Pattern recognition analyses of brain activation elicited by happy and neutral faces in unipolar and bipolar depression

Objectives: Recently, pattern recognition approaches have been used to classify patterns of brain activity elicited by sensory or cognitive processes. In the clinical context, these approaches have been mainly applied to classify groups of individuals based on structural magnetic resonance imaging (MRI) data. Only a few studies have applied similar methods to functional MRI (fMRI) data. Methods: We used a novel analytic framework to examine the extent to which unipolar and bipolar depressed individuals differed on discrimination between patterns of neural activity for happy and neutral faces. We used data from 18 currently depressed individuals with bipolar I disorder (BD) and 18 currently depressed individuals with recurrent unipolar depression (UD), matched on depression severity, age, and illness duration, and 18 age- and gender ratio-matched healthy comparison subjects (HC). fMRI data were analyzed using a general linear model and Gaussian process classifiers. Results: The accuracy for discriminating between patterns of neural activity for happy versus neutral faces overall was lower in both patient groups relative to HC. The predictive probabilities for intense and mild happy faces were higher in HC than in BD, and for mild happy faces were higher in HC than UD (all p < 0.001). Interestingly, the predictive probability for intense happy faces was significantly higher in UD than BD (p = 0.03). Conclusions: These results indicate that patterns of whole-brain neural activity to intense happy faces were significantly less distinct from those for neutral faces in BD than in either HC or UD. These findings indicate that pattern recognition approaches can be used to identify abnormal brain activity patterns in patient populations and have promising clinical utility as techniques that can help to discriminate between patients with different psychiatric illnesses.

Prefrontal cortical and striatal activity to happy and fear faces in bipolar disorder is associated with comorbid substance abuse and eating disorder

Background: The spectrum approach was used to examine contributions of comorbid symptom dimensions of substance abuse and eating disorder to abnormal prefrontal-cortical and subcortical-striatal activity to happy and fear faces previously demonstrated in bipolar disorder (BD). Method: Fourteen remitted BD-type I and sixteen healthy individuals viewed neutral, mild and intense happy and fear faces in two event-related fMRI experiments. All individuals completed Substance-Use and Eating-Disorder Spectrum measures. Region-of-Interest analyses for bilateral prefrontal and subcortical-striatal regions were performed. Results: BD individuals scored significantly higher on these spectrum measures than healthy individuals (p < 0.05), and were distinguished by activity in prefrontal and subcortical-striatal regions. BD relative to healthy individuals showed reduced dorsal prefrontal-cortical activity to all faces. Only BD individuals showed greater subcortical-striatal activity to happy and neutral faces. In BD individuals, negative correlations were shown between substance use severity and right PFC activity to intense happy faces (p < 0.04), and between substance use severity and right caudate nucleus activity to neutral faces (p < 0.03). Positive correlations were shown between eating disorder and right ventral putamen activity to intense happy (p < 0.02) and neutral faces (p < 0.03). Exploratory analyses revealed few significant relationships between illness variables and medication upon neural activity in BD individuals. Limitations: Small sample size of predominantly medicated BD individuals. Conclusion: This study is the first to report relationships between comorbid symptom dimensions of substance abuse and eating disorder and prefrontal-cortical and subcortical-striatal activity to facial expressions in BD. Our findings suggest that these comorbid features may contribute to observed patterns of functional abnormalities in neural systems underlying mood regulation in BD.

Ingroup categorization affects the structural encoding of other-race faces:evidence from the N170 event-related potential

The current research examined the influence of ingroup/outgroup categorization on brain event-related potentials measured during perceptual processing of own- and other-race faces. White participants performed a sequential matching task with upright and inverted faces belonging either to their own race (White) or to another race (Black) and affiliated with either their own university or another university by a preceding visual prime. Results demonstrated that the right-lateralized N170 component evoked by test faces was modulated by race and by social category: the N170 to own-race faces showed a larger inversion effect (i.e., latency delay for inverted faces) when the faces were categorized as other-university rather than own-university members; the N170 to other-race faces showed no modulation of its inversion effect by university affiliation. These results suggest that neural correlates of structural face encoding (as evidenced by the N170 inversion effects) can be modulated by both visual (racial) and nonvisual (social) ingroup/outgroup status. © 2014 © 2014 Taylor & Francis.

Attentional inhibition has social-emotional consequences for unfamiliar faces

Visual attention studies often rely on response time measures to show the impact of attentional facilitation and inhibition. Here we extend the investigation of the effects of attention on behavior and show that prior attentional states associated with unfamiliar faces can influence subsequent social-emotional judgments about those faces. Participants were shown pairs of face images and were asked to withhold a response if a transparent stop-signal cue appeared over one of the faces. This served to associate the cued face with an inhibitory state. Later, when asked to make social-emotional choices about these face pairs, participants chose uncued faces more often than cued faces as "more trustworthy" and chose cued faces more often than uncued faces as "less trustworthy." For perceptual choices, there was no effect of how the question was framed (which face is "on a lighter background" vs. "on a darker background"). These results suggest that attentional inhibition can be associated with socially relevant stimuli, such as faces, and can have specific, deleterious effects on social-emotional judgments.

