AIMC Topic: Rats, Long-Evans
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A virtual rodent predicts the structure of neural activity across behaviours.
Nature
Jun 11, 2024
Animals have exquisite control of their bodies, allowing them to perform a diverse range of behaviours. How such control is implemented by the brain, however, remains unclear. Advancing our understanding requires models that can relate principles of ...
Time series classification of multi-channel nerve cuff recordings using deep learning.
PloS one
Mar 12, 2024
Neurostimulation and neural recording are crucial to develop neuroprostheses that can restore function to individuals living with disabilities. While neurostimulation has been successfully translated into clinical use for several applications, it rem...
Early inner plexiform layer thinning and retinal nerve fiber layer thickening in excitotoxic retinal injury using deep learning-assisted optical coherence tomography.
Acta neuropathologica communications
Feb 1, 2024
Excitotoxicity from the impairment of glutamate uptake constitutes an important mechanism in neurodegenerative diseases such as Alzheimer's, multiple sclerosis, and Parkinson's disease. Within the eye, excitotoxicity is thought to play a critical rol...
Machine intelligence identifies soluble TNFa as a therapeutic target for spinal cord injury.
Scientific reports
Feb 9, 2021
Traumatic spinal cord injury (SCI) produces a complex syndrome that is expressed across multiple endpoints ranging from molecular and cellular changes to functional behavioral deficits. Effective therapeutic strategies for CNS injury are therefore li...
Selective peripheral nerve recordings from nerve cuff electrodes using convolutional neural networks.
Journal of neural engineering
Jan 31, 2020
OBJECTIVE: Recording and stimulating from the peripheral nervous system are becoming important components in a new generation of bioelectronics systems. Although neurostimulation has seen a history of successful chronic applications in humans, periph...
How Much Does Movement and Location Encoding Impact Prefrontal Cortex Activity? An Algorithmic Decoding Approach in Freely Moving Rats.
eNeuro
Apr 27, 2018
Specialized brain structures encode spatial locations and movements, yet there is growing evidence that this information is also represented in the rodent medial prefrontal cortex (mPFC). Disambiguating such information from the encoding of other typ...
Analysis of complex neural circuits with nonlinear multidimensional hidden state models.
Proceedings of the National Academy of Sciences of the United States of America
May 24, 2016
A universal need in understanding complex networks is the identification of individual information channels and their mutual interactions under different conditions. In neuroscience, our premier example, networks made up of billions of nodes dynamica...
Behavior modulation of rats to a robotic rat in multi-rat interaction.
Bioinspiration & biomimetics
Sep 28, 2015
In this paper, we study the behavioral response of rats to a robotic rat during multi-rat interaction. Experiments are conducted in an open-field where a robotic rat called WR-5 is put together with three laboratory rats. WR-5 is following one rat (t...
Watching from a distance: A robotically controlled laser and real-time subject tracking software for the study of conditioned predator/prey-like interactions.
Journal of neuroscience methods
Jun 22, 2015
BACKGROUND: The physical distance between predator and prey is a primary determinant of behavior, yet few paradigms exist to study this reliably in rodents.
Sub-processes of motor learning revealed by a robotic manipulandum for rodents.
Behavioural brain research
Nov 8, 2014
Rodent models are widely used to investigate neural changes in response to motor learning. Usually, the behavioral readout of motor learning tasks used for this purpose is restricted to a binary measure of performance (i.e. "successful" movement vs. ...
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