AIMC Topic: Behavior, Animal
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Deep learning tools for the measurement of animal behavior in neuroscience.
Current opinion in neurobiology
Nov 29, 2019
Recent advances in computer vision have made accurate, fast and robust measurement of animal behavior a reality. In the past years powerful tools specifically designed to aid the measurement of behavior have come to fruition. Here we discuss how capt...
The Effects of Population Tuning and Trial-by-Trial Variability on Information Encoding and Behavior.
The Journal of neuroscience : the official journal of the Society for Neuroscience
Nov 21, 2019
Identifying the features of population responses that are relevant to the amount of information encoded by neuronal populations is a crucial step toward understanding population coding. Statistical features, such as tuning properties, individual and ...
Considerations in using recurrent neural networks to probe neural dynamics.
Journal of neurophysiology
Oct 16, 2019
Recurrent neural networks (RNNs) are increasingly being used to model complex cognitive and motor tasks performed by behaving animals. RNNs are trained to reproduce animal behavior while also capturing key statistics of empirically recorded neural ac...
Design and development of a robotic predator as a stimulus in conditioned place aversion for the study of the effect of ethanol and citalopram in zebrafish.
Behavioural brain research
Oct 12, 2019
Zebrafish are becoming a species of choice in psychopharmacology, laying a promising path to refined pharmacological manipulations and high-throughput behavioral phenotyping. The field of robotics has the potential to accelerate progress along this p...
DeepPoseKit, a software toolkit for fast and robust animal pose estimation using deep learning.
eLife
Oct 1, 2019
Quantitative behavioral measurements are important for answering questions across scientific disciplines-from neuroscience to ecology. State-of-the-art deep-learning methods offer major advances in data quality and detail by allowing researchers to a...
Deep attention networks reveal the rules of collective motion in zebrafish.
PLoS computational biology
Sep 13, 2019
A variety of simple models has been proposed to understand the collective motion of animals. These models can be insightful but may lack important elements necessary to predict the motion of each individual in the collective. Adding more detail incre...
Sensory processing and categorization in cortical and deep neural networks.
NeuroImage
Aug 21, 2019
Many recent advances in artificial intelligence (AI) are rooted in visual neuroscience. However, ideas from more complicated paradigms like decision-making are less used. Although automated decision-making systems are ubiquitous (driverless cars, pil...
A critique of pure learning and what artificial neural networks can learn from animal brains.
Nature communications
Aug 21, 2019
Artificial neural networks (ANNs) have undergone a revolution, catalyzed by better supervised learning algorithms. However, in stark contrast to young animals (including humans), training such networks requires enormous numbers of labeled examples, l...
Bidirectional interactions facilitate the integration of a robot into a shoal of zebrafish Danio rerio.
PloS one
Aug 20, 2019
Many studies on collective animal behavior seek to identify the individual rules that underlie collective patterns. However, it was not until the recent advancements of micro-electronic and embedded systems that scientists were able to create mixed g...
An automatic behavior recognition system classifies animal behaviors using movements and their temporal context.
Journal of neuroscience methods
Aug 12, 2019
Animals can perform complex and purposeful behaviors by executing simpler movements in flexible sequences. It is particularly challenging to analyze behavior sequences when they are highly variable, as is the case in language production, certain type...
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