Classification of cognitive ability of healthy older individuals using resting-state functional connectivity magnetic resonance imaging and an extreme learning machine.

BACKGROUND: Quantitative determination of the correlation between cognitive ability and functional biomarkers in the older brain is essential. To identify biomarkers associated with cognitive performance in the older, this study combined an index model specific for resting-state functional connectivity (FC) with a supervised machine learning method. METHODS: Performance scores on conventional cognitive test scores and resting-state functional MRI data were obtained for 98 healthy older individuals and 90 healthy youth from two public databases. Based on the test scores, the older cohort was categorized into two groups: excellent and poor. A resting-state FC scores model (rs-FCSM) was constructed for each older individual to determine the relative differences in FC among brain regions compared with that in the youth cohort. Brain areas sensitive to test scores could then be identified using this model. To suggest the effectiveness of constructed model, the scores of these brain areas were used as feature matrix inputs for training an extreme learning machine. classification accuracy (CA) was then tested in separate groups and validated by N-fold cross-validation. RESULTS: This learning study could effectively classify the cognitive status of healthy older individuals according to the model scores of frontal lobe, temporal lobe, and parietal lobe with a mean accuracy of 86.67%, which is higher than that achieved using conventional correlation analysis. CONCLUSION: This classification study of the rs-FCSM may facilitate early detection of age-related cognitive decline as well as help reveal the underlying pathological mechanisms.

Adaptive Segmentation Algorithm for Subtle Defect Images on the Surface of Magnetic Ring Using 2D-Gabor Filter Bank.

In order to realize the unsupervised segmentation of subtle defect images on the surface of small magnetic rings and improve the segmentation accuracy and computational efficiency, here, an adaptive threshold segmentation method is proposed based on the improved multi-scale and multi-directional 2D-Gabor filter bank. Firstly, the improved multi-scale and multi-directional 2D-Gabor filter bank was used to filter and reduce the noise on the defect image, suppress the noise pollution inside the target area and the background area, and enhance the difference between the magnetic ring defect and the background. Secondly, this study analyzed the grayscale statistical characteristics of the processed image; the segmentation threshold was constructed according to the gray statistical law of the image; and the adaptive segmentation of subtle defect images on the surface of small magnetic rings was realized. Finally, a classifier based on a BP neural network is designed to classify the scar images and crack images determined by different threshold segmentation methods. The classification accuracies of the iterative method, the OTSU method, the maximum entropy method, and the adaptive threshold segmentation method are, respectively, 85%, 87.5%, 95%, and 97.5%. The adaptive threshold segmentation method proposed in this paper has the highest classification accuracy. Through verification and comparison, the proposed algorithm can segment defects quickly and accurately and suppress noise interference effectively. It is better than other traditional image threshold segmentation methods, validated by both segmentation accuracy and computational efficiency. At the same time, the real-time performance of our algorithm was performed on the advanced SEED-DVS8168 platform.

Optimized Multiscale Entropy Model Based on Resting-State fMRI for Appraising Cognitive Performance in Healthy Elderly.

Many studies have indicated that an entropy model can capture the dynamic characteristics of resting-state functional magnetic resonance imaging (rfMRI) signals. However, there are problems of subjectivity and lack of uniform standards in the selection of model parameters relying on experience when using the entropy model to analyze rfMRI. To address this issue, an optimized multiscale entropy (MSE) model was proposed to confirm the parameters objectively. All healthy elderly volunteers were divided into two groups, namely, excellent and poor, by the scores estimated through traditional scale tests before the rfMRI scan. The parameters of the MSE model were optimized with the help of sensitivity parameters such as receiver operating characteristic (ROC) and area under the ROC curve (AUC) in a comparison study between the two groups. The brain regions with significant differences in entropy values were considered biomarkers. Their entropy values were regarded as feature vectors to use as input for the probabilistic neural network in the classification of cognitive scores. Classification accuracy of 80.05% was obtained using machine learning. These results show that the optimized MSE model can accurately select the brain regions sensitive to cognitive performance and objectively select fixed parameters for MSE. This work was expected to provide the basis for entropy to test the cognitive scores of the healthy elderly.

[Optimized multi-scale entropy to localize epileptogenic hemisphere of temporal lobe epilepsy based on resting-state functional magnetic resonance imaging].

