AIMC Topic: Animals

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Morbidity Rate Prediction of Dengue Hemorrhagic Fever (DHF) Using the Support Vector Machine and the Aedes aegypti Infection Rate in Similar Climates and Geographical Areas.

PloS one
BACKGROUND: In the past few decades, several researchers have proposed highly accurate prediction models that have typically relied on climate parameters. However, climate factors can be unreliable and can lower the effectiveness of prediction when t...

Machine learning applications in genetics and genomics.

Nature reviews. Genetics
The field of machine learning, which aims to develop computer algorithms that improve with experience, holds promise to enable computers to assist humans in the analysis of large, complex data sets. Here, we provide an overview of machine learning ap...

Deep convolutional neural networks for annotating gene expression patterns in the mouse brain.

BMC bioinformatics
BACKGROUND: Profiling gene expression in brain structures at various spatial and temporal scales is essential to understanding how genes regulate the development of brain structures. The Allen Developing Mouse Brain Atlas provides high-resolution 3-D...

A realistic bi-hemispheric model of the cerebellum uncovers the purpose of the abundant granule cells during motor control.

Frontiers in neural circuits
The cerebellar granule cells (GCs) have been proposed to perform lossless, adaptive spatio-temporal coding of incoming sensory/motor information required by downstream cerebellar circuits to support motor learning, motor coordination, and cognition. ...

On simplicity and complexity in the brave new world of large-scale neuroscience.

Current opinion in neurobiology
Technological advances have dramatically expanded our ability to probe multi-neuronal dynamics and connectivity in the brain. However, our ability to extract a simple conceptual understanding from complex data is increasingly hampered by the lack of ...

Perception Evolution Network Based on Cognition Deepening Model--Adapting to the Emergence of New Sensory Receptor.

IEEE transactions on neural networks and learning systems
The proposed perception evolution network (PEN) is a biologically inspired neural network model for unsupervised learning and online incremental learning. It is able to automatically learn suitable prototypes from learning data in an incremental way,...

Characterizing Vocal Repertoires--Hard vs. Soft Classification Approaches.

PloS one
To understand the proximate and ultimate causes that shape acoustic communication in animals, objective characterizations of the vocal repertoire of a given species are critical, as they provide the foundation for comparative analyses among individua...

Eigenspectrum bounds for semirandom matrices with modular and spatial structure for neural networks.

Physical review. E, Statistical, nonlinear, and soft matter physics
The eigenvalue spectrum of the matrix of directed weights defining a neural network model is informative of several stability and dynamical properties of network activity. Existing results for eigenspectra of sparse asymmetric random matrices neglect...

A network model comprising 4 segmental, interconnected ganglia, and its application to simulate multi-legged locomotion in crustaceans.

Journal of computational neuroscience
Inter-segmental coordination is crucial for the locomotion of animals. Arthropods show high variability of leg numbers, from 6 in insects up to 750 legs in millipedes. Despite this fact, the anatomical and functional organization of their nervous sys...

Acute caffeine administration affects zebrafish response to a robotic stimulus.

Behavioural brain research
Zebrafish has been recently proposed as a valid animal model to investigate the fundamental mechanisms regulating emotional behavior and evaluate the modulatory effects exerted by psychoactive compounds. In this study, we propose a novel methodologic...