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Conditioning, Classical

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Zebrafish exhibit associative learning for an aversive robotic stimulus.

Lab animal
Zebrafish have quickly emerged as a species of choice in preclinical research, holding promise to advance the field of behavioral pharmacology through high-throughput experiments. Besides biological and heuristic considerations, zebrafish also consti...

Population coding in the cerebellum: a machine learning perspective.

Journal of neurophysiology
The cere resembles a feedforward, three-layer network of neurons in which the "hidden layer" consists of Purkinje cells (P-cells) and the output layer consists of deep cerebellar nucleus (DCN) neurons. In this analogy, the output of each DCN neuron i...

Investigating Pain-Related Avoidance Behavior using a Robotic Arm-Reaching Paradigm.

Journal of visualized experiments : JoVE
Avoidance behavior is a key contributor to the transition from acute pain to chronic pain disability. Yet, there has been a lack of ecologically valid paradigms to experimentally investigate pain-related avoidance. To fill this gap, we developed a pa...

DeepLabStream enables closed-loop behavioral experiments using deep learning-based markerless, real-time posture detection.

Communications biology
In general, animal behavior can be described as the neuronal-driven sequence of reoccurring postures through time. Most of the available current technologies focus on offline pose estimation with high spatiotemporal resolution. However, to correlate ...

Printed synaptic transistor-based electronic skin for robots to feel and learn.

Science robotics
An electronic skin (e-skin) for the next generation of robots is expected to have biological skin-like multimodal sensing, signal encoding, and preprocessing. To this end, it is imperative to have high-quality, uniformly responding electronic devices...

Resolving the associative learning paradox by category learning in pigeons.

Current biology : CB
A wealth of evidence indicates that humans can engage two types of mechanisms to solve category-learning tasks: declarative mechanisms, which involve forming and testing verbalizable decision rules, and associative mechanisms, which involve gradually...

Memristor-Based Neural Network Circuit With Multimode Generalization and Differentiation on Pavlov Associative Memory.

IEEE transactions on cybernetics
Most of the classical conditioning laws implemented by existing circuits are involved in learning and forgetting between only three neurons, and the problems between multiple neurons are not considered. In this article, a multimode generalization and...

Autoshaped impulsivity: Some explorations with a neural network model.

Behavioural processes
This study evaluated the effect of delay and magnitude of reinforcement in Pavlovian contingencies, extending the understanding of the phenomenon of autoshaped impulsivity as described in Alcalá's thesis (2017) and Burgos and García-Leal (2015). The ...

Temporal pavlovian conditioning of a model spiking neural network for discrimination sequences of short time intervals.

Journal of computational neuroscience
The brain's ability to learn and distinguish rapid sequences of events is essential for timing-dependent tasks, such as those in sports and music. However, the mechanisms underlying this ability remain an active area of research. Here, we present a P...

Design and Implementation of Pavlovian Associative Memory Based on DNA Neurons.

IEEE transactions on neural networks and learning systems
In the field of biocomputing and neural networks, deoxyribonucleic acid (DNA) strand displacement (DSD) technology performs well in computation, programming, and information processing. In this article, the multiplication gate, addition gate, and thr...