Exposure to electromagnetic fields by using cellular telephones and its influence on the brain
Notice bibliographique
Résumé
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.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».