InfoFlowNet: A Multi-head Attention-based Self-supervised Learning Model with Surrogate Approach for Uncovering Brain Effective Connectivity

Deciphering brain network topology can enhance the depth of neuroscientific knowledge and facilitate the development of neural engineering methods. Effective connectivity, a measure of brain network dynamics, is particularly useful for investigating the directional influences among different brain regions. In this study, we introduce a novel brain causal inference model named InfoFlowNet, which leverages the self-attention mechanism to capture associations among electroencephalogram (EEG) time series. The proposed method estimates the magnitude of directional information flow (dIF) among EEG processes by measuring the loss of model inference resulting from the shuffling of the time order of the original time series. To evaluate the feasibility of InfoFlowNet, we conducted experiments using a synthetic time series and two EEG datasets. The results demonstrate that InfoFlowNet can extract time-varying causal relationships among processes, reflected in the fluctuation of dIF values. Compared with the Granger causality model and temporal causal discovery framework, InfoFlowNet can identify more significant causal edges underlying EEG processes while maintaining an acceptable computation time. Our work demonstrates the potential of InfoFlowNet for analyzing effective connectivity in EEG data. The findings highlight the importance of effective connectivity in understanding the complex dynamics of the brain network

Granger causal connectivity dissociates navigation networks that subserve allocentric and egocentric path integration

Studies on spatial navigation demonstrate a significant role of the retrosplenial complex (RSC) in the transformation of egocentric and allocentric information into complementary spatial reference frames (SRFs). The tight anatomical connections of the RSC with a wide range of other cortical regions processing spatial information support its vital role within the human navigation network. To better understand how different areas of the navigational network interact, we investigated the dynamic causal interactions of brain regions involved in solving a virtual navigation task. EEG signals were decomposed by independent component analysis (ICA) and subsequently examined for information flow between clusters of independent components (ICs) using direct short-time directed transfer function (sdDTF). The results revealed information flow between the anterior cingulate cortex and the left prefrontal cortex in the theta (4-7 Hz) frequency band and between the prefrontal, motor, parietal, and occipital cortices as well as the RSC in the alpha (8-13 Hz) frequency band. When participants prefered to use distinct reference frames (egocentric vs. allocentric) during navigation was considered, a dominant occipito-parieto-RSC network was identified in allocentric navigators. These results are in line with the assumption that the RSC, parietal, and occipital cortices are involved in transforming egocentric visual-spatial information into an allocentric reference frame. Moreover, the RSC demonstrated the strongest causal flow during changes in orientation, suggesting that this structure directly provides information on heading changes in humans

Molecular Imaging, Pharmacokinetics, and Dosimetry of 111In-AMBA in Human Prostate Tumor-Bearing Mice

Molecular imaging with promise of personalized medicine can provide patient-specific information noninvasively, thus enabling treatment to be tailored to the specific biological attributes of both the disease and the patient. This study was to investigate the characterization of DO3A-CH2CO-G-4-aminobenzoyl-Q-W-A-V-G-H-L-M-NH2 (AMBA) in vitro, MicroSPECT/CT imaging, and biological activities of 111In-AMBA in PC-3 prostate tumor-bearing SCID mice. The uptake of 111In-AMBA reached highest with 3.87 ± 0.65% ID/g at 8 h. MicroSPECT/CT imaging studies suggested that the uptake of 111In-AMBA was clearly visualized between 8 and 48 h postinjection. The distribution half-life (t1/2α) and the elimination half-life (t1/2β) of 111In-AMBA in mice were 1.53 h and 30.7 h, respectively. The Cmax and AUC of 111In-AMBA were 7.57% ID/g and 66.39 h∗% ID/g, respectively. The effective dose appeared to be 0.11 mSv/MBq−1. We demonstrated a good uptake of 111In-AMBA in the GRPR-overexpressed PC-3 tumor-bearing SCID mice. 111In-AMBA is a safe, potential molecular image-guided diagnostic agent for human GRPR-positive tumors, ranging from simple and straightforward biodistribution studies to improve the efficacy of combined modality anticancer therapy

Benefit analysis of the auto-verification system of intelligent inspection for microorganisms

