In this article, we propose a framework for comparing three different architectures, in terms of deployment costs and performance metrics, and use the framework comparing the three alternatives for an AI architecture that handles standards-based beyond 5G (B5G) radio access networks. (springeropen.com)
Dynamical3
Therefore, aperiodically intermittent control is adopted to study the synchronization of dynamical networks. (springeropen.com)
The above results mainly concentrated on integer-order dynamical networks. (springeropen.com)
Compared with integer-order dynamical networks, fractional-order dynamical networks can excellently describe the memory and hereditary properties of various models. (springeropen.com)
Prefrontal cortex1
Here, we investigate these using a novel multiarea spiking neural network model of prefrontal cortex (PFC) and two parietotemporal cortical areas based on macaque data. (eneuro.org)
Ubiquitous1
This internal feedback is ubiquitous in neural sensorimotor systems, and we show how internal feedback compensates internal delays. (bvsalud.org)
Alterations3
However, it is unclear whether this onedimensional model is rich enough to capture the multiple neural circuit alterations underlying brain disorders. (biorxiv.org)
Additionally, we reproduced in silico the obtained experimental results with a novel spiking neurons network model of mouse V1, by implementing in the model both the synaptic alterations characterizing the FHM1 genetic mouse model adopted. (biomedcentral.com)
Our network model can help to shed light on the relationship between cellular and network levels of migraine neural alterations. (biomedcentral.com)
Mechanisms6
A neural network architecture models how humans learn and consciously perform musical lyrics and melodies with variable rhythms and beats, using brain design principles and mechanisms that evolved earlier than human musical capabilities, and that have explained and predicted many kinds of psychological and neurobiological data. (frontiersin.org)
The current article complements these contributions by developing a neural model of the brain mechanisms that regulate how humans consciously perceive, learn, and perform music. (frontiersin.org)
Computational models have been used to study the underlying neural mechanisms, but neglected the important role of short-term memory (STM) and long-term memory (LTM) interactions for WM. (eneuro.org)
Nevertheless, since there is limited availability of multiarea mesoscopic recordings of neural activity during WM, the neural mechanisms involved remain elusive. (eneuro.org)
To address this gap and draw attention to the wider cognitive perspective of WM accounting for more than STM correlates in PFC, we present a large-scale multiarea spiking neural network model of WM and focus on investigating the neural mechanisms behind the fundamental STM-LTM interactions critical to WM function. (eneuro.org)
Illustrative paintings or painterly theories by ten artists will be given a unified analysis in the light of neural design principles and mechanisms that have been articulated and computationally characterized by the most advanced neural models of how advanced brains consciously see. (vdocument.in)
Neurons are typically assumed to encode values-such as the orientation of a bar-using their mean firing rate, with individual spikes emitted using a Poisson process ( Dean, 1981 ). (frontiersin.org)
Modeling has predicted that suppressing the activity of inhibitory neurons can lead to increased or, paradoxically, decreased excitatory activity depending on the architecture of the network. (jneurosci.org)
Such neuronal selectivity arises in many brain areas and is shaped by complex, interconnected circuits of excitatory and inhibitory neurons ( Isaacson and Scanziani, 2011 ). (jneurosci.org)
Circuits4
It shows how variations of the same types of neural circuits that can store lyrics or melodies can be used to oscillate with a beat. (frontiersin.org)
These findings suggest that the basic E/I imbalance model should be updated to higher-dimensional models that can better capture the multidimensional computational functions of neural circuits. (biorxiv.org)
The nervous system shows complex organization at many spatial scales: from genes and molecules, to cells and synapses, to neural circuits. (biorxiv.org)
These considerations imply that a more promising level of analysis might be at the level of neural circuits, since the explanatory gap between circuits and behavior is smaller than the gap between molecules and behavior. (biorxiv.org)
Cognitive2
This prominent effect is envisaged to underlie complex cognitive phenomena, which are reported in experiments on humans as well as animals. (eneuro.org)
Learning in neuronal networks has developed in many directions, in particular to reproduce cognitive tasks like image recognition and speech processing. (plos.org)
Demonstrate2
We demonstrate that abnormally strong striatal feedforward inhibition can promote synchronous oscillatory activity that persists in the network over several tens of seconds as observed during seizures. (jneurosci.org)
We demonstrate that recurrent connectivity is able to transform information contained in the temporal structure of the signal into spatial covariances. (plos.org)
Sensory1
This control model can explain anatomical, physiological, and behavioral observations, including motor signals in the visual cortex, heterogeneous kinetics of sensory receptors, and the presence of giant cells in the cortex of humans as well as internal feedback patterns and unexplained heterogeneity in neural systems. (bvsalud.org)
Inhibition3
Theoretical studies have predicted that suppression of inhibition in such excitatory-inhibitory networks can lead to either an increase or, paradoxically, a decrease in excitatory neuronal firing, with consequent effects on stimulus selectivity. (jneurosci.org)
The same manipulations sometimes produced opposite changes in the behavior of different individuals, supporting theoretical predictions for inhibition-stabilized networks. (jneurosci.org)
It demonstrates that abnormally strong striatal feedforward inhibition promotes synchronous oscillatory activity in the BG-thalamo-cortical network and relate this property to the observed strong suppression of the striatal output during seizures. (jneurosci.org)
Cortical5
This correlation between cortical and behavioral change demonstrates that, despite the complex and varied effects that these manipulations can have on neuronal dynamics, the resulting changes in cortical activity account for accompanying changes in behavioral acuity. (jneurosci.org)
The computational model showed how these network effects may arise from a combination of changes in thalamocortical and intra-cortical synaptic transmission, with the former inducing a lower cortical activity and the latter inducing the higher frequencies ɣ oscillations. (biomedcentral.com)
