The effect and efficiency of attentional networks and the brain electrophysiology.

The attention networks test (ANT) is frequently utilized to evaluate executive, alerting, and orienting attentional components. Additionally, it serves as an activation task in neuroimaging studies. This study aimed to examine the relationship between attention networks and brain electrophysiology. The study enrolled 40 right-handed male students (age = 20.8 ± 1.3 years) who underwent the revised attention network test, while their electroencephalogram signals were recorded. The study aimed to explore the effects of attention networks and their efficiencies on brain electrophysiology. The results indicated that the P3 amplitude was modulated by the conflict effect in the central (p-value = 0.014) and parietal (p-value = 0.002) regions. The orienting component significantly influenced P1 and N1 latencies in the parietal and parieto-occipital regions (p-values < 0.006), as well as P1 and N1 amplitude in the parieto-occipital region (p-values = 0.017 and 0.011). The alerting component significantly affected P1 latency and amplitude in the parietal and parieto-occipital regions, respectively (p-value = 0.02). Furthermore, N1 amplitude and the time interval between P1 and N1 were significantly correlated with the efficiency of alerting and orienting networks. In terms of connectivity, the coherence of theta and alpha bands significantly decreased in the incongruent condition compared to the congruent condition. Additionally, the effects of attention networks on event-related spectral perturbation were observed. The study revealed the influence of attention networks on various aspects of brain electrophysiology. Specifically, the alerting score correlated with the amplitude of the N1 component in the double-cue and no-cue conditions in the parieto-occipital region, while the orienting score in the same region correlated with the N1 amplitude in the valid cue condition and the difference in N1 amplitude between the valid cue and double-cue conditions. Overall, empirical evidence suggests that attention networks not only impact the amplitudes of electrophysiological activities but also influence their time course.

Histopathological graded liver lesions: what role does the IVIM analysis method have?

PURPOSE: This study aims to investigate three different image processing methods on quantitative parameters of IVIM sequence, as well as apparent diffusion coefficients and simple perfusion fractions, for benign and malignant liver tumors. MATERIALS AND METHODS: IVIM images with 8 b-values (0-1000 s/mm2) and 1.5 T MRI scanner in 16 patients and 3 healthy people were obtained. Next, the regions of interest were selected for malignant, benign, and healthy liver regions (50, 56, and 12, respectively). Then, the bi-exponential equation of the IVIM technique was fitted with two segmented fitting methods as well as one full fitting method (three methods in total). Using the segmented fitting method, diffusion coefficient (D) is fixed with a mono-exponential equation with b-values that are greater than 200 s/mm2. The perfusion fraction (f) can then be calculated by extrapolating, as the first method, or fitting simultaneously with the pseudo-diffusion coefficient (D*) as the second method. In the full fitting method, as the third method, all IVIM parameters were obtained simultaneously. The mean values of parameters from different methods were compared in different grades of lesions. RESULTS: Our results indicate that the image processing method can change statistical comparisons between different groups for each parameter. The D value is the only quantity in this technique that does not depend on the fitting process and can be used as an indicator of comparison between studies (P < 0.05). The most effective method to distinguish liver lesions is the extrapolated f method (first method). This method created a significant difference (P < 0.05) between the perfusion parameters between benign and malignant lesions. CONCLUSION: Using extrapolated f is the most effective method of distinguishing liver lesions using IVIM parameters. The comparison between groups does not depend on the fitting method only for parameter D.

Volume-based and Surface-Based Methods in Autism Compared with Healthy Controls Are Free surfer and CAT12 in Agreement?

