AIMC Topic: Animals

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Decentralized control of insect walking: A simple neural network explains a wide range of behavioral and neurophysiological results.

PLoS computational biology
Controlling the six legs of an insect walking in an unpredictable environment is a challenging task, as many degrees of freedom have to be coordinated. Solutions proposed to deal with this task are usually based on the highly influential concept that...

Birds have peramorphic skulls, too: anatomical network analyses reveal oppositional heterochronies in avian skull evolution.

Communications biology
In contrast to the vast majority of reptiles, the skulls of adult crown birds are characterized by a high degree of integration due to bone fusion, e.g., an ontogenetic event generating a net reduction in the number of bones. To understand this proce...

Fully Automated Leg Tracking in Freely Moving Insects using Feature Learning Leg Segmentation and Tracking (FLLIT).

Journal of visualized experiments : JoVE
The Drosophila model has been invaluable for the study of neurological function and for understanding the molecular and cellular mechanisms that underlie neurodegeneration. While fly techniques for the manipulation and study of neuronal subsets have ...

Robust classification of cell cycle phase and biological feature extraction by image-based deep learning.

Molecular biology of the cell
Across the cell cycle, the subcellular organization undergoes major spatiotemporal changes that could in principle contain biological features that could potentially represent cell cycle phase. We applied convolutional neural network-based classifier...

A Spatiotemporal Convolutional Network for Multi-Behavior Recognition of Pigs.

Sensors (Basel, Switzerland)
The statistical data of different kinds of behaviors of pigs can reflect their health status. However, the traditional behavior statistics of pigs were obtained and then recorded from the videos through human eyes. In order to reduce labor and time c...

Artificial Intelligence in radiotherapy: state of the art and future directions.

Medical oncology (Northwood, London, England)
Recent advances in computing capability allowed the development of sophisticated predictive models to assess complex relationships within observational data, described as Artificial Intelligence. Medicine is one of the several fields of application a...

Bio-inspired multi-scale fusion.

Biological cybernetics
We reveal how implementing the homogeneous, multi-scale mapping frameworks observed in the mammalian brain's mapping systems radically improves the performance of a range of current robotic localization techniques. Roboticists have developed a range ...

Population coupling predicts the plasticity of stimulus responses in cortical circuits.

eLife
Some neurons have stimulus responses that are stable over days, whereas other neurons have highly plastic stimulus responses. Using a recurrent network model, we explore whether this could be due to an underlying diversity in their synaptic plasticit...

Deep learning for automated detection of Drosophila suzukii: potential for UAV-based monitoring.

Pest management science
BACKGROUND: The fruit fly Drosophila suzukii, or spotted wing drosophila (SWD), is a serious pest worldwide, attacking many soft-skinned fruits. An efficient monitoring system that identifies and counts SWD in crops and their surroundings is therefor...

Combination Strategies for Immune-Checkpoint Blockade and Response Prediction by Artificial Intelligence.

International journal of molecular sciences
The therapeutic concept of unleashing a pre-existing immune response against the tumor by the application of immune-checkpoint inhibitors (ICI) has resulted in long-term survival in advanced cancer patient subgroups. However, the majority of patients...