Efficiency at Rest: Magnetoencephalographic Resting-State Connectivity and Individual Differences in Verbal Working Memory

Inter-individual differences in cognitive performance are based on an efficient use of task-related brain resources. However, little is known yet on how these differences might be reflected on resting-state brain networks. Here we used Magnetoencephalography resting-state recordings to assess the relationship between a behavioral measurement of verbal working memory and functional connectivity as measured through Mutual Information. We studied theta (4?8 Hz), low alpha (8?10 Hz), high alpha (10?13 Hz), low beta (13?18 Hz) and high beta (18?30 Hz) frequency bands. A higher verbal working memory capacity was associated with a lower mutual information in the low alpha band, prominently among right-anterior and left-lateral sensors. The results suggest that an efficient brain organization in the domain of verbal working memory might be related to a lower resting-state functional connectivity across large-scale brain networks possibly involving right prefrontal and left perisylvian areas.

Text categorization methods for automatic estimation of verbal intelligence

In this paper we investigate whether conventional text categorization methods may suffice to infer different verbal intelligence levels. This research goal relies on the hypothesis that the vocabulary that speakers make use of reflects their verbal intelligence levels. Automatic verbal intelligence estimation of users in a spoken language dialog system may be useful when defining an optimal dialog strategy by improving its adaptation capabilities. The work is based on a corpus containing descriptions (i.e. monologs) of a short film by test persons yielding different educational backgrounds and the verbal intelligence scores of the speakers. First, a one-way analysis of variance was performed to compare the monologs with the film transcription and to demonstrate that there are differences in the vocabulary used by the test persons yielding different verbal intelligence levels. Then, for the classification task, the monologs were represented as feature vectors using the classical TF–IDF weighting scheme. The Naive Bayes, k-nearest neighbors and Rocchio classifiers were tested. In this paper we describe and compare these classification approaches, define the optimal classification parameters and discuss the classification results obtained.

Estimating Adaptacion of Dialogue Partners with Different Verbal Intelligence

This work investigates to what degree speakers with different verbal intelligence may adapt to each other. The work is based on a corpus consisting of 100 descriptions of a short film (monologues), 56 discussions about the same topic (dialogues), and verbal intelligence scores of the test participants. Adaptation between two dialogue partners was measured using cross-referencing, proportion of "I", "You" and "We" words, between-subject correlation and similarity of texts. It was shown that lower verbal intelligence speakers repeated more nouns and adjectives from the other and used the same linguistic categories more often than higher verbal intelligence speakers. In dialogues between strangers, participants with higher verbal intelligence showed a greater level of adaptation.

Investigating verbal intelligence using the TF-IDF approach

In this paper we investigated differences in language use of speakers yielding different verbal intelligence when they describe the same event. The work is based on a corpus containing descriptions of a short film and verbal intelligence scores of the speakers. For analyzing the monologues and the film transcript, the number of reused words, lemmas, n-grams, cosine similarity and other features were calculated and compared to each other for different verbal intelligence groups. The results showed that the similarity of monologues of higher verbal intelligence speakers was greater than of lower and average verbal intelligence participants. A possible explanation of this phenomenon is that candidates yielding higher verbal intelligence have a better short-term memory. In this paper we also checked a hypothesis that differences in vocabulary of speakers yielding different verbal intelligence are sufficient enough for good classification results. For proving this hypothesis, the Nearest Neighbor classifier was trained using TF-IDF vocabulary measures. The maximum achieved accuracy was 92.86%.

Relating dominance of dialogue participants with their verbal intelligence scores

In this work we investigated whether there is a relationship between dominant behaviour of dialogue participants and their verbal intelligence. The analysis is based on a corpus containing 56 dialogues and verbal intelligence scores of the test persons. All the dialogues were divided into three groups: H-H is a group of dialogues between higher verbal intelligence participants, L-L is a group of dialogues between lower verbal intelligence participant and L-H is a group of all the other dialogues. The dominance scores of the dialogue partners from each group were analysed. The analysis showed that differences between dominance scores and verbal intelligence coefficients for L-L were positively correlated. Verbal intelligence scores of the test persons were compared to other features that may reflect dominant behaviour. The analysis showed that number of interruptions, long utterances, times grabbed the floor, influence diffusion model, number of agreements and several acoustic features may be related to verbal intelligence. These features were used for the automatic classification of the dialogue partners into two groups (lower and higher verbal intelligence participants); the achieved accuracy was 89.36%.

