AIMC Topic: Neurons

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Representations of regular and irregular shapes by deep Convolutional Neural Networks, monkey inferotemporal neurons and human judgments.

PLoS computational biology
Recent studies suggest that deep Convolutional Neural Network (CNN) models show higher representational similarity, compared to any other existing object recognition models, with macaque inferior temporal (IT) cortical responses, human ventral stream...

Rhythmic modulation of thalamic oscillations depends on intrinsic cellular dynamics.

Journal of neural engineering
OBJECTIVE: Rhythmic brain stimulation has emerged as a powerful tool to modulate cognition and to target pathological oscillations related to neurological and psychiatric disorders. However, we lack a systematic understanding of how periodic stimulat...

Evaluating performance of neural codes in model neural communication networks.

Neural networks : the official journal of the International Neural Network Society
Information needs to be appropriately encoded to be reliably transmitted over physical media. Similarly, neurons have their own codes to convey information in the brain. Even though it is well-known that neurons exchange information using a pool of s...

Roles for globus pallidus externa revealed in a computational model of action selection in the basal ganglia.

Neural networks : the official journal of the International Neural Network Society
The basal ganglia are considered vital to action selection - a hypothesis supported by several biologically plausible computational models. Of the several subnuclei of the basal ganglia, the globus pallidus externa (GPe) has been thought of largely a...

Unsupervised and real-time spike sorting chip for neural signal processing in hippocampal prosthesis.

Journal of neuroscience methods
BACKGROUND: Damage to the hippocampus will result in the loss of ability to form new long-term memories and cognitive disorders. At present, there is no effective medical treatment for this issue. Hippocampal cognitive prosthesis is proposed to repla...

A Parallel Workflow Pattern Modeling Using Spiking Neural P Systems With Colored Spikes.

IEEE transactions on nanobioscience
Spiking neural P systems, otherwise known as named SN P systems, are bio-inspired parallel and distributed neural-like computing models. Due to the spiking behavior, SN P systems fall into the category of spiking neural networks, and are considered t...

Neural Classifiers with Limited Connectivity and Recurrent Readouts.

The Journal of neuroscience : the official journal of the Society for Neuroscience
For many neural network models in which neurons are trained to classify inputs like perceptrons, the number of inputs that can be classified is limited by the connectivity of each neuron, even when the total number of neurons is very large. This pose...

Multiple Mittag-Leffler stability of fractional-order competitive neural networks with Gaussian activation functions.

Neural networks : the official journal of the International Neural Network Society
In this paper, we explore the coexistence and dynamical behaviors of multiple equilibrium points for fractional-order competitive neural networks with Gaussian activation functions. By virtue of the geometrical properties of activation functions, the...

Learning of spatiotemporal patterns in a spiking neural network with resistive switching synapses.

Science advances
The human brain is a complex integrated spatiotemporal system, where space (which neuron fires) and time (when a neuron fires) both carry information to be processed by cognitive functions. To parallel the energy efficiency and computing functionalit...

Digital Multiplierless Realization of Coupled Wilson Neuron Model.

IEEE transactions on biomedical circuits and systems
The human brain is composed of 10 neurons with a switching speed of about 1 ms. Studying spiking neural networks, including the modeling, simulation, and implementation of the biological neuron models, helps us to learn about the brain and the relate...