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No relationship between proprioception and interoception in university athletes and non-athletes

BIOS 2023年第2期94卷 94-101页

作者： Kiera Borthwick Ryan Brindle Neuroscience Program Washington and Lee University Lexington VA 24450 Department of Cognitive and Behavioral Science Washington and Lee University Lexington VA 24450

Proprioception and interoception are two complex physiological functions believed to be dependent on a variety of factors. The present study examined the relationship between proprioception and interoception in a sample of undergraduate students to determine whether varsity athlete status moderated the relationship, as physical activity levels have been hypothesized to influence both proprioception and interoception. Participants (n = 24) completed two tasks: a heartbeat discrimination test of interoceptive accuracy and a joint position matching test of proprioceptive accuracy at the elbow joint. Participants completed a questionnaire to determine their status as a varsity athlete at the university and the amount of time they dedicated every week to physical activity. The relationship between proprioceptive and interoceptive accuracy scores was analyzed across the entire sample and compared across athletes and non-athletes. Despite differences in physical activity between athletes and non-athletes (p = 0.04, d = 0.87), results revealed no significant relationships between proprioceptive accuracy and interoceptive accuracy in the entire sample (r(22) = 0.16, p = 0.47), in athletes (r(9) = -0.31, p = 0.36), or in non-athletes (r(11) = 0.53, p = 0.06). Also, this relationship did not significantly differ between athletes and non-athletes (q = 0.91, p = 0.06), despite a large effect size. Overall, there were no significant relationships between athlete status, proprioceptive accuracy, and interoceptive accuracy.

关键词： interoceptive sensitivity proprioceptive sensitivity

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Representations of emotion concepts: Comparison across pairwise, appraisal feature-based, and word embedding-based similarity spaces 44

Representations of emotion concepts: Comparison across pairw...

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44th Annual Meeting of the cognitive science Society: cognitive Diversity, CogSci 2022

作者： Kwon, Mijin Wager, Tor D. Phillips, Jonathan Department of Psychological and Brain Sciences Dartmouth College United States Program in Cognitive Science Dartmouth College United States Department of Philosophy Dartmouth College United States

A question that has long interested cognitive scientists is how to best represent the different emotions we experience and attribute to others. For example, constructionist and appraisal theories propose that differences between emotions can be captured in part by their variation along a set of appraisal dimensions. More recently, researchers have used language models to capture the differences across different emotion terms. Both approaches allow us to represent emotions as occupying different locations in high-dimensional representational spaces. To ask how well these different approaches capture the similarity between emotion concepts, we collected pairwise similarity and appraisal feature ratings for 58 different emotion concepts and then employed representational similarity analysis to investigate the overlap between people's pairwise similarity judgments and emotion similarity in a 14-dimensional appraisal space and three word embedding spaces from two word2vec models (300 dimensions) and the newer GPT-3 model (12288 dimensions). The results indicate that while there is a high correlation between appraisal feature-based similarity and pairwise similarity judgments, word embedding-based similarity exhibits lower correlations, though GPT-3 showed much better performance than the word2vec models. Finally, characterizing the errors made by word embedding models showed that they can be largely attributed to an over-reliance on the valence of emotion concepts. © 2022 The Author(s). This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY)

关键词： Embeddings

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Do you see what I see? A meta-analysis of the Dot Perspective Task 43

Do you see what I see? A meta-analysis of the Dot Perspectiv...

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43rd Annual Meeting of the cognitive science Society: Comparative Cognition: Animal Minds, CogSci 2021

作者： Shin, Steven Holland, Catherine Phillips, Jonathan Program in Cognitive Science 23 N Main Street HanoverNH03755 United States

Recent research has found evidence for implicit theory of mind, suggesting that humans quickly and involuntarily compute the mental states of others. One highly influential task within this literature, known as the Dot Perspective Task (DPT), purports to demonstrate implicit visual-perspective taking within adult subjects. However, some studies, consisting of variations of the DPT, have challenged these findings suggesting that the DPT does not demonstrate genuine perspective taking. Instead, they argue that these results are reflective of simple attentional cueing. Additionally, some researchers have argued that the DPT is sensitive to unintended attentional and intentional factors. We report the preliminary findings of an on-ongoing meta-analysis which analyzes participant-level data from 23 experiments and 1381 individual subjects. We find evidence for both directional cueing and implicit perspective taking within the DPT, although the effects of directional cueing are significantly larger. Additionally, we find that the effects of perspective taking are sensitive to attentional and intentional factors. These results cast doubt upon much of the evidence which has been taken to demonstrate implicit theory of mind. At the same time, they suggest that future work may utilize a carefully controlled version of the DPT in order to measure genuine implicit theory of mind more accurately. © cognitive science Society: Comparative Cognition: Animal Minds, CogSci *** rights reserved.

