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Models, Neurological

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Decision making under uncertainty in a spiking neural network model of the basal ganglia.

Journal of integrative neuroscience
The mechanisms of decision-making and action selection are generally thought to be under the control of parallel cortico-subcortical loops connecting back to distinct areas of cortex through the basal ganglia and processing motor, cognitive and limbi...

Comparison of Classifier Architectures for Online Neural Spike Sorting.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
High-density, intracranial recordings from micro-electrode arrays need to undergo Spike Sorting in order to associate the recorded neuronal spikes to particular neurons. This involves spike detection, feature extraction, and classification. To reduce...

Using deep belief network modelling to characterize differences in brain morphometry in schizophrenia.

Scientific reports
Neuroimaging-based models contribute to increasing our understanding of schizophrenia pathophysiology and can reveal the underlying characteristics of this and other clinical conditions. However, the considerable variability in reported neuroimaging ...

Revealing unobserved factors underlying cortical activity with a rectified latent variable model applied to neural population recordings.

Journal of neurophysiology
The activity of sensory cortical neurons is not only driven by external stimuli but also shaped by other sources of input to the cortex. Unlike external stimuli, these other sources of input are challenging to experimentally control, or even observe,...

Exponentially Long Orbits in Hopfield Neural Networks.

Neural computation
We show that Hopfield neural networks with synchronous dynamics and asymmetric weights admit stable orbits that form sequences of maximal length. For [Formula: see text] units, these sequences have length [Formula: see text]; that is, they cover the ...

Modeling the N400 ERP component as transient semantic over-activation within a neural network model of word comprehension.

Cognition
The study of the N400 event-related brain potential has provided fundamental insights into the nature of real-time comprehension processes, and its amplitude is modulated by a wide variety of stimulus and context factors. It is generally thought to r...

Prediction of blood-brain barrier permeability of organic compounds.

Doklady. Biochemistry and biophysics
Using fragmental descriptors and artificial neural networks, a predictive model of the relationship between the structure of organic compounds and their blood-brain barrier permeability was constructed and the structural factors affecting the readine...

Anti-correlations in the degree distribution increase stimulus detection performance in noisy spiking neural networks.

Journal of computational neuroscience
Neuronal circuits in the rodent barrel cortex are characterized by stable low firing rates. However, recent experiments show that short spike trains elicited by electrical stimulation in single neurons can induce behavioral responses. Hence, the unde...

Unsupervised Learning in an Ensemble of Spiking Neural Networks Mediated by ITDP.

PLoS computational biology
We propose a biologically plausible architecture for unsupervised ensemble learning in a population of spiking neural network classifiers. A mixture of experts type organisation is shown to be effective, with the individual classifier outputs combine...

Introducing the Big Knowledge to Use (BK2U) challenge.

Annals of the New York Academy of Sciences
The purpose of the Big Data to Knowledge initiative is to develop methods for discovering new knowledge from large amounts of data. However, if the resulting knowledge is so large that it resists comprehension, referred to here as Big Knowledge (BK),...