Search results for "neuron"
showing 10 items of 2611 documents
GABAC receptors are functionally expressed in the intermediate zone and regulate radial migration in the embryonic mouse neocortex
2010
Radial neuronal migration in the cerebral cortex depends on trophic factors and the activation of different voltage- and ligand-gated channels. To examine the func- tional role of GABAC receptors in radial migration we ana- lyzed the effects of specific GABAA and GABAC receptor antagonists on the migration of BrdU-labeled neurons in vitro using organotypic neocortical slice cultures. These experi- ments revealed that the GABAA specific inhibitor bicuculline methiodide facilitated neuronal migration, while the GABAC specific inhibitor (1,2,5,6-tetrahydropyridine-4-yl) methylphos- phinic-acid (TPMPA) impeded migration. Co-application of TPMPA and bicuculline methiodide or the unspecific ionot…
Explanation of Qualia and Self-Awareness Using Elastic Membrane Concept
2017
In this work we show that our self-awareness and perception may be successfully explained using two dimensional holistic structures with closed topology embedded into our brains - elastic membranes. These membranes are able to preserve their structure during conscious processes. Their elastic oscillations may be associated with our perceptions, where the frequency of the oscillations is responsible for the perception of different colors, sounds and other stimuli, while the amplitude of the oscillations is responsible for the feeling of a distance. According to the model the squeezed regions of a membrane correspond to the brain zones involved into awareness and attention. The model may be u…
Amyloid Beta-Mediated Changes in Synaptic Function and Spine Number of Neocortical Neurons Depend on NMDA Receptors
2021
Onset and progression of Alzheimer’s disease (AD) pathophysiology differs between brain regions. The neocortex, for example, is a brain region that is affected very early during AD. NMDA receptors (NMDARs) are involved in mediating amyloid beta (Aβ) toxicity. NMDAR expression, on the other hand, can be affected by Aβ. We tested whether the high vulnerability of neocortical neurons for Aβ-toxicity may result from specific NMDAR expression profiles or from a particular regulation of NMDAR expression by Aβ. Electrophysiological analyses suggested that pyramidal cells of 6-months-old wildtype mice express mostly GluN1/GluN2A NMDARs. While synaptic NMDAR-mediated currents are unaltered in 5xFAD …
Prediction of Highly Non-stationary Time Series Using Higher-Order Neural Units
2017
Adaptive predictive models can use conventional and nonconventional neural networks for highly non-stationary time series prediction. However, conventional neural networks present a series of known drawbacks. This paper presents a brief discussion about this concern as well as how the basis of higher-order neural units can overcome some of them; it also describes a sliding window technique alongside the batch optimization technique for capturing the dynamics of non-stationary time series over a Quadratic Neural Unit, a special case of higher-order neural units. Finally, an experimental analysis is presented to demonstrate the effectiveness of the proposed approach.
Effect of foot health and quality of life in patients with Parkinson disease: A prospective case-control investigation.
2022
Financiado para publicación en acceso aberto: Universidade da Coruña/CISUG [Abstract] Background Parkinson's disease (PD) is a common neurodegenerative disorder, characterised by the presence of motor disturbances. Therefore, it can be related to musculoskeletal and orthopaedic problems, particularly in the foot status, that are linked to a negative effect on overall health, mobility and social function. Objective The aim was to analyse the impact of foot health and quality of life in patients with Parkinson's disease and people without Parkinson's disease, with normalised reference scores, in the light of the values recorded with regard to foot health status and overall health. Material an…
Higher-order Organization in the Human Brain from Matrix-Based R\'enyi's Entropy
2023
Pairwise metrics are often employed to estimate statistical dependencies between brain regions, however they do not capture higher-order information interactions. It is critical to explore higher-order interactions that go beyond paired brain areas in order to better understand information processing in the human brain. To address this problem, we applied multivariate mutual information, specifically, Total Correlation and Dual Total Correlation to reveal higher-order information in the brain. In this paper, we estimate these metrics using matrix-based R\'enyi's entropy, which offers a direct and easily interpretable approach that is not limited by direct assumptions about probability distr…
Psychophysics of Artificial Neural Networks Questions Classical Hue Cancellation Experiments
2023
We show that classical hue cancellation experiments lead to human-like opponent curves even if the task is done by trivial (identity) artificial networks. Specifically, human-like opponent spectral sensitivities always emerge in artificial networks as long as (i) the retina converts the input radiation into any tristimulus-like representation, and (ii) the post-retinal network solves the standard hue cancellation task, e.g. the network looks for the weights of the cancelling lights so that every monochromatic stimulus plus the weighted cancelling lights match a grey reference in the (arbitrary) color representation used by the network. In fact, the specific cancellation lights (and not the …
Artificial Neural Networks for Prediction
2005
The design and implementation of intelligent systems with human capabilities is the starting point to design Artificial Neural Networks (ANNs). The original idea takes after neuroscience theory on how neurons in the human brain cooperate to learn from a set of input signals to produce an answer. Because the power of the brain comes from the number of neurons and the multiple connections between them, the basic idea is that connecting a large number of simple elements in a specific way can form an intelligent system.
An Application of Spike-Timing-Dependent Plasticity to Readout Circuit for Liquid State Machine
2007
Liquid state machine (LSM) is a neural system based on spiking neurons that implements a mapping between functions of time. A typical application of LSM is classification of time functions obtained observing the state of the liquid by using a memoryless readout circuit, usually implemented by a linear perceptron. Due to the high number of neurons in the liquid the training of the readout is difficult. In this paper we show that using the Spike-Timing-Dependent Plasticity (STDP) a single neuron with short training session can be used to recognize the state of the liquid due to an input signal. Using STDP it is possible to identify the spikes timing of the neurons in the liquid and this allow…
Experimental study of bifurcations in modified FitzHugh-Nagumo cell
2003
A nonlinear electrical circuit is proposed as a basic cell for modelling the FitzHugh-Nagumo equation with a modified excitability. Depending on initial conditions and parameters, experiments show various dynamics including stability with excitation threshold, bistability and oscillations.