neuroelectro.org a window to the world’s neurophysiology data shreejoy tripathy university of...

NeuroElectro.orgA window to the world’s neurophysiology data

Shreejoy TripathyUniversity of British Columbia, Canada

Email: stripathy@chibi.ubc.caTwitter: @neuronJoy

Main Idea• Given that there is an extensive neuron

electrophysiology literature, what can we learn by compiling it?

PubMed search: neuron AND (electrophysiology OR biophysical OR neurophysiology)

>45K articles

Electrophysiology literature is notoriously heterogeneous

Electrophysiology literature is notoriously heterogeneous

Input resistancemeasurement differences

NeuroElectro overall methodology

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Semi-automated text-mining overview

• Identify within data tables:– Neuron types (from

NeuroLex.org)– Biophysical properties (in

normotypic conditions)– Biophysical data values

• Experimental conditions defined within methods sections

• Text-mined data is then checked by experts

Tripathy et al, 2014

“Experiments were conducted in acutely prepared brain slices of 24- to 28-day-old (65–120 g) male Wistar rats.”

NeuroElectro.org web interface

Code at github.com/neuroelectroData at neuroelectro.org/api

Database statistics

• Currently 100 neuron types, >300 articles

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Resting membrane potential

mV

Extensive variability among NeuroElectro data

Netzebrand et al, 1999

Tripathy et al, in revision

Input resistance

MΩ

Accounting for differences in experimental conditions

• Explain variability in electrophysiological data through influence of experimental conditions:– species/strain – electrode type– animal age,– recording temperature– in vitro/in vivo/cell culture– junction potential

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Electrode type

Tripathy et al, in revision

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Tripathy et al, in revision

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Whole-genome correlation of gene expression and electro-diversity

20,000 genes

Patterns of gene expression

Electrophysiologicalphenotypes

Tripathy et al, in revision/in progress

Systematic variation among

neuron types

Making hypotheses on electrophysiology - gene expression relationships

• Explaining electrophysiological phenotypes in terms of underlying gene expression (and vice versa)

Future directions

• Continuing to expand NeuroElectro– More neuron types– More domains• Synaptic plasticity

• Continuing to demonstrate the value of data integration– How can we move to a situation where

experimentalists are willingly sharing their data?

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Acknowledgements• Pavlidis Lab @ UBC• Urban Lab @ CMU• Gerkin Lab @ ASU

Shreejoy TripathyEmail: stripathy@chibi.ubc.ca

Twitter: @neuronJoyURL: neuroelectro.org

Code: github.com/neuroelectro

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Mapping neuron electrophysiology to gene expression

Neuron typeresolution

Cell layerresolution

Neuron type to cell layer mapping is approximate. Will be improved in future iterations with high resolution data.

Neocortex L5/6pyramidal cell

Neocortex layer 5/6

Neocortex basket cell

Neocortex

20,000 genes

Finding genes most correlated with electrophysiological diversity

Assessing predictive power between gene expression and electrophysiology