There is inconsistent evidence demonstrating a relationship between task complexity and hand preference. However, analyzing the point at which task complexity overrides the decision to demonstrate a biomechanically efficient movement can enable complexity to be quantified. Young children (ages 3-7), adolescents (ages 8-12), young adults (ages 18-25), and older adults (ages 65+) performed a newly developed Hand Selection Complexity Task (HSCT) and completed the Waterloo Handedness Questionnaire (WHQ). The HSCT included a reciprocal Fitts' tapping task performed in the contralateral space (i.e., same side as preferred hand), followed by ipsilateral space (i.e., opposite side of preferred hand). An alternating contralateral-ipsilateral pattern enabled the participant to progress through six levels of difficulty in three conditions (manipulating target amplitude, width, and combined factors). As participants were free to perform with whichever hand (i.e., preferred, non-preferred) they deemed most appropriate, the level of difficulty where a hand switch occurred was identified. HSCT completion time and error scores were also computed. Findings revealed age to be a significant predictor of dependent measures when considering significant effects and interactions. Combined with the covariate WHQ score as a significant predictor of HSCT time and errors (in some, but not all cases), it can be argued that age-related effects reflect the development of handedness, and changes in strength of handedness across the lifespan. Together, findings suggest that task complexity plays an important role in hand selection when performing a task of increasing difficulty. It appears that task complexity will take precedent over object proximity and biomechanical efficiency, at a certain point, in order to complete the movement with the preferred hand. This point ultimately changes throughout the lifespan.
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http://dx.doi.org/10.3389/fpsyg.2019.01130 | DOI Listing |
ESMO Open
January 2025
Office of Quality and Value, The University of Texas MD Anderson Cancer Center, Houston, USA.
Many patients with cancer approaching the end of life (EOL) continue to receive treatments that are unlikely to provide meaningful clinical benefit, potentially causing more harm than good. This is called overtreatment at the EOL. Overtreatment harms patients by causing side-effects, increasing health care costs, delaying important discussions about and preparation for EOL care, and occasionally accelerating death.
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Department of Radiology, Charles E. Schmidt College of Medicine, Florida Atlantic University, Boca Raton, FL 33431 (M.R.). Electronic address:
Large Language Models (LLMs) such as ChatGPT have been increasingly integrated into radiology research, revolutionizing the research landscape. The Radiology Research Alliance (RRA) of the Association for Academic Radiology (AAR) has convened a Task Force to develop this guide to help radiology researchers responsibly adopt LLM technologies. LLMs can improve various phases of the research process by helping to automate literature reviews, generate research questions, analyze complex datasets, and draft manuscripts.
View Article and Find Full Text PDFCell Rep
January 2025
Institut Interdisciplinaire de Neurosciences (IINS), University Bordeaux, CNRS, IINS, UMR 5297, 33000 Bordeaux, France; Centre Broca Nouvelle-Aquitaine, 146, rue Léo-Saignat, 33076 Bordeaux, France. Electronic address:
Optimal decision-making depends on interconnected frontal brain regions, enabling animals to adapt decisions based on internal states, experiences, and contexts. The secondary motor cortex (M2) is key in adaptive behaviors in expert rodents, particularly in encoding decision values guiding complex probabilistic tasks. However, its role in deterministic tasks during initial learning remains uncertain.
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