Search results for "COMPUTATIONAL MODEL"

3D objects descriptors methods: Overview and trends

2017

International audience; Object recognition or object's category recognition under varying conditions is one of the most astonishing capabilities of human visual system. The scientists in computer vision have been trying for decades to reproduce this ability by implementing algorithms and providing computers with appropriate tools. Hence, several intelligent systems have been proposed. To act in this field, numerous approaches have been proposed. In this paper we present an overview of the current trend in 3D objects recognition and describe some representative state of the art methods, highlighting their limits and complexity.

Interaction in Spoken Word Recognition Models: Feedback Helps

2018

Human perception, cognition, and action requires fast integration of bottom-up signals with top-down knowledge and context. A key theoretical perspective in cognitive science is the interactive activation hypothesis: forward and backward flow in bidirectionally connected neural networks allows humans and other biological systems to approximate optimal integration of bottom-up and top-down information under real-world constraints. An alternative view is that online feedback is neither necessary nor helpful; purely feed forward alternatives can be constructed for any feedback system, and online feedback could not improve processing and would preclude veridical perception. In the domain of spo…

A Neurocomputational Approach to Trained and Transitive Relations in Equivalence Classes

2017

A stimulus class can be composed of perceptually different but functionally equivalent stimuli. The relations between the stimuli that are grouped in a class can be learned or derived from other stimulus relations. If stimulus A is equivalent to B, and B is equivalent to C, then the equivalence between A and C can be derived without explicit training. In this work we propose, with a neurocomputational model, a basic learning mechanism for the formation of equivalence. We also describe how the relatedness between the members of an equivalence class is developed for both trained and derived stimulus relations. Three classic studies on stimulus equivalence are simulated covering typical and at…

Physics of the nuclear pore complex: Theory, modeling and experiment

2021

Abstract The hallmark of eukaryotic cells is the nucleus that contains the genome, enclosed by a physical barrier known as the nuclear envelope (NE). On the one hand, this compartmentalization endows the eukaryotic cells with high regulatory complexity and flexibility. On the other hand, it poses a tremendous logistic and energetic problem of transporting millions of molecules per second across the nuclear envelope, to facilitate their biological function in all compartments of the cell. Therefore, eukaryotes have evolved a molecular “nanomachine” known as the Nuclear Pore Complex (NPC). Embedded in the nuclear envelope, NPCs control and regulate all the bi-directional transport between the…

A computational model for motor learning in insects

2013

The aim of this paper is to propose a computational model, inspired by Drosophila melanogaster, able to handle problems related to motor learning. The role of the Mushroom Bodies and the Central Complex in solving this problem is analyzed and plausible biologically inspired models are proposed. The designed computational models have been evaluated in simulation using a dynamic structure inspired by the fruit fly. The obtained results open the way to new neurobiological experiments focused to better understand the underlined mechanisms involved, to verify the feasibility of the hypotheses formulated and the significance of the obtained results.

Inter-Model Consistency and Complementarity: Learning from ex-vivo Imaging and Electrophysiological Data towards an Integrated Understanding of Cardi…

2011

International audience; Computational models of the heart at various scales and levels of complexity have been independently developed, parameterised and validated using a wide range of experimental data for over four decades. However, despite remarkable progress, the lack of coordinated efforts to compare and combine these computational models has limited their impact on the numerous open questions in cardiac physiology. To address this issue, a comprehensive dataset has previously been made available to the community that contains the cardiac anatomy and fibre orientations from magnetic resonance imaging as well as epicardial transmembrane potentials from optical mapping measured on a per…

Neighborhood Effects in Visual Word Recognition and Reading

2015

Complex adaptative systems and computational simulation in Archaeology

2017

Traditionally the concept of ‘complexity’ is used as a synonym for ‘complex society’, i.e., human groups with characteristics such as urbanism, inequalities, and hierarchy. The introduction of Nonlinear Systems and Complex Adaptive Systems to the discipline of archaeology has nuanced this concept. This theoretical turn has led to the rise of modelling as a method of analysis of historical processes. This work has a twofold objective: to present the theoretical current characterized by generative thinking in archaeology and to present a concrete application of agent-based modelling to an archaeological problem: the dispersal of the first ceramic production in the western Mediterranean.

CHANGING PERSPECTIVE ON PERCEPTION PHYSIOLOGY: CAN YOU REALLY SEE WHAT IS HAPPENING?

2018

Perception is a complex, neural mechanism that requires organization and interpretation of input meaning and it has been a key topic in medicine, neuroscience and philosophy for centuries. Gestalt psychology proposed that the underlying mechanism is a constructive process that depends on both input of stimuli and the sensory-motor state of the agent. The Bayesian Brain hypothesis reframed it as probabilistic inference of previous beliefs, which are revised to accommodate new information. The Predictive Coding Theory proposes that this process is implemented through a top-down cascade of cortical predictions of lower level input and the concurrent propagation of a bottom-up prediction error …

Multi-objective optimization for computation offloading in mobile-edge computing

2017

Mobile-edge cloud computing is a new cloud platform to provide pervasive and agile computation augmenting services for mobile devices (MDs) at anytime and anywhere by endowing ubiquitous radio access networks with computing capabilities. Although offloading computations to the cloud can reduce energy consumption at the MDs, it may also incur a larger execution delay. Usually the MDs have to pay cloud resource they used. In this paper, we utilize queuing theory to bring a thorough study on the energy consumption, execution delay and price cost of offloading process in a mobile-edge cloud system. Specifically, both wireless transmission and computing capabilities are explicitly and jointly co…