Increased sensitivity in mapping task demand in visuospatial processing using reaction-time-dependent hemodynamic response predictors in rapid event-related fMRI

Searching for the neural correlates of visuospatial processing using functional magnetic resonance imaging (fMRI) is usually done in an event-related framework of cognitive subtraction, applying a paradigm comprising visuospatial cognitive components and a corresponding control task. Besides methodological caveats of the cognitive subtraction approach, the standard general linear model with fixed hemodynamic response predictors bears the risk of being underspecified. It does not take into account the variability of the blood oxygen level-dependent signal response due to variable task demand and performance on the level of each single trial. This underspecification may result in reduced sensitivity regarding the identification of task-related brain regions. In a rapid event-related fMRI study, we used an extended general linear model including single-trial reaction-time-dependent hemodynamic response predictors for the analysis of an angle discrimination task. In addition to the already known regions in superior and inferior parietal lobule, mapping the reaction-time-dependent hemodynamic response predictor revealed a more specific network including task demand-dependent regions not being detectable using the cognitive subtraction method, such as bilateral caudate nucleus and insula, right inferior frontal gyrus and left precentral gyrus.

ON THE MERITS OF VOXEL-BASED MORPHOMETRIC PATH-ANALYSIS FOR INVESTIGATING VOLUMETRIC MEDIATION OF A TOXICANT'S INFLUENCE ON COGNITIVE FUNCTION

We previously showed that lifetime cumulative lead dose, measured as lead concentration in the tibia bone by X-ray fluorescence, was associated with persistent and progressive declines in cognitive function and with decreases in MRI-based brain volumes in former lead workers. Moreover, larger region-specific brain volumes were associated with better cognitive function. These findings motivated us to explore a novel application of path analysis to evaluate effect mediation. Voxel-wise path analysis, at face value, represents the natural evolution of voxel-based morphometry methods to answer questions of mediation. Application of these methods to the former lead worker data demonstrated potential limitations in this approach where there was a tendency for results to be strongly biased towards the null hypothesis (lack of mediation). Moreover, a complimentary analysis using anatomically-derived regions of interest volumes yielded opposing results, suggesting evidence of mediation. Specifically, in the ROI-based approach, there was evidence that the association of tibia lead with function in three cognitive domains was mediated through the volumes of total brain, frontal gray matter, and/or possibly cingulate. A simulation study was conducted to investigate whether the voxel-wise results arose from an absence of localized mediation, or more subtle defects in the methodology. The simulation results showed the same null bias evidenced as seen in the lead workers data. Both the lead worker data results and the simulation study suggest that a null-bias in voxel-wise path analysis limits its inferential utility for producing confirmatory results.

A cognitive analysis of English cognate objects

In this paper, from the perspective of Cognitive Grammar, we consider the question of what kind of verbs can take cognate objects (COs) and what kind of verbs cannot. We investigate the syntactic properties of COs, such as the ability to take modifiers, the passivizability of cognate object constructions (COCs), and the it-pronominalization of COs. It is our contention that a detailed classification of verbs that occur in COCs is required in order to capture the relation between the syntactic properties and the modification of COs. While classifying verbs, we focus on three conceptual factors: the force of energy of the subject, a change of state of the subject, and the objectivity of the cognate noun. The study reveals that these three parameters enable us to capture the difference in the interpretation of COs in relation to modification and syntactic tests.

Analysis of eye and head coordination in a visual peripheral recognition task

Coordinated eye and head movements simultaneously occur to scan the visual world for relevant targets. However, measuring both eye and head movements in experiments allowing natural head movements may be challenging. This paper provides an approach to study eye-head coordination: First, we demonstra- te the capabilities and limits of the eye-head tracking system used, and compare it to other technologies. Second, a beha- vioral task is introduced to invoke eye-head coordination. Third, a method is introduced to reconstruct signal loss in video- based oculography caused by cornea reflection artifacts in order to extend the tracking range. Finally, parameters of eye- head coordination are identified using EHCA (eye-head co- ordination analyzer), a MATLAB software which was developed to analyze eye-head shifts. To demonstrate the capabilities of the approach, a study with 11 healthy subjects was performed to investigate motion behavior. The approach presented here is discussed as an instrument to explore eye-head coordination, which may lead to further insights into attentional and motor symptoms of certain neurological or psychiatric diseases, e.g., schizophrenia.

