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Record W2051176772 · doi:10.1159/000026662

Acute Nicotine Administration in Alzheimer’s Disease: An Exploratory EEG Study

2000· article· en· W2051176772 on OpenAlexaff
Verner Knott, Christopher G. Engeland, Erich Mohr, Colleen Mahoney, Vadim Ilivitsky

Bibliographic record

VenueNeuropsychobiology · 2000
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicNicotinic Acetylcholine Receptors Study
Canadian institutionsRoyal Ottawa Mental Health CentreWestern UniversityUniversity of Ottawa
Fundersnot available
KeywordsElectroencephalographyNicotinePlaceboPsychologyArousalAudiologyAlpha (finance)AnesthesiaAlpha waveDementiaMedicineInternal medicinePsychiatryNeuroscienceDevelopmental psychologyDiseasePsychometrics

Abstract

fetched live from OpenAlex

Previous findings of cognitive deficits and EEG slowing in Alzheimer's patients, together with independent reports of the performance enhancing and electrocortical activating properties of nicotine in normal adults, stimulated this study to examine the acute effects of nicotine on spectrum-analyzed EEG in patients with dementia of the Alzheimer type (DAT). Thirteen patients, 6 currently receiving cholinesterase inhibitor treatment and the remaining being medication free, were administered 2 mg of nicotine polacrilex under randomized, placebo-controlled conditions. Compared to age-regressed EEG norms, the pretreatment EEG spectrums of patients in general were characterized by excessive slow (delta and theta)-wave power, diminished fast (alpha and beta)-wave power and slow mean alpha and total band frequencies. Although postnicotine EEG indices remained within the abnormal range, nicotine, compared to placebo, significantly shifted EEG towards normal values by reducing slow wave (relative delta and theta) power and augmenting fast (relative alpha-1, alpha-2, beta-1) wave power. No differences were observed between treated and nontreated patients in response to nicotine. The results are discussed in relation to cholinergic and brain arousal systems and their relationship to cognitive processes.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.540
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.019
GPT teacher head0.315
Teacher spread0.296 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations27
Published2000
Admission routes1
Has abstractyes

Explore more

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