Objectives: Autism Spectrum Disorder (ASD) encompasses a range of neurodevelopmental disorders, and early detection is crucial. This study aims to identify the Regions of Interest (ROIs) with significant differences between healthy controls and individuals with autism, as well as evaluate the agreement between FreeSurfer 6 (FS6) and Computational Anatomy Toolbox (CAT12) methods. Materials & Methods: Surface-based and volume-based features were extracted from FS software and CAT12 toolbox for Statistical Parametric Mapping (SPM) software to estimate ROI-wise biomarkers. These biomarkers were compared between 18 males Typically Developing Controls (TDCs) and 40 male subjects with ASD to assess group differences for each method. Finally, agreement and regression analyses were performed between the two methods for TDCs and ASD groups. Results: Both methods revealed ROIs with significant differences for each parameter. The Analysis of Covariance (ANCOVA) showed that both TDCs and ASD groups indicated a significant relationship between the two methods (p<0.001). The R2 values for TDCs and ASD groups were 0.692 and 0.680, respectively, demonstrating a moderate correlation between CAT12 and FS6. Bland-Altman graphs showed a moderate level of agreement between the two methods. Conclusion: The moderate correlation and agreement between CAT12 and FS6 suggest that while some consistency is observed in the results, CAT12 is not a superior substitute for FS6 software. Further research is needed to identify a potential replacement for this method.

The effect of considering eye movement time in evaluating the efficiency of attentional networks.

The attention network test (ANT) is a tool for assessing the executive, alerting, and orienting components of attention. However, conflicting findings exist regarding the nature and correlation between attention networks. This study aims to investigate the influence of eye movement time on the assessment of attention network efficiency. Forty male students, with an average age of 20.8 ± 1.3 years, participated in the study. The revised attention network test was conducted concurrently with the recording of the electrooculogram signal. The electrooculogram signal was used to estimate eye placement time on target stimuli. Considering eye movement time for calculating the score of each network was proposed as a novel method. The study explored the nature of attention networks and their relationships, and revealed significant effects for attention networks with and without considering the eye movement time. Additionally, a significant correlation is observed between the alerting and orienting networks. However, no significant correlation is found between attention networks using the proposed method. Considering eye movement time alters the assessment of attention network efficiency and modifies the correlation among attention networks.

Impaired white matter integrity in infants and young children with autism spectrum disorder: What evidence does diffusion tensor imaging provide?

BACKGROUND: Abnormal functional connections are associated with impaired white matter tract integrity in the brain. Diffusion tensor imaging (DTI) is a promising method for evaluating white matter integrity in infants and young children. This work aims to shed light on the location and nature of the decrease in white matter integrity. METHODS: Here, the results of 19 studies have been presented that investigated white matter integrity in infants and young children (6 months to 12 years) with autism using diffusion tensor imaging. RESULTS: In most of the reviewed studies, an increase in Fractional Anisotropy (FA) and a decrease in Radial Diffusivity (RD) were reported in Corpus Callosum (CC), Uncinate Fasciculus (UF), Cingulum (Cg), Inferior Longitudinal Fasciculus (ILF), and Superior Longitudinal Fasciculus (SLF), and in the Inferior Fronto-Occipital Fasciculus (IFOF) tract, a decrease in FA and an increase in RD were reported. CONCLUSION: In the reviewed articles, except for one study, the diffusion indices were different compared to the control group.

Presentation of a matrix-based method to calculate dose distribution in brachytherapy with photon-emitting sources.

AIM OF STUDY: The report of the task group number 43(TG-43) of AAPM has been known as the most common method to obtain the dose distribution around brachytherapy sources. The error caused by independent obtaining and rounding and combinational error caused by algebraic operations of each TG-43 dosimetry parameters increase the total error in the calculation of the dose distribution around the brachytherapy sources. The aim of the present study is to present and evaluate a matrix-based approach for simplifying and reducing calculation errors. MATERIALS AND METHODS: In this study, the simulation method with MCNPX code was used to obtain the dose distribution. Four sources were simulated, and the dose matrix around these sources was obtained. Finally, the dose distribution obtained from the matrix-based method was compared with the dose distribution obtained from the method of TG-43 report. RESULTS: There is little difference between the values obtained from the two methods in some points. Absolute mean differences between the values obtained by these two methods were 1.4% for the 60Co, 3.52% for the 137Cs, 2.67% for the 192Ir, and 2.42% for the 103Pd sources. The advantage of the matrix-based method is its simple computing process and less computation time. CONCLUSION: Considering that the comparison of brachytherapy sources is not raised in calculations of treatment planning systems and also considering the more uncertainty in the calculation of the dose distribution in TG-43 method, it is recommended that dose distribution obtained from matrix-based method be used as input for treatment planning systems.