Characterizing the Input-Output Function of the Olfactory-Limbic Pathway in the Guinea Pig.

Abstract:

:Nowadays the neuroscientific community is taking more and more advantage of the continuous interaction between engineers and computational neuroscientists in order to develop neuroprostheses aimed at replacing damaged brain areas with artificial devices. To this end, a technological effort is required to develop neural network models which can be fed with the recorded electrophysiological patterns to yield the correct brain stimulation to recover the desired functions. In this paper we present a machine learning approach to derive the input-output function of the olfactory-limbic pathway in the in vitro whole brain of guinea pig, less complex and more controllable than an in vivo system. We first experimentally characterized the neuronal pathway by delivering different sets of electrical stimuli from the lateral olfactory tract (LOT) and by recording the corresponding responses in the lateral entorhinal cortex (l-ERC). As a second step, we used information theory to evaluate how much information output features carry about the input. Finally we used the acquired data to learn the LOT-l-ERC "I/O function," by means of the kernel regularized least squares method, able to predict l-ERC responses on the basis of LOT stimulation features. Our modeling approach can be further exploited for brain prostheses applications.

journal_name

Comput Intell Neurosci

authors

Breschi GL,Ciliberto C,Nieus T,Rosasco L,Taverna S,Chiappalone M,Pasquale V

doi

10.1155/2015/359590

subject

Has Abstract

pub_date

2015-01-01 00:00:00

pages

359590

eissn

1687-5265

issn

1687-5273

journal_volume

2015

pub_type

杂志文章
  • Modelling of Asphalt's Adhesive Behaviour Using Classification and Regression Tree (CART) Analysis.

    abstract::The modification by polymers and nanomaterials can significantly improve different properties of asphalt. However, during the service life, the oxidation affects the constituents of modified asphalt and subsequently results in deviation from the desired properties. One of the important properties affected due to oxida...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2019/3183050

    authors: Arifuzzaman M,Gazder U,Alam MS,Sirin O,Mamun AA

    更新日期:2019-08-15 00:00:00

  • Learning-Based Visual Saliency Model for Detecting Diabetic Macular Edema in Retinal Image.

    abstract::This paper brings forth a learning-based visual saliency model method for detecting diagnostic diabetic macular edema (DME) regions of interest (RoIs) in retinal image. The method introduces the cognitive process of visual selection of relevant regions that arises during an ophthalmologist's image examination. To reco...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2016/7496735

    authors: Zou X,Zhao X,Yang Y,Li N

    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

  • Modeling spike-train processing in the cerebellum granular layer and changes in plasticity reveal single neuron effects in neural ensembles.

    abstract::The cerebellum input stage has been known to perform combinatorial operations on input signals. In this paper, two types of mathematical models were used to reproduce the role of feed-forward inhibition and computation in the granular layer microcircuitry to investigate spike train processing. A simple spiking model a...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2012/359529

    authors: Medini C,Nair B,D'Angelo E,Naldi G,Diwakar S

    更新日期:2012-01-01 00:00:00

  • A Competitive Multiattribute Group Decision-Making Approach for the Game between Manufacturers.

    abstract::Under the competitive market environment, the game between manufacturers comes down to the competitive multiattribute group decision-making problem. In this study, the evaluation information of experts is given in the form of 2-dimension 2-tuple linguistic variables, and an approach is proposed for the competitive mul...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2019/8389035

    authors: Zhang Q,Jiang K,Yan M,Ma J

    更新日期:2019-11-11 00:00:00

  • 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 cog...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2013/921695

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

    更新日期:2013-01-01 00:00:00

  • Operating Comfort Prediction Model of Human-Machine Interface Layout for Cabin Based on GEP.