Spatio-temporal dynamics of alpha brain electric fields, and cognitive modes

Brian electric activity is viewed as sequences of momentary maps of potential distribution. Frequency-domain source modeling, estimation of the complexity of the trajectory of the mapped brain field distributions in state space, and microstate parsing were used as analysis tools. Input-presentation as well as task-free (spontaneous thought) data collection paradigms were employed. We found: Alpha EEG field strength is more affected by visualizing mentation than by abstract mentation, both input-driven as well as self-generated. There are different neuronal populations and brain locations of the electric generators for different temporal frequencies of the brain field. Different alpha frequencies execute different brain functions as revealed by canonical correlations with mentation profiles. Different modes of mentation engage the same temporal frequencies at different brain locations. The basic structure of alpha electric fields implies inhomogeneity over time — alpha consists of concatenated global microstates in the sub-second range, characterized by quasi-stable field topographies, and rapid transitions between the microstates. In general, brain activity is strongly discontinuous, indicating that parsing into field landscape-defined microstates is appropriate. Different modes of spontaneous and induced mentation are associated with different brain electric microstates; these are proposed as candidates for psychophysiological ``atoms of thought''.

Psychological Data from an Exploration of the Rapport / Synchrony Interplay Using Motion Energy Analysis

These data result from an investigation examining the interplay between dyadic rapport and consequential behavior-mirroring. Participants responded to a variety of interpersonally-focused pretest measures prior to their engagement in videotaped interdependent tasks (coded for interactional synchrony using Motion Energy Analysis [17,18]). A post-task evaluation of rapport and other related constructs followed each exchange. Four studies shared these same dependent measures, but asked distinct questions: Study 1 (Ndyad = 38) explored the influence of perceived responsibility and gender-specificity of the task; Study 2 (Ndyad = 51) focused on dyad sex-makeup; Studies 3 (Ndyad = 41) and 4 (Ndyad = 63) examined cognitive load impacts on the interactions. Versions of the data are structured with both individual and dyad as the unit of analysis. Our data possess strong reuse potential for theorists interested in dyadic processes and are especially pertinent to questions about dyad agreement and interpersonal perception / behavior association relationships.

Turning univalent stimuli bivalent: Synesthesia can cause cognitive conflict in task switching

In this study we investigated whether synesthetic color experiences have similar effects as real colors in cognitive conflict adaptation. We tested 24 synesthetes and two yoke-matched control groups in a task-switching experiment that involved regular switches between three simple decision tasks (a color decision, a form decision, and a size decision). In most of the trials the stimuli were univalent, that is, specific for each task. However, occasionally, black graphemes were presented for the size decisions and we tested whether they would trigger synesthetic color experiences and thus, turn them into bivalent stimuli. The results confirmed this expectation. We were also interested in their effect for subsequent performance (i.e., the bivalency effect). The results showed that for synesthetic colors the bivalency effect was not as pronounced as for real colors. The latter result may be related to differences between synesthetes and controls in coping with color conflict.

Unique and shared techniques in cognitive-behavioural and short-term psychodynamic psychotherapy: a content analysis of randomised trials on depression

Randomised controlled trials (RCTs) of psychotherapeutic interventions assume that specific techniques are used in treatments, which are responsible for changes in the client's symptoms. This assumption also holds true for meta-analyses, where evidence for specific interventions and techniques is compiled. However, it has also been argued that different treatments share important techniques and that an upcoming consensus about useful treatment strategies is leading to a greater integration of treatments. This makes assumptions about the effectiveness of specific interventions ingredients questionable if the shared (common) techniques are more often used in interventions than are the unique techniques. This study investigated the unique or shared techniques in RCTs of cognitive-behavioural therapy (CBT) and short-term psychodynamic psychotherapy (STPP). Psychotherapeutic techniques were coded from 42 masked treatment descriptions of RCTs in the field of depression (1979-2010). CBT techniques were often used in studies identified as either CBT or STPP. However, STPP techniques were only used in STPP-identified studies. Empirical clustering of treatment descriptions did not confirm the original distinction of CBT versus STPP, but instead showed substantial heterogeneity within both approaches. Extraction of psychotherapeutic techniques from the treatment descriptions is feasible and could be used as a content-based approach to classify treatments in systematic reviews and meta-analyses.

Task granularity analysis in logic programs

While logic programming languages offer a great deal of scope for parallelism, there is usually some overhead associated with the execution of goals in parallel because of the work involved in task creation and scheduling. In practice, therefore, the "granularity" of a goal, i.e. an estimate of the work available under it, should be taken into account when deciding whether or not to execute a goal concurrently as a sepárate task. This paper describes a method for estimating the granularity of a goal at compile time. The runtime overhead associated with our approach is usually quite small, and the performance improvements resulting from the incorporation of grainsize control can be quite good. This is shown by means of experimental results.

