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Principles of high–fidelity, high–density 3–d neural recording

BMC Neuroscience 2014年第1期15卷 1-2页

作者： Caroline Moore-Kochlacs Nancy Kopell Justin P Kinney Ed S Boyden Jorg Scholvin Jacob G Bernstein Scott K Arfin Young Gyu Yoon Graduate Program for Neuroscience Boston University Boston MA 02215 USA McGovern Institute Massachusetts Institute of Technology MA 02139 USA Department of Mathematics and Statistics Boston University Boston MA 02215 USA Media Lab Massachusetts Institute of Technology MA 02139 USA Brain and Cognitive Science Massachusetts Institute of Technology MA 02139 USA Biological Engineering Massachusetts Institute of Technology MA 02139 USA Electrical Engineering and Computer Science Massachusetts Institute of Technology MA 02139 USA

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A scalable chatbot platform leveraging online community posts: A proof-of-concept study

arXiv

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arXiv 2020年

作者： Jo, Sihyeon Yang, Seung Hee Yoo, Seungryong Zuo, Tong Im, Sangwon Kim, Hee-Eun Han, SangWook Kim, Seong-Woo Electrical & Computer Eng Seoul National University Interdisciplinary Program in Cognitive Science Seoul National University Nuclear Engineering Seoul National University Electronics & Information Eng North China Univ. of Technology Aerospace Engineering Seoul National University Curatorial Team Art Center Nabi Nabi Lab Art Center Nabi Korea Republic of Graduate School of Engineering Practice Seoul National University

The development of natural language processing algorithms and the explosive growth of conversational data are encouraging researches on the human-computer conversation. Still, getting qualified conversational data on a large scale is difficult and expensive. In this paper, we verify the feasibility of constructing a data-driven chatbot with processed online community posts by using them as pseudo-conversational data. We argue that chatbots for various purposes can be built extensively through the pipeline exploiting the common structure of community posts. Our experiment demonstrates that chatbots created along the pipeline can yield the proper responses. Copyright © 2020, The Authors. All rights reserved.

关键词： Pipelines

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Modularity maximization as a flexible and generic framework for brain network exploratory analysis

arXiv

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arXiv 2021年

作者： Esfahlani, Farnaz Zamani Jo, Youngheun Puxeddu, Maria Grazia Merritt, Haily Tanner, Jacob C. Greenwell, Sarah Patel, Riya Faskowitz, Joshua Betzel, Richard F. Department of Psychological and Brain Sciences Indiana University BloomingtonIN47405 United States Cognitive Science Program Indiana University BloomingtonIN47405 United States Program in Neuroscience Indiana University BloomingtonIN47405 United States Network Science Institute Indiana University BloomingtonIN47405 United States Department of Computer Control and Management Engineering Antonio Ruberti Sapienza University of Rome Rome00185 Italy IRCCS Fondazione Santa Lucia Rome00185 Italy

The modular structure of brain networks supports specialized information processing, complex dynamics, and cost-efficient spatial embedding. Inter-individual variation in modular structure has been linked to differences in performance, disease, and development. There exist many data-driven methods for detecting and comparing modular structure, the most popular of which is modularity maximization. Although modularity maximization is a general framework that can be modified and reparamaterized to address domain-specific research questions, its application to neuroscientific datasets has, thus far, been narrow. Here, we highlight several strategies in which the "out-of-the-box" version of modularity maximization can be extended to address questions specific to neuroscience. First, we present approaches for detecting "space-independent" modules and for applying modularity maximization to signed matrices. Next, we show that the modularity maximization frame is well-suited for detecting task- and condition-specific modules. Finally, we highlight the role of multi-layer models in detecting and tracking modules across time, tasks, subjects, and modalities. In summary, modularity maximization is a flexible and general framework that can be adapted to detect modular structure resulting from a wide range of hypotheses. This article highlights opens multiple frontiers for future research and applications. © 2021, CC BY.

