Complex of global functional network as the core of consciousness.

Finding the neural basis of consciousness is challenging, and the distribution location of the core of consciousness remains inconclusive. Integrated information theory (IIT) argues that the posterior part of the brain is the hot zone of consciousness, especially phenological consciousness. The IIT has proposed a "main complex", a set of elements determined such that the information loss in a hierarchical partition approach is the largest among those of any other supersets and subsets, as the core of consciousness in a dynamic system. This approach may be applicable not only to phenomenal but also to access-consciousness. This study estimated the main complex of brain dynamics using functional magnetic resonance imaging in Human Connectome Project (HCP) and sleep datasets. The complex analyses revealed the common networks across various tasks and rest-state in HCP, composed of executive control, salience, and dorsal/ventral attention networks. The set of networks of the main complex was maintained during sleep. However, compared with the wakefulness stage, the amount of information of these networks and the default mode network, was reduced for the hypnagogic stage. The global interconnected structure composed of major functional networks can comprise the core of consciousness.

Neural substrates of brand equity: applying a quantitative meta-analytical method for neuroimage studies.

Although the concept of brand equity has been investigated using various approaches, a comprehensive neural basis for brand equity remains unclear. The default mode network (DMN) as a mental process might influence brand equity related consumers' decision-making, as reported in the marketing literature. While studies on the overlapping regions between the DMN and value-based decision-making related brain regions have been reported in neuroscience literature, relationships between the DMN and a neural mechanism of brand equity have not been clarified. The aim of our study is to identify neural substrates of brand equity and examine brand equity-related mental processes by comparing them to the DMN. To determine the neural substrates of brand equity, we first carried out the activation likelihood estimation (ALE) meta-analysis. We examined 26 studies using branded objects as experimental stimuli for the ALE. Next, we set the output regions from ALE as the region of interest for meta-analytic connectivity modeling (MACM). Further, we compared the brand equity-related brain network (BE-RBN) revealed by the MACM with the DMN. We confirmed that the BE-RBN brain regions overlap with the medial temporal lobule (MTL) sub-system, a module composed of the DMN but excluding the retrosplenial cortex. Further, we discovered that several brain regions apart from the DMN are also distinctive BE-RBN brain regions (i.e., the insula, the inferior frontal gyrus, amygdala, ventral striatum, parietal region). We decoded the BE-RBN brain regions using the BrandMap module. The decoded results revealed that the brand equity-related mental processes are complex constructs integrated via multiple mental processes such as self-referential, reward, emotional, memory, and sensorimotor processing. Our study demonstrated that the DMN alone is insufficient to engage in brand equity-related mental processes. Therefore, marketers are required to make strategic plans to integrate the five consumer's multiple mental processes while building brand equity.

Varying the Directionality of Protein Catalysts for Aldol and Retro-Aldol Reactions.

Natural aldolase enzymes and created retro-aldolase protein catalysts often catalyze both aldol and retro-aldol reactions depending on the concentrations of the reactants and the products. Here, we report that the directionality of protein catalysts can be altered by replacing one amino acid. The protein catalyst derived from a scaffold of a previously reported retro-aldolase catalyst, catalyzed aldol reactions more efficiently than the previously reported retro-aldolase catalyst. The retro-aldolase catalyst efficiently catalyzed the retro-aldol reaction but was less efficient in catalyzing the aldol reaction. The results indicate that protein catalysts with varying levels of directionality in usually reversibly catalyzed aldol and retro-aldol reactions can be generated from the same protein scaffold.

Extended Invariant Information Clustering Is Effective for Leave-One-Site-Out Cross-Validation in Resting State Functional Connectivity Modeling.

