AIMC Topic: Synaptic Transmission

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A deep learning framework for automated and generalized synaptic event analysis.

eLife Mar 5, 2025
Quantitative information about synaptic transmission is key to our understanding of neural function. Spontaneously occurring synaptic events carry fundamental information about synaptic function and plasticity. However, their stochastic nature and lo...
Deep Learning Neurons Synapses Synaptic Transmission Animals
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Tipping prediction of a class of large-scale radial-ring neural networks.

Neural networks : the official journal of the International Neural Network Society Oct 16, 2024
Understanding the emergence and evolution of collective dynamics in large-scale neural networks remains a complex challenge. This paper seeks to address this gap by applying dynamical systems theory, with a particular focus on tipping mechanisms. Fir...
Neural Networks, Computer Algorithms Feedback Synaptic Transmission
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Signatures of Bayesian inference emerge from energy-efficient synapses.

eLife Aug 6, 2024
Biological synaptic transmission is unreliable, and this unreliability likely degrades neural circuit performance. While there are biophysical mechanisms that can increase reliability, for instance by increasing vesicle release probability, these mec...
Synaptic Transmission Neurons Energy Metabolism Synapses Neural Networks, Computer Animals Models, Neurological Bayes Theorem
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A novel machine learning-based approach for the detection and analysis of spontaneous synaptic currents.

PloS one Sep 19, 2022
Spontaneous synaptic activity is a hallmark of biological neural networks. A thorough description of these synaptic signals is essential for understanding neurotransmitter release and the generation of a postsynaptic response. However, the complexity...
Excitatory Postsynaptic Potentials Neurotransmitter Agents Animals Mice Synaptic Transmission Humans Machine Learning Algorithms
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Long-Tailed Characteristic of Spiking Pattern Alternation Induced by Log-Normal Excitatory Synaptic Distribution.

IEEE transactions on neural networks and learning systems Aug 3, 2021
Studies of structural connectivity at the synaptic level show that in synaptic connections of the cerebral cortex, the excitatory postsynaptic potential (EPSP) in most synapses exhibits sub-mV values, while a small number of synapses exhibit large EP...
Neural Networks, Computer Algorithms Models, Neurological Humans Nerve Net Entropy Synaptic Transmission Excitatory Postsynaptic Potentials Nonlinear Dynamics Synapses Cerebral Cortex
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Partial information decomposition reveals that synergistic neural integration is greater downstream of recurrent information flow in organotypic cortical cultures.

PLoS computational biology Jul 12, 2021
The directionality of network information flow dictates how networks process information. A central component of information processing in both biological and artificial neural networks is their ability to perform synergistic integration-a type of co...
Feedback, Physiological Somatosensory Cortex Models, Neurological Action Potentials Neurons Organ Culture Techniques Nerve Net Synaptic Transmission Animals Mice Computational Biology Neural Networks, Computer
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Controllable high-performance memristors based on 2D FeGeTeoxide for biological synapse imitation.

Nanotechnology May 19, 2021
Memristors are an important component of the next-generation artificial neural network, high computing systems, etc. In the past, two-dimensional materials based memristors have achieved a high performance and low power consumption, though one at the...
Electric Conductivity Germanium Iron Copper Biomimetic Materials Humans Electronics Animals Tellurium Synaptic Transmission Neural Networks, Computer Oxidation-Reduction Synapses Oxides
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Modulation of the dynamics of cerebellar Purkinje cells through the interaction of excitatory and inhibitory feedforward pathways.

PLoS computational biology Feb 10, 2021
The dynamics of cerebellar neuronal networks is controlled by the underlying building blocks of neurons and synapses between them. For which, the computation of Purkinje cells (PCs), the only output cells of the cerebellar cortex, is implemented thro...
Neural Pathways Normal Distribution Synaptic Transmission Interneurons Purkinje Cells Excitatory Postsynaptic Potentials Neural Networks, Computer Neurons Cerebellum Neuronal Plasticity Computer Simulation Cerebellar Cortex Synapses Models, Neurological Animals Action Potentials Signal Transduction Humans
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Biological batch normalisation: How intrinsic plasticity improves learning in deep neural networks.

PloS one Sep 23, 2020
In this work, we present a local intrinsic rule that we developed, dubbed IP, inspired by the Infomax rule. Like Infomax, this rule works by controlling the gain and bias of a neuron to regulate its rate of fire. We discuss the biological plausibilit...
Synaptic Transmission Neuronal Plasticity Learning Models, Statistical Models, Neurological Deep Learning Neural Networks, Computer Neurons Action Potentials Models, Theoretical Algorithms Synapses Computer Simulation
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A Mean-Field Description of Bursting Dynamics in Spiking Neural Networks with Short-Term Adaptation.

Neural computation Jul 20, 2020
Bursting plays an important role in neural communication. At the population level, macroscopic bursting has been identified in populations of neurons that do not express intrinsic bursting mechanisms. For the analysis of phase transitions between bur...
Computer Simulation Nerve Net Action Potentials Humans Synaptic Transmission Neurons Neural Networks, Computer
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