SVRMHC prediction server for MHC-binding peptides

The binding between antigenic peptides (epitopes) and the MHC molecule is a key step in the cellular immune response. Accurate in silico prediction of epitope-MHC binding affinity can greatly expedite epitope screening by reducing costs and experimental effort. Recently, we demonstrated the appealing performance of SVRMHC, an SVR-based quantitative modeling method for peptide-MHC interactions, when applied to three mouse class I MHC molecules. Subsequently, we have greatly extended the construction of SVRMHC models and have established such models for more than 40 class I and class II MHC molecules. Here we present the SVRMHC web server for predicting peptide-MHC binding affinities using these models. Benchmarked percentile scores are provided for all predictions. The larger number of SVRMHC models available allowed for an updated evaluation of the performance of the SVRMHC method compared to other well- known linear modeling methods. SVRMHC is an accurate and easy-to-use prediction server for epitope-MHC binding with significant coverage of MHC molecules. We believe it will prove to be a valuable resource for T cell epitope researchers.

VaxiJen:a server for prediction of protective antigens, tumour antigens and subunit vaccines

Background - Vaccine development in the post-genomic era often begins with the in silico screening of genome information, with the most probable protective antigens being predicted rather than requiring causative microorganisms to be grown. Despite the obvious advantages of this approach – such as speed and cost efficiency – its success remains dependent on the accuracy of antigen prediction. Most approaches use sequence alignment to identify antigens. This is problematic for several reasons. Some proteins lack obvious sequence similarity, although they may share similar structures and biological properties. The antigenicity of a sequence may be encoded in a subtle and recondite manner not amendable to direct identification by sequence alignment. The discovery of truly novel antigens will be frustrated by their lack of similarity to antigens of known provenance. To overcome the limitations of alignment-dependent methods, we propose a new alignment-free approach for antigen prediction, which is based on auto cross covariance (ACC) transformation of protein sequences into uniform vectors of principal amino acid properties. Results - Bacterial, viral and tumour protein datasets were used to derive models for prediction of whole protein antigenicity. Every set consisted of 100 known antigens and 100 non-antigens. The derived models were tested by internal leave-one-out cross-validation and external validation using test sets. An additional five training sets for each class of antigens were used to test the stability of the discrimination between antigens and non-antigens. The models performed well in both validations showing prediction accuracy of 70% to 89%. The models were implemented in a server, which we call VaxiJen. Conclusion - VaxiJen is the first server for alignment-independent prediction of protective antigens. It was developed to allow antigen classification solely based on the physicochemical properties of proteins without recourse to sequence alignment. The server can be used on its own or in combination with alignment-based prediction methods.

LIPPRED:a web server for accurate prediction of lipoprotein signal sequences and cleavage sites

Bacterial lipoproteins have many important functions and represent a class of possible vaccine candidates. The prediction of lipoproteins from sequence is thus an important task for computational vaccinology. Naïve-Bayesian networks were trained to identify SpaseII cleavage sites and their preceding signal sequences using a set of 199 distinct lipoprotein sequences. A comprehensive range of sequence models was used to identify the best model for lipoprotein signal sequences. The best performing sequence model was found to be 10-residues in length, including the conserved cysteine lipid attachment site and the nine residues prior to it. The sensitivity of prediction for LipPred was 0.979, while the specificity was 0.742. Here, we describe LipPred, a web server for lipoprotein prediction; available at the URL: http://www.jenner.ac.uk/LipPred/. LipPred is the most accurate method available for the detection of SpaseIIcleaved lipoprotein signal sequences and the prediction of their cleavage sites.

Femtosecond laser microstructuring through optical fibre end faces:inscription of surface gratings and sub-surface splitters

We present the results of femtosecond laser microstructuring of optical fibres by direct access of the fibre end face, both at the surface and several hundred microns into the fibre, to realise one-and two-dimensional grating structures and optical fibre splitters, respectively. We show the versatility of this simple but effective inscription method, where we demonstrate classic multiple slit diffraction patterns and show the potential for coarse wavelength division multiplexing for sensor signals. A key advantage for the fibre splitter is that the inscription method avoids the use of oil immersion that compensate for the fibre curvature in the standard side writing method. © 2012 SPIE.

Attentional inhibition determines emotional responses to unfamiliar faces

Complex abstract images that are ignored in a simple localization task are subsequently judged more negatively in an emotional evaluation task than previously unseen or attended images, suggesting that attentional inhibition may have affective consequences (Raymond, Fenske, & Tavassoli, in press). We examined the generality of this finding by asking whether inhibitory processes might also influence the generation of emotional responses to unfamiliar faces. To do this, we incorporated an emotional evaluation task within a paradigm that has been used to demonstrate long-term inhibition-of-return (IOR) of attention (Tipper, Grison, & Kessler, in press). On each 2-task trial, observers were first shown a unique pair of unfamiliar faces while performing a speeded go/no-go task. In this task, observers were required to withhold a response if there was an abrupt onset of an exogenous cue (no-go trials), and to make a response if a different stimulus was presented (go ‘catch’ trials). Following the completion of an intervening task, observers where asked to make an affective evaluation about the faces they had previously seen in the go/no-go task (e.g., Which of these people looks more friendly?). We found that observers were less likely to make positive affective responses to faces that attention had been exogenously drawn to in no-go trials than to faces to which attention had never been exogenously allocated. These results converge with our previous finding to suggest that inhibition may be associated with an episode encoded into memory, and that later retrieval acts to reinstate inhibitory processing. Importantly, our results suggest that this inhibitory processing involves affective devaluation, which may serve to encourage examination of new information.