TaiNi: Maximizing research output whilst improving animals’ welfare in neurophysiology experiments

Jiang, Zhou; Huxter, John R.; Bowyer, Stuart A; Blockeel, Anthony James; Butler, J. L.; Imtiaz, Syed Anas; Wafford, Keith A.; Phillips, Keith G.; Tricklebank, Mark D.; Marston, Hugh; Rodriguez‐Villegas, Esther

doi:10.1038/s41598-017-08078-8

Cited by 19 publications

(8 citation statements)

References 25 publications

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“…Meanwhile, advances in microelectrode fabrication techniques allow high channel counts in a relatively small surface area, enabling the acquisition of EEGs with higher spatial resolution and brain coverage ( Obien et al, 2014 ; Wasilczuk et al, 2016 ). Furthermore, multiple wireless recording systems are now available that allow long-term recordings without tethering mice, providing an opportunity for improved animal welfare ( Chang et al, 2011 ; Jiang et al, 2017 ; Lidster et al, 2016 ).…”

Section: Problems Of Two Sorts With Genetic Mouse Modelsmentioning

confidence: 99%

Modelling epilepsy in the mouse: challenges and solutions

Marshall

Gonzalez-Sulser

Abbott

2021

Disease Models &Amp; Mechanisms

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In most mouse models of disease, the outward manifestation of a disorder can be measured easily, can be assessed with a trivial test such as hind limb clasping, or can even be observed simply by comparing the gross morphological characteristics of mutant and wild-type littermates. But what if we are trying to model a disorder with a phenotype that appears only sporadically and briefly, like epileptic seizures? The purpose of this Review is to highlight the challenges of modelling epilepsy, in which the most obvious manifestation of the disorder, seizures, occurs only intermittently, possibly very rarely and often at times when the mice are not under direct observation. Over time, researchers have developed a number of ways in which to overcome these challenges, each with their own advantages and disadvantages. In this Review, we describe the genetics of epilepsy and the ways in which genetically altered mouse models have been used. We also discuss the use of induced models in which seizures are brought about by artificial stimulation to the brain of wild-type animals, and conclude with the ways these different approaches could be used to develop a wider range of anti-seizure medications that could benefit larger patient populations.

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Section: Problems Of Two Sorts With Genetic Mouse Modelsmentioning

confidence: 99%

Modelling epilepsy in the mouse: challenges and solutions

Marshall

Gonzalez-Sulser

Abbott

2021

Disease Models &Amp; Mechanisms

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“…To record and stimulate single hippocampal neurons in freely moving mice, we adapted our juxtacellular procedures-developed and optimized in rats (Tang et al, 2014)-to mice. Animals were implanted with miniaturized components, including a head post, micromanipulator base, recording chamber, and connector (Figures 1A and 1B; Figures S1A and S1B), whose size and total weight (1.4 g) were reduced to fit within the typical range of extracellular implants for mice (Jiang et al, 2017). Compared to the components previously used for rats (Tang et al, 2014;Diamantaki et al, 2016aDiamantaki et al, , 2016b, the fully assembled recording implant contained a more compact micromanipulator-base assembly and a smaller head stage (Figures 1A and 1B; Figures S1A and S1B).…”

Section: Juxtacellular Recording Procedures In Freely Moving Micementioning

confidence: 99%

Manipulating Hippocampal Place Cell Activity by Single-Cell Stimulation in Freely Moving Mice

et al. 2018

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Learning critically depends on the ability to rapidly form and store non-overlapping representations of the external world. In line with their postulated role in episodic memory, hippocampal place cells can undergo a rapid reorganization of their firing fields upon contextual manipulations. To explore the mechanisms underlying such global remapping, we juxtacellularly stimulated 42 hippocampal neurons in freely moving mice during spatial exploration. We found that evoking spike trains in silent neurons was sufficient for creating place fields, while in place cells, juxtacellular stimulation induced a rapid remapping of their place fields to the stimulus location. The occurrence of complex spikes was most predictive of place field plasticity. Our data thus indicate that plasticity-inducing stimuli are able to rapidly bias place cell activity, simultaneously suppressing existing place fields. We propose that such competitive place field dynamics could support the orthogonalization of the hippocampal map during global remapping.

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“…At the end of each session, a further 3x 2J stimuli were applied to either the dividing walls between the rats (sessions 1 & 2), or to the ceiling of the enclosure (sessions 3 & 4) as a control for potential auditory evoked responses. EEG data was acquired at a sampling rate of 19.525kHz (filtered 0.35 -9700Hz) using wireless TAINI transmitters (TainiTec Ltd, UK) 48 .…”

Section: Experimental Protocolmentioning

confidence: 99%

Trial by trial, machine learning approach identifies temporally discrete Aδ- and C-fibre mediated laser evoked potentials that predict pain behaviour in rats

Sales

Blockeel

Huxter³

et al. 2021

Preprint

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Laser evoked potentials (LEPs) – the EEG response to temporally-discrete thermal stimuli – are commonly used in experimental pain studies in humans. Such stimuli selectively activate nociceptors and produce EEG features which correlate with pain intensity. The rodent LEP has been proposed to be a translational biomarker of nociception and pain, however its validity has been questioned because of reported differences in the classes of nociceptive fibres mediating the response. Here we use a machine learning, trial by trial analysis approach on wavelet-denoised LEPs generated by stimulation of the plantar hindpaw of rats. The LEP amplitude was more strongly related to behavioural response than to laser stimulus energy. A simple decision tree classifier using LEP features was able to predict behavioural responses with 73% accuracy. An examination of the features used by the classifier showed that mutually exclusive short and long latency LEP peaks were clearly seen in single-trial data, yet were not evident in grand average data pooled from multiple trials. This bimodal distribution of LEP latencies was mirrored in the paw withdrawal latencies which were preceded and predicted by the LEP responses. The proportion of short latency events was increased after intradermal application of high dose capsaicin (to defunctionalise TRPV1 expressing nociceptors), suggesting they were mediated by Aδ-fibres (specifically AMH-I). These findings demonstrate that both C- and Aδ-fibres contribute to rodent LEPs and concomitant behavioural responses, providing a real-time assay of specific fibre function in conscious animals. Single-trial analysis approaches can improve the utility of LEPs as a translatable biomarker of pain.

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TaiNi: Maximizing research output whilst improving animals’ welfare in neurophysiology experiments

Cited by 19 publications

References 25 publications

Modelling epilepsy in the mouse: challenges and solutions

Modelling epilepsy in the mouse: challenges and solutions

Manipulating Hippocampal Place Cell Activity by Single-Cell Stimulation in Freely Moving Mice

Trial by trial, machine learning approach identifies temporally discrete Aδ- and C-fibre mediated laser evoked potentials that predict pain behaviour in rats

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