AIMC Topic:
Neurons

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Contrastive Similarity Matching for Supervised Learning.

Neural computation Apr 13, 2021
We propose a novel biologically plausible solution to the credit assignment problem motivated by observations in the ventral visual pathway and trained deep neural networks. In both, representations of objects in the same category become progressivel...
Feedback Supervised Machine Learning Neurons Neural Networks, Computer Algorithms
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The Remarkable Robustness of Surrogate Gradient Learning for Instilling Complex Function in Spiking Neural Networks.

Neural computation Mar 26, 2021
Brains process information in spiking neural networks. Their intricate connections shape the diverse functions these networks perform. Yet how network connectivity relates to function is poorly understood, and the functional capabilities of models of...
Learning Neurons Algorithms Brain Neural Networks, Computer
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Transition to synchronization in heterogeneous inhibitory neural networks with structured synapses.

Chaos (Woodbury, N.Y.) Mar 1, 2021
Inhibitory neurons form an extensive network involved in the development of different rhythms in the cerebral cortex. A transition from an incoherent state, where all inhibitory neurons fire unrelated to each other, to a synchronized or locked state,...
Action Potentials Neurons Nerve Net Synapses Neural Networks, Computer Models, Neurological
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Visualizing a joint future of neuroscience and neuromorphic engineering.

Neuron Feb 17, 2021
Recent research resolves the challenging problem of building biophysically plausible spiking neural models that are also capable of complex information processing. This advance creates new opportunities in neuroscience and neuromorphic engineering, w...
Forecasting Models, Neurological Neurons Humans Neural Networks, Computer Neurosciences Biomedical Engineering
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Unsupervised neural network models of the ventral visual stream.

Proceedings of the National Academy of Sciences of the United States of America Jan 19, 2021
Deep neural networks currently provide the best quantitative models of the response patterns of neurons throughout the primate ventral visual stream. However, such networks have remained implausible as a model of the development of the ventral stream...
Visual Cortex Macaca Nerve Net Pattern Recognition, Visual Animals Child Neurons Datasets as Topic Unsupervised Machine Learning Humans Neural Networks, Computer
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Functional differentiations in evolutionary reservoir computing networks.

Chaos (Woodbury, N.Y.) Jan 1, 2021
We propose an extended reservoir computer that shows the functional differentiation of neurons. The reservoir computer is developed to enable changing of the internal reservoir using evolutionary dynamics, and we call it an evolutionary reservoir com...
Nonlinear Dynamics Humans Computer Simulation Neural Networks, Computer Biological Evolution Neurons
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Stability, bifurcation and phase-locking of time-delayed excitatory-inhibitory neural networks.

Mathematical biosciences and engineering : MBE Nov 10, 2020
We study a model for a network of synaptically coupled, excitable neurons to identify the role of coupling delays in generating different network behaviors. The network consists of two distinct populations, each of which contains one excitatory-inhib...
Neurons Neural Networks, Computer Models, Neurological
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3D computational cannula fluorescence microscopy enabled by artificial neural networks.

Optics express Oct 26, 2020
Computational cannula microscopy (CCM) is a high-resolution widefield fluorescence imaging approach deep inside tissue, which is minimally invasive. Rather than using conventional lenses, a surgical cannula acts as a lightpipe for both excitation and...
Neurons Hippocampus Image Enhancement Microspheres Neuroimaging Cells, Cultured Phantoms, Imaging Equipment Design Cannula Neural Networks, Computer Animals Microscopy, Fluorescence Mice Imaging, Three-Dimensional Catheters, Indwelling
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Computation Through Neural Population Dynamics.

Annual review of neuroscience Jul 8, 2020
Significant experimental, computational, and theoretical work has identified rich structure within the coordinated activity of interconnected neural populations. An emerging challenge now is to uncover the nature of the associated computations, how t...
Population Dynamics Neurons Humans Nerve Net Brain Deep Learning Animals Computational Biology
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Validation of a Convolutional Neural Network Model for Spike Transformation Using a Generalized Linear Model.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2020
Identification of causal relationships of neural activity is one of the most important problems in neuroscience and neural engineering. We show that a novel deep learning approach using a convolutional neural network to model output neural spike acti...
Linear Models Neurons Neural Networks, Computer Action Potentials Probability
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