AI Medical Compendium Topic:
Models, Neurological

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Recurring Functional Interactions Predict Network Architecture of Interictal and Ictal States in Neocortical Epilepsy.

eNeuro
Human epilepsy patients suffer from spontaneous seizures, which originate in brain regions that also subserve normal function. Prior studies demonstrate focal, neocortical epilepsy is associated with dysfunction, several hours before seizures. How do...

Sparse and Specific Coding during Information Transmission between Co-cultured Dentate Gyrus and CA3 Hippocampal Networks.

Frontiers in neural circuits
To better understand encoding and decoding of stimulus information in two specific hippocampal sub-regions, we isolated and co-cultured rat primary dentate gyrus (DG) and CA3 neurons within a two-chamber device with axonal connectivity via micro-tunn...

HTM Spatial Pooler With Memristor Crossbar Circuits for Sparse Biometric Recognition.

IEEE transactions on biomedical circuits and systems
Hierarchical Temporal Memory (HTM) is an online machine learning algorithm that emulates the neo-cortex. The development of a scalable on-chip HTM architecture is an open research area. The two core substructures of HTM are spatial pooler and tempora...

Feedback for reinforcement learning based brain-machine interfaces using confidence metrics.

Journal of neural engineering
OBJECTIVE: For brain-machine interfaces (BMI) to be used in activities of daily living by paralyzed individuals, the BMI should be as autonomous as possible. One of the challenges is how the feedback is extracted and utilized in the BMI. Our long-ter...

Cracking the barcode of fullerene-like cortical microcolumns.

Neuroscience letters
Artificial neural systems and nervous graph theoretical analysis rely upon the stance that the neural code is embodied in logic circuits, e.g., spatio-temporal sequences of ON/OFF spiking neurons. Nevertheless, this assumption does not fully explain ...

A mathematical model for the two-learners problem.

Journal of neural engineering
OBJECTIVE: We present the first generic theoretical formulation of the co-adaptive learning problem and give a simple example of two interacting linear learning systems, a human and a machine.

Dual-memory neural networks for modeling cognitive activities of humans via wearable sensors.

Neural networks : the official journal of the International Neural Network Society
Wearable devices, such as smart glasses and watches, allow for continuous recording of everyday life in a real world over an extended period of time or lifelong. This possibility helps better understand the cognitive behavior of humans in real life a...

Noise-robust unsupervised spike sorting based on discriminative subspace learning with outlier handling.

Journal of neural engineering
OBJECTIVE: Spike sorting is a fundamental preprocessing step for many neuroscience studies which rely on the analysis of spike trains. Most of the feature extraction and dimensionality reduction techniques that have been used for spike sorting give a...

Classifier transfer with data selection strategies for online support vector machine classification with class imbalance.

Journal of neural engineering
OBJECTIVE: Classifier transfers usually come with dataset shifts. To overcome dataset shifts in practical applications, we consider the limitations in computational resources in this paper for the adaptation of batch learning algorithms, like the sup...

Structured Pyramidal Neural Networks.

International journal of neural systems
The Pyramidal Neural Networks (PNN) are an example of a successful recently proposed model inspired by the human visual system and deep learning theory. PNNs are applied to computer vision and based on the concept of receptive fields. This paper prop...