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1.  Potential for unreliable interpretation of EEG recorded with microelectrodes 
Epilepsia  2013;54(8):1391-1401.
Recent studies in epilepsy, cognition, and brain machine interfaces have shown the utility of recording intracranial EEG (iEEG) with greater spatial resolution. Many of these studies utilize microelectrodes connected to specialized amplifiers that are optimized for such recordings. We recently measured the impedances of several commercial microelectrodes and demonstrated that they will distort iEEG signals if connected to clinical EEG amplifiers commonly used in most centers. In this study we demonstrate the clinical implications of this effect and identify some of the potential difficulties in using microelectrodes.
Human iEEG data were digitally filtered to simulate the signal recorded by a hybrid grid (2 macro- and 8 microelectrodes) connected to a standard EEG amplifier. The filtered EEG data were read by three trained epileptologists, and high frequency oscillations (HFOs) detected with a well-known algorithm. The filtering method was verified experimentally by recording an injected EEG signal in a saline bath with the same physical acquisition system used to generate the model. Several electrodes underwent scanning electron microscopy (SEM).
Macroelectrode recordings were unaltered compared to the source iEEG signal, but microelectrodes attenuated low frequencies. The attenuated signals were difficult to interpret: all three clinicians changed their clinical scoring of slowing and seizures when presented with the same data recorded on different electrodes. The HFO detection algorithm was oversensitive with microelectrodes, classifying many more HFOs than when the same data were recorded with macroelectrodes. In addition, during experimental recordings the microelectrodes produced much greater noise as well as large baseline fluctuations, creating sharply-contoured transients, and superimposed “false” HFOs. SEM of these microelectrodes demonstrated marked variability in exposed electrode surface area, lead fractures, and sharp edges.
Microelectrodes should not be used with low impedance (< 1GΩ) amplifiers due to severe signal attenuation and variability that changes clinical interpretations. The current method of preparing microelectrodes can leave sharp edges and nonuniform amounts of exposed wire. Even when recorded with higher impedance amplifiers, microelectrode data is highly prone to artifacts that are difficult to interpret. Great care must be taken when analyzing iEEG from high impedance microelectrodes.
PMCID: PMC3731390  PMID: 23647099
electrodes; impedance; high frequency oscillations; electrocorticography
2.  Recording From Over 1,000 Cells: A New Toy in Place for Epilepsy Research? 
Epilepsy Currents  2014;14(2):95-96.
PMCID: PMC4010888  PMID: 24872790
3.  Signal distortion from microelectrodes in clinical EEG acquisition systems 
Journal of neural engineering  2012;9(5):056007.
Many centers are now using high-density microelectrodes during traditional intracranial EEG (iEEG) both for research and clinical purposes. These microelectrodes are FDA-approved and integrate into clinical EEG acquisition systems. However, the electrical characteristics of these electrodes are poorly described and clinical systems were not designed to use them; thus it is possible that this shift into clinical practice could have unintended consequences. In this study, we characterized the impedance of over 100 commercial macro- and microelectrodes using electrochemical impedance spectroscopy (EIS) to determine how electrode properties could affect signal acquisition and interpretation. The EIS data were combined with the published specifications of several commercial EEG systems to design digital filters that mimic the behavior of the electrodes and amplifiers. These filters were used to analyze simulated brain signals that contain a mixture of characteristic features commonly observed in iEEG. Each output was then processed with several common quantitative EEG measurements. Our results show that traditional macroelectrodes had low impedances and produced negligible distortion of the original signal. Brain tissue and electrical wiring also had negligible filtering effects. However, microelectrode impedances were much higher and more variable than the macroelectrodes. When connected to clinical amplifiers, higher impedance electrodes produced considerable distortion of the signal at low frequencies (< 60 Hz), which caused significant changes in amplitude, phase, variance, and spectral band power. In contrast, there were only minimal changes to the signal content for frequencies above 100 Hz. In order to minimize distortion with microelectrodes, we determined that an acquisition system should have an input impedance of at least 1 GΩ, which is much higher than most clinical systems. These results show that it is critical to account for variations in impedance when analyzing EEG from different-sized electrodes. Data from microelectrodes may yield misleading results unless recorded with high-impedance amplifiers.
PMCID: PMC3476479  PMID: 22878608
EEG; microelectrodes; electrodes; impedance; electrocorticography
4.  Data mining neocortical high-frequency oscillations in epilepsy and controls 
Brain  2011;134(10):2948-2959.
