Whole-brain functional connectivity during emotional word classification in medication-free Major Depressive Disorder: abnormal salience circuitry and relations to positive emotionality

Major Depressive Disorder (MDD) has been associated with biased processing and abnormal regulation of negative and positive information, which may result from compromised coordinated activity of prefrontal and subcortical brain regions involved in evaluating emotional information. We tested whether patients with MDD show distributed changes in functional connectivity with a set of independently derived brain networks that have shown high correspondence with different task demands, including stimulus salience and emotional processing. We further explored if connectivity during emotional word processing related to the tendency to engage in positive or negative emotional states. In this study, 25 medication-free MDD patients without current or past comorbidity and matched controls (n=25) performed an emotional word-evaluation task during functional MRI. Using a dual regression approach, individual spatial connectivity maps representing each subject’s connectivity with each standard network were used to evaluate between-group differences and effects of positive and negative emotionality (extraversion and neuroticism, respectively, as measured with the NEO-FFI). Results showed decreased functional connectivity of the medial prefrontal cortex, ventrolateral prefrontal cortex, and ventral striatum with the fronto-opercular salience network in MDD patients compared to controls. In patients, abnormal connectivity was related to extraversion, but not neuroticism. These results confirm the hypothesis of a relative (para)limbic-cortical decoupling that may explain dysregulated affect in MDD. As connectivity of these regions with the salience network was related to extraversion, but not to general depression severity or negative emotionality, dysfunction of this network may be responsible for the failure to sustain engagement in rewarding behavior.

Constraints on L2 learners’ processing of wh- dependencies: evidence from eye-movements

Using the eye movement monitoring technique, the present study examined whether wh-dependency formation is sensitive to island constraints in second language (L2) sentence comprehension, and whether the presence of an intervening relative clause island has any effects on learners’ ability to ultimately resolve long wh-dependencies. Participants included proficient learners of L2 English from typologically different language backgrounds (German, Chinese), as well as a group of native English-speaking controls. Our results indicate that both the learners and the native speakers were sensitive to relative clause islands during processing, irrespective of typological differences between the learners’ L1s, but that the learners had more difficulty than native speakers linking distant wh-fillers to their lexical subcategorizers during processing. We provide a unified processing-based account for our findings.

Cloud-assisted body area networks: state-of-the-art and future challenges

Body area networks (BANs) are emerging as enabling technology for many human-centered application domains such as health-care, sport, fitness, wellness, ergonomics, emergency, safety, security, and sociality. A BAN, which basically consists of wireless wearable sensor nodes usually coordinated by a static or mobile device, is mainly exploited to monitor single assisted livings. Data generated by a BAN can be processed in real-time by the BAN coordinator and/or transmitted to a server-side for online/offline processing and long-term storing. A network of BANs worn by a community of people produces large amount of contextual data that require a scalable and efficient approach for elaboration and storage. Cloud computing can provide a flexible storage and processing infrastructure to perform both online and offline analysis of body sensor data streams. In this paper, we motivate the introduction of Cloud-assisted BANs along with the main challenges that need to be addressed for their development and management. The current state-of-the-art is overviewed and framed according to the main requirements for effective Cloud-assisted BAN architectures. Finally, relevant open research issues in terms of efficiency, scalability, security, interoperability, prototyping, dynamic deployment and management, are discussed.

Age differences in brain activity during emotion processing: reflections of age-Related decline or increased emotion regulation?

Despite the fact that physical health and cognitive abilities decline with aging, the ability to regulate emotion remains stable and in some aspects improves across the adult life span. Older adults also show a positivity effect in their attention and memory, with diminished processing of negative stimuli relative to positive stimuli compared with younger adults. The current paper reviews functional magnetic resonance imaging studies investigating age-related differences in emotional processing and discusses how this evidence relates to two opposing theoretical accounts of older adults’ positivity effect. The aging-brain model [Cacioppo et al. in: Social Neuroscience: Toward Understanding the Underpinnings of the Social Mind. New York, Oxford University Press, 2011] proposes that older adults’ positivity effect is a consequence of age-related decline in the amygdala, whereas the cognitive control hypothesis [Kryla-Lighthall and Mather in: Handbook of Theories of Aging, ed 2. New York, Springer, 2009; Mather and Carstensen: Trends Cogn Sci 2005;9:496–502; Mather and Knight: Psychol Aging 2005;20:554–570] argues that the positivity effect is a result of older adults’ greater focus on regulating emotion. Based on evidence for structural and functional preservation of the amygdala in older adults and findings that older adults show greater prefrontal cortex activity than younger adults while engaging in emotion-processing tasks, we argue that the cognitive control hypothesis is a more likely explanation for older adults’ positivity effect than the aging-brain model.

