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Lack of effects of eight-week left dorsolateral prefrontal theta burst stimulation on white matter macro/microstructure and connection in autism

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brain imaging and behavior 2024年第4期18卷 794-807页

作者： Chun-Hung Yeh Po-Chun Lin Rung-Yu Tseng Yi-Ping Chao Chen-Te Wu Tai-Li Chou Rou-Shayn Chen Susan Shur-Fen Gau Hsing-Chang Ni Hsiang-Yuan Lin Department of Medical Imaging and Radiological Sciences Chang Gung University Taoyuan Taiwan. Department of Psychiatry Chang Gung Memorial Hospital at Linkou No.5 Fusing St. Gueishan Taoyuan 333 Taiwan. Deparment of Computer Science and Information Engineering Chang Gung University Taoyuan Taiwan. Department of Otorhinolaryngology-Head and Neck Surgery Chang Gung Memorial Hospital at Linkou Taoyuan Taiwan. Department of Medical Imaging and Intervention Chang Gung Memorial Hospital at Linkou Taoyuan Taiwan. Department of Psychology National Taiwan University Taipei Taiwan. Graduate Institute of Brain and Mind Sciences College of Medicine National Taiwan University Taipei Taiwan. Neurobiology and Cognitive Science Center National Taiwan University Taipei Taiwan. Department of Neurology Chang Gung Memorial Hospital at Linkou Taoyuan Taiwan. Department of Psychiatry National Taiwan University Hospital and College of Medicine Taipei Taiwan. Department of Psychiatry Chang Gung Memorial Hospital at Linkou No.5 Fusing St. Gueishan Taoyuan 333 Taiwan. alanni@cgmh.org.tw. College of Medicine Chang Gung University Taoyuan Taiwan. alanni@cgmh.org.tw. Azrieli Adult Neurodevelopmental Centre Campbell Family Mental Health Research Institute Centre for Addiction and Mental Health Toronto ON Canada. Department of Psychiatry Temerty Faculty of Medicine University of Toronto Toronto ON Canada.

Whether brain stimulation could modulate brain structure in autism remains unknown. This study explored the impact of continuous theta burst stimulation (cTBS) over the left dorsolateral prefrontal cortex (DLPFC) on white matter macro/microstructure in intellectually able children and emerging adults with autism. Sixty autistic participants were randomized (30 active) and received active or sham cTBS for eight weeks twice per week, 16 total sessions using a double-blind (participant-, rater-, analyst-blinded) design. All participants received high-angular resolution diffusion MR imaging at baseline and week 8. Twenty-eight participants in the active group and twenty-seven in the sham group with good imaging quality entered the final analysis. With longitudinal fixel-based analysis and network-based statistics, we found no significant difference between the active and sham groups in changes of white matter macro/microstructure and connections following cTBS. In addition, we found no association between baseline white matter macro/microstructure and autistic symptom changes from baseline to week 8 in the active group. In conclusion, we did not find a significant impact of left DLPFC cTBS on white matter macro/microstructure and connections in children and emerging adults with autism. These findings need to be interpreted in the context that the current intellectually able cohort in a single university hospital site limits the generalizability. Future studies are required to investigate if higher stimulation intensities and/or doses, other personal factors, or rTMS parameters might confer significant brain structural changes visible on MRI in ASD.

关键词： Autism Diffusion MRI Dorsolateral prefrontal cortex Theta burst stimulation White matter

Bridging the gap between monaural speech enhancement and recognition with distortion-independent acoustic modeling

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arXiv 2019年

作者： Wang, Peidong Tan, Ke Wang, DeLiang Department of Computer Science and Engineering Center for Cognitive and Brain Sciences Ohio State University ColumbusOH43210 United States

Monaural speech enhancement has made dramatic advances since the introduction of deep learning a few years ago. Although enhanced speech has been demonstrated to have better intelligibility and quality for human listeners, feeding it directly to automatic speech recognition (ASR) systems trained with noisy speech has not produced expected improvements in ASR performance. The lack of an enhancement benefit on recognition, or the gap between monaural speech enhancement and recognition, is often attributed to speech distortions introduced in the enhancement process. In this study, we analyze the distortion problem, compare different acoustic models, and investigate a distortion-independent training scheme for monaural speech recognition. Experimental results suggest that distortion-independent acoustic modeling is able to overcome the distortion problem. Such an acoustic model can also work with speech enhancement models different from the one used during training. Moreover, the models investigated in this paper outperform the previous best system on the CHiME-2 corpus. Copyright © 2019, The Authors. All rights reserved.