Transient high-frequency (100–500 Hz) oscillations of the local field potential have been studied extensively in human mesial temporal lobe. Previous studies report that both ripple (100–250 Hz) and fast ripple (250–500 Hz) oscillations are increased in the seizure-onset zone of patients with mesial temporal lobe epilepsy. Comparatively little is known, however, about their spatial distribution with respect to seizure-onset zone in neocortical epilepsy, or their prevalence in normal brain. We present a quantitative analysis of high-frequency oscillations and their rates of occurrence in a group of nine patients with neocortical epilepsy and two control patients with no history of seizures. Oscillations were automatically detected and classified using an unsupervised approach in a data set of unprecedented volume in epilepsy research, over 12 terabytes of continuous long-term micro- and macro-electrode intracranial recordings, without human preprocessing, enabling selection-bias-free estimates of oscillation rates. There are three main results: (i) a cluster of ripple frequency oscillations with median spectral centroid = 137 Hz is increased in the seizure-onset zone more frequently than a cluster of fast ripple frequency oscillations (median spectral centroid = 305 Hz); (ii) we found no difference in the rates of high frequency oscillations in control neocortex and the non-seizure-onset zone neocortex of patients with epilepsy, despite the possibility of different underlying mechanisms of generation; and (iii) while previous studies have demonstrated that oscillations recorded by parenchyma-penetrating micro-electrodes have higher peak 100–500 Hz frequencies than penetrating macro-electrodes, this was not found for the epipial electrodes used here to record from the neocortical surface. We conclude that the relative rate of ripple frequency oscillations is a potential biomarker for epileptic neocortex, but that larger prospective studies correlating high-frequency oscillations rates with seizure-onset zone, resected tissue and surgical outcome are required to determine the true predictive value.
PMCID: PMC3187540  PMID: 21903727
high-frequency oscillations; epilepsy; intracranial EEG
5.  Dyeing to Be Fired: Firing Order Distinguishes Two Types of Bursting Activity 
Epilepsy Currents  2012;12(5):176-177.
PMCID: PMC3482715  PMID: 23118601
6.  Better Resolution and Fewer Wires Discover Epileptic Spiral Waves 
Epilepsy Currents  2012;12(4):147-149.
PMCID: PMC3423214  PMID: 22936887
7.  Technology Insight: neuroengineering and epilepsy—designing devices for seizure control 
Despite substantial innovations in antiepileptic drug therapy over the past 15 years, the proportion of patients with uncontrolled epilepsy has not changed, highlighting the need for new treatments. New implantable antiepileptic devices, which are currently under development and in pivotal clinical trials, hold great promise for improving the quality of life for millions of people with epileptic seizures worldwide. A broad range of strategies is currently being investigated, using various modes of control and intervention in an attempt to stop seizures. The success of these devices rests upon collaboration between neuroengineers, physicians and industry to adapt new technologies for clinical use. The initial results are exciting, but considerable development and controlled clinical trials will be required before these treatments earn a place in our standard of clinical care.
PMCID: PMC2904395  PMID: 18301414
closed-loop devices; epilepsy; neuroengineering; open-loop devices; seizure control
8.  Glycogen synthase kinase 3 has a limited role in cell cycle regulation of cyclin D1 levels 
BMC Cell Biology  2006;7:33.
The expression level of cyclin D1 plays a vital role in the control of proliferation. This protein is reported to be degraded following phosphorylation by glycogen synthase kinase 3 (GSK3) on Thr-286. We recently showed that phosphorylation of Thr-286 is responsible for a decline in cyclin D1 levels during S phase, an event required for efficient DNA synthesis. These studies were undertaken to test the possibility that phosphorylation by GSK3 is responsible for the S phase specific decline in cyclin D1 levels, and that this event is regulated by the phosphatidylinositol 3-kinase (PI3K)/AKT signaling pathway which controls GSK3.
We found, however, that neither PI3K, AKT, GSK3, nor proliferative signaling activity in general is responsible for the S phase decline in cyclin D1 levels. In fact, the activity of these signaling kinases does not vary through the cell cycle of proliferating cells. Moreover, we found that GSK3 activity has little influence over cyclin D1 expression levels during any cell cycle phase. Inhibition of GSK3 activity by siRNA, LiCl, or other chemical inhibitors failed to influence cyclin D1 phosphorylation on Thr-286, even though LiCl efficiently blocked phosphorylation of β-catenin, a known substrate of GSK3. Likewise, the expression of a constitutively active GSK3 mutant protein failed to influence cyclin D1 phosphorylation or total protein expression level.
Because we were unable to identify any proliferative signaling molecule or pathway which is regulated through the cell cycle, or which is able to influence cyclin D1 levels, we conclude that the suppression of cyclin D1 levels during S phase is regulated by cell cycle position rather than signaling activity. We propose that this mechanism guarantees the decline in cyclin D1 levels during each S phase; and that in so doing it reduces the likelihood that simple over expression of cyclin D1 can lead to uncontrolled cell growth.
PMCID: PMC1592484  PMID: 16942622

Results 1-8 (8)