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A General Architecture for Social Intelligence in the Human Mind & Brain

Procedia Computer science 2018年 145卷 747-756页

作者： Jeungmin Lee Jerald D. Kralik Jaeseung Jeong Department of Bio and Brain Engineering College of Engineering Korea Advanced Institute of Science and Technology (KAIST) Daejeon 34141 South Korea Program of Brain and Cognitive Engineering College of Engineering Korea Advanced Institute of Science and Technology (KAIST) Daejeon 34141 South Korea

Substantial evidence has amassed for social cognition in the human mind and brain, but surprisingly little theoretical work exists that organizes the information in a complete, coherent framework. To address this deficiency, we recently developed a general framework of social intelligence. Here we describe multiple further developments. In particular, we develop metacognitive control over the entire process of problem-solving based on social information, including management of multiple simultaneous problems, and active outcome monitoring. We better delineate the critical influence of affect/emotion, and we distinguish structure vs process throughout the model more explicitly, including specifying the inputs and outputs of each main process. Ultimately, a comprehensive social cognitive architecture will be needed for the common model of cognition.

关键词： Social cognition decision-making theory of mind social neuroscience multiagent systems artificial social intelligence

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Analysis of font legibility for Korean serif and sans serif types in printed and displayed settings

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Proceedings of the Human Factors and Ergonomics Society Annual Meeting 2016年第1期59卷 1774 - 1777页

作者： Minjee KIM Sung-Hwan PARK Sung Hee AHN Myung Bin CHOI Myung-Hwan Yun Interdisciplinary Program in Cognitive Science Seoul National University Seoul Republic of Korea Department of Industrial Engineering Seoul National University Seoul Republic of Korea

Activities with smart devices have been more complicated and diversified, and font legibility influences these activities both directly and indirectly. This study investigated the difference of Korean font legibility between printed paper and VDT. Four Korean fonts, Dodum and Gulim - sans serif types, and Batang and Gungseo - serif types, were compared in experiments. The result showed that there was a significant difference in the font legibility for printed paper, but not for VDT. On printed paper, serif types were more legible than sans serif types. However, a significant difference between serif types and sans serif types were not found in VDT. Dodum, one of the sans serif font types achieved the highest score on preference in the survey questionnaire among the four Korean fonts. The paper suggests that serif types did not always provide the optimal legibility in VDT.

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Auditory Segmentation Based on Event Detection

Auditory Segmentation Based on Event Detection

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2004 ISCA Tutorial and Research Workshop on Statistical and Perceptual Audio Processing, SAPA 2004

作者： Hu, Guoning Wang, DeLiang Biophysics Program The Ohio State University 395 Dreese Lab. 2015 Neil Ave ColumbusOH43210 United States Department of Computer Science and Engineering Center for Cognitive Science The Ohio State University 395 Dreese Lab. 2015 Neil Ave ColumbusOH43210 United States

Acoustic signals from different sources in a natural environment form an auditory scene. Auditory scene analysis (ASA) is the process in which the auditory system segregates an auditory scene into streams corresponding to different sources. Segmentation is an important stage of ASA where an auditory scene is decomposed into segments, each of which contains signal mainly from one source. We propose a system for auditory segmentation based on analyzing onsets and offsets of auditory events. Our system first detects onsets and offsets, and then generates segments by matching corresponding onsets and offsets. This is achieved through a multiscale approach based on scale-space theory. Systematic evaluation shows that much target speech, including unvoiced speech, is correctly segmented, and target speech and interference are well separated into different segments. © SAPA 2004. All rights reserved.

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An integrative systems-biology approach defines mechanisms of Alzheimer’s disease neurodegeneration

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Nature Communications 2025年第1期16卷 1-21页

作者： Leventhal, Matthew J. Zanella, Camila A. Kang, Byunguk Peng, Jiajie Gritsch, David Liao, Zhixiang Bukhari, Hassan Wang, Tao Pao, Ping-Chieh Danquah, Serwah Benetatos, Joseph Nehme, Ralda Farhi, Samouil Tsai, Li-Huei Dong, Xianjun Scherzer, Clemens R. Feany, Mel B. Fraenkel, Ernest MIT Ph.D. Program in Computational and Systems Biology Cambridge MA United States Department of Biological Engineering Massachusetts Institute of Technology Cambridge MA United States Broad Institute of Harvard and MIT Cambridge MA United States Department of Pathology Brigham and Women’s Hospital and Harvard Medical School Boston MA United States Spatial Technology Platform Broad Institute of Harvard and MIT Cambridge MA United States Precision Neurology Program Brigham and Women’s Hospital and Harvard Medical school Boston MA United States APDA Center for Advanced Parkinson’s Disease Research Brigham and Women’s Hospital and Harvard Medical School Boston MA United States Picower Institute for Learning and Memory Massachusetts Institute of Technology Cambridge MA United States Department of Brain and Cognitive Sciences Massachusetts Institute of Technology Cambridge MA United States Stanley Center for Psychiatric Research Broad Institute of Harvard and MIT Cambridge MA United States School of Computer Science Northwestern Polytechnical University Xi’an China Stephen and Denise Adams Center of Yale School of Medicine New Haven CT United States

