Mental set switching is a key facet of executive control measured behaviorally through reaction time or accuracy (i.e., 'switch costs') when shifting among task types. One of several experimentally dissociable influences on switch costs is 'task set inertia', conceptualized as the residual interference conferred when a previous stimulus-response tendency interferes with subsequent stimulus processing on a new task. Task set inertia is thought to represent the passive decay of the previous stimulus-response set from working memory, and its effects decrease with increased interstimulus interval. Closely spaced trials confer high task set inertia, while sparsely spaced trials confer low task set inertia. This functional magnetic resonance imaging (fMRI) study characterized, for the first time, two opposing brain systems engaged to resolve task set inertia: 1) a frontoparietal 'cortical control' network for overcoming high task set inertia interference and 2) a subcortical-motor network more active during trials with low task set inertia. These networks were distinct from brain regions showing general switching effects (i.e., switch>non-switch) and from other previously characterized interference effects. Moreover, there were ongoing maturational effects throughout adolescence for the brain regions engaged to overcome high task set inertia not seen for generalized switching effects. These novel findings represent a new avenue of exploration of cognitive set switching neural function.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3482401 | PMC |
http://dx.doi.org/10.1016/j.neuroimage.2012.05.007 | DOI Listing |
Front Robot AI
December 2024
Department of Cognitive Robotics, Delft University of Technology, Delft, Netherlands.
In recent years, providing additional visual feedback about the interaction forces has been found to offer benefits to haptic-assisted teleoperation. However, there is limited insight into the effects of the design of force feedback-related visual cues and the type of visual display on the performance of teleoperation of robotic arms executing industrial tasks. In this study, we provide new insights into this interaction by extending these findings to the haptic assistance teleoperation of a simulated robotic arm in a virtual environment, in which the haptic assistance is comprised of a set of virtual fixtures.
View Article and Find Full Text PDFNeural Netw
December 2024
Faculty of Information Technology and Electrical Engineering, University of Oulu, Finland.
Real-time online optimisation plays a crucial role in high-frequency trading (HFT) strategies. The Markowitz model, as a Nobel Prize-winning framework, is widely used for portfolio management optimisation by framing the problem as a constrained quadratic programming task. While conventional analytical methods are typically effective for solving quadratic programming problems with linear constraints, the introduction of both linear equality and inequality constraints in the Markowitz model necessitates the use of numerical methods.
View Article and Find Full Text PDFJ Indian Soc Periodontol
December 2024
Department of Periodontology, Rajendra Institute of Medical Sciences, Ranchi, Jharkhand, India.
Background: For a periodontist, treating recession is always a proud moment and a challenging task. The current trial aimed at comparing and clinically evaluating semilunar coronally repositioned flap (SCRF) and coronally advanced flap (CAF) procedures combined with platelet-rich fibrin (PRF) in the management of Miller's Class I recession defects.
Materials And Methods: Thirty-six recession sites were randomly divided into the CAF or SCRF groups.
Front Hum Neurosci
December 2024
Department of Biomedical Engineering, Izmir Katip Celebi University, Izmir, Türkiye.
Introduction: Motor Imagery (MI) Electroencephalography (EEG) signals are non-stationary and dynamic physiological signals which have low signal-to-noise ratio. Hence, it is difficult to achieve high classification accuracy. Although various machine learning methods have already proven useful to that effect, the use of many features and ineffective EEG channels often leads to a complex structure of classifier algorithms.
View Article and Find Full Text PDFTransl Psychiatry
December 2024
Department of Psychiatry and Psychotherapy, University Hospital Bonn, Bonn, Germany.
Given the heterogeneous nature of attention-deficit/hyperactivity disorder (ADHD) and the absence of established biomarkers, accurate diagnosis and effective treatment remain a challenge in clinical practice. This study investigates the predictive utility of multimodal data, including eye tracking, EEG, actigraphy, and behavioral indices, in differentiating adults with ADHD from healthy individuals. Using a support vector machine model, we analyzed independent training (n = 50) and test (n = 36) samples from two clinically controlled studies.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!