    abstract::In view of the evaluation and decision-making problem of human-machine interface layout design for cabin, the operating comfort prediction model is proposed based on GEP (Gene Expression Programming), using operating comfort to evaluate layout scheme. Through joint angles to describe operating posture of upper limb, t...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2015/896072

    authors: Deng L,Wang G,Chen B

    更新日期:2015-01-01 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

  • Classifying EEG Signals during Stereoscopic Visualization to Estimate Visual Comfort.

    abstract::With stereoscopic displays a sensation of depth that is too strong could impede visual comfort and may result in fatigue or pain. We used Electroencephalography (EEG) to develop a novel brain-computer interface that monitors users' states in order to reduce visual strain. We present the first system that discriminates...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2016/2758103

    authors: Frey J,Appriou A,Lotte F,Hachet M

    更新日期:2016-01-01 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

  • 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

  • HDEC: A Heterogeneous Dynamic Ensemble Classifier for Binary Datasets.

    abstract::In recent years, ensemble classification methods have been widely investigated in both industry and literature in the field of machine learning and artificial intelligence. The main advantage of this approach is to benefit from a set of classifiers instead of using a single classifier with the aim of improving the pre...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2020/8826914

    authors: Ostvar N,Eftekhari Moghadam AM

    更新日期:2020-12-14 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

  • Simultaneous EEG-fMRI in patients with Unverricht-Lundborg disease: event-related desynchronization/synchronization and hemodynamic response analysis.

    abstract::We performed simultaneous acquisition of EEG-fMRI in seven patients with Unverricht-Lundborg disease (ULD) and in six healthy controls using self-paced finger extension as a motor task. The event-related desynchronization/synchronization (ERD/ERS) analysis showed a greater and more diffuse alpha desynchronization in c...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2010/164278

    authors: Visani E,Minati L,Canafoglia L,Gilioli I,Salvatoni L,Varotto G,Fazio P,Aquino D,Bruzzone MG,Franceschetti S,Panzica F

    更新日期:2010-01-01 00:00:00

  • Reducing the Schizophrenia Stigma: A New Approach Based on Augmented Reality.

    abstract::Schizophrenia is a chronic mental disease that usually manifests psychotic symptoms and affects an individual's functionality. The stigma related to this disease is a serious obstacle for an adequate approach to its treatment. Stigma can, for example, delay the start of treatment, and it creates difficulties in interp...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2017/2721846

    authors: Silva RDC,Albuquerque SGC,Muniz AV,Filho PPR,Ribeiro S,Pinheiro PR,Albuquerque VHC

    更新日期:2017-01-01 00:00:00

  • A novel design of 4-class BCI using two binary classifiers and parallel mental tasks.

    abstract::A novel 4-class single-trial brain computer interface (BCI) based on two (rather than four or more) binary linear discriminant analysis (LDA) classifiers is proposed, which is called a "parallel BCI." Unlike other BCIs where mental tasks are executed and classified in a serial way one after another, the parallel BCI u...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2008/437306

    authors: Geng T,Gan JQ,Dyson M,Tsui CS,Sepulveda F

    更新日期:2008-01-01 00:00:00

  • An Approach to Improve SSD through Skip Connection of Multiscale Feature Maps.

    abstract::SSD (Single Shot MultiBox Detector) is one of the best object detection algorithms and is able to provide high accurate object detection performance in real time. However, SSD shows relatively poor performance on small object detection because its shallow prediction layer, which is responsible for detecting small obje...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2020/2936920

    authors: Zhang X,Gao Y,Ye F,Liu Q,Zhang K

    更新日期:2020-04-05 00:00:00

  • A novel single neuron perceptron with universal approximation and XOR computation properties.

    abstract::We propose a biologically motivated brain-inspired single neuron perceptron (SNP) with universal approximation and XOR computation properties. This computational model extends the input pattern and is based on the excitatory and inhibitory learning rules inspired from neural connections in the human brain's nervous sy...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2014/746376

    authors: Lotfi E,Akbarzadeh-T MR

    更新日期:2014-01-01 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

  • Embedding Undersampling Rotation Forest for Imbalanced Problem.