Herein, we propose a new deep neural network model based on invariant information clustering (IIC), proposed by Ji et al., to improve the modeling performance of the leave-one-site-out cross-validation (LOSO-CV) for a multi-source dataset. Our Extended IIC (EIIC) is a type of contrastive learning; however, unlike the original IIC, it is characterized by transfer learning with labeled data pairs, but without the need for a data augmentation technique. Each site in LOSO-CV is left out in turn from the remaining sites used for training and receives a value for modeling evaluation. We applied the EIIC to the resting state functional connectivity magnetic resonance imaging dataset of the Autism Brain Imaging Data Exchange. The challenging nature of brain analysis for autism spectrum disorder (ASD) can be attributed to the variability of subjects, particularly the rapid change in the neural system of children as the target ASD age group. However, EIIC demonstrated higher LOSO-CV classification accuracy for the majority of scanning locations than previously used methods. Particularly, with the adjustment of a mini-batch size, EIIC outperformed other classifiers with an accuracy >0.8 for the sites with highest mean age of the subjects. Considering its effectiveness, our proposed method might be promising for harmonization in other domains, owing to its simplicity and intrinsic flexibility.

Task-induced brain functional connectivity as a representation of schema for mediating unsupervised and supervised learning dynamics in language acquisition.

INTRODUCTION: Based on the schema theory advanced by Rumelhart and Norman, we shed light on the individual variability in brain dynamics induced by hybridization of learning methodologies, particularly alternating unsupervised learning and supervised learning in language acquisition. The concept of "schema" implies a latent knowledge structure that a learner holds and updates as intrinsic to his or her cognitive space for guiding the processing of newly arriving information. METHODS: We replicated the cognitive experiment of Onnis and Thiessen on implicit statistical learning ability in language acquisition but included additional factors of prosodic variables and explicit supervised learning. Functional magnetic resonance imaging was performed to identify the functional network connections for schema updating by alternately using unsupervised and supervised artificial grammar learning tasks to segment potential words. RESULTS: Regardless of the quality of task performance, the default mode network represented the first stage of spontaneous unsupervised learning, and the wrap-up accomplishment for successful subjects of the whole hybrid learning in concurrence with the task-related auditory language networks. Furthermore, subjects who could easily "tune" the schema for recording a high task precision rate resorted even at an early stage to a self-supervised learning, or "superlearning," as a set of different learning mechanisms that act in synergy to trigger widespread neuro-transformation with a focus on the cerebellum. CONCLUSIONS: Investigation of the brain dynamics revealed by functional connectivity imaging analysis was able to differentiate the synchronized neural responses with respect to learning methods and the order effect that affects hybrid learning.

Evaluation of Task fMRI Decoding With Deep Learning on a Small Sample Dataset.

Recently, several deep learning methods have been applied to decoding in task-related fMRI, and their advantages have been exploited in a variety of ways. However, this paradigm is sometimes problematic, due to the difficulty of applying deep learning to high-dimensional data and small sample size conditions. The difficulties in gathering a large amount of data to develop predictive machine learning models with multiple layers from fMRI experiments with complicated designs and tasks are well-recognized. Group-level, multi-voxel pattern analysis with small sample sizes results in low statistical power and large accuracy evaluation errors; failure in such instances is ascribed to the individual variability that risks information leakage, a particular issue when dealing with a limited number of subjects. In this study, using a small-size fMRI dataset evaluating bilingual language switch in a property generation task, we evaluated the relative fit of different deep learning models, incorporating moderate split methods to control the amount of information leakage. Our results indicated that using the session shuffle split as the data folding method, along with the multichannel 2D convolutional neural network (M2DCNN) classifier, recorded the best authentic classification accuracy, which outperformed the efficiency of 3D convolutional neural network (3DCNN). In this manuscript, we discuss the tolerability of within-subject or within-session information leakage, of which the impact is generally considered small but complex and essentially unknown; this requires clarification in future studies.

Neural Substrates of Brand Love: An Activation Likelihood Estimation Meta-Analysis of Functional Neuroimaging Studies.