关键词： Neurophysiology

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Implementation of new services to support ubiquitous computing for campus life

Implementation of new services to support ubiquitous computi...

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IEEE Workshop on Software Technologies for Future Embedded Systems

作者： Tack-Don Han Cheolho Cheong Jae-Won Ann Jong-Young Kim Hyung-Min Yoon Chang-Su Lee Hyon-Gu Shin Young-Jin Lee Hyoung-Min Yook Myoung-Hoon Jeon Jung Soo Choi Joo-Hyeon Lee Young-Woo Sohn Yoon Su Baek Sang-Yong Lee Eun-Dong Shin WooShik Kang SeongWoon Kim Department of Computer Science Yonsei University Seoul South Korea Dept. of Computer Science Yonsei University Seodaemun-gu Seoul KR Dept. of Comput. Sci. Yonsei Univ. South Korea Department of Clothing & Textiles Yonsei University Seoul South Korea Dept. of Clothing & Textiles Graduate Program in Cognitive Science Yonsei University Seoul South Korea Graduate Program in Cognitive Science Department of Mechanical Engineering Yonsei University Seoul South Korea Dept. of Mechanical Engineering Department of Psychology Yonsei University Seoul South Korea Dept. of Psychology ColorZip Media Inc. Seoul South Korea Yonsei University ColorZip Media Inc. Samsung Advanced Institute of Technology Seoul South Korea

ISBN: (纸本)0769521231

Many new services have emerged to realize ubiquitous computing environments, owing to the increasing supply of mobile devices and more widespread Internet and wireless network facilities. We introduce the U-Campus (ubiquitous computing for campus) service. This study has been conducted through interdisciplinary research by four participating departments. The U-campus project is part of the UTOPIA project (Ubiquitous computing TOwn Project: Intelligent context Awareness), which covers town- and city-wide environments. Currently, a test bed for U-campus has been constructed to support various services suck as U-profile, U-messaging and U-campus tour guide services. Students, professors, school staffs, and campus visitors can easily access the various available campus services by using image-based sensors and mobile devices such as CDMA cellular phones or WiFi smart phones. The major purpose of this research is to provide a context-aware U-campus environment to users by utilizing sensors and mobile devices currently available in the public sector and the marketplace.

关键词： Ubiquitous computing Intelligent sensors Mobile computing IP networks Web and internet services Wireless networks Context awareness Testing Educational institutions Image sensors

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SAMENESS ENTICES, BUT NOVELTY ENCHANTS IN FANFICTION ONLINE

arXiv

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arXiv 2019年

作者： Jing, Elise DeDeo, Simon Wright, Devin Robert Ahn, Yong-Yeol Center for Complex Networks and Systems Research Luddy School of Informatics Computing and Engineering Indiana University Bloomington United States Social and Decision Sciences Dietrich College Carnegie Mellon University United States Sirius XM United States Cognitive Science Program Indiana University Bloomington United States Indiana University Network Science Institute Indiana University Bloomington United States

Cultural evolution is driven by how we choose what to consume and share with others. A common belief is that the cultural artifacts that succeed are ones that balance novelty and conventionality. This balance theory suggests that people prefer works that are familiar, but not so familiar as to be boring;novel, but not so novel as to violate the expectations of their genre. We test this idea using a large dataset of fanfiction. We apply a multiple regression model and a generalized additive model to examine how the recognition a work receives varies with its novelty, estimated through a Latent Dirichlet Allocation topic model, in the context of existing works. We find the opposite pattern of what the balance theory predicts—overall success decline almost monotonically with novelty and exhibits a U-shaped, instead of an inverse U-shaped, curve. This puzzle is resolved by teasing out two competing forces: sameness attracts the mass whereas novelty provides enjoyment. Taken together, even though the balance theory holds in terms of expressed enjoyment, the overall success can show the opposite pattern due to the dominant role of sameness to attract the audience. Under these two "forces", cultural evolution may have to work against inertia—the appetite for consuming the familiar—and may resemble a punctuated equilibrium, marked by occasional leaps. Copyright © 2019, The Authors. All rights reserved.