关键词： Speech enhancement

Predicting brain evoked response to external stimuli from temporal correlations of spontaneous activity

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Physical Review Research 2020年第3期2卷 033355-033355页

作者： A. Sarracino O. Arviv O. Shriki L. de Arcangelis Engineering Department University of Campania “Luigi Vanvitelli” 81031 Aversa (Caserta) Italy Department of Cognitive and Brain Sciences Ben-Gurion University of the Negev Beer-Sheva Israel The Inter-Faculty School for Brain Sciences Zlotowski Center for Neuroscience Ben-Gurion University of the Negev Beer-Sheva Israel Department of Computer Science Ben-Gurion University of the Negev Beer-Sheva Israel

The relation between spontaneous and stimulated global brain activity is a fundamental problem in the understanding of brain functions. This question is investigated both theoretically and experimentally within the context of nonequilibrium fluctuation-dissipation relations. We consider the stochastic coarse-grained Wilson-Cowan model in the linear noise approximation and compare analytical results to experimental data from magnetoencephalography of the human brain. The short-time behavior of the autocorrelation function for spontaneous activity is characterized by a double-exponential decay, with two characteristic times, differing by two orders of magnitude. Conversely, the response function exhibits a single-exponential decay in agreement with experimental data for evoked activity under visual stimulation. Results suggest that the brain response to weak external stimuli can be predicted from the observation of spontaneous activity and pave the way to controlled experiments on the brain response under different external perturbations.

关键词： Neuroscience Nonequilibrium statistical mechanics

The Localized Subtraction Approach For EEG and MEG Forward Modeling

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arXiv 2023年

作者： Höltershinken, Malte B. Lange, Pia Erdbrügger, Tim Buschermöhle, Yvonne Wallois, Fabrice Buyx, Alena Pursiainen, Sampsa Vorwerk, Johannes Engwer, Christian Wolters, Carsten H. Institute for Biomagnetism and Biosignalanalysis University of Münster Münster Germany Institute of Medical Informatics University of Münster Münster Germany Otto Creutzfeldt Center for Cognitive and Behavioral Neuroscience University of Münster Münster Germany INSERM U1105 Research Group on Multimodal Analysis of Brain Function Jules Verne University of Picardie Amiens France Pediatric functional exploration of the nervous system department CHU Picardie Amiens France Institute of History and Ethics in Medicine Technical University of Munich Munich Germany Computing Sciences Unit Faculty of Information Technology and Communication Sciences Tampere University Tampere Finland Institute of Electrical and Biomedical Engineering Private University for Health Sciences Medical Informatics and Technology Hall in Tyrol Austria Faculty of Mathematics and Computer Science University of Münster Münster Germany

In FEM-based EEG and MEG source analysis, the subtraction approach has been proposed to simulate sensor measurements generated by neural activity. While this approach possesses a rigorous foundation and produces accurate results, its major downside is that it is computationally prohibitively expensive in practical applications. To overcome this, we developed a new approach, called the localized subtraction approach. This approach is designed to preserve the mathematical foundation of the subtraction approach, while also leading to sparse right-hand sides in the FEM formulation, making it efficiently computable. We achieve this by introducing a cut-off into the subtraction, restricting its influence to the immediate neighborhood of the source. In this work, this approach will be presented, analyzed, and compared to other state-of-the-art FEM right-hand side approaches. Furthermore, we discuss how to arrive at an efficient and stable implementation. We perform validation in multi-layer sphere models where analytical solutions exist. There, we demonstrate that the localized subtraction approach is vastly more efficient than the subtraction approach. Moreover, we find that for the EEG forward problem, the localized subtraction approach is less dependent on the global structure of the FEM mesh, while the subtraction approach is sensitive to the mesh structure even at a distance to the source. Additionally, we show the localized subtraction approach to rival, and in many cases even surpass, the other investigated approaches in terms of accuracy. Especially for the MEG forward problem, where Biot-Savart’s law is employed, we show the localized subtraction approach and the subtraction approach to produce highly accurate approximations of the volume currents close to the source. The localized subtraction approach thus reduces the computational cost of the subtraction approach to an extent that makes it usable in practical applications without sacrificing the rigorousness and

关键词： Mesh generation

Investigating EEG-Based Functional Connectivity Patterns for Multimodal Emotion Recognition

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arXiv 2020年

作者： Wu, Xun Zheng, Wei-Long Lu, Bao-Liang Center for Brain-Like Computing and Machine Intelligence Department of Computer Science and Engineering Key Laboratory of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Brain Science and Technology Research Center Qing Yuan Research Institute Shanghai Jiao Tong University 800 Dong Chuan Road Shanghai200240 China Clinical Data Animation Center Department of Neurology Massachusetts General Hospital Harvard Medical School 55 Fruit Street BostonMA United States

