Quantifying the effects of the electrode-brain interface on the crossing electric currents in deep brain recording and stimulation

N Yousif, R Bayford, S Wang, X Liu

Research output: Contribution to journalArticlepeer-review

27 Citations (Scopus)


A depth electrode-brain interface (EBI) is formed once electrodes are implanted into the human brain. We investigated the impact of the EBI on the crossing electric currents during both deep brain recording (DBR) and deep brain stimulation (DBS) over the acute, chronic and transitional stages post-implantation, in order to investigate and quantify the effect which changes at the EBI have on both DBR and DBS. We combined two complementary methods: (1) physiological recording of local field potentials via the implanted electrode in patients; and (2) computational simulations of an EBI model. Our depth recordings revealed that the physiological modulation of the EBI in the acute stage via brain pulsation selectively affected the crossing neural signals in a frequency-dependent manner, as the amplitude of the electrode potential was inversely correlated with that of the tremor-related oscillation, but not the beta oscillation. Computational simulations of DBS during the transitional period showed that the shielding effect of partial giant cell growth on the injected current could shape the field in an unpredictable manner. These results quantitatively demonstrated that physiological modulation of the EBI significantly affected the crossing currents in both DBR and DBS. Studying the microenvironment of the EBI may be a key step in investigating the mechanisms of DBR and DBS, as well as brain-computer interactions in general.

Original languageEnglish
Pages (from-to)683-91
Number of pages9
Issue number3
Publication statusPublished - 27 Mar 2008


  • Action Potentials
  • Biological Clocks
  • Brain
  • Computer Simulation
  • Deep Brain Stimulation
  • Electrodes, Implanted
  • Electrodiagnosis
  • Electrophysiology
  • Evoked Potentials
  • Finite Element Analysis
  • Humans
  • Microelectrodes
  • Models, Neurological
  • Neurons
  • Neurophysiology
  • Signal Processing, Computer-Assisted


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