Novel analytical and datasharing tools for rich neuronal activity datasets obtained with a 4096 electrodes array

Lead Research Organisation: University of Edinburgh
Department Name: Sch of Informatics

Abstract

The functional intricacy of the central nervous system (CNS) arises from the complex anatomical and dynamic interactions between different types of neurones involved in specific networks. Hence, the encoding of information in neural circuits occurs as a result of interactions between individual neurones as well as through the interplay within both microcircuits (made of few neurones) and large scale networks involving thousands to millions of cells. One of the great challenges of neuroscience nowadays is to understand how these neural networks are formed and how they operate. Such challenge can be resolved only through simultaneous recording from thousands of neurones that become active during specific neuronal tasks. One of the experimental approaches to fulfil this goal is to use multielectrode arrays (MEAs) that consist of several channels (electrodes) that can each record (and/or stimulate) from few adjacent neurones within a particular area of the CNS. MEAs can be used in vitro to record from dissociated neuronal cultures or from brain slices or isolated retinas. These MEAs consist of assemblies of electrodes embedded in planar substrates. Typical commercial MEAs consist of 60-128 electrodes with a spacing of 100-200 um. Considering that a generic neurone in the mammalian CNS has a diameter of about 10 um, it is obvious that such MEAs cannot convey information on the activity of all neurones involved in a specific network, but rather just from a sample of these cells. To overcome this activity under-sampling, in this project, we will use the Active Pixel Sensor (APS) MEA, a novel type of MEA platform developed in a NEST-EU Project by our collaborator Luca Berdondini (Italian Institute of Technology, Genova). This MEA consists of 4,096 electrodes with near cellular resolution (21x21 um, 42 um centre-to-centre separation, covering an active area of 2.5 mm x 2.5 mm), where recording is possible from all channels at the same time. We will use the APS MEA to record spontaneous waves of activity that are present in the neonatal vertebrate retina. These waves occur during a short period of development during perinatal weeks and they are known to play an important role in guiding the precise wiring of neural connections in the visual system, both at the retinal and extra-retinal levels. The APS-MEA, thanks to its unmet size and resolution, will enable us to reach new insights into the precise dynamics of these waves as never achieved before. Recordings from such large scale networks at near cellular resolution generate extremely rich datasets with the drawback that these datasets are very large and difficult to handle, thus necessitating the development of new powerful analytical tools enabling to decode in a fast, efficient and user-friendly way how cellular elements interact in the network. The development of such computational tools is the central goal of this project, while the experimental work on the retina defines a challenging and unique scientific context. The tools we plan to develop will yield parameters that will help us reach better understanding of network function, from the temporal firing patterns of individual neurones to how activity precisely propagates within the network. We will also develop novel tools for easier visualisation of the dynamical behaviour of the activity within the network. These tools will be developed in a language that could be easily utilized by other investigators using the same recording system or other platforms of their choice. Finally, to ensure that these tools are accessible to the wide neurophysiology community, they will be deployed on CARMEN (Code Analysis, Repository and Modelling for e-Neuroscience), a new internet-based neurophysiology sharing resource designed for facilitating worldwide communication between collaborating neurophysiologists.

Technical Summary

publicly available if the proposal is funded. [up to 2000 characters] The complexity of neuronal communication arises from the exquisite precision of anatomical and functional connectivity within neuronal assemblies. To understand how neural connectivity is formed and operates, it is crucial to record simultaneously at high spatiotemporal precision from large scale neuronal networks. Multielectrode array (MEA) recordings have become one of the best experimental approaches for this purpose. Although MEAs offer excellent temporal resolution, their spatial resolution is poor, with typical commercial MEAs consisting of 60-128 electrodes with 30 um diameter and 200 um spacing, which is insufficient to study fine-grain spatiotemporal cellular interactions. In this project we will use the novel APS MEA platform developed by L. Berdondini and collaborators. The APS MEA is unique in terms of spatiotemporal resolution. It consists of 4,096 channels with near cellular resolution (21 um electrode diameter and separation) that can record simultaneously at a full frame rate of 7.8 kHz, which is high enough to reliably discriminate single spikes. We will use the APS MEA to record neonatal mouse retinal waves. Retinal waves undergo substantial changes in their spatiotemporal properties as the retina develops and the APS MEA will enable us to investigate these properties with a precision never been achieved before. The generation of such large and rich datasets necessitates the development of new powerful computational analytical tools, and this will be the central goal of this project. We will develop user-friendly new statistical approaches to decode large neuronal networks and new computational and visualization tools to quantify fine-grain spatiotemporal properties in neural networks. To allow community-wide access to these novel tools, they will be deployed on CARMEN, a new UK-based neurophysiology code development and data sharing facility developed in the past 3 years.

