Computational modelling reveals contrasting effects on reinforcement learning and cognitive flexibility in stimulant use disorder and obsessive-compulsive disorder: remediating effects of dopaminergic D2/3 receptor agents.

Rationale: Disorders of compulsivity such as stimulant use disorder (SUD) and obsessive-compulsive disorder (OCD) are characterised by deficits in behavioural flexibility, some of which have been captured using probabilistic reversal learning (PRL) paradigms.

Objectives: This study used computational modelling to characterise the reinforcement learning processes underlying patterns of PRL behaviour observed in SUD and OCD and to show how the dopamine D receptor agonist pramipexole and the D antagonist amisulpride affected these responses.

Methods: We applied a hierarchical Bayesian method to PRL data across three groups: individuals with SUD, OCD, and healthy controls.

Mapping Compulsivity in the DSM-5 Obsessive Compulsive and Related Disorders: Cognitive Domains, Neural Circuitry, and Treatment.

Compulsions are repetitive, stereotyped thoughts and behaviors designed to reduce harm. Growing evidence suggests that the neurocognitive mechanisms mediating behavioral inhibition (motor inhibition, cognitive inflexibility) reversal learning and habit formation (shift from goal-directed to habitual responding) contribute toward compulsive activity in a broad range of disorders. In obsessive compulsive disorder, distributed network perturbation appears focused around the prefrontal cortex, caudate, putamen, and associated neuro-circuitry.

Human Psychophysical Functions, an Update: Methods for Identifying their form; Estimating their Parameters; and Evaluating the Effects of Important Predictors.

Stevens' power law for the judgments of sensation has a long history in psychology and is used in many psychophysical investigations of the effects of predictors such as group or condition. Stevens' formulation [Formula: see text], where [Formula: see text] is the psychological judgment, P is the physical intensity, and [Formula: see text] is the power law exponent, is usually tested by plotting log [Formula: see text] against log (P). In some, but by no means all, studies, effects on the scale parameter, [Formula: see text], are also investigated.

In vitro and in vivo characterisation of a novel peptide delivery system: amphiphilic polyelectrolyte-salmon calcitonin nanocomplexes.

The cationic peptide, salmon calcitonin (sCT) was complexed with the cationic amphiphilic polyelectrolyte, poly(allyl)amine, grafted with palmitoyl and quaternary ammonium moieties at pH 5.0 and 7.4 to yield particulates (sCT-QPa).

Awareness of everyday executive difficulties precede overt executive dysfunction in schizotypal subjects.

Much evidence indicates that schizophrenic patients exhibit deficits on tests of executive functioning. It is therefore hypothesized that individuals with high schizotypal personality traits that may have a predisposition to schizophrenia, are also likely to exhibit impairments in neuropsychological tests of executive function. The sample consisted of 65 healthy controls that were divided into high and low scorers on the Schizotypal Personality Questionnaire (SPQ-B: Raine et al.

Improving computational predictions of cis-regulatory binding sites.

The location of cis-regulatory binding sites determine the connectivity of genetic regulatory networks and therefore constitute a natural focal point for research into the many biological systems controlled by such regulatory networks. Accurate computational prediction of these binding sites would facilitate research into a multitude of key areas, including embryonic development, evolution, pharmacogenemics, cancer and many other transcriptional diseases, and is likely to be an important precursor for the reverse engineering of genome wide, genetic regulatory networks. Many algorithmic strategies have been developed for the computational prediction of cis-regulatory binding sites but currently all approaches are prone to high rates of false positive predictions, and many are highly dependent on additional information, limiting their usefulness as research tools.

The role of global and feature based information in gender classification of faces: a comparison of human performance and computational models.

Most computational models for gender classification use global information (the full face image) giving equal weight to the whole face area irrespective of the importance of the internal features. Here, we use a global and feature based representation of face images that includes both global and featural information. We use dimensionality reduction techniques and a support vector machine classifier and show that this method performs better than either global or feature based representations alone.