Delay discounting task in pigs reveals response strategies related to dopamine metabolite.

We developed a novel delay discounting task to investigate outcome impulsivity in pigs. As impulsivity can affect aggression, and might also relate to proactive and reactive coping styles, eight proactive (HR) and eight reactive (LR) pigs identified in a manual restraint test ("Backtest", after Bolhuis et al., 2003) were weaned and mixed in four pens of four unfamiliar pigs, so that each pen had two HR and two LR pigs, and aggression was scored in the 9h after mixing. In the delay discounting task, each pig chose between two levers, one always delivering a small immediate reward, the other a large delayed reward with daily increasing delays, impulsive individuals being the ones discounting the value of the large reward quicker. Two novel strategies emerged: some pigs gradually switched their preference towards the small reward ('Switchers') as predicted, but others persistently preferred the large reward until they stopped making choices ('Omitters'). Outcome impulsivity itself was unrelated to these strategies, to urinary serotonin metabolite (5-HIAA) or dopamine metabolite (HVA) levels, aggression at weaning, or coping style. However, HVA was relatively higher in Omitters than Switchers, and positively correlated with behavioural measures of indecisiveness and frustration during choosing. The delay discounting task thus revealed two response strategies that seemed to be related to the activity of the dopamine system and might indicate a difference in execution, rather than outcome, impulsivity.

Development of the Davos Assessment of Cognitive Biases Scale (DACOBS)

Objective: Cognitive problems and biases play an important role in the development and continuation of psychosis. A self-report measure of these deficits and processes was developed (Davos Assessment of Cognitive Biases Scale: DACOBS) and is evaluated in this study. Methods: An item pool made by international experts was used to develop a self-report scale on a sample of 138 schizophrenia spectrum patients. Another sample of 71 patients was recruited to validate the subscales. A group of 186 normal control subjects was recruited to establish norms and examine discriminative validity. Results: Factor analyses resulted in seven factors, each with six items (jumping to conclusions, belief inflexibility bias, attention for threat bias, external attribution bias, social cognition problems, subjective cognitive problems and safety behavior). All factors independently explained the variance (eigenvalues > 2) and total explained variance was 45%. Reliability was good (Cronbach's alpha = .90; split-half reliability = .92; test–retest reliability = .86). The DACOBS discriminates between schizophrenia spectrum patients and normal control subjects. Validity was affirmed for five of seven subscales. The scale ‘Subjective Cognitive problems’ was not associated with objective cognitive functioning and ‘Social cognition problems’ was not associated with the Hinting task, but with the scale measuring ideas of social reference. Conclusions: The DACOBS scale, with seven independent subscales, is reliable and valid for use in clinical practice and research.

Implicit task sequence learning

Implicit task sequence learning (TSL) can be considered as an extension of implicit sequence learning which is typically tested with the classical serial reaction time task (SRTT). By design, in the SRTT there is a correlation between the sequence of stimuli to which participants must attend and the sequence of motor movements/key presses with which participants must respond. The TSL paradigm allows to disentangle this correlation and to separately manipulate the presences/absence of a sequence of tasks, a sequence of responses, and even other streams of information such as stimulus locations or stimulus-response mappings. Here I review the state of TSL research which seems to point at the critical role of the presence of correlated streams of information in implicit sequence learning. On a more general level, I propose that beyond correlated streams of information, a simple statistical learning mechanism may also be involved in implicit sequence learning, and that the relative contribution of these two explanations differ according to task requirements. With this differentiation, conflicting results can be integrated into a coherent framework.

An Extended Hierarchical Task Analysis for Error Prediction in Medical Devices

This paper introduces an extended hierarchical task analysis (HTA) methodology devised to evaluate and compare user interfaces on volumetric infusion pumps. The pumps were studied along the dimensions of overall usability and propensity for generating human error. With HTA as our framework, we analyzed six pumps on a variety of common tasks using Norman’s Action theory. The introduced method of evaluation divides the problem space between the external world of the device interface and the user’s internal cognitive world, allowing for predictions of potential user errors at the human-device level. In this paper, one detailed analysis is provided as an example, comparing two different pumps on two separate tasks. The results demonstrate the inherent variation, often the cause of usage errors, found with infusion pumps being used in hospitals today. The reported methodology is a useful tool for evaluating human performance and predicting potential user errors with infusion pumps and other simple medical devices.

Three-dimensional, task-specific robot therapy of the arm after stroke: a multicentre, parallel-group randomised trial

BACKGROUND: Arm hemiparesis secondary to stroke is common and disabling. We aimed to assess whether robotic training of an affected arm with ARMin--an exoskeleton robot that allows task-specific training in three dimensions-reduces motor impairment more effectively than does conventional therapy. METHODS: In a prospective, multicentre, parallel-group randomised trial, we enrolled patients who had had motor impairment for more than 6 months and moderate-to-severe arm paresis after a cerebrovascular accident who met our eligibility criteria from four centres in Switzerland. Eligible patients were randomly assigned (1:1) to receive robotic or conventional therapy using a centre-stratified randomisation procedure. For both groups, therapy was given for at least 45 min three times a week for 8 weeks (total 24 sessions). The primary outcome was change in score on the arm (upper extremity) section of the Fugl-Meyer assessment (FMA-UE). Assessors tested patients immediately before therapy, after 4 weeks of therapy, at the end of therapy, and 16 weeks and 34 weeks after start of therapy. Assessors were masked to treatment allocation, but patients, therapists, and data analysts were unmasked. Analyses were by modified intention to treat. This study is registered with ClinicalTrials.gov, number NCT00719433. FINDINGS: Between May 4, 2009, and Sept 3, 2012, 143 individuals were tested for eligibility, of whom 77 were eligible and agreed to participate. 38 patients assigned to robotic therapy and 35 assigned to conventional therapy were included in analyses. Patients assigned to robotic therapy had significantly greater improvements in motor function in the affected arm over the course of the study as measured by FMA-UE than did those assigned to conventional therapy (F=4.1, p=0.041; mean difference in score 0.78 points, 95% CI 0.03-1.53). No serious adverse events related to the study occurred. INTERPRETATION: Neurorehabilitation therapy including task-oriented training with an exoskeleton robot can enhance improvement of motor function in a chronically impaired paretic arm after stroke more effectively than conventional therapy. However, the absolute difference between effects of robotic and conventional therapy in our study was small and of weak significance, which leaves the clinical relevance in question.