Planned Impact

Although our project will be the first one using the APS MEA to study an intact neural network (e.g. the retina) rather than interactions between dissociated neurones, we have no doubt that the APS MEA (or other similar developments) will soon become sought after by many neuroscientists seeking deeper understanding of precise interactions within large neuronal assemblies. From that point of view, this project will bring a strong proof of concept for the development and use of large scale MEAs. An entire session on MEAs at the last Society for Neuroscience meeting in Chicago (October 17-21 2009, ~30,000 participants) has revealed the fast growing interest of the neuroscience community in these large arrays that are becoming increasingly sophisticated thanks to new developments in nanotechnology and microfabrication. At the same time it is obvious that the APS MEA is the best performing platform available nowadays (in terms of the number of channels that can be used at any single time at high acquisition rate). The system was highly praised at the Chicago meeting, and we are in the very fortunate position of being at the forefront of research and development of the APS MEA through our collaboration with Luca Berdondini. We believe that we will be able to generate data of superior quality that will generate strong interest amongst neurophysiologists and computational neuroscientists. Because recordings with the APS MEA generate data that has no precedents in terms of spatiotemporal resolution, our results will undoubtedly shed new light on how to analyse, visualise and quantify neural network function, and this will be of great interest for the development of new software resources that will be used by systems neuroscientists. Because our experimental data and new analytical tools will be deployed on an open access data sharing facility, the impact of our research will be of much wider extent and will facilitate the dissemination of important scientific knowledge. All aspects of our research fall within the remit of research supported by the BBSRC, with special emphasis on the Tools and Resources Development Fund.

Publications

10 25 50
 
Description A large-scale, high density multielectrode array platform recording neural activity simultaneously with 4,096 electrodes was successfully installed at Newcastle, and the recordings were analysed at Edinburgh. We found the array to be an excellent system for recording spontaneous neuronal activity from the neonatal retina (retinal waves) at a near cellular resolution.

The grant enabled us, as planned, to develop a suite of tools for the analysis of these large scale MEA recordings. In particular, we devised a new improved detection method for neural spikes. This was necessary as we found that conventional methods were not suitable for these systems because of a very different noise profile caused by the densely integrated electronic circuits. Furthermore, we developed several methods for quantitative analysis of spatio-temporal activity patterns observed in the developing retina.

The analysis of retinal waves with these methods revealed several previously unknown features. Most strikingly, we found that late stage waves appear in spatially constrained hot-spots, which move over the course of hours (in vitro). Our analysis also enabled us to publish the to date most comprehensive characterisation of their ontogeny during the first two postnatal weeks in mice.

The complete data set generated during the project is available for download for further analysis.
Exploitation Route Our work has led to a successful bid for a 3 year EC FET grant (03/2013-02/2016) with partners in Italy and France to study retinal light responses with high density arrays. The methods developed in this project are now routinely used in the EC project. Moreover, a successful EPSRC bid will make use of data and methods developed here to advance the development of statistical models for large scale neural recordings (11/2014-10/2017). We are in the process of publishing analysis code for academic use, and also engaged with industry to develop these methods for relevant applications such as toxicology and drug testing and development.
Sectors Pharmaceuticals and Medical Biotechnology

 
Description Methodologies developed in this project include tools and and software for the analysis of recordings from large scale, high density multielectrode arrays recordings (HD-MEA). HD-MEA reports the activity of thousands of neurons simultaneously in a range of in vitro preparations, and is used routinely in pharmacology and toxicology applications. Our algorithms are freely available as open source software, and were also implemented as part of a free software package (Brainwave by 3Brain GmbH). They are now used by several research labs as well as in industry. Continuing collaboration with 3Brain as well as users ensures the software is further improved and developed. In 2017 the algorithms were adapted to support a wide range of CMOS based recording systems, such as the Neuropixel and Neuroseeker arrays for in vivo applications.
First Year Of Impact 2014
Sector Pharmaceuticals and Medical Biotechnology
Impact Types Economic

 
Description EPSRC Responsive Mode
Amount £337,440 (GBP)
Funding ID EP/L027208/1 
Organisation Engineering and Physical Sciences Research Council (EPSRC) 
Sector Public
Country United Kingdom
Start 11/2014 
End 10/2017
 