Entropy model is widely used in epileptic electroencephalogram (EEG) analysis, but there are few reports on how to objectively select the parameters to compute the entropy model in the analysis of resting-state functional magnetic resonance imaging (rfMRI). Therefore, an optimization algorithm to confirm the parameters in multi-scale entropy (MSE) model was proposed, and the location of epileptogenic hemisphere was taken as an example to test the optimization effect by supervised machine learning. The rfMRI data of 20 temporal lobe epilepsy (TLE) patients with hippocampal sclerosis, positive on structural magnetic resonance imaging, were divided into left and right groups. Then, the parameters in MSE model were optimized by the receiver operating characteristic curves (ROC) and area under ROC curve (AUC) values in sensitivity analysis, and the entropy value of the brain regions with statistically significant difference between the groups were taken as sensitive features to epileptogenic hemisphere lateral. The optimized entropy values of these bio-marker brain areas were considered as feature vectors input into the support vector machine (SVM). Finally, combining optimized MSE model with SVM could accurately distinguish epileptogenic hemisphere in TLE at an average accuracy rate of 95%, which was higher than the current level. The results show that the MSE model parameter optimization algorithm can accurately extract the functional imaging markers sensitive to the epileptogenic hemisphere, and achieve the purpose of objectively selecting the parameters for MSE in rfMRI, which provides the basis for the application of entropy in advanced technology detection.

Negative effects of interictal spikes on theta rhythm in human temporal lobe epilepsy.

Interictal spike is a biomarker of epilepsy that can occur frequently between seizures. Its potential effects on brain oscillations, especially on theta rhythm (4-8 Hz) that is related to a variety of cognitive processes, remain controversial. Using local field potentials recorded from patients with temporal lobe epilepsy (TLE), we investigated here the impact of spikes on theta rhythm immediately after spikes and during the prolonged periods (lasting 4-36 s) between adjacent spikes. Local field potentials (LFPs) were recorded in different epileptogenic areas including the anterior hippocampus (aH) and the entorhinal cortex (EC) as well as in the extended propagation pathway. We found that interictal spikes had a significant inhibitory effect on theta rhythm. Power of theta rhythm was reduced immediately after spikes, and the inhibitory effect on theta rhythm might sustain during the prolonged between-spike periods. The inhibitory effect was more severe when the epileptogenic areas involved both the aH and EC compared to that involved only a single structure. These observations suggest that interictal spikes have a significant negative impact on theta rhythm and may thus play a role in theta-related cognition changes in patients with TLE.

Complexity analysis of EEG under magnetic stimulation on acupoint of Guangming(GB37).

Changes in electroencephalogram (EEG) signals under repetitive magnetic stimulation at the acupoint of Guangming (GB37) were analyzed using nonlinear dynamics complexity. C0 complexity is a statistical indicators which can quantify time dynamics of EEG signals. The study compared the C0 complexity under magnetic stimulation at GB37 with those at a mock point, as well as the C0 complexity under visual stimulation before and after magnetic stimulation at GB37. The results showed that the C0 complexity values of EEG signals in the electrode F3,Cz,C4 and P3 were different depending on whether magnetic stimulation was at the GB37 or a mock point (P <; 0.05),and the C0 complexity of magnetic stimulation on GB37 was generally higher than that on mock point. Moreover, EEG signals from visual stimulation before magnetic stimulation at GB37 were significantly different from those after magnetic stimulation at GB37 in two electrodes which were C4 and P3(P <; 0.05). The conclusion of the study is that magnetic stimulation at GB37 has a significant impact on EEG signals. First, EEG complexity during magnetic stimulation at GB37 was significantly higher than that at the mock point in frontal area, central area and parietal area (electrodes F3, Cz, C4 and P3). Second, EEG signals in central area and parietal area (electrodes C4 and P3) resulting from visual stimulation differed depending on whether magnetic stimulation at GB37 was given. The study has important significance for the application of magnetic stimulation on acupoints.

[Quantitative evaluation of inhibitory effects of epileptic spikes on theta rhythms in the network of hippocampal CA3 and entorhinal cortex in patients with temporal lobe epilepsy].

