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Conditioning, Operant

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Extending unified-theory-of-reinforcement neural networks to steady-state operant behavior.

Behavioural processes
The unified theory of reinforcement has been used to develop models of behavior over the last 20 years (Donahoe et al., 1993). Previous research has focused on the theory's concordance with the respondent behavior of humans and animals. In this exper...

Emergent coordination underlying learning to reach to grasp with a brain-machine interface.

Journal of neurophysiology
The development of coordinated reach-to-grasp movement has been well studied in infants and children. However, the role of motor cortex during this development is unclear because it is difficult to study in humans. We took the approach of using a bra...

Deep(er) Learning.

The Journal of neuroscience : the official journal of the Society for Neuroscience
Animals successfully thrive in noisy environments with finite resources. The necessity to function with resource constraints has led evolution to design animal brains (and bodies) to be optimal in their use of computational power while being adaptabl...

A Robotic System for Adaptive Training and Function Assessment of Forelimb Retraction in Mice.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Rodent models are decisive for translational research in healthy and pathological conditions of motor function thanks to specific similarities with humans. Here, we present an upgraded version of the M-Platform, a robotic device previously designed t...

Memristor Neural Network Circuit Based on Operant Conditioning With Immediacy and Satiety.

IEEE transactions on biomedical circuits and systems
Most of the operant conditioning only consider the basic theory, but the influencing factors such as immediacy and satiety are ignored. In this paper, a memristor neural network circuit based on operant conditioning with immediacy and satiety is prop...

Convolutional neural network model by deep learning and teaching robot in keyboard musical instrument teaching.

PloS one
Keyboard instruments play a significant role in the music teaching process, providing students with an enjoyable musical experience while enhancing their music literacy. This study aims to investigate the current state of keyboard instrument teaching...

Bird song comparison using deep learning trained from avian perceptual judgments.

PLoS computational biology
Our understanding of bird song, a model system for animal communication and the neurobiology of learning, depends critically on making reliable, validated comparisons between the complex multidimensional syllables that are used in songs. However, mos...

Operant Conditioning Neuromorphic Circuit With Addictiveness and Time Memory for Automatic Learning.

IEEE transactions on biomedical circuits and systems
Most operant conditioning circuits predominantly focus on simple feedback process, few studies consider the intricacies of feedback outcomes and the uncertainty of feedback time. This paper proposes a neuromorphic circuit based on operant conditionin...

Analysis of Operant Self-administration Behaviors with Supervised Machine Learning: Protocol for Video Acquisition and Pose Estimation Analysis Using DeepLabCut and Simple Behavioral Analysis.

eNeuro
The use of supervised machine learning to approximate poses in video recordings allows for rapid and efficient analysis of complex behavioral profiles. Currently, there are limited protocols for automated analysis of operant self-administration behav...

Of rats and robots: A mutual learning paradigm.

Journal of the experimental analysis of behavior
Robots are increasingly used alongside Skinner boxes to train animals in operant conditioning tasks. Similarly, animals are being employed in artificial intelligence research to train various algorithms. However, both types of experiments rely on uni...