Description FET Proactive: Neuro-Bio-Inspired Systems (NBIS)
Amount € 337,815 (EUR)
Funding ID RENVISION 
Organisation European Commission 
Department Seventh Framework Programme (FP7)
Sector Public
Country European Union (EU)
Start 03/2013 
End 02/2016
 
Description Analysis of high density multielectrode array recordings 
Organisation 3Brain GmbH
Country Switzerland 
Sector Private 
PI Contribution Development of analysis tools for data from large scale, high-density 4,096 channel multielectrode array (HD-MEA) recordings. All methods are published as open source projects.
Collaborator Contribution IIT provided existing and new experimental data for projects in my group. This in kind contribution includes hardware and reagents required for experiments, as well as investigator time to support the project. 3Brain GmbH provided support with software development, software implementations of algorithms developed in my group, and sponsored a conference visit for a student.
Impact Multi-disciplinary nature: linking theory, experiment and bioengineering, outputs (as of 02/2016): - publication DOIs: 10.1113/jphysiol.2013.262840, 10.1016/B978-0-12-397266-8.00151-4, 10.3389/fninf.2015.00028, 10.1523/JNEUROSCI.4421-14.2015 - data sets published online: http://www.carmen.org.uk/?page_id=13 - analysis algorithms published on the CARMEN web platform for electrophysiological data: https://portal.carmen.org.uk/ - open source spike sorting toolkit available: https://github.com/martinosorb/herding-spikes - algorithms (spike detection) developed in this collaboration were implemented in the free Brainwave Software, which is used by several groups worldwide to analyse HD-MEA data, http://www.3brain.com/brainwave-software - spike sorting methods are currently adopted by other research groups using HD-MEA
Start Year 2009
 
Description Analysis of high density multielectrode array recordings 
Organisation Italian Institute of Technology (Istituto Italiano di Tecnologia IIT)
Department Neuroscience and Brain Technologies IIT
Country Italy 
Sector Academic/University 
PI Contribution Development of analysis tools for data from large scale, high-density 4,096 channel multielectrode array (HD-MEA) recordings. All methods are published as open source projects.
Collaborator Contribution IIT provided existing and new experimental data for projects in my group. This in kind contribution includes hardware and reagents required for experiments, as well as investigator time to support the project. 3Brain GmbH provided support with software development, software implementations of algorithms developed in my group, and sponsored a conference visit for a student.
Impact Multi-disciplinary nature: linking theory, experiment and bioengineering, outputs (as of 02/2016): - publication DOIs: 10.1113/jphysiol.2013.262840, 10.1016/B978-0-12-397266-8.00151-4, 10.3389/fninf.2015.00028, 10.1523/JNEUROSCI.4421-14.2015 - data sets published online: http://www.carmen.org.uk/?page_id=13 - analysis algorithms published on the CARMEN web platform for electrophysiological data: https://portal.carmen.org.uk/ - open source spike sorting toolkit available: https://github.com/martinosorb/herding-spikes - algorithms (spike detection) developed in this collaboration were implemented in the free Brainwave Software, which is used by several groups worldwide to analyse HD-MEA data, http://www.3brain.com/brainwave-software - spike sorting methods are currently adopted by other research groups using HD-MEA
Start Year 2009
 
Title Efficient tools for analysis of high density multielectrode array recordings 
Description A range of methods and tools were developed to analyse recordings with large-scale, high density multielectrode arrays (HD-MEA). These range from spike detection and sorting algorithms to new methods to quantitatively analyse and compare recordings, quantify drug effects and characterise network activity. Overall these methods allow for improved and more consistent characterisation of in vitro preps on MEAs, reducing the number of animals required for the study of pharmacological interventions on neural systems. 
Type Of Technology Software 
Year Produced 2016 
Open Source License? Yes  
Impact Algorithms are now used routinely in several collaborating labs (and are/will be made publicly available upon publication), and implemented in custom free software by a Swiss SME (3Brain GmbH) that develops high density MEAs. Spike detection and sorting software is now in use in several labs worldwide. 
URL http://homepages.inf.ed.ac.uk/mhennig/herdingspikes/
 
Description Edinburgh Explorathon 2014 and 2015 exhibit 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? Yes
Geographic Reach Regional
Primary Audience Public/other audiences
Results and Impact Intensive discussions during presentation, requests for further information (flyers were available).

not assessed
Year(s) Of Engagement Activity 2014,2015
URL http://www.explorathon.co.uk/edinburgh/meet-the-experts