Method for detection of changes in the EEG induced by the presence of sensory stimuli

Carrubba, Simona; Frilot, Clifton; Chesson, Andrew L.; Marino, Andrew A.

doi:10.1016/j.jneumeth.2008.05.008

Cited by 13 publications

(11 citation statements)

References 12 publications

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“…We showed that magnetic fields comparable in frequency and strength to those produced by the battery current in GSM mobile phones consistently caused changes in brain electrical activity in human subjects, and that the changes could be detected only when the EEGs were analyzed using nonlinear methods (Carrubba and Marino, 2008;Carrubba et al, 2006Carrubba et al, , 2007aCarrubba et al, , 2007bCarrubba et al, , 2008aCarrubba et al, , 2008bMarino et al, 2004). Whether brain electrical activity is also affected by radio-frequency GSM EMFs is an empirical question.…”

Section: Analysis Of Reportsmentioning

confidence: 96%

The Effects of Mobile-Phone Electromagnetic Fields on Brain Electrical Activity: A Critical Analysis of the Literature

Marino¹,

Carrubba²

2009

LEBM

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We analyzed the reports in which human brain electrical activity was compared between the presence and absence of radio-frequency and low-frequency electromagnetic fields (EMFs) from mobile phones, or between pre- and post-exposure to the EMFs. Of 55 reports, 37 claimed and 18 denied an EMF-induced effect on either the baseline electro encephalogram (EEG), or on cognitive processing of visual or auditory stimuli as reflected in changes in event-related potentials. The positive reports did not adequately consider the family-wise error rate, the presence of spike artifacts in the EEG, or the confounding role of the two different EMFs. The negative reports contained neither positive controls nor power analyses. Almost all reports were based on the incorrect assumption that the brain was in equilibrium with its surroundings. Overall, the doubt regarding the existence of reproducible mobile-phone EMFs on brain activity created by the reports appeared to legitimate the knowledge claims of the mobile-phone industry. However, it funded, partly or wholly, at least 87% of the reports. From an analysis of their cognitive framework, the common use of disclaimers, the absence of information concerning conflicts of interest, and the industry's donations to the principal EMF journal, we inferred that the doubt was manufactured by the industry. The crucial scientific question of the pathophysiology of mobile-phone EMFs as reflected in measurements of brain electrical activity remains unanswered, and essentially unaddressed.

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Section: Analysis Of Reportsmentioning

confidence: 96%

The Effects of Mobile-Phone Electromagnetic Fields on Brain Electrical Activity: A Critical Analysis of the Literature

Marino¹,

Carrubba²

2009

LEBM

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“…The signal-processing techniques were developed to study nonlinear physical systems and subsequently extended to physiological signals [16,17], including the vigilant and sleep EEGs [9,[18][19][20]. Briefly, at time t a 5-component vector was formed that consisted of the EEG amplitude at t and four earlier times identified by four successive lags of five points (10 msec).…”

Section: Recurrence Analysismentioning

confidence: 99%

“…The Euclidean norm was used for measuring distance, and vectors were identified as near if they were within 15% of the distance between the two vectors that were furthest apart. These choices (and those for dimension and lag) were previously found to be useful for quantifying deterministic activity in the EEG [9,18,19].…”

Section: Recurrence Analysismentioning

confidence: 99%

EEG recurrence markers and sleep quality

Wang

Kim

McCarty

et al. 2013

Journal of the Neurological Sciences

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“…We recently described a nonlinear method for detecting a stimulus-induced presence effect in the EEG (10). Briefly, V(t) was embedded in a five-dimensional phase space using a time delay of 5 points (17 ms) (19).…”

Section: Nonlinear Analysismentioning

confidence: 99%

“…We recently described a method for determining whether a sensory stimulus produced a presence effect, as evidenced by steady-state changes in brain electrical activity (10). Using this method, we tested the hypothesis that a magnetic field comparable to a field generated during an MR scan produced changes in human brain electrical activity that persisted until the field was removed.…”

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confidence: 99%

Simulated MR magnetic field induces steady‐state changes in brain dynamics: Implications for interpretation of functional MR studies

Marino

Carrubba

Frilot

et al. 2010

Magnetic Resonance in Med

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We examined whether a magnetic field comparable to one of the fields produced during MRI induced steady-state changes in brain electrical activity while the field was applied (called a presence effect to distinguish it from evoked potentials). The electroencephalogram was measured from standard scalp locations in the presence and absence of 100-200 mT, 60 Hz, and the effect of the field was evaluated by nonlinear (recurrence analysis) and linear techniques; individual subjects served as their own controls. Using recurrence analysis, changes in brain activity lasting 1 sec (the longest interval considered) were found in 21 of 22 subjects (P < 0.05 for each subject). The presence effect was not detected using linear analysis and was reversible, as indicated by a return of brain activity to baseline levels in all subjects within 2 sec of field offset. The possible role of artifacts or systematic errors was ruled out by studies using electrical phantoms and by analyses of electroencephalograms recorded during sham exposure. It is reasonable to expect that actual scanner magnetic fields also produce nonlinear steady-state perturbations of brain dynamical activity. The effect may influence the picture of brain connectivity inferred in some functional MR studies. Magn Reson Med 64:349-357, 2010. V C 2010 Wiley-Liss, Inc.Key words: nonlinear analysis; brain electrical activity; limitation on fMRI; electric fields; magnetic fields Cognitive activity is mediated by temporal-spatial interactions involving specialized regions of the brain (1). The interactions are commonly studied using functional MRI (fMRI) employing blood-oxygen-level-dependent (BOLD) contrast imaging (2).Averaged images obtained when subjects were and were not performing particular tasks are typically used to identify brain regions that mediated task-related cognitive processing (3,4). This strategy is based on some problematical assumptions and has neuropsychological drawbacks (5), but it affords good statistical power for detecting BOLD signals (6).In MRI, static (0 Hz) magnetic fields of 1-9 T align nuclear spins, high-frequency magnetic fields (10-400 MHz) of about 0.2 mT induce transitions between spin states, and low-frequency magnetic fields (100-1000 Hz) of about 50 mT produce imaging gradients (7); in fMRI, gradient parameters produce additional magnetic fields. Physical law and physiologic conditions in the brain (blood flow, tissue motion, cell movement, motion of the head) result in the simultaneous presence of electric fields (8).Human subjects can detect magnetic fields, as evidenced by their ability to trigger onset and offset evoked potentials (9). We were interested in whether, in addition to these transient changes in brain electrical activity, magnetic fields relevant to those used in MRI also produced continuous changes during the time the field was applied (''presence effect''). Depending on the dynamical nature of the effect (see below), such a finding would enhance the possibility that BOLD data obtained during functional imaging c...

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Method for detection of changes in the EEG induced by the presence of sensory stimuli

Cited by 13 publications

References 12 publications

The Effects of Mobile-Phone Electromagnetic Fields on Brain Electrical Activity: A Critical Analysis of the Literature

The Effects of Mobile-Phone Electromagnetic Fields on Brain Electrical Activity: A Critical Analysis of the Literature

EEG recurrence markers and sleep quality

Simulated MR magnetic field induces steady‐state changes in brain dynamics: Implications for interpretation of functional MR studies

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