Prediction Model Based on BP-ANN and PCA for the Peak Occurrence of Liriomyza Huidobrensis

Liriomyza huidobrensis （Blanchard） is an important vegetable pest of pathology. In order to improve the accuracy of prediction of Liriomyza huidobrensis and to control the Liriomyza huidobrensis effectively, this paper presents a new prediction model by principal components analysis （PCA） and back propagation artificial neural network （BP-ANN） methods. The historical data from 1999 to 2007 on population occurrence are analyzed in order to find out a non-linear relationship between the pest occurrence and the meteorological factors. And then by using analysis results, the prediction model of Liriomyza huidobrensis occurrence in Jianshui in Yunnan is built. The new model has successfully applied to verify the paddy stem borer population occurrence in 2006. Test results show that the new prediction model with BP-ANN and PCA can improve the prediction accuracy.

Design of an EEG Preamplifier for Brain-Computer Interface

As a non-invasive neurophysiologieal index for brain-computer interface （BCI）, electroencephalogram （EEG） attracts much attention at present. In order to have a portable BCI, a simple and efficient pre-amplifier is crucial in practice. In this work, a preamplifier based on the characteristics of EEG signals is designed, which consists of a highly symmetrical input stage, low-pass filter, 50 Hz notch filter and a post amplifier. A prototype of this EEG module is fabricated and EEG data are obtained through an actual experiment. The results demonstrate that the EEG preamplifier will be a promising unit for BCI in the future.

Analysis of Brain Activation during Motor Imagery Based on fMRI

Brain activation during motor imagery （MI） has been studied extensively for years. Based on studies of brain activations of MI, in present study, a complex finger tapping imagery and execution experi- ment is designed to test the brain activation during MI. The experiment results show that during MI, brain activation exists mainly in the supplementary motor area （SMA） and precentral area where the dorsal premotor area （PMd） and the primary motor area （M1） mainly located; and some activation can be also observed in the primary and secondary somatosensory cortex （S1）, the inferior parietal lobule （IPL） and the superior parietal lobule （SPL）. Additionally, more brain activation can be observed during left-hand MI than during right-hand MI, this difference probably is caused by asymmetry of brain.

Simulation Study of the Dendritic Effect on Direct MRI Detection of Neural Electric Event

Currently hemodynamic-based functional MRI technique is of limitation in temporal resolution. As neural activities in the brain accompany with current induced neuronal magnetic fields （NMF）, it is possible to utilize MRI to detect NMF directly thus to improve the temporal resolution. In this work, the contribution of dendrite branch to NMF is investigated by numeric simulation. The results indicate that the existence of dendrite branch may enhance the detectability of NMF by MRI directly.

Enhancement of Spatial Learning-Memory in Developing Rats via Mozart Music

This paper studies the effect of musical stimulations on the capability of the spatial learningmemory in developing rats by behavioral and electrophysiological techniques. Rats, which are exposed to Mozart＇s Sonata for Two Pianos in D Major, complete learning tasks of the Moriss water maze with significantly shorter latencies, and the power spectrum of alpha band of electrohippocampogram （EHG） significantly increase, compared with the control rats and rats exposed to the horror music. The results indicate that if given the stimulation of Mozart music in the developmental period of the auditory cortex, the capability of the spatial learning-memory can be significantly changed. The enhancement of alpha band of EHG may be related to the change of this function mainly.

A Music Preference Test System for Rats

In music preference experiments, housing conditions and the control of parameters for animals can affect experimental results. However, the needs of animals are indeed insufficiently considered in many reports of animal experiments. In order to evaluate which music rats prefer, we developed a new music preference test system. Dwelling time and visiting frequency can be recorded automatically when rats moving among different compartments of the system. We can also observe the behaviors of rats captured by a video camera. By this system, the music preference can be found, and then the related music can be used in following various studies. In this paper, we described the design of this music preference test system of rat, and some primary results were reported.

Stochastic fluctuations of permittivity coupling regulate seizure dynamics in partial epilepsy

Partial epilepsy is characterized by recurrent seizures that arise from a localized pathological brain region. During the onset of partial epilepsy, the seizure evolution commonly exhibits typical timescale separation phenomenon. This timescale separation behavior can be mimicked by a paradigmatic model termed as Epileptor, which consists of coupled fast-slow neural populations via a permittivity variable. By incorporating permittivity noise into the Epileptor model, we show here that stochastic fluctuations of permittivity coupling participate in the modulation of seizure dynamics in partial epilepsy. In particular, introducing a certain level of permittivity noise can make the model produce more comparable seizure-like events that capture the temporal variability in realistic partial seizures. Furthermore, we observe that with the help of permittivity noise our stochastic Epileptor model can trigger the seizure dynamics even when it operates in the theoretical nonepileptogenic regime. These findings establish a deep mechanistic understanding on how stochastic fluctuations of permittivity coupling shape the seizure dynamics in partial epilepsy,and provide insightful biological implications.

Common Spatial Pattern Ensemble Classifier and Its Application in Brain-Computer Interface

Abstract-Common spatial pattern （CSP） algorithm is a successful tool in feature estimate of brain-computer interface （BCI）. However, CSP is sensitive to outlier and may result in poor outcomes since it is based on pooling the covariance matrices of trials. In this paper, we propose a simple yet effective approach, named common spatial pattern ensemble （CSPE） classifier, to improve CSP performance. Through division of recording channels, multiple CSP filters are constructed. By projection, log-operation, and subtraction on the original signal, an ensemble classifier, majority voting, is achieved and outlier contaminations are alleviated. Experiment results demonstrate that the proposed CSPE classifier is robust to various artifacts and can achieve an average accuracy of 83.02%.

