Computational model of amygdala network supported by neurobiological data
نویسندگان
چکیده
The amygdala has repeatedly been involved in the processing of emotional reactions and conditioning. This paper presents a neurobiologically inspired computational model of the emotional memory in aversive behaviors. This artificial neural network aims at partially reproduce the same characteristics as the amygdala when it induces the aversive state experienced by individuals with a withdrawal effect.
منابع مشابه
Computational model for amygdala neural networks
We present a computational model of amygdala neural networks. It is used to simulate neuronal activation in amygdala nuclei at different stages of aversive conditioning experiments with rats. Our model is based on neurobiological data. Simple formal neurons and an adaptive Hebbian rule are the key elements of the model. The results are compatible with neuronal activation maps obtained with C-Fo...
متن کاملFlow Variables Prediction Using Experimental, Computational Fluid Dynamic and Artificial Neural Network Models in a Sharp Bend
Bend existence induces changes in the flow pattern, velocity profiles and water surface. In the present study, based on experimental data, first three-dimensional computational fluid dynamic (CFD) model is simulated by using Fluent two-phase (water + air) as the free surface and the volume of fluid method, to predict the two significant variables (velocity and channel bed pressure) in 90º sharp...
متن کاملLarge amplitude vibration prediction of rectangular plates by an optimal artificial neural network (ANN)
In this paper, nonlinear equations of motion for laminated composite rectangular plates based on the first order shear deformation theory were derived. Using a perturbation method, the nonlinear equation of motion was solved and analytical relations were obtained for natural and nonlinear frequencies. After proving the validity of the obtained analytical relations, as an alternative and simple ...
متن کاملComputational modeling of dynamic decision making using connectionist networks
In this research connectionist modeling of decision making has been presented. Important areas for decision making in the brain are thalamus, prefrontal cortex and Amygdala. Connectionist modeling with 3 parts representative for these 3 areas is made based the result of Iowa Gambling Task. In many researches Iowa Gambling Task is used to study emotional decision making. In these kind of decisio...
متن کاملIdentification of rotor bearing parameters using vibration response data in a turbocharger rotor
Turbochargers are most widely used in automotive, marine and locomotive applications with diesel engines. To increase the engine performance nowadays, in aerospace applications also turbochargers are used. Mostly the turbocharger rotors are commonly supported over the fluid film bearings. With the operation, lubricant properties continuously alter leading to different load bearing capacities. T...
متن کامل