Improved detection of amnestic MCI by means of discriminative vector quantization of single-trial cognitive ERP responses

Cognitive event-related potentials (ERPs) are widely employed in the study of dementive disorders. The morphology of averaged response is known to be under the influence of neurodegenerative processes and exploited for diagnostic purposes. This work is built over the idea that there is additional information in the dynamics of single-trial responses. We introduce a novel way to detect mild cognitive impairment (MCI) from the recordings of auditory ERP responses. Using single trial responses from a cohort of 25 amnestic MCI patients and a group of age-matched controls, we suggest a descriptor capable of encapsulating single-trial (ST) response dynamics for the benefit of early diagnosis. A customized vector quantization (VQ) scheme is first employed to summarize the overall set of ST-responses by means of a small-sized codebook of brain waves that is semantically organized. Each ST-response is then treated as a trajectory that can be encoded as a sequence of code vectors. A subject's set of responses is consequently represented as a histogram of activated code vectors. Discriminating MCI patients from healthy controls is based on the deduced response profiles and carried out by means of a standard machine learning procedure. The novel response representation was found to improve significantly MCI detection with respect to the standard alternative representation obtained via ensemble averaging (13% in terms of sensitivity and 6% in terms of specificity). Hence, the role of cognitive ERPs as biomarker for MCI can be enhanced by adopting the delicate description of our VQ scheme.

Shying away: An observer-based microprocess analysis of experiential avoidance and resource activation in outpatients with generalized anxiety spectrum disorder

Despite long-standing calls for patient-focused research on individuals with generalized anxiety spectrum disorder there is little systematized knowledge about the in-session behaviors of these patients. The primary objective of this study was to describe of in-session trajectories of the patients' level of explication (as an indicator of an elaborated exposure of negative emotionality) and the patients' focus on their own resources and how these trajectories are associated with post-treatment outcome. In respect to GAD patients, a high level of explication might be seen as an indicator of successful exposure of avoided negative emotionality during therapy sessions. Observers made minute-by-minute ratings of 1100 minutes of video of 20 patients-therapists dyads. The results indicated that a higher level of explication generally observed at a later stage during the therapy sessions and the patients' focus on competencies at an early stage was highly associated with positive therapy outcome at assessment at post treatment, independent of pretreatment distress, rapid response of well-being and symptom reduction, as well as the therapists' professional experience and therapy lengths. These results will be discussed under the perspective of emotion regulation of patients and therapist's counterregulation. It is assumed that GAD-Patients are especially skilled in masking difficult emotions. Explication level and emotion regulation are important variables for this patient group but there's relation to outcome is different.

Experimental induction of psychotherapeutically relevant emotional states

Background: Emotion research in neuroscience targets brain structures and processes involved in discrete emotion categories (e.g. anger, fear, sadness) or dimensions (e.g. valence, arousal, approach-avoidance), and usually relies on carefully controlled experimental paradigms with standardized and often simple emotion-eliciting stimuli like e.g. unpleasant pictures. Emotion research in clinical psychology and psychotherapy is often interested in very subtle differences between emotional states, e.g. differences within emotion categories (e.g. assertive, self-protecting vs. rejecting, protesting anger or specific grief vs. global sadness), and/or the biographical, social, situational, or motivational contexts of the emotional experience, which are desired to be minimized in experimental neuroscientific research. Objective: In order to facilitate the experimental and neurophysiological investigation of psychotherapeutically relevant emotional experiences, the present study aims at developing a priming procedure to induce specific, therapeutically and biographically relevant emotional states under controlled experimental conditions. Methodology: N = 50 participants who reported negative feelings towards another close person were randomly assigned to 2 different conditions. They fulfilled 2 different sentence completion tasks that were supposed to prime either ‘therapeutically productive’ or ‘therapeutically unproductive’ emotional states and completed an expressive writing task and several self-report measures of specific emotion-related constructs. The sentence completion task consisted in max. 22 sentence stems drawn from psychotherapy patients’ statements that have been shown to be typical for productive or unproductive therapy sessions. The subjects of the present study completed these sentence stems with regard to their own negative feelings towards the close person. Results: There were a substantial inter-individual variability concerning the number of completed sentences, and significant correlations between number of completed sentences and problem activation in both conditions. No differences were observed in general mood or problem activation between both groups after priming. Descriptively, there were differences between groups concerning emotion regulation aspects. Significant differences between groups in resolution of negative feelings towards the other person were found. Discussion: The results point in the expected direction, however the small sample sizes (after exclusion of several subjects) and low power hinder the detection of convincing significant effects. More data is needed in order to evaluate the efficacy of this emotional priming procedure.