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Sylvester S, Sagehorn M, Gruber T, Atzmueller M, Schöne B. SHAP value-based ERP analysis (SHERPA): Increasing the sensitivity of EEG signals with explainable AI methods. Behav Res Methods 2024:10.3758/s13428-023-02335-7. [PMID: 38453828 DOI: 10.3758/s13428-023-02335-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/27/2023] [Indexed: 03/09/2024]
Abstract
Conventionally, event-related potential (ERP) analysis relies on the researcher to identify the sensors and time points where an effect is expected. However, this approach is prone to bias and may limit the ability to detect unexpected effects or to investigate the full range of the electroencephalography (EEG) signal. Data-driven approaches circumvent this limitation, however, the multiple comparison problem and the statistical correction thereof affect both the sensitivity and specificity of the analysis. In this study, we present SHERPA - a novel approach based on explainable artificial intelligence (XAI) designed to provide the researcher with a straightforward and objective method to find relevant latency ranges and electrodes. SHERPA is comprised of a convolutional neural network (CNN) for classifying the conditions of the experiment and SHapley Additive exPlanations (SHAP) as a post hoc explainer to identify the important temporal and spatial features. A classical EEG face perception experiment is employed to validate the approach by comparing it to the established researcher- and data-driven approaches. Likewise, SHERPA identified an occipital cluster close to the temporal coordinates for the N170 effect expected. Most importantly, SHERPA allows quantifying the relevance of an ERP for a psychological mechanism by calculating an "importance score". Hence, SHERPA suggests the presence of a negative selection process at the early and later stages of processing. In conclusion, our new method not only offers an analysis approach suitable in situations with limited prior knowledge of the effect in question but also an increased sensitivity capable of distinguishing neural processes with high precision.
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Affiliation(s)
- Sophia Sylvester
- Institute of Computer Science, Osnabrück University, Osnabrück, Germany
- Department of Mental Health, Norwegian University of Science and Technology, Trondheim, Norway
| | - Merle Sagehorn
- Institute of Psychology, Osnabrück University, Osnabrück, Germany
| | - Thomas Gruber
- Institute of Psychology, Osnabrück University, Osnabrück, Germany
| | - Martin Atzmueller
- Institute of Computer Science, Osnabrück University, Osnabrück, Germany
- German Research Center for Artificial Intelligence (DFKI), Osnabrück, Germany
| | - Benjamin Schöne
- Institute of Psychology, Osnabrück University, Osnabrück, Germany.
- Department of Psychology, Norwegian University of Science and Technology, Trondheim, Norway.
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Abstract
In order to support the burgeoning field of research into intra- and interpersonal synchrony, we present an open-source software package: multiSyncPy. Multivariate synchrony goes beyond the bivariate case and can be useful for quantifying how groups, teams, and families coordinate their behaviors, or estimating the degree to which multiple modalities from an individual become synchronized. Our package includes state-of-the-art multivariate methods including symbolic entropy, multidimensional recurrence quantification analysis, coherence (with an additional sum-normalized modification), the cluster-phase 'Rho' metric, and a statistical test based on the Kuramoto order parameter. We also include functions for two surrogation techniques to compare the observed coordination dynamics with chance levels and a windowing function to examine time-varying coordination for most of the measures. Taken together, our collation and presentation of these methods make the study of interpersonal synchronization and coordination dynamics applicable to larger, more complex and often more ecologically valid study designs. In this work, we summarize the relevant theoretical background and present illustrative practical examples, lessons learned, as well as guidance for the usage of our package - using synthetic as well as empirical data. Furthermore, we provide a discussion of our work and software and outline interesting further directions and perspectives. multiSyncPy is freely available under the LGPL license at: https://github.com/cslab-hub/multiSyncPy , and also available at the Python package index.
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Affiliation(s)
- Dan Hudson
- Semantic Information Systems Group, Institute of Computer Science, Osnabrück University, P.O. Box 4469, 49069, Osnabrueck, Germany.
- Department of Cognitive Science and Artificial Intelligence, Tilburg University, Tilburg, The Netherlands.
