A functional model of sensemaking in a neurocognitive architecture.

Abstract:

:Sensemaking is the active process of constructing a meaningful representation (i.e., making sense) of some complex aspect of the world. In relation to intelligence analysis, sensemaking is the act of finding and interpreting relevant facts amongst the sea of incoming reports, images, and intelligence. We present a cognitive model of core information-foraging and hypothesis-updating sensemaking processes applied to complex spatial probability estimation and decision-making tasks. While the model was developed in a hybrid symbolic-statistical cognitive architecture, its correspondence to neural frameworks in terms of both structure and mechanisms provided a direct bridge between rational and neural levels of description. Compared against data from two participant groups, the model correctly predicted both the presence and degree of four biases: confirmation, anchoring and adjustment, representativeness, and probability matching. It also favorably predicted human performance in generating probability distributions across categories, assigning resources based on these distributions, and selecting relevant features given a prior probability distribution. This model provides a constrained theoretical framework describing cognitive biases as arising from three interacting factors: the structure of the task environment, the mechanisms and limitations of the cognitive architecture, and the use of strategies to adapt to the dual constraints of cognition and the environment.

journal_name

Comput Intell Neurosci

authors

Lebiere C,Pirolli P,Thomson R,Paik J,Rutledge-Taylor M,Staszewski J,Anderson JR

doi

10.1155/2013/921695

subject

Has Abstract

pub_date

2013-01-01 00:00:00

pages

921695

eissn

1687-5265

issn

1687-5273

journal_volume

2013

pub_type

杂志文章
  • Analysis of Residual Dependencies of Independent Components Extracted from fMRI Data.

    abstract::Independent component analysis (ICA) of functional magnetic resonance imaging (fMRI) data can be employed as an exploratory method. The lack in the ICA model of strong a priori assumptions about the signal or about the noise leads to difficult interpretations of the results. Moreover, the statistical independence of t...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2016/2961727

    authors: Vanello N,Ricciardi E,Landini L

    更新日期:2016-01-01 00:00:00

  • GA-Based Membrane Evolutionary Algorithm for Ensemble Clustering.

    abstract::Ensemble clustering can improve the generalization ability of a single clustering algorithm and generate a more robust clustering result by integrating multiple base clusterings, so it becomes the focus of current clustering research. Ensemble clustering aims at finding a consensus partition which agrees as much as po...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2017/4367342

    authors: Wang Y,Liu X,Xiang L

    更新日期:2017-01-01 00:00:00

  • A Chaotic Particle Swarm Optimization-Based Heuristic for Market-Oriented Task-Level Scheduling in Cloud Workflow Systems.

    abstract::Cloud workflow system is a kind of platform service based on cloud computing. It facilitates the automation of workflow applications. Between cloud workflow system and its counterparts, market-oriented business model is one of the most prominent factors. The optimization of task-level scheduling in cloud workflow syst...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2015/718689

    authors: Li X,Xu J,Yang Y

    更新日期:2015-01-01 00:00:00

  • Robust SAR Automatic Target Recognition Based on Transferred MS-CNN with L2-Regularization.

    abstract::Though Synthetic Aperture Radar (SAR) Automatic Target Recognition (ATR) via Convolutional Neural Networks (CNNs) has made huge progress toward deep learning, some key issues still remain unsolved due to the lack of sufficient samples and robust model. In this paper, we proposed an efficient transferred Max-Slice CNN ...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2019/9140167

    authors: Zhai Y,Deng W,Xu Y,Ke Q,Gan J,Sun B,Zeng J,Piuri V

    更新日期:2019-11-15 00:00:00

  • n-Iterative Exponential Forgetting Factor for EEG Signals Parameter Estimation.

    abstract::Electroencephalograms (EEG) signals are of interest because of their relationship with physiological activities, allowing a description of motion, speaking, or thinking. Important research has been developed to take advantage of EEG using classification or predictor algorithms based on parameters that help to describe...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2018/4613740

    authors: Aguilar Cruz KA,Zagaceta Álvarez MT,Palma Orozco R,Medel Juárez JJ

    更新日期:2018-01-15 00:00:00

  • A Platoon-Based Adaptive Signal Control Method with Connected Vehicle Technology.

