1. Academic Validation
  2. Sensitivity of coherent oscillations in rat hippocampus to AC electric fields

Sensitivity of coherent oscillations in rat hippocampus to AC electric fields

  • J Physiol. 2007 Sep 1;583(Pt 2):555-65. doi: 10.1113/jphysiol.2007.137711.
Jacqueline K Deans 1 Andrew D Powell John G R Jefferys
Affiliations

Affiliation

  • 1 Department of Neurophysiology, Division of Neuroscience, Medical School, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK.
Abstract

The sensitivity of brain tissue to weak extracellular electric fields is important in assessing potential public health risks of extremely low frequency (ELF) fields, and potential roles of endogenous fields in brain function. Here we determine the effect of applied electric fields on membrane potentials and coherent network oscillations. Applied DC electric fields change transmembrane potentials in CA3 pyramidal cell somata by 0.18 mV per V m(-1) applied. AC sinusoidal electric fields have smaller effects on transmembrane potentials: sensitivity drops as an exponential decay function of frequency. At 50 and 60 Hz it is approximately 0.4 that for DC fields. Effects of fields of < or = 16 V m(-1) peak-to-peak (p-p) did not outlast application. Kainic acid (100 nm) induced coherent network oscillations in the beta and gamma bands (15-100 Hz). Applied fields of > or = 6 V m(-1) p-p (2.1 V m(-1) r.m.s.) shifted the gamma peak in the power spectrum to centre on the applied field frequency or a subharmonic. Statistically significant effects on the timing of pyramidal cell firing within the oscillation appeared at distinct thresholds: at 50 Hz, 1 V m(-1) p-p (354 mV m(-1) r.m.s.) had statistically significant effects in 71% of slices, and 0.5 V m(-1) p-p (177 mV m(-1) r.m.s.) in 20%. These threshold fields are consistent with current environmental guidelines. They correspond to changes in somatic potential of approximately 70 microV, below membrane potential noise levels for neurons, demonstrating the emergent properties of neuronal networks can be more sensitive than measurable effects in single neurons.

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