Information and predictability: bookmakers, prediction markets and tipsters as forecasters

The more information is available, and the more predictable are events, the better forecasts ought to be. In this paper forecasts by bookmakers, prediction markets and tipsters are evaluated for a range of events with varying degrees of predictability and information availability. All three types of forecast represent different structures of information processing and as such would be expected to perform differently. By and large, events that are more predictable, and for which more information is available, do tend to be forecast better.

Memory for medication side effects in younger and older adults: the role of subjective and objective importance

Older adults often experience memory impairments, but can sometimes use selective processing and schematic support to remember important information. The current experiments investigate to what degree younger and healthy older adults remember medication side effects that were subjectively or objectively important to remember. Participants studied a list of common side effects, and rated how negative these effects were if they were to experience them, and were then given a free recall test. In Experiment 1, the severity of the side effects ranged from mild (e.g., itching) to severe (e.g., stroke), and in Experiment 2, certain side effects were indicated as critical to remember (i.e., “contact your doctor if you experience this”). There were no age differences in terms of free recall of the side effects, and older adults remembered more severe side effects relative to mild effects. However, older adults were less likely to recognize critical side effects on a later recognition test, relative to younger adults. The findings suggest that older adults can selectively remember medication side effects, but have difficulty identifying familiar but potentially critical side effects, and this has implications for monitoring medication use in older age.

The AeroCom evaluation and intercomparison of organic aerosol in global models

This paper evaluates the current status of global modeling of the organic aerosol (OA) in the troposphere and analyzes the differences between models as well as between models and observations. Thirty-one global chemistry transport models (CTMs) and general circulation models (GCMs) have participated in this intercomparison, in the framework of AeroCom phase II. The simulation of OA varies greatly between models in terms of the magnitude of primary emissions, secondary OA (SOA) formation, the number of OA species used (2 to 62), the complexity of OA parameterizations (gas-particle partitioning, chemical aging, multiphase chemistry, aerosol microphysics), and the OA physical, chemical and optical properties. The diversity of the global OA simulation results has increased since earlier AeroCom experiments, mainly due to the increasing complexity of the SOA parameterization in models, and the implementation of new, highly uncertain, OA sources. Diversity of over one order of magnitude exists in the modeled vertical distribution of OA concentrations that deserves a dedicated future study. Furthermore, although the OA / OC ratio depends on OA sources and atmospheric processing, and is important for model evaluation against OA and OC observations, it is resolved only by a few global models. The median global primary OA (POA) source strength is 56 Tg a−1 (range 34–144 Tg a−1) and the median SOA source strength (natural and anthropogenic) is 19 Tg a−1 (range 13–121 Tg a−1). Among the models that take into account the semi-volatile SOA nature, the median source is calculated to be 51 Tg a−1 (range 16–121 Tg a−1), much larger than the median value of the models that calculate SOA in a more simplistic way (19 Tg a−1; range 13–20 Tg a−1, with one model at 37 Tg a−1). The median atmospheric burden of OA is 1.4 Tg (24 models in the range of 0.6–2.0 Tg and 4 between 2.0 and 3.8 Tg), with a median OA lifetime of 5.4 days (range 3.8–9.6 days). In models that reported both OA and sulfate burdens, the median value of the OA/sulfate burden ratio is calculated to be 0.77; 13 models calculate a ratio lower than 1, and 9 models higher than 1. For 26 models that reported OA deposition fluxes, the median wet removal is 70 Tg a−1 (range 28–209 Tg a−1), which is on average 85% of the total OA deposition. Fine aerosol organic carbon (OC) and OA observations from continuous monitoring networks and individual field campaigns have been used for model evaluation. At urban locations, the model–observation comparison indicates missing knowledge on anthropogenic OA sources, both strength and seasonality. The combined model–measurements analysis suggests the existence of increased OA levels during summer due to biogenic SOA formation over large areas of the USA that can be of the same order of magnitude as the POA, even at urban locations, and contribute to the measured urban seasonal pattern. Global models are able to simulate the high secondary character of OA observed in the atmosphere as a result of SOA formation and POA aging, although the amount of OA present in the atmosphere remains largely underestimated, with a mean normalized bias (MNB) equal to −0.62 (−0.51) based on the comparison against OC (OA) urban data of all models at the surface, −0.15 (+0.51) when compared with remote measurements, and −0.30 for marine locations with OC data. The mean temporal correlations across all stations are low when compared with OC (OA) measurements: 0.47 (0.52) for urban stations, 0.39 (0.37) for remote stations, and 0.25 for marine stations with OC data. The combination of high (negative) MNB and higher correlation at urban stations when compared with the low MNB and lower correlation at remote sites suggests that knowledge about the processes that govern aerosol processing, transport and removal, on top of their sources, is important at the remote stations. There is no clear change in model skill with increasing model complexity with regard to OC or OA mass concentration. However, the complexity is needed in models in order to distinguish between anthropogenic and natural OA as needed for climate mitigation, and to calculate the impact of OA on climate accurately.

