Modulation of neuronal activity in human centromedian nucleus during an auditory attention and working memory task
Bibliographic record
Abstract
Centromedian nucleus (CM) is one of several intralaminar nuclei of the thalamus and is thought to be involved in consciousness, arousal, and attention. CM has been suggested to play a key role in the control of attention, by regulating the flow of information to different brain regions such as the ascending reticular system, basal ganglia, and cortex. While the neurophysiology of attention in visual and auditory systems has been studied in animal models, combined single unit and LFP recordings in human have not, to our knowledge, been reported. Here, we recorded neuronal activity in the CM nucleus in 11 patients prior to insertion of deep brain stimulation electrodes for the treatment of epilepsy while subjects performed an auditory attention task. Patients were requested to attend and count the infrequent (p = 0.2) odd or "deviant" tones, ignore the frequent standard tones and report the total number of deviant tones at trial completion. Spikes were discriminated, and LFPs were band pass filtered (5-45 Hz). Average peri‑stimulus time histograms and spectra were constructed by aligning on tone onsets and statistically compared. The firing rate of CM neurons showed selective, multi-phasic responses to deviant tones in 81% of the tested neurons. Local field potential analysis showed selective beta and low gamma (13-45 Hz) modulations in response to deviant tones, also in a multi-phasic pattern. The current study demonstrates that CM neurons are under top-down control and participate in the selective processing during auditory attention and working memory. These results, taken together, implicate the CM in selective auditory attention and working memory and support a role of beta and low gamma oscillatory activity in cognitive processes. It also has potential implications for DBS therapy for epilepsy and non-motor symptoms of PD, such as apathy and other disorders of attention.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".