17 research outputs found

    Conflict Processing Across Development: The Progression of Response Inhibition Networks

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    Cognitive control processes allow individuals to guide their behaviour in the face of distracting or irrelevant stimuli, and typically continue developing into early adulthood. These processes are often tested using response inhibition paradigms such as the size congruency task, which require participants to select between conflicting responses. Previous studies have shown that activity in the dorsolateral prefrontal cortex (DLPFC) and the anterior cingulate cortex (ACC) parallels the protracted development of cognitive control. Recent evidence suggests that children and adolescents may rely on more subcortical regions such as the cerebellum to process conflict. The present study aimed to comprehensively investigate activity in the DLPFC, ACC, and cerebellum during response inhibition across developmental stages, thereby proposing conflict processing neural pathways utilized at various developmental stages. Five children, five adolescent and five adult participants completed a size congruency task while undergoing fMRI scanning. Incongruent trials (25%) elicited conflict processing. Incongruent-congruent contrasts were averaged within groups and compared across groups via visual inspection. While small regions of unilateral DLPFC activity were measured for children and adolescents, adults showed large regions of bilateral DLPFC activity. Children and adolescents showed no ACC activity while adults exhibited bilateral ACC activity. Children showed more widespread cerebellar activity compared to adolescents and adults. In light of these results and recent research findings, we propose a DLPFC-cerebellar conflict processing network in children, with the cerebellum performing conflict resolution by cancelling an ongoing but incorrect motor program. Adults are suggested to utilize a DLPFC-ACC network, where the ACC suppresses a prepotent response before it is initiated. Adolescents show evidence of activity in both networks. Future studies should focus on how conflict processing develops as a network, rather than identifying localized regions of development

    Additional file 1: of Kinematic and kinetic assessment of upper limb movements in patients with writer's cramp

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    Profiles of the Z-scores of the applied forces (Thumb, Index, and Hand), the measured joint angles (wrist, elbow, and shoulder), and the cramp severities on all surfaces for each individual patient. (PDF 241 kb

    Physiological, biochemical, anthropometric and biomechanical influences on exercise economy in humans

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    Inter-individual variation in running and cycling exercise economy (EE) remains unexplained although studied for more than a century. This study is the first to comprehensively evaluate the importance of biochemical, structural, physiological, anthropometric, and biomechanical influences on running and cycling EE within a single study. In 22 healthy males (VO2 max range 45.5 to 72.1 ml.min(-1) .kg(-1) ) no factor related to skeletal muscle structure (% slow twitch fibre content, number of capillaries per fibre), mitochondrial properties (volume density, oxidative capacity, or mitochondrial efficiency) or protein content (UCP3 and MFN2 expression) explained variation in cycling and running EE among subjects. In contrast, biomechanical variables related to vertical displacement correlated well with running EE, but were not significant when taking body weight into account. Thus, running EE and body weight were correlated (R(2) = 0.94; P < 0.001), but was lower for cycling EE (R(2) = 0.23; P < 0.023). To separate biomechanical determinants of running EE we contrasted individual running and cycling EE considering that during cycle ergometer exercise the biomechanical influence on EE would be small because of the fixed movement pattern. Differences in cycling and running exercise protocols, e.g., related to biomechanics, play however only a secondary role in determining EE. There was no evidence for an impact of structural or functional skeletal muscle variables on EE. Body weight was the main determinant of EE explaining 94% of variance in running EE, although more than 50% of the variability of cycling EE remains unexplained
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