AIMC Topic: Models, Neurological

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Approximating Nonlinear Functions With Latent Boundaries in Low-Rank Excitatory-Inhibitory Spiking Networks.

Neural computation Apr 23, 2024
Deep feedforward and recurrent neural networks have become successful functional models of the brain, but they neglect obvious biological details such as spikes and Dale's law. Here we argue that these details are crucial in order to understand how r...
Computer Simulation Animals Models, Neurological Humans Neural Networks, Computer Nerve Net Neural Inhibition Nonlinear Dynamics Synapses Action Potentials Neurons
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Heterogeneous Forgetting Rates and Greedy Allocation in Slot-Based Memory Networks Promotes Signal Retention.

Neural computation Apr 23, 2024
A key question in the neuroscience of memory encoding pertains to the mechanisms by which afferent stimuli are allocated within memory networks. This issue is especially pronounced in the domain of working memory, where capacity is finite. Presumably...
Models, Neurological Neural Networks, Computer Memory, Short-Term Brain Humans Memory
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Meta predictive learning model of languages in neural circuits.

Physical review. E Apr 1, 2024
Large language models based on self-attention mechanisms have achieved astonishing performances, not only in natural language itself, but also in a variety of tasks of different nature. However, regarding processing language, our human brain may not ...
Learning Models, Neurological Machine Learning Language Humans Neural Networks, Computer
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A robust balancing mechanism for spiking neural networks.

Chaos (Woodbury, N.Y.) Apr 1, 2024
Dynamical balance of excitation and inhibition is usually invoked to explain the irregular low firing activity observed in the cortex. We propose a robust nonlinear balancing mechanism for a random network of spiking neurons, which works also in the ...
Neural Networks, Computer Action Potentials Neurons Synapses Neuronal Plasticity Models, Neurological
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Applications of information geometry to spiking neural network activity.

Physical review. E Feb 1, 2024
The space of possible behaviors that complex biological systems may exhibit is unimaginably vast, and these systems often appear to be stochastic, whether due to variable noisy environmental inputs or intrinsically generated chaos. The brain is a pro...
Brain Neural Networks, Computer Models, Neurological Neural Inhibition Models, Statistical
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This AI learnt language by seeing the world through a baby's eyes.

Nature Feb 1, 2024
Photic Stimulation Eye Language Development Infant Models, Neurological Neural Networks, Computer Learning Humans
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Modelling and Controlling System Dynamics of the Brain: An Intersection of Machine Learning and Control Theory.

Advances in neurobiology Jan 1, 2024
The human brain, as a complex system, has long captivated multidisciplinary researchers aiming to decode its intricate structure and function. This intricate network has driven scientific pursuits to advance our understanding of cognition, behavior, ...
Models, Neurological Humans Brain Cognition Machine Learning
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A Computational Framework for Memory Engrams.

Advances in neurobiology Jan 1, 2024
Memory engrams in mice brains are potentially related to groups of concept cells in human brains. A single concept cell in human hippocampus responds, for example, not only to different images of the same object or person but also to its name written...
Humans Memory Mental Recall Neurons Animals Hippocampus Mice Models, Neurological Neural Networks, Computer Brain
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Neural Sequences and the Encoding of Time.

Advances in experimental medicine and biology Jan 1, 2024
Converging experimental and computational evidence indicate that on the scale of seconds the brain encodes time through changing patterns of neural activity. Experimentally, two general forms of neural dynamic regimes that can encode time have been o...
Humans Neural Networks, Computer Animals Time Factors Brain Models, Neurological Time Perception Neurons
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Noisy image segmentation based on synchronous dynamics of coupled photonic spiking neurons.

Optics express Oct 23, 2023
The collective dynamics in neural networks is essential for information processing and has attracted much interest on the application in artificial intelligence. Synchronization is one of the most dominant phenomenon in the collective dynamics of neu...
Neurons Models, Neurological Neural Networks, Computer Photons Optics and Photonics Action Potentials Artificial Intelligence
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