AIMC Topic: Rats

Clear Filters Showing 611 to 620 of 676 articles

Assessing Deep and Shallow Learning Methods for Quantitative Prediction of Acute Chemical Toxicity.

Toxicological sciences : an official journal of the Society of Toxicology
Animal-based methods for assessing chemical toxicity are struggling to meet testing demands. In silico approaches, including machine-learning methods, are promising alternatives. Recently, deep neural networks (DNNs) were evaluated and reported to ou...

Smart Data Analytics approach to model Complex Biochemical Oscillations in Hippocampal Neurons.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Calcium spiking can be used for drug screening studies in pharmaceutical industries. However, performing experiments for multiple drugs and doses are highly expensive. The oscillatory behavior of calcium spiking data demonstrates extreme nonlinearity...

A Comparison Study of Point-Process Filter and Deep Learning Performance in Estimating Rat Position Using an Ensemble of Place Cells.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
The emergence of deep learning techniques has provided new tools for the analysis of complex data in the field of neuroscience. In parallel, advanced statistical approaches like point-process modeling provide powerful tools for analyzing the spiking ...

Neural Decoding Forelimb Trajectory Using Evolutionary Neural Networks with Feedback-Error-Learning Schemes.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Changes in the functional mapping between neural activities and kinematic parameters over time poses a challenge to current neural decoder of brain machine interfaces (BMIs). Traditional decoders robust to changes in functional mappings required many...

Unsupervised Phase Learning and Extraction from Repetitive Movements.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Phase extraction from repetitive movements is one crucial part in various applications such as interactive robotics, physical rehabilitation, or gait analysis. However, pre-existing automatic phase extraction techniques are specific to a target movem...

Object Recognition: Complexity of Recognition Strategies.

Current biology : CB
Primate brains and state-of-the-art convolutional neural networks can recognize many faces, objects and scenes, though how they do so is often mysterious. New research unveils some of the mystery, revealing unexpected complexity in the recognition st...

Real-time cerebellar neuroprosthetic system based on a spiking neural network model of motor learning.

Journal of neural engineering
OBJECTIVE: Damage to the brain, as a result of various medical conditions, impacts the everyday life of patients and there is still no complete cure to neurological disorders. Neuroprostheses that can functionally replace the damaged neural circuit h...