AIMC Topic: Neural Networks, Computer

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Computational Architecture of the Granular Layer of Cerebellum-Like Structures.

Cerebellum (London, England)
In the adaptive filter model of the cerebellum, the granular layer performs a recoding which expands incoming mossy fibre signals into a temporally diverse set of basis signals. The underlying neural mechanism is not well understood, although various...

TRACX2: a connectionist autoencoder using graded chunks to model infant visual statistical learning.

Philosophical transactions of the Royal Society of London. Series B, Biological sciences
Even newborn infants are able to extract structure from a stream of sensory inputs; yet how this is achieved remains largely a mystery. We present a connectionist autoencoder model, TRACX2, that learns to extract sequence structure by gradually const...

Complementary learning systems within the hippocampus: a neural network modelling approach to reconciling episodic memory with statistical learning.

Philosophical transactions of the Royal Society of London. Series B, Biological sciences
A growing literature suggests that the hippocampus is critical for the rapid extraction of regularities from the environment. Although this fits with the known role of the hippocampus in rapid learning, it seems at odds with the idea that the hippoca...

[Modeling and Predicting of MODIS Leaf Area Index Time Series Based on a Hybrid SARIMA and BP Neural Network Method].

Guang pu xue yu guang pu fen xi = Guang pu
The modeling and predicting of vegetation Leaf area index (LAI) is an important component of land surface model and assimilation of remote sensing data. The MODIS LAI product (i.e. MOD15A2) is one of the most widely used LAI data sources. However, th...

Digging deeper on "deep" learning: A computational ecology approach.

The Behavioral and brain sciences
We propose an alternative approach to "deep" learning that is based on computational ecologies of structurally diverse artificial neural networks, and on dynamic associative memory responses to stimuli. Rather than focusing on massive computation of ...

The architecture challenge: Future artificial-intelligence systems will require sophisticated architectures, and knowledge of the brain might guide their construction.

The Behavioral and brain sciences
In this commentary, we highlight a crucial challenge posed by the proposal of Lake et al. to introduce key elements of human cognition into deep neural networks and future artificial-intelligence systems: the need to design effective sophisticated ar...

Right putamen and age are the most discriminant features to diagnose Parkinson's disease by using I-FP-CIT brain SPET data by using an artificial neural network classifier, a classification tree (ClT).

Hellenic journal of nuclear medicine
OBJECTIVE: The differential diagnosis of Parkinson's disease (PD) and other conditions, such as essential tremor and drug-induced parkinsonian syndrome or normal aging brain, represents a diagnostic challenge. I-FP-CIT brain SPET is able to contribut...

Deep Diabetologist: Learning to Prescribe Hypoglycemic Medications with Recurrent Neural Networks.

Studies in health technology and informatics
In healthcare, applying deep learning models to electronic health records (EHRs) has drawn considerable attention. This sequential nature of EHR data make them wellmatched for the power of Recurrent Neural Network (RNN). In this poster, we propose "D...

Avoiding Overfitting in Deep Neural Networks for Clinical Opinions Generation from General Blood Test Results.

Studies in health technology and informatics
We have used deep neural networks (DNNs) to generate clinical opinions from general blood test results. DNNs have overfitting problem in general. We believe the complex structure of DNN and insufficient data to be the major reasons of overfitting in ...

A Deep Learning-Based Method for Similar Patient Question Retrieval in Chinese.

Studies in health technology and informatics
The online patient question and answering (Q&A) system, either as a website or a mobile application, attracts an increasing number of users in China. Patients will post their questions and the registered doctors then provide the corresponding ans...