关键词： Automaticity Dot Perspective Task Implicit Submentalizing Theory of Mind Visual Perspective Taking

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The Utilization of Fuzzy Logic and Bollinger Bands to Enhance Trading Decision-Making During the Bitcoin Halving Phase

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Procedia Computer science 2024年 245卷 272-281页

作者： Oscar Adam Darmawan Yaya Heryadi Lukas Lili Ayu Wulandhari Ilvico Sonata Computer Science Department Binus Graduate Program Doctor of Computer Science Bina Nusantara University Jakarta 11480 Indonesia Cognitive Engineering Research Group (CERG) Universitas Katolik Indonesia Atma Jaya Jakarta 12930 Indonesia

The volatile behavior of Bitcoin's price, especially during its halving periods, poses considerable obstacles for forecasting and decision-making in cryptocurrency trading. This paper presents a novel method that combines application fuzzy logic with Bollinger Bands to improve trading decision-making in times of high market volatility. This study conducted an experiment utilizing three fuzzy logic controllers and Bollinger Bands (BB) to determine the strength of buy, hold, and sell signals. This dataset includes the initial and final prices that are used to calculate the BB. The raw and computed values serve as the precise input parameters for the Fuzzy Inference System (FIS). The membership functions were categorized into four levels: very low, low, high, and very high, based on the input default settings utilized by traders. Rulesets were created using fuzzy logic to produce signals that indicate the level of strength of a trading advice. This study evaluate the effectiveness of this hybrid method in comparison to the traditional utilization of the Bollinger Band only indicator and Moving Average Convergence Divergence (MACD) indicator, which is widely favored by traders to identify possible market fluctuations. This methodology involves creating a trading simulation that is based on past Bitcoin halving events. The objective is to assess the efficacy of these strategies in managing heightened volatility. The application of fuzzy logic with the Bollinger Bands model yielded a success rate of 92.47% while analyzing 93 daily data points from the previous Bitcoin halving event on May 11, 2020.

关键词： fuzzy logic crypto price prediction bitcoin bollinger bands macd cryptocurrency

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Downstream Task Performance of Pre-Trained Model For Outdoor Audio Event Classification 9

Downstream Task Performance of Pre-Trained Model For Outdoor...

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9th International Conference on Signal Processing and Intelligent Systems, ICSPIS 2023

作者： Rochadiani, Theresia Herlina Heryadi, Yaya Sonata, Ilvico Lukas Suparta, Wawan Bina Nusantara University Binus Graduate Program- Computer Science Jakarta Indonesia Universitas Katolik Indonesia Atma Jaya Cognitive Engineering Research Group Jakarta Indonesia Institut Teknologi Nasional Yogyakarta Department of Electrical Engineering Yogyakarta Indonesia

ISBN: (纸本)9798350369922

Our surroundings' auditory landscapes are a wealth of knowledge, providing insights into a range of outdoor pursuits. The automatic classification of these actions using audio event detection and classification (AEDC) systems has a great deal of potential applications in environmental monitoring, security, surveillance, and driverless cars. Even though AEDC has advanced significantly in indoor settings, difficulties still exist outside because of the variable and changing acoustic conditions brought on by elements like the weather, different sound sources, and ambient noise from traffic and industry. This study suggests an outdoor audio event categorization model based on convolutional neural networks (CNNs). The suggested model shows passable accuracy by utilizing adaptation to the downstream task using the ESC-50 dataset and transfer learning from a pre-trained model. The effectiveness of multi-class audio classification models in downstream tasks is analyzed in this paper, with an emphasis on the effect of an increasing number of output classes on accuracy. Three models - three, four, and five classes - with different output class configurations are used in the study, and their training and validation accuracies are assessed. Although the accuracy scores above 80% are commendable, the data show a discernible reduction in performance as the number of classes rises. Notably, the three-class model attains a validation accuracy exceeding 90%, whereas the four-class and five-class models exhibit reduced accuracies, falling below 90% and 85%, respectively. © 2023 IEEE.

