Biomedical subjects

Dezhong Yao

Publications and source records attributed to Dezhong Yao.

At least 19 recordsLinked to original sources

PubMed2026

Angiotensin II regulates anxiety and social-affective top-down and bottom-up attention control in a sex-dependent manner.

BACKGROUND: The renin-angiotensin system (RAS) has been increasingly recognized as potent modulator of cognitive and affective functions, with angiotensin II type 1 receptor (AT1R) antagonists emerging as repurposing candidate for anxiety and stress-related disorders. However, it remains unclear whether transient AT1R blockade modulates emotional attentional control and whether these effects are sex-dependent. METHODS: We conducted a preregistered, randomized, double-blind, placebo-controlled pharmacological eye-tracking study in 79 healthy adults (males and females) and determined effects of transient AT1R blockade via losartan (50 mg) on emotional attention control using a validated anti-saccade paradigm with social (emotional faces) and non-social stimuli. Treatment effects on state anxiety and oculomotor responses were characterized using traditional metrics and a novel trial-history informed dynamic control framework. RESULTS: Losartan reduced state anxiety irrespective of sex but induced sexually dimorphic effects on attentional control. In females, losartan enhanced performance by reducing endpoint error without altering latency. Conversely, in males, losartan increased endpoint error and prolonged latency of the first correct saccade. Trial-history analyses revealed losartan reduced error probabilities following errors and repeat trials in both sexes. Yet, following correct trials, females receiving losartan maintained lower error probabilities, while males exhibited higher errors, potentially reflecting failure to disengage from effortful control. CONCLUSIONS: The RAS modulates anxiety and attentional control, the latter sex-dependently. AT1R blockade reconfigures attentional processing and adaptive control, suggesting sex-specific therapeutic potential in disorders characterized by excessive anxiety and attentional dysregulation. CLINICAL TRIALS REGISTRATION: ClinicalTrials.gov; https://clinicaltrials.gov/;NCT06329050.

Humans↗

PubMed2006

Removal of the ocular artifacts from EEG data using a cascaded spatio-temporal processing.

Eye movements and blinks may produce unusual voltage changes in human electroencephalogram (EEG). These effects may spread across scalp and mask brain signals. In this paper, a cascaded spatio-temporal processing procedure (CAST) is presented to remove artifact electrooculogram (EOG). Firstly a discrete equivalent distributed source on the cortical surface is reconstructed from the contaminated scalp recordings by a linear minimum norm estimation (i.e. a spatial analysis step). Then, the equivalent sources of EOG are identified by principal component analysis (PCA) of the equivalent distributed source time series (i.e. a temporal analysis step). Finally, the EOG-corrected scalp EEG is reconstructed from the equivalent distributed source where EOG components have been removed. The effectiveness of CAST is confirmed by the application to actual scalp data and a detailed comparative study.

Adult↗

PubMed2006

A novel method based on realistic head model for EEG denoising.

It is necessary to remove the noise in EEG before further EEG analysis and processing. For EEG is deeply masked in the noise background, it is very difficult to denoise EEG effectively. Proposed in this paper is a novel realistic head model based sparse decomposition algorithm to denoise EEG, which is an iterative procedure combining the subject's physiology of EEG generation into the denoising procedure. In this algorithm, the lead field overcomplete dictionary is numerically calculated according to the realistic head model firstly, and then the instantaneous EEG spatial potential is decomposed into one sparse combination of atoms in the lead field matrix by matching pursuit, and the sparse combination of atoms is to be regarded as the denoised EEG signal. The realistic head based sparse decomposition was tested by the simulated noisy potential and a real EEG recording collected in an oddball stimulus experiment, the results consistently confirmed the new method removed the uncorrelated noise in EEG effectively.

Algorithms↗

PubMed2006

The mechanism of involuntary visual spatial attention revealed by a new linear computation model.