A Study on Melody Tempo with EEG

In this paper, tempo perception is investi- gated by recording spontaneous electroencephalograph （EEG）. Ten normal male non-musician college students are selected according to questionnaire results after listening absorbedly to four different tempos of an excerpt from a Mozart sonata. EEGs data are recorded when the subjects are listening to the music. The EEG spectral power （SP） is analyzed for alpha band. The varying trend of power spectrum during exposure to music excerpts of different tempos is studied and shows the consistence with the previous tempo-specific hypothesis： a tempo-transformed performance will sound less natural than an original performance does. The results presented in this paper suggest that tempo is an important factor that could influence the alpha rhythm.

Robot Animals Based on Brain-Computer Interface

The study of robot animals based on brain-computer interface （BCI） technology is an important field in robots and neuroscience at present. In this paper, the development status at home and abroad of the motion control of robot based on BCI and principle of robot animals are introduced, then a new animals＇ behavior control method by photostimulation is presented. At last, the application prospect is provided.

Language as Context Modulates Social Judgments

Social judgments are usually made in the context of complex information including verbal cues.Here we investigated the impact of verbal statements on social judgments by biasing male and female neutral faces with descriptives of differentially-valenced behaviour（criticizing or praising） targeting others or objects. Results showed significant main effects of valence and target, such that critical individuals were rated lower in likeability than praising ones and those targeting others relative to objects were valued less. In particular, those who criticized others were the most unlikeable. Among critical individuals, men were less likeable than women. Similarly, men became less valued while targeting others. Overall these findings suggest that the negative impact of critical attributes may trigger avoidance in social interaction while the positive impact of praise may trigger approach.

Increased Arousal Levels and Decreased Sleep by Brain Music in Rats

More and more studies have been reported on whether music and other types of auditory stimulation would improve the quality of sleep. Many of these studies have found significant results, but others argue that music is not significantly better than the tones or control conditions in improving sleep. For further understanding the relationship between music and sleep or music and arousal, the present study therefore examines the effects of brain music on sleep and arousal by means of biofeedback. The music is from the transformation of rapid eye movement （REM） sleep electroencephalogram （EEG） of rats using an algorithm in the Chengdu Brain Music （CBM） system. When the brain music was played back to rats, EEG data were recorded to assess the efficacy of music to induce or improve sleep, or increase arousal levels by sleep staging, etc. Our results demonstrate that exposure to the brain music increases arousal levels and decreases sleep in rats, and the underlying mechanism of decreased non-rapid eye movement （NREM） and REM sleep may be different.

fMRI-BCI:a Review

Functional magnetic resonance imaging （fMRI） is a new tool for brain-computer interface （BCI）. This paper presents an overview to fMRI-BCI. Our attention is mainly put on the methods of signal acquisition, signal preprocessing, and signal analysis of basic fMRI-BCI structure. The available softwares and the applications of fMRI-BCI are briefly introduced. At last, we suggest focusing on some technologies to make fMRI-BCI more perfect.

Diffusion magnetic resonance imaging for Brainnetome:A critical review

Increasing evidence shows that the human brain is a highly self-organized system that shows attributes of smallworldness,hierarchy and modularity.The ＂connectome＂ was conceived several years ago to identify the underpinning physical connectivities of brain networks.The need for an integration of multi-spatial and-temporal approaches is becoming apparent.Therefore,the ＂Brainnetome＂（brain-net-ome） project was proposed.Diffusion magnetic resonance imaging（dMRI） is a non-invasive way to study the anatomy of brain networks.Here,we review the principles of dMRI,its methodologies,and some of its clinical applications for the Brainnetome.Future research in this field is discussed.

A neglected GABAergic astrocyte:Calcium dynamics and involvement in seizure activity

Gamma-aminobutyric acid(GABA) contributes substantially to neurocognitive function as an important inhibitory neurotransmitter in the human cerebral cortex. However, the pathophysiology of disorders such as epilepsy are not well understood, since GABA agonists are not quite effective in treating epilepsy. Knowledge of the mechanism of action of GABA would contribute to review previously proposed anti-epileptic processes by GABA agonists. In this study based on recent experiments on GABAergic astrocytes, we developed a modified GABAergic astrocyte model, and successfully simulated a long-lasting Ca^(2+) oscillation in astrocytes after 0.5-s stimulation of GABAergic transmission. We then incorporated this GABAergic astrocyte model into a classical Ullah-Schiff seizure model and surprisingly found that this GABAergic astrocyte model functions to hinder the anti-epileptic action of GABA agonists, thereby explaining their low efficiency in previous experiments. These results also update our knowledge of the mechanism of action of GABA and the effects of astrocytes on physiological and pathological functions of the brain.

An EEG Acquisition System with Dynamic DC Suppression

A three op-amps instrumentation amplifier(I.A) is one of the most important segments in the electroencephalographic(EEG) acquisition system, which is used to suppress the interference of the common mode noise. However, electrode and op-amps offset voltages could saturate the I.A, so the ability of noise suppression for the I.A might be limited. To compensate for the electrode and op-amps offset voltages and improve the property of the I.A, the optical-isolated technology was used in the present study.This paper described the theory of DC suppression and employed the simulation software(i.e. Multisim10.0.) to demonstrate the constant<urrent source of the optical-isolated device comprised of general-purpose optocouplers.Using this technology we designed and tested an EEG acquisition system.During the test,a constant current was generated by the optocoupler(the MOTOROLA 4N35)when DC offset voltages from 0 to 15 mV were imposed on the input signal in the EEG acquisition system and the value of load resistance in the optical--isolated device was from 3 k to 15 kom.We also found that the IA with the gain of 857 could effectively reject a DC input rangeof±15mV.And An EEG signal is obtained by the EEG acquisition system,and a CMRR of 104.5 dB was achieved without trimmings.