AIMC Topic: Models, Neurological

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Spread of α-synuclein pathology through the brain connectome is modulated by selective vulnerability and predicted by network analysis.

Nature neuroscience Jul 25, 2019
Studies of patients afflicted by neurodegenerative diseases suggest that misfolded proteins spread through the brain along anatomically connected networks, prompting progressive decline. Recently, mouse models have recapitulated the cell-to-cell tran...
Leucine-Rich Repeat Serine-Threonine Protein Kinase-2 Neural Networks, Computer Cell Death Brain Linear Models alpha-Synuclein Female Connectome Neurons Models, Neurological Animals Mice, Inbred C57BL Male Brain Mapping Mice
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A New Nonlinear Sparse Component Analysis for a Biologically Plausible Model of Neurons.

Neural computation Jul 23, 2019
It is known that brain can create a sparse representation of the environment in both sensory and mnemonic forms (Olshausen & Field, 2004). Such sparse representation can be combined in downstream areas to create rich multisensory responses to support...
Humans Neural Networks, Computer Brain Models, Neurological Action Potentials Nonlinear Dynamics Principal Component Analysis Neurons
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Learning with Precise Spike Times: A New Decoding Algorithm for Liquid State Machines.

Neural computation Jul 23, 2019
There is extensive evidence that biological neural networks encode information in the precise timing of the spikes generated and transmitted by neurons, which offers several advantages over rate-based codes. Here we adopt a vector space formulation o...
Machine Learning Humans Algorithms Neural Networks, Computer Models, Neurological Action Potentials Speech Recognition Software
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Bifurcation structure determines different phase-amplitude coupling patterns in the activity of biologically plausible neural networks.

NeuroImage Jul 19, 2019
Phase-amplitude cross frequency coupling (PAC) is a rather ubiquitous phenomenon that has been observed in a variety of physical domains; however, the mechanisms underlying the emergence of PAC and its functional significance in the context of neural...
Parkinson Disease Brain Waves Neural Networks, Computer Models, Neurological Humans
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Efficient Epileptic Seizure Prediction Based on Deep Learning.

IEEE transactions on biomedical circuits and systems Jul 17, 2019
Epilepsy is one of the world's most common neurological diseases. Early prediction of the incoming seizures has a great influence on epileptic patients' life. In this paper, a novel patient-specific seizure prediction technique based on deep learning...
Humans Child Models, Neurological Electroencephalography Deep Learning Seizures Adolescent Signal Processing, Computer-Assisted Child, Preschool Female Male
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A theory of consciousness: computation, algorithm, and neurobiological realization.

Biological cybernetics Jul 9, 2019
The most enigmatic aspect of consciousness is the fact that it is felt, as a subjective sensation. The theory proposed here aims to explain this particular aspect. The theory encompasses both the computation that is presumably involved and the way in...
Humans Models, Neurological Consciousness Neural Networks, Computer Algorithms Brain
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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...
Neural Networks, Computer Entorhinal Cortex Models, Neurological Sensory Receptor Cells Computer Simulation Action Potentials Animals Orientation, Spatial
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Characterization of the non-stationary nature of steady-state visual evoked potentials using echo state networks.

PloS one Jul 5, 2019
State Visual Evoked Potentials (SSVEPs) arise from a resonance phenomenon in the visual cortex that is produced by a repetitive visual stimulus. SSVEPs have long been considered a steady-state response resulting from purely oscillatory components pha...
Photic Stimulation Middle Aged Visual Cortex Models, Neurological Electroencephalography Humans Algorithms Brain-Computer Interfaces Neural Networks, Computer Adult Evoked Potentials, Visual Male
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Robust Associative Learning Is Sufficient to Explain the Structural and Dynamical Properties of Local Cortical Circuits.

The Journal of neuroscience : the official journal of the Society for Neuroscience Jul 3, 2019
The ability of neural networks to associate successive states of network activity lies at the basis of many cognitive functions. Hence, we hypothesized that many ubiquitous structural and dynamical properties of local cortical networks result from as...
Conditioning, Classical Neural Networks, Computer Association Learning Models, Neurological Synapses Action Potentials Memory Neurons
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Approximating the Architecture of Visual Cortex in a Convolutional Network.

Neural computation Jul 1, 2019
Deep convolutional neural networks (CNNs) have certain structural, mechanistic, representational, and functional parallels with primate visual cortex and also many differences. However, perhaps some of the differences can be reconciled. This study de...
Neural Networks, Computer Neural Pathways Visual Cortex Macaca Animals Models, Neurological Neurons
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