Progresses and prospects on frequency recognition methods for steady-state visual evoked potential / 生物医学工程学杂志

Steady-state visual evoked potential (SSVEP) is one of the commonly used control signals in brain-computer interface (BCI) systems. The SSVEP-based BCI has the advantages of high information transmission rate and short training time, which has become an important branch of BCI research field. In this review paper, the main progress on frequency recognition algorithm for SSVEP in past five years are summarized from three aspects, i.e., unsupervised learning algorithms, supervised learning algorithms and deep learning algorithms. Finally, some frontier topics and potential directions are explored.

Bacomics--a new discipline integrating brain and the outside / 生物医学工程学杂志

Bacomics is a unified framework for the interactions of the brain and the outside world, integrating the subject, method, and application mode of brain-apparatus conversation. This article divides the brain-apparatus conversation modes from the perspective of biological and non-biological apparatus, including the brain-biological organ interaction (BAC-1), brain-external non-living equipment and environment interaction (BAC-2), and the fusion agents of these two interactions (BAC-3), and explains the ways and potential applications in different modes.

Brain-computer interface: from lab to real scene / 生物医学工程学杂志

Brain-computer interface (BCI) can be summarized as a system that uses online brain information to realize communication between brain and computer. BCI has experienced nearly half a century of development, although it now has a high degree of awareness in the public, but the application of BCI in the actual scene is still very limited. This collection invited some BCI teams in China to report their efforts to promote BCI from laboratory to real scene. This paper summarizes the main contents of the invited papers, and looks forward to the future of BCI.

Atypical Antipsychotics Mediate Dynamics of Intrinsic Brain Activity in Early-Stage Schizophrenia? A Preliminary Study

Objective@#Abnormalities of static brain activity have been reported in schizophrenia, but it remains to be clarified the temporal variability of intrinsic brain activities in schizophrenia and how atypical antipsychotics affect it. @*Methods@#We employed a resting-state functional magnetic resonance imaging (rs-fMRI) and a sliding-window analysis of dynamic amplitude of low-frequency fluctuation (dALFF) to evaluate the dynamic brain activities in schizophrenia (SZ) patients before and after 8-week antipsychotic treatment. Twenty-six schizophrenia individuals and 26 matched healthy controls (HC) were included in this study. @*Results@#Compared with HC, SZ showed stronger dALFF in the right inferior temporal gyrus (ITG.R) at baseline. After medication, the SZ group exhibited reduced dALFF in the right middle occipital gyrus (MOG.R) and increased dALFF in the left superior frontal gyrus (SFG.L), right middle frontal gyrus (MFG.R), and right inferior parietal lobule (IPL.R). Dynamic ALFF in IPL.R was found to significant negative correlate with the Scale for the Assessment of Negative Symptoms (SANS) scores at baseline. @*Conclusion@#Our results showed dynamic intrinsic brain activities altered in schizophrenia after short term antipsychotic treatment. The findings of this study support and expand the application of dALFF method in the study of the pathological mechanism in psychosis in the future.

Multi?modal evaluation of Alzheimer disease by using joint independent component analysis of functional MRI diffusion tensor imaging / 中华放射学杂志

Objective We utilized a joint independent component analysis (Joint ICA), a novel method that combined rs?fMRI and DTI information, to describe comprehensive characteristics of brain functional activities and microstructural changes in the continuum of AD. Methods We employed a Joint ICA to calculate ALFF maps of fMRI data and FA maps of DTI data and fuse them in healthy controls (n=68), SCD (n=35), amnesic MCI (n=47) and AD (n=31). Besides, we applied one way ANOVA to detect the significant differences of joint components among groups, while controlling the age, gender, education, head motion, volumes of gray matter, white matter and CSF. Partial correlation analysis was used to test the relationships between joint ICs and cognitive measures. Results The results showed that there was no inner?group difference in HC and SCD groups (F=14.16, P<0.05). Compared to HC, SCD and AD groups, the ALFF component of aMCI group showed higher values in the bilateral cerebellum, bilateral precuneus, bilateral angular gyrus, bilateral frontal gyrus, bilateral temporal areas, thalamus and left insula. And in these regions, the ALFF of AD group was lower than HC. For the FA component map, same differences were found in the corpus callosum and limbic system. Furthermore, positive partial correlation between the IC weights and Mini?Mental State Examination (MMSE) scores was also found (r=0.29, P<0.01). Conclusions Multi?modal evaluation of AD has been implemented by using Joint ICA analysis of fMRI?DTI, which would contribute to early prediction, diagnosis, and even effective intervention in AD. These findings could help to explain the underlying mechanism of the disease progression.

Brain function network analysis and recognition for psychogenic non-epileptic seizures based on resting state electroencephalogram / 生物医学工程学杂志

Studies have shown that the clinical manifestation of patients with neuropsychiatric disorders might be related to the abnormal connectivity of brain functions. Psychogenic non-epileptic seizures (PNES) are different from the conventional epileptic seizures due to the lack of the expected electroencephalographically epileptic changes in central nervous system, but are related to the presence of significant psychological factors. Diagnosis of PNES remains challenging. We found in the present work that the connectivity between the frontal and parieto-occipital in PNES was weaker than that of the controls by using network analysis based on electroencephalogram (EEG) signals. In addition, PNES were recognized by using the network properties as linear discriminant nalysis (LDA) input and classification accuracy was 85%. This study may provide a feasible tool for clinical diagnosis of PNES.

