AIMC Topic: Sensory Receptor Cells

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Spike Encoding with Optic Sensory Neurons Enable a Pulse Coupled Neural Network for Ultraviolet Image Segmentation.

Nano letters Oct 16, 2020
Drawing inspiration from biology, neuromorphic systems are of great interest in direct interaction and efficient processing of analogue signals in the real world and could be promising for the development of smart sensors. Here, we demonstrate an art...
Neural Networks, Computer Vision, Ocular Sensory Receptor Cells
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Separability and geometry of object manifolds in deep neural networks.

Nature communications Feb 6, 2020
Stimuli are represented in the brain by the collective population responses of sensory neurons, and an object presented under varying conditions gives rise to a collection of neural population responses called an 'object manifold'. Changes in the obj...
Brain Deep Learning Models, Neurological Humans Neural Networks, Computer Algorithms Photic Stimulation Sensory Receptor Cells Visual Perception Pattern Recognition, Visual
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Reaction-diffusion memory unit: Modeling of sensitization, habituation and dishabituation in the brain.

PloS one Dec 5, 2019
We propose a novel approach to investigate the effects of sensitization, habituation and dishabituation in the brain using the analysis of the reaction-diffusion memory unit (RDMU). This unit consists of Morris-Lecar-type sensory, motor, interneuron ...
Memory Interneurons Sensory Receptor Cells Motor Neurons Habituation, Psychophysiologic Animals Neurons Synapses Neural Networks, Computer Brain Learning
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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 Jul 8, 2019
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...
Orientation, Spatial Animals Neural Networks, Computer Entorhinal Cortex Models, Neurological Computer Simulation Sensory Receptor Cells Action Potentials
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Discrimination of bursts and tonic activity in multifunctional sensorimotor neural network using the extended hill-valley method.

Journal of neurophysiology Jun 19, 2019
Individual neurons can exhibit a wide range of activity, including spontaneous spiking, tonic spiking, bursting, or spike-frequency adaptation, and can also transition between these activity types. Manual identification of these activity patterns can...
Algorithms Animals Action Potentials Models, Biological Neural Networks, Computer Astacoidea Nerve Net Sensory Receptor Cells Motor Neurons
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Characterisation of nonlinear receptive fields of visual neurons by convolutional neural network.

Scientific reports Mar 7, 2019
A comprehensive understanding of the stimulus-response properties of individual neurons is necessary to crack the neural code of sensory cortices. However, a barrier to achieving this goal is the difficulty of analysing the nonlinearity of neuronal r...
Mice, Inbred C57BL Nonlinear Dynamics Photic Stimulation Animals Male Models, Neurological Visual Cortex Sensory Receptor Cells Neural Networks, Computer
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Emergence of spontaneous assembly activity in developing neural networks without afferent input.

PLoS computational biology Sep 28, 2018
Spontaneous activity is a fundamental characteristic of the developing nervous system. Intriguingly, it often takes the form of multiple structured assemblies of neurons. Such assemblies can form even in the absence of afferent input, for instance in...
Neural Networks, Computer Software Retina Neuronal Plasticity Zebrafish Female Sensory Receptor Cells Models, Neurological Calcium Stochastic Processes Animals Superior Colliculi Models, Statistical Neurogenesis Male
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Sensory cortex is optimized for prediction of future input.

eLife Jun 18, 2018
Neurons in sensory cortex are tuned to diverse features in natural scenes. But what determines which features neurons become selective to? Here we explore the idea that neuronal selectivity is optimized to represent features in the recent sensory pas...
Sensory Receptor Cells Anticipation, Psychological Neural Networks, Computer Acoustic Stimulation Reaction Time Computer Simulation Photic Stimulation Auditory Cortex Mammals Animals Visual Cortex Video Recording
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Fitting of dynamic recurrent neural network models to sensory stimulus-response data.

Journal of biological physics Jun 2, 2018
We present a theoretical study aiming at model fitting for sensory neurons. Conventional neural network training approaches are not applicable to this problem due to lack of continuous data. Although the stimulus can be considered as a smooth time-de...
Reaction Time Electric Stimulation Photic Stimulation Sensory Receptor Cells Animals Neural Networks, Computer Models, Neurological Action Potentials
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Demixed principal component analysis of neural population data.

eLife Apr 12, 2016
Neurons in higher cortical areas, such as the prefrontal cortex, are often tuned to a variety of sensory and motor variables, and are therefore said to display mixed selectivity. This complexity of single neuron responses can obscure what information...
Spatial Navigation Reward Sensory Receptor Cells Datasets as Topic Decision Making Olfactory Perception Animals Motor Neurons Task Performance and Analysis Principal Component Analysis Multifactor Dimensionality Reduction Prefrontal Cortex Memory, Short-Term Macaca mulatta Rats
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