    abstract::One important objective of urban traffic signal control is to reduce individual delay and improve safety for travelers in both private car and public bus transit. To achieve signal control optimization from the perspective of all users, this paper proposes a platoon-based adaptive signal control (PASC) strategy to pro...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2020/2764576

    authors: Li N,Chen S,Zhu J,Sun DJ

    更新日期:2020-06-01 00:00:00

  • Predictive Modeling in Race Walking.

    abstract::This paper presents the use of linear and nonlinear multivariable models as tools to support training process of race walkers. These models are calculated using data collected from race walkers' training events and they are used to predict the result over a 3 km race based on training loads. The material consists of 1...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2015/735060

    authors: Wiktorowicz K,Przednowek K,Lassota L,Krzeszowski T

    更新日期:2015-01-01 00:00:00

  • Inclusion of Neuropsychological Scores in Atrophy Models Improves Diagnostic Classification of Alzheimer's Disease and Mild Cognitive Impairment.

    abstract::Brain atrophy in mild cognitive impairment (MCI) and Alzheimer's disease (AD) are difficult to demarcate to assess the progression of AD. This study presents a statistical framework on the basis of MRI volumes and neuropsychological scores. A feature selection technique using backward stepwise linear regression togeth...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2015/865265

    authors: Goryawala M,Zhou Q,Barker W,Loewenstein DA,Duara R,Adjouadi M

    更新日期:2015-01-01 00:00:00

  • Neurophysiological Responses to Different Product Experiences.

    abstract::It is well known that the evaluation of a product from the shelf considers the simultaneous cerebral and emotional evaluation of the different qualities of the product such as its colour, the eventual images shown, and the envelope's texture (hereafter all included in the term "product experience"). However, the measu...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2018/9616301

    authors: Modica E,Cartocci G,Rossi D,Martinez Levy AC,Cherubino P,Maglione AG,Di Flumeri G,Mancini M,Montanari M,Perrotta D,Di Feo P,Vozzi A,Ronca V,Aricò P,Babiloni F

    更新日期:2018-09-24 00:00:00

  • A Reweighted Scheme to Improve the Representation of the Neural Autoregressive Distribution Estimator.

    abstract::The neural autoregressive distribution estimator(NADE) is a competitive model for the task of density estimation in the field of machine learning. While NADE mainly focuses on the problem of estimating density, the ability for dealing with other tasks remains to be improved. In this paper, we introduce a simple and ef...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2018/6401645

    authors: Wang Z,Wu Q

    更新日期:2018-12-23 00:00:00

  • Designs and Algorithms to Map Eye Tracking Data with Dynamic Multielement Moving Objects.

    abstract::Design concepts and algorithms were developed to address the eye tracking analysis issues that arise when (1) participants interrogate dynamic multielement objects that can overlap on the display and (2) visual angle error of the eye trackers is incapable of providing exact eye fixation coordinates. These issues were ...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2016/9354760

    authors: Kang Z,Mandal S,Crutchfield J,Millan A,McClung SN

    更新日期:2016-01-01 00:00:00

  • Analysis of human standing balance by largest lyapunov exponent.

    abstract::The purpose of this research is to analyse the relationship between nonlinear dynamic character and individuals' standing balance by the largest Lyapunov exponent, which is regarded as a metric for assessing standing balance. According to previous study, the largest Lyapunov exponent from centre of pressure time serie...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2015/158478

    authors: Liu K,Wang H,Xiao J,Taha Z

    更新日期:2015-01-01 00:00:00

  • Ranking of Sites for Installation of Hydropower Plant Using MLP Neural Network Trained with GA: A MADM Approach.

    abstract::Every energy system which we consider is an entity by itself, defined by parameters which are interrelated according to some physical laws. In recent year tremendous importance is given in research on site selection in an imprecise environment. In this context, decision making for the suitable location of power plant ...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2017/4152140

    authors: Shimray BA,Singh KM,Khelchandra T,Mehta RK

    更新日期:2017-01-01 00:00:00

  • Design of Festival Sentiment Classifier Based on Social Network.