    abstract::Rotation Forest is an ensemble learning approach achieving better performance comparing to Bagging and Boosting through building accurate and diverse classifiers using rotated feature space. However, like other conventional classifiers, Rotation Forest does not work well on the imbalanced data which are characterized ...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2018/6798042

    authors: Guo H,Diao X,Liu H

    更新日期:2018-11-01 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

  • Study on optimized Elman neural network classification algorithm based on PLS and CA.

    abstract::High-dimensional large sample data sets, between feature variables and between samples, may cause some correlative or repetitive factors, occupy lots of storage space, and consume much computing time. Using the Elman neural network to deal with them, too many inputs will influence the operating efficiency and recognit...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2014/724317

    authors: Jia W,Zhao D,Shen T,Tang Y,Zhao Y

    更新日期:2014-01-01 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

  • Fuzzy Classification of High Resolution Remote Sensing Scenes Using Visual Attention Features.

    abstract::In recent years the spatial resolutions of remote sensing images have been improved greatly. However, a higher spatial resolution image does not always lead to a better result of automatic scene classification. Visual attention is an important characteristic of the human visual system, which can effectively help to cl...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2017/9858531

    authors: Li L,Xu T,Chen Y

    更新日期:2017-01-01 00:00:00

  • Liraglutide Activates the Nrf2/HO-1 Antioxidant Pathway and Protects Brain Nerve Cells against Cerebral Ischemia in Diabetic Rats.

    abstract::This study aimed to determine the effect of liraglutide pretreatment and to elucidate the mechanism of nuclear factor erythroid 2-related factor (Nrf2)/heme oxygenase-1 (HO-1) signaling after focal cerebral ischemia injury in diabetic rats model. Adult male Sprague-Dawley rats were randomly divided into the sham-opera...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2018/3094504

    authors: Deng C,Cao J,Han J,Li J,Li Z,Shi N,He J

    更新日期:2018-02-12 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

  • A red-light running prevention system based on artificial neural network and vehicle trajectory data.

    abstract::The high frequency of red-light running and complex driving behaviors at the yellow onset at intersections cannot be explained solely by the dilemma zone and vehicle kinematics. In this paper, the author presented a red-light running prevention system which was based on artificial neural networks (ANNs) to approximate...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2014/892132

    authors: Li P,Li Y,Guo X

    更新日期:2014-01-01 00:00:00

  • Feature selection with neighborhood entropy-based cooperative game theory.

    abstract::Feature selection plays an important role in machine learning and data mining. In recent years, various feature measurements have been proposed to select significant features from high-dimensional datasets. However, most traditional feature selection methods will ignore some features which have strong classification a...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2014/479289

    authors: Zeng K,She K,Niu X

    更新日期:2014-01-01 00:00:00

  • Pilot Study on Gait Classification Using fNIRS Signals.

    abstract::Rehabilitation training is essential for motor dysfunction patients, and the training through their subjective motion intention, comparing to passive training, is more conducive to rehabilitation. This study proposes a method to identify motion intention of different walking states under the normal environment, by usi...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2018/7403471

    authors: Jin H,Li C,Xu J

    更新日期:2018-10-17 00:00:00

  • Real-Time Control of a Video Game Using Eye Movements and Two Temporal EEG Sensors.

    abstract::EEG-controlled gaming applications range widely from strictly medical to completely nonmedical applications. Games can provide not only entertainment but also strong motivation for practicing, thereby achieving better control with rehabilitation system. In this paper we present real-time control of video game with eye...

    journal_title:Computational intelligence and neuroscience

    pub_type: 杂志文章

    doi:10.1155/2015/653639

    authors: Belkacem AN,Saetia S,Zintus-art K,Shin D,Kambara H,Yoshimura N,Berrached N,Koike Y

    更新日期:2015-01-01 00:00:00