In recent years, the automatic machine for microbial identification and antibiotic susceptibility tests has been introduced into the microbiology laboratory of our hospital, but there are still many steps that need manual operation. The purpose of this study was to establish an auto-verification system for bacterial naming to improve the turnaround time (TAT) and reduce the burden on clinical laboratory technologists. After the basic interpretation of the gram staining results of microorganisms, the appearance of strain growth, etc., the 9 rules were formulated by the laboratory technologists specialized in microbiology for auto-verification of bacterial naming. The results showed that among 70,044 reports, the average pass rate of auto-verification was 68.2%, and the reason for the failure of auto-verification was further evaluated. It was found that the main causes reason the inconsistency between identification results and strain appearance rationality, the normal flora in the respiratory tract and urine that was identified, the identification limitation of the mass spectrometer, and so on. The average TAT for the preliminary report of bacterial naming was 35.2 h before, which was reduced to 31.9 h after auto-verification. In summary, after auto-verification, the laboratory could replace nearly 2/3 of manual verification and issuance of reports, reducing the daily workload of medical laboratory technologists by about 2 h. Moreover, the TAT on the preliminary identification report was reduced by 3.3 h on average, which could provide treatment evidence for clinicians in advance

Cerebro-Cerebellar Pathways for Verbal Working Memory

The current study examined the structural and functional connectivity of the cerebro-cerebellar network of verbal working memory as proposed by Chen and Desmond (2005a). Diffusion spectrum imaging was employed to establish structural connectivity between cerebro-cerebellar regions co-activated during a verbal working memory task. The inferior frontal gyrus, inferior parietal lobule, pons, thalamus, superior cerebellum and inferior cerebellum were used as regions of interest to reconstruct and segment the contralateral white matter cerebro-cerebellar circuitry. The segmented pathways were examined further to establish the relationship between structural and effective connectivity as well as the relationship between structural connectivity and verbal working memory performance. No direct relationship between structural and effective connectivity was found but the results demonstrated that structural connectivity is indirectly related to effective connectivity as DCM models that resembled more closely with underlying white matter pathways had a higher degree of model inference confidence. Additionally, it was demonstrated that the structural connectivity of the ponto-cerebellar tract was associated with individual differences in response time for verbal working memory. The findings of the study contribute to further our understanding of the relationship between structural and functional connectivity and the impact of variability in verbal working memory performance

Emulsified Nanoparticles Containing Inactivated Influenza Virus and CpG Oligodeoxynucleotides Critically Influences the Host Immune Responses in Mice

Antigen sparing and cross-protective immunity are regarded as crucial in pandemic influenza vaccine development. Both targets can be achieved by adjuvantation strategy to elicit a robust and broadened immune response. We assessed the immunogenicity of an inactivated H5N1 whole-virion vaccine (A/Vietnam/1194/2004 NIBRG-14, clade 1) formulated with emulsified nanoparticles and investigated whether it can induce cross-clade protecting immunity.After formulation with PELC, a proprietary water-in-oil-in-water nanoemulsion comprising of bioresorbable polymer/Span(R)85/squalene, inactivated virus was intramuscularly administered to mice in either one-dose or two-dose schedule. We found that the antigen-specific serum antibody responses elicited after two doses of non-adjuvanted vaccine were lower than those observed after a single dose of adjuvanted vaccine, PELC and the conventional alum adjuvant as well. Moreover, 5 microg HA of PELC-formulated inactivated virus were capable of inducing higher antibodies than those obtained from alum-adjuvanted vaccine. In single-dose study, we found that encapsulating inactivated virus into emulsified PELC nanoparticles could induce better antibody responses than those formulated with PELC-adsorbed vaccine. However, the potency was rather reduced when the inactivated virus and CpG (an immunostimulatory oligodeoxynucleotide containing unmethylated cytosine-guanosine motifs) were co-encapsulated within the emulsion. Finally, the mice who received PELC/CpG(adsorption)-vaccine could easily and quickly reach 100% of seroprotection against a homologous virus strain and effective cross-protection against a heterologous virus strain (A/Whooper swan/Mongolia/244/2005, clade 2.2).Encapsulating inactivated H5N1 influenza virus and CpG into emulsified nanoparticles critically influences the humoral responses against pandemic influenza. These results demonstrated that the use of PELC could be as antigen-sparing in preparation for a potential shortage of prophylactic vaccines against local infectious diseases, in particular pandemic influenza. Moreover, the cross-clade neutralizing antibody responses data verify the potential of such adjuvanted H5N1 candidate vaccine as an effective tool in pre-pandemic preparedness