Compared with the rich studies on the motor brain-computer interface (BCI), the recently emerging affective BCI presents distinct challenges since the brain functional connectivity networks involving emotion are not well investigated. Previous studies on emotion recognition based on electroencephalography (EEG) signals mainly rely on single-channel-based feature extraction methods. In this paper, we propose a novel emotion-relevant critical subnetwork selection algorithm and investigate three EEG functional connectivity network features: strength, clustering coefficient, and eigenvector centrality. The discrimination ability of the EEG connectivity features in emotion recognition is evaluated on three public emotion EEG datasets: SEED, SEED-V, and DEAP. The strength feature achieves the best classification performance and outperforms the state-of-the-art differential entropy feature based on single-channel analysis for the EEG signals. The experimental results reveal that distinct functional connectivity patterns are exhibited for the five emotions of disgust, fear, sadness, happiness, and neutrality. Furthermore, we construct a multimodal emotion recognition model by combining the functional connectivity features from EEG and the features from eye movements or physiological signals using deep canonical correlation analysis. The classification accuracies of multimodal emotion recognition are 95.08 ± 6.42% on the SEED dataset, 84.51 ± 5.11% on the SEED-V dataset, and 85.34 ± 2.90% and 86.61 ± 3.76% for arousal and valence on the DEAP dataset, respectively. The results demonstrate the complementary representation properties of the EEG functional connectivity network features with eye movement data. In addition, we find that the brain networks constructed with fewer channels, i.e., 18 channels, achieve comparable performance with that of the 62-channel network with respect to multimodal emotion recognition and enable easier setups for BCI systems in real scenarios. Cop

关键词： Electrophysiology

An analysis of pathologists’ viewing processes as they diagnose whole slide digital images

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Journal of Pathology Informatics 2022年 13卷 100104-100104页

作者： Ghezloo, Fatemeh Wang, Pin-Chieh Kerr, Kathleen F. Brunyé, Tad T. Drew, Trafton Chang, Oliver H. Reisch, Lisa M. Shapiro, Linda G. Elmore, Joann G. Paul G. Allen School of Computer Science and Engineering University of Washington Seattle WA United States Department of Medicine University of California Los Angeles David Geffen School of Medicine Los Angeles CA United States Department of Biostatistics University of Washington Seattle WA United States Center for Applied Brain and Cognitive Sciences Tufts University Medford MA United States Department of Psychology University of Utah Salt Lake City UT United States Department of Laboratory Medicine and Pathology University of Washington Seattle WA United States

Although pathologists have their own viewing habits while diagnosing, viewing behaviors leading to the most accurate diagnoses are under-investigated. Digital whole slide imaging has enabled investigators to analyze pathologists’ visual interpretation of histopathological features using mouse and viewport tracking techniques. In this study, we provide definitions for basic viewing behavior variables and investigate the association of pathologists' characteristics and viewing behaviors, and how they relate to diagnostic accuracy when interpreting whole slide images. We use recordings of 32 pathologists’ actions while interpreting a set of 36 digital whole slide skin biopsy images (5 sets of 36 cases;180 cases total). These viewport tracking data include the coordinates of a viewport scene on pathologists’ screens, the magnification level at which that viewport was viewed, as well as a timestamp. We define a set of variables to quantify pathologists' viewing behaviors such as zooming, panning, and interacting with a consensus reference panel's selected region of interest (ROI). We examine the association of these viewing behaviors with pathologists’ demographics, clinical characteristics, and diagnostic accuracy using cross-classified multilevel models. Viewing behaviors differ based on clinical experience of the pathologists. Pathologists with a higher caseload of melanocytic skin biopsy cases and pathologists with board certification and/or fellowship training in dermatopathology have lower average zoom and lower variance of zoom levels. Viewing behaviors associated with higher diagnostic accuracy include higher average and variance of zoom levels, a lower magnification percentage (a measure of consecutive zooming behavior), higher total interpretation time, and higher amount of time spent viewing ROIs. Scanning behavior, which refers to panning with a fixed zoom level, has marginally significant positive association with accuracy. Pathologists’ training, clinical e

关键词： Computational pathology Digital imaging Digital pathology Statistical analysis Whole slide imaging