Study on neurofeedback system based on electroencephalogram signals / 生物医学工程学杂志

Neurofeedback, as an alternative treatment method of behavioral medicine, is a technique which translates the electroencephalogram (EEG) signals to styles as sounds or animation to help people understand their own physical status and learn to enhance or suppress certain EEG signals to regulate their own brain functions after several repeated trainings. This paper develops a neurofeedback system on the foundation of brain-computer interface technique. The EEG features are extracted through real-time signal process and then translated to feedback information. Two feedback screens are designed for relaxation training and attention training individually. The veracity and feasibility of the neurofeedback system are validated through system simulation and preliminary experiment.

Chinese brain template built on 3D high resolution MR imaging at 3.0T / 生物医学工程学杂志

Brain atlas provides a spatial reference system on which other images can be interpreted in a consistent way, and it is essential for the brain imaging research. However, because of the differences in structure between occidental and oriental brains, the brain atlas based on Western populations, e. g., the International Consortium for Brain Mapping's 154 T1 Weighted Average Atlas, may not be appropriate for other ethnic groups. Therefore, in the present study, we produce an average brain atlas which is based on the data collected from 100 healthy Chinese volunteers. The differences in brains between the Chinese population and the Western population were also investigated. Comparatively,Chinese brains are wider and shorter in size, and smaller in volume.

ERP spatio-temporal analysis for perception of motion-in-depth: the effect of size factor on cognition / 生物医学工程学杂志

By means of continuous visual stimulation to simulate the motion-in-depth course where object was approaching to observer gradually, we studied the event-related potentials (ERP) response in that course. This article was directed to the effect of object size factor on the ERP of motion-in-depth perception. The subjects recruited were 9 health men, aged 22-29 years. The results illustrated that, in motion-in-depth course, the main components were P80, N100, P140, N220, P300, N350, and P400. They mainly appeared in the frontal area, occipital area and occipital-parietal area; some of them showed near by the parietal-temporal or occipital-temporal area. Among these components, N220 was most closely related to the perception of motion-in-depth. From the data analysis in 500 ms, bigger object led to earlier and stronger response.

On the study methods of electroencephalograph synchronization / 生物医学工程学杂志

Synchronous brain activities are considered as an indicator of the functional binding or integration. In this paper, based on the neural electric activities at various spatial scales, we explained the basic concept and measuring index of neural synchronization; then we summarized the main signal processing methods developed for phase synchronization analysis of electroencephalograph (EEG), including the conventional signal processing method, and modern signal modeling approaches. Finally, the main differences among the different methods were compared and some critical problems in the study of EEG synchronization were discussed.

Study on direct MRI detection of neuronal magnetic field / 国际生物医学工程杂志

With the development of medical imaging technology, hemodynamics-based functional magnetic resonance imaging (fMRI) has gradually become one of the major tools to investigate human brain function, however, it is of limited temporal resolution. In recent years, neuronal current MRI (nc-MRI) was proposed as a new imaging method to directly map the magnetic field change caused by neural activities. Theoretically, nc-MRI can non-inva- sively locate brain activities with very high spatial and temporal resolution, thus it may greatly improve the study of human brain function. This paper reviews the construction mechanism of nc-MRI, including theoretical model of the neuronal magnetic field and signal source. Arithmetic simulation of nc-MRI signal with an illustration of our work on simulation of a dendrite branch magnetic field is presented. New development of the experimental studies and foreground of nc-MRI area are discussed.

Research on analytical methods of phase synchronization in EEG / 生物医学工程学杂志

Synchronous brain activities are regarded as the indicator of the functional integration of the brain. Based on the physiological mechanism of synchronous activity, the detection process and research on quantification methods concerning synchronization are explained. Conventional and modern signal processing approaches, such as time analysis, frequency analysis, Hilbert transform (HT), especially wavelet transform (WT), are applied to EEG (electroencephalograph) synchronization study. Simulation data and real data are utilized to test the methods mentioned above, which prove the usefulness and validity of methods. According to the final results, Hilbert analysis is better for its authenticity.

Detrended fluctuation analysis of epileptic rat EEG / 生物医学工程学杂志

Detrended fluctuation analysis (DFA) is a new technique used to characterize the long-range temporal correlation (LRTC) structure of non-stationary time series, which has been applied in electroencephalographic (EEG) oscillations and diseases such as Alzheimer and stroke. In this paper, DFA is used to study the scaling exponents of intracranial EEG recordings of Pilocarpine-induced epileptic rat. It was found that when the brain functional status changed from non-epileptiform discharges to continuous-epileptiform discharges and to period-epileptiform discharges, the average scaling exponents of four brain regions (left cortex and left hippocampus, right cortex and right hippocampus) changed from 0.97 to 0.82 and to 0.94, and a statistically significant difference between the brain functional states was shown by paired T test (P < 0.05), thus suggesting that the local neuronal network dynamics of the three brain function states may be different. But in regard to the three brain function states, there is no statistically significant difference between the four brain regions(P >0.05).