Epileptic spike is an indicator of hyper-excitability and hyper-synchrony in the neural networks. The inhibitory effects of spikes on theta rhythms (4-8 Hz) might be helpful to understand the mechanism of epileptic damage on the cognitive functions. To quantitatively evaluate the inhibitory effects of spikes on theta rhythms, intracerebral electroencephalogram (EEG) recordings with both sporadic spikes (SSs) and spike-free transient period between adjacent spikes were selected in 4 patients in the status of rapid eyes movement (REM) sleep with temporal lobe epilepsy (TLE) under the pre-surgical monitoring. The electrodes of hippocampal CA3 and entorhinal cortex (EC) were employed, since CA3 and EC built up one of key loops to investigate cognition and epilepsy. These SSs occurred only in CA3, only in EC, or in both CA3 and EC synchronously. Theta power was respectively estimated around SSs and during the spike-free transient period by Gabor wavelet transform and Hilbert transform. The intermittent extent was then estimated to represent for the loss of theta rhythms during the spike-free transient period. The following findings were obtained: (1) The prominent rhythms were in theta frequency band; (2) The spikes could transiently reduce theta power, and the inhibitory effect was severer around SSs in both CA3 and EC synchronously than that around either SSs only in EC or SSs only in CA3; (3) During the spike-free transient period, theta rhythms were interrupted with the intermittent theta rhythms left and theta power level continued dropping, implying the inhibitory effect was sustained. Additionally, the intermittent extent of theta rhythms was converged to the inhibitory extent around SSs; (4) The average theta power level during the spike-free transient period might not be in line with the inhibitory extent of theta rhythms around SSs. It was concluded that the SSs had negative effects on theta rhythms transiently and directly, the inhibitory effects aroused by SSs sustained during the spike-free transient period and were directly related to the intermittent extent. It was indicated that the loss of theta rhythms might qualify exactly the sustained inhibitory effects on theta rhythms aroused by spikes in EEG. The work provided an argumentation about the relationship between the transient negative impact of interictal spike and the loss of theta rhythms during spike-free activity for the first time, offered an intuitive methodology to estimate the inhibitory effect of spikes by EEG, and might be helpful to the analysis of EEG rhythms based on local field potentials (LFPs) in deep brain.

Combining task-evoked and spontaneous activity to improve pre-operative brain mapping with fMRI.

Noninvasive localization of brain function is used to understand and treat neurological disease, exemplified by pre-operative fMRI mapping prior to neurosurgical intervention. The principal approach for generating these maps relies on brain responses evoked by a task and, despite known limitations, has dominated clinical practice for over 20years. Recently, pre-operative fMRI mapping based on correlations in spontaneous brain activity has been demonstrated, however this approach has its own limitations and has not seen widespread clinical use. Here we show that spontaneous and task-based mapping can be performed together using the same pre-operative fMRI data, provide complimentary information relevant for functional localization, and can be combined to improve identification of eloquent motor cortex. Accuracy, sensitivity, and specificity of our approach are quantified through comparison with electrical cortical stimulation mapping in eight patients with intractable epilepsy. Broad applicability and reproducibility of our approach are demonstrated through prospective replication in an independent dataset of six patients from a different center. In both cohorts and every individual patient, we see a significant improvement in signal to noise and mapping accuracy independent of threshold, quantified using receiver operating characteristic curves. Collectively, our results suggest that modifying the processing of fMRI data to incorporate both task-based and spontaneous activity significantly improves functional localization in pre-operative patients. Because this method requires no additional scan time or modification to conventional pre-operative data acquisition protocols it could have widespread utility.

[Inhibitory effects of epileptic spikes on theta rhythm in rat pilocarpine model of temporal lobe epilepsy].

Epilepsy clinically has an inhibitory impact on cognitive function, but whether it is associated with epileptogenesis is unclear. Since the epileptic spike characterizes temporal lobe epilepsy (TLE), the present study was aimed to analyze the transient effects of sporadic spikes (SSs) on theta rhythm during epileptogenesis. The local field potentials (LFPs) were recorded in CA1 area in four rats with the pilocarpine injections during exploration, and theta phase stability and power were globally estimated around SSs, also during prolonged period without SS (both as experiments) as well as pre-injections (control). Finally, the LFPs were simulated by changing the average excitatory and inhibitory synaptic gain values (including slow and fast inhibition loops) with the help of simplified dynamical model of CA1 networks, and then theta phase stability was evaluated in several cases. It was found that the SSs could have negative impacts on theta rhythm both transiently and persistently, which may be dependent on the temporal courses leading to epilepsy, being acuter in early stage than later stage, but even in latent stage, theta power was strong. The simulations partly demonstrated that the synaptic imbalance concomitant with the occurrence of SSs might be related to the dynamics of theta phase stability. The results indicate that the SSs might have persistent negative impacts on the cognition rhythm, and the effects might alter during epileptogenesis, leading to the cognitive dysfunction.