关键词： Large dataset

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Redundant information encoding in primary motor cortex during motor tasks

Redundant information encoding in primary motor cortex durin...

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International IEEE/EMBS Conference on Neural engineering, CNE

作者： Kelvin So Karunesh Ganguly Michael Gastpar Jose M. Carmena Department of Electrical Engineering and Computer Sciences University of California Berkeley CA USA Neurology and Rehabilitation Services San Francisco Veterans Affairs Medical Center San Francisco CA USA Department of Electrical Engineering and Computer Sciences and the Helen Wills Neuroscience Institute University of California Berkeley CA USA Department of Electrical Engineering and Computer Sciences the Program in Cognitive Science and the Helen WillsNeuroscience Institute University of California Berkeley CA USA

Information encoded in neuron ensembles has previously been hypothesized to be highly redundant, despite the apparent inefficiency of a redundant encoding system. The recent availability of intracortical, multi-electrode recordings has enabled the possibility of exploring how neuronal ensembles encode information as a whole. Applying concepts from information theory, we examined the redundancy of the target information encoded in both contralateral and ipsilateral hemispheres of the primary motor cortex (M1) in macaque monkeys performing a center-out reaching task. During movement, we reliably found neurons in contralateral M1 to contain higher target information and to be more redundant than ipsilateral M1 neurons, which is consistent with the conventional understanding that motor control is mainly governed by contralateral M1. Secondly, neuron ensembles in both hemispheres showed largely redundant information encoding. These results suggest that redundancy in information encoding is highly prevalent in the motor cortex and may contribute to proficient motor control.

关键词： Neurons Redundancy Encoding Neuroscience Muscles Firing Mutual information

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Semantic categories of artifacts and animals reflect efficient coding

arXiv

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arXiv 2019年

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

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 nearoptimal 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. Copyright © 2019, The Authors. All rights reserved.

关键词： Animals

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Color naming reflects both perceptual structure and communicative need

arXiv

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arXiv 2018年

作者： Zaslavsky, Noga Kemp, Charles Tishby, Naftali Regier, Terry Edmond and Lily Safra Centre for Brain Sciences Hebrew University Jerusalem9190401 Israel Department of Psychology Carnegie Mellon University PittsburghPA15213 United States Benin School of Computer Science and Engineering Hebrew University Jerusalem9190401 Israel Department of Linguistics University of California BerkeleyCA94720 United States Cognitive Science Program University of California BerkeleyCA94720 United States

Gibson et al. (2017) argued that color naming is shaped by patterns of communicative need. In support of this claim, they showed that color naming systems across languages support more precise communication about warm colors than cool colors, and that the objects we talk about tend to be warm-colored rather than cool-colored. Here, we present new analyses that alter this picture. We show that greater communicative precision for warm than for cool colors, and greater communicative need, may both be explained by perceptual structure. However, using an information-theoretic analysis, we also show that color naming across languages bears signs of communicative need beyond what would be predicted by perceptual structure alone. We conclude that color naming is shaped both by perceptual structure, as has traditionally been argued, and by patterns of communicative need, as argued by Gibson et al. - although for reasons other than those they advanced. Copyright © 2018, The Authors. All rights reserved.

关键词： Color

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Biomimetic evolutionary analysis: Robotically-simulated vertebrates in a predator-prey ecology

Biomimetic evolutionary analysis: Robotically-simulated vert...