Human PEX1 cloned by functional complementation on a CHO cell mutant is responsible for peroxisome-deficient Zellweger syndrome of complementation group I

The peroxisome biogenesis disorders (PBDs), including Zellweger syndrome (ZS) and neonatal adrenoleukodystrophy (NALD), are autosomal recessive diseases caused by defects in peroxisome assembly, for which at least 10 complementation groups have been reported. We have isolated a human PEX1 cDNA (HsPEX1) by functional complementation of peroxisome deficiency of a mutant Chinese hamster ovary (CHO) cell line, ZP107, transformed with peroxisome targeting signal type 1-tagged “enhanced” green fluorescent protein. This cDNA encodes a hydrophilic protein (Pex1p) comprising 1,283 amino acids, with high homology to the AAA-type ATPase family. A stable transformant of ZP107 with HsPEX1 was morphologically and biochemically restored for peroxisome biogenesis. HsPEX1 expression restored peroxisomal protein import in fibroblasts from three patients with ZS and NALD of complementation group I (CG-I), which is the highest-incidence PBD. A CG-I ZS patient (PBDE-04) possessed compound heterozygous, inactivating mutations: a missense point mutation resulting in Leu-664 → Pro and a deletion of the sequence from Gly-634 to His-690 presumably caused by missplicing (splice site mutation). Both PBDE-04 PEX1 cDNAs were defective in peroxisome-restoring activity when expressed in the patient fibroblasts as well as in ZP107 cells. These results demonstrate that PEX1 is the causative gene for CG-I peroxisomal disorders.

Monitoring protein–protein interactions in intact eukaryotic cells by β-galactosidase complementation

We present an approach for monitoring protein–protein interactions within intact eukaryotic cells, which should increase our understanding of the regulatory circuitry that controls the proliferation and differentiation of cells and how these processes go awry in disease states such as cancer. Chimeric proteins composed of proteins of interest fused to complementing β-galactosidase (β-gal) deletion mutants permit a novel analysis of protein complexes within cells. In this approach, the β-gal activity resulting from the forced interaction of nonfunctional weakly complementing β-gal peptides (Δα and Δω) serves as a measure of the extent of interaction of the non-β-gal portions of the chimeras. To test this application of lacZ intracistronic complementation, proteins that form a complex in the presence of rapamycin were used. These proteins, FRAP and FKBP12, were synthesized as fusion proteins with Δα and Δω, respectively. Enzymatic β-gal activity served to monitor the formation of the rapamycin-induced chimeric FRAP/FKBP12 protein complex in a time- and dose-dependent manner, as assessed by histochemical, biochemical, and fluorescence-activated cell sorting assays. This approach may prove to be a valuable adjunct to in vitro immunoprecipitation and crosslinking methods and in vivo yeast two-hybrid and fluorescence energy transfer systems. It may also allow a direct assessment of specific protein dimerization interactions in a biologically relevant context, localized in the cell compartments in which they occur, and in the milieu of competing proteins.

Human argininosuccinate lyase: A structural basis for intragenic complementation

Intragenic complementation has been observed at the argininosuccinate lyase (ASL) locus. Intragenic complementation is a phenomenon that occurs when a multimeric protein is formed from subunits produced by different mutant alleles of a gene. The resulting hybrid protein exhibits enzymatic activity that is greater than that found in the oligomeric proteins produced by each mutant allele alone. The mutations involved in the most successful complementation event observed in ASL deficiency were found to be an aspartate to glycine mutation at codon 87 of one allele (D87G) coupled with a glutamine to arginine mutation at codon 286 of the other (Q286R). To understand the structural basis of the Q286R:D87G intragenic complementation event at the ASL locus, we have determined the x-ray crystal structure of recombinant human ASL at 4.0 Å resolution. The structure has been refined to an R factor of 18.8%. Two monomers related by a noncrystallographic 2-fold axis comprise the asymmetric unit, and a crystallographic 2-fold axis of space group P3121 completes the tetramer. Each of the four active sites is composed of residues from three monomers. Structural mapping of the Q286R and D87G mutations indicate that both are near the active site and each is contributed by a different monomer. Thus when mutant monomers combine randomly such that one active site contains both mutations, it is required by molecular symmetry that another active site exists with no mutations. These “native” active sites give rise to the observed partial recovery of enzymatic activity.