EEG reveals brain electrical activities with high temporal resolution. Yet, multiple implicit variables may be involved in limited event related potential (ERP) measures. Special computation techniques are needed to recover these parameters. In the study of involuntary visual spatial attention, we may obtain the ERP in valid cued (V), invalid cued (I) and neutral cued (N) conditions. Usually, the effect of involuntary attention is computed by the subtraction model with the assumption that V/I and N are independent. Yet, they should be related. Treating V/I as a function of N, a linear model V(I) = W + GN is assumed, where W and G are implicit in the ERP measures. G is the gain control on the neutral function. Provided G and W are constant over a local brain region, we may use the Total Least Square (TLS) algorithm to compute their values. The values of W and G computed from an involuntary attention experiment data show that multiple implicit variables are involved in obtained ERPs. Here G acts as a "top-down" sensory modulator on the neutral ERPs and W is related to possible newly involved neural activities. The parameters derived from the new linear model also suggest that there are different mechanisms involved in involuntary attention and voluntary allocation of attention.

Adult↗

PubMed2006

Localization of latent epileptic activities using spatio-temporal independent component analysis of FMRI data.

Localizing interictal epileptic activities is a difficult problem in clinical practice. We report a novel noninvasive technique, resting functional magnetic resonance imaging (fMRI) with spatio-temporal independent component analysis (ICA), for localizing interictal epileptic activities. First, the fMRI data is separated into independent spatial patterns by spatial-ICA, and the patterns with Z-values larger than a threshold are selected as the potential spatial patterns of the epileptic activities. Second, the temporal series of the active points in the selected patterns are separated by temporal-ICA, and the component with the biggest Gaussian deviation (kurtosis) is selected as the representative of the epileptic discharge activity in a sub-region. Finally, those spatial sub-regions, which have distinct epileptic discharge activities confirmed by temporal-ICA are considered as the epileptic foci. This method was applied to fMRI data of six epileptic patients, and the results are consistent with the clinical assessment. Though more studies are required to validate this technique, the above preliminary results demonstrate the potential of using the resting fMRI with spatio-temporal ICA to detect and localize latent epileptic activities.

Adult↗

PubMed2006

An integrated neighborhood correlation and hierarchical clustering approach of functional MRI.

Clustering analysis is a promising data-driven method for the analysis of functional magnetic resonance imaging (fMRI) time series, however, the huge computation load makes it difficult for practical use. In this paper, neighborhood correlation (NC) and hierarchical clustering (HC) methods are integrated as a new approach where fMRI data are processed first by NC to get a preliminary image of brain activations, and then by HC to remove some noises. In HC, to better use spatial and temporal information in fMRI data, a new spatio-temporal measure is introduced. A simulation study and an application to visual fMRI data show that the brain activations can be effectively detected and that different response patterns can be discriminated. These results suggest that the proposed new integrated approach could be useful in detecting weak fMRI signals.

Brain↗

PubMed2005

A projection-based image registration algorithm and its application.

Proposed is a projection-based image registration technique where, by rearranging the projections of characteristic images, the image registration is implemented with two independent steps - rotation and translation, to perform the two-dimensional or three-dimensional rigid-body image registration addressing the head motion problem in functional magnetic resonance imaging (fMRI). For a 2D problem, the approach is based on a one-dimensional projection of a segmented two-dimensional characteristic image, in which the translation and rotation parameters are obtained with a one-dimensional cross-correlation-based estimator. This is then used to compute the cross-correlation between the projection of an image and a registration table that is created by rearranged projections of a selected two-dimensional image with various rotation angles. In this approach, the translation registration table may be created by rearranged projections of sub-voxel level two-dimensional images with various sub-voxel level parameters, and so it may be applied into a sub-voxel registration. Such an approach replaced the general multi-dimensional optimization procedure with a linear projection calculation and a finite cross-correlation with a registration table, thus the amount of computation is considerably reduced. The performance of this method was confirmed by simulation study different SNRs and applications to 2D and 3D actual functional MRI images.

Algorithms↗

PubMed2005

A particle swarm optimization algorithm for beam angle selection in intensity-modulated radiotherapy planning.

