Expanding the spectrum of the “texting rhythm” in <scp>EEG</scp>
Bibliographic record
Abstract
A 49-year-old male was evaluated with video-electroencephalography for possible epilepsy due to recurrent anxiety with confusion. EEG showed 5–6 Hertz monomorphic, generalized, frontocentral activity during tasks like reading, texting, computer work, and LEGO play (Figure 1). This ceased when relaxed or asleep (Figure 2). Two non-epileptic events were captured, and MRI was normal. Frontal-midline theta rhythms relate to tasks requiring cognitive control.1, 2 Texting rhythm (TR) is a novel pattern defined as reproducible, stimulus-evoked, generalized frontocentral monomorphic 5–6 Hertz activity.3-6 EEG/MEG studies suggest frontal-midline theta originates in the dorsal anterior cingulate and medial prefrontal cortex.1, 2 TR may involve broader networks, including brainstem–thalamic, occipital–parietal, and prefrontal neocortical networks.3, 7 TR-like patterns, seen in knitting, may arise from the same regions and the supplementary motor cortex for motor planning and visuospatial processing,5 possibly also explaining LEGO-related rhythms. TR, a normal finding seen in 24% of adults, should not be misinterpreted as pathologic.3 The authors report no disclosures relevant to the manuscript. Written informed consent was obtained from the patient for publication. The data that support the findings of this study are available from the corresponding author upon reasonable request. Data S1. Data S2. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article. Texting rhythm has been reported in approximately what percentage of adults? Which of the following statements is part of the definition of texting rhythm? Fronto-central theta rhythms have been described during: Answers may be found in the supporting information.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".