| | - Travis J Wiltshire
- Department of Cognitive Science and Artificial Intelligence, Tilburg University, Tilburg, The Netherlands
| | - Martin Atzmueller
- Semantic Information Systems Group, Institute of Computer Science, Osnabrück University, P.O. Box 4469, 49069, Osnabrueck, Germany
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Swaminathan HB, Sommer A, Becker A, Atzmueller M. Performance Evaluation of GNSS Position Augmentation Methods for Autonomous Vehicles in Urban Environments. Sensors (Basel) 2022; 22:8419. [PMID: 36366117 PMCID: PMC9657055 DOI: 10.3390/s22218419] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/28/2022] [Revised: 10/25/2022] [Accepted: 10/26/2022] [Indexed: 06/16/2023]
Abstract
Global Navigation Satellite Systems provide autonomous vehicles with precise position information through the process of position augmentation. This paper presents a series of performance tests aimed to compare the position accuracy of augmentation techniques such as classical Differential Global Navigation Satellite System, Real-time Kinematic and Real-time eXtended. The aim is to understand the limitations and choose the best position augmentation technique in order to obtain accurate, trustworthy position estimates of a vehicle in urban environments. The tests are performed in and around the German cities of Wuppertal and Duesseldorf, using a vehicle fitted with the navigation system POS-LV 220, developed by Applanix Corporation. In order to evaluate the real-time performance of position augmentation techniques in a highly challenging environment, a total of four test regions are selected. The four test regions are characterized mainly by uneven terrain with tall buildings around the University of Wuppertal, flat terrain with roads of varying width in the city centre of Wuppertal and Duesseldorf and flat terrain in a tunnel section located in the city of Wuppertal. The performances of the different position augmentation are compared using a Root Mean Square (RMS) error estimate obtained as an output from the Applanix system. Furthermore, a High-Definition map of the environment is used for the purpose of model validation, which justifies the use of RMS error estimate as an evaluation metric for the performance analysis tests. According to the performance tests carried out as per the conditions specified in this paper, the Real-time eXtended (RTX) position augmentation method enables to obtain a more robust position information of the vehicle than Real-time Kinematic (RTK) method, with a typical accuracy of a few centimeter in an urban environment.
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Affiliation(s)
| | - Aron Sommer
- Aptiv Services Deutschland GmbH, 42119 Wuppertal, Germany
| | - Andreas Becker
- Faculty of Information Technology, Dortmund University of Applied Science and Arts, 44139 Dortmund, Germany
| | - Martin Atzmueller
- Semantic Information Systems Group, Osnabrück University, 49090 Osnabrück, Germany
- German Research Center for Artificial Intelligence (DKFI), 49090 Osnabrueck, Germany
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Nalepa GJ, Bobek S, Kutt K, Atzmueller M. Semantic Data Mining in Ubiquitous Sensing: A Survey. Sensors (Basel) 2021; 21:4322. [PMID: 34202654 PMCID: PMC8271490 DOI: 10.3390/s21134322] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/22/2021] [Revised: 06/15/2021] [Accepted: 06/18/2021] [Indexed: 12/20/2022]
Abstract
Mining ubiquitous sensing data is important but also challenging, due to many factors, such as heterogeneous large-scale data that is often at various levels of abstraction. This also relates particularly to the important aspects of the explainability and interpretability of the applied models and their results, and thus ultimately to the outcome of the data mining process. With this, in general, the inclusion of domain knowledge leading towards semantic data mining approaches is an emerging and important research direction. This article aims to survey relevant works in these areas, focusing on semantic data mining approaches and methods, but also on selected applications of ubiquitous sensing in some of the most prominent current application areas. Here, we consider in particular: (1) environmental sensing; (2) ubiquitous sensing in industrial applications of artificial intelligence; and (3) social sensing relating to human interactions and the respective individual and collective behaviors. We discuss these in detail and conclude with a summary of this emerging field of research. In addition, we provide an outlook on future directions for semantic data mining in ubiquitous sensing contexts.
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Affiliation(s)
- Grzegorz J. Nalepa
- Institute of Applied Computer Science and Jagiellonian Human-Centered Artificial Intelligence Laboratory (JAHCAI), ul. Prof. Stanislawa Lojasiewicza 11, Jagiellonian University, 30-348 Krakow, Poland; (S.B.); (K.K.)
- Department of Applied Computer Science, AGH University of Science and Technology, Al. Mickiewicza 30, 30-059 Krakow, Poland
| | - Szymon Bobek
- Institute of Applied Computer Science and Jagiellonian Human-Centered Artificial Intelligence Laboratory (JAHCAI), ul. Prof. Stanislawa Lojasiewicza 11, Jagiellonian University, 30-348 Krakow, Poland; (S.B.); (K.K.)
- Department of Applied Computer Science, AGH University of Science and Technology, Al. Mickiewicza 30, 30-059 Krakow, Poland
| | - Krzysztof Kutt
- Institute of Applied Computer Science and Jagiellonian Human-Centered Artificial Intelligence Laboratory (JAHCAI), ul. Prof. Stanislawa Lojasiewicza 11, Jagiellonian University, 30-348 Krakow, Poland; (S.B.); (K.K.)
| | - Martin Atzmueller
- Semantic Information Systems Group, Osnabrück University, 49074 Osnabrück, Germany
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Abstract
AbstractFinding communities that are not only relatively densely connected in a graph but that also show similar characteristics based on attribute information has drawn strong attention in the last years. There exists already a remarkable body of work that attempts to find communities in vertex-attributed graphs that are relatively homogeneous with respect to attribute values. Yet, it is scattered through different research fields and most of those publications fail to make the connection. In this paper, we identify important characteristics of the different approaches and place them into three broad categories: those that select descriptive attributes, related to clustering approaches, those that enumerate attribute-value combinations, related to pattern mining techniques, and those that identify conditional attribute weights, allowing for post-processing. We point out that the large majority of these techniques treat the same problem in terms of attribute representation, and are therefore interchangeable to a certain degree. In addition, different authors have found very similar algorithmic solutions to their respective problem.
