AI Medical Compendium Journal:
Journal of computational neuroscience

Showing 1 to 10 of 36 articles

Temporal pavlovian conditioning of a model spiking neural network for discrimination sequences of short time intervals.

Journal of computational neuroscience
The brain's ability to learn and distinguish rapid sequences of events is essential for timing-dependent tasks, such as those in sports and music. However, the mechanisms underlying this ability remain an active area of research. Here, we present a P...

Self-supervised learning of scale-invariant neural representations of space and time.

Journal of computational neuroscience
Hippocampal representations of space and time seem to share a common coding scheme characterized by neurons with bell-shaped tuning curves called place and time cells. The properties of the tuning curves are consistent with Weber's law, such that, in...

Neural waves and computation in a neural net model II: Data-like structures and the dynamics of episodic memory.

Journal of computational neuroscience
The computational resources of a neuromorphic network model introduced earlier were investigated in the first paper of this series. It was argued that a form of ubiquitous spontaneous local convolution enabled logical gate-like neural motifs to form ...

Antiferromagnetic artificial neuron modeling of the withdrawal reflex.

Journal of computational neuroscience
Replicating neural responses observed in biological systems using artificial neural networks holds significant promise in the fields of medicine and engineering. In this study, we employ ultra-fast artificial neurons based on antiferromagnetic (AFM) ...

Brain-guided manifold transferring to improve the performance of spiking neural networks in image classification.

Journal of computational neuroscience
Spiking neural networks (SNNs), as the third generation of neural networks, are based on biological models of human brain neurons. In this work, a shallow SNN plays the role of an explicit image decoder in the image classification. An LSTM-based EEG ...

Dynamic branching in a neural network model for probabilistic prediction of sequences.

Journal of computational neuroscience
An important function of the brain is to predict which stimulus is likely to occur based on the perceived cues. The present research studied the branching behavior of a computational network model of populations of excitatory and inhibitory neurons, ...

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...

Reducing variability in motor cortex activity at a resting state by extracellular GABA for reliable perceptual decision-making.

Journal of computational neuroscience
Interaction between sensory and motor cortices is crucial for perceptual decision-making, in which intracortical inhibition might have an important role. We simulated a neural network model consisting of a sensory network (N) and a motor network (N) ...

Modeling grid fields instead of modeling grid cells : An effective model at the macroscopic level and its relationship with the underlying microscopic neural system.

Journal of computational neuroscience
A neuron's firing correlates are defined as the features of the external world to which its activity is correlated. In many parts of the brain, neurons have quite simple such firing correlates. A striking example are grid cells in the rodent medial e...

Spatiotemporal discrimination in attractor networks with short-term synaptic plasticity.

Journal of computational neuroscience
We demonstrate that a randomly connected attractor network with dynamic synapses can discriminate between similar sequences containing multiple stimuli suggesting such networks provide a general basis for neural computations in the brain. The network...