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Neural Pathways

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Statistical algorithms for emotion classification via functional connectivity.

Journal of integrative neuroscience
Pattern recognition algorithms decode emotional brain states by using functional connectivity measures which are extracted from EEG signals as input to the statistical classifiers. An open-access EEG dataset for emotional state analysis is used to cl...

Detection and Classification of Novel Renal Histologic Phenotypes Using Deep Neural Networks.

The American journal of pathology
With the advent and increased accessibility of deep neural networks (DNNs), complex properties of histologic images can be rigorously and reproducibly quantified. We used DNN-based transfer learning to analyze histologic images of periodic acid-Schif...

Machine learning multivariate pattern analysis predicts classification of posttraumatic stress disorder and its dissociative subtype: a multimodal neuroimaging approach.

Psychological medicine
BACKGROUND: The field of psychiatry would benefit significantly from developing objective biomarkers that could facilitate the early identification of heterogeneous subtypes of illness. Critically, although machine learning pattern recognition method...

Approximating the Architecture of Visual Cortex in a Convolutional Network.

Neural computation
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...

A Convolutional Neural Network-based Model of Neural Pathways in the Retina.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
A variety of the visual functions of the vertebrate retina rely on the interactions between excitation and inhibition within specialized retinal circuitry. The nonlinear properties of these interactions, as well as a large number of cell types and pa...

A self-organized recurrent neural network for estimating the effective connectivity and its application to EEG data.

Computers in biology and medicine
OBJECTIVE: Effective connectivity is an important notion in neuroscience research, useful for detecting the interactions between regions of the brain.

A Computational Perspective of the Role of the Thalamus in Cognition.

Neural computation
The thalamus has traditionally been considered as only a relay source of cortical inputs, with hierarchically organized cortical circuits serially transforming thalamic signals to cognitively relevant representations. Given the absence of local excit...

Spatiotemporal discrimination in attractor networks with short-term synaptic plasticity.

Journal of computational neuroscience
We demonstrate that a randomly connected attractor network with dynamic synapses can discriminate between similar sequences containing multiple stimuli suggesting such networks provide a general basis for neural computations in the brain. The network...

Functional connectivity in multiple sclerosis after robotic rehabilitative treatment: A case report.

Medicine
RATIONALE: Multiple sclerosis (MS) is an inflammatory demyelinating disease of central nervous system and it is associated with an impaired motor function status. The efficacy of rehabilitation in promoting functional recovery and increasing quality ...

Membrane potential resonance in non-oscillatory neurons interacts with synaptic connectivity to produce network oscillations.

Journal of computational neuroscience
Several neuron types have been shown to exhibit (subthreshold) membrane potential resonance (MPR), defined as the occurrence of a peak in their voltage amplitude response to oscillatory input currents at a preferred (resonant) frequency. MPR has been...