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Güven Ç, Atzmueller M. Applying Answer Set Programming for Knowledge-Based Link Prediction on Social Interaction Networks. Front Big Data 2019; 2:15. [PMID: 33693338 PMCID: PMC7931864 DOI: 10.3389/fdata.2019.00015] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2019] [Accepted: 05/28/2019] [Indexed: 11/29/2022] Open
Abstract
Link prediction targets the prediction of possible future links in a social network, i. e., we aim to predict the next most likely links of the network given the current state. However, predicting the future solely based on (scarce) historic data is often challenging. In this paper, we investigate, if we can make use of additional (domain) knowledge to tackle this problem. For this purpose, we apply answer set programming (ASP) for formalizing the domain knowledge for social network (and graph) analysis. In particular, we investigate link prediction via ASP based on node proximity and its enhancement with background knowledge, in order to test intuitions that common features, e. g., a common educational background of students, imply common interests. In addition, then the applied ASP formalism enables explanation-aware prediction approaches.
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Affiliation(s)
- Çiçek Güven
- Computational Sensemaking Lab, Department of Cognitive Science and Artificial Intelligence, Tilburg University, Tilburg, Netherlands
| | - Martin Atzmueller
- Computational Sensemaking Lab, Department of Cognitive Science and Artificial Intelligence, Tilburg University, Tilburg, Netherlands
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Thiele L, Sauer NC, Atzmueller M, Kauffeld S. The co-evolution of career aspirations and peer relationships in psychology bachelor students: A longitudinal social network study. Journal of Vocational Behavior 2018. [DOI: 10.1016/j.jvb.2017.12.005] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
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Mitzlaff F, Atzmueller M, Hotho A, Stumme G. The social distributional hypothesis: a pragmatic proxy for homophily in online social networks. Soc Netw Anal Min 2014. [DOI: 10.1007/s13278-014-0216-2] [Citation(s) in RCA: 44] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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Atzmueller M, Becker M, Kibanov M, Scholz C, Doerfel S, Hotho A, Macek BE, Mitzlaff F, Mueller J, Stumme G. Ubicon and its applications for ubiquitous social computing. NEW REV HYPERMEDIA M 2014. [DOI: 10.1080/13614568.2013.873488] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
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Atzmueller M, Baumeister J, Puppe F. Semi-automatic learning of simple diagnostic scores utilizing complexity measures. Artif Intell Med 2006; 37:19-30. [PMID: 16242309 DOI: 10.1016/j.artmed.2005.03.003] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2004] [Revised: 03/18/2005] [Accepted: 03/21/2005] [Indexed: 12/29/2022]
Abstract
OBJECTIVE Knowledge acquisition and maintenance in medical domains with a large application domain ontology is a difficult task. To reduce knowledge elicitation costs, semi-automatic learning methods can be used to support the domain specialists. They are usually not only interested in the accuracy of the learned knowledge: the understandability and interpretability of the learned models is of prime importance as well. Then, often simple models are more favorable than complex ones. METHODS AND MATERIAL We propose diagnostic scores as a promising approach for the representation of simple diagnostic knowledge, and present a method for inductive learning of diagnostic scores. It can be incrementally refined by including background knowledge. We present complexity measures for determining the complexity of the learned scores. RESULTS We give an evaluation of the presented approach using a case base from the fielded system SonoConsult. We further discuss that the user can easily balance between accuracy and complexity of the learned knowledge applying the presented measures. CONCLUSIONS We argue that semi-automatic learning methods can support the domain specialist efficiently when building (diagnostic) knowledge systems from scratch. The presented complexity measures allow for an intuitive assessment of the learned patterns.
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Affiliation(s)
- Martin Atzmueller
- Department of Computer Science, University of Würzburg, Am Hubland, 97074 Würzburg, Germany.
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Atzmueller M, Baumeister J, Hemsing A, Richter EJ, Puppe F. Subgroup Mining for Interactive Knowledge Refinement. Artif Intell Med 2005. [DOI: 10.1007/11527770_61] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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Kohl JV, Atzmueller M, Fink B, Grammer K. Human pheromones: integrating neuroendocrinology and ethology. Neuro Endocrinol Lett 2001; 22:309-21. [PMID: 11600881] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Received: 08/06/2001] [Accepted: 09/10/2001] [Indexed: 02/21/2023]
Abstract
The effect of sensory input on hormones is essential to any explanation of mammalian behavior, including aspects of physical attraction. The chemical signals we send have direct and developmental effects on hormone levels in other people. Since we don t know either if, or how, visual cues might have direct and developmental effects on hormone levels in other people, the biological basis for the development of visually perceived human physical attraction is currently somewhat questionable. In contrast, the biological basis for the development of physical attraction based on chemical signals is well detailed.
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Affiliation(s)
- J V Kohl
- JVK Resources, Inc. Las Vegas, Nevada, USA
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