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Dynamic rewiring of electrophysiological brain networks during learning
(2023-06-30) Ruggeri, Paolo; Miehlbradt, Jenifer; Kabbara, Aya; Hassan, Mahmoud
Human learning is an active and complex process. However, the brain mechanisms underlying human skill learning and the effect of learning on the communication between brain regions, at different frequency bands, are still largely unknown. Here, we tracked changes in large-scale electrophysiological networks over a 6-week training period during which participants practiced a series of motor sequences during 30 home training sessions. Our findings showed that brain networks become more flexible with learning in all the frequency bands from theta to gamma ranges. We found consistent increase of flexibility in the prefrontal and limbic areas in the theta and alpha band, and over somatomotor and visual areas in the alpha band. Specific to the beta rhythm, we revealed that higher flexibility of prefrontal regions during the early stage of learning strongly correlated with better performance measured during home training sessions. Our findings provide novel evidence that prolonged motor skill practice results in higher, frequency-specific, temporal variability in brain network structure.
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Reproducibility Companion Paper : MeTILDA - Platform for Melodic Transcription in Language Documentation and Application
(Association for Computing Machinery, Inc, 2023-06-12) Lee, Mitchell; Lee, Chris; Penmetsa, Sanjay; Chen, Min; Miyashita, Mizuki; Fish, Naatosi; Wu, Bo; Khan, Omar
This companion paper supports the replication of the development and evaluation of "MeTILDA - Platform for Melodic Transcription in Language Documentation and Application"that we presented in the ICMR 2021. MeTILDA aims to help document and analyze pitch patterns of endangered languages including Blackfoot, whose prosodic system is characterized by pitch movements. It develops a new form of audio analysis (termed MeT scale which is a perceptual scale) and automates the process of creating visual aids (Pitch Art) to provide more effective visuals of perceived changes in pitch movement. In this paper, we explain the file structure of the source code and publish the details of our data as well as system operations. Moreover, we provide a link to the demo video for facilitating the use of our platform.
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Energy Management and Network Traffic Avoidance Using GAODM and E-AODV Protocols in Mobile Ad-Hoc Network
(2023-06-01) Vatambeti, Ramesh; Pradhan, Nrusingha Charan; Sandhya, E.; Vinta, Surendra Reddy; Anbarasu, V.; Venkateswara Rao, K.
Because of the mobility of its nodes, MANET plays a significant role in mobile communication. As a result, network infrastructure is frequently changed, resulting in data loss and communication overheads. Despite this, the large packet size causes network congestion or traffic. The difficult task is efficient routing through a dynamic network. For node generation and energy management, the proposed approach in this paper employs GAODM (Geography-based Ad-hoc On Demand disjoint multipath) and E-AODM (Energy Ad-hoc On Demand Vector routing). The proposed GAODM routing protocol reduces congestion using Spider Monkey (SM) Optimization. The E-AODM protocol assesses the energy management solution based on parameters such as delay, energy consumption, routing overhead, and node energy. By choosing the best path through the network, the proposed protocol's effectiveness is increased. The proposed protocol reduces routing overload, delay, and congestion. The simulated results show that increasing the number of packets transmitted in the network using the proposed GAODM and E-AODM routing protocols over the existing protocols on NS 2 reduces node energy and, as a result, overload and delay.
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Successful reproduction of a large EEG study across software packages
(2023-06) Kabbara, Aya; Forde, Nina; Maumet, Camille; Hassan, Mahmoud
As an active field of research and with the development of state-of-the-art algorithms to analyze EEG datasets, the parametrization of Electroencephalography (EEG) analysis workflows has become increasingly flexible and complex, with a great variety of methodological options and tools to be selected at each step. This high analytical flexibility can be problematic as it can yield to variability in research outcomes. Therefore, growing attention has been recently paid to understand the potential impact of different methodological decisions on the reproducibility of results. In this paper, we aim to examine how sensitive the results of EEG analyses are to variations in preprocessing with different software tools. We reanalyzed the shared EEG data (N = 500) from (Williams et al., 2021) using three of the most commonly used open-source Matlab-based EEG software tools: EEGLAB, Brainstorm and FieldTrip. After reproducing the same original preprocessing workflow in each software, the resulting event-related potentials (ERPs) were qualitatively and quantitatively compared in order to examine the degree of consistency/discrepancy between software packages. Our findings show a good degree of convergence in terms of the general profile of ERP waveforms, peak latencies and effect size estimates related to specific signal features. However, considerable variability was also observed in the magnitude of the absolute voltage observed with each software package as reflected by the similarity values and observed statistical differences at particular channels and time instants. In conclusion, we believe that this study provides valuable clues to better understand the impact of the software tool on the analysis of EEG results.
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Analyzing the Relationship between Participation in Sports and Harmful Alcohol Drinking in Early Adolescence : Two-Year Prospective Analysis
(2023-06) Zenic, Natasa; Kvesic, Ivan; Corluka, Mate; Trivic, Tatjana; Drid, Patrik; Saavedra, Jose M.; Foretic, Nikola; Modric, Toni; Gilic, Barbara; Department of Sport Science
Alcohol drinking is an important health-related problem and one of the major risk factors for a wide array of non-communicable diseases, while there is a lack of studies investigating environment-specific associations between sports participation and alcohol drinking in adolescence. This study prospectively investigated the relationship between sports factors (i.e., participation in sports and competitive achievement), with the prevalence of harmful alcohol drinking (HD), and HD initiation in 14-to-16 years old adolescents from Bosnia and Herzegovina (n = 641, 337 females, 43% living in rural community). Participants were tested over 4-time points divided by approximately 6 months, from the beginning of high school to the end of the second grade. Variables included gender, factors related to sport participation, a community of residence (urban or rural), and outcome: alcohol consumption was assessed by the AUDIT questionnaire. Results evidenced that the prevalence of HD increased over the study period from 6 to 19%, with no significant differences between urban and rural youth. Logistic regression for HD as criterion evidenced adolescents who participated in sports and then quit as being at particular risk for drinking alcohol at the study baseline. Sports factors were not correlated with HD initiation in the period between 14 and 16 years of age. It seems that the problem of alcohol drinking should be preventively targeted in all youth, irrespective of living environment. Although sports participation was not evidenced as being a factor of influence on HD initiation, results highlight the necessity of developing targeted preventive campaigns against alcohol drinking for adolescents who quit sports.

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