关键词： Convolutional neural networks

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YOLOS-MCI: Automating Microservices Coupling Index Calculation using Vision Transformers

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Procedia Computer science 2024年 245卷 924-933页

作者： Gintoro Yaya Heryadi Lukas Lili Ayu Wulandhari Ilvico Sonata Computer Science Department BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta 11480 Indonesia Cognitive Engineering Research Group (CERG) Universitas Katolik Indonesia Atma Jaya Jakarta 12930 Indonesia

Microservice Architectures (MSA) provide flexibility and scalability in software development. However, accurately measuring the level of interdependence among Microservices continues to be a difficult task. Precisely evaluating this connection is essential for efficient MSA design, maintenance, and future development. Conventional techniques for assessing Microservice coupling are frequently done by hand, require a significant amount of time, and are susceptible to mistakes. This impedes the capacity to make well-informed judgments regarding the integration and adjustment of services. This study introduces a new method for automating the computation of the Microservice Coupling Index (MCI) by utilizing the You Only Look at One Sequence (YOLOS) object identification technique in combination with Vision Transformer (ViTs) technology. YOLOS is utilized for identifying constituents within Unified Modeling Language (UML) Component Diagrams, facilitating precise classification and effective assessment of coupling. The model exhibits varying performance over multiple Intersection over Union (IoU) thresholds and object sizes, with an average precision (AP) of 0.406 over IoU values ranging from 0.50 to 0.95. The maximum precision is achieved at an IoU of 0.50, with an AP of 0.709. The model demonstrates good performance in identifying smaller components, especially when evaluated at a 0.75 IoU threshold. However, it faces challenges in detecting small items, suggesting potential areas for improvement in future iterations. Initial results indicate that this automation greatly decreases the need for manual, labor-intensive tasks and enhances the precision of measuring coupling in MSA, hence facilitating effective decision-making in service integration and modification. Automating the computation of the coupling index has the potential to significantly influence the design and management of durable and readily controllable microservice architectures.

关键词： Coupling Microservices Microservices Coupling Index UML Component Diagrams Vision Transformer YOLO

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Deep Learning Model for Classifying Public Opinions on Energy Sector IHSG Stocks on the Twitter Social Media Platform

Deep Learning Model for Classifying Public Opinions on Energ...

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2023 International Conference on Artificial Intelligence Robotics, Signal and Image Processing, AIRoSIP 2023

作者： Sulistio, Bambang Heryadi, Yaya Lukas Suparta, Wayan Sonata, Ilvico Binus Graduate Program - Doctor of Computer Science Bina Nusantara University Computer Science Department Jakarta Indonesia Universitas Katolik Indonesia Atma Jaya Cognitive Engineering Research Group Jakarta Indonesia Institut Teknologi Nasional Yogyakarta Faculty of Industrial Technology Department of Electrical Engineering Yogyakarta Indonesia

ISBN: (纸本)9798350327472

Capital market transactions provide an opportunity for investors to acquire ownership of company shares and capital gains, as well as dividends. However, alongside the benefits, there are risks of capital loss and liquidation, leading to stress and depression due to profit targets and decision-making errors. To mitigate the risk of decision-making errors in investment, data analysis is needed, including sentiment analysis, which influences stock prices. This study aims to develop a new deep learning model to classify Indonesian public opinion on JCI stocks, especially the Energy sector, obtained from the Twitter social media platform. The model will perform sentiment analysis and categorize opinions as negative, neutral, or positive. We created a dataset that was trained using Bidirectional Encoder Representations from Transformers (BERT) to summarize the analysis of public sentiment above so that it can assist investors in studying public sentiment as a reference for investing with a yield precision of 76%, Recall of 77%, and F1-score on 76%. © 2023 IEEE.

关键词： Tweets

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The emergence of moral foundations in child language development 44

The emergence of moral foundations in child language develop...

