Hongyan Cui

Time-frequency patterns of somatosensory evoked potentials in predicting the location of spinal cord injury

Somatosensory evoked potentials (SEPs) were found to exhibit different time-frequency patterns after acute spinal cord injury (SCI) at different levels, which implies that changes of these patterns may be associated with the location of SCI. Based on this finding, we propose the hypothesis that there are information regarding the location of SCI contained in the time-frequency patterns of SEPs. Purpose of the present study is to verify this hypothesis by comparing the time-frequency patterns of SEPs after acute and chronic SCI at the same level. The study examined the distribution patterns of the time-frequency components (TFCs) of SEPs before and after acute and chronic injury at C5 level in the spinal cord. Experimental results of SEP recordings from 24 adult rats show that there are common areas in the time-frequency distributions of SEPs. The TFCs from both the acute injury group and the chronic injury group are located in these areas with no TFCs from the normal group. Findings suggest that these areas are likely to possess information concerning the site of neurological deficits in spinal cord while independent of the modality of injury. This study provides basis for identification of stable time-frequency patterns of SEPs after different types and locations of SCI, which will guide the development of SEP-based SCI location detection.

Spatio-temporal measures of electrophysiological correlates for behavioral multisensory enhancement during visual, auditory and somatosensory stimulation: A behavioral and ERP study

Multisensory enhancement, as a facilitation phenomenon, is responsible for superior behavioral performance when an individual is responding to cross-modal versus modality-specific stimuli. However, the event-related potential (ERP) counterparts of behavioral multisensory enhancement are not well known. We recorded ERPs and behavioral data from 14 healthy volunteers with three types of target stimuli (modality-specific, bimodal, and trimodal) to examine the spatio-temporal electrophysiological characteristics of multisensory enhancement by comparing behavioral data with ERPs. We found a strong correlation between P3 latency and behavioral performance in terms of reaction time (RT) (R = 0.98, P <0.001), suggesting that P3 latency constitutes a temporal measure of behavioral multisensory enhancement. In addition, a fast RT and short P3 latency were found when comparing the modality-specific visual target with the modality-specific auditory and somatosensory targets. Our results indicate that behavioral multisensory enhancement can be identified by the latency and source distribution of the P3 component. These findings may advance our understanding of the neuronal mechanisms of multisensory enhancement.

Automatic lumbar motion analysis based on particle filtering

Spinal motion is produced by complex coordination of nerves and muscles and is constrained by vertebral structure. The observation and measurement of lumbar motion is of great value for clinical diagnosis and surgical plan of lumbar disorders. Digitalized Video Fluoroscopy (DVF) is the most suitable one to image the spine motion but it is quite time consuming. This paper proposes an automatic lumbar motion analysis system (ALMAS) with particle filtering technology. The automatically vertebral tracking for motion analysis was utilized with a friendly-interface, which provides a window for users to process the acquired DVF sequence and to analyze the tracking results. A set of simulation vertebra image were used to evaluate the performance and accuracy of this system. In simulated sequence, the maximal difference is 1.3 mm in translation and 1° in rotation angle. The error is small in x- and y-translation (fiducial error: 2.4%, repeatability error: 0.5%) and in rotation angle (fiducial error: 1.0%, repeatability error: 0.7%). The ALMAS can still track the sequence contaminated by noise with the density ≤ 0.5. Besides, the results demonstrate that the data from the auto-tracking algorithm shows a strong correlation with the actual measurement and that the ALMAS is highly repetitive. Results from this study showed that ALMAS based on particle filtering are relatively robust and accurate for automatic lumbar motion analysis.