Brand love is a critical concept for building a relationship between brands and consumers because falling in love with a brand can lead to strong brand loyalty. Despite the importance of marketing strategies, however, the underlying neural mechanisms of brand love remain unclear. The present study used an activation likelihood estimation meta-analysis method to investigate the neural correlates of brand love and compared it with those of maternal and romantic love. In total, 47 experiments investigating brand, maternal, and romantic love were examined, and the neural systems involved for the three loves were compared and contrasted. Results revealed that the putamen and insula were commonly activated in the three loves. Moreover, activated brain regions in brand love were detected in the dorsal striatum. Activated regions for maternal love were detected in the cortical area and globus pallidus and were associated with pair bonds, empathy, and altruism. Finally, those for romantic love were detected in the hedonic, strong passionate, and intimate-related regions, such as the nucleus accumbens and ventral tegmental area. Thus, the common regions of brain activation between brand and romantic love were in the dorsal striatum. Meanwhile, no common activated regions were observed between brand and maternal love except for the regions shared among the three love types. Although brand love shared little with the two interpersonal (maternal and romantic) loves and relatively resembled aspects of romantic rather than maternal love, our results demonstrated that brand love may have intrinsically different dispositions from the two interpersonal loves.

Using Graph Components Derived from an Associative Concept Dictionary to Predict fMRI Neural Activation Patterns that Represent the Meaning of Nouns.

In this study, we introduce an original distance definition for graphs, called the Markov-inverse-F measure (MiF). This measure enables the integration of classical graph theory indices with new knowledge pertaining to structural feature extraction from semantic networks. MiF improves the conventional Jaccard and/or Simpson indices, and reconciles both the geodesic information (random walk) and co-occurrence adjustment (degree balance and distribution). We measure the effectiveness of graph-based coefficients through the application of linguistic graph information for a neural activity recorded during conceptual processing in the human brain. Specifically, the MiF distance is computed between each of the nouns used in a previous neural experiment and each of the in-between words in a subgraph derived from the Edinburgh Word Association Thesaurus of English. From the MiF-based information matrix, a machine learning model can accurately obtain a scalar parameter that specifies the degree to which each voxel in (the MRI image of) the brain is activated by each word or each principal component of the intermediate semantic features. Furthermore, correlating the voxel information with the MiF-based principal components, a new computational neurolinguistics model with a network connectivity paradigm is created. This allows two dimensions of context space to be incorporated with both semantic and neural distributional representations.

Neural basis of language switching in the brain: fMRI evidence from Korean-Chinese early bilinguals.

Using fMRI, we conducted two types of property generation task that involved language switching, with early bilingual speakers of Korean and Chinese. The first is a more conventional task in which a single language (L1 or L2) was used within each trial, but switched randomly from trial to trial. The other consists of a novel experimental design where language switching happens within each trial, alternating in the direction of the L1/L2 translation required. Our findings support a recently introduced cognitive model, the 'hodological' view of language switching proposed by Moritz-Gasser and Duffau. The nodes of a distributed neural network that this model proposes are consistent with the informative regions that we extracted in this study, using both GLM methods and Multivariate Pattern Analyses: the supplementary motor area, caudate, supramarginal gyrus and fusiform gyrus and other cortical areas.

Decoding semantics across fMRI sessions with different stimulus modalities: a practical MVPA study.

Both embodied and symbolic accounts of conceptual organization would predict partial sharing and partial differentiation between the neural activations seen for concepts activated via different stimulus modalities. But cross-participant and cross-session variability in BOLD activity patterns makes analyses of such patterns with MVPA methods challenging. Here, we examine the effect of cross-modal and individual variation on the machine learning analysis of fMRI data recorded during a word property generation task. We present the same set of living and non-living concepts (land-mammals, or work tools) to a cohort of Japanese participants in two sessions: the first using auditory presentation of spoken words; the second using visual presentation of words written in Japanese characters. Classification accuracies confirmed that these semantic categories could be detected in single trials, with within-session predictive accuracies of 80-90%. However cross-session prediction (learning from auditory-task data to classify data from the written-word-task, or vice versa) suffered from a performance penalty, achieving 65-75% (still individually significant at p « 0.05). We carried out several follow-on analyses to investigate the reason for this shortfall, concluding that distributional differences in neither time nor space alone could account for it. Rather, combined spatio-temporal patterns of activity need to be identified for successful cross-session learning, and this suggests that feature selection strategies could be modified to take advantage of this.

