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modeling face recognition in the predictive coding framework: A combined computational modeling and functional imaging study

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CORTEX 2023年 168卷 203-225页

作者： Zaragoza-Jimenez, Nestor Niehaus, Hauke Thome, Ina Vogelbacher, Christoph Ende, Gabriele Kamp-Becker, Inge Endres, Dominik Jansen, Andreas Univ Marburg Dept Psychiat Lab Multimodal Neuroimaging Marburg Germany Univ Marburg Ctr Mind Brain & Behav CMBB Giessen Germany Justus Liebig Univ Giessen Giessen Germany Philipps Univ Dept Psychol Theoret Cognit Sci Grp Marburg Germany Heidelberg Univ Med Fac Mannheim Cent Inst Mental Hlth CIMH Dept Psychiat & Psychotherapy Mannheim Germany Univ Marburg Dept Child & Adolescent Psychiat Psychosomat & Psy Marburg Germany Univ Marburg Fac Med Core Facil BrainImaging Marburg Germany Univ Marburg Dept Psychiat Rudolf Bultmann Str 8 D-35039 Marburg Germany

The learning of new facial identities and the recognition of familiar faces are crucial processes for social interactions. Recently, a combined computational modeling and functional magnetic resonance imaging (fMRI) study used predictive coding as a biologically plausible framework to model face identity learning and to relate specific model parameters with brain activity (Apps and Tsakiris, Nat Commun 4, 2698, 2013). On the one hand, it was shown that behavioral responses on a two-option face recognition task could be predicted by the level of contextual and facial familiarity in a computational model derived from predictive-coding principles. On the other hand, brain activity in specific brain regions was associated with these parameters. More specifically, brain activity in the superior temporal sulcus (STS) varied with contextual familiarity, whereas activity in the fusiform face area (FFA) covaried with the prediction error parameter that updated facial familiarity. Literature combining fMRI assessments and computational modeling in humans still needs to be expanded. Furthermore, prior results are largely not replicated. The present study was, therefore, specifically set up to replicate these previous findings. Our results support the original findings in two critical aspects. First, on a group level, the behavioral responses were modeled best by the same computational model reported by the original authors. Second, we showed that estimates of these model parameters covary with brain activity in specific, face-sensitive brain regions. Our results thus provide further evidence that the functional properties of the face perception network conform to central principles of predictive coding. However, our study yielded diverging findings on specific computational model parameters reflected in brain activity. On the one hand, we did not find any evidence of a computational involvement of the STS. On the other hand, our results showed that activity in the right FFA wa

关键词： Face learning computational modeling Predictive coding Functional neuroimaging Functional magnetic resonance imaging fMRI Core system FFA pSTS

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Toward Ontological Alignment: Coordinating Student Ideas with the Representational System of a computational modeling Unit for Science Learning

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COGNITION AND INSTRUCTION 2025年第1-2期43卷 1-32页

作者： Wagh, Aditi Rosenbaum, Leah F. Fuhrmann, Tamar Eloy, Adelmo Blikstein, Paulo Wilkerson, Michelle MIT Scheller Teacher Educ Program Cambridge MA 02139 USA Columbia Univ Teachers Coll Dept Math Sci & Technol New York NY USA Univ Calif Berkeley Berkeley Sch Educ Berkeley CA USA

computational modeling tools present unique opportunities and challenges for student learning. Each tool has a representational system that impacts the kinds of explorations students engage in. Inquiry aligned with a tool's representational system can support more productive engagement toward target learning goals. However, little research has examined how teachers can make visible the ways students' ideas about a phenomenon can be expressed and explored within a tool's representational system. In this paper, we elaborate on the construct of ontological alignment-that is, identifying and leveraging points of resonance between students' existing ideas and the representational system of a tool. Using interaction analysis, we identify alignment practices adopted by a science teacher and her students in a computational agent-based modeling unit. Specifically, we describe three practices: (1) Elevating student ideas relevant to the tool's representational system;(2) Exploring and testing links between students' conceptual and computational models;and (3) Drawing on evidence resonant with the tool's representational system to differentiate between theories. Finally, we discuss the pedagogical value of ontological alignment as a way to leverage students' ideas in alignment with a tool's representational system and suggest the presented practices as exemplary ways to support students' computational modeling for science learning.

