Search results for "Potential"

Complex analysis for the solution of torsion problems: a comparison among three methods

2009

Multistate active spaces from local CAS-SCF molecular orbitals: the photodissociation of HFCO as an example.

2005

A recently developed algorithm to generate localized molecular orbitals (LMO) is applied to the study of excited states along a photodissociation process. The LMOs allow for the selection of a consistent complete active space (CAS) for the simultaneous description of all the electronic states involved in a multistate process on the basis of simple chemical criteria. The local nature of the orbitals is used to label them in a unique way that does not depend on the molecular geometry. The selection of the electronic configurations of interest for the set of target states on only the basis of the dominant excitations required by the simplest configuration interaction (CI) descriptions for both…

The tandem Diels-Alder reaction between acetylenedicarboxyaldehyde and N,N'-dipyrrolylmethane. An ab initio study of the molecular mechanisms

1998

Abstract An extensive exploration at RHF/3-21G and RHF/6-31G ∗ levels of the potential energy surface for the tandem cycloaddition of acetylenedicarboxyaldehyde to N,N'-dipyrrolylmethane allows us to characterize the reaction pathways and the associated stationary points. The formation of the pincer and/or domino adducts can be described as a stepwise mechanism. The first step, associated with an intermolecular [4 + 2] cycloaddition, is the rate determining step and an azanorbornadiene intermediate is obtained. The second step is an intramolecular [4 + 2] cycloaddition. The formation of the pincer adduct is the step which kinetically controls the global process, due to the low barrier heigh…

A Fly-Inspired Mushroom Bodies Model for Sensory-Motor Control Through Sequence and Subsequence Learning

2016

Classification and sequence learning are relevant capabilities used by living beings to extract complex information from the environment for behavioral control. The insect world is full of examples where the presentation time of specific stimuli shapes the behavioral response. On the basis of previously developed neural models, inspired by Drosophila melanogaster, a new architecture for classification and sequence learning is here presented under the perspective of the Neural Reuse theory. Classification of relevant input stimuli is performed through resonant neurons, activated by the complex dynamics generated in a lattice of recurrent spiking neurons modeling the insect Mushroom Bodies n…

Sequence Learning in a Single Trial: A Spiking Neurons Model Based on Hippocampal Circuitry.

2020

ABSTRACTIn contrast with our everyday experience using brain circuits, it can take a prohibitively long time to train a computational system to produce the correct sequence of outputs in the presence of a series of inputs. This suggests that something important is missing in the way in which models are trying to reproduce basic cognitive functions. In this work, we introduce a new neuronal network architecture that is able to learn, in a single trial, an arbitrary long sequence of any known objects. The key point of the model is the explicit use of mechanisms and circuitry observed in the hippocampus, which allow the model to reach a level of efficiency and accuracy that, to the best of our…

Topology of synaptic connectivity constrains neuronal stimulus representation, predicting two complementary coding strategies

2022

In motor-related brain regions, movement intention has been successfully decoded from in-vivo spike train by isolating a lower-dimension manifold that the high-dimensional spiking activity is constrained to. The mechanism enforcing this constraint remains unclear, although it has been hypothesized to be implemented by the connectivity of the sampled neurons. We test this idea and explore the interactions between local synaptic connectivity and its ability to encode information in a lower dimensional manifold through simulations of a detailed microcircuit model with realistic sources of noise. We confirm that even in isolation such a model can encode the identity of different stimuli in a lo…

Acceptability Study of A3-K3 Robotic Architecture for a Neurorobotics Painting

2019

In this paper, authors present a novel architecture for controlling an industrial robot via Brain Computer Interface. The robot used is a Series 2000 KR 210-2. The robotic arm was fitted with DI drawing devices that clamp, hold and manipulate various artistic media like brushes, pencils, pens. User selected a high-level task, for instance a shape or movement, using a human machine interface and the translation in robot movement was entirely demanded to the Robot Control Architecture defining a plan to accomplish user's task. The architecture was composed by a Human Machine Interface based on P300 Brain Computer Interface and a robotic architecture composed by a deliberative layer and a reac…

UnipaBCI a novel general software framework for brain computer interface

2017

The increasing interest in Brain Computer Interface (BCI) requires new fast, reliable and scalable frameworks that can be used by researchers to develop BCI based high performance applications in efficient and fast ways. In this paper is presented "UnipaBCI", a general software framework for BCI applications based on electroencephalogra-phy (EEG) that can fulfill these new needs. A visual evoked potentials (VEP) application has also been developed using the proposed framework in order to test the modular architecture and the overall performance. Different types of users (beginners and experts in BCI) have been involved during the "UnipaBCI" experimental test and they have exhibited good and…

Efficient FPGA Implementation of an Adaptive Noise Canceller

2006

A hardware implementation of an adaptive noise canceller (ANC) is presented. It has been synthesized within an FPGA, using a modified version of the least mean square (LMS) error algorithm. The results obtained so far show a significant decrease of the required gate count when compared with a standard LMS implementation, while increasing the ANC bandwidth and signal to noise (S/N) ratio. This novel adaptive noise canceller is then useful for enhancing the S/N ratio of data collected from sensors (or sensor arrays) working in noisy environment, or dealing with potentially weak signals.

A Meshfree Solver for the MEG Forward Problem

2015

Noninvasive estimation of brain activity via magnetoencephalography (MEG) involves an inverse problem whose solution requires an accurate and fast forward solver. To this end, we propose the Method of Fundamental Solutions (MFS) as a meshfree alternative to the Boundary Element Method (BEM). The solution of the MEG forward problem is obtained, via the Method of Particular Solutions (MPS), by numerically solving a boundary value problem for the electric scalar potential, derived from the quasi-stationary approximation of Maxwell’s equations. The magnetic field is then computed by the Biot-Savart law. Numerical experiments have been carried out in a realistic single-shell head geometry. The p…