Development of an immunochromatographic strip for simple detection of penicillin-binding protein 2'.

Infections with methicillin-resistant Staphylococcus aureus (MRSA) and methicillin-resistant coagulase-negative Staphylococcus (MR-CNS) are a serious problem in hospitals because these bacteria produce penicillin-binding protein 2' (PBP2' or PBP2a), which shows low affinity to ß-lactam antibiotics. Furthermore, the bacteria show resistance to a variety of antibiotics. Identification of these pathogens has been carried out mainly by the oxacillin susceptibility test, which takes several days to produce a reliable result. We developed a simple immunochromatographic test that enabled the detection of PBP2' within about 20 min. Anti-PBP2' monoclonal antibodies were produced by a hybridoma of recombinant PBP2' (rPBP2')-immunized mouse spleen cells and myeloma cells. The monoclonal antibodies reacted only with PBP2' of whole-cell extracts and showed no detectable cross-reactivity with extracts from other bacterial species tested so far. One of the monoclonal antibodies was conjugated with gold colloid particles, which react with PBP2', and another antibody was immobilized on a nitrocellulose membrane, which captures the PBP2'-gold colloid particle complex on a nitrocellulose strip. This strip was able to detect 1.0 ng of rPBP2' or 2.8 × 10(5) to 1.7 × 10(7) CFU of MRSA cells. The cross-reactivity test using 15 bacterial species and a Candida albicans strain showed no detectable false-positive results. The accuracy of this method in the detection of MRSA and MR-CNS appeared to be 100%, compared with the results obtained by PCR amplification of the PBP2' gene, mecA. This newly developed immunochromatographic test can be used for simple and accurate detection of PBP2'-producing cells in clinical laboratories.

Trends of beta-lactam antibiotic susceptibility in blood-borne methicillin-resistant Staphylococcus aureus (MRSA) and their linkage to the staphylococcal cassette chromosome mec (SCCmec) type.

We investigated trends of beta-lactam antibiotic susceptibility in a total of 218 strains of blood-borne methicillin-resistant Staphylococcus aureus (MRSA) isolated from 1978 through 2002 at a middle-size geriatric hospital in Tokyo; the strains were classified by the MRSA marker, staphylococcal cassette chromosome mec (SCCmec). The minimum growth inhibitory concentration (MIC) of cloxacillin at which 50% of the strains were inhibited (MIC50) was 2 microg/ml in the strains isolated in 1978-1984 and 32 to 64 microg/ml in the strains isolated subsequently. Similarly, the MIC50 values of cefazolin and imipenem in the 1978-1984 isolates were 16 and

Trends in the gentamicin and arbekacin susceptibility of methicillin-resistant Staphylococcus aureus and the genes encoding aminoglycoside-modifying enzymes.

It is generally accepted that methicillin-resistant Staphylococcus aureus (MRSA) is also resistant to aminoglycoside antibiotics. We investigated trends of gentamicin and arbekacin susceptibilities and the prevalence of the genes encoding aminoglycoside-modifying enzymes (AMEs) for a total of 218 strains of MRSA isolated from blood specimens obtained from 1978 through 2002 in one hospital. The minimum inhibitory concentrations of gentamicin at which 50% of the strains were inhibited (MIC(50)) were > or =128 and 32 microg/ml for isolates obtained from 1978 to 1984 and from 1985 to 1989, respectively, and 0.5 microg/ml for isolates obtained from 1990 to 2002. The MIC(90) of gentamicin was consistently > or =128 microg/ml. Investigation of the occurrence of AME revealed that the MIC(50) of gentamicin was highly correlated with the presence of aac(6')/aph(2'') encoding aminoglycoside acetyl/phosphotransferase. The MIC(50) of arbekacin was 2 microg/ml for strains isolated in 1978-1984 and

Multidrug transporter MexB of Pseudomonas aeruginosa: overexpression, purification, and initial structural characterization.