Here we present a large-scale biologically detailed spiking neural network model accounting for three connected cortical areas to study dynamic STM-LTM interactions that reflect the underlying theoretical concept of memory indexing, adapted to support distributed cortical WM. (eneuro.org)
D'Esposito and Postle, 2015 ), there is accumulated evidence for the involvement of other cortical regions, particularly parietotemporal networks associated with long-term memory (LTM) correlates. (eneuro.org)
To this end, we combine analytical calculations with numerical simulations to investigate a computational model of the BG-thalamo-cortical network. (jneurosci.org)
Nodes4
For many networks, especially those coupled with large number of nodes, they cannot synchronize themselves or synchronize with desired goals without external controls. (springeropen.com)
On the other hand, for large-scale networks, it is impractical to add controllers onto all nodes. (springeropen.com)
That is, only a fraction of network nodes is controlled. (springeropen.com)
In such data-driven network automation paradigm, network nodes are able to determine the best policy based on the experience obtained by processing previous data [ 7 ]. (springeropen.com)
Consistently1
Changes in neural population responses consistently predicted behavioral changes for individuals separately, including improvement and impairment in acuity. (jneurosci.org)
Models3
To better understand how network structure shapes intelligent behavior, we developed a learning algorithm that we used to build personalized brain network models for 650 Human Connectome Project participants. (nature.com)
Neural models of how advanced brains see have characterized various of these processes. (vdocument.in)
Classical models of neuronal networks therefore map a set of input signals to a set of activity levels in the output of the network. (plos.org)
Artificial3
However, conventional Artificial Neural Networks (ANNs) and machine learningalgorithms cannot take advantage of this coding strategy, due to their rate-based representation of signals. (frontiersin.org)
Even in the case of artificial Spiking Neural Networks (SNNs), identifying applications where temporal coding outperforms the rate coding strategies of ANNs is still an open challenge. (frontiersin.org)
Network automation requires the development of a network architecture that accommodates multiple solutions based on artificial intelligence (AI) and machine learning (ML). Consequently, integrating AI into the 5th-generation (5G) systems such that we could leverage the advantages of ML techniques to optimize and improve the networks is one challenging topic for B5G networks. (springeropen.com)
Neuronal1
Gilson M, Dahmen D, Moreno-Bote R, Insabato A, Helias M (2020) The covariance perceptron: A new paradigm for classification and processing of time series in recurrent neuronal networks. (plos.org)
Dynamics1
Moreover, we argue why such a scheme of representation is more consistent with known forms of synaptic plasticity than rate-based network dynamics. (plos.org)
Signals1
We find that a fluctuation-based scheme is not only powerful in distinguishing signals into several classes, but also that networks can efficiently be trained in the new paradigm. (plos.org)
Systems1
On their basis, it is possible not only to solve the problems of digital twins, but also to manage groups of robots, robotic systems and complexes. (aurora-journals.com)
Paradigm2
Leveraging recent progress in AI/ML, future radio networks are expected to follow a data-driven paradigm for resource management and for operations, where the level of network automation is increased [ 5 , 6 ]. (springeropen.com)
In this new paradigm both afferent and recurrent weights in a network are tuned to shape the input-output mapping for covariances, the second-order statistics of the fluctuating activity. (plos.org)
Article2
article{straub2023visual, abstract = {In multiphase flows, the evolution of fluid-fluid interfaces is of interest in many applications. (uni-stuttgart.de)
article{bauer2023visual, abstract = {We study the question of how visual analysis can support the comparison of spatio-temporal ensemble data of liquid and gas flow in porous media. (uni-stuttgart.de)
The same network design that controls walking, running, and finger tapping also generates beats and the urge to move with a beat. (frontiersin.org)
The aperiodically intermittent pinning control scheme is adopted to design effective controllers for achieving the synchronization. (springeropen.com)
Naturally, how to design aperiodically intermittent pinning controllers for achieving synchronization of fractional-order networks is an important issue and deserves further investigations. (springeropen.com)
The main contribution of this paper is the design of aperiodically intermittent pinning controllers and the derivation of the sufficient conditions for achieving synchronization of fractional-order network. (springeropen.com)
Levels1
The evolution of mobile communications towards beyond 5th-generation (B5G) networks is envisaged to incorporate high levels of network automation. (springeropen.com)
Architecture5
Based on a review of 5G system architecture, the state-of-the-art candidate AI/ML techniques, and the progress of the state of the art, and the on AI/ML for 5G in standards we define an AI architecture and performance evaluation framework for the deployment of the AI/ML solution in B5G networks. (springeropen.com)
More specifically, the framework identifies the logical AI functions, determines their mapping to the B5G radio access network architecture and analyses the associated deployment cost factors in terms of compute, communicate and store costs. (springeropen.com)
The framework is evaluated based on a use case scenario for heterogeneous networks where it is shown that the deployment cost profiling is different for the different AI architecture alternatives, and that this cost should be considered for the deployment and selection of the AI/ML solution. (springeropen.com)
The natural question that arises is how to integrate AI-based resource management into the architecture of a radio access network, i.e. where should one store the required data and where should the related computations be executed. (springeropen.com)
As an alternative, in a decentralized architecture, where the data and AI tasks are distributed across the network and the mobile devices, the communication overhead and the traffic load can be significantly reduced. (springeropen.com)
Shape1
To form a body of complex shape, parametric solid-state elements can be connected together. (aurora-journals.com)
Highly1
Migraine is a complex disorder highly prevalent worldwide [ 1 ] and associated with a dysfunction in multisensory information processing. (biomedcentral.com)