Search results for "Neural"
showing 10 items of 2783 documents
Reservoir computing model of prefrontal cortex creates novel combinations of previous navigation sequences from hippocampal place-cell replay with sp…
2019
As rats learn to search for multiple sources of food or water in a complex environment, they generate increasingly efficient trajectories between reward sites. Such spatial navigation capacity involves the replay of hippocampal place-cells during awake states, generating small sequences of spatially related place-cell activity that we call “snippets”. These snippets occur primarily during sharp-wave-ripples (SWRs). Here we focus on the role of such replay events, as the animal is learning a traveling salesperson task (TSP) across multiple trials. We hypothesize that snippet replay generates synthetic data that can substantially expand and restructure the experience available and make learni…
Regional models based on Multi-Gene Genetic Programming for the simulation of monthly runoff series
2022
Accurate estimates of runoff in river basins are useful for several applications. The use of data-driven procedures for simulating the complex runoff generation process is a promising frontier that could allow for overcoming some typical problems related to more complex traditional approaches. This study explores soft computing based regional models for the reconstruction of monthly runoff in river basins. The region under analysis is the Sicily (Italy), where a regressive rainfall-runoff model, here used as benchmark model, was previously built using data from almost a hundred gauged watersheds across the region. This previous model predicts monthly river runoff based on a unique regional,…
Performance evaluation of fuzzy-neural HTTP request distribution for Web clusters
2006
In this paper we present the performance evaluation of our fuzzy-neural HTTP request distribution algorithm called FNRD, which assigns each incoming request to the server in the Web cluster with the quickest expected response time. The fuzzy mechanism is used to estimate the expected response times. A neural-based feedback loop is used for real-time tuning of response time estimates. To evaluate the system, we have developed a detailed simulation and workload model using CSIM19 package. Our simulations show that FNRD can be more effective than its competitors.
Neural network prediction of AE data
1997
Neural network (NN) models were constructed to study prediction of the AE index. Both solar wind (vBz) and previous observed AE inputs were used to predict AE data for different numbers of time steps ahead. It seems that prediction of the original unsmoothed AE data is possible only for 10 time steps (25 min) ahead. The predicted time series of the AE data for 50 time steps (125 min) ahead was found to be dynamically different from the original time series. It is possible that the NN model cannot reproduce the turbulent part of the power spectrum of the AE data. However, when using smoothed AE data the prediction for 10 time steps ahead gave an NMSE of 0.0438, and a correlation coefficient …
CEND1 and NEUROGENIN2 Reprogram Mouse Astrocytes and Embryonic Fibroblasts to Induced Neural Precursors and Differentiated Neurons
2015
Summary Recent studies demonstrate that astroglia from non-neurogenic brain regions can be reprogrammed into functional neurons through forced expression of neurogenic factors. Here we explored the effect of CEND1 and NEUROG2 on reprogramming of mouse cortical astrocytes and embryonic fibroblasts. Forced expression of CEND1, NEUROG2, or both resulted in acquisition of induced neuronal cells expressing subtype-specific markers, while long-term live-cell imaging highlighted the existence of two different modes of neuronal trans-differentiation. Of note, a subpopulation of CEND1 and NEUROG2 double-transduced astrocytes formed spheres exhibiting neural stem cell properties. mRNA and protein exp…
Advantages of binaural hearing provided through bimodal stimulation via a cochlear implant and a conventional hearing aid: a 6-month comparative stud…
2005
Our study data demonstrate the additional benefit derived from continued use of a contralateral hearing aid (HA) post-cochlear implantation for speech recognition ability in quiet and in noise. Postoperative bimodal stimulation is recommended for all subjects who show some speech recognition ability in the contralateral ear as it may offer binaural listening advantages in various listening situations encountered in everyday life.To assess the benefits derived from bimodal stimulation for experienced HA users implanted with a cochlear implant (CI) (score=20% in disyllabic test). The correlation between pre- and postoperative performance on speech perception measures was examined to determine…
A spiking network for spatial memory formation: Towards a fly-inspired ellipsoid body model
2013
Neural centers devoted to spatial memory and path integration were largely studied in rats and in different insect species like ants and bees. In this paper a neural-based model for the formation of a spatial working memory is proposed mirroring some peculiarities of the Drosophila central brain and in particular the ellipsoid body. Simulation results are reported opening the way to applications on roving platforms.
Isolation, Long-Term Expansion, and Differentiation of Murine Neural Stem Cells
2014
Stem cells are capable of extensive self-renewal while preserving the ability to generate cell progeny that can differentiate into different cell types. Here, we describe some methods for the isolation of neural stem cells (NSCs) from the adult murine subependymal zone (SEZ), their extensive culturing and the assessment of their full developmental potential, particularly with respect to their differentiation capacity. The procedure includes chemically defined conditions such as absence of serum and addition of specific growth factors, in which differentiated cells die and are rapidly eliminated from the culture. In contrast, undifferentiated precursors become hypertrophic and proliferate, f…
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…
Hardware-accelerated spike train generation for neuromorphic image and video processing
2014
Recent studies concerning Spiking Neural Networks show that they are a powerful tool for multiple applications as pattern recognition, image tracking, and detection tasks. The basic functional properties of SNN reside in the use of spike information encoding as the neurons are specifically designed and trained using spike trains. We present a novel and efficient frequency encoding algorithm with Gabor-like receptive fields using probabilistic methods and targeted to FPGA for online pro-cessing. The proposed encoding is versatile, modular and, when applied to images, it is able to perform simple image transforms as edge detection, spot detection or removal, and Gabor-like filtering without a…