Despite years of intense investigation, the mechanisms underlying neuronal death in Alzheimer’s disease, remain incompletely understood. To define relevant pathways, we conducted an unbiased, genome-scale forward genetic screen for age-associated neurodegeneration in Drosophila. We also measured proteomics, phosphoproteomics, and metabolomics in Drosophila models of Alzheimer’s disease and identified Alzheimer’s genetic variants that modify gene expression in disease-vulnerable neurons in humans. We then used a network model to integrate these data with previously published Alzheimer’s disease proteomics, lipidomics and genomics. Here, we computationally predict and experimentally confirm how HNRNPA2B1 and MEPCE enhance toxicity of the tau protein, a pathological feature of Alzheimer’s disease. Furthermore, we demonstrated that the screen hits CSNK2A1 and NOTCH1 regulate DNA damage in Drosophila and human stem cell-derived neural progenitor cells. Our study identifies candidate pathways that could be targeted to ameliorate neurodegeneration in Alzheimer’s disease. © The Author(s) 2025.

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Micro-objective learning: Accelerating deep reinforcement learning through the discovery of continuous subgoals

arXiv

引用

arXiv 2017年

作者： Lee, Sungtae Lee, Sang-Woo Choi, Jinyoung Kwak, Dong-Hyun Zhang, Byoung-Tak School of Computer Science and Engineering Seoul National University College of Medicine Yonsei University Interdisciplinary Program in Cognitive Science Seoul National University Interdisciplinary Program in Neuroscience Seoul National University

Recently, reinforcement learning has been successfully applied to the logical game of Go, various Atari games, and even a 3D game, Labyrinth, though it continues to have problems in sparse reward settings. It is difficult to explore, but also difficult to exploit, a small number of successes when learning policy. To solve this issue, the subgoal and option framework have been proposed. However, discovering subgoals online is too expensive to be used to learn options in large state spaces. We propose Micro-objective learning (MOL) to solve this problem. The main idea is to estimate how important a state is while training and to give an additional reward proportional to its importance. We evaluated our algorithm in two Atari games: Montezuma's Revenge and Seaquest. With three experiments to each game, MOL significantly improved the baseline scores. Especially in Montezuma's Revenge, MOL achieved two times better results than the previous state-of-the-art model. Copyright © 2017, The Authors. All rights reserved.

关键词： Deep learning

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Glushko Dissertation Prize Symposium 35

Glushko Dissertation Prize Symposium

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35th Annual Meeting of the cognitive science Society - Cooperative Minds: Social Interaction and Group Dynamics, CogSci 2013

作者： Bemis, Douglas Knox Cohn, Neil Kachergis, George Lovett, Andrew Goldstone, Robert L. NSERM-CEA Cognitive Neuroimaging Unit CEA/SAC/DSV/DRM/Neurospin Center Gif-sur-YvetteCedex F-91191 France Center for Research in Language University of California La Jolla San DiegoCA92093-0526 United States Cognitive Psychology Unit Leiden Institute for Brain and Cognition LeidenNL-2333 AK Netherlands Dept. of Electrical Engineering & Computer Science Northwestern University EvanstonIL60208-3118 United States Department of Psychological and Brain Sciences Program in Cognitive Science Indiana University BloomingtonIN47405 United States

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3D-to-2D-to-3D Conscious Learning

3D-to-2D-to-3D Conscious Learning

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2022 IEEE International Conference on Consumer Electronics, ICCE 2022

作者： Weng, Juyang Department of Computer Science and Engineering Michigan State University East LansingMI48824 United States Cognitive Science Program Michigan State University East LansingMI48824 United States Neuroscience Program Michigan State University East LansingMI48824 United States Brain-Mind Institute OkemosMI48864 United States GENISAMA OkemosMI48864 United States

