AIMC Topic: Models, Neurological

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Integrated 3D Modeling and Functional Simulation of the Human Amygdala: A Novel Anatomical and Computational Analyses.

Neuroinformatics Aug 7, 2025
The amygdala plays a central role in emotion, memory, and decision-making and comprises approximately 13 distinct nuclei with connectivity. Despite its functional importance, high-resolution subnuclear mapping is challenging. This study aimed to cons...
Female Adult Male Humans Computer Simulation Magnetic Resonance Imaging Models, Neurological Amygdala Deep Learning Imaging, Three-Dimensional
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Rapid, interpretable data-driven models of neural dynamics using recurrent mechanistic models.

Proceedings of the National Academy of Sciences of the United States of America Aug 4, 2025
Obtaining predictive models of a neural system is notoriously challenging. Detailed models suffer from excess model complexity and are difficult to fit efficiently. Simplified models must negotiate a tradeoff between tractability, predictive power, a...
Neural Networks, Computer Models, Neurological Animals Neurons
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A multisynaptic spiking neuron for simultaneously encoding spatiotemporal dynamics.

Nature communications Aug 4, 2025
Spiking neural networks (SNNs) are biologically more plausible and computationally more powerful than artificial neural networks due to their intrinsic temporal dynamics. However, vanilla spiking neurons struggle to simultaneously encode spatiotempor...
Neural Networks, Computer Algorithms Animals Humans Synapses Action Potentials Neurons Axons Spatio-Temporal Analysis Models, Neurological
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Contrastive learning-driven framework for neuron morphology classification.

Scientific reports Jul 30, 2025
The Neuron morphology classification is a critical task in neuroscience research, as the morphological features of neurons are closely linked to the functional characteristics of neural circuits. However, traditional classification methods often stru...
Algorithms Models, Neurological Neurons Humans Neural Networks, Computer Machine Learning
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Spiking dynamics of individual neurons reflect changes in the structure and function of neuronal networks.

Nature communications Jul 30, 2025
Brain networks exhibit diverse topological structures to adapt and support brain functions. The changes in neuronal network architecture can lead to alterations in neuronal spiking activity, yet how individual neuronal behavior reflects network struc...
Action Potentials Neurons Nerve Net Animals Models, Neurological Fractals Humans Brain
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Learning place cells and remapping by decoding the cognitive map.

eLife Jul 28, 2025
Hippocampal place cells are known for their spatially selective firing and are believed to encode an animal's location while forming part of a cognitive map of space. These cells exhibit marked tuning curves and rate changes when an animal's environm...
Models, Neurological Place Cells Neural Networks, Computer Animals Cognition Learning
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Reinforced Odor Representations in the Anterior Olfactory Nucleus Can Serve as Memory Traces for Conspecifics.

eNeuro Jul 28, 2025
Recognition of conspecific individuals in mammals is an important skill, thought to be mediated by a distributed array of neural networks, including those processing olfactory cues. Recent data from our groups have shown that social memory can be sup...
Odorants Olfactory Pathways Computer Simulation Smell Models, Neurological Memory Animals Recognition, Psychology Olfactory Perception Oxytocin Reinforcement, Psychology
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Wave Propagation Phenomena in Nonlinear Hierarchical Neural Networks with Predictive Coding Feedback Dynamics.

Bulletin of mathematical biology Jul 24, 2025
We propose a mathematical framework to systematically explore the propagation properties of a class of continuous in time nonlinear neural network models comprising a hierarchy of processing areas, mutually connected according to the principles of pr...
Humans Neural Networks, Computer Mathematical Concepts Models, Neurological Nonlinear Dynamics Computer Simulation Nerve Net Feedback
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Taming the chaos gently: a predictive alignment learning rule in recurrent neural networks.

Nature communications Jul 23, 2025
Recurrent neural circuits often face inherent complexities in learning and generating their desired outputs, especially when they initially exhibit chaotic spontaneous activity. While the celebrated FORCE learning rule can train chaotic recurrent net...
Synapses Nerve Net Recurrent Neural Networks Humans Neuronal Plasticity Neural Networks, Computer Learning Models, Neurological Nonlinear Dynamics
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Biologically-informed excitatory and inhibitory ratio for robust spiking neural network training.

Scientific reports Jul 10, 2025
Spiking neural networks drawing inspiration from biological constraints of the brain promise an energy-efficient paradigm for artificial intelligence. However, challenges exist in identifying guiding principles to train these networks in a robust fas...
Action Potentials Animals Neurons Humans Models, Neurological Nerve Net Neural Networks, Computer
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