Surface somatosensory evoked potential detection by FPGA based multi-adaptive filter

Surface somatosensory evoked potentials (SSEP) collected from conscious subjects usually presents poor signal-to-noise ratio (SNR), requiring several hundreds ensembles averaging to provide a meaningful waveform. A FPGA based adaptive filtering is proposed to perform fast and accurate SSEP extraction by fixed-point adaptive noise canceller (ANC). In 6 normal subjects and 1 neurological abnormal patient, the latency and the peak-to-peak amplitude in SSEP by FPGA based ANC technique were compared with that measured by ensemble averaging. Using 100 trials ANC processed SSEP was sufficient to extract a waveform in equivalent to that extracted by 1000 trials ensemble averaging. The use of fixed-point ANC based on FPGA proved to shorten SSEP measurement time and provide varying information underlying SSEP.

A dynamic prediction model for intraoperative somatosensory evoked potential monitoring

This study proposed a support vector regression model applied in prediction of intraoperative somatosensory evoked potential changes associated with physiological and anesthetic changes. This model was developed from probability distribution and support vector machines. The predicted results showed that observed and predicted SEP has similar variation trend with different values, with acceptable errors. With this prediction model, changes of SEP in correlation with non-surgical factors were estimated. Not only the prediction accuracy of SEP has been improved, but also provides the reliability of the classification. It will be helpful to develop an intelligent monitor model based expert system that can make a reliable decision for the potential spinal injury.

Trial-to-trial latency variability of somatosensory evoked potential in early stage of cervical myelopathy

Somatosensory evoked potentials (SEP) have been widely used in monitoring spinal cord function during surgery. However, its clinical diagnostic value was limited because of big test-retest variability in SEP measurement. This study applied constrained second order based blind source separation (CSOB-BSS) algorithm to extract single trial SEP. This novel method provides a new measurement of trial-to trial latency variability (TTLV) of SEP. Ten healthy subjects and ten patients with cervical myelopathy (CM) at early stage were recruited in this study. Latency in averaging SEP did not show significant difference between healthy and CM. However, median SEP showed significant lower TTLV (4.9±1.6%) in healthy subjects in comparison with TTLV (10.8±1.0%) in CM (p<;0.05). To investigate the meaningful interpretation of TTLV, clinical measures of disease severity including modified Japanese Orthopaedic Association (mJOA) and transverse area ratio between spinal cord to canal in MRI were performed in CM patients. There is no correlation among TTLV, mJOA and MRI measurement. Results suggested the diagnostic value of TTLV to discriminate CM from healthy subjects in early stage, as well, TTLV provides different features in CM other than functional evaluation in mJOA and anatomic features in MRI.

Wide field epiretinal micro-electrode-design and feature test

This study was aimed to design and fabricate a wide field implantable epi-retinal microelectrode array for the purpose of retinal repair, and to perform electrochemical test on the array. With parylene as flexible substrate material and Pt as electrode and route material, microelectrode array prototypes was designed and fabricated, and electric characteristics of the array was tested with the three-electrode test system. The feature analysis showed that morphological and electrical properties of the array well met the requirements of implantation and electrical stimulation of retina. The microelectrode array can be put in the in vivo electrophysiological experiments on animal and can perform reliably.

Source analysis of bimodal event-related potentials with auditory-visual stimuli

Dipole source analysis is applied to model brain generators of surface-recorded evoked potentials, epileptiform activity, and event-related potentials (ERP). The aim of this study was to explore brain activity of interaction between bimodal sensory cognition. Seven healthy volunteers were recruited in the study and ERP to these stimuli were recorded by 64 electrodes EEG recording system. Subjects were exposed to either the auditory and the visual stimulus alone or the combined auditory-visual (AV) stimuli. The identification of brain areas of the EP was realized using CURRY 6.0 software. A source localization analysis was performed across conditions over initial, early and later temporal stages (i.e. 3 stimuli conditions × 3 temporal stages). The source locations across conditions were contrasted over similar time periods, indicating that source location of the bimodal auditory-visual (AV) stimuli differed from the sum of source locations from the auditory and the visual stimulus alone. These data provide evidence that there exists interplay in the brain in the bimodal auditory-visual stimuli paradigm.