Comparison of steady-state visually evoked potential evoked by different monochromatic light / 生物医学工程学杂志

The cone cell on the retina of human is the sensor of vision under illumination; it can be classified into three types: red cone cell, green cone cell, and blue cone cell. There is different property of absorbing light for each type of cone cell. In this work, a 10 Hz pulse was used to drive red, green and blue light emitting diodes respectively, and the different monochromatic light with the same luminance was obtained. The eyes of ten subjects were stimulated by different monochromatic light independently; an EGI system with 128 channels was used to record the steady-state visually evoked potential (SSVEP). After applying the fast fourier transform (FFT) to the SSVEP data, we found that the distribution of the neural network in the initial vision cortex activated by the output of the different-typed cone cell remained mainly identical, but there was some difference in intensity between the three types of network: the activity by blue light is the strongest one, that by red light is in the middle, and that by green light is the weakest one.

The improved FOCUSS combined with the fMRI priors for EEG source localization and its preliminary application / 生物医学工程学杂志

The sources generating the scalp recordings can be more precisely estimated with the use of fMRI priors. In this paper, an improved source localization algorithm which combines the fMRI priors into the iteration procedure of FOCUSS is presented. The modified algorithm consists of three steps: Firstly, the statistical parameters of fMRI are estimated with the ruler of SPM; Secondly, a diagonal weight matrix is constructed with the estimated parameters; Finally, the weight matrix is integrated into the iteration procedure of FOCUSS. The method was used to localize the EEG sources in the form discrimination experiments, where the fMRI and EEG were recorded, and the results preliminarily confirmed the validity of method.

Synchronization analysis of ECoG and EHG from eplieptiform discharges rats / 生物医学工程学杂志

The mechanisms leading to the occurrence of seizures in humans are still poorly understood. It is widely accepted, however, that the process of seizure generation is closely associated with an abnormal synchronization of neurons. In order to investigate this process, we have studied synchronization between different regions of the brain from intracranial EEG recordings of Pilocarpine-induced epileptic rat by Synchronization likelihood (SL). It was found that during the state of transition from non-epileptiform discharges to continuous-epileptiform discharges, synchronization between left-ECoG and left-EHG was significantly strengthened, and similar change had taken place between right-ECoG and right-EHGd; left-ECoG; and right-ECoG and left-EHG and right-EHG (P < 0.05). During the state of transition from continuous-epileptiform discharges to period-epileptiform discharges, the synchronization was significantly weakened between left-ECoG and left-EHG, and similar change was noted between left-EHG and right-EHG (P < 0.01). The results showed that SL might be used to assess the dynamics of synchronization and it might be helpful to understanding the mechanisms involving the origin of epileptiform discharge.

A new method based on sparse component decomposition to remove MRI artifacts in the continuous EEG recordings / 生物医学工程学杂志

How to effectively remove the magnetic resonance imaging (MRI) artifacts in the electroencephalography (EEG) recordings, when EEG and functional magnetic resonance imaging (FMRI) are simultaneous recorded, is a challenge for integration of EEG and FMRI. According to the temporal-spatial difference between MRI artifacts and EEG, a new method based on sparse component decomposition in the mixed over-complete dictionary is proposed in this paper to remove MR artifacts. A mixed over-complete dictionary (MOD) of waveletes and discrete cosine which can exhibit the temporal-spatial discrepancy between MRI artificats and EEG is constructed first, and then the signals are separated by learning in this MOD with matching pursuit (MP) algorithm. The method is applied to the MRI artifacts corrupted EEG recordings and the decomposition result shows its validation.

A method for the medical image registration based on the statistics samples averaging distribution theory / 生物医学工程学杂志

The registration method based on mutual information is currently a popular technique for the medical image registration, but the computation for the mutual information is complex and the registration speed is slow. In engineering process, a subsampling technique is taken to accelerate the registration speed at the cost of registration accuracy. In this paper a new method based on statistics sample theory is developed, which has both a higher speed and a higher accuracy as compared with the normal subsampling method, and the simulation results confirm the validity of the new method.

A 3D tomography technique based study on event-related potential in attention / 生物医学工程学杂志

In this paper the event-related potential (ERP) of selective attention to the left and right visual field is investigated with 3D tomography technique. The results show that compared with the scalp surface ERP data, the current source intensity derived from tomography can better reflect the enhanced effect of P1 and N1, especially N1. Moreover, C1 component can be observed in the results, which cannot be identified in the scalp data.

Single visual-evoked potential estimation based on sparse decomposition / 生物医学工程学杂志

Iterative weighted sparse decomposition is a method to determine the weight coefficients of the minimum l1 norm optimization in accord with the two-scale relationship of the white noise in the multiresolution wavelet structure and to gradually suppress the influence of the strong noises through an iteration operation. The single-trial Visual Evoked Potential(VEP) estimation results confirmed the effectiveness of the method, and thus supported the viewpoint that the results of the single VEP estimation were different.