscience
- Clinical Electrophysiology
Background:
- A novel electroencephalogram (EEG) phenomenon was observed in patients with paroxysmal neurological events during video EEG monitoring.
- This unique EEG pattern is associated with the use of personal electronic devices.
Purpose of the Study:
- To identify and characterize a novel EEG waveform, termed the texting rhythm (TR).
- To determine the specificity and prevalence of the TR in patients undergoing epilepsy monitoring.
- To investigate potential associations between the TR and epilepsy characteristics.
Main Methods:
- Analysis of interictal scalp EEG data from two epilepsy centers (Florida and Illinois).
- Definition of the texting rhythm (TR) as a reproducible, stimulus-evoked, generalized frontocentral 5-6 Hz theta burst induced by active text messaging.
- Comparison of prospective and retrospective cohorts, assessing patient demographics, epilepsy classification, MRI, and EEG findings.
Main Results:
- The TR was identified in 31 out of 129 (24.0%) evaluable patients across both centers.
- The waveform was highly specific to active text messaging, absent during other cognitive or motor tasks.
- A higher prevalence of TR was noted in patients with epilepsy (P=0.03) and generalized seizures (P=0.025).
Conclusions:
- The texting rhythm (TR) is a novel, task-specific EEG waveform time-locked to smartphone text messaging.
- Electroencephalographers should recognize the TR to differentiate it from abnormal EEG activity.
- Further research is needed to understand the implications of this technology-related cognitive-motor network.