关键词： computational modeling model-based inquiry middle school classroom discourse teachers instructional practice epistemic forms

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computational modeling of Emotion-Motivated Decisions for Continuous Control of Mobile Robots

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IEEE TRANSACTIONS ON COGNITIVE AND DEVELOPMENTAL SYSTEMS 2021年第1期13卷 31-44页

作者： Huang, Xiao Wu, Wei Qiao, Hong Chinese Acad Sci State Key Lab Management & Control Complex Syst Inst Automat Beijing 100190 Peoples R China Chinese Acad Sci Beijing Key Lab Res & Applicat Robot Intelligence Beijing 100190 Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China Chinese Acad Sci Beijing Key Lab Res & Applicat Robot Intelligence CAS Ctr Excellence Brain Sci & Intelligence Techn Beijing 100190 Peoples R China Chinese Acad Sci Cloud Comp Ctr Beijing 100190 Peoples R China

Immediate rewards are usually very sparse in the real world, which brings a great challenge to plain learning methods. Inspired by the fact that emotional reactions are incorporated into the computation of subjective value during decision-making in humans, an emotion-motivated decision-making framework is proposed in this article. Specifically, we first build a brain-inspired computational model of amygdala-hippocampus interaction to generate emotional reactions. The intrinsic emotion derives from the external reward and episodic memory and represents three psychological states: 1) valence;2) novelty;and 3) motivational relevance. Then, a model-based (MB) decision-making approach with emotional intrinsic rewards is proposed to solve the continuous control problem of mobile robots. This method can execute online MB control with the constraint of the model-free policy and global value function, which is conducive to getting a better solution with a faster policy search. The simulation results demonstrate that the proposed approach has higher learning efficiency and maintains a higher level of exploration, especially, in some very sparse-reward environments.

关键词： Decision making Brain modeling computational modeling Robots Hippocampus Neuroscience Brain-inspired computing decision making emotion– memory interactions emotion-motivated learning reinforcement learning

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computational modeling of Spatially Selective Retinal Stimulation With Temporally Interfering Electric Fields

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IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING 2021年 29卷 418-428页

作者： Su, Xiaofan Guo, Jiahui Zhou, Meixuan Chen, Jianpin Li, Liming Chen, Yao Sui, Xiaohong Li, Heng Chai, Xinyu Shanghai Jiao Tong Univ Sch Biomed Engn Shanghai 200240 Peoples R China

Retinal electrical stimulation is a widely utilized method to restore visual function for patients with retinal degenerative diseases. Transcorneal electrical stimulation (TES) represents an effective way to improve the visual function due to its potential neuroprotective effect. However, TES with single electrode fails to spatially and selectively stimulate retinal neurons. Herein, a computational modeling method was proposed to explore the feasibility of spatially selective retinal stimulation via temporally interfering electric fields. An eyeball model with multiple electrodes was constructed to simulate the interferential electric fields with various electrode montages and current ratios. The results demonstrated that the temporal interference (TI) stimulation would gradually generate an increasingly localized high-intensity region on retina as the return electrodes moved towards the posterior of the eyeball and got closer. Additionally, the position of the convergent region could be modulated by regulating the current ratio of different electrode channels. The TI strategy with multisite and steerable stimulation can stimulate local retinal region with certain convergence and a relatively large stimulation range, which would be a feasible approach for the spatially selective retinal neuromodulation.