Automatic beam angle selection is an important but challenging problem for intensity-modulated radiation therapy (IMRT) planning. Though many efforts have been made, it is still not very satisfactory in clinical IMRT practice because of overextensive computation of the inverse problem. In this paper, a new technique named BASPSO (Beam Angle Selection with a Particle Swarm Optimization algorithm) is presented to improve the efficiency of the beam angle optimization problem. Originally developed as a tool for simulating social behaviour, the particle swarm optimization (PSO) algorithm is a relatively new population-based evolutionary optimization technique first introduced by Kennedy and Eberhart in 1995. In the proposed BASPSO, the beam angles are optimized using PSO by treating each beam configuration as a particle (individual), and the beam intensity maps for each beam configuration are optimized using the conjugate gradient (CG) algorithm. These two optimization processes are implemented iteratively. The performance of each individual is evaluated by a fitness value calculated with a physical objective function. A population of these individuals is evolved by cooperation and competition among the individuals themselves through generations. The optimization results of a simulated case with known optimal beam angles and two clinical cases (a prostate case and a head-and-neck case) show that PSO is valid and efficient and can speed up the beam angle optimization process. Furthermore, the performance comparisons based on the preliminary results indicate that, as a whole, the PSO-based algorithm seems to outperform, or at least compete with, the GA-based algorithm in computation time and robustness. In conclusion, the reported work suggested that the introduced PSO algorithm could act as a new promising solution to the beam angle optimization problem and potentially other optimization problems in IMRT, though further studies need to be investigated.

Algorithms↗

PubMed2005

A comparative study of different references for EEG spectral mapping: the issue of the neutral reference and the use of the infinity reference.

Based on EEG data recorded from 11 subjects with eyes open and the left mastoid (M) reference, three data sets were generated by re-referencing to the conventional linked mastoids (L), average (A) and the new 'infinity' (I) reference provided by the reference electrode standardization technique (REST, Yao 2001 Physiol. Meas. 22 693-711). The EEG power in the alpha frequency band with the four different references was calculated and compared with respect to the total energy and spatial amplitude weight centre (AWC) coordinates, to compare the effects of different references on power mapping in the frequency domain. Compared with the I reference, the AWCs of the EEG with the M reference show significant shifts to the right, frontal and superficial positions, the L reference significant shifts to frontal and superficial positions, and the A reference shifts the AWC significantly to a deeper position. Furthermore, the power maps of the M and L references have larger total power than the I reference, while that of the A reference has the smallest total power. These results confirm that different choices of reference electrodes result in systematic changes in the distribution of EEG frequency power, and in order to reduce the effect of such systematic shifts on the explanation of EEG mappings, a common reference is necessary for EEG research. We recommend the I reference for objective use in cross-laboratory studies and clinical practices, as it is far from all the other electrodes and can act as a neutral reference.

Adolescent↗

PubMed2005

A comparison of Gamma and Gaussian dynamic convolution models of the fMRI BOLD response.

Blood oxygenation level-dependent (BOLD) contrast-based functional magnetic resonance imaging (fMRI) has been widely utilized to detect brain neural activities and great efforts are now stressed on the hemodynamic processes of different brain regions activated by a stimulus. The focus of this paper is the comparison of Gamma and Gaussian dynamic convolution models of the fMRI BOLD response. The convolutions are between the perfusion function of the neural response to a stimulus and a Gaussian or Gamma function. The parameters of the two models are estimated by a nonlinear least-squares optimal algorithm for the fMRI data of eight subjects collected in a visual stimulus experiment. The results show that the Gaussian model is better than the Gamma model in fitting the data. The model parameters are different in the left and right occipital regions, which indicate that the dynamic processes seem different in various cerebral functional regions.

Algorithms↗

PubMed2005

Delay correlation subspace decomposition algorithm and its application in fMRI.

This paper reports a new delay subspace decomposition (DSD) algorithm. Instead of using the canonical zero-delay correlation matrix, the new DSD algorithm introduces a delay into the correlation matrix of the subspace decomposition to suppress noises in the data. The algorithm is applied to functional magnetic resonance imaging (fMRI) to detect the regions of focal activities in the brain. The efficiency is evaluated by comparing with independent component analysis and principal component analysis method of fMRI.