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44th Annual Meeting of the cognitive science Society: cognitive Diversity, CogSci 2022

作者： Ramezani, Aida Liu, Emmy Pinto, Renato Ferreira Lee, Spike W.S. Xu, Yang Department of Computer Science University of Toronto Canada Language Technologies Institute Carnegie Mellon University United States Rotman School of Management Department of Psychology University of Toronto Canada Department of Computer Science Cognitive Science Program University of Toronto Canada

One of the most influential modern theories of morality, Moral Foundations Theory, proposes that morality is formed on innate and shared modular foundations. Psychologists have studied the conceptual development of these moral foundations in childhood, but there exists no comprehensive effort on characterizing the early emergence of moral foundations in naturalistic settings. We explore the emerging order of moral foundations through child and caretaker speech. Using computational methods, we contribute an annotated dataset of moral utterances and find that the individualizing foundations emerge earlier than the binding foundations. Furthermore, caretakers tend to talk more about fairness and degradation, while children talk more about cheating. These results are robust across child gender, family's social class, and race. © 2022 The Author(s). This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY)

关键词： Foundations

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Integrating Machine Learning and cognitive Modeling of Decision Making 1st

Integrating Machine Learning and Cognitive Modeling of Decis...

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1st International Symposium, ToM for Teams 2021

作者： Rahgooy, Taher Venable, K. Brent Trueblood, Jennifer S. University of West Florida PensacolaFL United States PensacolaFL United States Department of Psychological and Brain Sciences and Cognitive Science Program Indiana University BloomingtonIN United States

ISBN: (纸本)9783031216701

Modeling human decision making plays a fundamental role in the design of intelligent systems capable of rich interactions and effective teamwork. In this paper we consider the task of choice prediction in settings with multiple alternatives. cognitive models of decision making can successfully replicate and explain behavioral effects involving uncertainty and interactions among alternatives but are computationally intensive to train. ML approaches excel in terms of choice prediction accuracy, but fail to provide insights on the underlying preference reasoning. We study different degrees of integration of ML and cognitive models for this task. We show, via testing on behavioral data, that our hybrid approach, based on the integration of a neural network and the Multi-alternative Linear Ballistic Accumulator cognitive model, requires significantly less time to train, and allows to capture important cognitive parameters while maintaining similar accuracy to the pure ML approach. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Decision making

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Resting-state functional connectivity in lifelong musicians

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Psychoradiology 2023年第1期3卷 154-161页

作者： Cyrus Eierud Andrew Michael David Banks Edna Andrews Linguistics Program Duke UniversityDurhamNC 27708USA Duke Institute for Brain Sciences Duke UniversityDurhamNC 27708USA Department of Statistical Science Duke UniversityDurhamNC 27708USA Center for Cognitive Neuroscience Duke UniversityDurhamNC 27708USA

Background:It has been postulated that musicianship can lead to enhanced brain and cognitive reserve,but the neural mechanisms of this effect have been poorly *** professional musicianship in conjunction with novel brain imaging techniques offers a unique opportunity to examine brain network differences between musicians and matched ***:In this study we aim to investigate how resting-state functional networks(FNs)manifest in lifelong active *** will evaluate the FNs of lifelong musicians and matched healthy controls using resting-state functional magnetic resonance ***:We derive FNs using the data-driven independent component analysis approach and analyze the functional network con-nectivity(FNC)between the default mode(DMN),sensory-motor(SMN),visual(VSN),and auditory(AUN)*** examine whether the linear regressions between FNC and age are different between the musicians and the control ***:The age trajectory of average FNC across all six pairs of FNs shows significant differences between musicians and *** show an increase in average FNC with age while controls show a decrease(P=0.013).When we evaluated each pair of FN,we note that in musicians FNC values increased with age in DMN–AUN,DMN–VSN,and SMN–VSN and in controls FNC values decreased with age in DMN–AUN,DMN–SMN,AUN–SMN,and SMN–***:This result provides early evidence that lifelong musicianship may contribute to enhanced brain and cognitive *** of this study are preliminary and need to be replicated with a larger number of participants.

关键词： resting-state fMRI lifelong musicianship default mode network sensory-motor network functional network connectivity cognitive reserve

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