Neurobiological basis of head motion in brain imaging.

Individual differences in brain metrics, especially connectivity measured with functional MRI, can correlate with differences in motion during data collection. The assumption has been that motion causes artifactual differences in brain connectivity that must and can be corrected. Here we propose that differences in brain connectivity can also represent a neurobiological trait that predisposes to differences in motion. We support this possibility with an analysis of intra- versus intersubject differences in connectivity comparing high- to low-motion subgroups. Intersubject analysis identified a correlate of head motion consisting of reduced distant functional connectivity primarily in the default network in individuals with high head motion. Similar connectivity differences were not found in analysis of intrasubject data. Instead, this correlate of head motion was a stable property in individuals across time. These findings suggest that motion-associated differences in brain connectivity cannot fully be attributed to motion artifacts but rather also reflect individual variability in functional organization.

Transient impact of spike on theta rhythm in temporal lobe epilepsy.

Epileptic spike is an indicator of hyper-excitability and hyper-synchrony of neural networks. While cognitive deficit in epilepsy is a common observation, how spikes transiently influence brain oscillations, especially those essential for cognitive functions, remains obscure. Here we aimed to quantify the transient impacts of sporadic spikes on theta oscillations and investigate how such impacts may evolve during epileptogenesis. Longitudinal depth EEG data were recorded in the CA1 area of pilocarpine temporal lobe epilepsy (TLE) rat models. Phase stability, a measure of synchrony, and theta power were estimated around spikes as well as in the protracted spike-free periods (FP) at least 1h after spike bursts. We found that the change in theta power did not correlate with the change in phase stability. More importantly, the impact of spikes on theta rhythm was highly time-dependent. While theta power decreased abruptly after spikes both in the latent and chronic stages, changes of theta phase stability demonstrated opposite trends in the latent and chronic stages, potentially due to the substantial reorganization of neural circuits along epileptogenesis. During FP, theta phase stability was significantly higher than the baseline level before injections, indicating that hyper-synchrony remained even hours after the spike bursts. We concluded that spikes have transient negative effects on theta rhythm, however, impacts are different during latent and chronic stages, implying that its influence on cognitive processes may also change over time during epileptogenesis.

Destructive power dynamics of alpha-theta oscillations via spike and wave in CA3.

The power dynamics of alpha-theta oscillations via inter-ictal spikes and waves (SWs) in CA3 is investigated by means of Hilbert transform and the statistical method based on CA3 channel of LFP(Local Field Potention) data sampled on total 6 rats in resting with sniffing and of iEEG data on total 10 patients in quiet wakefulness. The comparison of alpha-theta power is done between the inter-ictal groups and control groups. It is concluded that the inter-ictal SWs can disrupt the power of alpha-theta oscillations, leading to the decreased power after SW. Because the alpha-theta oscillations are related with the cognition, it is estimated that the inter-ictal SWs can negatively affecte the cognitive function during the inter-ictal dynamics, although the alpha-theta power will be recoverable in some days after injections, even exceed over the power level before injections.

A simulation for effects of RF electromagnetic radiation from a mobile handset on eyes model using the finite-difference time-domain method.

Finite-difference time-domain (FDTD) method and specific absorption rate (SAR) are employed here to study the relationship between the radiation of a mobile handset and the human being health. Nowadays, much more attention has been paid to the simulations for the effects of RF radiation on the particular organs, such as the eyes or the ears because they are more sensitive and more near to the working mobile. In the paper, the simulation of the RF fields is focused on the eyes model and the eyes with glasses of metal frame respectively. A planar inverted F antenna is used as an exposure source at 900 MHz. Under this case, the intensity of the electrical field is calculated and analyzed. Also, SAR is utilized to evaluate the absorption of the organs to the radiation. Through the simulation, the peak values of SAR per 1G tissue at the radiating power being 600mW are obtained. It is concluded that when people are wearing glasses of metal framework, the peak value of SAR is shown to be a little higher than the safety limits. It is suggested that the radiation from the mobile handset do more harmful effect on the eyes with the glasses of metal frameworks.