    abstract::With the development of society, more and more attention has been paid to cultural festivals. In addition to the government's emphasis, the increasing consumption in festivals also proves that cultural festivals are playing increasingly important role in public life. Therefore, it is very vital to grasp the public fes...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2020/8824009

    authors: Yuan H,Song Y,Hu J,Ma Y

    更新日期:2020-08-07 00:00:00

  • A Db-Scan Binarization Algorithm Applied to Matrix Covering Problems.

    abstract::The integration of machine learning techniques and metaheuristic algorithms is an area of interest due to the great potential for applications. In particular, using these hybrid techniques to solve combinatorial optimization problems (COPs) to improve the quality of the solutions and convergence times is of great inte...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2019/3238574

    authors: García J,Moraga P,Valenzuela M,Crawford B,Soto R,Pinto H,Peña A,Altimiras F,Astorga G

    更新日期:2019-09-16 00:00:00

  • Cloud Model-Based Artificial Immune Network for Complex Optimization Problem.

    abstract::This paper proposes an artificial immune network based on cloud model (AINet-CM) for complex function optimization problems. Three key immune operators-cloning, mutation, and suppression-are redesigned with the help of the cloud model. To be specific, an increasing half cloud-based cloning operator is used to adjust t...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2017/5901258

    authors: Wang M,Feng S,Li J,Li Z,Xue Y,Guo D

    更新日期:2017-01-01 00:00:00

  • Large-Truck Safety Warning System Based on Lightweight SSD Model.

    abstract::Transportation is an important link in the mining process, and large trucks are one of the important tools for mine transportation. Due to their large size and small driving position, large trucks have a blind spot, which is a hidden danger to the safe transportation of mines and has a great impact on production effic...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2019/2180294

    authors: Xiao D,Li H,Liu C,He Q

    更新日期:2019-10-13 00:00:00

  • Modified Mahalanobis Taguchi System for Imbalance Data Classification.

    abstract::The Mahalanobis Taguchi System (MTS) is considered one of the most promising binary classification algorithms to handle imbalance data. Unfortunately, MTS lacks a method for determining an efficient threshold for the binary classification. In this paper, a nonlinear optimization model is formulated based on minimizing...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2017/5874896

    authors: El-Banna M

    更新日期:2017-01-01 00:00:00

  • The track of brain activity during the observation of TV commercials with the high-resolution EEG technology.

    abstract::We estimate cortical activity in normal subjects during the observation of TV commercials inserted within a movie by using high-resolution EEG techniques. The brain activity was evaluated in both time and frequency domains by solving the associate inverse problem of EEG with the use of realistic head models. In partic...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2009/652078

    authors: Astolfi L,Vecchiato G,De Vico Fallani F,Salinari S,Cincotti F,Aloise F,Mattia D,Marciani MG,Bianchi L,Soranzo R,Babiloni F

    更新日期:2009-01-01 00:00:00

  • EEGLAB, SIFT, NFT, BCILAB, and ERICA: new tools for advanced EEG processing.

    abstract::We describe a set of complementary EEG data collection and processing tools recently developed at the Swartz Center for Computational Neuroscience (SCCN) that connect to and extend the EEGLAB software environment, a freely available and readily extensible processing environment running under Matlab. The new tools incl...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2011/130714

    authors: Delorme A,Mullen T,Kothe C,Akalin Acar Z,Bigdely-Shamlo N,Vankov A,Makeig S

    更新日期:2011-01-01 00:00:00

  • Software Development Effort Estimation Using Regression Fuzzy Models.

    abstract::Software effort estimation plays a critical role in project management. Erroneous results may lead to overestimating or underestimating effort, which can have catastrophic consequences on project resources. Machine-learning techniques are increasingly popular in the field. Fuzzy logic models, in particular, are widely...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2019/8367214

    authors: Nassif AB,Azzeh M,Idri A,Abran A

    更新日期:2019-02-20 00:00:00

  • Study on the calculation models of bus delay at bays using queueing theory and Markov chain.

