This paper focuses on the impact of long-term Antarctic conditions on cognitive processes. Behavioral responses and event-related potentials were recorded during an auditory distraction task and an attention network paradigm. Participants were members of the over-wintering crew at Concordia Antarctic Research Station. Due to the reduced partial pressure of oxygen this environment caused moderate hypoxia. Beyond the hypoxia, the fluctuation of sunshine duration, isolation and confinement were the main stress factors of this environment. We compared 6 measurement periods completed during the campaign. Behavioral responses and N1/MMN (mismatch negativity), N1, N2, P3, RON (reorientation negativity) event-related potential components have been analyzed. Reaction time decreased in both tasks in response to repeated testing during the course of mission. The alerting effect increased, the inhibition effect decreased and the orienting effect did not change in the ANT task. Contrary to our expectations the N2, P3, RON components related to the attentional functions did not show any significant changes. Changes attributable to early stages of information processing were observed in the ANT task (N1 component) but not in the distraction task (N1/MMN). The reaction time decrements and the N1 amplitude reduction in ANT task could be attributed to sustained effect of practice. We conclude that the Antarctic conditions had no negative impacts on cognitive activity despite the presence of numerous stressors.
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http://dx.doi.org/10.3389/fnhum.2016.00331 | DOI Listing |
Cortex
December 2024
Department of Psychology and the Zelman Center for Brain Science, Ben-Gurion University, Be'er-Sheva, Israel.
Posner and Petersen (1990) suggested that the attention system is composed of three networks: alerting, orienting, and executive functioning or control. Drawing on this theory, the Attentional Networks Test (ANT) was designed to quantify the functionality of the three attention networks. The ANT is used extensively in psychology, neuroscience, and medicine.
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December 2024
Zhejiang University, Hangzhou, China.
As the parameter size of large language models (LLMs) continues to expand, there is an urgent need to address the scarcity of high-quality data. In response, existing research has attempted to make a breakthrough by incorporating federated learning (FL) into LLMs. Conversely, considering the outstanding performance of LLMs in task generalization, researchers have also tried applying LLMs within FL to tackle challenges in relevant domains.
View Article and Find Full Text PDFMol Ecol
January 2025
Institute of Organismic and Molecular Evolution, Johannes Gutenberg University, Mainz, Germany.
Social insects form complex societies with division of labour between different female castes. In most species, a single queen heads the colony; in others, several queens share the task of reproduction. These different social organisations are often associated with distinct queen morphologies and life-history strategies and occur in different environments.
View Article and Find Full Text PDFSci Rep
January 2025
Grupo de Investigación Ecología y Evolución en los Trópicos-EETrop, Universidad de Las Américas, Quito, Ecuador.
Forecasting insect responses to environmental variables at local and global spatial scales remains a crucial task in Ecology. However, predicting future responses requires long-term datasets, which are rarely available for insects, especially in the tropics. From 2002 to 2017, we recorded male ant incidence of 155 ant species at ten malaise traps on the 50-ha ForestGEO plot in Barro Colorado Island.
View Article and Find Full Text PDFCurr Biol
December 2024
Department of Evolutionary Biology and Ecology, Institute of Biology I, University of Freiburg, Hauptstraße 1, 79104 Freiburg, Germany. Electronic address:
Recognition protects biological systems at all scales, from cells to societies. Social insects recognize their nestmates by colony-specific olfactory labels that individuals store as neural templates in their memory. Throughout an ant's life, learning continuously shapes the nestmate recognition template to keep up with the constant changes in colony labels.
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