Application of the directed transfer function method to the study of the propagation of epilepsy neural information.

A study of the propagation of electroencephalogram (EEG) activity before seizure by means of the Directed Transfer Function (DTF) is presented. The DTF method is a multi-channel parametric method of analysis based on an autoregressive model, and is capable of supplying such information as the direction, spectra and dynamics of the propagation of EEG signals. This method is typically utilized to determine patterns of neural information flow. In this paper, the DTF method is applied to detect the propagation of EEG signals, and the work is focused on aiding the clinical diagnose for the foci and the propagation pathway of the epilepsy neural information. The work has been efficiently utilized to diagnose complex partial seizures originating from temporal and frontal lobe structures in 10 patients, based on the intracranial recordings. It is concluded that the source of the seizure onset, as well as the neural circuitry, can be found so that the propagation of the epileptic information from the foci to the entire brain can be determined. It is tested that the DTF method may be effective and practical in the clinical diagnose.

An understanding for the abnormal spikes of the EEG simulation in a 2-d neural network.

The work here presents an abnormal EEG simulation and an analysis for the abnormal spikes in the simulation by using the wavelet method. The simulation is derived from the electrophysiological model of an excitable neuron being in a disorder process. The spike wave and the multi-spike wave of the EEG morphology are reconstructed by step changes in the concentration of the intracellular calcium ions ([Ca]i). In the further work, when the concentration of [Ca] i is sufficiently large, the multi-spike wave can also be reconstructed and the spikes of the potentials are analyzed by the multi-layer wavelet method. The work will be helpful to understand how the EEG morphology is formed from the microcosmic viewpoint.

Study of the effects of 50 Hz homogeneous magnetic field on apoptosis and proliferation of SNU cells in vitro.

The biological effects of magnetic field on SNU (human low differentiated gastric adenocarcinoma cell line) cells are studied in this paper. SNU cells were randomly divided into control groups and four treatment groups, the treatment groups were respectively irradiated by 50 Hz ferromagnetic field (0.097 T) 5 min., 30 min., 60 min., and 120 min. We observed the effects on proliferation and apoptosis of SNU cells after the treatment of magnetic field by flow cytometric (FCM) DNA analysis and electron microscope observation. The apoptosis rate in treatment groups are 4.75% +/- 1.24%, 6.50% +/- 0.61%, 9.20% +/- 1.76% and 6.26% +/- 2.95% respectively and significantly higher than that in control group. In the irradiation time range from 5 min to 60 min, there is a significant time-depended response correlation of apoptosis rate( r = 0.97, P < 0.01), but FCM results showed that the effects of 50 Hz homogeneous ferromagnetic field on the proliferation and distribution of cell cycle of SNU cells is not significant. We concluded that irradiation of 50 Hz homogeneous ferromagnetic field could promote apoptosis of SNU cells.

A theoretical study for the chaos and complexity of the synchronous oscillations in electrically coupled abnormal neurons.

Many experiments demonstrate that the synchrony of neurons is a hallmark in epileptic seizure and the dynamical process of the epilepsy is complex with new oscillations born. In fact, epileptic seizure is very complicated relating to many factors so that it can't be understood thoroughly only in some special aspect. Based on the previous work on synchronous oscillations of electrically coupled abnormal neurons, a theoretical effort is carried out to further investigate the chaos by Lyapunov exponent and phase portrait and degree of complexity by approximate entropy in the dynamical activities. It is concluded that the synchronous activities are chaotic and complex with new oscillations born and the values of Lyapunov exponent and approximate entropy are different with the electrical coupling strength. It is also found that the trend of approximate entropy is same as that of Lyapunov exponent in the study at the dynamical activity of the two electrical coupling neurons. In the synchrony of 2-D neuronal network, the values of Lyapunov exponent are almost much greater than that of the two electrical coupling neurons. The values of approximate entropy of the different neurons in the 2-D network have almost the same trend but approximate entropy of neuron in synchrony is greater than that of neuron in non-synchrony. It is indicated that the neurons in synchrony have greater ability to produce new oscillations than that in non-synchrony. The theoretical work is helpful to understand the pathological mechanism of new oscillations born in epilepsy from a nonlinear point of view.