    abstract::Traffic congestion at bus bays has decreased the service efficiency of public transit seriously in China, so it is crucial to systematically study its theory and methods. However, the existing studies lack theoretical model on computing efficiency. Therefore, the calculation models of bus delay at bays are studied. Fi...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2015/750304

    authors: Sun F,Sun L,Sun SW,Wang DH

    更新日期:2015-01-01 00:00:00

  • Explore Interregional EEG Correlations Changed by Sport Training Using Feature Selection.

    abstract::This paper investigated the interregional correlation changed by sport training through electroencephalography (EEG) signals using the techniques of classification and feature selection. The EEG data are obtained from students with long-time professional sport training and normal students without sport training as bas...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2016/6184823

    authors: Gao J,Wang W,Zhang J

    更新日期:2016-01-01 00:00:00

  • Prediction of Attendance Demand in European Football Games: Comparison of ANFIS, Fuzzy Logic, and ANN.

    abstract::An artificial neural network (ANN), adaptive neurofuzzy inference system (ANFIS) models, and fuzzy rule-based system (FRBS) models are developed to predict the attendance demand in European football games, in this paper. To determine the most successful method, each of the methods is analyzed under different situation...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2018/5714872

    authors: Şahin M,Erol R

    更新日期:2018-08-07 00:00:00

  • Towards an Accessible Use of a Brain-Computer Interfaces-Based Home Care System through a Smartphone.

    abstract::This study proposes a home care system (HCS) based on a brain-computer interface (BCI) with a smartphone. The HCS provides daily help to motor-disabled people when a caregiver is not present. The aim of the study is two-fold: (1) to develop a BCI-based home care system to help end-users control their household applian...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2020/1843269

    authors: Sun KT,Hsieh KL,Syu SR

    更新日期:2020-08-28 00:00:00

  • New algorithms for computing the time-to-collision in freeway traffic simulation models.

    abstract::Ways to estimate the time-to-collision are explored. In the context of traffic simulation models, classical lane-based notions of vehicle location are relaxed and new, fast, and efficient algorithms are examined. With trajectory conflicts being the main focus, computational procedures are explored which use a two-dime...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2014/761047

    authors: Hou J,List GF,Guo X

    更新日期:2014-01-01 00:00:00

  • Hybrid Degradation Equipment Remaining Useful Life Prediction Oriented Parallel Simulation considering Model Soft Switch.

    abstract::Equipment parallel simulation is an emerging simulation technology in recent years, and equipment remaining useful life (RUL) prediction oriented parallel simulation is an important branch of parallel simulation. An important concept in equipment parallel simulation is the model evolution driven by real-time data, inc...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2019/9179870

    authors: Ge C,Zhu Y,Di Y

    更新日期:2019-03-12 00:00:00

  • Improved Transductive Support Vector Machine for a Small Labelled Set in Motor Imagery-Based Brain-Computer Interface.

    abstract::Long and tedious calibration time hinders the development of motor imagery- (MI-) based brain-computer interface (BCI). To tackle this problem, we use a limited labelled set and a relatively large unlabelled set from the same subject for training based on the transductive support vector machine (TSVM) framework. We fi...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2019/2087132

    authors: Xu Y,Hua J,Zhang H,Hu R,Huang X,Liu J,Guo F

    更新日期:2019-11-25 00:00:00

  • Towards development of a 3-state self-paced brain-computer interface.

    abstract::Most existing brain-computer interfaces (BCIs) detect specific mental activity in a so-called synchronous paradigm. Unlike synchronous systems which are operational at specific system-defined periods, self-paced (asynchronous) interfaces have the advantage of being operational at all times. The low-frequency asynchron...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2007/84386

    authors: Bashashati A,Ward RK,Birch GE

    更新日期:2007-01-01 00:00:00

  • High-frequency electroencephalographic activity in left temporal area is associated with pleasant emotion induced by video clips.

    abstract::Recent findings suggest that specific neural correlates for the key elements of basic emotions do exist and can be identified by neuroimaging techniques. In this paper, electroencephalogram (EEG) is used to explore the markers for video-induced emotions. The problem is approached from a classifier perspective: the fea...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2015/762769

    authors: Kortelainen J,Väyrynen E,Seppänen T

    更新日期:2015-01-01 00:00:00