For whom? Anyone concerned with the practical aspects of electrophysiology in the behaving laboratory animal.
What? A curated list of resources for how to get started with extracellular (in vivo/behaving) ephys experiments. Mostly in small animals/rodents. Also an easy-access reference list for more experienced users.
How? The aim is for necessary and sufficient. By reading these sources, you should in principle be able to set up in vivo ephys experiments based on open-access information (and gear as far as possible). The list is not comprehensive – it’s based on our own (probably biased) experimental experience, and we are always happy to add open access resources. If you have comments or recommendations, please contact us at: contact -AT- 3dneuro.com
Last revision May 18, 2021
Use This work is licensed under a Creative Commons Attribution 4.0 International License. In a nutshell, this means anyone is free to share and adapt it, as long as they give proper credit to the original source (this website).
Table of contents
Electrophysiology reference documentation
- If new to the field, start here: Approaches to study neural circuits course (2020) – 11 lectures, with 2 dedicated to electrophysiology (lectures 3-4) by Luke Sjulson, Albert Einstein College of Medicine
- Some study design guidelines: Recommendations for the Design and Analysis of In Vivo Electrophysiology Studies by the editorial board, J. Neurosci. (2018)
- A good primer: Tools for probing local circuits: high-density silicon probes combined with optogenetics, Buzsaki et al. 2015
- A good protocol with video: Implantation of Chronic Silicon Probes and Recording of Hippocampal Place Cells in an Enriched Treadmill Apparatus, Sariev et al. 2017 (No open source alternative, but too valuable to omit)
- A unified data format: Neurodata Without Borders (NWB), a formatting standard for cell-based neurophysiology data, Teeters et al. 2015
- A classic reference manual (to consult before hitting the search engines): The Axon guide – Electrophysiology and Biophysics Laboratory Techniques 3rd ed.
- Cool Neuropixels resources: Nick Steinmetz’s lab page, includes data, analysis software and training materials.
- Introduction: Past, Present and Future of Spike Sorting Techniques, Rey et al. 2015
- Alternatively, introductory lecture: An Introduction to Spike Sorting, Bhagtat and Moore-Kochlacs, MIT 2017
- Comparing algorithms: SpikeForest, reproducible web-facing ground-truth validation of automated neural spike sorters, Magland et al. 2020
- A popular method developed for Neuropixels data: Kilosort2, Pachitariu 2020
- Ground-truth validated method: A spike sorting toolbox for up to thousands of electrodes validated with ground truth recordings in vitro and in vivo, Yger et al. 2018
Behavior reference documentation
- Conceptual start: Neuroscience Needs Behavior: Correcting a Reductionist Bias, Krakauer et al. 2017
- General considerations: A hitchhiker’s guide to behavioral analysis in laboratory rodents, Sousa et al. 2006 and Probing perceptual decisions in rodents, Carandini & Churchland 2013
- Head-fixed tasks in virtual reality are growing in popularity as they enable tight control of the stimulus combined with easier recordings. See recent introductory review of head-fixed tasks (Bjerre & Palmer 2020). In that context, 2 approaches have emerged that are a very good start when you are considering behavioral task design (Full disclosure: Two from the 3Dneuro team worked with co-authors of 1 as post-docs, and one led the studies in 2).
- Standardized tasks that optimize for reproducibility across different labs, The International Brain Laboratory et al. 2020
- Tasks that push the limits of what animals can achieve, but are less easily reproducible: e.g. The Virtual-Environment-Foraging Task (1) and (2), Havenith et al. 2018, 2019. Give special attention to the supplementary note: Seven principles of task design for mice.
- Freely moving tasks: These tasks typically enable more naturalistic behaviors, from the classic Morris water maze to more recent route planning studies (e.g. Jackson et al. 2020). See also automated experiments below.
- Food/water restriction: See the Janelia protocol for water restriction, which also includes procedures for weight and health monitoring, data on task performance as a function of weight, and on long-term effects (Guo et al. 2014). Note that the choice of either food or water restriction has an effect on learning (Goltstein et al. 2018)
- Automated experiments: Combined with ephys, e.g. Automated long-term recording and analysis of neural activity in behaving animals, Dhawale et al. 2017. Or just behavioral assessment, e.g. An automated home-cage-based 5-choice serial reaction time task for rapid assessment of attention and impulsivity in rats, Bruinsma et al. 2019
- General-purpose animal 3D pose estimation: DeepLabCut. In addition to pose estimation for multiple species, can be applied to whiskers and eye tracking. SimBA, A toolkit for analyzing complex social behavior in rodents (also supports DeepLabCut).
Welfare and handling
Happy animals are good lab animals.
These resources go beyond typical ‘license to work with animals’ training, and are great for making lab animals less stressed, which improves the odds of pretty much anything you wish to achieve with them.
Select open hardware projects & papers
Some projects include software as well.
- General lab equipment, with focus on affordability and education: Open Labware: 3-D Printing Your Own Lab Equipment, Baden et al. 2015. See also project website for more context and design files.
- A robot for automated craniotomies: Autosurgery – Website for latest documentation, see also paper by Pak et al. 2015
- Implant surgery without stereotaxic device & modular implant designs: RatHat: A Self-Targeting Printable Brain Implant System, Allen et al. 2020
- Implant design for optoelectronic probes: Micro-drive and headgear for chronic implant and recovery of optoelectronic probes, Chung et al. 2017
- Chronic drive implant for tetrode arrays: The Open Ephys ShuttleDrive, see webpage and paper by Voigts et al. 2019
- Complete mouse virtual reality rig design: Harvey Lab mouse VR (2020), lab webpage here
- Microscopes: OpenFlexure, UC2
Open hardware/software repositories
Build your own lab.
- Possibly the largest in size and scope: Open Behavior. Their resources page also lists many tools/companies for building stuff. See also Open Neuroscience
- Recording hardware/software: Open Ephys wiki. Open Ephys is becoming the standard for both high-channel count electrophysiology and open hardware projects.
- With a focus on affordability: Lab on the Cheap (not neuroscience specific)
How to open hardware
Spread the love.
There’s a whole ecosystem for electrophysiology in behaving animals. This section is work in progress and we appreciate your feedback.
Probes, accessories and electronics
- Probes: Neuronexus, Cambridge NeuroTech, Atlas Neuro, Neural Dynamics Technologies, Thomas Recording, MicroProbes
- Probes (nonprofit): Neuropixels
- Recording electronics and accessories (open source): Open Ephys
- Recording electronics and accessories: Neuralynx, TDT, Blackrock, Plexon, White Matter
- Recording electronics and accessories (open and closed source): SpikeGadgets, NeuroTek (including a tetrode drive loading service)
- Assembly service for open hardware: Labmaker, Sanworks, NeuroGig (also equipment re-use and more), see also #NeuroRigBuilder
- Open hardware: Prometheus Science
- Software: Metacell
- Many great resources: Allen institute Products & tools
- Don’t make everything yourself: The case for consulting in neuroscience (Voigts, 2019)
- Don’t draw everything yourself: SciDraw, a free repository of quality scientific drawings.
- Smart bibliography tool: Connectedpapers builds a visual graph of connected work around a paper, based on similarity.
- Beyond scope, yet awesome: INSS builds custom multiphoton microscopes, hardware & software, at a fraction of the cost for commercial systems.
- Open solution for systems neuroscience research (blog): Labrigger
- For educators on a budget: Reducing the Cost of Electrophysiology in the Teaching Laboratory, Wyttenbach et al. 2018