Helsinki University of Technology

About: Helsinki University of Technology is a based out in . It is known for research contribution in the topics: Artificial neural network & Finite element method. The organization has 8962 authors who have published 20136 publications receiving 723787 citations. The organization is also known as: TKK & Teknillinen korkeakoulu.

Cognitive control in auditory working memory is enhanced in musicians

Abstract: Musical competence may confer cognitive advantages that extend beyond processing of familiar musical sounds Behavioural evidence indicates a general enhancement of both working memory and attention in musicians It is possible that musicians, due to their training, are better able to maintain focus on task-relevant stimuli, a skill which is crucial to working memory We measured the blood oxygenation-level dependent (BOLD) activation signal in musicians and non-musicians during working memory of musical sounds to determine the relation among performance, musical competence and generally enhanced cognition All participants easily distinguished the stimuli We tested the hypothesis that musicians nonetheless would perform better, and that differential brain activity would mainly be present in cortical areas involved in cognitive control such as the lateral prefrontal cortex The musicians performed better as reflected in reaction times and error rates Musicians also had larger BOLD responses than non-musicians in neuronal networks that sustain attention and cognitive control, including regions of the lateral prefrontal cortex, lateral parietal cortex, insula, and putamen in the right hemisphere, and bilaterally in the posterior dorsal prefrontal cortex and anterior cingulate gyrus The relationship between the task performance and the magnitude of the BOLD response was more positive in musicians than in non-musicians, particularly during the most difficult working memory task The results confirm previous findings that neural activity increases during enhanced working memory performance The results also suggest that superior working memory task performance in musicians rely on an enhanced ability to exert sustained cognitive control This cognitive benefit in musicians may be a consequence of focused musical training

Process Monitoring and Modeling Using the Self-Organizing Map

Abstract: The Self-Organizing Map (SOM) is a powerful neural network method for analysis and visualization of high-dimensional data. It maps nonlinear statistical dependencies between high-dimensional measurement data into simple geometric rela- tionships on a usually two-dimensional grid. The mapping roughly preserves the most important topological and metric relationships of the original data elements and, thus, inherently clusters the data. The need for visualization and clustering occurs, for instance, in the analysis of various engineering problems. In this paper, the SOM has been applied in monitoring and modeling of complex industrial processes. Case studies, including pulp process, steel production, and paper industry are described.