Algorithms↗

PubMed2005

[Applying exponent method of density to amend bone's edge of X-ray image].

Because of the difference in organic density, a simple and effective method for exponent restraint of active edge is applied to X-ray image of bone. And it is easy to use histogram method to get the active image of bone. At last, by associating it with Canny method, the edge of bone can be abstracted from a complex X-ray image.

Algorithms↗

PubMed2005

[Research progress in the technique of integrating multiple imaging modalities in the functional brain imaging].

In the last few years, brain science has exhibited an explosive growth in hemodynamic/metabolic data on brain function. In particular, PET and functional MRI provide excellent spatial resolution, but their temporal resolutions are severely limited by relatively slow responses of brain metabolism. By contrast, EEG and MEG are able to track modulations of current source activity at millisecond time scales, but suffer from poor spatial resolution. Hence, high-resolution spatiotemporal imaging of brain activity requires integration of information from multiple signal modalities. In this paper we discuss what is known about the physical and physiological basis of the imaging signals, suggest various approaches that have been proposed for integrating information across multiple modalities, and briefly analyze the future directions and remaining challenges in the field of multi-modality integration.

Brain↗

PubMed2005

[A method for the medical image registration based on the statistics samples averaging distribution theory].

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.

Algorithms↗

PubMed2005

[A 3D tomography technique based study on event-related potential in attention].

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.

Adult↗

PubMed2005

[Single visual-evoked potential estimation based on sparse decomposition].

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.

Evoked Potentials↗

PubMed2004

High-resolution electroencephalogram (EEG) mapping: scalp charge layer.

The neural electrical signal related to the human brain function is one of the tracks to understanding ourselves. Various electroencephalogram imaging techniques have been developed to reveal spatial information on neural activities in the brain from scalp recordings, such as Laplacian, equivalent source layer and potential. Physically, these methods may be classified into two categories: scalp surface or cortical surface based techniques. In this work, the focus is on the scalp surface based equivalent charge layer (ECL), with a comparison to the scalp potential with different references and scalp Laplacian (SL). The contents include theoretical analysis and numeric evaluation of simulated data and real alpha (8-12 Hz) data. The results confirm the fact that SL and ECL are of higher spatial resolution than various scalp potential maps, and for SL and ECL, SL is of higher resolution but more sensitive to noise.

Brain↗

PubMed2004

Automatic beam angle selection in IMRT planning using genetic algorithm.

The selection of suitable beam angles in external beam radiotherapy is at present generally based upon the experience of the human planner. The requirement to automatically select beam angles is particularly highlighted in intensity-modulated radiation therapy (IMRT), in which a smaller number of modulated beams is hoped to be used, in comparison with conformal radiotherapy. It has been proved by many researchers that the selection of suitable beam angles is most valuable for a plan with a small number of beams (< or = 5). In this paper an efficient method is presented to investigate how to improve the dose distributions by selecting suitable coplanar beam angles. In our automatic beam angle selection (ABAS) algorithm, the optimal coplanar beam angles correspond to the lowest objective function value of the dose distributions calculated using the intensity-modulated maps of this group of candidate beams. Due to the complexity of the problem and the large search space involved, the selection of beam angles and the optimization of intensity maps are treated as two separate processes and implemented iteratively. A genetic algorithm (GA) incorporated with an immunity operation is used to select suitable beam angles, and a conjugate gradient (CG) method is used to quickly optimize intensity maps for each selected beam combination based on a dose-based objective function. A pencil-beam-based three-dimensional (3D) full scatter convolution (FSC) algorithm is employed for the dose calculation. Two simulated cases with obvious optimal beam angles are used to verify the validity of the presented technique, and a more complicated case simulating a prostate tumour and two clinical cases are employed to test the efficiency of ABAS. The results show that ABAS is valid and efficient and can improve the dose distributions within a clinically acceptable computation time.

Algorithms↗