Journal of neuroscience methods
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J. Neurosci. Methods · Aug 2013
Monitoring the depth of anesthesia using entropy features and an artificial neural network.
Monitoring the depth of anesthesia using an electroencephalogram (EEG) is a major ongoing challenge for anesthetists. The EEG is a recording of brain electrical activity, and it contains valuable information related to the different physiological states of the brain. This study proposes a novel automated method consisting of two steps for assessing anesthesia depth. ⋯ The experimental results indicated that an overall accuracy of 88% could be obtained during sevoflurane anesthesia in 17 patients to classify the EEG data into awake, light, general and deep anesthetized states. In addition, this method yielded a classification accuracy of 92.4% to distinguish between awake and general anesthesia in an independent database of propofol and desflurane anesthesia in 129 patients. Considering the high accuracy of this method, a new EEG monitoring system could be developed to assist the anesthesiologist in estimating the depth of anesthesia in a rapid and accurate manner.
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J. Neurosci. Methods · May 2013
Pig lumbar spine anatomy and imaging-guided lateral lumbar puncture: a new large animal model for intrathecal drug delivery.
Intrathecal (IT) administration is an important route of drug delivery, and its modelling in a large animal species is of critical value. Although domestic swine is the preferred species for preclinical pharmacology, no minimally invasive method has been established to deliver agents into the IT space. While a "blind" lumbar puncture (LP) can sample cerebrospinal fluid (CSF), it is unreliable for drug delivery in pigs. ⋯ Effective IT delivery was validated by the injection of contrast media to obtain a CT myelogram. LLP represents a safe and reliable method to deliver agents to the lumbar pig IT space, which can be implemented in a straightforward way by any laboratory with access to CT equipment. Therefore, LLP is an attractive large animal model for preclinical studies of IT therapies.
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J. Neurosci. Methods · May 2013
SACICA: a sparse approximation coefficient-based ICA model for functional magnetic resonance imaging data analysis.
Independent component analysis (ICA) has been widely used in functional magnetic resonance imaging (fMRI) data to evaluate the functional connectivity, which assumes that the sources of functional networks are statistically independent. Recently, many researchers have demonstrated that sparsity is an effective assumption for fMRI signal separation. In this research, we present a sparse approximation coefficient-based ICA (SACICA) model to analyse fMRI data, which is a promising combination model of sparse features and an ICA technique. ⋯ The hybrid data experimental results demonstrated that the SACICA method exhibited the stronger spatial source reconstruction ability with respect to the unsmoothed fMRI data and better detection sensitivity of the functional signal on the smoothed fMRI data than the FastICA method. Furthermore, task-related experiments also revealed that SACICA was not only effective in discovering the functional networks but also exhibited a better detection sensitivity of the visual-related functional signal. In addition, the SACICA combined with Fast-FENICA proposed by Wang et al. (2012) was demonstrated to conduct the group analysis effectively on the resting-state data set.
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J. Neurosci. Methods · Apr 2013
New disposable forehead electrode set with excellent signal quality and imaging compatibility.
The use of emergency electroencephalography (EEG) in clinical practice is limited in part due to the lack of commercially available EEG monitoring sets that are suitable for rapid and simple use. The aim of this study was to develop a rapid and simple-to-use disposable forehead EEG electrode set for routine use that is also suitable for long-term monitoring. The EEG set we developed consists of 12 hydrogel-coated electrodes (10 recording electrodes, plus a reference and ground electrode) attached to a solid polymer film. ⋯ Electric performance testing showed that the impedance spectra of the developed EEG electrodes were comparable to those of three commercially available, disposable electrodes, and the noise level was lower than that of the commercial electrodes. The developed EEG set is also MRI and CT compatible and lacks any signs of imaging artefacts or heat induction. These promising results provide a reason to expect that the developed EEG set may be applicable to situations in which the full, conventional 10-20 electrode setup is not available.
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J. Neurosci. Methods · Mar 2013
Quantifying changes following spinal cord injury with velocity dependent locomotor measures.
Many locomotor measures commonly used to assess functional deficits following neurological injury are velocity dependent. This makes the comparison of faster pre-injury walking to slower post-injury walking a challenging process. In lieu of calculating mean values at specific velocities, we have employed the use of nonlinear regression techniques to quantify locomotor measures across all velocities. ⋯ For example, while the mean stride length of the hindlimbs decreased following injury, regression analysis revealed that the change was due to the reduction in walking speed and not a functional deficit. A significant difference in the percent of the right forelimb step cycle that was spent in stance phase, or duty factor, was found across all velocities, however this deficit spontaneously recovered after 6 weeks. Conversely, no differences were initially found in hindlimb stride length, but abnormal compensatory techniques were found to have developed 3 weeks after injury.