Search results for "Cognitive Neuroscience"

Affective matching of odors and facial expressions in infants: shifting patterns between 3 and 7 months.

2016

Recognition of emotional facial expressions is a crucial skill for adaptive behavior. Past research suggests that at 5 to 7 months of age, infants look longer to an unfamiliar dynamic angry/happy face which emotionally matches a vocal expression. This suggests that they can match stimulations of distinct modalities on their emotional content. In the present study, olfaction-vision matching abilities were assessed across different age groups (3, 5 and 7 months) using dynamic expressive faces (happy vs. disgusted) and distinct hedonic odor contexts (pleasant, unpleasant and control) in a visual-preference paradigm. At all ages the infants were biased toward the disgust faces. This visual bias…

When Choice Makes Sense: Menthol Influence on Mating, Oviposition and Fecundity in Drosophila melanogaster

2016

International audience; The environment to which insects have been exposed as larvae and adults can affect subsequent behaviors, such as mating, oviposition, food preference or fitness. Experience can change female preference for oviposition, particularly in phytophagous insects. In Drosophila melanogaster, females avoid laying eggs on menthol rich-food when given the choice. Exposure to menthol during larval development reduces this aversion. However, this observation was not reproduced in the following generation. Recently, we have shown that oviposition-site preference (OSP) differs between wild type D. melanogaster lines freely or forcibly exposed to menthol. After 12 generations, menth…

2018

<b><i>Background:</i></b> A major and complex challenge when trying to support individuals with dementia is meeting the needs of those who experience changes in behaviour and mood. <b><i>Aim:</i></b> To explore how a sensor measuring electrodermal activity (EDA) impacts assistant nurses’ structured assessments of problematic behaviours amongst people with dementia and their choices of care interventions. <b><i>Methods:</i></b> Fourteen individuals with dementia wore a sensor that measured EDA. The information from the sensor was presented to assistant nurses during structured assessments of problematic behaviours. The e…

UJI RobInLab's approach to the Amazon Robotics Challenge 2017

2017

This paper describes the approach taken by the team from the Robotic Intelligence Laboratory at Jaume I University to the Amazon Robotics Challenge 2017. The goal of the challenge is to automate pick and place operations in unstructured environments, specifically the shelves in an Amazon warehouse. RobInLab's approach is based on a Baxter Research robot and a customized storage system. The system's modular architecture, based on ROS, allows communication between two computers, two Arduinos and the Baxter. It integrates 9 hardware components along with 10 different algorithms to accomplish the pick and stow tasks. We describe the main components and pipelines of the system, along with some e…

Extreme minimal learning machine: Ridge regression with distance-based basis

2019

The extreme learning machine (ELM) and the minimal learning machine (MLM) are nonlinear and scalable machine learning techniques with a randomly generated basis. Both techniques start with a step in which a matrix of weights for the linear combination of the basis is recovered. In the MLM, the feature mapping in this step corresponds to distance calculations between the training data and a set of reference points, whereas in the ELM, a transformation using a radial or sigmoidal activation function is commonly used. Computation of the model output, for prediction or classification purposes, is straightforward with the ELM after the first step. In the original MLM, one needs to solve an addit…

2D/3D Object Recognition and Categorization Approaches for Robotic Grasping

2017

International audience; Object categorization and manipulation are critical tasks for a robot to operate in the household environment. In this paper, we propose new methods for visual recognition and categorization. We describe 2D object database and 3D point clouds with 2D/3D local descriptors which we quantify with the k-means clustering algorithm for obtaining the Bag of Words (BOW). Moreover, we develop a new global descriptor called VFH-Color that combines the original version of Viewpoint Feature Histogram (VFH) descriptor with the color quantization histogram, thus adding the appearance information that improves the recognition rate. The acquired 2D and 3D features are used for train…

Simulation Goals and Metrics Identification

2016

Agent-Based Modeling and Simulation (ABMS) is a very useful means for producing high quality models during simulation studies. When ABMS is part of a methodological ap- proach it becomes important to have a method for identifying the objectives of the simulation study in a disciplined fashion. In this work we propose a set of guidelines for properly capturing and representing the goals of the simulations and the metrics, allowing and evaluating the achievement of a simulation objective. We take inspiration from the goal-question-metric approach and with the aid of a specific problem formalization we are able to derive the right questions for relating simulation goals and metrics.

Fault detection for nonlinear networked systems based on quantization and dropout compensation: An interval type-2 fuzzy-model method

2016

Abstract This paper investigates the problem of filter-based fault detection for a class of nonlinear networked systems subject to parameter uncertainties in the framework of the interval type-2 (IT2) T–S fuzzy model-based approach. The Bernoulli random distribution process and logarithm quantizer are used to describe the measurement loss and signals quantization, respectively. In the framework of the IT2 T–S fuzzy model, the parameter uncertainty is handled by the membership functions with lower and upper bounds. A novel IT2 fault detection filter is designed to guarantee the residual system to be stochastically stable and satisfy the predefined H ∞ performance. It should be mentioned that…

Exposure to a Highly Caloric Palatable Diet During Pregestational and Gestational Periods Affects Hypothalamic and Hippocampal Endocannabinoid Levels…

2016

Journal Article; Exposure to unbalanced diets during pre-gestational and gestational periods may result in long-term alterations in metabolism and behavior. The contribution of the endocannabinoid system to these long-term adaptive responses is unknown. In the present study, we investigated the impact of female rat exposure to a hypercaloric-hypoproteic palatable diet during pre-gestational, gestational and lactational periods on the development of male offspring. In addition, the hypothalamic and hippocampal endocannabinoid contents at birth and the behavioral performance in adulthood were investigated. Exposure to a palatable diet resulted in low weight offspring who exhibited low hypotha…

Peripheral Maintenance of the Axis SIRT1-SIRT3 at Youth Level May Contribute to Brain Resilience in Middle-Aged Amateur Rugby Players

2019

Physical exercise performed regularly is known to improve health and to reduce the risk of age-related diseases. Furthermore, there is some evidence of cognitive improvement in physically active middle-aged and older adults. We hypothesized that long-term physically active middle-aged men may have developed brain resilience that can be detected with the analysis of peripheral blood markers. We aimed to analyze the activation of pathways potentially modulated by physical activity in a cohort of healthy amateur rugby players (n = 24) and control subjects with low physical activity (n = 25) aged 45¿65 years. We had previously reported neuropsychological improvement in immediate memory response…