Reward, rest, and antidepressant drug action

Purpose of the study: Reduced subjective experience of reward (anhedonia) is a key symptom of major depression. We have developed a human model of reward processing to investigate the neural correlates of anhedonia. Methods: We report the data from studies that examined reward processing using functional magnetic resonance imaging (fMRI) in those vulnerable to depression. We also report the effects of antidepressant medications on our neural model of reward processing and on the resting state in healthy volunteers. Results: Our results thus far indicate that deficits in reward processing are apparent in those vulnerable to depression, and also that antidepressant medication modulates reward processing and resting state functional connectivity in parts of the brain consistent with serotonin and catecholamine transmitter pathways in healthy volunteers. Conclusions: We conclude that this type of human model of reward processing might be useful in detecting biomarkers for depression and also in illuminating why antidepressant medications may not be very effective in treating anhedonia.

On the 'special' status of emotional faces... Comment on Yang, Hong, and Blake (2010)

A wealth of literature suggests that emotional faces are given special status as visual objects: Cognitive models suggest that emotional stimuli, particularly threat-relevant facial expressions such as fear and anger, are prioritized in visual processing and may be identified by a subcortical “quick and dirty” pathway in the absence of awareness (Tamietto & de Gelder, 2010). Both neuroimaging studies (Williams, Morris, McGlone, Abbott, & Mattingley, 2004) and backward masking studies (Whalen, Rauch, Etcoff, McInerney, & Lee, 1998) have supported the notion of emotion processing without awareness. Recently, our own group (Adams, Gray, Garner, & Graf, 2010) showed adaptation to emotional faces that were rendered invisible using a variant of binocular rivalry: continual flash suppression (CFS, Tsuchiya & Koch, 2005). Here we (i) respond to Yang, Hong, and Blake's (2010) criticisms of our adaptation paper and (ii) provide a unified account of adaptation to facial expression, identity, and gender, under conditions of unawareness

K-Surfer: a KNIME extension for the management and analysis of Human brain MRI FreeSurfer/FSL data

Human brain imaging techniques, such as Magnetic Resonance Imaging (MRI) or Diffusion Tensor Imaging (DTI), have been established as scientific and diagnostic tools and their adoption is growing in popularity. Statistical methods, machine learning and data mining algorithms have successfully been adopted to extract predictive and descriptive models from neuroimage data. However, the knowledge discovery process typically requires also the adoption of pre-processing, post-processing and visualisation techniques in complex data workflows. Currently, a main problem for the integrated preprocessing and mining of MRI data is the lack of comprehensive platforms able to avoid the manual invocation of preprocessing and mining tools, that yields to an error-prone and inefficient process. In this work we present K-Surfer, a novel plug-in of the Konstanz Information Miner (KNIME) workbench, that automatizes the preprocessing of brain images and leverages the mining capabilities of KNIME in an integrated way. K-Surfer supports the importing, filtering, merging and pre-processing of neuroimage data from FreeSurfer, a tool for human brain MRI feature extraction and interpretation. K-Surfer automatizes the steps for importing FreeSurfer data, reducing time costs, eliminating human errors and enabling the design of complex analytics workflow for neuroimage data by leveraging the rich functionalities available in the KNIME workbench.

Using E-Z Reader to examine the concurrent development of eye-movement control and reading skill

Compared to skilled adult readers, children typically make more fixations that are longer in duration, shorter saccades, and more regressions, thus reading more slowly (Blythe & Joseph, 2011). Recent attempts to understand the reasons for these differences have discovered some similarities (e.g., children and adults target their saccades similarly; Joseph, Liversedge, Blythe, White, & Rayner, 2009) and some differences (e.g., children’s fixation durations are more affected by lexical variables; Blythe, Liversedge, Joseph, White, & Rayner, 2009) that have yet to be explained. In this article, the E-Z Reader model of eye-movement control in reading (Reichle, 2011; Reichle, Pollatsek, Fisher, & Rayner, 1998) is used to simulate various eye-movement phenomena in adults versus children in order to evaluate hypotheses about the concurrent development of reading skill and eye-movement behavior. These simulations suggest that the primary difference between children and adults is their rate of lexical processing, and that different rates of (post-lexical) language processing may also contribute to some phenomena (e.g., children’s slower detection of semantic anomalies; Joseph et al., 2008). The theoretical implications of this hypothesis are discussed, including possible alternative accounts of these developmental changes, how reading skill and eye movements change across the entire lifespan (e.g., college-aged vs. elderly readers), and individual differences in reading ability.

