Introduction: Working memory (WM) is a multi-component model that among others involves the two processes of filtering and storage. The first reflects the necessity to inhibit irrelevant information from entering memory, whereas the latter refers to the active maintenance of object representations in memory. In this study, we aimed at a) redefining the neuronal networks sustaining filtering and storage within visual working memory by avoiding shortcomings of prior studies, and b) assessing age-related changes in these networks.
Methods: We designed a new paradigm that strictly controlled for perceptual load by presenting the same number of stimuli in each of three conditions. We calculated fMRI contrasts between a baseline condition (low filter and low storage load) and conditions that posed high demands on filtering and storage, respectively, in large samples of younger (= 40) and elder (= 38) participants.
Results: Our approach of comparing contrasts between groups revealed more extensive filter and storage WM networks than previous studies. In the younger group, filtering involved the bilateral insulae, the right occipital cortex, the right brainstem, and the right cerebellum. In the elder group, filtering was associated with the bilateral insulae, right precuneus, and bilateral ventromedial prefrontal cortex. An extensive neuronal network was also found during storage of information in the bilateral posterior parietal cortex, the left ventromedial prefrontal cortex, and the right precuneus in the younger participants. In addition to these brain regions, elder participants recruited the bilateral ventral prefrontal cortex, the superior, middle and inferior and temporal cortex, the left cingulum and the bilateral parahippocampal cortex.
Conclusions: In general, elder participants recruited more brain regions in comparison to younger participants to reach similar accuracy levels. Furthermore, in elder participants one brain region emerged in both contrasts, namely the left ventromedial prefrontal cortex. Hence, elder participants seem to routinely recruit this brain region in demanding tasks, irrespective of whether filtering or storing is challenged.
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http://dx.doi.org/10.1002/brb3.544 | DOI Listing |
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Department of Computer Science and Engineering, College of Engineering, Anna University, Guindy, Chennai, Tamilnadu, India.
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School of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, AZ, 85281, USA.
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View Article and Find Full Text PDFGround Water
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Faculty of Civil Engineering and Geosciences, Delft University of Technology, Delft, The Netherlands.
Drilling wells in unconsolidated formations is commonly undertaken to extract drinking water and other applications, such as aquifer thermal energy storage (ATES). To increase the efficiency of an ATES system, the drilling campaigns are targeting greater depths and enlarging the wellbore diameter in the production section to enhance the flow rates. In these cases, wells are more susceptible to collapse.
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Department of Biomedical Physiology and Kinesiology, 8888 University Dr., Burnaby, BC, V5A 1S6, Canada.
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Sensors (Basel)
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ZHONGNENG Integrated Smart Energy Technology Co., Ltd., Beijing 100013, China.
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