MétaCan
Menu
Back to cohort

Exposure to electromagnetic fields by using cellular telephones and its influence on the brain

2000· article· en· W2090323545 on OpenAlexaff
Michael Petrides

Bibliographic record

VenueNeuroreport · 2000
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicElectromagnetic Fields and Biological Effects
Canadian institutionsMontreal Neurological Institute and HospitalMcGill University
Fundersnot available
KeywordsElectroencephalographyElectromagnetic fieldVigilance (psychology)Brain activity and meditationAudiologyCognitionBrain functionExtremely low frequencyNeuroscienceMagnetoencephalographyPhysicsPsychologyMedicine

Abstract

fetched live from OpenAlex

The widespread use of cellular telephones in recent years inevitably raises the question of the effects on brain function of the electromagnetic fields emitted by such telephones. A number of reports have now appeared indicating that the high-frequency electromagnetic fields emitted by cellular telephones do influence cognitive function and brain electrical activity. Two studies published this year in NeuroReport by Koivisto and colleagues showed that exposure to a 902 MHz electromagnetic field, typical of mobile telephones, decreased response times in simple reaction time and vigilance tasks and the time needed to perform a mental arithmetic task [1], as well as the response times on a working memory task [2]. Furthermore, the same group of investigators examined the effects of electromagnetic field exposure on electrical oscillatory activity in the human brain during an auditory memory task [3]. This study, which focused on event-related desynchronization and synchronization of the 4–6 Hz, 6–8 Hz, 8–10 Hz and 10–12 Hz narrow EEG frequency bands, found that exposure to the electromagnetic field increased EEG power in the 8–10 Hz frequency. Other studies have also demonstrated effects on eventrelated brain activity [4,5] and cognitive function [6] as a result of the exposure of the brain to the electromagnetic field emitted by cellular telephones. In the present issue of NeuroReport, Huber et al. [7] report a study on the effects of exposure for 30 min to the electromagnetic field emitted by digital radiotelephone handsets on the EEG recorded during subsequent sleep. The electromagnetic field was directed either to the left or right hemisphere in order to simulate real life exposure conditions. Exposure to the electromagnetic field did not affect sleep stages or sleep latency, but it did enhance EEG power density in the 9.75–13.25 Hz range during the initial part of sleep. Interestingly, despite the fact that the exposure was unilateral there was no hemispheric asymmetry on the changes in EEG power. These results show that even a short exposure to the electromagnetic fields emitted by cellular telephones can affect brain physiology. The currently available literature suggests that some aspects of cognitive function and some direct measures of brain physiology may be affected by exposure to electromagnetic fields of the type emitted by cellular telephones. It has been suggested that the facilitatory effects on cognitive function may be the result of a slight increase in the temperature of the underlying brain tissue which might affect synaptic transmission [6], but the mechanisms remain unknown. It is too early to state whether there might be any long-term effects on human brain function. It is important to note that, in the study published in the current issue of NeuroReport, the changes in EEG power observed during the first 30 min of nonREM sleep were not observed at the end of the 3 h sleep episode. Similarly, the results of the studies that examined cognitive function do not allow conclusions about any long-term effects of cellular telephone use. Thus, it remains to be established whether repeated exposure to electromagnetic fields could have long-lasting effects on brain physiology and cognitive function.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.411

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 head0.006
GPT teacher head0.217
Teacher spread0.211 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations6
Published2000
Admission routes1
Has abstractyes

Explore more

Same venueNeuroreportSame topicElectromagnetic Fields and Biological EffectsFrench-language works237,207