Dataset Information

Scalable and modular wireless-network infrastructure for large-scale behavioural neuroscience.

ABSTRACT: The use of rodents to acquire understanding of the function of neural circuits and of the physiological, genetic and developmental underpinnings of behaviour has been constrained by limitations in the scalability, automation and high-throughput operation of implanted wireless neural devices. Here we report scalable and modular hardware and software infrastructure for setting up and operating remotely programmable miniaturized wireless networks leveraging Bluetooth Low Energy for the study of the long-term behaviour of large groups of rodents. The integrated system allows for automated, scheduled and real-time experimentation via the simultaneous and independent use of multiple neural devices and equipment within and across laboratories. By measuring the locomotion, feeding, arousal and social behaviours of groups of mice or rats, we show that the system allows for bidirectional data transfer from readily available hardware, and that it can be used with programmable pharmacological or optogenetic stimulation. Scalable and modular wireless-network infrastructure should facilitate the remote operation of fully automated large-scale and long-term closed-loop experiments for the study of neural circuits and animal behaviour.

SUBMITTER: Qazi R

PROVIDER: S-EPMC10180496 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature

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Scalable and modular wireless-network infrastructure for large-scale behavioural neuroscience.

Qazi Raza R Parker Kyle E KE Kim Choong Yeon CY Rill Ruediger R Norris Makenzie R MR Chung Jaeyoon J Bilbily John J Kim Jenny R JR Walicki Marie C MC Gereau Graydon B GB Lim Hyoyoung H Xiong Yanyu Y Lee Jenna R JR Tapia Melissa A MA Kravitz Alexxai V AV Will Matthew J MJ Ha Sangtae S McCall Jordan G JG Jeong Jae-Woong JW

Nature biomedical engineering 20211125 6

The use of rodents to acquire understanding of the function of neural circuits and of the physiological, genetic and developmental underpinnings of behaviour has been constrained by limitations in the scalability, automation and high-throughput operation of implanted wireless neural devices. Here we report scalable and modular hardware and software infrastructure for setting up and operating remotely programmable miniaturized wireless networks leveraging Bluetooth Low Energy for the study of the ...[more]

PMID: 34824397

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Project description:Many contemporary neuroscience experiments utilize high-throughput approaches to simultaneously collect behavioural data from many animals. The resulting data are often complex in structure and are subjected to systematic biases, which require new approaches for analysis and normalization. This study addressed the normalization need by establishing an approach based on linear-regression modeling. The model was established using a dataset of visual motor response (VMR) obtained from several strains of wild-type (WT) zebrafish collected at multiple stages of development. The VMR is a locomotor response triggered by drastic light change, and is commonly measured repeatedly from multiple larvae arrayed in 96-well plates. This assay is subjected to several systematic variations. For example, the light emitted by the machine varies slightly from well to well. In addition to the light-intensity variation, biological replication also created batch-batch variation. These systematic variations may result in differences in the VMR and must be normalized. Our normalization approach explicitly modeled the effect of these systematic variations on VMR. It also normalized the activity profiles of different conditions to a common baseline. Our approach is versatile, as it can incorporate different normalization needs as separate factors. The versatility was demonstrated by an integrated normalization of three factors: light-intensity variation, batch-batch variation and baseline. After normalization, new biological insights were revealed from the data. For example, we found larvae of TL strain at 6 days post-fertilization (dpf) responded to light onset much stronger than the 9-dpf larvae, whereas previous analysis without normalization shows that their responses were relatively comparable. By removing systematic variations, our model-based normalization can facilitate downstream statistical comparisons and aid detecting true biological differences in high-throughput studies of neurobehaviour.

Dataset Information

Scalable and modular wireless-network infrastructure for large-scale behavioural neuroscience.

Publications

Scalable and modular wireless-network infrastructure for large-scale behavioural neuroscience.

Similar Datasets

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