Gradient descent in materia through homodyne gradient extraction

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arXiv 2021年

作者： Boon, Marcus N. Cassola, Lorenzo Euler, Hans-Christian Ruiz Chen, Tao van de Ven, Bram Ibarra, Unai Alegre Bobbert, Peter A. van der Wiel, Wilfred G. NanoElectronics Group MESA+ Institute for Nanotechnology BRAINS Center for Brain-Inspired Nano Systems University of Twente PO Box 217 Enschede7500 AE Netherlands Exzellenzcluster Science of Intelligence Technische Universität Berlin Marchstr. 23 Berlin10587 Germany Department for Electrical Engineering and Computer Science Modeling of Cognitive Processes Technische Universität Berlin Berlin Germany Molecular Materials and Nanosystems Eindhoven Institute for Renewable Energy Systems Department of Applied Physics Eindhoven University of Technology PO Box 513 Eindhoven5600 MB Netherlands Institute of Physics University of Münster Münster48149 Germany

Deep learning, a multi-layered neural network approach inspired by the brain, has revolutionized machine learning [1]. One of its key enablers has been backpropagation [2], an algorithm that computes the gradient of a loss function with respect to the weights and biases in the neural network model, in combination with its use in gradient descent [3]. However, the implementation of deep learning in digital computers is intrinsically energy hungry, with energy consumption becoming prohibitively high for many applications [4]. This has stimulated the development of specialized hardware, ranging from neuromorphic CMOS integrated circuits [5] [6, 7] and integrated photonic tensor cores [8] to unconventional, material-based computing systems [9] [10] [11] [12] [13] [14] [15] [16]. The learning process in these material systems, realized, e.g., by artificial evolution [13] [14], equilibrium propagation [17] or surrogate modelling [18] [19], is a complicated and time-consuming process. Here, we demonstrate a simple yet efficient and accurate gradient extraction method, based on the principle of homodyne detection, for performing gradient descent on a loss function directly in a physical system without the need of an analytical description. By perturbing the parameters that need to be optimized using sinusoidal waveforms with distinct frequencies, we effectively obtain the gradient information in a highly robust and scalable manner. We illustrate the method in dopant network processing units [14], but argue that it is applicable in a wide range of physical systems. Homodyne gradient extraction can in principle be fully implemented in materia, facilitating the development of autonomously learning material systems. © 2021, CC BY-NC-SA.

关键词： CMOS integrated circuits

Evolution and efficiency in color naming: The case of Nafaanra 41

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Evolution and efficiency in color naming: The case of Nafaan...

41st Annual Meeting of the cognitive science Society: Creativity + Cognition + Computation, CogSci 2019

作者： Zaslavsky, Noga Garvin, Karee Kemp, Charles Tishby, Naftali Regier, Terry Edmond and Lily Safra Centre for Brain Sciences Hebrew University Jerusalem9190401 Israel Department of Linguistics University of California BerkeleyCA94720 United States School of Psychological Sciences University of Melbourne ParkvilleVIC3010 Australia Benin School of Computer Science and Engineering Hebrew University Jerusalem9190401 Israel Cognitive Science Program University of California BerkeleyCA94720 United States

Semantic categories of artifacts and animals reflect efficient coding 41

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Semantic categories of artifacts and animals reflect efficie...

41st Annual Meeting of the cognitive science Society: Creativity + Cognition + Computation, CogSci 2019

作者： Zaslavsky, Noga Regier, Terry Tishby, Naftali Kemp, Charles Edmond and Lily Safra Center for Brain Sciences Hebrew University Jerusalem9190401 Israel Department of Linguistics University of California BerkeleyCA94720 United States Cognitive Science Program University of California BerkeleyCA94720 United States Benin School of Computer Science and Engineering Hebrew University Jerusalem9190401 Israel School of Psychological Sciences University of Melbourne ParkvilleVIC3010 Australia

ISBN: (纸本)0991196775

It has been argued that semantic categories across languages reflect pressure for efficient communication. Recently, this idea has been cast in terms of a general information-theoretic principle of efficiency, the Information Bottleneck (IB) principle, and it has been shown that this principle accounts for the emergence and evolution of named color categories across languages, including soft structure and patterns of inconsistent naming. However, it is not yet clear to what extent this account generalizes to semantic domains other than color. Here we show that it generalizes to two qualitatively different semantic domains: names for containers, and for animals. First, we show that container naming in Dutch and French is near-optimal in the IB sense, and that IB broadly accounts for soft categories and inconsistent naming patterns in both languages. Second, we show that a hierarchy of animal categories derived from IB captures cross-linguistic tendencies in the growth of animal taxonomies. Taken together, these findings suggest that fundamental information-theoretic principles of efficient coding may shape semantic categories across languages and across domains. © cognitive science Society: Creativity + Cognition + Computation, CogSci *** rights reserved.

关键词： Semantics