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IEEE Symposium on Artificial Life, ALIFE

作者： Nicole Doorly Kira Irving Gianna McArthur Keon Combie Virginia Engel Hassan Sakhtah Elise Stickles Hannah Rosenblum Andres Gutierrez Robert Root Chun Wai Liew John H. Long Mechanical and Aerospace Engineering Department Case Western Reserve University Cleveland OH USA Interdisciplinary Robotics Research Laboratory and the Cognitive Science Program Vassar College Poughkeepsie NY USA Neuroscience Institute Stanford University School of Medicine Stanford CA USA Neuroscience and Behavior Program Vassar College Poughkeepsie NY USA Memorial Sloan Kettering Cancer Care Center New York NY USA Department of Biology Vassar College Poughkeepsie NY USA Biochemistry Program Vassar College Poughkeepsie NY USA College of Medicine Howard University College of Medicine Washington D.C. USA School of Oceanography University of Washington Seattle WA USA Vassar College Poughkeepsie NY USA Department of Mathematics Lafayette College Easton PA USA Computer Science Department Lafayette College Easton PA USA Interdisciplinary Robotics Research Laboratory the Department of Biology and the Cognitive Science Program Vassar College Poughkeepsie NY USA

To test adaptation hypotheses about the evolution of animals, we need information about the behavior of phenotypically-variable individuals in a specific environment. To model behavior of ancient fish-like vertebrates, we previously combined evolutionary robotics and software simulations to create autonomous biomimetic swimmers in a simple aquatic environment competing and foraging for a single source of food. This system allowed us to test the hypothesis that selection for improved forage navigation drove the evolution of stiffer tails. In this paper, we extend our framework to evaluate more complex environments and hypotheses. Specifically, we test the hypothesis that predator-prey dynamics and the need for effective foraging strategies, operating simultaneously, were key selection pressures driving the evolution of morphological and sensory traits in early, fish-like vertebrates. Three evolvable traits were chosen because of their importance in propulsion and predator avoidance: (1) the number of vertebrae in the axial skeleton, (2) the trailing edge span of the caudal fin, and (3) the sensitivity of the sensory lateral line. To produce variable offspring, we used a genetic algorithm that rewarded parents with high fitness, allowing them to mate randomly and combine their mutated gametes. Offspring were then instantiated as autonomous embodied robots, the prey. These prey were chased by a non-evolving autonomous predator. Both kinds of robots were surface swimmers. The prey used a control architecture based on that of living fish: a two-layer subsumption architecture with predator escape over-riding steady swimming during foraging. The performance of six different prey robots in each generation was judged with a relative fitness function that rewarded a combination of high speed, rapid escape acceleration, escape responses, and the ability to stay away from the predator while at the same time staying close to the food source. This approach, which we call biomimet

关键词： Biomimetics Environmental factors Biological system modeling System testing Evolution (biology) Robot sensing systems Animals Navigation Tail Propulsion

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Modeling brain connectivity with graphical models on frequency domain

arXiv

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arXiv 2018年

作者： Gao, Xu Shen, Weining Ting, Chee-Ming Cramer, Steven C. Srinivasan, Ramesh Ombao, Hernando Department of Statistics University of California IrvineCA United States School of Biomedical Engineering and Health Sciences Universiti Teknologi Malaysia Malaysia Department of Anatomy and Neurobiology University of California IrvineCA United States Department of Cognitive Sciences University of California IrvineCA United States Statistics Program King Abdullah University of Science and Technology Thuwal Saudi Arabia

Multichannel electroencephalograms (EEGs) have been widely used to study cortical connectivity during acquisition of motor skills. In this paper, we introduce copula Gaussian graphical models on spectral domain to characterize dependence in oscillatory activity between channels. To obtain a simple and robust representation of brain connectivity that can explain the most variation in the observed signals, we propose a framework based on maximizing penalized likelihood with Lasso regularization to search for the sparse precision matrix. To address the optimization problem, graphical Lasso, Ledoit-Wolf and sparse estimation of a covariance matrix (SPCOV) algorithms were modified and implemented. Simulations show the benefit of using the proposed algorithms in terms of robustness and small estimation errors. Furthermore, analysis of the EEG data in a motor skill task conducted using algorithms of modified graphical LASSO and Ledoit-Wolf, reveal a sparse pattern of brain connectivity among cortices which is consistent with the results from other work in the literature. Copyright © 2018, The Authors. All rights reserved.

关键词： Electroencephalography

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