Structural and functional characterization of the multidrug transporter, MexB, of Pseudomonas aeruginosa is significantly restricted due to a low yield of approximately 0.1 mg/L of culture from natural sources. To facilitate structural studies of this medically important transporter protein, we developed a large-scale system for expression of the genetically engineered recombinant, MexB, in the Escherichia coli cell. Using the system, the eventual yield of MexB attained was about 10mg/L of culture. The optimized purification protocol in the presence of dodecyl beta-D-maltoside allowed isolation of highly homogeneous MexB. The oligomeric state of the protein in detergent solution has been characterized to verify that the native state of the purified protein has been preserved. The molecular mass of the protein-detergent complex was found to be 380-450kDa. The MexB-dodecyl beta-d-maltoside mass ratio was determined to be 1.8 +/- 0.05. Taking into account the monomeric MexB molecular mass deduced from its amino acid sequence (112.8 kDa), we concluded that the purified MexB exists as the homotrimer in the surfactant solution. Circular dichroism analysis of MexB showed dominance of the alpha-helix structures. High yield, homogeneity, and stability of MexB position it as a good candidate for structural and functional characterization.

Forceful large-scale expression of "problematic" membrane proteins.

We developed an Escherichia coli expression system for overproduction of a highly toxic membrane protein that is impossible to overexpress by traditionally used approaches. The method is based on combination of the genetic modifications of a bicistronic expression plasmid, stabilization of a synthesized protein, and selection of a compatible expression host. This enabled us to enhance the expression level of a toxic membrane protein 30-50 times compared with expression in the native state and to obtain 3-5mg of a highly purified functionally active protein per liter of culture. We describe the method for the amplified expression of membrane proteins, using the Pseudomonas aeruginosa multidrug resistance protein, MexY, as an example. The amplified MexY was correctly folded in the cytoplasmic membrane of the E. coli without forming inclusion bodies. This method can be applicable to the large-scale expression of the other problematic membrane proteins that are otherwise extremely difficult to overproduce.

Preliminary crystallographic analysis of the antibiotic discharge outer membrane lipoprotein OprM of Pseudomonas aeruginosa with an exceptionally long unit cell and complex lattice structure.

Crystals of the drug-discharge outer membrane protein OprM (MW = 50.9 kDa) of the MexAB-OprM multidrug transporter of Pseudomonas aeruginosa have been grown at 293 K in the presence of 2-methyl-2,4-propanediol and a combination of surfactants. The crystal belonged to space group R32, with unit-cell parameters a = b = 85.43, c = 1044.3 A. Diffraction data for OprM were obtained using the undulator synchrotron-radiation beamline at SPring-8 (BL44XU, Osaka University), which allowed an extra-long specimen-to-detector distance with a wide detector area. The crystal diffracted to 2.56 A resolution using 0.9 A X-rays from the synchrotron-radiation source. A heavy-atom derivative for isomorphous replacement phasing was obtained using iridium chloride.

Crystal structure of the drug discharge outer membrane protein, OprM, of Pseudomonas aeruginosa: dual modes of membrane anchoring and occluded cavity end.

The OprM lipoprotein of Pseudomonas aeruginosa is a member of the MexAB-OprM xenobiotic-antibiotic transporter subunits that is assumed to serve as the drug discharge duct across the outer membrane. The channel structure must differ from that of the porin-type open pore because the protein facilitates the exit of antibiotics but not the entry. For better understanding of the structure-function linkage of this important pump subunit, we studied the x-ray crystallographic structure of OprM at the 2.56-angstroms resolution. The overall structure exhibited trimeric assembly of the OprM monomer that consisted mainly of two domains: the membrane-anchoring beta-barrel and the cavity-forming alpha-barrel. OprM anchors the outer membrane by two modes of membrane insertions. One is via the covalently attached NH(2)-terminal fatty acids and the other is the beta-barrel structure consensus on the outer membrane-spanning proteins. The beta-barrel had a pore opening with a diameter of about 6-8 angstroms, which is not large enough to accommodate the exit of any antibiotics. The periplasmic alpha-barrel was about 100 angstroms long formed mainly by a bundle of alpha-helices that formed a solvent-filled cavity of about 25,000 angstroms(3). The proximal end of the cavity was tightly sealed, thereby not permitting the entry of any molecule. The result of this structure was that the resting state of OprM had a small outer membrane pore and a tightly closed periplasmic end, which sounds plausible because the protein should not allow free access of antibiotics. However, these observations raised another unsolved problem about the mechanism of opening of the OprM cavity ends. The crystal structure offers possible mechanisms of pore opening and pump assembly.

