AIMC Topic: Neurons

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Multimodal neural networks better explain multivoxel patterns in the hippocampus.

Neural networks : the official journal of the International Neural Network Society
The human hippocampus possesses "concept cells", neurons that fire when presented with stimuli belonging to a specific concept, regardless of the modality. Recently, similar concept cells were discovered in a multimodal network called CLIP (Radford e...

Spiking Neural Network Regularization With Fixed and Adaptive Drop-Keep Probabilities.

IEEE transactions on neural networks and learning systems
Dropout and DropConnect are two techniques to facilitate the regularization of neural network models, having achieved the state-of-the-art results in several benchmarks. In this paper, to improve the generalization capability of spiking neural networ...

Toward the Optimal Design and FPGA Implementation of Spiking Neural Networks.

IEEE transactions on neural networks and learning systems
The performance of a biologically plausible spiking neural network (SNN) largely depends on the model parameters and neural dynamics. This article proposes a parameter optimization scheme for improving the performance of a biologically plausible SNN ...

A framework for macroscopic phase-resetting curves for generalised spiking neural networks.

PLoS computational biology
Brain rhythms emerge from synchronization among interconnected spiking neurons. Key properties of such rhythms can be gleaned from the phase-resetting curve (PRC). Inferring the PRC and developing a systematic phase reduction theory for large-scale b...

Fixed-time projective synchronization of delayed memristive neural networks via aperiodically semi-intermittent switching control.

ISA transactions
This paper studies the fixed-time projective synchronization problem for a class of delayed memristive neural networks via aperiodically semi-intermittent switching control. Instead of using the common traditional controller containing two power expo...

Multiscale segmentation- and error-guided iterative convolutional neural network for cerebral neuron segmentation in microscopic images.

Microscopy research and technique
This article uses microscopy images obtained from diverse anatomical regions of macaque brain for neuron semantic segmentation. The complex structure of brain, the large intra-class staining intensity difference within neuron class, the small inter-c...

On the Tuning of the Computation Capability of Spiking Neural Membrane Systems with Communication on Request.

International journal of neural systems
Spiking neural P systems (abbreviated as SNP systems) are models of computation that mimic the behavior of biological neurons. The spiking neural P systems with communication on request (abbreviated as SNQP systems) are a recently developed class of ...

A disector-based framework for the automatic optical fractionator.

Journal of chemical neuroanatomy
Stereology-based methods provide the current state-of-the-art approaches for accurate quantification of numbers and other morphometric parameters of biological objects in stained tissue sections. The advent of artificial intelligence (AI)-based deep ...

Exact mean-field models for spiking neural networks with adaptation.

Journal of computational neuroscience
Networks of spiking neurons with adaption have been shown to be able to reproduce a wide range of neural activities, including the emergent population bursting and spike synchrony that underpin brain disorders and normal function. Exact mean-field mo...

On Spiking Neural Membrane Systems with Neuron and Synapse Creation.

International journal of neural systems
Spiking neural membrane systems are models of computation inspired by the natural functioning of the brain using the concepts of neurons and synapses, and represent a way of building computational systems of a biological inspiration. A variant of suc...