关键词： Electrodes Retina Electric fields Electrical stimulation Three-dimensional displays Neuromodulation Conductivity computational modeling retinal neuromodulation spatial selectivity temporal interference transcorneal electrical stimulation

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computational modeling of constitutive behaviour of 3D printed composite structures

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JOURNAL OF MATERIALS RESEARCH AND TECHNOLOGY-JMR&T 2021年 11卷 1710-1718页

作者： Somireddy, Madhukar Czekanski, Aleksander York Univ Dept Mech Engn Toronto ON M3J 1P3 Canada

Anisotropy is one of the main limitations in the effective design of 3D printed structures. Further, experimental evaluation of the material behaviour of printed parts is tedious, and expensive. An alternate solution is computational material modeling of printed parts. In the present work, the computational homogenization is applied to estimate the final constitutive behaviour of parts printed with polymeric composite material. To begin, the mesostructure of layers of the printed parts was considered for finite element modeling of the representative volume element (RVE), and to determine their elastic moduli. computationally estimated material properties were higher than experimental values, and the percent difference between them was higher for parts made of ABS polymer containing short carbon fibers (sCF) versus ABS alone. The computational models provided more insights on the final properties of 3D printed parts for different materials. Further, the stress contours of the RVEs revealed that the printed parts are prone to two different failure types: delamination and fiber pull-out. Also, the lateral and transverse elastic moduli of layers were found to be approximately the same, and therefore the constitutive behaviour of the layers can be treated as transversely isotropic material. In summary, this research work represents an important step towards enabling the effective design and analysis of 3D printed structures using computational methodology. ? 2021 The Authors. Published by Elsevier B.V. This is an open access article under the CC Anisotropy is one of the main limitations in the effective design of 3D printed structures. Further, experimental evaluation of the material behaviour of printed parts is tedious, and expensive. An alternate solution is computational material modeling of printed parts. In the present work, the computational homogenization is applied to estimate the final constitutive behaviour of parts printed with polymeric composite material. T

关键词： 3D printing Composite laminates computational modeling Mesostructure

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Analyzing students’ systems thinking in-situ through screencasts in the context of computational modeling: a case study

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Disciplinary and Interdisciplinary Science Education Research 2024年第1期6卷 24页

作者： Bowers, Jonathan Eidin, Emil Michigan State University East Lansing MI United States University of Wyoming Laramie 82071 WY United States

In our interconnected world, Systems Thinking (ST) is increasingly being recognized as a key learning goal for science education to help students make sense of complex phenomena. To support students in mastering ST, educators are advocating for using computational modeling programs. However, studies suggest that students often have challenges with using ST in the context of computational modeling. While previous studies have suggested that students have challenges modeling change over time through collector and flow structures and representing iterative processes through feedback loops, most of these studies investigated student ST through pre and post tests or through interviews. As such there is a gap in the literature regarding how student ST approaches develop and change throughout a computational modeling unit. In this case study, we aimed to determine which aspects of ST students found challenging during a computational modeling unit, how their approaches to ST changed over time, and how the learning environment was supporting students with ST. Building on prior frameworks, we developed a seven-category analysis tool that enabled us to use a mixture of student discourse, writing, and screen actions to categorize seven ST behaviors in real time. Through using this semi-quantitative tool and subsequent narrative analysis, we found evidence for all seven behavior categories, but not all categories were equally represented. Meanwhile our results suggest that opportunities for students to engage in discourse with both their peers and their teacher supported them with ST. Overall, this study demonstrates how student discourse and student writing can be important evidence of ST and serve as a potential factor to evaluate ST application as part of students’ learning progression. The case study also provides evidence for the positive impact that the implementation of a social constructivist approach has in the context of constructing computational system models. © The

关键词： Case study computational modeling High school modeling Science education Systems thinking

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Understanding Human Cognition Through computational modeling

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TOPICS IN COGNITIVE SCIENCE 2024年第3期16卷 349-376页

作者： Hsiao, Janet Hui-wen Hong Kong Univ Sci & Technol Div Social Sci Hong Kong Peoples R China Hong Kong Univ Sci & Technol Div Social Sci Kowloon Clear Water Bay Hong Kong Peoples R China

