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4,132 Result(s)
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Article
Open AccessHow the brain can be trained to achieve an intermittent control strategy for stabilizing quiet stance by means of reinforcement learning
The stabilization of human quiet stance is achieved by a combination of the intrinsic elastic properties of ankle muscles and an active closed-loop activation of the ankle muscles, driven by the delayed feedba...
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Open AccessFull Hill-type muscle model of the I1/I3 retractor muscle complex in Aplysia californica
The coordination of complex behavior requires knowledge of both neural dynamics and the mechanics of the periphery. The feeding system of Aplysia californica is an excellent model for investigating questions in s...
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Open AccessCOVID-19 and silent hypoxemia in a minimal closed-loop model of the respiratory rhythm generator
Silent hypoxemia, or “happy hypoxia,” is a puzzling phenomenon in which patients who have contracted COVID-19 exhibit very low oxygen saturation ( $$\t...
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Neural coding of space by time
The intertwining of space and time poses a significant scientific challenge, transcending disciplines from philosophy and physics to neuroscience. Deciphering neural coding, marked by its inherent spatial and ...
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Open AccessA computational neural model that incorporates both intrinsic dynamics and sensory feedback in the Aplysia feeding network
Studying the nervous system underlying animal motor control can shed light on how animals can adapt flexibly to a changing environment. We focus on the neural basis of feeding control in Aplysia californica. Usin...
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Controlling flat-foot limit cycle walkers with compliant joints based on local stability variation
This study investigates local stability of a four-link limit cycle walking biped with flat feet and compliant ankle joints. Local stability represents the behavior along the solution trajectory between Poincar...
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Open AccessStability against fluctuations: a two-dimensional study of scaling, bifurcations and spontaneous symmetry breaking in stochastic models of synaptic plasticity
Stochastic models of synaptic plasticity must confront the corrosive influence of fluctuations in synaptic strength on patterns of synaptic connectivity. To solve this problem, we have proposed that synapses a...
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What have we learned about artificial intelligence from studying the brain?
Neuroscience and artificial intelligence (AI) share a long, intertwined history. It has been argued that discoveries in neuroscience were (and continue to be) instrumental in driving the development of new AI ...
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Open AccessFluctuation–response relations for integrate-and-fire models with an absolute refractory period
We study the problem of relating the spontaneous fluctuations of a stochastic integrate-and-fire (IF) model to the response of the instantaneous firing rate to time-dependent stimulation if the IF model is end...
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A dynamic computational model of the parallel circuit on the basal ganglia-cortex associated with Parkinson’s disease dementia
The cognitive impairment will gradually appear over time in Parkinson's patients, which is closely related to the basal ganglia-cortex network. This network contains two parallel circuits mediated by putamen a...
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Open AccessEmpirical modeling and prediction of neuronal dynamics
Mathematical modeling of neuronal dynamics has experienced a fast growth in the last decades thanks to the biophysical formalism introduced by Hodgkin and Huxley in the 1950s. Other types of models (for instan...
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EEG rhythm separation and time–frequency analysis of fast multivariate empirical mode decomposition for motor imagery BCI
Motor imagery electroencephalogram (EEG) is widely employed in brain–computer interface (BCI) systems. As a time–frequency analysis method for nonlinear and non-stationary signals, multivariate empirical mode ...
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Four attributes of intelligence, a thousand questions
Jeff Hawkins is one of those rare individuals who speaks the languages of both AI and neuroscience. In his recent book, "A Thousand Brains: A New Theory of Intelligence", Hawkins proposes that current learning...
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Multistability in neural systems with random cross-connections
Neural circuits with multiple discrete attractor states could support a variety of cognitive tasks according to both empirical data and model simulations. We assess the conditions for such multistability in ne...
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Open AccessDivisive normalization processors in the early visual system of the Drosophila brain
Divisive normalization is a model of canonical computation of brain circuits. We demonstrate that two cascaded divisive normalization processors (DNPs), carrying out intensity/contrast gain control and element...
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Open AccessFace detection based on a human attention guided multi-scale model
Multiscale models are among the cutting-edge technologies used for face detection and recognition. An example is Deformable part-based models (DPMs), which encode a face as a multiplicity of local areas (parts...
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Energy optimisation predicts the capacity of ion buffering in the brain
Neurons store energy in the ionic concentration gradients they build across their cell membrane. The amount of energy stored, and hence the work the ions can do by mixing, can be enhanced by the presence of io...
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Single-compartment model of a pyramidal neuron, fitted to recordings with current and conductance injection
For single neuron models, reproducing characteristics of neuronal activity such as the firing rate, amplitude of spikes, and threshold potentials as functions of both synaptic current and conductance is a chal...
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Open AccessToward metacognition: subject-aware contrastive deep fusion representation learning for EEG analysis
We propose a subject-aware contrastive learning deep fusion neural network framework for effectively classifying subjects’ confidence levels in the perception of visual stimuli. The framework, called WaveFusion, ...
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Stakes of neuromorphic foveation: a promising future for embedded event cameras
Foveation can be defined as the organic action of directing the gaze towards a visual region of interest to acquire relevant information selectively. With the recent advent of event cameras, we believe that ta...