AIMC Topic: Animals

Clear Filters Showing 5481 to 5490 of 8866 articles

Episodic Memory in Minicolumn Associative Knowledge Graphs.

IEEE transactions on neural networks and learning systems
A generalization of active neural associative knowledge graphs (ANAKGs) to their minicolumn form is presented in this paper. Each minicolumn represents a single symbol, and the activation of an individual neuron in a minicolumn depends on the context...

Beyond the "Conceptual Nervous System": Can computational cognitive neuroscience transform learning theory?

Behavioural processes
In the last century, learning theory has been dominated by an approach assuming that associations between hypothetical representational nodes can support the acquisition of knowledge about the environment. The similarities between this approach and c...

Artificial Intelligence for Drug Toxicity and Safety.

Trends in pharmacological sciences
Interventional pharmacology is one of medicine's most potent weapons against disease. These drugs, however, can result in damaging side effects and must be closely monitored. Pharmacovigilance is the field of science that monitors, detects, and preve...

Using artificial neural networks to predict pH, ammonia, and volatile fatty acid concentrations in the rumen.

Journal of dairy science
The objectives of this study were (1) to predict ruminal pH and ruminal ammonia and volatile fatty acid (VFA) concentrations by developing artificial neural networks (ANN) using dietary nutrient compositions, dry matter intake, and body weight as inp...

Characterization of Nanoscale Organization of F-Actin in Morphologically Distinct Dendritic Spines Using Supervised Learning.

eNeuro
The cytoarchitecture of a neuron is very important in defining morphology and ultrastructure. Although there is a wealth of information on the molecular components that make and regulate these ultrastructures, there is a dearth of understanding of ho...

Convergent Temperature Representations in Artificial and Biological Neural Networks.

Neuron
Discoveries in biological neural networks (BNNs) shaped artificial neural networks (ANNs) and computational parallels between ANNs and BNNs have recently been discovered. However, it is unclear to what extent discoveries in ANNs can give insight into...

Machine learning and data mining frameworks for predicting drug response in cancer: An overview and a novel in silico screening process based on association rule mining.

Pharmacology & therapeutics
A major challenge in cancer treatment is predicting the clinical response to anti-cancer drugs on a personalized basis. The success of such a task largely depends on the ability to develop computational resources that integrate big "omic" data into e...

scGen predicts single-cell perturbation responses.

Nature methods
Accurately modeling cellular response to perturbations is a central goal of computational biology. While such modeling has been based on statistical, mechanistic and machine learning models in specific settings, no generalization of predictions to ph...

Development and experiments of a bio-inspired robot with multi-mode in aerial and terrestrial locomotion.

Bioinspiration & biomimetics
This paper introduces a new multi-modal robot capable of terrestrial and aerial locomotion, aiming to operate in a wider range of environments. The robot was built to achieve two locomotion modes of walking and gliding while preventing one modality h...

Spread of α-synuclein pathology through the brain connectome is modulated by selective vulnerability and predicted by network analysis.

Nature neuroscience
Studies of patients afflicted by neurodegenerative diseases suggest that misfolded proteins spread through the brain along anatomically connected networks, prompting progressive decline. Recently, mouse models have recapitulated the cell-to-cell tran...