One important goal of cognitive science is to understand the mind in terms of its representational and computational capacities, where computational modeling plays an essential role in providing theoretical explanations and predictions of human behavior and mental phenomena. In my research, I have been using computational modeling, together with behavioral experiments and cognitive neuroscience methods, to investigate the information processing mechanisms underlying learning and visual cognition in terms of perceptual representation and attention strategy. In perceptual representation, I have used neural network models to understand how the split architecture in the human visual system influences visual cognition, and to examine perceptual representation development as the results of expertise. In attention strategy, I have developed the Eye Movement analysis with Hidden Markov Models method for quantifying eye movement pattern and consistency using both spatial and temporal information, which has led to novel findings across disciplines not discoverable using traditional methods. By integrating it with deep neural networks (DNN), I have developed DNN+HMM to account for eye movement strategy learning in human visual cognition. The understanding of the human mind through computational modeling also facilitates research on artificial intelligence's (AI) comparability with human cognition, which can in turn help explainable AI systems infer humans' belief on AI's operations and provide human-centered explanations to enhance human-AI interaction and mutual understanding. Together, these demonstrate the essential role of computational modeling methods in providing theoretical accounts of the human mind as well as its interaction with its environment and AI systems. In this paper, I summarize my research in visual cognition, language processing, and explainable AI to demonstrate the essential role of computational modeling methods in providing theoretical accounts of the

关键词： computational modeling Deep neural network Hidden Markov model Eye movement Explainable artificial intelligence Visual cognition Psycholinguistics Human learning Machine learning

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Angiography-Based computational modeling for In Vivo Assessment of Endothelial Dynamic Strain in Coronary Arteries with De Novo Lesions:Comparison of Treatment Effects of Drug-Coated Balloons Between Small and Large Arteries

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Cardiovascular Innovations and Applications 2024年第1期9卷 616-627页

作者： Lei Xu Zhouhao Tang He Zou Yiqiu Jiang Youxian Shen Xinmin Zhang Ahmed Elkoumy Xueqiang Guan Lianpin Wu Xinlei Wu Zhejiang-Ireland Joint Laboratory for Precision Diagnosis and Treatment of Valvular Heart Diseases The Second Afffliated Hospital of Wenzhou Medical UniversityWenzhouChina Department of Cardiology Key Laboratory of Panvascular Diseases of WenzhouThe Second Afffliated Hospital and Yuying Children’s Hospital of Wenzhou Medical UniversityWenzhouChina Department of Radiology The Second Afffliated Hospital and Yuying Children’s Hospital of Wenzhou Medical UniversityWenzhouChina Islamic Center of Cardiology Al-Azhar UniversityCairoEgypt Discipline of Cardiology Saolta GroupGalway University HospitalHealth Service ExecutiveGalwayIreland CORRIB Core Lab University of GalwayGalwayIreland

Acute morphological changes in de novo coronary lesions after drug-coated balloon(DCB)angioplasty can affect endothelial mechanics and consequently clinical ***-based computational modeling has been validated to assess endothelial dynamic strain(EDS)in coronary arteries in *** EDS was calculated on the basis of pre-and post-DCB *** of quantitative coronary angiography and EDS were quantified at cross-sections in the treated segments.A total of 336 and 348 lesion cross-sections were included in the small/large vessel groups,*** acute lumen gain after DCB was significantly higher in large than small vessels(relative changes:21.3%[17.4%,25.1%]vs.7.4%[4.8%,10.1%],P<0.001).Before treatment,three indices of EDS were significantly higher in small than large vessels(for ED-EDS:29.2%[19.8%,44.8%]vs.20.4%[14.3%,30.2%];for ES-EDS:26.8%[18.9%,37.7%]vs.18.3%[13.9%,25.4%];for TA-EDS:19.1%[13.9%,27.8%]vs.14.3%[10.5%,20.1%],P<0.001).After treatment,the EDS in small vessels significantly decreased(P<0.001).ED-EDS showed the highest correlation with pre-DCB DSP(r=0.43,P<0.001)and post-DCB MLD(r=0.35,P<0.001).The levels of EDS parameters for small or large vessel lesions significantly *** study is required to examine the clinical value of EDS in predicting cardiac events after DCB treatment.