Role of the membrane fusion protein in the assembly of resistance-nodulation-cell division multidrug efflux pump in Pseudomonas aeruginosa.

The tripartite xenobiotic-antibiotic transporter of Pseudomonas aeruginosa consists of the inner membrane transporter (e.g., MexB, MexY), the periplasmic membrane-fusion-protein (e.g., MexA, MexX), and the outer membrane channel protein (e.g., OprM). These subunits were assumed to assemble into a transporter unit during export of the substrates. However, subunit interaction and their specificity in native form remained to be elucidated. To address these important questions, we analyzed the role of the individual subunits for the assembly of MexAB-OprM by pull-down assay tagging only one of the subunits. We found stable MexA-MexB-OprM complex without chemical cross-linking that withstand all purification procedures. Results of bi-partite interactions analysis showed tight association between MexA and OprM in the absence of MexB, whereas the expression systems lacking MexA failed to co-purify MexB or OprM. None of the heterologous subunit combinations such as MexA+MexY(his)+OprM and MexX+MexB(his)+OprM showed interaction. These results implied that the membrane fusion protein is central to the tripartite xenobiotic transporter assembly.

Crystal structure of the membrane fusion protein, MexA, of the multidrug transporter in Pseudomonas aeruginosa.

The MexAB-OprM efflux pump of Pseudomonas aeruginosa is central to multidrug resistance of this organism, which infects immunocompromised hospital patients. The MexA, MexB, and OprM subunits were assumed to function as the membrane fusion protein, the body of the transporter, and the outer membrane channel protein, respectively. For better understanding of this important xenobiotic transporter, we show the x-ray crystallographic structure of MexA at a resolution of 2.40 A. The global MexA structure showed unforeseen new features with a spiral assembly of six and seven protomers that were joined together at one end by a pseudo 2-fold image. The protomer showed a new protein structure with a tandem arrangement consisting of at least three domains and presumably one more. The rod domain had a long hairpin of twisted coiled-coil that extended to one end. The second domain adjacent to the rod alpha-helical domain was globular and constructed by a cluster of eight short beta-sheets. The third domain located distal to the alpha-helical rod was globular and composed of seven short beta-sheets and one short alpha-helix. The 13-mer was shaped like a woven rattan cylinder with a large internal tubular space and widely opened flared ends. The 6-mer and 7-mer had a funnel-like structure consisting of a tubular rod at one side and a widely opened flared funnel top at the other side. Based on these results, we constructed a model of the MexAB-OprM pump assembly. The three pairs of MexA dimers interacted with the periplasmic alpha-barrel domain of OprM via the alpha-helical hairpin, the second domain interacted with both MexB and OprM at their contact site, and the third and disordered domains probably interacted with the distal domain of MexB. In this fashion, the MexA subunit connected MexB and OprM, indicating that MexA is the membrane bridge protein.

Mutations affecting DNA-binding activity of the MexR repressor of mexR-mexA-mexB-oprM operon expression.

We have isolated 25 MexR mutants that retained their dimerizing ability but were unable to bind mexOP DNA. Surprisingly, 20 mutations were located in the hydrophobic core region at alpha4, W1, alpha2, alpha3, and beta2, and only 3 were in positively charged residues. These results verified that DNA binding is mediated by distinct regions of MexR and showed the importance of the hydrophobic core region of the DNA-binding domain.