Paddy Hartley: of faces and facades

Paddy Hartley's work is primarily concerned with the ways in which the human face can be repaired, manipulated and recontextualised, and the questions these processes raise about our concepts of beauty and disfigurement. Incorporating surgical and pharmaceutical equipment as well as steel, scrap metal, digital embroidery and textiles, Hartley sets out a critique of how we think about the face today. Taking as a starting point records of facially injured servicemen of the First World War and the pioneering surgery they underwent, Project Facade examines the impact of disfigurement on the human psyche, as well as tracing the development of early facial reconstructive surgery. His Face Corsets, meanwhile, examines attitudes towards cosmetic surgery and the beauty industry, providing a non-surgical means to brutally mimic the results of cosmetic procedures and beyond. The series gained notoriety and success in a wide variety of popular publications both nationally and internationally, and continue to feature in contemporary textiles and fashion publications. Paddy Hartley: Of Faces and Facades brings together these works in book form for the first time, presenting previously unpublished texts from David Houston Jones and Marjorie Gehrhardt, as well as drawings and photographs which document a remarkable creative process and a history that is still insufficiently explored.

A psychometric analysis of reliability and validity of the index of learning styles (ILS)

Prior literature showed that Felder and Silverman learning styles model (FSLSM) was widely adopted to cater to individual styles of learners whether in traditional or Technology Enhanced Learning (TEL). In order to infer this model, the Index of Learning Styles (ILS) instrument was proposed. This research aims to analyse the soundness of this instrument in an Arabic sample. Data were integrated from different courses and years. A total of 259 engineering students participated voluntarily in the study. The reliability was analysed by applying internal construct reliability, inter-scale correlation, and total item correlation. The construct validity was also considered by running factor analysis. The overall results indicated that the reliability and validity of perception and input dimensions were moderately supported, whereas processing and understanding dimensions showed low internal-construct consistency and their items were weakly loaded in the associated constructs. Generally, the instrument needs further effort to improve its soundness. However, considering the consistency of the produced results of engineering students irrespective of cross-cultural differences, it can be adopted to diagnose learning styles.

Resting tremor classification and detection in Parkinson's disease patients

Parkinson is a neurodegenerative disease, in which tremor is the main symptom. This paper investigates the use of different classification methods to identify tremors experienced by Parkinsonian patients.Some previous research has focussed tremor analysis on external body signals (e.g., electromyography, accelerometer signals, etc.). Our advantage is that we have access to sub-cortical data, which facilitates the applicability of the obtained results into real medical devices since we are dealing with brain signals directly. Local field potentials (LFP) were recorded in the subthalamic nucleus of 7 Parkinsonian patients through the implanted electrodes of a deep brain stimulation (DBS) device prior to its internalization. Measured LFP signals were preprocessed by means of splinting, down sampling, filtering, normalization and rec-tification. Then, feature extraction was conducted through a multi-level decomposition via a wavelettrans form. Finally, artificial intelligence techniques were applied to feature selection, clustering of tremor types, and tremor detection.The key contribution of this paper is to present initial results which indicate, to a high degree of certainty, that there appear to be two distinct subgroups of patients within the group-1 of patients according to the Consensus Statement of the Movement Disorder Society on Tremor. Such results may well lead to different resultant treatments for the patients involved, depending on how their tremor has been classified. Moreover, we propose a new approach for demand driven stimulation, in which tremor detection is also based on the subtype of tremor the patient has. Applying this knowledge to the tremor detection problem, it can be concluded that the results improve when patient clustering is applied prior to detection.

Manipulation of milk fatty acid composition in lactating cows: opportunities and challenges

Public health policies recommend a population wide decrease in the consumption of saturated fatty acids (SFA) to lower the incidence of cardiovascular and metabolic diseases. In most developed countries, milk and dairy products are the major source of SFA in the human diet. Altering milk fat composition offers the opportunity to lower the consumption of SFA without requiring a change in eating habits. Supplementing the diet of lactating cows with oilseeds, plant oils and marine lipids can be used to replace the SFA in milk fat with monounsaturated fatty acids (MUFA), and to a lesser extent, polyunsaturated fatty acids (PUFA). Due to ruminal metabolism, the decreases in milk SFA are also accompanied by increases in trans fatty acids (TFA), including conjugated isomers. The potential to lower SFA, enrich cis MUFA and PUFA, and alter the abundance and distribution of individual TFA in milk differs according to oil source, form of lipid supplement and degree of oilseed processing, and the influence of other components in the diet. The present review summarises recent evidence on changes in milk fat composition that can be achieved using dietary lipid supplements and highlights the challenges to commercial production of modified milk and dairy products. A meta-analysis on the effects of oilseeds on milk fatty acid composition is also presented.