关键词： computational modeling coronary angiography endothelial dynamic strain drug-coated balloon de novo lesion

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Biophysical Principles and computational modeling of Deep Brain Stimulation

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Neuromodulation 2024年第3期27卷 422-439页

作者： Ng, Patrick R. Bush, Alan Vissani, Matteo McIntyre, Cameron C. Richardson, Robert Mark Harvard Medical School Boston MA United States Department of Neurosurgery Massachusetts General Hospital Boston MA United States Department of Biomedical Engineering Duke University Durham NC United States Department of Neurosurgery Duke University Durham NC United States

Background: Deep brain stimulation (DBS) has revolutionized the treatment of neurological disorders, yet the mechanisms of DBS are still under investigation. computational models are important in silico tools for elucidating these underlying principles and potentially for personalizing DBS therapy to individual patients. The basic principles underlying neurostimulation computational models, however, are not well known in the clinical neuromodulation community. Objective: In this study, we present a tutorial on the derivation of computational models of DBS and outline the biophysical contributions of electrodes, stimulation parameters, and tissue substrates to the effects of DBS. Results: Given that many aspects of DBS are difficult to characterize experimentally, computational models have played an important role in understanding how material, size, shape, and contact segmentation influence device biocompatibility, energy efficiency, the spatial spread of the electric field, and the specificity of neural activation. Neural activation is dictated by stimulation parameters including frequency, current vs voltage control, amplitude, pulse width, polarity configurations, and waveform. These parameters also affect the potential for tissue damage, energy efficiency, the spatial spread of the electric field, and the specificity of neural activation. Activation of the neural substrate also is influenced by the encapsulation layer surrounding the electrode, the conductivity of the surrounding tissue, and the size and orientation of white matter fibers. These properties modulate the effects of the electric field and determine the ultimate therapeutic response. Conclusion: This article describes biophysical principles that are useful for understanding the mechanisms of neurostimulation. © 2023 International Neuromodulation Society

关键词： Biophysics computational modeling deep brain stimulation

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Highly logical and non-emotional decisions in both risky and social contexts: understanding decision making in autism spectrum disorder through computational modeling

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COGNITIVE PROCESSING 2024年第3期25卷 503-512页

作者： Molins, Francisco Jemni, Nour Ben-Hassen Garrote-Petisco, Dolores Serrano, Miguel Angel Univ Valencia Dept Psychobiol Ave Blasco Ibanez 13 Valencia 46010 Spain

In risky contexts, autism spectrum disorder (ASD) individuals exhibit more logical consistency and non-emotional decisions than do typical adults (TAs). This way of deciding could be also prevailing in social contexts, leading to maladaptive decisions. This evidence is scarce and inconsistent, and further research is needed. Recent developments in computational modeling allow analysis of decisional subcomponents that could provide valuable information to understand the decision-making and help address inconsistencies. Twenty-seven individuals with ASD and 25 TAs were submitted to a framing-task and the ultimatum game (UG). The Rescorla-Wagner computational model was used to analyze UG decisions. Results showed that in the UG, the ASD group exhibited a higher utilitarianism, characterized by lower aversion to unfairness and higher acceptance of offers. Moreover, this way of deciding was predicted by the higher economic rationality found in the framing task, where people with ASD did not manifest emotional biases such as framing effect. These results could suggest an atypical decision making, highly logical and non-emotional, as a robust feature of ASD.

关键词： Autism spectrum disorder Decision making Framing effect Ultimatum game computational modeling

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