ISBN: (纸本)9781665441544

This is a theoretical paper on conscious learning for thoughts and creativity through general-purpose and autonomous imitation of demonstrations. This conscious learning is end-to-end (3D-to-2D-to-3D) and free from annotations of 2D images and 2D motor images (e.g., a bounding box to be attended to). The conscious learning algorithm directly takes that of the Developmental Networks that has been previously published extensively with rich experimental results. Apparently, humans and animals do this type of fully automated learning daily, but it is unclear a robot can do the same. Recently, [1], [2] presented a theory of conscious learning rooted in emergent universal Turing machines. It appeared to be the first algorithmic level theory of holistic consciousness, other than many papers in the literature about piecemeal consciousness. However, [1], [2] proved only conscious learning in motor-imposed training mode, namely 3D-to-2D taught by 2D motor impositions, free from 2D annotations. This paper fills the challenging gap in [1], [2] so the conscious learning is 3D-to-2D-to-3D (end-to-end) without motor-impositions or computing 'inverse kinematics'. This is a major departure from traditional AI-handcrafting symbolic labels that tend to be brittle (e.g., for driverless cars) and then 'spoon-feeding' pre-collected 'big data'. Autonomous imitations drastically reduce the teaching complexity compared to pre-collected 'big data', especially because no annotations of training data are needed. Furthermore, conscious learning allows creativity beyond what is taught. This work is directly related to consumer electronics because it requires large-scale on-the-fly brainoid chips in future wearable robots/devices for consumers. © 2022 IEEE.

关键词： Big data

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A neural model for sonar-based navigation in obstacle fields

A neural model for sonar-based navigation in obstacle fields

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： T.K. Horiuchi Institute for Systems Research & The Neuroscience and Cognitive Science Program Electrical and Computer Engineering Department University of Maryland College Park MD USA

The rapid control of sonar-guided vehicles through obstacle fields has been a goal of robotics for decades. How sensory data is represented strongly affects how obstacles and goal information can be combined to select a direction of travel. While typical approaches combine attractive and repulsive effects to directly determine steering, we are investigating an algorithm that evaluates multiple directions simultaneously followed by a winner-take-all (WTA) function which then guides steering. In this paper we describe a neuromorphic VLSI implementation of this algorithm using the inherent echo delay to create a range-dependent gain in a 'race-to-first-spike' neural WTA circuit. The chip was fabricated in a commercially-available 0.5 mum CMOS process and in this paper we present preliminary test results

关键词： Sonar navigation Robot sensing systems Neurons Automotive engineering Neuroscience cognitive science Educational institutions Control systems Vehicles cognitive robotics

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infotheory: A C++/Python package for multivariate information theoretic analysis

arXiv

引用

arXiv 2019年

作者： Candadai, Madhavun Izquierdo, Eduardo J. Program in Cognitive Science Indiana University Bloomington United States School of Informatics Computing and Engineering Indiana University Bloomington United States

This paper introduces infotheory: a package written in C++ and usable from Python and C++, for multivariate information theoretic analyses of discrete and continuous data. This package allows the user to study the relationship between components of a complex system simply from the data recorded during its operation, using the tools of information theory. It implements widely used measures such as entropy and mutual information, as well as more recent measures that arise from multivariate extensions to information theory, specifically Partial Information Decomposition. It provides an easy-to-use and flexible tool for use in research as well as pedgogical purposes to introduce students to information theory. Copyright © 2019, The Authors. All rights reserved.

关键词： Information theory

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A summating, exponentially-decaying CMOS synapse for spiking neural systems

A summating, exponentially-decaying CMOS synapse for spiking...

引用

17th Annual Conference on Neural Information Processing Systems, NIPS 2003

作者： Shi, Rock Z. Horiuchi, Timothy Electrical and Computer Engineering Department University of Maryland College Park MD 20742 United States Institute for Systems Research University of Maryland College Park MD 20742 United States Neuroscience and Cognitive Science Program University of Maryland College Park MD 20742 United States

ISBN: (纸本)0262201526

Synapses are a critical element of biologically-realistic, spike-based neural computation, serving the role of communication, computation, and modification. Many different circuit implementations of synapse function exist with different computational goals in mind. In this paper we describe a new CMOS synapse design that separately controls quiescent leak current, synaptic gain, and time-constant of decay. This circuit implements part of a commonly-used kinetic model of synaptic conductance. We show a theoretical analysis and experimental data for prototypes fabricated in a commercially-available 1.5μm CMOS process.

关键词： CMOS integrated circuits

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