Dysfunctional and compensatory duality in mild cognitive impairment during a continuous recognition memory task

One of the current issues of debate in the study of mild cognitive impairment (MCI) is deviations of oscillatory brain responses from normal brain states and its dynamics. This work aims to characterize the differences of power in brain oscillations during the execution of a recognition memory task in MCI subjects in comparison with elderly controls. Magnetoencephalographic (MEG) signals were recorded during a continuous recognition memory task performance. Oscillatory brain activity during the recognition phase of the task was analyzed by wavelet transform in the source space by means of minimum norm algorithm. Both groups obtained a 77% hit ratio. In comparison with healthy controls, MCI subjects showed increased theta (p < 0.001), lower beta reduction (p < 0.001) and decreased alpha and gamma power (p < 0.002 and p < 0.001 respectively) in frontal, temporal and parietal areas during early and late latencies. Our results point towards a dual pattern of activity (increase and decrease) which is indicative of MCI and specific to certain time windows, frequency bands and brain regions. These results could represent two neurophysiological sides of MCI. Characterizing these opposing processes may contribute to the understanding of the disorder.

Analysis of spontaneous MEG activity in mild cognitive impairment and Alzheimer's disease using spectral entropies and statistical complexity measures

Alzheimer's disease (AD) is the most common cause of dementia. Over the last few years, a considerable effort has been devoted to exploring new biomarkers. Nevertheless, a better understanding of brain dynamics is still required to optimize therapeutic strategies. In this regard, the characterization of mild cognitive impairment (MCI) is crucial, due to the high conversion rate from MCI to AD. However, only a few studies have focused on the analysis of magnetoencephalographic (MEG) rhythms to characterize AD and MCI. In this study, we assess the ability of several parameters derived from information theory to describe spontaneous MEG activity from 36 AD patients, 18 MCI subjects and 26 controls. Three entropies (Shannon, Tsallis and Rényi entropies), one disequilibrium measure (based on Euclidean distance ED) and three statistical complexities (based on Lopez Ruiz–Mancini–Calbet complexity LMC) were used to estimate the irregularity and statistical complexity of MEG activity. Statistically significant differences between AD patients and controls were obtained with all parameters (p < 0.01). In addition, statistically significant differences between MCI subjects and controls were achieved by ED and LMC (p < 0.05). In order to assess the diagnostic ability of the parameters, a linear discriminant analysis with a leave-one-out cross-validation procedure was applied. The accuracies reached 83.9% and 65.9% to discriminate AD and MCI subjects from controls, respectively. Our findings suggest that MCI subjects exhibit an intermediate pattern of abnormalities between normal aging and AD. Furthermore, the proposed parameters provide a new description of brain dynamics in AD and MCI.

DAEDALUS at SemEval-2014 Task 9: Comparing approaches for sentiment analysis in twitter

This paper describes our participation at SemEval- 2014 sentiment analysis task, in both contextual and message polarity classification. Our idea was to com- pare two different techniques for sentiment analysis. First, a machine learning classifier specifically built for the task using the provided training corpus. On the other hand, a lexicon-based approach using natural language processing techniques, developed for a ge- neric sentiment analysis task with no adaptation to the provided training corpus. Results, though far from the best runs, prove that the generic model is more robust as it achieves a more balanced evaluation for message polarity along the different test sets.

Anomalous Consistency in Mild Cognitive Impairment: A Complex Networks Approach

Increased variability in performance has been associated with the emergence of several neurological and psychiatric pathologies. However, whether and how consistency of neuronal activity may also be indicative of an underlying pathology is still poorly understood. Here we propose a novel method for evaluating consistency from non-invasive brain recordings. We evaluate the consistency of the cortical activity recorded with magnetoencephalography in a group of subjects diagnosed with Mild Cognitive Impairment (MCI), a condition sometimes prodromal of dementia, during the execution of a memory task. We use metrics coming from nonlinear dynamics to evaluate the consistency of cortical regions. A representation known as parenclitic networks is constructed, where atypical features are endowed with a network structure, the topological properties of which can be studied at various scales. Pathological conditions correspond to strongly heterogeneous networks, whereas typical or normative conditions are characterized by sparsely connected networks with homogeneous nodes. The analysis of this kind of networks allows identifying the extent to which consistency is affected in the MCI group and the focal points where MCI is especially severe. To the best of our knowledge, these results represent the first attempt at evaluating the consistency of brain functional activity using complex networks theory.