CARMEN for the storage and analysis of rich datasets obtained from 60 and 4,096 channels MEA

recordings of retinal activity

Evelyne Sernagor

Spontaneous activity in the immature retina

• Present during a short developmental window

• Consists of recurring bursts in RGCs, correlated between neighbouring cells, resulting in propagating waves

• Episodes occur every few minutes• Patterns change with development• Important for wiring the visual

system

Retinal waves are believed to drive the wiring of retinal projections

Important wave features

Asynchrony between both eyes

Wave spatial extent

Synchronisation between neighbouring ganglion cells

Visualising and characterising retinal waves necessitates techniques to

record neural activity from large cell assemblies in the RGC layer

Multielectrode arrays (MEAs)

.

Sekirnjak C et al. J Neurophysiol 2006;95:3311-3327

©2006 by American Physiological Society

We have made extensive use of 60 channels MEAs (Multichannel Systems)

Electrode diameter 30 mmElectrode centre-to-centre separation 100-200 mm

Data processing from MCS MEA recordings1. Spike threshold detection on all electrodes

2. Ascii files of spike time stamps

3. Burst and wave detection algorithms developed in R by Stephen Eglen and Jennifer Simonotto

Services on the CARMEN portalFourplot Service (Stephen Eglen)Reads data in from all MEA retinal data formats currently on CARMENMEA Movie Calculator ServiceCreates an animated .gif file showing bursting over time on a MEA grid.Burst Analysis Service (Jennifer Simonotto)Takes text file spike times from multi-electrode array data, and computes network and burst characteristics, outputting a pdf with figures showing burst and networkMEA Burst and IBI Cumulative Distribution Calculator ServiceThis service calculates the cumulative distribution functions for burst lengths and inter-burst intervals of spike time series, returning pdfs of the burst length distribution versus burst length, the inter-burst interval distribution versus the interval length, and also returns comma separated variable files for x-y coordinates of the above plots.

Newcastle

Cambridge

U. WashingtonSeattle

UC Berkeley

UC Santa Cruz

UC Davis

Exchange data and share analytical codes

Perform cross-labs analysis of retinal waves data using CARMEN analytical tools

We have established an international network involving labs investigating retinal waves using MEAs

Edinburgh

Burst, Network and Propagation Analysis of Retinal Waves - Cross lab comparison

Jennifer Simonotto

Propagation analysis

MEA Spike time data

Network analysisBurst analysis

Mammalian retinal waves: 3 distinct developmental stages

Stage I - Before synapse formation (Gap junctions, adenosine)

Bipolar cells

gluglu

GABAgly ACh ACh

Retinal Ganglion Cell

Stage III (P9-P15)Glutamatergic waves

Inhibitory amacrine cells

StarburstAmacrine cells

X

Cholinergic StarburstAmacrine cells

ACh ACh

Retinal Ganglion Cell

Stage II (late gestation to P9)Cholinergic waves

ACh ACh

Retinal Ganglion Cell

GABAgly

Inhibitory amacrine cells

StarburstAmacrine cells

Stage II + GABA (P4-P9)

Despite fundamental developmental changes in network organization, no consistent changes

in wave dynamics have been reported

Possible reasons:

Retinal area viewed is too small

Spatio-temporal resolution of the recordings is not high enough

data management as images

time

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time

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Vxy(ti) encoded in the pixel color

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Active Pixel Sensor (APS)

in-pixel▪microelectrode▪ pre-amplifier

on-chip▪ random addressing logic▪ amplifier

implementation of dense MEAs adapted data management and analysis

The Active Pixel Sensor (APS) MEA(collaboration with Luca Berdondini,

Alessandro Maccione and Mauro Gandolfo, IIT)Camera chip

Pixels are metallic electrodes instead of light sensors

4,096 electrodes (64x64 array)

Spatial resolution of 21 mm (el. diameter, 42 mm centre-to-centre) - spatial resolution comparable to neuronal somata in intact networks

Can acquire at full frame rate of 7.8kHz

L. Berdondini, et al., Lab On Chip, 2009.K. Imfeld, et al., IEEE Transactions on Biomedical Engineering , Vol. 55, Issue 8, 2008.L. Berdondini, et al., IEEE-ICECS, 2001

Data acquisition and processing similar to light imager

Each metallic electrode represents one pixel

Activity acquired with a frame grabber

Fast signal acquisition performed as a sequence of frames by encoding extracellular voltage signals as pixels data.

Single microelectrode raw data is reconstructed by combining single pixel data from sequential frames. Activity movies “functional electrophysiological imaging”

www.3brain.com

Newcastle

Edinburgh Cambridge

IITGenova

U. WashingtonSeattle

UC Berkeley

UC Santa Cruz

UC Davis

Activity moviesRaw signals

2.67

mm

1.6 mV

P5 retina

Visualization based either on signal variance (e.g. within 5ms window) or on electrical potential

Screenshot from BrainWave

Spike detection

The BrainWave developers (Mauro Gandolfo and Alessandro Maccione) are soon going to add a data

export tool directly to CARMEN

Spike time stamps files exported to Matlab

Spikes extraction and visualization of spike trains

P10 retina

Movie of firing ratesR (Stephen Eglen)

Movie of detected wavesBased on burst analysisMatlab (Matthias Hennig)

Raster plot

Spatiotemporal resolution is important!!!!!

Down-sampling to 8x8 electrodes42 mm diameter (2x2 APS channels)240 mm pitch (6 APS channels)

APS64x64 electrodes21 mm diameter40 mm pitch

P3 retina

Data processing from APS MEA recordings

1. Spike threshold detection on all electrodes

2. Export to MATLAB files of spike time stamps (also possible to export .MAT files of raw data)

3. Burst and wave detection algorithms developed in MATLAB by Matthias Hennig

4. Additional algorithms to compute wave trajectories and cluster analysis (Mauro Gandolfo, Matlab) and wave spatial extent (Stephen Eglen, R).

Services on the CARMEN portal (Matt Down)Bursts DetectionFinds bursts of activity from spike times, for each channel in an MEA.

Analyse Waves APS2This service takes the output from burst detection 2 and classifies the bursts into waves

Developmental changes in wave spatiotemporal patterns

Stage IISlowRandom initiation pointsRandom patternsMore widespread

Stage IIIFasterMore spatially restrictedRepetitive patterns

Developmental changes in wave spatiotemporal patterns

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Thanks to…NewcastleMatt DownJames van CoppenhagenJennifer SimonottoRolando Berlinguer-PalminiPatrick DegenaarChristopher Adams

CambridgeStephen Eglen

EdinburghMatthias Hennig

Funders BBSRC, EPSRC, IIT

CARMENColin IngramTom JacksonMike WeeksMark Jessop

GenovaLuca Berdondini (IIT)Alessandro Maccione (IIT)Mauro Gandolfo (Univ. of Genova)Kilian Imfeld (3Brain, Switzerland)

USA collaborators who made data availableRachel WongMarla FellerLeo ChalupaDavid Feldheim and Alan Litke